English for computer science student

English for computer science student
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English++

English++ English for Computer Science Students

Complementary Course Book open book

Jagiellonian Language Center Jagiellonian University Cracow 2008 1

English++ Książka฀ English++฀English฀for฀Computer฀Science฀Students฀powstała฀w฀ramach฀niekomercyjnego฀projektu฀o฀nazwie฀English++,฀który฀został฀zrealizowany฀przez฀Monikę฀ Stawicką฀wraz฀grupą฀studentów฀III฀roku฀informatyki฀uczących฀się฀języka฀angielskie-฀ go฀ w฀ Jagiellońskim฀ Centrum฀ Językowym฀ Uniwersytetu฀ Jagiellońskiego฀ w฀ Krakowie฀฀ w฀ roku฀ akademickim฀ 2007/2008.฀ Autorka฀ i฀ realizatorzy฀ projektu฀ dziękują฀ Dyrekcji฀฀ Centrum฀za฀umożliwienie฀jego฀realizacji,฀a฀użytkowników฀skryptu฀w฀wersji฀papierowej฀ lub฀ elektronicznej฀ zachęcają฀ do฀ korzystania฀ z฀ materiałów฀ tam฀ zawartych฀ w฀ sposób฀ twórczy฀rozszerzając฀je,฀adoptując฀do฀własnych฀potrzeb,฀korygując฀lub฀tworząc฀nowe.

Autorka฀projektu฀English++฀฀฀฀฀฀฀฀฀฀฀฀฀Monika฀Stawicka

Realizatorzy฀projektu฀English++฀

Monika฀Stawicka

฀

Aleksandra฀Bieńkowska

฀

Paweł฀Fidelus

฀

Bartłomiej฀Filipek

฀

Krystian฀Kichewko

฀

Szymon฀Kaczorowski

฀

Michał฀Kubak

฀

Ewa฀Matczyńska฀

฀

Tomasz฀Paczkowski

฀

Michał฀Pal

฀

Krzysztof฀Roksela

฀

Aleksandra฀Sendecka฀

฀฀

Artur฀Staszczyk

฀

Krzysztof฀Szromba

฀

Piotr฀Śmigielski฀

English++

Contents Acknowledgements ………………………………………………………. 4 Introduction by Władysław T. Miodunka …………………………….. 7 Introduction by Monika Stawicka ……………………………………… 9 1. Reading Chapter……………………………………………………… 13 •฀฀฀฀฀Roderick฀Hames฀“History฀of฀Computers”฀(1998) •฀ Wikipedia฀“IloveYou฀Worm” •฀ Tim฀Jones฀“Anatomy฀of฀the฀Linux฀Kernel”฀(2007) •฀ Damien฀Stolarz฀“How฀to฀Stream฀Video฀Over฀a฀Network฀or฀the฀Internet”฀(2004) •฀ Wikipedia฀“Computer฀Simulation” •฀ Wikipedia฀”Computer฀Facial฀Animation” •฀ Stanisław฀Migórski฀“An฀Introduction฀to฀the฀Modelling฀of฀Real-World฀Problems฀ ฀

by฀the฀Simplest฀Ordinary฀Differential฀Equations”(2007)

•฀ Martin฀Fowler฀“Writing฀Software฀Patterns” •฀ Randy฀Nash฀“Cyber฀Warfare:฀Reality฀or฀Box฀Office฀Hit?”฀(2007) •฀ Martin฀Fowler฀and฀Pramod฀Sadalage฀“Evolutionary฀Database฀Design”฀(2003) •฀ Joel฀Spolsky฀“Lord฀Palmerston฀on฀Programming”฀(2002) •฀ Wikipedia฀“Quake฀–฀Game฀Engine”฀฀฀฀ •฀ Piotr฀Kalita,฀Robert฀Schaefer฀฀“Mechanical฀Models฀of฀Artery฀Walls”฀(2007) •฀ Robert฀Ahlfinger,฀Brenton฀Cheeseman,฀Patrick฀Doody฀“The฀Pitch฀Correction฀ ฀

Algorithm:฀an฀Overview”฀(2006)฀Wikipedia

•฀ Wikipedia฀“Software฀Development฀Process”

2. Listening Chapter …………………………………………………… 141 •฀ John฀McCarthy,฀“What฀is฀Artificial฀Intelligence?฀Basic฀Questions”฀฀(2007) •฀ Agile฀Software฀Development฀from฀IT฀Conversation •฀ Open฀News฀Episode฀25฀from฀Open฀News฀ •฀ Open฀News฀Episode฀29฀from฀Open฀News฀ •฀ Open฀News฀Episode฀31฀from฀Open฀News฀

3. Presentation Chapter ……………………………………………….177 •฀ How฀to฀Give฀a฀Succesful฀Presentation?฀Practical฀Information •฀ Repertoire฀of฀Presentation฀Phrases •฀ Slide฀show.฀“Successful฀Presentations.฀A฀Few฀Tips฀From฀English++”฀฀฀฀฀฀฀฀฀฀

4. Appendixes …………………………………………………………. 191 •฀ Appendix฀A:฀Mathematical฀Terminology •฀ Appendix฀B:฀Mathematical฀Formulas •฀ Appendix฀C:฀Greek฀Alphabet

5. Glossary …………………………………………………………….. 201

English++

English++ Acknowledgements Many฀people฀have฀assisted฀in฀the฀preparation฀of฀this฀first฀version฀of฀the฀book.฀But,฀ of฀ course,฀ as฀ the฀ leader฀ of฀ the฀ English++฀ project฀ I฀ alone฀ feel฀ responsible฀ for฀ any฀ shortcomings.฀I฀would฀like฀to฀give฀special฀thanks฀to฀a฀group฀of฀enthusiastic฀3rd฀year฀ computer฀ science฀ students฀ of฀ the฀ Jagiellonian฀ University฀ without฀ whom฀ this฀ book฀ would฀have฀never฀been฀prepared.฀They฀have฀worked฀as฀experts฀in฀the฀IT฀field,฀text฀ selectors,฀authors฀of฀complementary฀exercises,฀and฀finally฀shaped฀the฀book.฀Above฀all฀ I฀am฀grateful฀for฀the฀support฀and฀coordination฀of฀the฀project฀provided฀by฀Artur฀Staszczyk฀and฀Paweł฀Fidelus฀and฀for฀creativeness฀and฀engagement฀of฀all฀the฀English++฀members:฀Aleksandra฀Sendecka,฀Aleksandra฀Bieńkowska,฀Ewa฀Matczyńska,฀Artur฀Staszczyk฀ ,฀ Paweł฀ Fidelus,Tomasz฀ Paczkowski,฀ Piotr฀ Śmigielski,฀ Bartłomiej฀ Filipek,฀ Krzysztof฀ Szromba,฀Michał฀Kubak,฀Michał฀Pal,฀Krzysztof฀Roksela,฀Krystian฀Kichewko฀and฀Szymon฀฀ Kaczorowski.฀They฀all฀have฀contributed฀to฀the฀accomplishment฀of฀the฀book฀not฀only฀ by฀practicing฀their฀English฀language฀skills฀but฀also฀by฀actively฀using฀their฀knowledge฀ as฀experts฀in฀the฀field.฀Their฀work฀goes฀much฀beyond฀standard฀requirements฀of฀an฀ English฀university฀course.฀ Special฀ thanks฀ also฀ go฀ to:฀ Dr฀ Anna฀ Ochal฀ from฀ the฀ Institute฀ of฀ Computer฀฀ Science,฀ who฀ revised฀ the฀ mathematical฀ part฀ of฀ the฀ manuscript฀ and฀ to฀ Dr฀ Jerzy฀฀ Freundlich,฀ a฀ colleague฀ of฀ mine,฀ who฀ painstakingly฀ revised฀ reading฀ and฀ listening฀ texts฀ and฀ the฀ exercises;฀ Małgorzata฀ Świątek,฀ Director฀ of฀ the฀ Jagiellonian฀ Language฀ Center฀ and฀ Professor฀ Marek฀ Skomorowski,฀ Director฀ of฀ the฀ Institute฀ of฀ Computer฀฀ Science฀for฀the฀support฀of฀my฀initiative;฀Professor฀Władysław฀Miodunka฀for฀helping฀ me฀to฀maintain฀belief฀in฀the฀value฀of฀the฀Project,฀Dr฀Rafał฀Maciąg฀and฀Jerzy฀Zając฀for฀ their฀help฀in฀the฀recording฀studio,฀Dr฀Monika฀Coghen฀for฀her฀supportive฀comments฀ and฀Maciek฀Kwiatkowski฀for฀giving฀the฀book฀its฀final฀shape.฀Particular฀thanks฀go฀to฀ Jolanta฀ Krzyształowska,฀ Financial฀ Director฀ of฀ the฀ Jagiellonian฀ Language฀ Center฀ and฀ the฀administrative฀staff฀of฀the฀Center. The฀project฀members฀are฀grateful฀to฀Professor฀Stanisław฀Migórski,฀Dr฀Igor฀Podolak฀and฀ Dr฀Piotr฀Kalita฀from฀the฀Institute฀of฀Computer฀Science฀of฀the฀Jagiellonian฀University฀฀ for฀ giving฀ us฀ permission฀ to฀ reproduce฀ extracts฀ of฀ their฀ work฀ in฀ our฀ book:฀ “An฀฀ Introduction฀ to฀ the฀ Modelling฀ of฀ Real–World฀ Problem฀ by฀ the฀ Simplest฀ Ordinary฀฀ Differential฀ Equations”฀ by฀ Stanisław฀ Migórski฀ and฀ “Mechanical฀ Model฀ of฀ Artery฀ Walls”฀ by฀ Piotr฀ Kalita฀ and฀ Robert฀ Schaefer.฀ We฀ are฀ also฀ grateful฀ to฀ the฀ following฀฀ authors฀ for฀ permission฀ to฀ reproduce฀ extracts฀ of฀ their฀ work฀ in฀ English++฀ book:฀

Joel฀ Spolsky฀ for฀ “Lord฀ Palmerston฀ on฀ Programming”,฀ http://www.joelonsoftware.

English++ com/articles/LordPalmerston.html;฀ Randy฀ Nash฀ for฀ “Cyber฀ Warfare:฀ Reality฀ or฀ Box฀ Office฀ Hit?”,฀ http://www.informit.com/articles/article.aspx?p=1016106;฀ Roderick฀ Hames฀ for฀ “History฀ of฀ Computers”),฀ http://www.crews.org/curriculum฀ /ex/compsci/articles/history.htm;฀ Damien฀ Stolarz฀ for฀ “How฀ to฀ Stream฀ Video฀ Over฀฀ a฀Network฀or฀the฀Internet”,฀http://www.informit.com/articles/article.aspx?p=331397฀ &seqNum=1;฀ John฀ McCarthy฀ for฀ „What฀ Is฀ Artificial฀ Intelligence?฀ -฀ Basic฀ Questions”,฀ http://www-formal.stanford.edu/jmc/whatisai/node1.html;฀Martin฀Fowler฀and฀Pramod฀฀ Sadalage฀ for฀ “Evolutionary฀ Database฀ Design”,฀ http://www.martinfowler.com/articles/ evodb.html;฀Martin฀Fowler฀for฀“Writing฀Software฀Patterns”,฀http://www.martinfowler. com/articles/writingPatterns.html;฀Tim฀Jones฀for฀“Anatomy฀of฀the฀Linux฀Kernel”,฀http:// www.ibm.com/developerworks/linux/library/l-linux-kernel;฀ Robert฀ Ahlfinger,฀ Brenton฀ Cheeseman,฀Patrick฀Doody฀for฀„The฀Pitch฀Correction฀Algorithm:฀an฀Overview”฀,฀http://cnx.org฀ /content/m12539/latest/.฀ A฀ special฀ word฀ of฀ thanks฀ go฀ to฀ those฀ authors฀ who฀฀ additionally฀supported฀us฀with฀their฀enthusiastic฀mails.฀ The฀ following฀ texts฀ come฀ from฀ open฀ sources:฀ “Computer฀ Facial฀ Animation”,฀ http://en.wikipedia.org/wiki/Facial_animation;฀“IloveYou฀Worm”,฀http://en.wikipedia. org/wiki/ILOVEYOU;฀„Software฀Development฀Process”,฀http://en.wikipedia.org/wiki/Software_development_process;฀„Quake฀-฀Game฀Engine”฀ h t t p : / / e n . w i k i p e d i a . o rg / w /฀ index.php?title=Quake&diff=172131494&oldid=172045276#Quake_engine;฀ Open฀ News฀ episodes฀ 25,฀ 29฀ and฀ 31฀ are฀ under฀ the฀ licence฀ of฀ Creative฀฀ Commons฀ -฀ http://opennewsshow.org/;฀ Agile฀ Software฀ Development฀ -฀ http://itc.฀ conversationsnetwork.org/shows/detail175.html.฀The฀pictures฀come฀from:฀History฀of฀Computers:฀ http://www.flickr.com/photos/dmealiffe/171720479/sizes/o/;฀ http://www.flickr. com/photos/indigoprime/2240131208/sizes/o/;฀http://www.flickr.com/photos/broughturner/2331185712/sizes/o/.฀I฀Love฀you฀Worm:฀Photo฀owned฀by฀LuiDuar฀(cc)฀http://www.flickr.com/ photos/[email protected]/2482225688/;฀

http://www.flickr.com/photos/vidiot/35382084/

sizes/l/;฀ http://www.flickr.com/photos/joffley/135052908/sizes/l/.฀ How฀ to฀ Stream฀ Video฀ Over฀a฀Network฀or฀the฀Internet:฀http://www.flickr.com/photos/inju/2493101180/sizes/l/;฀ http:/www.flickr.com/photos/msjacoby/208642529/sizes/l/;฀http://www.flickr.com/photos฀ /pbo31/2162247328/sizes/o/.฀ Computer฀ Simulation:฀ http://www.flickr.com/photos/ensight/2125461254/;฀ http://www.flickr.com/photos/oubliette/17538292/sizes/o/;฀ http:// www.flickr.com/photos/jurvetson/447302275/sizes/l/.฀Computer฀Facial฀Animation:฀http:// www.flickr.com/photos/ko_an/53060221/sizes/o/;฀ http://www.flickr.com/photos/giopuo฀ /483784528/sizes/o/;฀

http://www.flickr.com/photos/guccibear2005/173969294/sizes/l/;฀฀

http://www.flickr.com/photos/coreburn/166237292/.฀Cyber฀Warfare:฀Reality฀or฀Box฀Office฀ Hit?฀http://www.flickr.com/photos/devachan77/338153377/sizes/l/;฀http://www.flickr.com/ photos/krazykory/2437404581/sizes/l/;฀ http://www.flickr.com/photos/juan23/82888194/ sizes/l/.฀Lord฀Palmerston฀on฀Programming:฀http://www.flickr.com/photos/vancouversun฀ /446503999/sizes/l/;฀ http://www.flickr.com/photos/icco/2246383366/sizes/l/;฀ http://www.

English++ flickr.com/photos/jonnowitts/2399505874/sizes/l/.฀Quake฀-฀Game฀Engine:฀฀http://www.flickr.฀ com/photos/nothingpersonal/251603538/sizes/o/;฀ http://www.flickr.com/photos/psycho฀ _al/66541940/sizes/o/;฀ http://www.flickr.com/photos/prh/412670043/sizes/l/.฀ Mechanical฀฀ Models฀ of฀ Artery฀ Walls:฀ http://www.flickr.com/photos/patrlynch/450142019/sizes/o/;฀฀ http://www.flickr.com/photos/patrlynch/450129220/sizes/o/;฀ http://www.flickr.com/ photos/andycarvin/2220691059/sizes/o/.฀The฀Pitch฀Correctiom฀Algorythm.฀An฀Overwiev:฀฀ Photo฀ owned฀ by฀ woodleywonderworks฀ (cc),฀ http://www.flickr.com/photos/73645804฀ @N00/2267564159/;฀ http://www.flickr.com/photos/zen/40081589/sizes/o/;฀ http://www.฀ flickr.com/photos/timcaynes/102981762/sizes/l/.฀ Software฀ Development฀ Process฀ ฀ http:// www.flickr.com/photos/kubernan/401923870/sizes/l/;฀http://www.flickr.com/photos/reinholdbehringer/1072000705/sizes/l/;฀http://www.flickr.com/photos/bootload/146803248/sizes/o/.฀ What฀is฀Artificial฀Intelligence:฀http://www.flickr.com/photos/sashko/362105716/sizes/o/;฀ http://www.flickr.com/photos/gla/1790915676/sizes/o/;฀http://www.flickr.com/photos/easys฀ leazycheesy/1423829545/sizes/l/. ฀Monika฀Stawicka July฀2008

English++

Introduction

English++฀ is฀ an฀ interesting฀ project฀ realized฀ in฀ the฀ Jagiellonian฀ Language฀ Center฀ by฀Monika฀Stawicka฀and฀computer฀science฀students฀learning฀English฀with฀her.฀The฀ project฀is฀interesting฀first฀of฀all,฀because฀it฀shows฀how฀to฀integrate฀learning฀English฀ with฀ professional฀ development.฀ Moreover,฀ it฀ is฀ interesting฀ because฀ it฀ proves฀ that฀ passive฀acquisition฀of฀a฀foreign฀language฀can฀be฀transformed฀into฀creative฀activities,฀ where฀both฀parties,฀a฀language฀teacher฀and฀students฀know฀that฀they฀do฀something฀ really฀new฀and฀beneficial฀not฀only฀for฀themselves,฀but฀perhaps฀also฀for฀others฀who฀ study฀English฀in฀a฀professional฀context. I฀really฀believe฀that฀all฀of฀you฀who฀will฀come฀across฀Project฀English++฀will฀share฀their฀ creative฀enthusiasm฀as฀I฀did฀during฀the฀meeting฀with฀the฀Project฀team฀in฀June฀2008.

Władysław฀T.฀Miodunka

Cracow,฀18฀July฀2008฀

English++

Introduction The aim of the book Language฀ for฀ Specific฀ Purposes฀ (LSP)฀ is฀ an฀ important฀ issue฀ in฀ studying฀ foreign฀฀ languages฀at฀lektoraty฀within฀the฀Polish฀higher฀education฀context.฀In฀the฀English++฀ project฀a฀foreign฀language฀is฀naturally฀English฀and฀a฀specific฀purpose฀is฀the฀field฀of฀

LSP

computer฀science.฀

Language฀

The฀idea฀of฀a฀complementary฀English฀course฀book฀for฀computer฀science฀students฀evolved฀

for฀Specific฀Purposes

when฀I฀was฀asked฀to฀run฀an฀English฀course฀for฀such฀students.฀A฀lack฀of฀appropriate฀and฀ coherent฀materials฀for฀teaching฀and฀learning฀the฀ESP฀element฀was฀a฀serious฀drawback฀ of฀ the฀ course.฀ The฀ reading฀ or฀ listening฀ texts฀ I฀ brought฀ to฀ the฀ classroom฀ were฀ not฀฀ always฀at฀the฀satisfactionary฀level฀as฀far฀as฀the฀subject฀matter฀was฀concerned.฀ The฀main฀aim฀of฀English++฀book,฀therefore,฀is฀an฀attempt฀to฀bridge฀the฀gap฀between฀ the฀students’฀needs฀and฀teachers’฀competences฀in฀the฀area฀of฀English฀for฀computer฀ science฀by฀offering,฀among฀other฀things,฀a฀selection฀of฀texts฀suitable฀for฀students฀at฀ their฀level฀of฀professional฀development.฀The฀unique฀trait฀of฀this฀book฀is฀the฀fact฀that฀ the฀texts฀have฀been฀selected฀and฀exercises฀have฀been฀prepared฀by฀future฀experts฀in฀ the฀field฀–฀a฀group฀of฀3rd฀year฀computer฀science฀students฀working฀under฀the฀supervision฀of฀their฀English฀teacher.฀All฀this฀to฀ease฀studying฀a฀foreign฀language฀in฀a฀subject฀ specific฀context.฀

The book’s audience This฀book฀has฀been฀aimed฀at฀two฀kinds฀of฀users.฀One฀is฀a฀computer฀science฀student฀

CEFR

whose฀general฀competence฀in฀English฀is฀at฀least฀at฀an฀upper฀intermediate฀level฀(B2฀

Common฀European

level฀according฀to฀Common฀European฀Framework฀of฀Reference).฀He฀can฀use฀the฀book฀

Framework฀of฀Reference฀

for฀self-study฀or฀in฀the฀classroom฀with฀his฀teacher’s฀assistance.฀A฀teacher฀is฀the฀second฀฀ kind฀of฀a฀user.฀He฀can฀use฀a฀given฀text฀as฀a฀starting฀point฀for฀creating฀his฀own฀activities฀฀ in฀ the฀ classroom฀ or฀ he฀ can฀ simply฀ follow฀ the฀ suggestions฀ of฀ exercises฀ the฀ book฀ provides.฀Both฀groups฀of฀users฀can฀benefit฀additionally฀by฀becoming฀more฀familiar฀฀ with฀various฀aspects฀of฀a฀broad฀area฀of฀computer฀science.

The contents of the book The฀ book฀ is฀ divided฀ into฀ three฀ chapters.฀ They฀ are฀ the฀ main฀ chapter฀ containing฀฀ authentic฀reading฀material,฀the฀chapter฀with฀listening฀material฀and฀the฀chapter฀dealing฀ with฀a฀difficult฀task฀of฀delivering฀an฀oral฀presentation.฀At฀the฀end฀of฀the฀book฀there฀ are฀appendixes฀and฀the฀glossary.฀The฀second฀and฀third฀chapters฀and฀the฀appendixes฀ are฀accompanied฀by฀audio฀and฀video฀material.฀

English++ Reading Chapter The฀following฀are฀parts฀of฀the฀reading฀chapter฀with฀a฀brief฀summary฀of฀their฀contents:

• Information on the reading text ESP

This฀section฀contains฀‘technical’฀information฀on฀a฀reading฀text,฀such฀as฀IT฀sub-areas฀

English

the฀article฀covers,฀the฀length฀of฀a฀text฀expressed฀in฀a฀number฀of฀words,฀levels฀of฀the฀

฀for฀Specific฀Purposes฀

English฀language฀complexity,฀computer฀science฀or฀math฀content,฀summaries฀in฀English฀ ฀and฀Polish,฀keywords฀with฀their฀definitions฀and฀learning฀objectives.฀This฀part฀has฀ been฀designed฀for฀both฀teachers฀and฀students฀to฀make฀their฀preliminary฀choices฀for฀ reading฀easier.฀The฀evaluation฀of฀the฀English฀level฀difficulty฀and฀subject฀matter฀complexity฀ has฀been฀provided฀by฀the฀students.

• Pre-reading questions This฀section฀has฀been฀designed฀to฀encourage฀a฀reader฀to฀think฀about฀the฀topic฀which฀ will฀be฀then฀discussed฀in฀a฀given฀text.฀The฀pre–reading฀questions฀are฀supposed฀to฀฀ IT information฀technology

provoke฀an฀exchange฀of฀opinions฀or฀a฀short฀discussion.฀Some฀of฀them฀are฀accompanied฀ by฀suggested฀answers฀provided฀in฀the฀section:฀Exercises.

• Text This฀section฀contains฀the฀whole฀text฀of฀an฀original฀article,฀or฀as฀it฀happens฀in฀the฀case฀ of฀several฀articles,฀just฀excerpts.฀The฀remaining฀parts฀are฀then฀located฀in฀the฀e-version฀ of฀the฀book.฀The฀texts฀have฀been฀selected฀for฀their฀intrinsic฀interest.฀They฀vary฀in฀ length;฀therefore฀they฀may฀be฀suitable฀for฀either฀intensive฀or฀extensive฀reading฀and฀ for฀practicing฀reading฀skills.฀

• Exercises The฀first฀part฀of฀this฀section฀contains฀suggestions฀of฀pre-reading฀questions฀this฀time฀ accompanied฀by฀suggestions฀of฀the฀answers,฀followed฀by฀comprehension฀questions฀ also฀complemented฀by฀the฀answers.฀This฀might฀be฀practical฀when฀the฀book฀is฀used฀ both฀by฀a฀learner฀for฀self฀-฀study฀and฀by฀a฀teacher฀in฀the฀classroom.฀We฀believe฀that฀ providing฀suggested฀answers฀just฀after฀the฀text฀and฀not฀at฀the฀end฀of฀the฀book฀or฀in฀ another฀book฀will฀make฀a฀teacher’s฀life฀in฀the฀classroom฀a฀bit฀easier.฀

Listening Chapter The฀organization฀of฀the฀listening฀chapter฀is฀similar฀to฀the฀organization฀of฀the฀reading฀ chapter.฀Consequently,฀the฀listening฀chapter฀contains฀the฀following฀sections:

• Information on the listening text Instead฀of฀a฀number฀of฀words฀a฀running฀time฀of฀a฀particular฀listening฀piece฀has฀been฀

provided.฀The฀level฀of฀listening฀difficulty฀has฀been฀also฀evaluated฀by฀the฀students.

English++ • Pre-listening questions The฀questions฀should฀help฀students฀focus฀their฀attention฀and฀predict฀the฀content฀of฀a฀ listening฀material.฀They฀may฀also฀provoke฀a฀short฀exchange฀of฀opinions.

• Transcript It฀ can฀ be฀ particularly฀ useful฀ when฀ the฀ listening฀ material฀ has฀ been฀ evaluated฀ as฀฀ difficult,฀which฀is฀expressed฀by฀medium฀or฀high฀English฀complexity฀or฀when฀computer฀ science฀content฀is฀high,฀too.

• Exercises They฀have฀been฀designed฀by฀the฀students฀and฀can฀be฀used฀as฀a฀starting฀point฀for฀a฀ teacher฀to฀prepare฀his/her฀own฀exercises. The฀ listening฀ chapter฀ is฀ accompanied฀ by฀ a฀ CD฀ with฀ the฀ recordings฀ selected฀ by฀ the฀ students฀from฀English++฀team.฀

Presentation Chapter The฀third฀chapter฀is฀devoted฀to฀the฀development฀of฀students’฀presentation฀skills.฀It฀ contains฀the฀following฀sections:฀

• Practical tips This฀ part฀ contains฀ practical฀ information฀ on฀ how฀ to฀ get฀ ready฀ for฀ an฀ oral฀ presentation฀ and฀make฀it฀effective.฀Therefore฀a฀reader฀will฀find฀there฀information฀about฀a฀preparatory฀ phase,฀a฀dress฀rehearsal฀or฀visual฀aids.

• Repertoire of presentation phrases This฀section฀contains฀a฀selection฀of฀ready฀to฀use฀presentation฀phrases฀to฀be฀implemented฀ into฀different฀parts฀of฀an฀oral฀presentation฀to฀make฀it฀a฀coherent฀entity.

• Slide show English++฀DVD฀with฀a฀slide฀show:฀“Successful฀Presentations.฀A฀Few฀Tips฀from฀English++”฀shows฀examples฀of฀both฀well฀done฀and฀less฀successful฀presentations.฀It฀simply฀฀ presents฀practical฀application฀of฀selected฀presentation฀phrases฀taken฀from฀the฀previous฀฀ section฀of฀this฀chapter.฀The฀main฀actors฀are฀the฀students฀from฀English++฀team,฀who฀ additionally฀have฀decided฀to฀show฀what฀a฀presentation฀should฀not฀like.

Appendixes In฀the฀appendixes฀of฀the฀book฀the฀material฀for฀pronunciation฀practice฀is฀included.฀Three฀ appendixes฀A,฀B฀and฀C฀contain฀mathematical฀terminology,฀mathematical฀formulas฀and฀

English++ the฀ Greek฀ alphabet,฀ respectively.฀ The฀ material฀ can฀ be฀ used฀ for฀ self-study฀ or฀ in฀ the฀ classroom฀to฀practice฀field฀related฀language.฀

Glossary The฀glossary฀contains฀entries฀for฀the฀keywords฀which฀have฀been฀selected฀from฀the฀ reading฀and฀listening฀texts฀of฀English++฀book.฀The฀definitions฀have฀been฀provided฀ by฀the฀students.

How to use English++ book English++฀book฀is฀an฀open฀book,฀which฀means฀that฀both฀teachers฀and฀students฀can฀ use฀and/or฀modify฀the฀material฀it฀contains฀to฀adapt฀it฀for฀their฀own฀teaching/learning฀ needs.฀However,฀any฀commercial฀usage฀of฀the฀book฀is฀prohibited.฀The฀e-version฀of฀ English฀++฀open฀book฀can฀be฀found฀on฀the฀English++฀webpage:฀ www.englishplusplus.jcj.uj.edu.pl

Pilot version This฀is฀a฀pilot฀version฀of฀the฀English++฀book.฀This฀means฀that฀over฀next฀academic฀year฀ those฀teachers฀who฀run฀English฀courses฀for฀computer฀science฀or฀math฀students฀at฀B2฀ level฀or฀above฀can฀test฀it฀in฀their฀classroom฀to฀complement฀general฀English฀materials.฀It฀ would฀be฀extremely฀valuable฀to฀have฀my฀colleagues’฀opinions,฀information฀on฀spotted฀฀ inaccuracies฀or฀suggestions฀for฀improvements.฀It฀would฀be฀equally฀valuable฀to฀obtain฀ the฀feedback฀from฀those฀for฀whom฀this฀book฀has฀been฀created฀-฀from฀computer฀science฀฀ students.฀Feel฀free฀to฀be฀constructively฀critical฀and฀comment! But฀first฀of฀all฀enjoy! Monika฀Stawicka author฀and฀leader฀of฀the฀project Cracow,฀June฀2008

Addresses฀for฀correspondence: [email protected] Monika฀Stawicka Jagiellońskie฀Centrum฀Językowe Uniwersytet฀Jagielloński ul.฀Krupnicza฀2

31-123฀Kraków

English++

English++ English for Computer Science Students

Reading Chapter

English++

History of Computers Roderick Hames Number฀of฀words฀฀

1050

Computer฀science฀content฀฀

Low

Math฀content฀฀

Low

English฀language฀complexity฀฀

Low

Learning objectives •฀ to฀acquire฀basic฀knowledge฀about฀computer฀history฀

Sub-areas covered •฀ Computer฀history

Keywords •฀ punched฀card฀-฀a฀card฀on฀which฀data฀can฀be฀recorded฀in฀the฀form฀of฀punched฀holes฀ •฀ binary฀code฀-฀code฀using฀a฀string฀of฀8฀binary฀digits฀to฀represent฀characters

Summary A฀short฀article฀which฀describes฀the฀history฀of฀computers฀and฀their฀precursors.฀It฀briefly฀ mentions฀important฀events฀from฀1600฀up฀to฀the฀times฀when฀the฀first฀computer฀was฀ built.฀A฀nice฀text฀written฀in฀a฀simple฀language.฀It฀could฀be฀used฀as฀a฀lead-in฀to฀interesting฀ discussions฀about฀the฀future฀of฀computers฀or฀the฀pace฀of฀their฀evolution. Krótki฀tekst฀opisujący฀historię฀komputerów฀wraz฀z฀tym,฀co฀można฀nazwać฀ich฀protoplastami.฀Pokrótce฀opisane฀są฀ważniejsze฀wydarzenia฀od฀1600฀roku฀aż฀do฀powstania฀ pierwszego฀ komputera.฀ Przyjemny฀ tekst,฀ napisany฀ nieskomplikowanym฀ językiem.฀ Może฀być฀wstępem฀do฀ciekawych฀dyskusji฀na฀przykład฀o฀przyszłości฀komputerów฀lub฀ tempie฀ich฀dalszego฀rozwoju.

English++

Pre-reading questions 1.฀ Why฀do฀so฀many฀people฀not฀know฀how฀the฀modern฀computer฀began? 2.฀ Why฀do฀you฀think฀the฀computer฀has฀changed฀more฀rapidly฀than฀anything฀else? 3.฀ How฀ do฀ you฀ think฀ W.W.II฀ might฀ have฀ been฀ different฀ if฀ the฀ ENIAC,฀ the฀ first฀ all฀฀ electrical฀computer,฀whose฀first฀job฀was฀to฀calculate฀the฀feasibility฀of฀a฀design฀for฀ the฀hydrogen฀bomb,฀had฀not฀been฀invented฀then?

English++

History of Computers

Early Start Computers฀have฀been฀around฀for฀quite฀a฀few฀years.฀Some฀of฀your฀parents฀were฀probably฀฀

punched฀card

around฀in฀1951฀when฀the฀first฀computer฀was฀bought฀by฀a฀business฀firm.฀Computers฀฀

a฀card฀on฀which฀data฀฀

have฀ changed฀ so฀ rapidly฀ that฀ many฀ people฀ cannot฀ keep฀ up฀ with฀ the฀ changes.฀

can฀be฀recorded฀฀

One฀ newspaper฀ tried฀ to฀ describe฀ what฀ the฀ auto฀ industry฀ would฀ look฀ like฀ if฀ it฀ had฀฀

in฀the฀form฀฀

developed฀at฀a฀similar฀pace฀to฀changes฀in฀computer฀technology:฀

of฀punched฀holes฀

“Had฀the฀automobile฀developed฀at฀a฀pace฀equal฀to฀that฀of฀the฀computer฀during฀the฀ past฀twenty฀years,฀today฀a฀Rolls฀Royce฀would฀cost฀less฀than฀$3.00,฀get฀3฀million฀miles฀ to฀the฀gallon,฀deliver฀enough฀power฀to฀drive฀(the฀ship)฀the฀Queen฀Elizabeth฀II,฀and฀six฀ of฀them฀would฀fit฀on฀the฀head฀of฀a฀pin!”฀These฀changes฀have฀occurred฀so฀rapidly฀that฀ many฀people฀do฀not฀know฀how฀our฀modern฀computer฀got฀started.฀

The First Computing Machines “Computers” ฀Since฀ancient฀times,฀people฀have฀had฀ways฀of฀dealing฀with฀data฀and฀numbers.฀Early฀ people฀tied฀knots฀in฀rope฀and฀carved฀marks฀on฀clay฀tablets฀to฀keep฀track฀of฀livestock฀ and฀ trade.฀ Some฀ people฀ consider฀ the฀ 5000-year-old฀ ABACUS฀ -฀ a฀ frame฀ with฀ beads฀ strung฀on฀wires฀-฀to฀be฀the฀first฀true฀computing฀aid.฀ As฀the฀trade฀and฀tax฀system฀grew฀in฀complexity,฀people฀saw฀that฀faster,฀more฀reliable฀ and฀accurate฀tools฀were฀needed฀for฀doing฀math฀and฀keeping฀records.฀ In฀ the฀ mid-600’s,฀ Blaise฀ Pascal฀ and฀ his฀ father,฀ who฀ was฀ a฀ tax฀ officer฀ himself,฀ were฀ working฀on฀taxes฀for฀the฀French฀government฀in฀Paris.฀The฀two฀spent฀hours฀figuring฀ and฀refiguring฀taxes฀that฀each฀citizen฀owed.฀Young฀Blaise฀decided฀in฀1642฀to฀build฀an฀ adding฀and฀subtraction฀machine฀that฀could฀assist฀in฀such฀a฀tedious฀and฀time-consuming฀ process.฀The฀machine฀Blaise฀made฀had฀a฀set฀of฀eight฀gears฀that฀worked฀together฀in฀much฀ the฀same฀way฀as฀an฀odometer฀keeps฀track฀of฀a฀car’s฀mileage.฀His฀machine฀encountered฀ many฀problems.฀For฀one฀thing,฀it฀was฀always฀breaking฀down.฀Second,฀the฀machine฀was฀

English++ slow฀and฀extremely฀costly.฀And฀third,฀people฀were฀afraid฀to฀use฀the฀machine,฀thinking฀ it฀might฀replace฀their฀jobs.฀Pascal฀later฀became฀famous฀for฀math฀and฀philosophy,฀but฀ he฀is฀still฀remembered฀for฀his฀role฀in฀computer฀technology.฀In฀his฀honor,฀there฀is฀a฀ computer฀language฀named฀Pascal.฀ The฀next฀big฀step฀for฀computers฀arrived฀in฀the฀1830s,฀when฀Charles฀Babbage฀decided฀ binary฀code

to฀build฀a฀machine฀to฀help฀him฀complete฀and฀print฀mathematical฀tables.฀Babbage฀was฀

฀code฀using฀a฀string฀฀

a฀mathematician฀who฀taught฀at฀Cambridge฀University฀in฀England.฀He฀began฀planning฀

of฀8฀binary฀digits฀฀

his฀calculating฀machine,฀calling฀it฀the฀Analytical฀Engine.฀The฀idea฀for฀this฀machine฀was฀

to฀represent฀characters

amazingly฀like฀the฀computer฀we฀know฀today.฀It฀was฀to฀read฀a฀program฀from฀punched฀ cards,฀figure฀and฀store฀the฀answers฀to฀different฀problems,฀and฀print฀the฀answer฀on฀ paper.฀Babbage฀died฀before฀he฀could฀complete฀the฀machine.฀However,฀because฀of฀his฀ remarkable฀ideas฀and฀work,฀Babbage฀is฀known฀as฀the฀Father฀of฀Computers.฀ The฀next฀huge฀step฀for฀computers฀came฀when฀Herman฀Hollerith฀entered฀a฀contest฀organised฀by฀the฀U.S.฀Census฀Bureau.฀The฀contest฀was฀to฀see฀who฀could฀build฀a฀machine฀ that฀would฀count฀and฀record฀information฀the฀fastest.฀Hollerith,฀a฀young฀man฀working฀ for฀the฀Bureau,฀built฀a฀machine฀called฀the฀Tabulating฀Machine฀that฀read฀and฀sorted฀ data฀ from฀ punched฀ cards.฀ The฀ holes฀ punched฀ in฀ the฀ cards฀ matched฀ each฀ person’s฀ answers฀to฀questions.฀For฀example,฀married,฀single,฀and฀divorced฀were฀answers฀on฀ the฀cards.฀The฀Tabulator฀read฀the฀punched฀cards฀as฀they฀passed฀over฀tiny฀brushes.฀ Each฀time฀a฀brush฀found฀a฀hole,฀it฀completed฀an฀electrical฀circuit.฀This฀caused฀special฀ counting฀dials฀to฀increase฀the฀data฀for฀that฀answer.฀ Thanks฀to฀Hollerith’s฀machine,฀instead฀of฀taking฀seven฀and฀a฀half฀years฀to฀count฀the฀ census฀information฀it฀only฀took฀three฀years,฀even฀with฀13฀million฀more฀people฀since฀ the฀ last฀ census.฀ Happy฀ with฀ his฀ success,฀ Hollerith฀ formed฀ the฀ Tabulating฀ Machine฀ Company฀in฀1896.฀The฀company฀was฀later฀sold฀in฀1911฀and฀in฀1912฀his฀company฀ became฀the฀International฀Business฀Machines฀Corporation,฀better฀known฀today฀as฀IBM.฀

The First Electric Powered Computer What฀ is฀ considered฀ to฀ be฀ the฀ first฀ computer฀ was฀ made฀ in฀ 1944฀ by฀ Harvard฀ Professor฀ ENIAC฀

Howard฀Aiken.฀The฀Mark฀I฀computer฀was฀very฀much฀like฀the฀design฀of฀Charles฀Babbage’s฀

Electronic฀฀

Analytical฀Engine,฀having฀mainly฀mechanical฀parts฀but฀with฀some฀electronic฀parts.฀His฀

Numerical฀Integrator฀฀

machine฀was฀designed฀to฀be฀programmed฀to฀do฀many฀computing฀jobs.฀This฀all-purpose฀

and฀Computer

machine฀is฀what฀we฀now฀know฀as฀the฀PC฀or฀personal฀computer.฀The฀Mark฀I฀was฀the฀ first฀computer฀financed฀by฀IBM฀and฀was฀about฀50฀feet฀long฀and฀8฀feet฀tall.฀It฀used฀ mechanical฀switches฀to฀open฀and฀close฀its฀electric฀circuits.฀It฀contained฀over฀500฀miles฀ of฀wire฀and฀750,000฀parts.฀

English++ The First All Electronic Computer The฀first฀all฀electronic฀computer฀was฀the฀ENIAC฀(Electronic฀Numerical฀Integrator฀and฀

EDVAC

Computer).฀ENIAC฀was฀a฀general฀purpose฀digital฀computer฀built฀in฀1946฀by฀J.฀Presper฀

Electronic฀฀

Eckert฀and฀John฀Mauchly.฀The฀ENIAC฀contained฀over฀18,000฀vacuum฀tubes฀(used฀instead฀

Discrete฀Variable฀Computer

of฀the฀mechanical฀switches฀of฀the฀Mark฀I)฀and฀was฀1000฀times฀faster฀than฀the฀Mark฀I.฀ In฀twenty฀seconds,฀ENIAC฀could฀do฀a฀math฀problem฀that฀would฀have฀taken฀40฀hours฀ for฀one฀person฀to฀finish.฀The฀ENIAC฀was฀built฀at฀the฀time฀of฀World฀War฀II฀and฀as฀its฀ first฀job฀had฀to฀calculate฀the฀feasibility฀of฀a฀design฀for฀the฀hydrogen฀bomb.฀The฀ENIAC฀ was฀100฀feet฀long฀and฀10฀feet฀tall.฀

More Modern Computers A฀ more฀ modern฀ type฀ of฀ computer฀ began฀ with฀ John฀ von฀ Neumann’s฀ development฀ of฀software฀written฀in฀binary฀code.฀It฀was฀von฀Neumann฀who฀began฀the฀practice฀of฀ storing฀data฀and฀instructions฀in฀binary฀code฀and฀initiated฀the฀use฀of฀memory฀to฀store฀ data,฀as฀well฀as฀programs.฀A฀computer฀called฀the฀EDVAC฀(Electronic฀Discrete฀Variable฀ Computer)฀was฀built฀using฀binary฀code฀in฀1950.฀Before฀the฀EDVAC,฀computers฀like฀the฀ ENIAC฀could฀do฀only฀one฀task;฀then฀they฀had฀to฀be฀rewired฀to฀perform฀a฀different฀task฀ or฀ program.฀ The฀ EDVAC’s฀ concept฀ of฀ storing฀ different฀ programs฀ on฀ punched฀ cards฀ instead฀of฀rewiring฀computers฀led฀to฀the฀computers฀that฀we฀know฀today.฀ While฀the฀modern฀computer฀is฀far฀better฀and฀faster฀than฀the฀EDVAC฀of฀its฀time,฀computers฀ of฀ today฀ would฀ not฀ have฀ been฀ possible฀ without฀ the฀ knowledge฀ and฀ work฀ of฀ many฀ great฀inventors฀and฀pioneers.

English++

Exercises Comprehension questions 1.฀ Why฀was฀Pascal฀honored฀with฀a฀computer฀language฀named฀for฀him? •฀ This฀programming฀language฀was฀named฀as฀a฀tribute฀to฀Blaise฀Pascal,฀because฀of฀ his฀contribution฀to฀computer฀development.฀He฀was฀the฀first฀to฀build฀a฀precursor฀ of฀the฀modern฀computer-an฀adding฀an฀subtraction฀machine฀that฀could฀assist฀in฀ tedious฀and฀time-consuming฀computational฀process. 2.฀ Who฀was฀the฀first฀to฀invent฀a฀machine฀whose฀operating฀principle฀is฀very฀similar฀ to฀present-day฀computers?฀Describe฀these฀similarities. •฀ Charles฀Babbage,฀whose฀idea฀was฀remarkably฀similar฀to฀the฀way฀modern฀computers฀ work:฀read฀program฀from฀punched฀cards฀(input),฀figure฀and฀store฀the฀answers฀to฀ different฀problems,฀and฀print฀the฀answer฀on฀paper฀(output)฀ 3.฀ In฀which฀process฀was฀Hollerith’s฀machine฀involved฀and฀what฀was฀its฀role? •฀ Hollerith’s฀machine฀helped฀with฀the฀counting฀of฀census฀information.฀It฀took฀three฀ years,฀instead฀of฀seven฀and฀half,฀even฀with฀13฀million฀more฀people฀since฀the฀previous฀ census.฀“The฀machine฀read฀and฀sorted฀data฀from฀punched฀cards.฀The฀holes฀punched฀ in฀ the฀ cards฀ matched฀ each฀ person’s฀ answers฀ to฀ questions.฀ For฀ example,฀ married,฀ single,฀and฀divorced฀were฀answers฀on฀the฀cards.฀The฀Tabulator฀read฀the฀punched฀cards฀ as฀they฀passed฀over฀tiny฀brushes.฀Each฀time฀a฀brush฀found฀a฀hole,฀it฀completed฀an฀฀ electrical฀circuit.฀This฀caused฀special฀counting฀dials฀to฀increase฀the฀data฀for฀that฀answer. 4.฀ Describe฀all฀the฀technical฀parameters฀of฀the฀first฀electric฀powered฀computer. •฀ 50฀feet฀long,฀8฀feet฀tall,฀electrical฀circuits฀are฀opened฀and฀closed฀by฀mechanical฀ switches,฀contained฀500฀miles฀of฀wire฀and฀750฀000฀parts 5.฀ What฀were฀the฀differences฀between฀the฀Mark฀I฀and฀the฀ENIAC? •฀ Mark฀ I฀ -฀ electric฀ powered,฀ 50฀ feet฀ long฀ and฀ 8฀ tall,฀ used฀ mechanical฀ switches฀ to฀ open/close฀electrical฀circuits •฀ ENIAC฀-฀all฀electronic฀computer,฀used฀18,000฀vacuum฀tubes฀instead฀of฀mechanical฀ switches,฀1000฀times฀faster฀than฀Mark฀I,฀100฀feet฀long฀and฀10฀feet฀tall 6.฀ What฀is฀the฀main฀advantage฀of฀using฀binary฀code฀in฀storing฀data฀and฀instructions? •฀ First฀computers฀like฀the฀ENIAC฀could฀do฀only฀one฀task,฀then฀they฀had฀to฀be฀rewired฀ to฀perform฀a฀different฀task฀or฀program.฀The฀binary฀code฀concept฀of฀storing฀different฀ programs฀on฀punched฀cards฀instead฀of฀rewiring฀computers฀led฀to฀computers฀that฀we฀ know฀today.

Possible topics for discussion 1.฀ Future฀of฀computers.

Possible difﬁculties 20

This฀is฀a฀fairly฀easy฀to฀text฀to฀encourage฀a฀reader฀to฀study฀a฀bit฀more฀advanced฀articles.฀ There฀should฀not฀be฀any฀problems฀with฀understanding฀this฀article.

English++

ILOVEYOU Worm Wikipedia Number฀of฀words฀฀

1150

Computer฀science฀content฀฀

Medium

Math฀content฀฀

Low

English฀language฀complexity฀฀

Medium

Learning objectives •฀ to฀understand฀why฀the฀ILOVEYOU฀worm฀was฀so฀successful •฀ to฀understand฀the฀architecture฀of฀the฀ILOVEYOU฀worm฀as฀a฀basic฀script฀virus •฀ to฀recognize฀how฀big฀an฀effect฀a฀single฀virus฀can฀have฀on฀global฀IT

Sub-areas covered •฀ Computer฀virus •฀ Computer฀worm •฀ Popular฀worms/viruses

Keywords •฀ malware฀-฀software฀designed฀to฀infiltrate฀or฀damage฀a฀computer฀system฀without฀ the฀owner’s฀informed฀consent •฀ VBScript฀-฀Visual฀Basic฀Scripting฀Edition฀-฀an฀Active฀Scripting;฀technology฀used฀in฀฀ Windows฀to฀implement฀component-based฀scripting฀support;฀a฀language฀developed฀฀ by฀Microsoft฀ •฀ social฀engineering฀-฀practice฀of฀obtaining฀confidential฀information฀by฀manipulating฀ users •฀ Barok฀trojan฀-฀this฀trojan฀horse฀gathers฀information฀such฀as฀user฀name,฀IP฀address฀ and฀passwords,฀and฀attempts฀to฀send฀the฀information฀to฀the฀creator฀of฀the฀virus

Summary The฀ article฀ provides฀ information฀ about฀ the฀ creation฀ and฀ history฀ of฀ a฀ well-known฀ computer฀worm฀called฀‘ILOVEYOU’.฀The฀first฀section฀contains฀its฀basic฀description฀ and฀explains฀the฀features฀of฀the฀worm฀that฀made฀it฀effective.฀The฀following฀sections฀ describe฀how฀the฀worm฀spread฀and฀the฀effect฀it฀had฀worldwide.฀The฀article฀gives฀information฀about฀the฀author฀of฀the฀worm฀and฀the฀man฀who฀wrote฀the฀software฀that฀ repaired฀the฀damage฀it฀caused.฀This฀is฀followed฀by฀a฀section฀on฀how฀the฀‘ILOVEYOU’฀ worm฀affects฀computers.฀The฀text฀ends฀with฀brief฀information฀about฀the฀legal฀measures฀against฀the฀author฀of฀the฀worm.

English++ Tekst฀opisuje฀jeden฀z฀bardziej฀znanych฀robaków฀komputerowych฀-฀‘ILOVEYOU’.฀Pierwsza฀฀ część฀zawiera฀podstawowe฀informacje฀o฀programie฀i฀tym,฀co฀uczyniło฀go฀efektywnym.฀ Następna฀opowiada฀o฀rozprzestrzenianiu฀się฀wirusa.฀Kolejne฀przedstawiają฀globalne฀ działanie฀ robaka,฀ informują฀ o฀ jego฀ autorze฀ oraz฀ o฀ twórcy฀ programu฀ naprawiającego฀ szkody.฀Kolejna฀część฀tekstu฀dostarcza฀wiadomości฀o฀działaniach฀‘ILOVEYOU’฀na฀komputerze฀-฀co฀robi฀i฀jakie฀wywołuje฀szkody.฀Tekst฀kończy฀się฀informacją฀na฀temat฀konsekwencji฀prawnych฀wyciągniętych฀wobec฀autora฀‘ILOVEYOU’.฀

Pre-reading questions 1.฀ What฀attacks฀have฀you฀heard฀about?฀ 2.฀ Have฀you฀ever฀had฀a฀virus฀or฀worm฀in฀your฀mail?฀ 3.฀ Name฀a฀few฀of฀the฀most฀famous฀viruses.

English++

ILOVEYOU Worm

social฀engineering฀ practice฀of฀obtaining฀ confidential฀information฀ by฀manipulating฀users The฀ILOVEYOU฀worm,฀also฀known฀as฀VBS/Loveletter฀and฀Love฀Bug฀worm,฀is฀a฀computer฀ worm฀written฀in฀VBScript.

Description The฀worm,฀first฀discovered฀in฀Hong฀Kong,฀arrived฀in฀e-mail฀boxes฀on฀May฀4,฀2000,฀

VBScript

with฀the฀simple฀subject฀of฀“ILOVEYOU”฀and฀an฀attachment฀“LOVE-LETTER-FOR-YOU.

Visual฀Basic฀Scripting฀

TXT.vbs”.

Edition฀-฀an฀Active฀ Scripting฀

Two aspects of the worm made it effective: •฀ It฀relied฀on฀social฀engineering฀to฀entice฀users฀to฀open฀the฀e-mail฀and฀ensure฀its฀ continued฀propagation. •฀ It฀employed฀a฀mechanism฀—฀VBScripts฀—฀that,฀while฀not฀entirely฀novel,฀had฀not฀ been฀exploited฀to฀such฀a฀degree฀previously฀to฀direct฀attention฀to฀their฀potential,฀ reducing฀the฀layers฀of฀protection฀that฀would฀have฀to฀be฀navigated฀for฀success.

(technology฀used฀ in฀Windows฀to฀implement component-based฀ scripting฀support)฀ language฀developed฀ by฀Microsoft฀

Spread Its฀massive฀spread฀moved฀westward฀as฀workers฀arrived฀at฀their฀offices฀and฀encountered฀ messages฀generated฀by฀people฀from฀the฀East.฀Because฀the฀virus฀used฀mailing฀lists฀as฀ its฀source฀of฀targets,฀the฀messages฀often฀appeared฀to฀come฀from฀an฀acquaintance฀and฀ so฀might฀be฀considered฀“safe”,฀providing฀further฀incentive฀to฀open฀them.฀All฀it฀took฀ was฀a฀few฀users฀at฀each฀site฀to฀access฀the฀VBS฀attachment฀to฀generate฀the฀thousands฀ and฀thousands฀of฀e-mails฀that฀would฀cripple฀e-mail฀systems฀under฀their฀weight,฀not฀ to฀mention฀overwrite฀thousands฀of฀files฀on฀workstations฀and฀accessible฀servers.

Effects It฀began฀in฀the฀Philippines฀on฀May฀4,฀2000,฀and฀spread฀across฀the฀world฀in฀one฀day฀ (travelling฀from฀Hong-Kong฀to฀Europe฀to฀the฀United฀States),฀infecting฀10฀percent฀of฀all฀ computers฀connected฀to฀the฀Internet฀and฀causing฀about฀$5.5฀billion฀in฀damage.฀Most฀

English++ of฀the฀“damage”฀was฀the฀labor฀of฀getting฀rid฀of฀the฀virus.฀The฀Pentagon,฀CIA,฀and฀the฀ British฀Parliament฀had฀to฀shut฀down฀their฀e-mail฀systems฀to฀get฀rid฀of฀the฀worm,฀as฀ did฀most฀large฀corporations. This฀ particular฀ malware฀ caused฀ widespread฀ outrage,฀ making฀ it฀ the฀ most฀ damaging฀ malware

worm฀ever.฀The฀worm฀overwrote฀important฀files,฀as฀well฀as฀music,฀multimedia฀and฀

software฀designed฀

more,฀with฀a฀copy฀of฀itself.฀It฀also฀sent฀the฀worm฀to฀everyone฀on฀a฀user’s฀contact฀list.฀

to฀infiltrate฀or฀damage฀

This฀ particular฀ worm฀ only฀ affected฀ computers฀ running฀ the฀ Microsoft฀ Windows฀

a฀computer฀system฀

operating฀system.฀While฀any฀computer฀accessing฀e-mail฀could฀receive฀an฀“ILOVEYOU”฀

without฀the฀owner’s฀

e-mail,฀only฀Microsoft฀Windows฀systems฀would฀be฀infected.

informed฀consent

Authorship The฀ILOVEYOU฀worm฀is฀believed฀to฀have฀been฀written฀by฀Michael฀Buen.฀The฀Barok฀ trojan฀horse฀used฀by฀the฀worm฀is฀believed฀to฀have฀been฀written฀by฀Onel฀de฀Guzman,฀ a฀Filipino฀student฀of฀AMA฀Computer฀University฀in฀Makati,฀Philippines. An฀ international฀ manhunt฀ for฀ the฀ perpetrator฀ finally฀ led฀ to฀ a฀ young฀ programming฀ student.฀On฀May฀11฀(one฀week฀after฀the฀virus฀spread),฀he฀held฀a฀news฀conference฀and฀ said฀that฀he฀did฀not฀mean฀to฀cause฀so฀much฀harm.฀He฀was฀unable฀to฀graduate฀because฀ the฀university฀rejected฀his฀thesis฀on฀the฀basis฀of฀its฀illegality.฀Helped฀by฀a฀group฀of฀ friends฀ called฀ the฀ Grammersoft฀ Group,฀ he฀ distributed฀ his฀ virus฀ the฀ day฀ before฀ the฀ school฀held฀their฀graduation฀ceremony.

Detection Narinnat฀Suksawat,฀a฀25-year-old฀Thai฀software฀engineer,฀was฀the฀first฀person฀to฀write฀ software฀that฀repaired฀the฀damage฀caused฀by฀the฀worm,฀releasing฀it฀to฀the฀public฀on฀ May฀5,฀2000,฀24฀hours฀after฀the฀worm฀had฀spread.฀“Rational฀Killer”,฀the฀program฀he฀ created,฀removed฀virus฀files฀and฀restored฀the฀previously฀removed฀system฀files฀so฀they฀ again฀functioned฀normally.฀Two฀months฀later,฀Narinnat฀was฀offered฀a฀senior฀consultant฀job฀at฀Sun฀Microsystems฀and฀worked฀there฀for฀two฀years.฀He฀resigned฀to฀start฀his฀ own฀business.฀Today,฀Narinnat฀owns฀a฀software฀company฀named฀Moscii฀Systems,฀a฀ system฀management฀software฀company฀in฀Thailand.

Architecture of the worm The฀worm฀is฀written฀using฀Microsoft฀Visual฀Basic฀Scripting฀(VBS),฀and฀requires฀that฀ the฀end-user฀run฀the฀script฀in฀order฀to฀deliver฀its฀payload.฀It฀will฀add฀a฀set฀of฀registry฀ keys฀to฀the฀Windows฀registry฀that฀will฀allow฀the฀malware฀to฀start฀up฀at฀every฀boot.

English++ The฀worm฀will฀then฀search฀all฀drives฀which฀are฀connected฀to฀the฀infected฀computer฀and฀ replace฀files฀with฀the฀extensions฀*.JPG,฀*.JPEG,฀*.VBS,฀*.VBE,฀*.JS,฀*.JSE,฀*.CSS,฀*.WSH,฀ *.SCT,฀*.DOC฀*.HTA฀with฀copies฀of฀itself,฀while฀appending฀to฀the฀file฀name฀a฀.VBS.฀ extension.฀The฀malware฀will฀also฀locate฀*.MP3฀and฀*.MP2฀files,฀and฀when฀found,฀makes฀ the฀files฀hidden,฀copies฀itself฀with฀the฀same฀file฀name฀and฀appends฀a฀.VBS. The฀ worm฀ propagates฀ by฀ sending฀ out฀ copies฀ of฀ itself฀ to฀ all฀ entries฀ in฀ the฀ Microsoft฀฀

Barok฀trojan

Outlook฀address฀book.฀It฀also฀has฀an฀additional฀component,฀in฀which฀it฀will฀download฀and฀

this฀trojan฀horse

execute฀an฀infected฀program฀called฀variously฀“WIN-BUGSFIX.EXE”฀or฀“Microsoftv25.exe”.฀

฀gathers฀information฀

This฀is฀a฀password-stealing฀program฀which฀will฀e-mail฀cached฀passwords.

such฀as฀user฀name,฀ IP฀address฀and฀passwords,฀

Variants 1.฀ Attachment:฀LOVE-LETTER-FOR-YOU.TXT.vbs ฀

Subject฀Line:฀ILOVEYOU

฀

Message฀Body:฀kindly฀check฀the฀attached฀LOVELETTER฀coming฀from฀me.

and฀attempts฀to฀send฀the฀ information฀to฀the฀creator฀ of฀the฀virus

2.฀ Attachment:฀Very฀Funny.vbs ฀

Subject฀Line:฀fwd:฀Joke

฀

Message฀Body:฀empty

3.฀ Attachment:฀mothersday.vbs ฀

Subject฀Line:฀Mothers฀Day฀Order฀Confirmation

฀

Message฀Body:฀We฀have฀proceeded฀to฀charge฀your฀credit฀card฀for฀the฀amount฀of฀ $326.92฀for฀the฀mothers฀day฀diamond฀special.฀We฀have฀attached฀a฀detailed฀invoice฀ to฀this฀email.฀Please฀print฀out฀the฀attachment฀and฀keep฀it฀in฀a฀safe฀place.฀Thanks฀ Again฀and฀Have฀a฀Happy฀Mothers฀Day!฀[email protected]

4.฀ Attachment:฀virus_warning.jpg.vbs ฀

Subject฀Line:฀Dangerous฀Virus฀Warning

฀

Message฀Body:฀There฀is฀a฀dangerous฀virus฀circulating.฀Please฀click฀attached฀picture฀ to฀view฀it฀and฀learn฀to฀avoid฀it.

5.฀ Attachment:฀protect.vbs ฀

Subject฀Line:฀Virus฀ALERT!!!

฀

Message฀Body:฀a฀long฀message฀regarding฀VBS.LoveLetter.A

6.฀ Attachment:฀Important.TXT.vbs ฀

Subject฀Line:฀Important!฀Read฀carefully!!

฀

Message฀Body:฀Check฀the฀attached฀IMPORTANT฀coming฀from฀me!

7.฀ Attachment:฀Virus-Protection-Instructions.vbs ฀

Subject฀Line:฀How฀to฀protect฀yourself฀from฀the฀IL0VEYOU฀bug!

฀

Message฀Body:฀Here’s฀the฀easy฀way฀to฀fix฀the฀love฀virus.

8.฀ Attachment:฀KillEmAll.TXT.VBS ฀

Subject฀Line:฀I฀Cant฀Believe฀This!!!

฀

Message฀Body:฀I฀Cant฀Believe฀I฀have฀Just฀received฀This฀Hate฀Email฀..฀Take฀A฀Look!

English++ 9.฀ Attachment:฀ArabAir.TXT.vbs ฀

Subject฀Line:฀Thank฀You฀For฀Flying฀With฀Arab฀Airlines

฀

Message฀Body:฀Please฀check฀if฀the฀bill฀is฀correct,฀by฀opening฀the฀attached฀file

10.฀Attachment:฀IMPORTANT.TXT.vbs ฀

Subject฀Line:฀Variant฀Test

฀

Message฀Body:฀This฀is฀a฀variant฀to฀the฀vbs฀virus.

11.฀Attachment:฀Vir-Killer.vbs ฀

Subject฀Line:฀Yeah,฀Yeah฀another฀time฀to฀DEATH…

฀

Message฀Body:฀This฀is฀the฀Killer฀for฀VBS.LOVE-LETTER.WORM.

12.฀Attachment:฀LOOK.vbs ฀

Subject฀Line:฀LOOK!

฀

Message฀Body:฀hehe…check฀this฀out.

13.฀Attachment:฀BEWERBUNG.TXT.vbs ฀

Subject฀Line:฀Bewerbung฀Kreolina

฀

Message฀Body:฀Sehr฀geehrte฀Damen฀und฀Herren!

14.฀Subject฀Line:฀Is฀this฀you฀in฀this฀picture? ฀

Message฀Body:฀Is฀this฀you฀in฀this฀picture?

Legislative aftermath As฀ there฀ were฀ no฀ laws฀ against฀ virus-writing฀ at฀ the฀ time,฀ on฀ August฀ 21,฀ 2000,฀ the฀ prosecutors฀dropped฀all฀charges฀against฀Onel฀A.฀de฀Guzman฀in฀a฀resolution฀signed฀ by฀ Jovencito฀ Zuno.฀ The฀ original฀ charges฀ brought฀ up฀ against฀ de฀ Guzman฀ dealt฀ with฀ the฀illegal฀use฀of฀passwords฀for฀credit฀card฀and฀bank฀transactions.฀The฀Philippines฀฀ E-Commerce฀Law฀(Republic฀Act฀No.฀8792),฀passed฀on฀June฀14,฀2000,฀laid฀out฀penalties฀฀ for฀ cybercrime.฀ Under฀ the฀ law,฀ those฀ who฀ spread฀ computer฀ viruses฀ or฀ otherwise฀฀ engage฀ in฀ cybercrime฀ (including฀ copyright฀ infringement฀ and฀ software฀ cracking)฀ can฀ be฀ fined฀ a฀ minimum฀ of฀ 100,000฀ pesos฀ (about฀ USD$2,000),฀ and฀ a฀ maximum฀฀ commensurate฀ with฀ the฀ damage฀ caused,฀ and฀ imprisoned฀ for฀ six฀ months฀ to฀ three฀ years.

English++

Exercises Pre-reading exercises 1.฀ What฀attacks฀have฀you฀heard฀about?฀ 2.฀ Have฀you฀ever฀had฀a฀virus฀or฀worm฀in฀mail?฀ 3.฀ Name฀a฀few฀of฀the฀most฀famous฀viruses. •฀ Melissa •฀ Love฀Bug •฀ Code฀Red •฀ Bugbear •฀ Blaster

Comprehension questions 1.฀ What฀kind฀of฀attachment฀was฀in฀the฀ILOVEYOU฀worm? •฀ It฀was฀a฀visual฀basic฀script.฀ 2.฀ In฀what฀language฀was฀the฀ILOVEYOU฀worm฀written?฀ •฀ VBScript฀programming฀language 3.฀ When฀was฀the฀ILOVEYOU฀worm฀detected?฀ •฀ 4th฀May,฀2000 4.฀ Who฀created฀the฀Barok฀trojan? •฀ Onel฀de฀Guzman,฀a฀Filipino฀student 5.฀ What฀action฀did฀the฀Pentagon฀take฀in฀order฀to฀protect฀itself฀from฀the฀‘I฀Love฀ You’฀virus? •฀ Pentagon฀had฀to฀shut฀down฀own฀e-mail฀system.฀

Further exercises 1.฀ Match฀headings฀to฀paragraphs.฀ 2.฀ There฀are฀several฀different฀variants฀of฀emails฀with฀this฀virus฀in฀the฀article.฀Write฀ your฀own฀variant฀of฀email฀that฀will฀encourage฀people฀to฀open฀the฀attachment.฀

Possible topics for discussion 1.฀ Why฀was฀this฀virus฀so฀dangerous฀and฀harmful?฀ •฀ The฀ worm฀ overwrote฀ important฀ files,฀ as฀ well฀ as฀ music,฀ multimedia฀ and฀ more,฀ with฀a฀copy฀of฀itself.฀It฀also฀sent฀the฀worm฀to฀everyone฀on฀a฀user’s฀contact฀list. 2.฀ Why฀did฀it฀attack฀only฀Windows฀Operating฀Systems?฀ •฀ Bad฀ security฀ policy,฀ holes฀ in฀ the฀ security฀ mechanism฀ system฀ and฀ a฀ lot฀ of฀ users฀ oblivious฀of฀danger฀-฀these฀factors฀have฀added฀to฀virus฀success. 3.฀ What฀legal฀consequences฀should฀be฀faced฀by฀the฀authors฀of฀computer฀viruses?฀ •฀ high฀fines •฀ ban฀on฀access฀to฀computers

English++ 4.฀ What฀ action฀ each฀ computer฀ user฀ can฀ take฀ to฀ protect฀ their฀ computers฀ against฀฀ computer฀worms? •฀ install฀anti-virus฀software •฀ be฀careful฀what฀e-mail฀attachment฀you฀open,฀what฀websites฀you฀visit •฀ check฀source฀of฀software฀which฀you฀install •฀ check฀data฀mediums,฀before฀you฀open฀them,฀–฀especially฀pen-drives฀

Possible difﬁculties To฀help฀you฀understand฀certain฀parts฀of฀the฀text,฀make฀sure฀you฀know฀the฀meaning฀ of฀the฀keywords฀before฀you฀start฀reading.฀

฀

English++

Anatomy of the Linux Kernel Tim Jones Number฀of฀words฀฀

2730

Computer฀science฀content฀฀

High

Math฀content฀฀

Low

English฀language฀complexity฀฀

Low

Learning objectives •฀ to฀acquire฀basic฀vocabulary฀related฀to฀operating฀systems •฀ to฀understand฀the฀basics฀of฀Linux฀kernel฀architecture

Sub-areas covered •฀ Linux฀kernel฀and฀its฀subsystems฀

Keywords •฀ kernel฀ -฀ the฀ central฀ component฀ of฀ most฀ computer฀ operating฀ systems฀ (OS).฀ Its฀ functions฀include฀managing฀the฀system’s฀resources฀(the฀communication฀between฀ hardware฀and฀software฀components)฀ •฀ Linux฀kernel฀-฀Unix-like฀operating฀system฀kernel฀ •฀ VFS(Virtual฀file฀system)฀-฀an฀abstraction฀layer฀on฀top฀of฀a฀more฀concrete฀file฀system฀ •฀ GNU฀-฀a฀computer฀operating฀system฀composed฀entirely฀of฀free฀software,฀initiated฀ in฀1984฀by฀Richard฀Stallman฀ •฀ GPL฀-฀a฀widely฀used฀free฀software฀license,฀originally฀written฀by฀Richard฀Stallman฀ for฀the฀GNU฀project฀ •฀ Minix฀-฀free/open฀source,฀Unix-like฀operating฀system฀(OS)฀based฀on฀a฀microkernel฀ architecture฀ •฀ Unix฀-฀a฀computer฀operating฀system฀originally฀developed฀in฀1969฀by฀a฀group฀of฀AT&T฀ employees฀at฀Bell฀Labs฀including฀Ken฀Thompson,฀Dennis฀Ritchie฀and฀Douglas฀Ilroy •฀ operating฀ system฀ -฀ the฀ software฀ that฀ manages฀ the฀ sharing฀ of฀ the฀ resources฀ of฀ a฀ computer฀ and฀ provides฀ programmers฀ with฀ an฀ interface฀ used฀ to฀ access฀ those฀฀ resources฀ •฀ buffer฀-฀a฀region฀of฀memory฀used฀to฀temporarily฀hold฀data฀while฀it฀is฀being฀moved฀ from฀one฀place฀to฀another •฀ buffer฀cache฀-฀a฀collection฀of฀data฀duplicating฀original฀values฀stored฀elsewhere฀or฀ computed฀earlier,฀where฀the฀original฀data฀is฀expensive฀to฀fetch฀(owing฀to฀longer฀ access฀time)฀or฀to฀compute,฀compared฀to฀the฀cost฀of฀reading฀the฀cache

English++

Summary As฀the฀title฀suggests,฀this฀article฀is฀about฀the฀linux฀kernel.฀It฀starts฀with฀a฀historical฀ introduction,฀ which฀ includes฀ information฀ on฀ unix฀ and฀ minix,฀ the฀ predecessors฀ of฀ linux.฀The฀next฀section฀is฀about฀the฀linux฀kernel฀in฀general฀and฀how฀it฀is฀constructed.฀ The฀third฀section฀is฀divided฀into฀sub-sections฀which฀describe฀the฀subsystems฀in฀the฀linux฀฀ kernel.฀ Subsequent฀ sections฀ deal฀ with฀ memory฀ management,฀ process฀ management,฀ drivers฀layer฀or฀network฀stack.฀The฀article฀is฀not฀very฀complex,฀being฀only฀an฀introduction฀ to฀the฀linux฀kernel.฀It฀concludes฀with฀a฀list฀of฀links฀to฀longer฀articles฀about฀the฀linux฀kernel฀ and฀its฀subsystems.฀ Jak฀wskazuje฀tytuł,฀artykuł฀ten฀jest฀o฀jądrze฀linuxa.฀Na฀początku฀mały฀wstęp฀historyczny.฀W฀tej฀części฀zawarte฀są฀informacje฀o฀unixie฀i฀minixie,฀poprzednikach฀linuxa.฀ Następna฀część฀traktuje฀o฀jądrze฀linuxa฀jako฀całości,฀czyli฀jak฀ogólnie฀jest฀ono฀zbudowane.฀Trzecia฀część฀jest฀złożona฀z฀mniejszych฀podczęści.฀Każda฀opisuje฀jeden฀z฀podsystemów฀jądra.฀Kolejne฀części฀mówią฀o:฀zarządzaniu฀pamięcią,฀zarządzaniu฀procesami,฀ warstwą฀sterowników,฀systemie฀plików,฀interfejsie฀wywołań฀systemowych฀oraz฀stosie฀ sieciowym.฀ Artykuł฀ nie฀ jest฀ zbyt฀ rozbudowany,฀ jest฀ on฀ tylko฀ wstępem฀ do฀ jądra฀ linuxa.฀Na฀końcu฀tekstu฀znajduje฀się฀lista฀odnośników฀do฀innych฀artykułów฀bardziej฀ szczegółowo฀omawiających฀różne฀części฀jądra.฀

Pre-reading exercises 1.฀ What฀are฀the฀most฀popular฀operating฀systems? 2.฀ What฀are฀the฀advantages฀of฀Linux? 3.฀ What฀are฀the฀disadvantages฀of฀Linux?

English++

Anatomy of the Linux Kernel The฀Linux®฀kernel฀is฀the฀core฀of฀a฀large฀and฀complex฀operating฀system,฀and฀while฀it฀

operating฀system

is฀huge,฀it฀is฀well฀organized฀in฀terms฀of฀subsystems฀and฀layers.฀In฀this฀article,฀you฀can฀

the฀software฀that฀manages฀

explore฀the฀general฀structure฀of฀the฀Linux฀kernel฀and฀get฀to฀know฀its฀major฀subsystems฀

the฀sharing฀of฀the฀resourc-

and฀core฀interfaces.฀Where฀possible,฀you฀get฀links฀to฀other฀IBM฀articles฀to฀help฀you฀

es฀of฀a฀computer฀and฀

dig฀deeper.

provides฀programmers฀

Given฀that฀the฀goal฀of฀this฀article฀is฀to฀introduce฀you฀to฀the฀Linux฀kernel฀and฀explore฀its฀ architecture฀and฀major฀components,฀let’s฀start฀with฀a฀short฀tour฀of฀Linux฀kernel฀history,฀

with฀an฀interface฀used฀to฀ access฀those฀resources฀

then฀look฀at฀the฀Linux฀kernel฀architecture฀from฀30,000฀feet,฀and,฀finally,฀examine฀its฀ major฀subsystems.฀The฀Linux฀kernel฀is฀over฀six฀million฀lines฀of฀code,฀so฀this฀introduction฀ is฀not฀exhaustive.฀Use฀the฀pointers฀to฀more฀content฀to฀dig฀in฀further.

A short tour of Linux history While฀Linux฀is฀arguably฀the฀most฀popular฀open฀source฀operating฀system,฀its฀history฀ is฀ actually฀ quite฀ short฀ considering฀ the฀ timeline฀ of฀ operating฀ systems.฀ In฀ the฀ early฀ days฀of฀computing,฀programmers฀developed฀on฀the฀bare฀hardware฀in฀the฀hardware’s฀ language.฀The฀lack฀of฀an฀operating฀system฀meant฀that฀only฀one฀application฀(and฀one฀ user)฀ could฀ use฀ the฀ large฀ and฀ expensive฀ device฀ at฀ a฀ time.฀ Early฀ operating฀ systems฀ were฀developed฀in฀the฀1950s฀to฀provide฀a฀simpler฀development฀experience.฀Examples฀ include฀the฀General฀Motors฀Operating฀System฀(GMOS)฀developed฀for฀the฀IBM฀701฀and฀ the฀FORTRAN฀Monitor฀System฀(FMS)฀developed฀by฀North฀American฀Aviation฀for฀the฀ IBM฀709. In฀the฀1960s,฀the฀Massachusetts฀Institute฀of฀Technology฀(MIT)฀and฀a฀host฀of฀companies฀ developed฀an฀experimental฀operating฀system฀called฀Multics฀(or฀Multiplexed฀Information฀ and฀Computing฀Service)฀for฀the฀GE-645.฀One฀of฀the฀developers฀of฀this฀operating฀system,฀ AT&T,฀ dropped฀ out฀ of฀ Multics฀ and฀ developed฀ their฀ own฀ operating฀ system฀ in฀ 1970฀ called฀Unics.฀Along฀with฀this฀operating฀system฀was฀the฀C฀language,฀for฀which฀C฀was฀ developed฀and฀then฀rewritten฀to฀make฀operating฀system฀development฀portable. Twenty฀ years฀ later,฀ Andrew฀ Tanenbaum฀ created฀ a฀ microkernel฀ version฀ of฀ UNIX®,฀ called฀MINIX฀(for฀minimal฀UNIX),฀that฀ran฀on฀small฀personal฀computers.฀This฀open฀ source฀operating฀system฀inspired฀Linus฀Torvalds’฀initial฀development฀of฀Linux฀in฀the฀ early฀1990s฀ Linux฀ quickly฀ evolved฀ from฀ a฀ single-person฀ project฀ to฀ a฀ world-wide฀ development฀ project฀involving฀thousands฀of฀developers.฀One฀of฀the฀most฀important฀decisions฀for฀ Linux฀was฀its฀adoption฀of฀the฀GNU฀General฀Public฀License฀(GPL).฀Under฀the฀GPL,฀the฀ Linux฀kernel฀was฀protected฀from฀commercial฀exploitation,฀and฀it฀also฀benefited฀from฀

English++ the฀user-space฀development฀of฀the฀GNU฀project฀(of฀Richard฀Stallman,฀whose฀source฀ dwarfs฀that฀of฀the฀Linux฀kernel).฀This฀allowed฀useful฀applications฀such฀as฀the฀GNU฀ Compiler฀Collection฀(GCC)฀and฀various฀shell฀support.

Introduction to the Linux kernel Now฀on฀to฀a฀high-altitude฀look฀at฀the฀GNU/Linux฀operating฀system฀architecture.฀You฀ can฀think฀about฀an฀operating฀system฀from฀two฀levels.฀ buffer a฀region฀of฀memory฀used฀ to฀temporarily฀hold฀ data฀while฀it฀is฀being฀ moved฀from฀one฀place฀ to฀another

At฀the฀top฀is฀the฀user,฀or฀application,฀space.฀This฀is฀where฀the฀user฀applications฀are฀ executed.฀Below฀the฀user฀space฀is฀the฀kernel฀space.฀Here,฀the฀Linux฀kernel฀exists. There฀ is฀ also฀ the฀ GNU฀ C฀ Library฀ (glibc).฀ This฀ provides฀ the฀ system฀ call฀ interface฀ that฀฀ connects฀to฀the฀kernel฀and฀provides฀the฀mechanism฀to฀transition฀between฀the฀user-space฀ application฀and฀the฀kernel.฀This฀is฀important฀because฀the฀kernel฀and฀user฀application฀฀ occupy฀different฀protected฀address฀spaces.฀And฀while฀each฀user-space฀process฀occupies฀ its฀own฀virtual฀address฀space,฀the฀kernel฀occupies฀a฀single฀address฀space.฀For฀more฀ information,฀see฀the฀links฀in฀the฀resources฀section. The฀Linux฀kernel฀can฀be฀further฀divided฀into฀three฀gross฀levels.฀At฀the฀top฀is฀the฀system฀ call฀interface,฀which฀implements฀the฀basic฀functions฀such฀as฀read฀and฀write.฀Below฀the฀ system฀call฀interface฀is฀the฀kernel฀code,฀which฀can฀be฀more฀accurately฀defined฀as฀the฀ architecture-independent฀kernel฀code.฀This฀code฀is฀common฀to฀all฀of฀the฀processor฀architectures฀supported฀by฀Linux.฀Below฀this฀is฀the฀architecture-dependent฀code,฀which฀ forms฀what฀is฀more฀commonly฀called฀a฀BSP฀(Board฀Support฀Package).฀This฀code฀serves฀ as฀the฀processor฀and฀platform-specific฀code฀for฀the฀given฀architecture.

Properties of the Linux kernel VFS(Virtual฀File฀System)

When฀ discussing฀ the฀ architecture฀ of฀ a฀ large฀ and฀ complex฀ system,฀ you฀ can฀ view฀ the฀฀

an฀abstraction฀layer฀

system฀ from฀ many฀ perspectives.฀ One฀ goal฀ of฀ an฀ architectural฀ decomposition฀ is฀ to฀฀

on฀top฀of฀a฀more฀concrete฀ file฀system฀

provide฀a฀way฀to฀understand฀the฀source฀better฀and฀that’s฀what฀we’ll฀do฀here. The฀Linux฀kernel฀implements฀a฀number฀of฀important฀architectural฀attributes.฀At฀a฀high฀ level,฀and฀at฀lower฀levels,฀the฀kernel฀is฀layered฀into฀a฀number฀of฀distinct฀subsystems.฀ Linux฀can฀also฀be฀considered฀monolithic฀because฀it฀lumps฀all฀of฀the฀basic฀services฀into฀ the฀kernel.฀This฀differs฀from฀a฀microkernel฀architecture,฀where฀the฀kernel฀provides฀ basic฀services฀such฀as฀communication,฀I/O,฀and฀memory฀and฀process฀management,฀ and฀more฀specific฀services฀are฀plugged฀in฀to฀the฀microkernel฀layer.฀Each฀has฀its฀own฀ advantages,฀but฀I’ll฀steer฀clear฀of฀that฀debate. Over฀time,฀the฀Linux฀kernel฀has฀become฀efficient฀in฀terms฀of฀both฀memory฀and฀CPU฀

usage,฀as฀well฀as฀extremely฀stable.฀But฀the฀most฀interesting฀aspect฀of฀Linux,฀given฀its฀

English++ size฀and฀complexity,฀is฀its฀portability.฀Linux฀can฀be฀compiled฀to฀run฀on฀a฀huge฀number฀ of฀processors฀and฀platforms฀with฀different฀architectural฀constraints฀and฀needs.฀One฀ example฀is฀the฀ability฀of฀Linux฀to฀run฀on฀a฀process฀with฀a฀memory฀management฀unit฀ (MMU),฀as฀well฀as฀those฀that฀provide฀no฀MMU.฀The฀uClinux฀port฀of฀the฀Linux฀kernel฀ provides฀for฀non-MMU฀support.฀See฀the฀resources฀section฀for฀more฀details.

Major subsystems of the Linux kernel Now฀let’s฀look฀at฀some฀of฀the฀major฀components฀of฀the฀Linux฀kernel฀using฀the฀breakdown.

System call interface The฀SCI฀is฀a฀thin฀layer฀that฀provides฀the฀means฀to฀perform฀function฀calls฀from฀user฀

Linux฀kernel

space฀ into฀ the฀ kernel.฀ As฀ discussed฀ previously,฀ this฀ interface฀ can฀ be฀ architecture฀฀

Unix-like

dependent,฀even฀within฀the฀same฀processor฀family.฀The฀SCI฀is฀actually฀an฀interesting฀฀

฀operating฀system฀kernel฀

function-call฀ multiplexing฀ and฀ demultiplexing฀ service.฀ You฀ can฀ find฀ the฀ SCI฀฀ implementation฀ in฀ ./linux/kernel,฀ as฀ well฀ as฀ architecture-dependent฀ portions฀ in฀฀ ./linux/arch.฀More฀details฀for฀this฀component฀are฀available฀in฀the฀resources฀section.

Process management Process฀management฀is฀focused฀on฀the฀execution฀of฀processes.฀In฀the฀kernel,฀these฀ are฀called฀threads฀and฀represent฀an฀individual฀virtualization฀of฀the฀processor฀(thread฀ code,฀data,฀stack,฀and฀CPU฀registers).฀In฀user฀space,฀the฀term฀process฀is฀typically฀used,฀ though฀the฀Linux฀implementation฀does฀not฀separate฀the฀two฀concepts฀(processes฀and฀ threads).฀The฀kernel฀provides฀an฀application฀program฀interface฀(API)฀through฀the฀SCI฀ to฀create฀a฀new฀process฀(fork,฀exec,฀or฀Portable฀Operating฀System฀Interface฀[POSIX]฀

kernel

functions),฀ stop฀ a฀ process฀ (kill,฀ exit),฀ and฀ communicate฀ and฀ synchronize฀ between฀

the฀central฀component฀

them฀(signal,฀or฀POSIX฀mechanisms).

of฀most฀computer฀

Also฀ in฀ process฀ management฀ there฀ is฀ a฀ need฀ to฀ share฀ the฀ CPU฀ between฀ the฀ active฀ threads.฀The฀kernel฀implements฀a฀novel฀scheduling฀algorithm฀that฀operates฀in฀constant฀ time,฀regardless฀of฀the฀number฀of฀threads฀vying฀for฀the฀CPU.฀This฀is฀called฀the฀O(1)฀ scheduler,฀denoting฀that฀the฀same฀amount฀of฀time฀is฀taken฀to฀schedule฀one฀thread฀as฀ it฀is฀to฀schedule฀many.฀The฀O(1)฀scheduler฀also฀supports฀multiple฀processors฀(called฀ Symmetric฀MultiProcessing,฀or฀SMP).฀You฀can฀find฀the฀process฀management฀sources฀ in฀./linux/kernel฀and฀architecture-dependent฀sources฀in฀./linux/arch).฀You฀can฀learn฀

operating฀systems฀(OS).฀ Its฀functions฀include฀ managing฀the฀system’s฀ resources฀ (the฀communication฀ between฀hardware฀and฀ software฀components

more฀about฀this฀algorithm฀in฀the฀resources฀section.

Memory management Another฀important฀resource฀that’s฀managed฀by฀the฀kernel฀is฀memory.฀For฀efficiency,฀ given฀the฀way฀that฀the฀hardware฀manages฀virtual฀memory,฀memory฀is฀managed฀in฀

English++ Minix

what฀are฀called฀pages฀(4KB฀in฀size฀for฀most฀architectures).฀Linux฀includes฀the฀means฀

free/open฀source,฀Unix-like฀

to฀manage฀the฀available฀memory,฀as฀well฀as฀the฀hardware฀mechanisms฀for฀physical฀

operating฀system฀(OS)฀ based฀on฀a฀microkernel฀ architecture฀

and฀virtual฀mappings. But฀memory฀management฀is฀much฀more฀than฀managing฀4KB฀buffers.฀Linux฀provides฀ abstractions฀over฀4KB฀buffers,฀such฀as฀the฀slab฀allocator.฀This฀memory฀management฀ scheme฀uses฀4KB฀buffers฀as฀its฀base,฀but฀then฀allocates฀structures฀from฀within,฀keeping฀ track฀of฀which฀pages฀are฀full,฀partially฀used,฀and฀empty.฀This฀allows฀the฀scheme฀to฀ dynamically฀grow฀and฀shrink฀based฀on฀the฀needs฀of฀the฀greater฀system. Supporting฀multiple฀users฀of฀memory,฀there฀are฀times฀when฀the฀available฀memory฀ can฀be฀exhausted.฀For฀this฀reason,฀pages฀can฀be฀moved฀out฀of฀memory฀and฀onto฀the฀ disk.฀This฀process฀is฀called฀swapping฀because฀the฀pages฀are฀swapped฀from฀memory฀ onto฀the฀hard฀disk.฀You฀can฀find฀the฀memory฀management฀sources฀in฀./linux/mm.

Virtual ﬁle system The฀virtual฀file฀system฀(VFS)฀is฀an฀interesting฀aspect฀of฀the฀Linux฀kernel฀because฀it฀ provides฀a฀common฀interface฀abstraction฀for฀file฀systems.฀The฀VFS฀provides฀a฀switching฀ layer฀between฀the฀SCI฀and฀the฀file฀systems฀supported฀by฀the฀kernel.฀ At฀the฀top฀of฀the฀VFS฀is฀a฀common฀API฀abstraction฀of฀functions฀such฀as฀open,฀close,฀ read,฀and฀write.฀At฀the฀bottom฀of฀the฀VFS฀are฀the฀file฀system฀abstractions฀that฀define฀ how฀the฀upper-layer฀functions฀are฀implemented.฀These฀are฀plug-ins฀for฀the฀given฀file฀ system฀(of฀which฀over฀50฀exist).฀You฀can฀find฀the฀file฀system฀sources฀in฀./linux/fs. GPL฀

Below฀the฀file฀system฀layer฀is฀the฀buffer฀cache,฀which฀provides฀a฀common฀set฀of฀functions฀

a฀widely฀used฀

to฀the฀file฀system฀layer฀(independent฀of฀any฀particular฀file฀system).฀This฀caching฀layer฀

free฀software฀license,฀

optimizes฀access฀to฀the฀physical฀devices฀by฀keeping฀data฀around฀for฀a฀short฀time฀(or฀

originally฀written฀by฀

speculatively฀read฀ahead฀so฀that฀the฀data฀is฀available฀when฀needed).฀Below฀the฀buffer฀

Richard฀Stallman฀for฀the฀

cache฀are฀the฀device฀drivers,฀which฀implement฀the฀interface฀for฀the฀particular฀physical฀฀

GNU฀project฀

device.

Network stack The฀network฀stack,฀by฀design,฀follows฀a฀layered฀architecture฀modeled฀after฀the฀protocols฀ themselves.฀Recall฀that฀the฀Internet฀Protocol฀(IP)฀is฀the฀core฀network฀layer฀protocol฀that฀ sits฀below฀the฀transport฀protocol฀(most฀commonly฀the฀Transmission฀Control฀Protocol,฀ or฀TCP).฀Above฀TCP฀is฀the฀sockets฀layer,฀which฀is฀invoked฀through฀the฀SCI. The฀sockets฀layer฀is฀the฀standard฀API฀to฀the฀networking฀subsystem฀and฀provides฀a฀user฀ interface฀ to฀ a฀ variety฀ of฀ networking฀ protocols.฀ From฀ raw฀ frame฀ access฀ to฀ IP฀ protocol฀

data฀units฀(PDUs)฀and฀up฀to฀TCP฀and฀the฀User฀Datagram฀Protocol฀(UDP),฀the฀sockets฀

English++ layer฀ provides฀a฀ standardized฀way฀ to฀ manage฀connections฀and฀ move฀ data฀between฀ endpoints.฀You฀can฀find฀the฀networking฀sources฀in฀the฀kernel฀at฀./linux/net.

Device drivers The฀vast฀majority฀of฀the฀source฀code฀in฀the฀Linux฀kernel฀exists฀in฀device฀drivers฀that฀ make฀a฀particular฀hardware฀device฀usable.฀The฀Linux฀source฀tree฀provides฀a฀drivers฀ subdirectory฀that฀is฀further฀divided฀by฀the฀various฀devices฀that฀are฀supported,฀such฀as฀ Bluetooth,฀I2C,฀serial,฀and฀so฀on.฀You฀can฀find฀the฀device฀driver฀sources฀in฀./linux/drivers.

Architecture-dependent code While฀much฀of฀Linux฀is฀independent฀of฀the฀architecture฀on฀which฀it฀runs,฀there฀are฀

GNU

elements฀that฀must฀consider฀the฀architecture฀for฀normal฀operation฀and฀for฀efficiency.฀

a฀computer฀operating

The฀/linux/arch฀subdirectory฀defines฀the฀architecture-dependent฀portion฀of฀the฀kernel฀

system฀composed฀

source฀contained฀in฀a฀number฀of฀subdirectories฀that฀are฀specific฀to฀the฀architecture฀

entirely฀of฀free฀software,฀

(collectively฀forming฀the฀BSP).฀For฀a฀typical฀desktop,฀the฀i386฀directory฀is฀used.฀Each฀

initiated฀in฀1984฀

architecture฀ subdirectory฀ contains฀ a฀ number฀ of฀ other฀ subdirectories฀ that฀ focus฀ on฀ a฀

by฀Richard฀Stallman฀

particular฀aspect฀of฀the฀kernel,฀such฀as฀boot,฀kernel,฀memory฀management,฀and฀others.฀ You฀can฀find฀the฀architecture-dependent฀code฀in฀./linux/arch.

Interesting features of the Linux kernel If฀the฀portability฀and฀efficiency฀of฀the฀Linux฀kernel฀weren’t฀enough,฀it฀provides฀some฀ other฀features฀that฀could฀not฀be฀classified฀in฀the฀previous฀decomposition. Linux,฀being฀a฀production฀operating฀system฀and฀open฀source,฀is฀a฀great฀test฀bed฀for฀ new฀protocols฀and฀advancements฀of฀those฀protocols.฀Linux฀supports฀a฀large฀number฀of฀ networking฀protocols,฀including฀the฀typical฀TCP/IP,฀and฀also฀extension฀for฀high-speed฀ networking฀(greater฀than฀1฀Gigabit฀Ethernet฀[GbE]฀and฀10฀GbE).฀Linux฀also฀supports฀ protocols฀such฀as฀the฀Stream฀Control฀Transmission฀Protocol฀(SCTP),฀which฀provides฀ many฀advanced฀features฀above฀TCP฀(as฀a฀replacement฀transport฀level฀protocol). Linux฀ is฀ also฀ a฀ dynamic฀ kernel,฀ supporting฀ the฀ addition฀ and฀ removal฀ of฀ software฀ components฀on฀the฀fly.฀These฀are฀called฀dynamically฀loadable฀kernel฀modules,฀and฀ they฀can฀be฀inserted฀at฀boot฀when฀they’re฀needed฀(when฀a฀particular฀device฀is฀found฀ requiring฀the฀module)฀or฀at฀any฀time฀by฀the฀user. A฀recent฀advancement฀of฀Linux฀is฀its฀use฀as฀an฀operating฀system฀for฀other฀operating฀ systems฀(called฀a฀hypervisor).฀Recently,฀a฀modification฀to฀the฀kernel฀was฀made฀called฀ the฀Kernel-based฀Virtual฀Machine฀(KVM).฀This฀modification฀enabled฀a฀new฀interface฀ to฀ user฀ space฀ that฀ allows฀ other฀ operating฀ systems฀ to฀ run฀ above฀ the฀ KVM-enabled฀ kernel.฀In฀addition฀to฀running฀another฀instance฀of฀Linux,฀Microsoft®฀Windows®฀can฀

English++ also฀be฀virtualized.฀The฀only฀constraint฀is฀that฀the฀underlying฀processor฀must฀support฀ the฀new฀virtualization฀instructions.฀See฀the฀resource฀section฀for฀more฀information.

Going further This฀article฀just฀scratched฀the฀surface฀of฀the฀Linux฀kernel฀architecture฀and฀its฀features฀ and฀capabilities.฀You฀can฀check฀out฀the฀Documentation฀directory฀that฀is฀provided฀in฀ every฀Linux฀distribution฀for฀detailed฀information฀about฀the฀contents฀of฀the฀kernel.฀

Resources buffer฀cache

•฀ The฀ GNU฀ site฀ (http://www.gnu.org/licenses)฀ describes฀ the฀ GNU฀ GPL฀ that฀ covers฀

฀a฀collection฀of฀

the฀Linux฀kernel฀and฀most฀useful฀applications฀provided฀with฀it.฀Also฀described฀is฀

data฀duplicating฀

a฀less฀restrictive฀form฀of฀the฀GPL฀called฀the฀Lesser฀GPL฀(LGPL).

original฀values฀stored฀

•฀ UNIX฀ (http://en.wikipedia.org/wiki/Unics),฀ MINIX฀ (http://en.wikipedia.org/wiki/

elsewhere฀or฀computed฀

Minix)฀and฀Linux฀(http://en.wikipedia.org/wiki/Linux)฀are฀covered฀in฀Wikipedia,฀

earlier,฀where฀the฀original฀

along฀with฀a฀detailed฀family฀tree฀of฀the฀operating฀systems.

data฀is฀expensive฀to฀fetch฀

•฀ The฀GNU฀C฀Library฀(http://www.gnu.org/software/libc/),฀or฀glibc,฀is฀the฀implementation฀

(owing฀to฀longer฀access฀

of฀the฀standard฀C฀library.฀It’s฀used฀in฀the฀GNU/Linux฀operating฀system,฀as฀well฀as฀the฀

time)฀or฀to฀compute,฀

GNU/Hurd฀(http://directory.fsf.org/hurd.html)฀microkernel฀operating฀system.

compared฀to฀the฀cost฀of฀

•฀ uClinux฀ (http://www.uclinux.org/)฀ is฀ a฀ port฀ of฀ the฀ Linux฀ kernel฀ that฀ can฀ execute฀

reading฀the฀cache

on฀systems฀that฀lack฀an฀MMU.฀This฀allows฀the฀Linux฀kernel฀to฀run฀on฀very฀small฀฀ embedded฀platforms,฀such฀as฀the฀Motorola฀DragonBall฀processor฀used฀in฀the฀PalmPilot฀ ฀Personal฀Digital฀Assistants฀(PDAs). •฀ “Kernel฀ command฀ using฀ Linux฀ system฀ calls”฀ (http://www.ibm.com/developerworks/linux/library/l-system-calls/฀)฀(developerWorks,฀March฀2007)฀covers฀the฀SCI,฀ which฀ is฀ an฀ important฀ layer฀ in฀ the฀ Linux฀ kernel,฀ with฀ user-space฀ support฀ from฀ glibc฀that฀enables฀function฀calls฀between฀user฀space฀and฀the฀kernel. •฀ “Inside฀ the฀ Linux฀ scheduler”฀ (http://www.ibm.com/developerworks/linux/library/lscheduler/)฀(developerWorks,฀June฀2006)฀explores฀the฀new฀O(1)฀scheduler฀introduced฀ in฀Linux฀2.6฀that฀is฀efficient,฀scales฀with฀a฀large฀number฀of฀processes฀(threads),฀ and฀takes฀advantage฀of฀SMP฀systems. •฀ “Access฀the฀Linux฀kernel฀using฀the฀/proc฀filesystem”฀(http://www.ibm.com/developerworks/linux/library/l-proc.html)฀ (developerWorks,฀ March฀ 2006)฀ looks฀ at฀ the฀ /proc฀file฀system,฀which฀is฀a฀virtual฀file฀system฀that฀provides฀a฀novel฀way฀for฀userspace฀applications฀to฀communicate฀with฀the฀kernel.฀This฀article฀demonstrates฀/ proc,฀as฀well฀as฀loadable฀kernel฀modules. •฀ “Server฀ clinic:฀ Put฀ virtual฀ filesystems฀ to฀ work”฀ (http://www.ibm.com/developerworks/linux/library/l-sc12.html฀)฀(developerWorks,฀April฀2003)฀delves฀into฀the฀VFS฀ layer฀ that฀ allows฀ Linux฀ to฀ support฀ a฀ variety฀ of฀ different฀ file฀ systems฀ through฀ a฀

common฀ interface.฀ This฀ same฀ interface฀ is฀ also฀ used฀ for฀ other฀ types฀ of฀ devices,฀ such฀as฀sockets.

English++ •฀ “Inside฀ the฀ Linux฀ boot฀ process”฀ (http://www.ibm.com/developerworks/linux/library/฀ l-linuxboot/index.html)฀(developerWorks,฀May฀2006)฀examines฀the฀Linux฀boot฀process,฀฀ which฀ takes฀ care฀ of฀ bringing฀ up฀ a฀ Linux฀ system฀ and฀ is฀ the฀ same฀ basic฀ process฀ whether฀you’re฀booting฀from฀a฀hard฀disk,฀floppy,฀USB฀memory฀stick,฀or฀over฀the฀ network. •฀ “Linux฀ initial฀ RAM฀ disk฀ (initrd)฀ overview”฀ (http://www.ibm.com/developerworks/

Unix

linux/library/l-initrd.html)฀(developerWorks,฀July฀2006)฀inspects฀the฀initial฀RAM฀disk,฀

a฀computer฀operating฀

which฀isolates฀the฀boot฀process฀from฀the฀physical฀medium฀from฀which฀it’s฀booting.

system฀originally฀

•฀ “Better฀ networking฀ with฀ SCTP”฀ (http://www.ibm.com/developerworks/linux/฀

developed฀in฀1969฀

library/l-sctp/)฀(developerWorks,฀February฀2006)฀covers฀one฀of฀the฀most฀interesting฀

by฀a฀group฀of฀AT&T฀

networking฀protocols,฀Stream฀Control฀Transmission฀Protocol,฀which฀operates฀like฀

employees฀at฀Bell฀Labs฀

TCP฀but฀adds฀a฀number฀of฀useful฀features฀such฀as฀messaging,฀multi-homing,฀and฀

including฀Ken฀Thompson,฀

multi-streaming.฀Linux,฀like฀BSD,฀is฀a฀great฀operating฀system฀if฀you’re฀interested฀

Dennis฀Ritchie฀

in฀networking฀protocols.

and฀Douglas฀Ilroy

•฀ “Anatomy฀of฀the฀Linux฀slab฀allocator”฀(http://www.ibm.com/developerworks/linux/฀ library/l-linux-slab-allocator/)฀(developerWorks,฀May฀2007)฀covers฀one฀of฀the฀most฀฀ interesting฀ aspects฀ of฀ memory฀ management฀ in฀ Linux,฀ the฀ slab฀ allocator.฀ This฀ mechanism฀originated฀in฀SunOS,฀but฀it’s฀found฀a฀friendly฀home฀inside฀the฀Linux฀ kernel. •฀ “Virtual฀ Linux”฀ ฀ (http://www.ibm.com/developerworks/linux/library/l-linuxvirt/)฀ (developerWorks,฀ December฀ 2006)฀ shows฀ how฀ Linux฀ can฀ take฀ advantage฀ of฀฀ processors฀with฀virtualization฀capabilities. •฀ “Linux฀ and฀ symmetric฀ multiprocessing”฀ (http://www.ibm.com/developerworks/฀ library/l-linux-smp/)฀(developerWorks,฀March฀2007)฀discusses฀how฀Linux฀can฀also฀ take฀advantage฀of฀processors฀that฀offer฀chip-level฀multiprocessing. •฀ “Discover฀the฀Linux฀Kernel฀Virtual฀Machine”฀(http://www.ibm.com/developerworks/฀ linux/library/l-linux-kvm/)฀(developerWorks,฀April฀2007)฀covers฀the฀recent฀introduction฀ of฀virtualization฀into฀the฀kernel,฀which฀turns฀the฀Linux฀kernel฀into฀a฀hypervisor฀for฀ other฀virtualized฀operating฀systems. •฀ Check฀out฀Tim’s฀book฀GNU/Linux฀Application฀Programming฀(http://www.charlesriver.฀ com/Books/BookDetail.aspx?productID=91525)฀for฀more฀information฀on฀programming฀ Linux฀in฀user฀space. •฀ In฀the฀developerWorks฀Linux฀zone฀(http://www.ibm.com/developerworks/linux/),฀ find฀more฀resources฀for฀Linux฀developers,฀including฀Linux฀tutorials฀(http://www.ibm. com/developerworks/views/linux/libraryview.jsp?type_by=Tutorials),฀as฀well฀as฀our฀ readers’฀favorite฀Linux฀articles฀and฀tutorials฀(http://www.ibm.com/developerworks/฀ linux/library/l-top-10.html)฀over฀the฀last฀month. •฀ Stay฀current฀with฀developerWorks฀technical฀events฀and฀Webcasts฀(http://www.ibm. com/developerworks/offers/techbriefings/?S_TACT=105AGX03&S_CMP=art).

English++

Exercises Pre-reading exercises 1.฀ What฀are฀the฀most฀popular฀operating฀systems? •฀ Windows,฀Linux,฀Mac฀OS 2.฀ What฀are฀the฀advantages฀of฀Linux? •฀ GPL฀license฀(free฀to฀use) •฀ stability •฀ security 3.฀ What฀are฀the฀disadvantages฀of฀Linux? •฀ difficult฀in฀use •฀ some฀software฀isn’t฀available฀in฀a฀Linux฀version

Comprehension questions 1.฀ Name฀a฀few฀of฀the฀earliest฀operating฀systems. •฀ GMOS,฀FMS. 2.฀ Who฀created฀MINIX? •฀ Andrew฀Tanenbaum 3.฀ How฀many฀lines฀of฀code฀does฀the฀Linux฀kernel฀have฀now? •฀ over฀6฀million 4.฀ What฀are฀the฀advantages฀of฀Linux฀adoption฀of฀the฀GPL? •฀ protection฀from฀commercial฀exploitation •฀ benefits฀from฀the฀user-space฀development •฀ various฀shell฀support 5.฀ Name฀the฀three฀gross฀levels฀of฀the฀Linux฀kernel. •฀ system฀call฀interface •฀ kernel฀code •฀ architecture-dependant฀code฀(BSP) 6.฀ What฀are฀the฀major฀components฀of฀the฀Linux฀kernel? •฀ System฀Call฀Interface •฀ Process฀Management •฀ Memory฀Management •฀ Virtual฀File฀System •฀ Network฀Stack •฀ Arch •฀ Device฀Drivers 7.฀ Describe฀in฀a฀few฀words฀what฀process฀management฀does? •฀ Process฀management฀is฀focused฀on฀the฀execution฀of฀processes.฀The฀kernel฀provides฀฀ an฀application฀program฀interface฀through฀the฀SCI฀to฀create฀a฀new฀process,฀stop฀a฀

process฀or฀communicate฀and฀synchronize฀between฀them.฀There฀is฀also฀a฀need฀to฀ share฀the฀CPU฀between฀the฀active฀threads฀in฀the฀process฀management.

English++ 8.฀ What฀could฀you฀do฀if฀you฀have฀Linux฀and฀you฀want฀to฀run฀a฀Windows฀program? •฀ find฀its฀Linux฀equivalent •฀ virtualize฀Microsoft฀Windows •฀ install฀Windows฀as฀a฀second฀system

Possible topics for discussion 1.฀ Which฀ operating฀ system,฀ Windows฀ or฀ Linux,฀ is฀ better฀ and฀ why?฀ What฀ is฀ your฀ opinion? 2.฀ Which฀ operating฀ system฀ architecture฀ is฀ better:฀ one฀ with฀ a฀ number฀ of฀ distinct฀฀ subsystems฀or฀one฀with฀a฀single฀microkernel? 3.฀ Is฀it฀better฀to฀build฀small฀kernels฀which฀are฀easy฀to฀understand฀or฀large฀ones฀with฀ all฀the฀necessary฀functions?฀

Possible difﬁculties The฀article฀can฀be฀hard฀to฀understand฀because฀of฀a฀big฀amount฀of฀฀words฀and฀phrases฀ from฀the฀area฀of฀IT.฀

English++

How to Stream Video over a Network or the Internet Damien Stolarz Number฀of฀words฀฀

1880

Computer฀science฀content฀฀

High

Math฀content฀฀

Low

English฀language฀complexity฀฀

Medium

Learning objectives •฀ to฀understand฀different฀kinds฀of฀transfer:฀radio,฀television,฀telephone,฀internet •฀ to฀recognize฀general฀differences฀in฀the฀data฀transfer฀of฀radio,฀television,฀telephone฀ and฀the฀Internet฀ •฀ to฀ understand฀ why฀ internet฀ video฀ streaming฀ is฀ vulnerable฀ to฀ delays,฀ and฀ why฀฀ delays฀do฀not฀affect฀radio,฀television฀and฀telephone

Sub-areas covered •฀ Computer฀networks฀ •฀ Transferring฀data฀through฀the฀Internet฀

Keywords •฀ streaming฀protocol฀-฀a฀set฀of฀rules฀to฀ensure฀that฀data฀will฀be฀supported฀in฀real฀ time •฀ network฀ protocol฀-฀a฀set฀of฀rules฀that฀set฀out฀how฀to฀establish฀communication฀ between฀two฀or฀more฀computers฀over฀the฀network฀ •฀ routing฀-฀the฀process฀of฀selecting฀paths฀in฀a฀network฀along฀which฀data฀can฀be฀sent฀ between฀computers฀(through฀the฀router) •฀ router฀-฀a฀network฀device฀that฀groups฀computers฀in฀the฀network฀and฀establishes฀ an฀area฀inside฀it฀ •฀ Internet฀-฀a฀global฀network฀connecting฀millions฀of฀computers฀ •฀ peering฀-฀the฀arrangement฀of฀traffic฀exchange฀between฀the฀Internet฀service฀providers฀ (ISPs).฀ •฀ Internet฀provider฀-฀a฀company฀that฀sells฀bandwidth฀and฀access฀to฀the฀Internet฀ •฀ bandwidth฀-฀฀the฀amount฀of฀data฀that฀can฀be฀transferred฀through฀a฀specific฀path฀in฀

the฀network฀usually฀expressed฀in฀kb/s฀[kilo฀bits฀per฀second]฀

English++ •฀ circuit฀switching฀network฀-฀a฀network฀in฀which฀computers฀establish฀a฀constant฀ bandwidth฀connection฀before฀they฀start฀to฀share฀any฀data฀ •฀ broadcast฀–฀the฀action฀of฀sending฀data฀by฀one฀computer฀in฀the฀network฀to฀all฀the฀ others฀that฀are฀available฀inside฀the฀network฀

Summary The฀ text,฀ divided฀ into฀ several฀ parts,฀ familiarises฀ the฀ reader฀ with฀ the฀ problem฀ of฀฀ receiving฀video฀data฀transferred฀through฀a฀network฀(especially฀the฀Internet).฀The฀author฀฀ outlines฀ the฀ methods฀ of฀ transferring฀ data฀ by฀ means฀ of฀ phone฀ lines,฀ radio฀ waves฀ and฀ television฀ wires.฀ He฀ explains฀ why฀ the฀ transfer฀ of฀ data฀ is฀ not฀ problematic฀ in฀ those฀cases,฀while฀in฀computer฀networks฀it฀poses฀a฀real฀problem.฀After฀giving฀a฀brief฀฀ account฀of฀the฀basis฀of฀the฀global฀network,฀the฀author฀describes฀the฀transfer฀of฀video฀data฀ through฀the฀Internet.฀The฀article฀gives฀detailed฀descriptions฀of฀methods฀of฀transferring฀ that฀type฀of฀data฀and฀lists฀reasons฀why฀receiving฀them฀can฀be฀a฀problem.฀ Tekst฀przybliża฀czytelnikowi฀problem฀odbioru฀danych฀wideo฀transportowanych฀przez฀ sieć,฀zwłaszcza฀przez฀Internet.฀By฀naświetlić฀problem฀przesyłania฀tego฀typu฀danych฀ autor฀artykułu฀opisuje฀sposób฀transferu฀danych฀przez฀linię฀telefoniczną,฀fale฀radiowe฀ oraz฀sieć฀telewizyjną.฀Zaznacza฀on฀powody,฀dla฀których฀wymienione฀rozwiązania฀nie฀ nastręczają฀problemów฀typowych฀dla฀sieci฀komputerowych.฀Artykuł฀przedstawia฀także฀ zarys฀funkcjonowania฀intersieci฀oraz฀opisuje฀główne฀powody,฀dla฀których฀przesyłanie฀ i฀właściwe฀odbieranie฀tego฀typu฀danych฀jest฀problematyczne.฀

Pre-reading exercises 1.฀ ฀What฀do฀you฀know฀about฀the฀history฀of฀TV฀and฀radio?฀ 2.฀ Do฀you฀know฀the฀origins฀of฀the฀Internet?฀ 3.฀ ฀Which฀kind฀of฀media฀do฀you฀find฀important฀and฀valuable?฀ 4.฀ Can฀you฀explain฀how฀connections฀are฀made฀between฀‘users’฀of฀radio,฀TV฀and฀the฀ Internet?

English++

How to Stream Video over a Network or the Internet ฀How

Video Travels Across the Internet

As฀noted฀in฀earlier฀chapters฀and฀as฀any฀end฀user฀would฀be฀quick฀to฀point฀out,฀viewing฀ streaming฀video฀over฀the฀Internet฀is฀hardly฀a฀seamless฀experience.฀Streaming฀video฀ suffers฀from฀hiccups,฀delays,฀drop-outs,฀skips,฀and฀connection฀loss.฀In฀this฀section,฀ we฀explain฀how฀the฀Internet฀moves฀data฀and฀how฀this฀affects฀video฀playback.฀ It’s฀sometimes฀hard฀to฀understand฀why฀the฀Internet฀has฀trouble฀moving฀audio฀and฀ video฀when฀radio,฀television,฀and฀telephones฀do฀it฀fairly฀well฀and฀have฀existed฀for฀ almost฀100฀years.฀So฀first฀let’s฀look฀at฀the฀mechanisms฀of฀these฀traditional฀media.฀

Radio router฀

Radio฀works฀simply฀because฀a฀single฀tower฀broadcasts฀the฀same฀signal฀to฀many฀receivers.฀฀

a฀network฀device฀

Everyone฀listens฀to฀the฀same฀thing฀at฀the฀same฀time.฀All฀the฀stations฀are฀available฀at฀any฀

that฀groups฀computers฀

time;฀you฀simply฀have฀to฀tune฀into฀a฀different฀frequency฀signal.฀The฀main฀barriers฀to฀

in฀the฀network฀

radio฀transmission฀are฀distance;฀physical฀barriers฀such฀as฀hills,฀buildings,฀and฀tunnels฀

and฀establishes฀an฀area฀

that฀block฀the฀signal;฀and฀interference฀between฀two฀strong฀signals฀near฀each฀other฀on฀

inside฀it฀

the฀dial.฀In฀terms฀of฀communication,฀radio฀is฀a฀one-way฀broadcast฀transmission.฀

Television Television฀ works฀ much฀ like฀ radio,฀ except฀ that฀ television฀ broadcasting฀ is฀ organized฀ into฀national฀networks.฀The฀same฀program฀is฀delivered฀to฀television฀receivers฀around฀ the฀country฀by฀broadcasting฀the฀originating฀signal฀to฀branch฀offices,฀which฀broadcasts฀ it฀out฀from฀towers,฀out฀through฀cable฀companies,฀or฀to฀people฀with฀satellite฀dishes.฀In฀ any฀case,฀the฀same฀signal฀is฀sent฀to฀everyone฀at฀the฀same฀time฀-฀a฀one-way฀broadcast.฀ ฀ All฀ the฀ channels฀ are฀ available฀ at฀ any฀ time;฀ there฀ is฀ no฀ noticeable฀ delay฀ caused฀ by฀ changing฀channels.฀The฀main฀barriers฀to฀television฀reception฀are฀bent฀or฀frayed฀cables,฀

badly฀ aimed฀ antennas฀ or฀ dishes,฀ physical฀ barriers฀ as฀ in฀ radio,฀ and฀ interference฀ of฀฀ stations฀with฀each฀other.฀

English++ Telephone Telephone฀ calls฀ use฀ many฀ of฀ the฀ same฀ wires฀ used฀ by฀ the฀ Internet.฀ The฀ telephone฀ central฀ office฀ maintains฀ devices฀ called฀ switches฀ (automated฀ versions฀ of฀ the฀ classic฀฀ telephone฀ switchboard)฀ that฀ are฀ used฀ to฀ connect฀ the฀ call฀ to฀ the฀ next฀ location.฀฀ Telephone฀calls฀create฀a฀two-way฀circuit฀all฀the฀way฀from฀caller฀to฀receiver.฀The฀message฀฀ “All฀ circuits฀ are฀ busy”฀ -฀ usually฀ heard฀ only฀ during฀ disasters฀ or฀ radio฀ call-in฀ concert฀ ticket฀giveaways฀-฀means฀the฀switch฀does฀not฀have฀any฀more฀slots฀in฀which฀to฀carry฀ this฀call.฀The฀main฀barriers฀to฀telephone฀transmission฀are฀found฀at฀the฀beginning฀of฀

routing

the฀call—฀if฀there฀are฀not฀enough฀circuits฀to฀place฀the฀call.฀While฀a฀call฀is฀in฀progress,฀

฀the฀process฀of฀selecting฀

the฀entire฀route฀between฀the฀caller฀and฀recipient฀is฀reserved฀for฀their฀use฀only,฀even฀if฀

paths฀in฀a฀network฀

there฀is฀silence฀and฀no฀one฀is฀talking.฀Telephones฀use฀what฀is฀called฀a฀circuit-switched฀

along฀which฀data฀

connection.฀

can฀be฀sent฀between ฀computers

Internet Basics

฀(through฀the฀router)

The฀ path฀ from฀ a฀ website฀ to฀ a฀ web฀ browser฀ is฀ different฀ than฀ these฀ other฀ systems.฀฀ Conceptually,฀it฀is฀similar฀to฀the฀telephone฀conversation:฀It’s฀a฀two-way฀conversation฀in฀ which฀the฀browser฀asks฀for฀a฀document฀and฀the฀server฀sends฀it.฀Unlike฀the฀telephone฀ call,฀however,฀there฀is฀no฀reserved฀circuit.฀Data,฀in฀the฀form฀of฀requests฀and฀responses,฀ are฀organized฀into฀chunks฀called฀packets฀and฀sent฀between฀the฀requesting฀web฀browser฀ and฀the฀web฀server.฀ In฀between฀the฀requester฀and฀the฀server฀is฀a฀series฀of฀routers.฀These฀machines฀route฀

bandwidth

traffic฀between฀different฀smaller฀networks.฀Each฀time฀a฀packet฀crosses฀the฀boundary฀

the฀amount฀of฀data฀

from฀one฀ISP฀to฀another,฀or฀from฀one฀kind฀of฀network฀to฀another,฀it฀goes฀through฀a฀

that฀can฀be฀transferred฀

router.฀The฀packets฀“hop”฀from฀router฀to฀router฀like฀a฀bucket฀brigade.฀This฀type฀of฀data฀

through฀a฀specific฀path฀

transmission฀is฀called฀packet฀switching,฀instead฀of฀circuit฀switching.฀Internet฀packet฀

in฀the฀network

switching฀has฀some฀attributes฀that฀make฀it฀reliable฀and฀unreliable฀at฀the฀same฀time.฀

(usually฀expressed฀in฀kb/s฀

The฀Internet฀is฀an฀extremely฀heterogeneous฀network,฀consisting฀of฀several฀different฀

[kilo฀bits฀per฀second])฀

kinds฀of฀networks฀and฀ways฀of฀connecting฀networks฀to฀the฀Internet,฀as฀described฀in฀ the฀next฀few฀sections.฀

The Internet Backbone The฀Internet฀backbone฀(as฀much฀as฀a฀large,฀shapeless฀and฀ever-shifting฀cloud฀of฀networks฀ can฀have฀a฀backbone!)฀consists฀of฀long-haul฀connections฀that฀carry฀large฀volumes฀of฀ Internet฀traffic฀(packets)฀across฀and฀between฀continents.฀

English++ Public Exchange Points Public฀exchange฀points฀exist฀at฀various฀points฀on฀continents฀and฀are฀the฀major฀nerve฀ ฀

฀

streaming฀protocol

centers฀ where฀ many฀ regional฀ private฀ networks,฀ Internet฀ providers,฀ corporations,฀

a฀set฀of฀rules฀to฀ensure฀

schools,฀ and฀ government฀ divisions—large฀ and฀ small—converge฀ to฀ exchange฀ traffic฀

that฀data฀will฀be฀

destined฀for฀other฀points฀on฀the฀Internet.฀You฀can฀compare฀these฀centers฀to฀major฀

supported฀in฀real฀time

public฀airports,฀where฀international฀and฀domestic฀flights฀arrive฀24฀hours฀a฀day฀and฀

network฀protocol฀

trade฀passengers฀from฀different฀airlines.฀

-฀a฀set฀of฀rules฀that฀set฀out฀ how฀to฀establish฀ communication฀between฀ two฀or฀more฀computers฀ over฀the฀network฀

Peering The฀process฀of฀connecting฀a฀network฀to฀the฀Internet฀at฀one฀of฀these฀exchange฀points฀ is฀called฀peering,฀and฀connecting฀to฀the฀backbone฀this฀way฀makes฀one฀a฀Tier-1฀Internet฀฀ provider.฀ ISPs฀ that฀ rent฀ their฀ connection฀ from฀ a฀ Tier-1฀ provider฀ are฀ called฀ Tier-2฀฀ providers,฀ and฀ so฀ on.฀ The฀ policies,฀ prices,฀ and฀ agreements฀ that฀ cover฀ how฀ data฀ is฀ treated฀on฀these฀connections฀are฀as฀numerous฀as฀there฀are฀companies฀involved.฀This฀ is฀the฀first฀source฀of฀variability฀for฀our฀packet฀switching.฀

Private Peering Peering฀is฀simply฀two฀networks฀connecting฀to฀each฀other฀with฀routers.฀Public฀peering฀ occurs฀at฀large฀exchange฀points,฀but฀any฀two฀networks฀that฀find฀a฀lot฀of฀traffic฀flowing฀ between฀them฀can฀choose฀to฀create฀a฀direct฀private฀link฀between฀the฀networks฀(called฀ private฀peering).฀This฀reduces฀the฀cost฀of฀access฀through฀a฀public฀exchange฀point฀or฀other฀ provider฀for฀all฀the฀bandwidth฀that฀travels฀between฀these฀two฀networks.฀It฀also฀decreases฀ the฀number฀of฀intermediate฀connections฀between฀the฀networks.฀For฀instance,฀when฀ several฀schools฀in฀the฀same฀organization฀link฀together,฀their฀inter-campus฀network฀ traffic฀does฀not฀have฀to฀go฀out฀to฀the฀Internet฀at฀large,฀and฀is฀often฀more฀reliable฀as฀a฀ result.฀In฀this฀scenario,฀though,฀each฀school฀has฀its฀own฀connection฀to฀the฀Internet.฀ What฀if฀one฀of฀the฀school’s฀Internet฀connections฀went฀down?฀Would฀it฀be฀fair฀to฀send฀ its฀ traffic฀ through฀ the฀ private฀ peering฀ connection฀ and฀ use฀ another฀ school’s฀ Internet฀ ฀

connection?฀The฀way฀these฀kinds฀of฀questions฀are฀answered฀and฀the฀internal฀policies฀in฀

circuit฀switching฀network฀฀

this฀regard฀are฀another฀contributing฀factor฀to฀the฀variability฀of฀Internet฀packet฀switching.฀

a฀network฀in฀which฀ computers฀establish฀ a฀constant฀bandwidth฀ connection฀before฀they฀ start฀to฀share฀any฀data฀

Internet Complexity As฀everything฀“goes฀digital,”฀the฀distinction฀between฀cable฀TV฀wires,฀telephone฀wires,฀ radio฀waves,฀and฀satellite฀transmission฀blurs.฀However,฀there฀are฀many฀ways฀to฀send฀ data฀over฀these฀media.฀Internet฀data฀transmission฀can฀be฀complicated,฀leading฀to฀a฀ variety฀of฀undesirable฀transmission฀characteristics.฀

English++ Packet Loss

peering

Circuit฀switching฀on฀the฀Internet฀is฀described฀as฀“best-effort,”฀meaning฀that฀one฀of฀

the฀arrangement฀

the฀routers฀along฀the฀way฀can฀lose฀a฀packet฀before฀it฀reaches฀its฀destination.฀In฀this฀

of฀traffic฀exchange฀

case,฀the฀sender฀or฀receiver฀must฀somehow฀note฀that฀the฀packet฀was฀lost฀(perhaps฀by฀

between฀the฀Internet฀

receiving฀the฀next฀packet฀and฀noting฀that฀it฀is฀out฀of฀context)฀and฀re-requesting฀the฀

service฀providers฀(ISPs).

lost฀packet.฀This฀mechanism฀is฀fairly฀reliable฀in฀that฀two฀machines฀will฀usually฀(and฀ eventually)฀figure฀out฀what฀went฀wrong฀and฀resend฀the฀missing฀packets.฀Packet฀loss฀ causes฀audio฀and฀video฀to฀pause฀if฀the฀packets฀are฀eventually฀resent,฀and฀it฀causes฀ video฀to฀pause,฀drop฀out,฀and฀skip฀if฀the฀packets฀are฀not฀resent฀at฀all.฀In฀our฀analogy฀ of฀a฀public฀exchange฀point฀being฀a฀major฀airport,฀if฀it’s฀a฀“foggy฀day”฀at฀that฀exchange,฀ the฀part฀of฀the฀Internet฀that฀goes฀through฀that฀exchange฀can฀be฀slowed฀down฀(called฀ a฀brownout)฀by฀the฀data฀that฀can’t฀“take฀off.”฀

Different Routes Not฀all฀packets฀in฀a฀file฀follow฀the฀same฀route฀to฀the฀destination฀computer.฀This฀is฀ not฀unlike฀the฀airline’s฀hub฀and฀spoke฀system:฀One฀packet฀might฀go฀“direct”฀from฀ San฀Francisco฀to฀Washington;฀others฀might฀“transfer”฀in฀Atlanta฀or฀Chicago฀to฀get฀to฀฀ Washington.฀ Contributing฀ to฀ this฀ issue฀ is฀ private฀ peering฀ and฀ the฀ variable฀ rules฀ and฀ costs฀ associated฀ with฀ all฀ the฀ choices฀ to฀ be฀ made.฀ Alternate฀ routes฀ can฀ be฀ excellent฀ when฀one฀path฀between฀two฀machines฀goes฀down฀and฀a฀packet฀can฀use฀another฀path.฀ It฀can฀also฀cause฀strange฀effects,฀such฀as฀when฀a฀packet฀is฀sent฀down฀a฀slow฀route,฀ is฀assumed฀lost,฀is฀resent฀-฀and฀then฀later฀reappears฀as฀a฀duplicate฀packet!฀Audio฀can฀ stutter฀and฀skip฀if฀duplicate฀packets฀are฀not฀detected฀and฀discarded.฀Also,฀some฀paths฀ travel฀far฀out฀of฀the฀way,฀hopping฀through฀many฀more฀routers฀than฀necessary฀and฀

broadcast the฀action฀of฀sending฀data฀ by฀one฀computer฀ in฀the฀network฀to฀ all฀the฀others฀ that฀are฀available฀ inside฀the฀network฀

causing฀large฀delays.฀The฀more฀“hops”฀or฀routers฀between฀two฀machines,฀the฀higher฀ the฀chance฀of฀unexpected฀delays.฀

Delay (Latency) Because฀of฀the฀many฀different฀routers฀a฀packet฀has฀to฀go฀through฀to฀get฀from฀sender฀ to฀receiver฀and฀because฀there฀are฀no฀reserved฀circuits฀on฀the฀Internet฀like฀there฀are฀for฀ telephones,฀the฀delay฀of฀any฀given฀packet฀can฀be฀high฀or฀low,฀or฀change฀unexpectedly.฀ This฀can฀be฀caused฀by฀a฀variety฀of฀factors฀such฀as:฀A฀router฀is฀too฀busy฀and฀can’t฀keep฀ up฀with฀traffic.฀A฀particular฀link฀between฀sender฀and฀receiver฀becomes฀saturated.฀A฀ link฀goes฀down,฀causing฀traffic฀to฀be฀rerouted฀to฀a฀different฀link.฀One฀or฀more฀routers฀ in฀ between฀ can’t฀ think฀ fast฀ enough.฀ A฀ firewall฀ looks฀ at฀ all฀ the฀ packets฀ for฀ viruses.฀ Delay฀is฀added฀due฀to฀the฀use฀of฀older฀technology,฀such฀as฀modems.฀Other฀downloads฀ on฀a฀pipe฀cause฀it฀to฀delay.฀Packets฀are฀lost,฀resulting฀in฀resends,฀and฀other฀packets฀ get฀bunched฀up฀behind฀them.฀These฀factors฀make฀predicting฀how฀long฀it฀will฀take฀to฀ get฀packets฀back฀from฀a฀server฀difficult.฀Because฀of฀varying฀latency,฀video฀can฀take฀a฀

English++ long฀time฀to฀start฀playing;฀fast-forward฀and฀rewind฀features฀can฀be฀slow฀and฀clunky;฀ and฀video฀can฀pause,฀stutter,฀skip,฀and฀stop฀altogether.฀Bandwidth฀Variation฀Another฀ factor฀on฀the฀Internet฀is฀the฀variability฀of฀bandwidth.฀With฀broadcast฀media,฀such฀as฀ Internet฀provider

radio฀or฀television,฀as฀well฀as฀telephones,฀the฀bandwidth฀is฀always฀the฀same฀-฀just฀

a฀company฀that฀sells฀

enough฀to฀carry฀the฀channel฀or฀the฀conversation.฀There฀is฀no฀wasted฀bandwidth;฀the฀

bandwidth฀and฀access฀

size฀of฀the฀channel฀is฀just฀enough฀to฀carry฀the฀data.฀It฀was฀designed฀to฀be฀that฀way.฀

to฀the฀Internet฀

Because฀the฀Internet฀is฀designed฀to฀allow฀different฀computers฀of฀different฀speeds฀and฀ different฀channel฀sizes฀communicate,฀it฀is฀possible฀to฀have฀bottlenecks,฀not฀just฀due฀ to฀traffic฀that฀the฀size฀of฀the฀channel฀varies฀from฀sender฀to฀receiver.฀The฀Internet฀link฀ for฀a฀major฀website’s฀hosting฀provider฀might฀be฀excellent.฀The฀links฀between฀the฀host’s฀ ISP฀ and฀ its฀ branch฀ in฀ a฀ particular฀ city฀ might฀ be฀ high-capacity.฀ However,฀ the฀ Internet฀ link฀provided฀by฀a฀small฀ISP฀to฀the฀end฀user฀might฀be฀very฀small฀due฀to฀oversubscription.฀If฀that฀Internet฀provider฀has฀incurred฀a฀good฀deal฀of฀customer฀growth฀without฀฀ upgrading฀its฀own฀connection฀to฀the฀Internet฀backbone,฀the฀potentially฀high-bandwidth฀ connection฀from฀the฀website฀host฀is฀lowered฀to฀the฀slowest฀intermediate฀link฀in฀the฀ chain.฀In฀other฀words,฀the฀bandwidth฀between฀a฀website฀and฀a฀client฀is฀no฀faster฀than฀ its฀slowest฀link.฀

NOTE Internet

Fundamentally,฀the฀Internet฀is฀far฀better฀suited฀for฀sending฀web฀pages฀than฀real-time฀

a฀global฀network฀

media฀ because฀ web฀ pages฀ are฀ far฀ smaller฀ and฀ far฀ less฀ sensitive฀ to฀ delays.฀ There฀ is฀

connecting฀millions฀

not฀much฀difference฀between฀a฀one-฀and฀two-second฀delay฀in฀getting฀a฀web฀page,฀but฀

of฀computers฀

a฀one-second฀pause฀in฀real-time฀video฀is฀unacceptable.฀The฀brute-force฀approach฀of฀ keeping฀the฀bit฀rate฀of฀the฀video฀far฀below฀the฀maximum฀bandwidth฀of฀the฀Internet฀ connection฀can฀be฀effective฀in฀getting฀Internet฀video฀to฀perform฀predictably.฀

English++

Exercises Pre-reading questions 1.฀What฀do฀you฀know฀about฀the฀history฀of฀TV฀and฀radio?฀ •฀ The฀first฀use฀of฀radio฀took฀place฀Franklin฀Institute฀in฀Philadelphia฀in฀February฀1893.฀It฀ was฀the฀demonstration฀of฀wireless฀telegraph.฀Transmission฀of฀voice฀was฀the฀invention฀฀ of฀the฀beginning฀of฀XX฀century.฀Development฀of฀TV฀was฀divided฀into฀two฀paths:฀ the฀mechanical฀and฀electrical฀and฀purely฀electrical.฀The฀first฀idea฀of฀construction฀฀ the฀TV฀(electromechanical)฀was฀abandoned฀about฀1925.฀Demonstration฀of฀first฀color฀ television฀display฀was฀given฀on฀August฀16,฀1944. 2.฀ Do฀you฀know฀the฀origins฀of฀the฀Internet?฀ •฀ The฀first฀idea฀of฀global฀network฀of฀computers฀was฀created฀by฀J.C.R.฀Licklider.฀He฀ moved฀to฀the฀Defense฀Advanced฀Research฀Projects฀Agency฀(DARPA)฀to฀develop฀it.฀ The฀first฀connection฀of฀two฀computers฀(by฀the฀phone฀line)฀took฀place฀in฀1965.฀The฀ first฀form฀of฀the฀Internet,฀called฀ARPANET,฀was฀brought฀online฀in฀1969.฀In฀those฀ time,฀ the฀ first฀ ideas฀ of฀ reliability฀ of฀ connections฀ (nowadays฀ included฀ in฀ many฀฀ protocols)฀was฀implemented฀into฀networks. 3.฀ ฀Which฀kind฀of฀media฀do฀you฀find฀important฀and฀valuable?฀ •฀ I฀find฀the฀Internet฀the฀most฀important฀and฀valuable฀kind฀of฀media.฀Any฀information฀ that฀can฀be฀found฀in฀other฀media฀(tv฀or฀radio)฀can฀also฀be฀found฀in฀the฀Internet. 4.฀ Can฀you฀explain฀how฀connections฀are฀made฀between฀‘users’฀of฀radio,฀TV฀and฀the฀ Internet? •฀ The฀radio฀waves฀are฀divided฀into฀frequency฀which฀enables฀the฀receivers฀to฀distinguish฀ the฀channels.฀The฀same฀way฀of฀transferring฀data฀in฀the฀wireless฀TV฀is฀used฀to฀receive฀ from฀broadcasting฀stations.฀When฀using฀cable฀connected฀TV฀receiver฀no฀division฀ of฀data฀stream฀is฀needed฀as฀one฀channel฀is฀received฀through฀the฀cable฀in฀time.฀In฀ the฀Internet฀every฀media฀is฀shared฀so฀protocols฀(describing฀the฀way฀the฀data฀is฀ transferred)฀need฀to฀provide฀effective฀way฀to฀avoid฀collisions฀of฀the฀packets.

Comprehension questions 1.฀ Can฀you฀point฀out฀the฀differences฀between฀TV,฀radio฀and฀the฀Internet฀in฀terms฀ of฀communication?฀ •฀ only฀broadcast฀communication฀(TV,฀Radio) •฀ each฀of฀nodes฀can฀be฀both฀sender฀and฀recipient฀(฀the฀Internet) •฀ information฀can฀be฀reviewed฀any฀time฀(the฀Internet)฀ 2.฀ Can฀you฀explain฀the฀process฀of฀establishing฀connections฀by฀telephone฀and฀on฀ the฀Internet?฀ •฀ Telephone฀calls฀use฀many฀of฀the฀same฀wires฀used฀by฀the฀Internet.฀The฀telephone฀ central฀office฀maintains฀devices฀called฀switches฀(automated฀versions฀of฀the฀classic฀฀ telephone฀ switchboard)฀ that฀ are฀ used฀ to฀ connect฀ the฀ call฀ to฀ the฀ next฀ location.฀฀

English++ Telephone฀ calls฀ create฀ a฀ two-way฀ circuit฀ all฀ the฀ way฀ from฀ caller฀ to฀ receiver.฀฀ The฀message฀“All฀circuits฀are฀busy”—usually฀heard฀only฀during฀disasters฀or฀radio฀฀ call-in฀ concert฀ ticket฀ giveaways—means฀ the฀ switch฀ does฀ not฀ have฀ any฀ more฀ slots฀ in฀ which฀ to฀ carry฀ this฀ call.฀ The฀ main฀ barriers฀ to฀ telephone฀ transmission฀ ฀are฀found฀at฀the฀beginning฀of฀the฀call—฀if฀there฀are฀not฀enough฀circuits฀to฀place฀ the฀call.฀While฀a฀call฀is฀in฀progress,฀the฀entire฀route฀between฀the฀caller฀and฀recipient฀฀ is฀ reserved฀ for฀ their฀ use฀ only,฀ even฀ if฀ there฀ is฀ silence฀ and฀ no฀ one฀ is฀ talking.฀฀ Telephones฀use฀what฀is฀called฀a฀circuit-switched฀connection. 3.฀ What฀is฀the฀idea฀of฀“packet฀communication”?฀ •฀ The฀ path฀ from฀ a฀ website฀ to฀ a฀ web฀ browser฀ is฀ different฀ than฀ these฀ other฀ systems.฀ Conceptually,฀it฀is฀similar฀to฀the฀telephone฀conversation:฀It’s฀a฀two฀way฀conversation฀฀ in฀ which฀ the฀ browser฀ asks฀ for฀ a฀ document฀ and฀ the฀ server฀ sends฀ it.฀ Unlike฀ the฀฀ telephone฀call,฀however,฀there฀is฀no฀reserved฀circuit.฀Data,฀in฀the฀form฀of฀requests฀and฀ responses,฀are฀organized฀into฀chunks฀called฀packets฀and฀sent฀between฀the฀requesting฀ web฀ browser฀ and฀ the฀ web฀ server.฀ In฀ between฀ the฀ requester฀ and฀ the฀ server฀ are฀ a฀ series฀of฀routers.฀These฀machines฀route฀traffic฀between฀different฀smaller฀networks.฀ Each฀time฀a฀packet฀crosses฀the฀boundary฀from฀one฀ISP฀(Internet฀Service฀Provider)฀to฀฀ another฀or฀from฀one฀kind฀of฀network฀to฀another,฀it฀goes฀through฀a฀router.฀The฀packets฀฀ “hop”฀from฀router฀to฀router฀like฀a฀bucket฀brigade.฀This฀type฀of฀data฀transmission฀ is฀called฀packet฀switching,฀instead฀of฀circuit฀switching.฀Internet฀packet฀switching฀ has฀some฀attributes฀that฀make฀it฀reliable฀and฀unreliable฀at฀the฀same฀time. ฀4.฀ Explain,฀in฀general฀terms,฀how฀routing฀works.฀ •฀ Routing฀is฀the฀process฀of฀selecting฀paths฀in฀a฀network฀along฀which฀to฀send฀data฀ or฀physical฀traffic,฀usually฀directs฀forwarding฀on฀the฀basis฀of฀routing฀tables฀which฀ maintain฀a฀record฀of฀the฀routes฀to฀various฀network฀destinations.฀Thus฀constructing฀ routing฀tables,฀which฀are฀held฀in฀the฀routers’฀memory,฀becomes฀very฀important฀for฀ efficient฀routing. 5.฀ Give฀5฀reasons฀for฀packet฀delays.฀ •฀ a฀router฀is฀too฀busy฀and฀can’t฀keep฀up฀with฀traffic •฀ a฀particular฀link฀between฀sender฀and฀receiver฀becomes฀saturated •฀ a฀link฀goes฀down,฀causing฀traffic฀to฀be฀rerouted฀to฀a฀different฀link •฀ one฀or฀more฀routers฀in฀between฀can’t฀think฀fast฀enough •฀ a฀firewall฀looks฀at฀all฀the฀packets฀for฀viruses •฀ delay฀is฀added฀due฀to฀the฀use฀of฀older฀technology,฀such฀as฀modems •฀ other฀downloads฀on฀a฀pipe฀cause฀it฀to฀delay •฀ packets฀are฀lost,฀resulting฀in฀resends,฀and฀other฀packets฀get฀bunched฀up฀behind฀ them฀

English++ Further exercises 1.฀ Pre-prepare฀a฀list฀of฀features.฀Classify฀them฀into฀four฀groups:฀Internet,฀telephone,฀ radio,฀television.฀The฀features฀could฀be฀taken฀from฀the฀text฀and/or฀worked฀out฀by฀ students฀working฀in฀groups.฀

฀

TV฀

Radio฀

Phone฀

Internet

฀

broadcast฀

direct฀

broadcast/direct

฀ ฀

real-time฀ ฀

real-time/ prepared฀documents

฀

circuit-switched฀

packet-based

฀

routing

฀

streaming฀transmission

Possible topics for discussion 1.฀ What฀do฀you฀think฀is฀the฀main฀cause฀of฀interruptions฀in฀internet฀transmission?฀ 2.฀ Why฀is฀audio฀data฀not฀transferred฀in฀the฀same฀way฀as฀telephone฀calls฀although฀ both฀the฀Internet฀and฀telephone฀calls฀use฀the฀same฀wires? •฀ Fundamentally,฀the฀Internet฀is฀far฀better฀suited฀for฀sending฀web฀pages฀than฀real-time฀ media฀because฀web฀pages฀are฀far฀smaller฀and฀far฀less฀sensitive฀to฀delays.฀There฀is฀ not฀much฀difference฀between฀a฀one-฀and฀two-second฀delay฀in฀getting฀a฀web฀page,฀ but฀a฀one-second฀pause฀in฀real-time฀video฀is฀unacceptable.฀ 3.฀ How฀do฀you฀use฀the฀Internet?฀(Which฀Internet฀services฀do฀you฀use฀most฀often?) 4.฀ Do฀you฀use฀the฀Internet฀for฀making฀phone฀calls?฀Why/why฀not?฀What฀are฀advantages฀ and฀disadvantages? •฀ low฀price •฀ video฀transmission฀is฀possible •฀ there฀is฀no฀difference฀(in฀costs)฀between฀long฀and฀short฀distance฀communication •฀ the฀phone฀call฀quality฀depends฀on฀bandwidth฀of฀the฀connection฀฀ •฀ requires฀computer฀connected฀to฀the฀Internet ฀

English++

Computer Simulation Wikipedia

Number฀of฀words฀฀

2220

Computer฀science฀content฀฀

Low

Math฀content฀฀

Medium

English฀language฀complexity฀฀

Medium

Learning objectives •฀ to฀acquire฀basic฀knowledge฀about฀simulation฀kinds฀and฀history •฀ to฀understand฀difference฀between฀simulation฀and฀modelling •฀ to฀understand฀the฀power฀of฀simulation฀and฀its฀influence฀on฀modern฀science

Sub-areas covered •฀ Computer฀simulation •฀ Computer฀graphics •฀ Maths

Keywords •฀ mathematical฀model฀-฀an฀abstract฀model฀that฀uses฀mathematical฀language฀to฀describe฀฀ a฀system •฀ stochastic฀ process฀ -฀ a฀ process฀ with฀ an฀ indeterminate฀ or฀ random฀ element฀ as฀ opposed฀to฀a฀deterministic฀process฀that฀has฀no฀random฀element •฀ discrete฀-฀not฀supporting฀or฀requiring฀the฀notion฀of฀continuity;฀discrete฀objects฀are฀ countable฀sets฀such฀as฀integers •฀ Computer฀ Generated฀ Imagery฀ (CGI)฀ -฀ an฀ application฀ of฀ the฀ field฀ of฀ computer฀ graphics฀(or,฀more฀specifically,฀3D฀computer฀graphics)฀to฀special฀effects฀in฀films,฀ television฀programs,฀commercials฀and฀simulation •฀ differential฀equation฀-฀a฀mathematical฀equation฀for฀an฀unknown฀function฀of฀one฀or฀ several฀variables฀that฀relates฀the฀values฀of฀the฀function฀itself฀and฀of฀its฀derivatives •฀ gamut฀-฀a฀complete฀range฀or฀฀extent฀ •฀ Monte฀Carlo฀method฀-฀a฀computational฀algorithm฀which฀relies฀on฀repeated฀random฀ sampling฀to฀compute฀its฀results

English++

Summary The฀ article฀ presents฀ a฀ general฀ view฀ of฀ computer฀ simulations.฀ It฀ explains฀ what฀ a฀฀ computer฀ simulation฀ is฀ and฀ the฀ differences฀ between฀ simulation฀ and฀ modelling.฀ It฀฀ provides฀a฀brief฀฀overview฀of฀the฀history฀of฀computer฀simulation฀and฀divides฀computer฀฀ simulation฀ into฀ specific฀ types:฀ stochastic฀ and฀ deterministic฀ and฀ continuous฀ and฀฀ discrete,฀giving฀examples฀of฀each฀kind.฀It฀sets฀out฀the฀advantages฀of฀CGI฀simulations฀ and฀ describes฀ the฀ impact฀ of฀ simulations฀ on฀ present-day฀ ฀ science.฀ The฀ final฀ part฀ of฀ the฀article฀lists฀practical฀contexts฀for฀computer฀simulation฀which฀are฀฀important฀in฀ everyday฀life.฀ Artykuł฀prezentuje฀ogólną฀ideę฀symulacji฀komputerowych.฀Wyjaśnia,฀co฀nazywamy฀ symulacją฀ komputerową฀ oraz฀ jaka฀ jest฀ różnica฀ między฀ symulacją฀ a฀ modelowaniem.฀ Krótko฀ opowiada฀ o฀ historii฀ symulacji฀ komputerowych,฀ oraz฀ prezentuje฀ różne฀ typy฀ symulacji:฀stochastyczne฀i฀deterministyczne,฀ciągłe฀i฀dyskretne฀wraz฀z฀przykładami.฀ Przedstawia฀zalety฀symulacji฀typu฀CGI฀oraz฀wpływ฀symulacji฀na฀współczesną฀naukę.฀ Na฀końcu฀możemy฀się฀dowiedzieć,฀gdzie฀spotykamy฀się฀z฀symulacją฀w฀naszym฀codziennym฀życiu.฀

Pre-reading exercises 1.฀ How฀can฀we฀solve฀problems฀in฀cases฀where฀physical฀models฀are฀too฀complex฀or฀ expensive฀to฀build? 2.฀ Name฀some฀problems฀which฀can฀be฀solved฀using฀computer฀simulation?

English++

Computer simulation

A฀computer฀simulation฀(also฀referred฀to฀as฀a฀computer฀model฀or฀a฀computational฀model)฀ is฀a฀computer฀program,฀or฀network฀of฀computers,฀that฀attempts฀to฀simulate฀an฀abstract฀ model฀of฀a฀particular฀system.฀Computer฀simulations฀have฀become฀a฀useful฀part฀of฀the฀ mathematical฀modelling฀of฀many฀natural฀systems฀in฀physics฀(computational฀physics),฀ chemistry฀and฀biology;฀human฀systems฀in฀economics,฀psychology,฀and฀social฀science,฀and฀ in฀the฀process฀of฀engineering฀new฀technology,฀so฀as฀to฀gain฀insight฀into฀the฀operation฀of฀ those฀systems฀or฀to฀observe฀their฀behaviour.฀ mathematical฀model฀

Computer฀simulations฀vary฀from฀computer฀programs฀that฀run฀a฀few฀minutes,฀to฀network-฀

an฀abstract฀model฀

-based฀ groups฀ of฀ computers฀ running฀ for฀ hours฀ or฀ ongoing฀ simulations฀ that฀ run฀ for฀

that฀uses฀mathematical฀

days.฀The฀scale฀of฀events฀being฀simulated฀by฀computer฀simulations฀has฀far฀exceeded฀

language฀to฀describe฀

anything฀possible฀(or฀perhaps฀even฀imaginable)฀using฀the฀traditional฀paper-and-pencil฀

a฀system

mathematical฀ modelling:฀ over฀ 10฀ years฀ ago.฀ A฀ desert-battle฀ simulation,฀ of฀ one฀ force฀ invading฀another,฀involved฀the฀modelling฀of฀66,239฀tanks,฀trucks฀and฀other฀vehicles฀ on฀simulated฀terrain฀around฀Kuwait,฀using฀multiple฀supercomputers฀in฀the฀DoD฀High฀ Performance฀ Computer฀ Modernization฀ Program.฀ Another฀ simulation฀ ran฀ a฀ 1-billion-฀ -atom฀model,฀where฀previously,฀a฀2.64-million-atom฀model฀of฀a฀ribosome,฀in฀2005,฀had฀ been฀considered฀a฀massive฀computer฀simulation.฀And฀the฀Blue฀Brain฀project฀at฀EPFL฀ (Switzerland)฀began฀in฀May฀2005฀to฀create฀the฀first฀computer฀simulation฀of฀the฀entire฀ human฀brain,฀right฀down฀to฀the฀molecular฀level.฀

Simulation versus modelling Traditionally,฀the฀formal฀modelling,฀or฀modelling,฀of฀systems฀has฀been฀via฀a฀mathematical฀ ฀model,฀which฀attempts฀to฀find฀analytical฀solutions฀to฀problems,฀which฀enables฀the฀ prediction฀ of฀ the฀ behaviour฀ of฀ the฀ system฀ from฀ a฀ set฀ of฀ parameters฀ and฀ initial฀฀ conditions.฀ While฀computer฀simulations฀might฀use฀some฀algorithms฀from฀purely฀mathematical฀ models,฀computers฀can฀combine฀simulations฀with฀the฀reality฀of฀actual฀events,฀such฀

as฀generating฀input฀responses฀to฀simulate฀test฀subjects฀who฀are฀no฀longer฀present.฀ Although฀the฀missing฀test฀subjects฀(i.e.฀the฀users฀of฀equipment฀or฀systems)฀are฀being฀

English++ modelled/simulated,฀the฀whole฀process฀can฀be฀conducted฀with฀the฀actual฀equipment฀ or฀system฀they฀use,฀revealing฀performance฀limits฀or฀defects฀in฀long-term฀use฀by฀the฀ simulated฀users.฀ Note฀that฀the฀term฀computer฀simulation฀is฀broader฀than฀computer฀modelling,฀which฀ implies฀that฀all฀aspects฀are฀being฀modelled฀in฀the฀computer฀representation.฀However,฀

stochastic฀process

computer฀ simulation฀ also฀ includes฀ generating฀ inputs฀ from฀ simulated฀ users฀ to฀ run฀

a฀process฀

actual฀computer฀software฀or฀equipment,฀with฀only฀part฀of฀the฀system฀being฀modelled:฀

with฀an฀indeterminate฀

an฀ example฀ would฀ be฀ flight฀ simulators฀ which฀ can฀ run฀ machines฀ as฀ well฀ as฀ actual฀

or฀random฀element฀

flight฀software.฀

as฀opposed฀to฀

Computer฀simulations฀are฀used฀in฀many฀fields,฀including฀science,฀technology,฀entertainment,฀and฀business฀planning฀and฀scheduling.฀

a฀deterministic฀process฀ that฀has฀no฀random฀ element

History Computer฀ simulation฀ was฀ developed฀ hand-in-hand฀ with฀ the฀ rapid฀ growth฀ of฀ the฀฀ computer,฀following฀its฀first฀large-scale฀deployment฀during฀the฀Manhattan฀Project฀in฀ World฀ War฀ II฀ to฀ model฀ the฀ process฀ of฀ nuclear฀ detonation.฀ It฀ was฀ a฀ simulation฀ of฀ 12฀ hard฀spheres฀using฀a฀Monte฀Carlo฀algorithm.฀Computer฀simulation฀is฀often฀used฀as฀an฀ adjunct฀to,฀or฀substitution฀for,฀modelling฀systems฀for฀which฀simple฀closed฀form฀analytic฀ solutions฀are฀not฀possible.฀There฀are฀many฀different฀types฀of฀computer฀simulation;฀the฀ common฀feature฀they฀all฀share฀is฀the฀attempt฀to฀generate฀a฀sample฀of฀representative฀ scenarios฀for฀a฀model฀in฀which฀a฀complete฀enumeration฀of฀all฀possible฀states฀of฀the฀ model฀would฀be฀prohibitive฀or฀impossible.฀Computer฀models฀were฀initially฀used฀as฀a฀ supplement฀for฀other฀arguments,฀but฀their฀use฀later฀became฀rather฀widespread.

Data preparation The฀data฀input/output฀for฀the฀simulation฀can฀be฀either฀through฀formatted฀text฀files฀ or฀a฀pre-฀and฀post฀processor.฀

Types of computer simulation Computer฀models฀can฀be฀classified฀according฀to฀several฀criteria฀including:฀ •฀ stochastic฀or฀deterministic฀(and฀as฀a฀special฀case฀of฀deterministic,฀chaotic)฀ •฀ steady-state฀or฀dynamic฀ •฀ continuous฀or฀discrete฀(and฀as฀an฀important฀special฀case฀of฀discrete,฀discrete฀event฀ or฀DE฀models)฀ •฀ local฀or฀distributed.฀ For฀example,฀steady-state฀models฀use฀equations฀defining฀the฀relationships฀between฀ elements฀of฀the฀modelled฀system฀and฀attempt฀to฀find฀a฀state฀in฀which฀the฀system฀is฀in฀ equilibrium.฀Such฀models฀are฀often฀used฀in฀simulating฀physical฀systems฀as฀a฀simpler฀฀

English++ gamut

modelling฀case฀before฀dynamic฀simulation฀is฀attempted.฀Dynamic฀simulations฀model฀

a฀complete฀range

changes฀in฀a฀system฀in฀response฀to฀(usually฀changing)฀input฀signals.฀Stochastic฀models฀

or฀฀extent

use฀random฀number฀generators฀to฀model฀chance฀or฀random฀events;฀they฀are฀also฀called฀ Monte฀Carlo฀simulations.฀A฀discrete฀event฀simulation฀(DES)฀manages฀events฀in฀time.฀ Most฀ computer,฀ logic-test฀ and฀ fault-tree฀ simulations฀ are฀ of฀ this฀ type.฀ In฀ this฀ type฀ of฀ simulation,฀the฀simulator฀maintains฀a฀queue฀of฀events฀sorted฀by฀the฀simulated฀time฀ in฀which฀they฀should฀occur.฀The฀simulator฀reads฀the฀queue฀and฀triggers฀new฀events฀as฀ each฀event฀is฀processed.฀It฀is฀not฀important฀to฀execute฀the฀simulation฀in฀real฀time.฀ It’s฀often฀more฀important฀to฀be฀able฀to฀access฀the฀data฀produced฀by฀the฀simulation,฀

฀

to฀discover฀logic฀defects฀in฀the฀design฀or฀the฀sequence฀of฀events.฀A฀continuous฀dynamic฀simulation฀performs฀numerical฀solutions฀of฀differential-algebraic฀equations฀or฀฀ differential฀equations฀(either฀partial฀or฀ordinary).฀Periodically,฀the฀simulation฀program฀ solves฀all฀the฀equations,฀and฀uses฀the฀numbers฀to฀change฀the฀state฀and฀output฀of฀the฀ simulation.฀Applications฀include฀flight฀simulators,฀simulation฀games,฀chemical฀process฀฀ modelling,฀and฀simulations฀of฀electrical฀circuits.฀Originally,฀these฀kinds฀of฀simulations฀฀ were฀actually฀implemented฀on฀analogue฀computers,฀where฀the฀differential฀equations฀

discrete

could฀be฀represented฀directly฀by฀various฀electrical฀components฀such฀as฀op-amps.฀By฀the฀

not฀supporting฀or฀

late฀1980s,฀however,฀most฀“analogue”฀simulations฀were฀run฀on฀conventional฀digital฀฀

requiring฀the฀notion฀of฀

computers฀ that฀ emulate฀ the฀ behaviour฀ of฀ an฀ analogue฀ computer.฀ A฀ special฀ type฀ of฀

continuity;฀

discrete฀simulation฀which฀does฀not฀rely฀on฀a฀model฀with฀an฀underlying฀equation,฀but฀

discrete฀objects฀are฀

can฀nonetheless฀be฀represented฀formally,฀is฀agent-based฀simulation.฀In฀agent-based฀

countable฀sets฀

simulation,฀the฀individual฀entities฀(such฀as฀molecules,฀cells,฀trees฀or฀consumers)฀in฀

such฀as฀integers

the฀model฀are฀represented฀directly฀(rather฀than฀by฀their฀density฀or฀concentration)฀and฀ possess฀an฀internal฀state฀and฀set฀of฀behaviours฀or฀rules฀which฀determine฀how฀the฀ agent’s฀state฀is฀updated฀from฀one฀time-step฀to฀the฀next.฀Distributed฀models฀run฀on฀ a฀network฀of฀interconnected฀computers,฀possibly฀through฀the฀Internet.฀Simulations฀฀ dispersed฀across฀multiple฀host฀computers฀like฀this฀are฀often฀referred฀to฀as฀“distributed฀฀ simulations”.฀ There฀ are฀ several฀ standards฀ for฀ distributed฀ simulation,฀ including฀฀ Aggregate฀Level฀Simulation฀Protocol฀(ALSP),฀Distributed฀Interactive฀Simulation฀(DIS),฀ the฀High฀Level฀Architecture฀(HLA)฀and฀the฀Test฀and฀Training฀Enabling฀Architecture฀ (TENA).฀

CGI computer simulation Formerly,฀the฀output฀data฀from฀a฀computer฀simulation฀was฀sometimes฀presented฀in฀ a฀ table,฀ or฀ a฀ matrix,฀ showing฀ how฀ data฀ was฀ affected฀ by฀ numerous฀ changes฀ in฀ the฀ simulation฀parameters.฀The฀use฀of฀the฀matrix฀format฀was฀related฀to฀the฀traditional฀฀ use฀ of฀ the฀ matrix฀ concept฀ in฀ mathematical฀ models;฀ however,฀ psychologists฀ and฀฀ others฀noted฀that฀humans฀could฀quickly฀perceive฀trends฀by฀looking฀at฀graphs฀or฀even฀

moving-images฀or฀motion-pictures฀generated฀from฀the฀data,฀as฀displayed฀by฀computer฀ -generated-imagery฀ (CGI)฀ animation.฀ Although฀ observers฀ couldn’t฀ necessarily฀ read฀

English++ out฀numbers,฀or฀spout฀maths฀formulas,฀from฀observing฀a฀moving฀weather฀chart,฀they฀ might฀ be฀ able฀ to฀ predict฀ events฀ (and฀ “see฀ that฀ rain฀ was฀ headed฀ their฀ way”),฀ much฀ faster฀than฀scanning฀tables฀of฀rain-cloud฀coordinates.฀Such฀intense฀graphical฀displays,฀ which฀transcended฀the฀world฀of฀numbers฀and฀formulae,฀sometimes฀also฀led฀to฀output฀฀ that฀lacked฀a฀coordinate฀grid฀or฀omitted฀timestamps,฀as฀if฀straying฀too฀far฀from฀numeric฀฀ data฀ displays.฀ Today,฀ weather฀ forecasting฀ models฀ tend฀ to฀ balance฀ the฀ view฀ of฀ moving฀ rain/snow฀clouds฀against฀a฀map฀that฀uses฀numeric฀coordinates฀and฀numeric฀timestamps฀฀ of฀events.฀

Computer฀Generated฀ Imagery฀(CGI) an฀application฀of฀the฀field฀ of฀computer฀graphics฀ (or,฀more฀specifically,฀

Similarly,฀CGI฀computer฀simulations฀of฀CAT฀scans฀can฀simulate฀how฀a฀tumour฀might฀

3D฀computer฀graphics)฀

shrink฀or฀change,฀during฀an฀extended฀period฀of฀medical฀treatment,฀presenting฀the฀

to฀special฀effects฀in฀films,฀

passage฀of฀time฀as฀a฀spinning฀view฀of฀the฀visible฀human฀head,฀as฀the฀tumour฀changes.฀

television฀programs,

Other฀applications฀of฀CGI฀computer฀simulations฀are฀being฀developed฀to฀graphically฀ display฀large฀amounts฀of฀data฀in฀motion,฀as฀changes฀occur฀during฀a฀simulation฀run.฀

฀commercials ฀and฀simulation

Computer simulation in science The฀ following฀ are฀ generic฀ examples฀ of฀ types฀ of฀ computer฀ simulations฀ in฀ science,฀ which฀are฀derived฀from฀an฀underlying฀mathematical฀description:฀ A฀ numerical฀ simulation฀ of฀ differential฀ equations฀ which฀ cannot฀ be฀ solved฀฀ analytically.฀Falling฀into฀this฀category฀are:฀ •฀ theories฀ which฀ involve฀ continuous฀ systems฀ such฀ as฀ phenomena฀ in฀ physical฀฀ cosmology฀ •฀ fluid฀dynamics฀(e.g.฀climate฀models,฀roadway฀noise฀models,฀roadway฀air฀dispersion฀฀ models)฀ •฀ continuum฀mechanics฀and฀chemical฀kinetics฀ A฀stochastic฀simulation,฀typically฀used฀for฀discrete฀systems฀where฀events฀occur฀probabilistically,฀฀and฀which฀cannot฀be฀described฀directly฀with฀differential฀equations฀(this฀is฀ a฀discrete฀simulation฀in฀the฀above฀sense).฀Phenomena฀in฀this฀category฀include: •฀ genetic฀drift฀ •฀ biochemical฀or฀gene฀regulatory฀networks฀with฀small฀numbers฀of฀molecules฀(See฀ also:฀Monte฀Carlo฀method).฀ Specific฀examples฀of฀computer฀simulations฀follow:฀ •฀ statistical฀simulations฀based฀upon฀an฀agglomeration฀of฀a฀large฀number฀of฀input฀ profiles,฀such฀as฀the฀forecasting฀of฀equilibrium฀temperature฀of฀receiving฀waters,฀ allowing฀the฀gamut฀of฀meteorological฀data฀to฀be฀input฀for฀a฀specific฀locale.฀This฀ technique฀was฀developed฀for฀thermal฀pollution฀forecasting.฀ •฀ agent฀based฀simulation฀has฀been฀used฀effectively฀in฀ecology,฀where฀it฀is฀often฀called฀ individual฀based฀modelling฀and฀has฀been฀used฀in฀situations฀for฀which฀individual฀

English++ variability฀ in฀ the฀ agents฀ cannot฀ be฀ neglected,฀ such฀ as฀ population฀ dynamics฀ of฀ salmon฀ and฀ trout฀ (most฀ purely฀ mathematical฀ models฀ assume฀ all฀ trout฀ behave฀ identically)฀ •฀ time฀stepped฀dynamic฀model;฀in฀hydrology฀there฀are฀several฀such฀hydrology฀transport฀models฀such฀as฀the฀SWMM฀and฀DSSAM฀Models฀developed฀by฀the฀U.S.฀Environmental฀Protection฀Agency฀for฀river฀water฀quality฀forecasting฀ •฀ computer฀simulations฀have฀also฀been฀used฀to฀formally฀model฀theories฀of฀human฀ Monte฀Carlo฀method a฀computational฀algorithm฀

cognition฀and฀performance,฀e.g.฀ACT-R฀ •฀ computer฀simulation฀using฀molecular฀modelling฀for฀drug฀discovery฀

which฀relies฀on฀repeated

•฀ computational฀ fluid฀ dynamics฀ simulations฀ are฀ used฀ to฀ simulate฀ the฀ behaviour฀ of฀฀

฀random฀sampling฀to฀

flowing฀ air,฀ water฀ and฀ other฀ fluids.฀ There฀ are฀ one-,฀ two-฀ and฀ three-฀ dimensional฀

compute฀

models฀used.฀A฀one฀dimensional฀model฀might฀simulate฀the฀effects฀of฀water฀hammer฀

its฀results

in฀ a฀ pipe.฀ A฀ two-dimensional฀ model฀ might฀ be฀ used฀ to฀ simulate฀ the฀ drag฀ forces฀ on฀the฀cross-section฀of฀an฀aeroplane฀wing.฀A฀three-dimensional฀simulation฀might฀ estimate฀the฀heating฀and฀cooling฀requirements฀of฀a฀large฀building.฀฀ Understanding฀of฀statistical฀thermodynamic฀molecular฀theory฀is฀fundamental฀to฀the฀ appreciation฀of฀molecular฀solutions.฀Development฀of฀the฀Potential฀Distribution฀Theorem฀ (PDT)฀allows฀one฀to฀simplify฀this฀complex฀subject฀to฀down-to-earth฀presentations฀of฀ molecular฀theory.฀ Notable,฀and฀sometimes฀controversial,฀computer฀simulations฀used฀in฀science฀include:฀ •฀ Donella฀Meadows’฀World3฀used฀in฀the฀Limits฀to฀Growth฀฀ •฀ James฀Lovelock’s฀Daisyworld •฀ Thomas฀Ray’s฀Tierra.฀

Simulation environments for physics and engineering Graphical฀environments฀to฀design฀simulations฀have฀been฀developed.฀Special฀care฀was฀ taken฀to฀handle฀“events”฀(situations฀in฀which฀the฀simulation฀equations฀are฀not฀valid฀ and฀have฀to฀be฀changed).฀The฀open฀project฀Open฀Source฀Physics฀was฀started฀in฀order฀to฀ develop฀reusable฀libraries฀for฀simulations฀in฀Java,฀together฀with฀Easy฀Java฀Simulations,฀ a฀complete฀graphical฀environment฀that฀generates฀code฀based฀on฀these฀libraries.฀

Pitfalls in computer simulation Although฀sometimes฀ignored฀in฀computer฀simulations,฀it฀is฀very฀important฀to฀perform฀ sensitivity฀analysis฀to฀ensure฀that฀the฀accuracy฀of฀the฀results฀is฀properly฀understood.฀ For฀example,฀the฀probabilistic฀risk฀analysis฀of฀factors฀determining฀the฀success฀of฀an฀ oilfield฀exploration฀program฀involves฀combining฀samples฀from฀a฀variety฀of฀statistical฀ distributions฀using฀the฀Monte฀Carlo฀method.฀If,฀for฀instance,฀one฀of฀the฀key฀parameters฀ (i.e.฀the฀net฀ratio฀of฀oil-bearing฀strata)฀is฀known฀to฀only฀one฀significant฀figure,฀then฀

the฀result฀of฀the฀simulation฀might฀not฀be฀more฀precise฀than฀one฀significant฀figure,฀ although฀it฀might฀(misleadingly)฀be฀presented฀as฀having฀four฀significant฀figures.฀

English++ Computer simulation in practical contexts Computer฀simulations฀are฀used฀in฀a฀wide฀variety฀of฀practical฀contexts,฀such฀as: •฀ analysis฀of฀air฀pollutant฀dispersion฀using฀atmospheric฀dispersion฀modelling •฀ design฀of฀complex฀systems฀such฀as฀aircraft฀and฀logistics฀systems฀ •฀ design฀of฀noise฀barriers฀to฀effect฀roadway฀noise฀mitigation฀ •฀ flight฀simulators฀to฀train฀pilots฀ •฀ weather฀forecasting฀ •฀ behaviour฀of฀structures฀(such฀as฀buildings฀and฀industrial฀parts)฀under฀stress฀and฀ other฀conditions฀฀ •฀ design฀of฀industrial฀processes,฀such฀as฀chemical฀processing฀plants฀ •฀ strategic฀management฀and฀organizational฀studies฀ •฀ reservoir฀simulation฀for฀the฀petroleum฀engineering฀to฀model฀the฀subsurface฀ ฀

reservoir฀

•฀ Process฀Engineering฀Simulation฀tools฀ •฀ robot฀simulators฀for฀the฀design฀of฀robots฀and฀robot฀control฀algorithms฀ The฀reliability฀and฀the฀trust฀people฀put฀in฀computer฀simulations฀depends฀on฀the฀validity฀ of฀the฀simulation฀model,฀therefore฀verification฀and฀validation฀are฀of฀crucial฀importance฀

differential฀equation฀ a฀mathematical฀equation฀ for฀an฀unknown฀function฀ of฀one฀or฀several฀variables฀ that฀relates฀the฀values฀ of฀the฀function฀itself฀and฀ of฀its฀derivatives

in฀the฀development฀of฀computer฀simulations.฀Another฀important฀aspect฀of฀computer฀ simulations฀is฀that฀of฀reproducibility฀of฀the฀results,฀meaning฀that฀a฀simulation฀model฀ should฀not฀provide฀a฀different฀answer฀for฀each฀execution.฀Although฀this฀might฀seem฀ obvious,฀this฀is฀a฀special฀point฀of฀attention฀in฀stochastic฀simulations,฀where฀random฀ numbers฀should฀actually฀be฀semi-random฀numbers.฀An฀exception฀to฀reproducibility฀are฀ “human-in-the-loop”฀ simulations,฀ such฀ as฀ flight฀ simulations฀ and฀ computer฀ games.฀ Here฀a฀human฀is฀part฀of฀the฀simulation฀and฀thus฀influences฀the฀outcome฀in฀a฀way฀that฀ is฀hard฀if฀not฀impossible฀to฀reproduce฀exactly.฀ Computer฀ graphics฀ can฀ be฀ used฀ to฀ display฀ the฀ results฀ of฀ a฀ computer฀ simulation.฀฀ Animations฀ can฀ be฀ used฀ to฀ experience฀ a฀ simulation฀ in฀ real-time฀ e.g.฀ in฀ training฀฀ simulations.฀ In฀ some฀ cases฀ animations฀ may฀ also฀ be฀ useful฀ in฀ faster฀ than฀ real-time฀ or฀even฀slower฀than฀real-time฀modes.฀For฀example,฀faster฀than฀real-time฀animations฀ can฀ be฀ useful฀ in฀ visualizing฀ the฀ build-up฀ of฀ queues฀ in฀ the฀ simulation฀ of฀ humans฀฀ evacuating฀a฀building.฀Furthermore,฀simulation฀results฀are฀often฀aggregated฀into฀static฀ images฀using฀various฀ways฀of฀scientific฀visualization.฀ In฀ debugging,฀ simulating฀ a฀ program฀ execution฀ under฀ test฀ (rather฀ than฀ executing฀฀ natively)฀can฀detect฀far฀more฀errors฀than฀the฀hardware฀itself฀can฀detect฀and,฀at฀the฀ same฀ time,฀ log฀ useful฀ debugging฀ information฀ such฀ as฀ instruction฀ trace,฀ memory฀฀ alterations฀ and฀ instruction฀ counts.฀ This฀ technique฀ can฀ also฀ detect฀ buffer฀ overflow฀ and฀similar฀“hard฀to฀detect”฀errors฀as฀well฀as฀produce฀performance฀information฀and฀ tuning฀data.

English++

Exercises Pre-reading exercises 1.฀ How฀can฀we฀solve฀problems฀in฀cases฀where฀physical฀models฀are฀too฀complex฀or฀ expensive฀to฀build? •฀ computer฀simulation 2.฀ Name฀some฀problems฀which฀can฀be฀solved฀using฀computer฀simulation? •฀ spread฀of฀infectious฀diseases฀ •฀ panic฀in฀crowds฀ •฀ crash฀testing฀ •฀ explosions฀modelling฀ •฀ aerodynamic฀solutions฀testing •฀ building฀demolition฀

Comprehension question 1.฀ Explain฀the฀differences฀between฀discrete/continuous฀and฀stochastic/deterministic฀ simulation,฀giving฀examples. •฀ Stochastic฀ models฀ use฀ random฀ number฀ generators฀ to฀ model฀ chance฀ or฀ random฀ events;฀they฀are฀also฀called฀Monte฀Carlo฀simulations. •฀ Deterministic฀models฀have฀no฀random฀elements.฀ •฀ A฀discrete฀event฀simulation฀(DES)฀manages฀events฀in฀time.฀Most฀computer,฀logic-test฀ and฀fault-tree฀simulations฀are฀of฀this฀type.฀In฀this฀type฀of฀simulation,฀the฀simulator฀฀ maintains฀a฀queue฀of฀events฀sorted฀by฀the฀simulated฀time฀they฀should฀occur.฀The฀ simulator฀reads฀the฀queue฀and฀triggers฀new฀events฀as฀each฀event฀is฀processed.฀It฀ is฀not฀important฀to฀execute฀the฀simulation฀in฀real฀time. •฀ A฀ continuous฀ dynamic฀ simulation฀ performs฀ numerical฀ solution฀ of฀ differential฀ -algebraic฀equations฀or฀differential฀equations฀(either฀partial฀or฀ordinary).฀Periodically,฀ the฀simulation฀program฀solves฀all฀the฀equations,฀and฀uses฀the฀numbers฀to฀change฀the฀ state฀and฀output฀of฀the฀simulation.฀Applications฀include฀flight฀simulators,฀simulation฀ games,฀chemical฀process฀modelling,฀and฀simulations฀of฀electrical฀circuits.

Possible topics for discussion 1.฀ Is฀it฀possible฀to฀simulate฀any฀problem?฀

Possible difﬁculties A฀big฀number฀of฀mathematical฀terms.฀ Rather฀than฀focusing฀on฀the฀words฀you฀don’t฀understand,฀try฀to฀get฀the฀main฀idea.฀ .฀

฀฀฀ ฀

English++

Computer Facial Animation Wikipedia Number฀of฀words฀฀

1970

Computer฀science฀content฀฀

Medium

Math฀content฀฀

Low

English฀language฀complexity฀฀

Medium

Learning objectives •฀ ฀to฀acquire฀basic฀vocabulary฀related฀to฀facial •฀ to฀become฀familiar฀with฀different฀3D-animation฀systems •฀ to฀gain฀understanding฀of฀the฀major฀problems฀connected฀with฀speech฀animation

Sub-areas covered •฀ Computer฀graphics฀

Keywords •฀ morphing฀-฀a฀special฀effect฀in฀motion฀pictures฀and฀animations฀that฀changes฀(or฀ morphs)฀one฀image฀into฀another฀through฀a฀seamless฀transition฀ •฀ rendering฀-฀the฀process฀of฀generating฀an฀image฀from฀a฀model฀by฀means฀of฀computer฀ programs฀ •฀ keyframe฀-฀or฀a฀key฀frame฀in฀animation฀and฀film฀making฀is฀a฀drawing฀which฀defines฀฀ the฀starting฀and฀ending฀points฀of฀any฀smooth฀transition฀texture฀-฀a฀bitmap฀image฀ applied฀to฀a฀surface฀in฀computer฀graphics฀ •฀ texture฀-฀a฀bitmap฀image฀applied฀to฀a฀surface฀in฀computer฀graphics฀ •฀ computer฀vision฀-฀a฀branch฀of฀artificial฀intelligence฀that฀deals฀with฀computer฀processing฀฀ of฀images฀from฀the฀real฀world •฀ alignment฀ -฀ the฀ adjustment฀ of฀ an฀ object฀ in฀ relation฀ to฀ other฀ objects,฀ or฀ a฀ static฀ orientation฀of฀some฀object฀or฀set฀of฀objects฀in฀relation฀to฀others฀ •฀ motion฀capture฀-฀a฀technique฀of฀recording฀the฀actions฀of฀human฀actors฀and฀using฀ that฀information฀to฀animate฀digital฀character฀models฀in฀3D฀animation฀

Summary A฀fairly฀general฀text฀about฀facial฀animation฀in฀computer฀graphics.฀It฀contains฀a฀short฀ history฀of฀facial฀animation฀from฀the฀Facial฀Action฀Coding฀System,฀which฀defines฀64฀basic฀facial฀Action฀Units,฀to฀films฀like:฀The฀Matrix฀or฀The฀Lord฀of฀the฀Rings.฀The฀second฀part฀ describes฀animation฀techniques:฀2D฀animation,฀3D฀animation฀and฀speech฀animation.฀

English++ Tekst฀traktuje฀w฀sposób฀ogólny฀problem฀komputerowej฀animacji฀twarzy.฀Pierwsza฀część฀ zapoznaje฀nas฀z฀historią฀tego฀zagadnienia฀poczynając฀od฀roku฀1978,฀gdy฀pierwszy฀raz฀ pojawił฀się฀FACS฀(Facial฀Action฀Coding฀System)฀zawierający฀64฀podstawowe฀jednostki฀ ruchu฀twarzy,฀na฀animacji฀twarzy฀w฀filmach฀takich฀jak฀Matrix,฀czy฀Władca฀Pierścieni฀ kończąc.฀Dalsza฀część฀tekstu฀zapoznaje฀nas฀z฀technikami฀używanymi฀w฀komputerowej฀ animacji฀twarzy.฀Po฀kolei฀omawiane฀są฀techniki฀2D,฀3D฀i฀animacja฀mowy.฀

Pre-reading questions 1.฀ ฀Students฀are฀given฀pictures฀of฀human฀faces฀and฀try฀to฀guess฀what฀emotions฀they฀ show. 2.฀ What฀is฀the฀number฀of฀facial฀muscles?฀ 3.฀ Why฀are฀facial฀expressions฀so฀important฀in฀our฀lives?฀ 4.฀ Where฀can฀facial฀animations฀be฀used?฀ 5.฀ What฀is฀the฀rendering฀process฀in฀computer฀graphics?฀What฀is฀the฀motion฀capture฀ technique?฀

English++

Computer facial animation

Computer฀facial฀animation฀is฀primarily฀an฀area฀of฀computer฀graphics฀that฀encapsulates฀฀ models฀and฀techniques฀for฀generating฀and฀animating฀images฀of฀the฀human฀head฀and฀ face.฀Due฀to฀its฀subject฀and฀output฀type,฀it฀is฀also฀related฀to฀many฀other฀scientific฀and฀ artistic฀fields฀from฀psychology฀to฀traditional฀animation.฀The฀importance฀of฀human฀ faces฀ in฀ verbal฀ and฀ non-verbal฀ communication฀ and฀ advances฀ in฀ computer฀ graphics฀ hardware฀and฀software฀have฀caused฀considerable฀scientific,฀technological,฀and฀artistic฀ interest฀in฀computer฀facial฀animation.฀ Although฀the฀development฀of฀computer฀graphics฀methods฀for฀facial฀animation฀started฀ in฀the฀early฀1970s,฀major฀achievements฀in฀this฀field฀are฀more฀recent฀and฀have฀taken฀ place฀since฀the฀late฀1980s.฀ Computer฀facial฀animation฀includes฀a฀variety฀of฀techniques฀from฀morphing฀to฀three฀ -dimensional฀ modelling฀ and฀ rendering.฀ It฀ has฀ become฀ well-known฀ and฀ popular฀ through฀animated฀feature฀films฀and฀computer฀games฀but฀its฀applications฀include฀many฀ more฀areas฀such฀as฀communication,฀education,฀scientific฀simulation,฀and฀agent-based฀

rendering the฀process฀of฀generating฀ an฀image฀from฀ a฀model฀by฀means฀ of฀computer฀programs฀

systems฀(for฀example,฀online฀customer฀service฀representatives).฀

History Human฀facial฀expressions฀have฀been฀the฀subject฀of฀scientific฀investigation฀for฀more฀ than฀one฀hundred฀years.฀The฀study฀of฀facial฀movements฀and฀expressions฀started฀from฀

morphing฀

a฀biological฀point฀of฀view.฀After฀some฀older฀investigations,฀i.e.฀by฀John฀Bulwer฀in฀late฀

a฀special฀effect฀

1640s,฀Charles฀Darwin’s฀book฀The฀Expression฀of฀the฀Emotions฀in฀Men฀and฀Animals฀

in฀motion฀pictures฀

can฀be฀considered฀a฀major฀departure฀for฀modern฀research฀in฀behavioural฀biology.฀

and฀animations฀

More฀recently,฀one฀of฀the฀most฀important฀attempts฀to฀describe฀facial฀activities฀(movements)฀was฀the฀Facial฀Action฀Coding฀System฀(FACS).฀Introduced฀by฀Ekman฀and฀Friesen฀ in฀ 1978,฀ FACS฀ defines฀ 64฀ basic฀ facial฀ Action฀ Units฀ (AUs).฀ A฀ major฀ group฀ of฀ these฀฀ Action฀Units฀represent฀primitive฀movements฀of฀facial฀muscles฀in฀actions฀such฀as฀raising฀฀

that฀changes฀(or฀morphs)฀ one฀image฀into฀another฀ through฀a฀seamless฀ transition฀

brows,฀winking,฀and฀talking.฀Eight฀AUs฀are฀for฀rigid฀three-dimensional฀head฀movements,฀ i.e.฀turning฀and฀tilting฀left฀and฀right฀and฀going฀up,฀down,฀forward฀and฀backward.฀FACS฀

English++ keyframe or฀a฀key฀frame฀in฀ animation฀and฀film฀ making฀is฀a฀drawing฀ which฀defines฀ the฀starting฀and฀ending฀ points฀of฀any฀smooth฀ transition฀texture฀ -฀a฀bitmap฀image฀applied฀

has฀been฀successfully฀used฀for฀describing฀desired฀movements฀of฀synthetic฀faces฀and฀also฀ in฀tracking฀facial฀activities.฀ Computer฀based฀facial฀expression฀modelling฀and฀animation฀is฀not฀a฀new฀endeavour.฀ The฀earliest฀work฀with฀computer฀based฀facial฀representation฀was฀done฀in฀the฀early฀ 1970s.฀The฀first฀three-dimensional฀facial฀animation฀was฀created฀by฀Parke฀in฀1972.฀In฀ 1973,฀ Gillenson฀ developed฀ an฀ interactive฀ system฀ to฀ assemble฀ and฀ edit฀ line฀ drawn฀ facial฀images.฀And฀in฀1974,฀Parke฀developed฀a฀parameterized฀three-dimensional฀facial฀ model.฀

to฀a฀surface฀in฀

The฀early฀1980s฀saw฀the฀development฀of฀the฀first฀physically-based฀muscle-controlled฀

computer฀graphics฀

face฀model฀by฀Platt฀and฀the฀development฀of฀techniques฀for฀facial฀caricatures฀by฀Brennan.฀ In฀1985,฀the฀short฀animated฀film฀Tony฀de฀Peltrie฀฀was฀a฀landmark฀for฀facial฀animation;฀ for฀the฀first฀time฀computer฀facial฀expression฀and฀speech฀animation฀were฀a฀fundamental฀ part฀of฀telling฀the฀story.฀ The฀late฀1980s฀saw฀the฀development฀of฀a฀new฀muscle-based฀model฀by฀Waters,฀the฀ development฀ of฀ an฀ abstract฀ muscle฀ action฀ model฀ by฀ Magnenat-Thalmann฀ and฀฀ colleagues,฀and฀approaches฀to฀automatic฀speech฀synchronization฀by฀Lewis฀and฀by฀Hill.฀ The฀1990s฀฀saw฀increasing฀activity฀in฀the฀development฀of฀facial฀animation฀techniques฀ and฀the฀use฀of฀computer฀facial฀animation฀as฀a฀key฀storytelling฀component฀as฀illustrated฀฀ in฀animated฀films฀such฀as฀Toy฀Story,฀Antz,฀Shrek,฀and฀Monsters,฀Inc,฀and฀computer฀ games฀such฀as฀Sims.฀Casper฀(1995)฀is฀a฀milestone฀in฀this฀period,฀being฀the฀first฀movie฀ with฀a฀lead฀actor฀produced฀exclusively฀using฀digital฀facial฀animation฀(Toy฀Story฀was฀ released฀later฀the฀same฀year).฀

computer฀vision

The฀ sophistication฀ of฀ the฀ films฀ increased฀ after฀ 2000.฀ In฀ The฀ Matrix฀ Reloaded฀ and฀

the฀science฀and฀technology฀

Matrix฀Revolutions฀dense฀optical฀flow฀from฀several฀high-definition฀cameras฀was฀used฀

of฀machines฀that฀see฀

to฀capture฀realistic฀facial฀movement฀at฀every฀point฀on฀the฀face.฀Polar฀Express฀used฀ a฀large฀Vicon฀system฀to฀capture฀upward฀of฀150฀points.฀Although฀these฀systems฀are฀ automated,฀a฀large฀amount฀of฀manual฀clean-up฀effort฀is฀still฀needed฀to฀make฀the฀data฀ usable.฀Another฀milestone฀in฀facial฀animation฀was฀reached฀by฀The฀Lord฀of฀the฀Rings฀ where฀a฀character฀specific฀shape฀base฀system฀was฀developed.฀Mark฀Sagar฀pioneered฀ the฀use฀of฀FACS฀in฀entertainment฀facial฀animation,฀and฀FACS฀based฀systems฀developed฀by฀Sagar฀were฀used฀on฀Monster฀House,฀King฀Kong,฀and฀other฀films.฀

Techniques 2D฀Animation Two-dimensional฀ facial฀ animation฀ is฀ commonly฀ based฀ upon฀ the฀ transformation฀ of฀฀ images,฀including฀both฀images฀from฀still฀photography฀and฀sequences฀of฀video.฀Image฀

morphing฀is฀a฀technique฀which฀allows฀in-between฀transitional฀images฀to฀be฀generated฀

English++ between฀a฀pair฀of฀target฀still฀images฀or฀between฀frames฀from฀sequences฀of฀video.฀These฀ morphing฀ techniques฀ usually฀ consist฀ of฀ a฀ combination฀ of฀ a฀ geometric฀ deformation฀ technique,฀which฀aligns฀the฀target฀images,฀and฀a฀cross-fade,฀which฀creates฀the฀smooth฀ transition฀in฀the฀image฀texture.฀An฀early฀example฀of฀image฀morphing฀can฀be฀seen฀in฀ Michael฀Jackson’s฀video฀for฀Black฀And฀White.฀In฀1997฀Ezzat฀and฀Poggio฀working฀at฀ the฀ MIT฀ Center฀ for฀ Biological฀ and฀ Computational฀ Learning฀ created฀ a฀ system฀ called฀ Miketalk,฀which฀morphs฀between฀image฀keyframes,฀representing฀visemes,฀to฀create฀ speech฀animation.฀ Another฀form฀of฀animation฀from฀images฀consists฀of฀concatenating฀together฀sequences฀

computer฀vision

captured฀from฀video.฀In฀1997฀Bregler฀et฀al.฀described฀a฀technique฀called฀video-rewrite,฀

a฀branch฀of฀artificial฀

where฀ existing฀ footage฀ of฀ an฀ actor฀ is฀ cut฀ into฀ segments฀ corresponding฀ to฀ phonetic฀฀

intelligence฀that฀deals

units฀ which฀ are฀ blended฀ together฀ to฀ create฀ new฀ animations฀ of฀ a฀ speaker.฀ Video฀

with฀computer฀processing฀

-rewrite฀ uses฀ computer฀ vision฀ techniques฀ to฀ automatically฀ track฀ lip฀ movements฀ in฀

of฀images฀from฀the฀real฀

video฀ and฀ these฀ features฀ are฀ used฀ in฀ the฀ alignment฀ and฀ blending฀ of฀ the฀ extracted฀

world

phonetic฀ units.฀ This฀ animation฀ technique฀ only฀ generates฀ animations฀ of฀ the฀ lower฀ part฀of฀the฀face,฀these฀are฀then฀composited฀with฀video฀of฀the฀original฀actor฀to฀produce฀ the฀final฀animation.฀ 3D฀Animation Three-dimensional฀ head฀ models฀ provide฀ the฀ most฀ powerful฀ means฀ of฀ generating฀฀ computer฀facial฀animation.฀One฀of฀the฀earliest฀works฀on฀computerized฀head฀models฀ for฀graphics฀and฀animation฀was฀done฀by฀Parke.฀The฀model฀was฀a฀mesh฀of฀3D฀points฀ controlled฀ by฀ a฀ set฀ of฀ conformation฀ and฀ expression฀ parameters.฀ The฀ former฀ group฀฀ controls฀the฀relative฀location฀of฀facial฀feature฀points฀such฀as฀eye฀and฀lip฀corners.฀Changing฀ these฀parameters฀can฀re-shape฀a฀base฀model฀to฀create฀new฀heads.฀The฀latter฀group฀of฀ parameters฀(expression)฀are฀facial฀actions฀that฀can฀be฀performed฀on฀a฀face,฀such฀as฀ stretching฀lips฀or฀closing฀eyes.฀This฀model฀was฀extended฀by฀other฀researchers฀to฀include฀฀ more฀ facial฀ features฀ and฀ add฀ more฀ flexibility.฀ Different฀ methods฀ for฀ initializing฀฀ such฀“generic”฀models฀based฀on฀individual฀(3D฀or฀2D)฀data฀have฀been฀proposed฀and฀ successfully฀ implemented.฀ The฀ parameterized฀ models฀ are฀ effective฀ due฀ to฀ the฀ use฀ of฀limited฀parameters,฀associated฀with฀the฀main฀facial฀feature฀points.฀The฀MPEG-4฀ standard฀defines฀a฀minimum฀set฀of฀parameters฀for฀facial฀animation.฀ Animation฀is฀done฀by฀changing฀parameters฀over฀time.฀Facial฀animation฀is฀approached฀ in฀different฀ways.฀Traditional฀techniques฀include:฀ 1.฀ shapes/morph฀targets,฀ 2.฀ bones/cages,฀ 3.฀ skeleton-muscle฀systems,฀ 4.฀ motion฀capture฀on฀points฀on฀the฀face฀and฀

English++ 5.฀ knowledge฀based฀solver฀deformations.฀ ฀

1.฀ Shape฀ based฀ systems฀ offer฀ a฀ fast฀ playback฀ as฀ well฀ as฀ a฀ high฀ degree฀ of฀ fidelity฀ of฀ expressions.฀ The฀ technique฀ involves฀ modelling฀ portions฀ of฀ the฀ face฀ mesh฀ to฀฀ approximate฀expressions฀and฀visemes฀and฀then฀blending฀the฀different฀sub฀meshes,฀฀ known฀as฀morph฀targets฀or฀shapes.฀Perhaps฀the฀most฀accomplished฀character฀using฀฀ this฀technique฀was฀Gollum,฀from฀The฀Lord฀of฀the฀Rings.฀Drawbacks฀of฀this฀technique฀ are฀that฀they฀involve฀intensive฀manual฀labor,฀are฀specific฀to฀each฀character฀and฀ must฀be฀animated฀by฀slider฀parameter฀tables.฀

฀

2.฀‘Envelope฀Bones’฀or฀‘Cages’฀are฀commonly฀used฀in฀games.฀They฀produce฀simple฀ and฀fast฀models,฀but฀are฀not฀prone฀to฀portray฀subtlety.฀

฀

3.฀Skeletal฀Muscle฀systems,฀physically-based฀head฀models฀form฀another฀approach฀ in฀modelling฀the฀head฀and฀face.฀Here฀the฀physical฀and฀anatomical฀characteristics฀of฀ bones,฀tissues,฀and฀skin฀are฀simulated฀to฀provide฀a฀realistic฀appearance฀(e.g.฀spring-like฀฀ elasticity).฀Such฀methods฀can฀be฀very฀powerful฀for฀creating฀realism฀but฀the฀complexity฀฀ of฀facial฀structures฀make฀them฀computationally฀expensive฀and฀difficult฀to฀create.฀

alignment

Considering฀the฀effectiveness฀of฀parameterized฀models฀for฀communicative฀purposes฀฀

the฀adjustment฀

(as฀explained฀in฀the฀next฀section),฀it฀may฀be฀argued฀that฀physically-based฀models฀are฀

of฀an฀object฀in฀relation฀to฀

not฀a฀very฀efficient฀choice฀in฀many฀applications.฀This฀does฀not฀deny฀the฀advantages฀

other฀objects,฀or฀a฀static฀

of฀physically-based฀models฀or฀the฀fact฀that฀they฀can฀even฀be฀used฀within฀the฀context฀

orientation฀of฀some฀

of฀parameterized฀models฀to฀provide฀local฀details฀when฀needed.฀Waters,฀Terzopoulos,฀

object฀or฀set฀of฀objects฀

Kahler,฀and฀Seidel฀(among฀others)฀have฀developed฀physically-based฀facial฀animation฀systems.฀

in฀relation฀to฀others฀ ฀

4.฀Motion฀capture฀uses฀cameras฀placed฀around฀a฀subject.฀The฀subject฀is฀generally฀฀ fitted฀either฀with฀reflectors฀(passive฀motion฀capture)฀or฀sources฀(active฀motion฀capture)฀฀ that฀precisely฀determine฀the฀subject’s฀position฀in฀space.฀The฀data฀recorded฀by฀the฀ cameras฀is฀then฀digitized฀and฀converted฀into฀a฀three-dimensional฀computer฀model฀ of฀ the฀ subject.฀ Until฀ recently,฀ the฀ size฀ of฀ the฀ detectors/sources฀ used฀ by฀ motion฀ capture฀systems฀made฀the฀technology฀inappropriate฀for฀facial฀capture.฀However,฀฀ miniaturization฀and฀other฀advancements฀have฀made฀motion฀capture฀a฀viable฀tool฀ for฀ computer฀ facial฀ animation.฀ Facial฀ motion฀ capture฀ was฀ used฀ extensively฀ in฀฀ Polar฀ Express,฀ where฀ hundreds฀ of฀ motion฀ points฀ were฀ captured.฀ This฀ film฀ was฀ very฀ accomplished฀ and฀ while฀ it฀ attempted฀ to฀ recreate฀ realism,฀ it฀ was฀ criticised฀ for฀having฀fallen฀in฀the฀‘uncanny฀valley’,฀the฀realm฀where฀animation฀realism฀is฀ sufficient฀for฀human฀recognition฀but฀fails฀to฀convey฀the฀emotional฀message.฀The฀ main฀difficulties฀of฀motion฀capture฀are฀the฀quality฀of฀the฀data฀which฀may฀include฀ vibration฀as฀well฀as฀the฀retargeting฀of฀the฀geometry฀of฀the฀points.฀

฀

5.฀Deformation฀Solver฀Face฀Robot.฀

English++ Speech Animation Speech฀is฀usually฀treated฀in฀a฀different฀way฀to฀the฀animation฀of฀facial฀expressions;฀ this฀is฀because฀simple฀keyframe-based฀approaches฀to฀animation฀typically฀provide฀a฀ poor฀approximation฀to฀real฀speech฀dynamics.฀Often฀visemes฀are฀used฀to฀represent฀ the฀key฀poses฀in฀observed฀speech฀(i.e.฀the฀position฀of฀the฀lips,฀jaw฀and฀tongue฀when฀

motion฀capture

producing฀a฀particular฀phoneme);฀however,฀there฀is฀a฀great฀deal฀of฀variation฀in฀the฀

a฀technique฀of฀recording฀

realisation฀of฀visemes฀during฀the฀production฀of฀natural฀speech.฀The฀source฀of฀this฀

the฀actions฀of฀human฀

variation฀ is฀ termed฀ coarticulation,฀ which฀ is฀ the฀ influence฀ of฀ surrounding฀ visemes฀

actors฀and฀using฀that฀

upon฀ the฀ current฀ viseme฀ (i.e.฀ the฀ effect฀ of฀ context.)฀ To฀ account฀ for฀ coarticulation,฀

information฀to฀animate฀

current฀ systems฀ either฀ explicitly฀ take฀ into฀ account฀ context฀ when฀ blending฀ viseme฀

digital฀character฀models฀

keyframes฀or฀use฀longer฀units฀such฀as฀diphone,฀triphone,฀syllable฀or฀even฀word฀and฀

in฀3D฀animation฀

sentence-length฀units.฀ One฀of฀the฀most฀common฀approaches฀to฀speech฀animation฀is฀the฀use฀of฀dominance฀ functions฀introduced฀by฀Cohen฀and฀Massaro.฀Each฀dominance฀function฀represents฀the฀ influence฀over฀time฀that฀a฀viseme฀has฀on฀a฀speech฀utterance.฀Typically฀the฀influence฀฀ will฀be฀greatest฀at฀the฀center฀of฀the฀viseme฀and฀will฀degrade฀with฀distance฀from฀the฀viseme฀฀ center.฀ Dominance฀ functions฀ are฀ blended฀ together฀ to฀ generate฀ a฀ speech฀ trajectory฀฀ in฀much฀the฀same฀way฀that฀spline฀basis฀functions฀are฀blended฀together฀to฀generate฀ a฀curve.฀The฀shape฀of฀each฀dominance฀function฀will฀be฀different฀according฀to฀both฀ which฀viseme฀it฀represents฀and฀฀which฀aspect฀of฀the฀face฀is฀being฀controlled฀(e.g.฀lip฀ width,฀jaw฀rotation฀etc.)฀This฀approach฀to฀computer-generated฀speech฀animation฀can฀ be฀seen฀in฀the฀Baldi฀talking฀head.฀ Other฀ models฀ of฀ speech฀ use฀ basis฀ units฀ which฀ include฀ context฀ (e.g.฀ diphones,฀฀ triphones฀etc.)฀instead฀of฀visemes.฀As฀the฀basis฀units฀already฀incorporate฀the฀variation฀฀ of฀each฀viseme฀according฀to฀context฀and฀to฀some฀degree฀the฀dynamics฀of฀each฀viseme,฀no฀ model฀of฀coarticulation฀is฀required.฀Speech฀is฀simply฀generated฀by฀selecting฀appropriate฀฀ units฀from฀a฀database฀and฀blending฀the฀units฀together.฀This฀is฀similar฀to฀concatenative฀฀ techniques฀in฀audio฀speech฀synthesis.฀The฀disadvantage฀to฀these฀models฀is฀that฀a฀large฀ amount฀ of฀ captured฀ data฀ is฀ required฀ to฀ produce฀ natural฀ results,฀ and฀ whilst฀ longer฀฀

texture

units฀produce฀more฀natural฀results,฀the฀size฀of฀database฀required฀expands฀with฀the฀

a฀bitmap฀image฀

average฀length฀of฀each฀unit.฀

applied฀to฀a฀surface฀

Finally,฀some฀models฀directly฀generate฀speech฀animations฀from฀audio.฀These฀systems฀

in฀computer฀graphics฀

typically฀use฀hidden฀Markov฀models฀or฀neural฀nets฀to฀transform฀audio฀parameters฀ into฀a฀stream฀of฀control฀parameters฀for฀a฀facial฀model.฀

English++

Exercises Pre-reading questions 1.฀฀Students฀are฀given฀pictures฀of฀human฀faces฀and฀try฀to฀guess฀what฀emotions฀they฀฀ ฀฀฀฀฀show. 2.฀ What฀is฀the฀number฀of฀facial฀muscles?฀ •฀ 48฀ 3.฀ Why฀are฀facial฀expressions฀so฀important฀in฀our฀lives?฀ •฀ Gestures฀and฀facial฀expressions฀in฀general฀mean฀more฀than฀words฀or฀sentences.฀ 4.฀ Where฀can฀facial฀animations฀be฀used?฀ •฀ In฀ cartoons,฀ 3D฀ rendered฀ films฀ (like฀ Toy฀ Story,฀ Shrek)฀ and฀ in฀ computer฀ games.฀ Facial฀animation฀is฀constantly฀improving฀and฀in฀a฀couple฀of฀years฀it฀will฀be฀hard฀to฀ distinguish฀between฀a฀real฀actor฀and฀a฀virtual฀one.฀ 5.฀ What฀is฀the฀rendering฀process฀in฀computer฀graphics?฀What฀is฀the฀motion฀capture฀ technique?฀ •฀ Rendering:฀all฀of฀the฀methods฀used฀to฀make฀a฀picture฀using฀a฀computer.฀It฀involves฀ maths฀calculations,฀data฀loading฀and฀so฀on.฀ •฀ Motion฀capture฀is฀a฀technique฀used฀to฀obtain฀realistic฀animated฀movement.฀An฀฀ actor฀wears฀a฀special฀outfit฀with฀a฀number฀of฀sensors.฀When฀he฀moves,฀a฀computer฀ captures฀all฀the฀necessary฀movement฀data.฀

Comprehension questions 1.฀ How฀would฀you฀define฀facial฀animation?฀ •฀ Area฀of฀computer฀graphics฀that฀encapsulates฀models฀and฀techniques฀for฀generating฀฀ and฀animating฀images฀of฀the฀human฀head฀and฀face.฀ 2.฀ What฀is฀FACS?฀ •฀ Facial฀Action฀Coding฀System฀-฀defines฀64฀basic฀facial฀Action฀Units฀which฀represent฀ primitive฀movements฀of฀muscles฀in฀actions,฀e.g.฀raising฀brows,฀talking.฀ 3.฀ What฀was฀Michael฀Jackson’s฀contribution฀to฀computer฀animation?฀ •฀ His฀video฀of฀the฀song฀“Black฀Or฀White”฀was฀the฀first฀to฀use฀image฀morphing฀animation.฀฀ The฀video฀showed฀a฀lot฀of฀human฀faces฀which฀are฀morphed฀from฀one฀to฀another.฀ 4.฀ What฀can฀2D฀animation฀be฀based฀on:฀images฀from฀still฀photography฀or฀ ฀

sequences฀of฀video?฀

•฀ Both.฀ There฀ are฀ methods฀ for฀ animating฀ still฀ images฀ and฀ others฀ for฀ animating฀฀ sequences฀of฀video.฀ 5.฀ What฀is฀the฀most฀realistic฀method฀of฀3D฀animation?฀What฀makes฀it฀so฀good?฀ •฀ The฀skeleton-muscle฀system.฀It฀is฀so฀effective฀because฀the฀method฀tries฀to฀imitate฀ human฀ head฀ muscles,฀ skin฀ and฀ bones.฀ It฀ is฀ very฀ complicated฀ to฀ build฀ a฀ model฀ consistent฀with฀this฀method฀but฀the฀effects฀are฀breathtaking.฀It฀cannot฀be฀used฀

English++ in฀computer฀games฀or฀on-line฀animation฀because฀of฀its฀complexity฀but฀is฀great฀for฀ high-budget฀films.฀ 6.฀ How฀does฀motion฀capture฀work?฀ •฀ The฀subject฀is฀fitted฀with฀reflectors฀or฀sources฀that฀precisely฀determine฀its฀position฀฀ in฀ space.฀ Every฀ movement฀ of฀ the฀ sensor฀ is฀ recorded฀ and฀ then฀ retraced฀ on฀ the฀ model.฀It’s฀very฀realistic฀but฀there฀are฀also฀some฀disadvantages฀like฀vibrations฀of฀ sensors฀causing฀disturbances.฀ 7.฀ How฀are฀visemes฀used฀in฀speech฀animation?฀ •฀ Visemes฀are฀movements฀of฀lips฀and฀mouth฀muscles฀performed฀during฀speaking.฀ Visemes฀are฀used฀to฀represent฀key฀poses฀in฀observed฀speech.฀(position฀of฀lips,฀jaw,฀ tongue).฀

Possible topics for discussion 1.฀ How฀do฀you฀see฀the฀future฀of฀facial฀animation? 2.฀ Think฀of฀your฀favourite฀computer฀animated฀character.฀Try฀to฀name฀the฀techniques฀ used฀to฀create฀it. 3.฀ Is฀it฀probable฀that฀facial฀animation฀will฀achieve฀such฀a฀level฀of฀sophistication฀that฀ it฀will฀be฀impossible฀to฀distinguish฀real฀faces฀from฀virtual฀ones?฀

Possible difﬁculties The฀text฀contains฀professional฀vocabulary฀items.฀Some฀of฀them฀are฀explained.฀

English++

An Introduction to the Modelling of Real-World Problems by the Simplest Ordinary Differential Equations* Stanisław Migórski ฀

Number฀of฀words฀฀

฀

Computer฀science฀content฀฀

Low฀

฀

Math฀content฀฀

High฀

฀

English฀language฀complexity฀฀ Medium฀

฀

9100฀฀

Sub-areas covered •฀ ฀Calculus •฀ ฀Ordinary฀differential฀equations •฀ ฀Modelling฀

Learning objectives •฀ to฀understand฀the฀relations฀between฀math฀and฀real-world฀phenomena •฀ to฀show฀how฀mathematical฀descriptions฀of฀฀real-world฀phenomena฀are฀created฀

Keywords ODE฀ -฀ ordinary฀ differential฀ equation฀ -฀ a฀ relation฀ that฀ contains฀ functions฀ of฀ only฀ one฀฀ independent฀variable,฀and฀one฀or฀more฀of฀its฀derivatives฀with฀respect฀to฀that฀variable฀ interval฀-฀฀a฀set฀of฀real฀numbers฀with฀the฀property฀that฀any฀number฀that฀lies฀between฀two฀฀ numbers฀in฀the฀set฀is฀also฀included฀in฀the฀set.฀For฀example,฀the฀set฀of฀all฀numbers฀ x฀satisfying฀0฀ ฀x฀ ฀1฀is฀an฀interval฀which฀contains฀0฀and฀1,฀as฀well฀as฀all฀numbers฀ between฀them.฀The฀set฀of฀positive฀numbers฀is฀also฀an฀interval.฀ differentiable฀function฀-฀a฀real฀function฀is฀said฀to฀be฀differentiable฀at฀a฀point฀if฀its฀ derivative฀exists฀at฀that฀point฀

*฀ This฀ work฀ was฀ prepared฀ as฀ part฀ of฀ the฀ English++฀ project฀ carried฀ out฀ by฀ students฀ of฀ the฀฀ Institute฀of฀Computer฀Science,฀Jagiellonian฀University,฀Kraków฀in฀the฀academic฀year฀2007–2008.฀ *฀The฀author฀is฀grateful฀for฀the฀encouragement฀he฀received฀from฀the฀students฀and฀Faculty฀at฀ the฀Jagiellonian฀University.฀His฀special฀thanks฀go฀to฀Monika฀Stawicka,฀who฀through฀her฀untiring฀฀

efforts฀and฀devotion฀to฀duty฀convinced฀him฀to฀join฀the฀project.

English++ separable฀differential฀equation฀-฀a฀class฀of฀equations฀that฀can฀be฀separated฀into฀a฀pair฀฀ of฀integrals฀ autonomous฀differential฀equation฀-฀a฀system฀of฀ordinary฀differential฀equations฀which฀฀ does฀not฀depend฀on฀the฀independent฀variable฀ homogeneous฀ linear฀ differential฀ equation฀ -฀ a฀ differential฀ equation฀ is฀ said฀ to฀ be฀฀ homogeneous฀if฀there฀is฀no฀isolated฀constant฀term฀in฀the฀equation,฀e.g.,฀each฀term฀ in฀a฀differential฀equation฀for฀y฀has฀y฀or฀some฀derivative฀of฀y฀in฀each฀term฀ IVP฀(initial฀value฀problem)฀or฀Cauchy฀problem฀-฀an฀ordinary฀differential฀equation฀฀ together฀with฀specified฀value,฀called฀the฀initial฀condition,฀of฀the฀unknown฀function฀฀ at฀a฀given฀point฀in฀the฀domain฀of฀the฀solution฀ general฀solution฀-฀a฀general฀solution฀of฀a฀differential฀equation฀is฀the฀set฀of฀all฀of฀its฀ particular฀solutions,฀often฀expressed฀using฀constants,฀which฀could฀have฀any฀fixed฀ value฀฀ model฀for฀the฀system฀-฀a฀set฀of฀differential฀equations฀describing฀the฀behaviour฀of฀a฀ system rate฀of฀change฀-฀an฀indicator฀showing฀the฀difference฀between฀parameters฀in฀a฀specific฀฀ unit฀of฀time

Summary In฀ this฀ note฀ we฀ present฀ several฀ simple฀ ordinary฀ differential฀ equations฀ ฀ modeling฀฀ selected฀real-world฀phenomena฀met฀in฀physics,฀archeology,฀art฀forgeries,฀population฀ dynamics,฀heat฀radiation,฀epidemiology฀and฀economics.฀ Niniejszy฀tekst฀jest฀wstępem฀do฀problematyki฀równań฀różniczkowych฀zwyczajnych.฀ Zawiera฀definicje฀podstawowych฀pojęć฀potrzebnych฀do฀zrozumienia฀tematu.฀Pokazuje฀ jak฀ sprowadzić฀ dany฀ problem฀ z฀ życia฀ codziennego฀ do฀ modelu฀ matematycznego,฀ co฀ jest฀zilustrowane฀prostym,฀ciekawym฀przykładem.฀Tekst฀składa฀się฀z฀wybranych฀fragmentów,฀szerszego฀opracowania฀profesora฀Stanislawa฀Migórskiego.฀

Pre-reading questions 1.฀฀Do฀you฀know฀how฀to฀build฀a฀mathematical฀model? 2.฀฀Do฀you฀think฀that฀theoretical฀mathematical฀models฀can฀be฀applied฀to฀solve฀practical฀problems?

English++ 1 Introduction and preliminary terminology autonomous฀

This฀note฀is฀a฀preliminary฀version฀of฀a฀self-contained฀introduction฀to฀the฀modeling฀

differential฀equation฀

of฀selected฀real-life฀phenomena฀by฀simple฀ordinary฀differential฀equations.We฀restrict฀

-฀฀a฀system฀of฀ordinary฀

ourselves฀to฀a฀discussion฀on฀first฀order฀ordinary฀differential฀equations,฀leaving฀the฀฀

differential฀equations฀

details฀ on฀ models฀ described฀ by฀ higher฀ order฀ equations฀ and฀ systems฀ of฀ first-order฀฀

which฀does฀not฀depend฀ on฀the฀independent฀ variable฀

equations฀to฀the฀sequel฀of฀the฀present฀work.฀ The฀ text฀ was฀ designed฀ for฀ computer฀ science฀ students฀ who฀ have฀ a฀ calculus฀ back฀ ground1฀and฀have฀taken฀prior฀physics฀courses฀(cf.฀[4]).฀It฀is฀our฀belief฀that฀computer฀ science฀students฀should฀know฀how฀to฀model฀a฀selected฀problem,฀particularly฀in฀light฀

interval

of฀rapidly฀changing฀technologies.฀We฀begin฀with฀preliminary฀notations฀and฀defnitions.฀

a฀set฀of฀real฀numbers฀

By฀a฀differential฀equation฀we฀mean฀a฀mathematical฀equation฀involving฀an฀unknown฀

with฀the฀property฀

function฀of฀one฀or฀several฀variables฀and฀its฀derivatives฀of฀various฀orders.฀The฀order฀of฀

that฀any฀number฀

the฀differential฀equation฀is฀the฀order฀of฀the฀highest฀derivative฀of฀the฀unknown฀function฀

that฀lies฀between฀

involved฀in฀the฀equation.฀For฀instance,฀the฀equation฀

two฀numbers฀in฀the฀set฀is฀ also฀included฀in฀the฀set.฀

฀

x’฀=฀f(t,฀x)฀฀

฀

(1)฀

For฀example,฀

is฀called฀an฀ordinary฀differential฀equation฀(often฀abbreviated฀to฀ODE)฀of฀first฀order2฀

the฀set฀of฀all฀numbers฀x฀

in฀the฀normal฀form.฀It฀relates฀an฀independent฀variable฀t฀to฀an฀unknown฀function฀x฀

satisfying฀ 0฀฀ ฀x฀ ฀1฀is฀

and฀its฀first฀order฀derivative.฀The฀function฀f฀is฀given฀f:฀I฀×E฀

฀E,฀where฀I฀is฀an฀interval3฀฀

and฀E฀is฀a฀prescribed฀space฀and฀we฀are฀looking฀for฀a฀function฀x:฀I฀

฀E.฀Of฀course฀the฀

an฀interval฀which฀contains฀

equation฀(1)฀obliges฀the฀unknown฀function฀x฀to฀have฀some฀restrictions:฀it฀should฀be฀

0฀and฀1,฀as฀well฀as฀

differentiable฀in฀a฀suitable฀sense฀and฀the฀compose฀function฀f(t,฀x(t))฀should฀have฀a฀

all฀numbers฀between฀ them.฀The฀set฀of฀ positive฀numbers฀is฀also฀ an฀interval฀

meaning.฀Classically,฀we฀admit฀the฀following฀ Definition฀1฀A฀function฀x:฀I฀

฀E฀is฀called฀a฀solution฀of฀the฀equation฀(1)฀on฀the฀interval฀I,฀

if฀x฀ ฀C1(I,E)4฀and฀x’(t)฀=฀f(t,฀x(t))฀for฀all฀t฀ ฀I.฀ Remark฀2฀We฀remark฀that฀if฀f:฀I×E฀ that฀a฀solution฀x:฀I฀

฀E฀is฀a฀continuous฀function,฀we฀may฀require฀฀

฀฀E฀is฀only฀differentiable.฀This฀follows฀from฀the฀observation฀that฀

in฀this฀case฀the฀composition฀of฀continuous฀functions฀f(t,฀·)฀and฀x(·)฀is฀continuous฀and฀ it฀is฀equal฀to฀x’(·).฀Hence฀x’฀is฀continuous฀on฀I฀and฀thus฀x฀is฀a฀solution.฀ differentiable฀function a฀real฀function฀is฀said฀ to฀be฀differentiable฀at฀a฀

If฀the฀right฀hand฀side฀of฀the฀equation฀(1)฀can฀be฀expressed฀as฀a฀product฀g(t)h(x)฀where฀g฀ depends฀only฀on฀t฀and฀h฀depends฀only฀on฀x,฀then฀the฀differential฀equation฀(1)฀is฀called

point฀if฀its฀derivative฀ exists฀at฀that฀point฀

1฀ Some฀ universities,฀ the฀ Jagiellonian฀ among฀ them,฀ make฀ linear฀ algebra฀ a฀ prerequisite฀ for฀฀

differential฀equations.฀Many฀schools,฀especially฀engineering,฀only฀require฀calculus.฀ 2฀฀The฀most฀general฀(implicit)฀form฀of฀an฀ordinary฀differential฀equation฀of฀the฀first-order฀is฀as฀

follows:฀F(t,฀x,฀x’)฀=฀0฀with฀a฀prescribed฀function฀F.฀

3฀฀The฀interval฀I฀may฀have฀a฀form฀[a,฀b],฀[a,฀b),฀(a,฀b],฀(a,฀b),฀(-฀

,฀b]฀and฀[a,+ ).฀

4฀฀A฀function฀x:฀I฀–›฀E฀is฀C1,฀if฀x฀is฀differentiable฀on฀I฀and฀its฀derivative฀x’฀is฀a฀continuous฀function.

English++ separable.฀ If฀ the฀ right฀ hand฀ side฀ f฀ is฀ independent฀ of฀ t,฀ then฀ the฀ resulting฀ differential฀฀ equation฀is฀called฀autonomous.฀Every฀autonomous฀differential฀equation฀is฀separable.฀

initial฀value฀problem฀

When฀the฀function฀f฀in฀(1)฀is฀(affine)฀linear฀with฀respect฀to฀the฀second฀variable,฀the฀first฀฀

(IVP)฀

order฀equation฀of฀the฀form฀x’฀=฀α(t)x฀+฀β(t)฀with฀prescribed฀functions฀α and฀β฀is฀called฀฀

an฀ordinary฀differential฀

a฀nonhomogeneous฀linear฀differential฀equation.฀If฀β=฀0,฀then฀the฀equation฀x=α(t)x฀฀

equation฀together฀with฀

with฀a฀prescribed฀function฀α฀is฀called฀a฀homogeneous฀linear฀differential฀equation.฀

specified฀value,฀called฀the฀

Definition฀3฀Let฀t0฀ ฀I฀and฀x0฀ ฀E.฀A฀problem฀in฀which฀we฀are฀looking฀for฀the฀unknown฀ function฀x:฀I฀

฀E฀of฀a฀differential฀equation฀(1)฀where฀the฀value฀of฀the฀unknown฀function฀฀

at฀some฀point฀is฀known฀x(t0)฀=฀x0฀5฀is฀called฀an฀initial฀value฀problem฀(in฀short฀IVP)฀or฀ a฀Cauchy6฀problem฀for฀(1).฀

initial฀condition,฀ of฀the฀unknown฀function฀ at฀a฀given฀point฀in฀ the฀domain฀of฀the฀ solution฀

Analogously฀as฀above,฀we฀have฀ Definition฀4฀Let฀t0฀ ฀I฀and฀x0฀ ฀E.฀We฀say฀that฀a฀function฀x:฀I฀

฀

฀E฀is฀a฀solution฀of฀the฀IVP฀

x’฀=฀f(t,฀x)฀ x(t0)฀=฀x0฀

if฀x฀is฀a฀solution฀to฀equation฀(1)฀on฀the฀interval฀I฀and฀it฀satisfies฀x(t0)฀=฀x0.฀

Cauchy฀problem see฀IVP

Sometimes฀if฀no฀initial฀condition฀is฀given,฀we฀call฀the฀family฀of฀all฀solutions฀to฀the฀ differential฀equation฀(1)฀the฀general฀solution.฀

2 Modelling “How฀do฀we฀translate฀a฀physical฀phenomenon฀into฀a฀set฀of฀equations฀which฀describes฀ it?”฀–฀this฀is฀certainly฀one฀of฀the฀most฀difficult฀problems฀that฀scientists฀deal฀with฀in฀their฀฀ everyday฀ research.฀ This฀ problem฀ is฀ a฀ difficult฀ one฀ since฀ it฀ is฀ usually฀ impossible฀ to฀฀ describe฀a฀phenomenon฀totally,฀so฀one฀often฀tries฀to฀reformulate฀a฀real-world฀problem฀฀ as฀ a฀ mathematical฀ one฀ making฀ certain฀ simplyfying฀ assumptions.฀ As฀ a฀ result฀ one฀฀ usually฀describes฀the฀system฀approximately฀and฀adequately.฀

฀ general฀solution a฀general฀solution฀ of฀a฀differential฀equation฀ is฀the฀set฀of฀all฀of฀its฀ particular฀solutions,฀ often฀expressed฀using฀

The฀ problem฀ of฀ generating฀ “good”฀ equations฀ is฀ not฀ an฀ easy฀ task.฀ The฀ set฀ of฀฀

constants฀which฀could฀

equations฀one฀deals฀with฀is฀called฀a฀model฀for฀the฀system.฀In฀general,฀once฀we฀have฀

have฀any฀fixed฀value.฀฀

built฀a฀set฀of฀equations,฀we฀compare฀the฀data฀generated฀by฀the฀equations฀with฀real฀data฀฀

(Source:฀http://math.uww.

collected฀from฀the฀system฀(by฀measurement).฀When฀the฀two฀sets฀of฀data฀“agree”฀(or฀are฀฀

edu/~mcfarlat/250dej.

“sufficiently”฀close),฀we฀gain฀confidence฀that฀the฀set฀of฀equations฀will฀lead฀to฀a฀good฀de-

htm฀)

scription฀of฀the฀real-world฀system.฀If฀a฀prediction฀from฀the฀equations฀leads฀to฀some฀conclusions฀which฀are฀by฀no฀means฀close฀to฀real-world฀future฀behavior,฀we฀should฀modify฀฀ and฀“correct”฀the฀underlying฀equations.฀When฀creating฀a฀model,฀it฀is฀necessary฀to฀formulate฀฀ the฀problem฀under฀consideration฀into฀questions฀that฀can฀be฀answered฀mathematically.฀ 5฀฀This฀condition฀is฀called฀an฀initial฀condition.฀ 6฀฀Augustin฀Louis฀Cauchy฀(1789–1857),฀a฀French฀mathematician.฀

English++ The฀following฀are฀basic฀steps฀in฀building฀a฀model.฀ separable฀ differential฀equation a฀class฀of฀equations฀that฀ can฀be฀separated฀into ฀a฀pair฀of฀integrals฀

(1)฀Clearly฀state฀the฀assumptions฀on฀which฀the฀model฀will฀be฀based.฀These฀assumptions฀฀ should฀describe฀the฀relationships฀between฀the฀quantities฀to฀be฀studied.฀ (2)฀Completely฀describe฀the฀parameters฀and฀variables฀to฀be฀used฀in฀the฀model.฀ (3)฀Use฀the฀assumptions฀(from฀step฀(1))฀to฀derive฀mathematical฀equations฀relating฀the฀ parameters฀and฀variables฀(from฀step฀(2)).฀ A฀large฀number฀of฀laws฀of฀physics,฀chemistry,฀economics,฀medicine,฀etc.฀can฀be฀for-฀ mulated฀as฀differential฀equations.฀They฀serve฀as฀models฀that฀describe฀the฀behavior฀of฀ complex฀systems.฀The฀mathematical฀theory฀of฀differential฀equations฀first฀developed฀

homogeneous฀ linear฀differential฀฀ equation a฀differential฀equation฀ is฀said฀to฀be฀homogeneous฀ if฀there฀is฀no฀isolated฀ constant฀term฀

together฀with฀the฀sciences฀where฀the฀equations฀had฀originated฀and฀where฀the฀results฀ found฀application.฀Whenever฀a฀mathematical฀model฀involves฀the฀rate฀of฀change฀of฀ one฀variable฀with฀respect฀to฀another,฀a฀differential฀equation฀is฀apt฀to฀appear.฀As฀we฀ will฀see฀in฀the฀following฀sections,฀diverse฀problems,฀sometimes฀originating฀in฀quite฀ distinct฀scientific฀fields,฀may฀give฀rise฀to฀identical฀differential฀equations.฀Whenever฀this฀ happens,฀the฀mathematical฀theory฀behind฀the฀equations฀can฀be฀viewed฀as฀a฀unifying฀ principle฀behind฀diverse฀phenomena.฀

in฀the฀equation,฀e.g.,฀each฀

In฀the฀following฀sections฀we฀provide฀examples฀of฀mathematical฀models฀of฀several฀฀rela-

term฀in฀a฀differential฀

tively฀simple฀phenomena฀which฀are฀described฀by฀ordinary฀differential฀equations฀of฀the฀

equation฀for฀y฀has฀y฀or฀

form฀(1).฀We฀mainly฀concentrate฀on฀modeling฀issues.฀The฀modern฀theory฀of฀ordinary฀฀

some฀derivative฀of฀y฀in฀

differential฀ equations฀ together฀ with฀ known฀ techniques,฀ methods฀ and฀ applications฀

each฀term฀

can฀be฀found฀in฀references฀[1]฀and฀[2].฀

3 Radioactive decay ODE ordinary฀differential฀฀ equation฀฀ -฀a฀relation฀that฀฀ contains฀functions฀of฀

It฀is฀known฀that฀for฀many฀radioactive฀materials,฀for฀small฀amounts฀of฀the฀substance฀ and฀in฀a฀short฀time฀interval,฀the฀amount฀of฀disintegrated฀mass฀is฀proportional฀to฀the฀ length฀of฀the฀time฀interval฀and฀the฀amount฀of฀radioactive฀mass.฀Assuming฀that฀the฀ amount฀of฀the฀material฀changes฀in฀time฀continuously,฀find฀the฀dependence฀of฀radioactive฀mass฀on฀time.฀

only฀one฀independent฀

Radioactive฀decay฀is฀the฀process฀in฀which฀an฀unstable฀atomic฀nucleus฀loses฀energy฀

variable,฀and฀one฀or฀

by฀emitting฀radiation฀in฀the฀form฀of฀particles฀or฀electromagnetic฀waves.฀We฀denote฀

more฀of฀its฀derivatives฀

the฀time฀by฀t฀and฀the฀amount฀of฀radioactive฀substance฀by฀m(t).฀We฀will฀show฀that฀

with฀respect฀to฀that฀

the฀mass฀m(t)฀is฀described฀by฀the฀following฀ordinary฀differential฀equation฀of฀the฀first฀

variable฀

order฀ ฀

฀

m’(t)=-km(t).฀฀

฀

Let฀∆t฀ ฀0฀be฀the฀length฀of฀a฀time฀interval.฀Then฀we฀can฀write฀

฀

฀฀฀฀฀฀฀m(t฀+∆t)฀-฀m(t)฀฀฀฀฀฀~฀฀฀m(t)฀∆t. amount฀of฀disintegrated฀mass

฀

(2)฀฀

English++ We฀ denote฀ by฀ k฀ a฀ positive฀ constant฀ being฀ the฀ proportionality฀ coefficient฀ which฀฀ characterizes฀the฀radioactive฀material.฀Since฀the฀rate฀of฀change฀of฀m(t)฀with฀respect฀to฀ time฀t฀is฀negative฀(the฀amount฀of฀mass฀decreases฀in฀time),฀we฀obtain฀m(t฀+∆฀t)฀-฀m(t)฀ =฀-km(t)∆t฀and฀

model฀for฀the฀system

m(t฀+∆t)฀-฀m(t)฀ ฀ =฀-km(t). ∆t฀ ฀฀฀฀฀฀฀฀฀฀฀ Since฀ the฀ amount฀ of฀ the฀ material฀ changes฀ in฀ time฀ continuously7,฀ this฀ leads฀ to฀ the฀

A฀set฀of฀differential฀ equations฀describing฀ the฀behaviour฀of฀a฀system฀

equation฀ ฀m(t฀+∆t)฀-฀m(t)฀ ฀ =฀-km(t). ∆t฀ ฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀ which฀means฀that฀the฀rate฀of฀decay฀is฀proportional฀to฀the฀amount฀of฀the฀substance฀ m’(t)฀=฀lim฀฀ ∆t฀–›฀฀0฀฀

฀

present.฀The฀mass฀m฀is฀the฀unknown฀function฀to฀be฀determinated.฀The฀equation฀฀ ฀฀

฀

m’(t)฀=฀-km(t)฀฀฀ ฀

฀

(3)

rate฀of฀change an฀indicator฀showing฀ the฀difference฀between฀

is฀called฀the฀equation฀of฀radioactive฀decay.฀It฀is฀a฀linear฀homogeneous฀differential฀฀

parameters฀in฀a฀specific฀

equation.฀

unit฀of฀time

Assuming฀that฀the฀mass฀is฀positive,฀we฀can฀solve฀(3)฀as฀follows.฀We฀observe฀that฀the฀ equality฀

=-k฀฀is฀equivalent฀to฀฀

(ln฀m(t))฀=฀-k.฀Integrating฀the฀latter,฀we฀have฀

ln฀m(t)฀=฀-kt฀+฀C1,฀where฀C1฀is฀a฀constant฀of฀integration.฀Hence,฀ ฀฀

฀

m(t)฀=฀e-kt+C1฀=฀e-kteC1฀=฀Ce-kt฀

with฀a฀positive฀constant฀C.฀ Furthermore,฀we฀remark8฀that฀every฀function฀m(t)฀=฀Ce-kt฀with฀C฀ ฀R฀is฀a฀solution฀to฀ the฀differential฀equation฀m’(t)฀=-km(t)9.฀The฀value฀of฀C฀is฀determined฀if฀the฀initial฀ amount฀of฀radioactive฀substance฀is฀given.฀It฀can฀be฀found฀without฀difficulty10฀that฀if฀ m(t0)฀=฀m0,฀m0฀denotes฀the฀initial฀amount฀of฀substance฀at฀time฀instant฀t0,฀then฀the฀ value฀of฀C฀can฀be฀found฀and฀the฀Cauchy฀problem฀ m’(t)฀=฀km(t)

฀

m(t0)฀=฀m0

admits฀a฀unique฀solution฀of฀the฀form฀ ฀

฀

m(t)฀=฀m0e-k(t-t0).฀฀฀

฀

(4)฀

After฀taking฀into฀account฀the฀“real”฀constraints฀on฀the฀problem฀under฀consideration,฀this฀ solution฀gives฀a฀formula฀for฀the฀amount฀of฀radioactive฀substance฀at฀any฀future฀฀time฀t.฀

7฀In฀fact,฀we฀assume฀that฀the฀derivative฀m’(t)฀exists฀at฀every฀time฀instant฀t.฀ 8฀We฀cannot฀expect฀to฀get฀a฀unique฀solution,฀since฀there฀will฀be฀an฀arbitrary฀“constant฀of฀฀฀฀

฀฀฀integration”.฀ 9฀So฀there฀are฀infinitely฀many฀solutions฀to฀this฀ODE.฀ 10฀This฀is฀left฀to฀the฀reader.฀

English++ Summing฀up,฀we฀have฀the฀implication฀ ฀

฀

if฀a฀function฀m(·)฀describes฀the฀radioactive฀decay,฀then฀

฀

the฀function฀m(·)฀satisfies฀the฀differential฀equation฀(3).฀

The฀converse฀does฀not฀hold฀because฀there฀are฀solutions฀which฀do฀not฀have฀a฀physical฀ meaning.฀For฀example,฀m(t)฀=฀-e-kt฀is฀a฀solution฀which฀is฀not฀acceptable฀(mass฀can฀not฀ 10

be฀negative)฀or฀m(t)฀=฀1010 ฀e-kt฀solves฀the฀equation฀but฀the฀mass฀is฀too฀large฀to฀exist฀ on฀Earth.฀In฀consequence,฀there฀are฀physical฀reasons฀which฀eliminate฀some฀solutions฀ to฀the฀equation,฀i.e.฀for฀the฀solution฀to฀make฀sense฀we฀suppose฀that฀ ฀

฀

0฀ ฀m0฀ ฀mcrit

where฀ mcrit฀ denotes฀ the฀ critical฀ mass฀ of฀ radioactive฀ material.฀ Then,฀ we฀ clearly฀ get฀฀ that฀0฀ ฀m(t)฀ ฀mcrit฀for฀all฀t฀ ฀t0. Despite฀the฀physical฀aspects,฀the฀following฀question฀arises.฀Do฀any฀other฀solutions฀฀to฀ the฀equation฀of฀radioactive฀decay฀exist?฀The฀answer฀is฀negative.฀ Remark฀ 5฀ All฀ solutions฀ to฀ the฀ equation฀ m’(t)=฀ -km(t)฀ have฀ the฀ form฀ m(t)฀ =฀ Ce-kt฀

with฀C฀ ฀R.฀There฀are฀no฀other฀solutions.฀Indeed,฀let฀φ฀be฀a฀solution฀to฀the฀equation.฀฀

Consider฀the฀function฀฀ψ(t)฀:=฀φ(t)ekt.฀Since฀φ฀solves฀the฀equation,฀we฀have฀฀ ฀฀

฀฀฀฀฀฀฀฀฀ψ‘(t)฀=฀φ’(t)ekt฀+฀kφ(t)ekt฀=฀ekt(φ’(t)฀+฀kφ(t))฀=฀0.฀

Hence฀the฀function฀ ψ฀is฀constant,฀say฀C1,฀which฀means฀that฀ φ(t)ekt฀=฀C1.฀Finally,฀we฀

get฀φ(t)฀=฀C1e–kt.฀

We฀have฀seen฀that฀function฀(4)฀describes฀radioactive฀decay.฀Clearly,฀in฀order฀to฀฀determine฀ m(t)฀we฀need฀to฀find฀the฀constant฀k.฀This฀can฀be฀done฀using฀what฀is฀called฀the฀half-life฀ of฀the฀radioactive฀material.฀ Definition฀6฀The฀half-life฀is฀the฀time฀span฀needed฀to฀disintegrate฀half฀of฀the฀radioac1 tive฀substance,฀i.e.฀a฀time฀T฀is฀the฀half-life฀of฀the฀material฀if฀ m(T)฀=฀ ฀m0.฀ 2 If฀T฀is฀the฀half-life,฀then฀from฀(4),฀we฀have฀ ฀

฀

฀฀฀฀฀฀฀฀฀฀฀฀฀

m฀ m(T)฀=฀m0e-kT฀=฀ 0 ฀

which฀implies฀kT฀=฀ln฀2.฀Hence,฀if฀we฀know฀T,฀we฀can฀get฀k฀and฀vice-versa.฀Inserting฀ the฀value฀of฀k฀into฀(4),฀we฀have฀ ฀฀

฀

฀฀฀฀m(t)฀=฀m0e-฀

฀ln฀2.฀฀฀

฀

(5)

Many฀chemistry฀textbooks฀contain฀the฀half-life฀of฀some฀important฀radioactive฀materials.฀ As฀Table฀1฀shows,฀some฀radioactive฀materials฀disintegrate฀almost฀immediately,฀others฀ need฀milions฀of฀years.฀

There฀are฀several฀applications฀of฀the฀decay฀of฀radioactive฀materials.฀

English++ ฀

฀

isotope฀ ฀

฀

half-life฀

฀

14C฀carbon฀

฀

5730฀y฀

฀

131I฀iodine฀

฀

8.02070฀d฀

฀

214Po฀polonium฀

฀

1.64฀·฀10-4฀sec฀

฀

226Ra฀radium฀฀

฀

1602฀y฀

฀

238U฀uranium฀

฀

4.468฀·฀109฀y฀

฀

Table฀1:฀Half-lives฀of฀isotopes฀

฀

Example฀7฀(Chernobyl฀disaster)฀One฀of฀the฀most฀dangerous฀radioisotopes฀released฀in฀

the฀Chernobyl฀catastrophe฀in฀1986฀was฀Strontium฀90Sr฀whose฀half-life฀is฀28฀years.฀(a)฀ How฀much฀time฀does฀it฀take฀to฀reduce฀the฀isotope฀fallout฀to฀10%฀of฀its฀initial฀value?฀(b)฀ Assuming฀that฀during฀the฀catastrophe฀the฀number฀of฀released฀atoms฀was฀1027,฀how฀ much฀time฀does฀it฀take฀for฀all฀the฀atoms฀of฀the฀substance฀to฀disappear?฀ Solution.฀Let฀t0฀=฀0฀and฀half-life฀T฀=฀28.฀(a)฀We฀use฀formula฀(5).฀Since฀the฀half-life฀is฀ given฀in฀years,฀we฀will฀measure฀time฀in฀years.฀The฀time฀t฀needed฀to฀reduce฀the฀isotope฀ fallout฀to฀p%฀of฀its฀initial฀value฀is฀calculated฀from฀the฀equality฀฀ ฀m(t) ฀฀m ฀100%฀=฀p%. 0

฀ We฀obtain฀

p฀฀ 100฀฀ ;฀฀ e-฀ ฀ln2฀=฀฀฀ ฀;฀e฀ ฀ln2฀= ฀฀฀฀฀฀฀฀฀฀฀฀฀฀100฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀p and฀finally฀ ฀

฀

฀ln฀ ฀ t฀=฀T฀ ฀฀฀฀฀฀. ln฀2฀

฀

(6)฀

Inserting฀the฀value฀p฀=฀10,฀we฀have฀t฀ ฀93.04฀years11.฀ ฀฀฀฀฀฀฀฀฀฀฀฀ (b)฀Let฀N฀=฀10-27.฀Again฀we฀use฀formula฀(5)฀and฀calculate,฀as฀in฀(6),฀the฀time฀for฀all฀the฀ atoms฀of฀the฀radioisotope฀to฀disappear฀

฀ln ฀m(t) ฀฀฀฀฀฀. ฀฀m ฀100฀=฀N฀฀and฀hence t฀=฀T฀ ln฀2฀ 0 ฀฀฀฀฀฀฀฀฀฀฀฀

ln฀1029

An฀easy฀calculation฀yields฀฀t฀=฀28฀ ฀ ฀ .฀29฀ln฀10 ฀ ฀฀฀ ฀2698฀years ฀ ฀฀.฀ ฀=฀28฀ ln฀2฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀ln฀2฀ Example฀8฀(Radiocarbon฀dating฀in฀archeological฀research)฀Carbon฀dating฀is฀often฀used฀ ฀฀฀฀฀฀฀฀฀฀฀฀฀

to฀determine฀the฀age฀of฀a฀fossil.฀For฀instance,฀a฀humanoid฀skull฀was฀found฀in฀a฀cave฀

11฀In฀these฀and฀other฀computations฀in฀this฀note,฀we฀round฀our฀answers฀to฀two฀decimal฀

places.฀

English++ in฀South฀Africa฀along฀with฀the฀remains฀of฀a฀campfire.฀Archeologists฀believe฀the฀age฀of฀ the฀skull฀to฀be฀the฀same฀as฀the฀campfire.฀It฀is฀determined฀that฀only฀2%฀of฀the฀original฀ amount฀of฀Carbon฀14C฀remains฀in฀the฀burnt฀wood฀of฀the฀campfire.฀Estimate฀the฀age฀of฀ the฀skull฀if฀the฀half-life฀of฀Carbon฀14C฀is฀about฀5730฀years.฀ Solution.฀Denote฀by฀p฀the฀percent฀of฀mass฀remaining.฀We฀use฀formula฀(6)฀to฀estimate฀ the฀age฀of฀the฀skull.฀If฀the฀half-life฀T฀=฀5730฀and฀p฀=฀2,฀then฀ ln฀50 3.9120 ฀ln ฀=฀5730฀ ฀฀฀ ฀31325฀years. t฀=฀T฀ ฀฀฀฀฀฀= 5730฀ ln฀2฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀0.6931 ln฀2฀ To฀see฀how฀sensitive฀the฀technique฀of฀carbon฀dating฀is,฀we฀can฀change฀the฀values฀of฀ ฀฀฀฀฀฀฀฀฀฀ ฀฀฀฀฀฀฀฀฀฀฀฀ the฀two฀parameters฀of฀half-life฀T฀and฀percent฀p฀of฀mass฀remaining.฀For฀example,฀fix฀ p฀=฀2%฀and฀calculate฀the฀estimated฀age฀of฀the฀skull฀for฀T฀=฀5700,฀5650,฀5600฀and฀ 5550.฀We฀obtain฀from฀(6)฀the฀following฀values฀of฀the฀age฀t฀=฀32171,฀31890,฀31607฀and฀ 31325฀respectively.฀A฀similar฀sensitivity฀analysis฀can฀be฀carried฀out฀with฀respect฀to฀the฀ changes฀in฀the฀parameter฀p.฀Precision฀is฀very฀dependent฀on฀the฀care฀with฀which฀the฀ radiometric฀dating฀procedure฀is฀performed.฀ Remark฀ 9฀ (K-Ar฀ dating฀ in฀ archeology)฀ Potassium-argon฀ (or฀ K-Ar฀ dating)฀ is฀ based฀ on฀

measuring฀ the฀ products฀ of฀ the฀ radioactive฀ decay฀ of฀ potassium฀ (K).฀ The฀ radioactive฀ isotope฀40K฀decays฀to฀40Ar฀with฀a฀half-life฀of฀1.26฀·฀109฀years.฀Due฀to฀the฀long฀฀half-life,฀ the฀technique฀is฀most฀applicable฀for฀dating฀minerals฀and฀rocks฀more฀than฀100฀000฀ years฀old.฀It฀plays฀an฀important฀role฀in฀archeology.฀In฀1959฀in฀the฀Olduvai฀Gorge฀in฀ the฀Serengeti฀plains฀of฀northern฀Tanzania,฀archeologists฀Mary฀and฀Louis฀Leakey฀uncovered฀the฀tools฀and฀fossils฀of฀an฀ancient฀humanoid฀called฀Zinjanthropus.฀According฀ to฀the฀K-Ar฀dating฀method,฀there฀was฀a฀1.75฀million-year-old฀skull.฀In฀1965฀their฀team฀ uncovered฀a฀Homo฀erectus฀skull,฀dated฀at฀one฀million฀years฀old.฀It฀was฀in฀1978฀at฀the฀ Laetoli฀site,฀located฀45฀km฀south฀of฀Olduvai฀gorge,฀that฀Mary฀discovered฀the฀footprintbearing฀layers,฀dated฀by฀the฀K-Ar฀method฀to฀3.75฀million฀years฀ago.฀The฀stratigraphy฀ of฀the฀Olduvai฀Gorge฀is฀extremely฀deep฀and฀layers฀of฀volcanic฀ashes฀and฀stones฀allow฀ radiometric฀dating฀of฀the฀embedded฀artifacts,฀mostly฀through฀K-Ar฀dating.฀The฀archeologists฀have฀been฀bracketing฀the฀age฀of฀archeological฀deposits฀at฀Olduvai฀Gorge฀by฀ dating฀lava฀flows฀above฀and฀below฀the฀deposits.฀The฀Olduvai฀Gorge฀is฀now฀commonly฀ referred฀to฀as฀“The฀Cradle฀of฀Mankind”.฀ By฀ the฀ way,฀ modern฀ geologists฀ consider฀ the฀ age฀ of฀ the฀ Earth฀ to฀ be฀ around฀ 4.54฀฀ billion฀years฀(4.54·109฀years).฀This฀age฀has฀been฀determined฀by฀radiometric฀age฀dating฀ of฀meteorite฀material฀and฀is฀consistent฀with฀the฀ages฀of฀the฀oldest-known฀terrestrial฀ and฀lunar฀samples.฀The฀uranium-lead฀radiometric฀dating฀scheme฀is฀one฀of฀the฀oldest฀ available,฀as฀well฀as฀one฀of฀the฀most฀highly฀respected.฀It฀has฀been฀refined฀to฀the฀point฀ where฀the฀error฀in฀dates฀of฀rocks฀about฀three฀billion฀years฀old฀is฀no฀more฀than฀two฀

million฀years.฀

English++ Example฀10฀Using฀the฀data฀in฀Table฀1,฀find฀the฀percentage฀of฀the฀initial฀amount฀of฀

Carbon฀14C฀which฀remains฀after฀10฀000฀years.฀ Solution.฀By฀Table฀1฀we฀know฀that฀the฀half-life฀of฀the฀isotope฀T฀=฀5730฀years.฀Using฀ formula฀(5),฀we฀have฀

฀m(10000) ฀฀10000 ฀100%฀=฀exp฀฀฀฀฀ln2฀฀฀ ฀29.83฀% ฀฀฀฀m 0฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀5730 Example฀11฀A฀radioactive฀isotope฀has฀a฀half-life฀of฀14฀days.฀You฀wish฀to฀have฀50฀g฀at฀

the฀end฀of฀30฀days.฀How฀much฀radioisotope฀should฀you฀start฀with?฀ Solution.฀Since฀the฀half-life฀T฀=฀14฀days,฀we฀will฀measure฀time฀in฀days.฀Let฀m(t)฀be฀ the฀amount฀present฀at฀time฀t฀and฀m0฀the฀initial฀amount฀we฀are฀looking฀for.฀From฀(5)฀฀ we฀obtain฀ ฀

฀

฀฀฀฀฀฀฀฀฀฀฀฀฀฀m0฀=฀e

฀ln2.฀

Putting฀t฀=฀30,฀m(t)฀=฀50,฀we฀find฀m0฀=฀50฀฀฀฀฀฀฀฀฀ e ฀ln2 ฀220.8฀g.฀ Remark฀ 12฀ (Turin฀ shroud฀ and฀ carbon฀ dating)฀ The฀ Shroud฀ of฀ Turin฀ is฀ a฀ linen฀ cloth฀

bearing฀the฀hidden฀image฀of฀a฀man฀who฀appears฀to฀have฀been฀physically฀traumatized฀ in฀a฀manner฀consistent฀with฀crucifixion.฀It฀is฀kept฀in฀the฀royal฀chapel฀of฀the฀Cathedral฀ of฀Saint฀John฀the฀Baptist฀in฀Turin,฀Italy.฀ Various฀tests฀have฀been฀performed฀on฀the฀shroud฀and฀the฀debates฀about฀its฀origin฀ continue.฀Radiocarbon฀dating฀in฀1988฀by฀three฀independent฀teams฀of฀scientists฀pro-฀ duced฀ consistent฀ results฀ indicating฀ that฀ the฀ analysed฀ portion฀ of฀ the฀ shroud฀ dated฀ from฀the฀13th฀to฀14th฀centuries฀(1260–1390).฀This฀research฀has฀raised฀doubts฀about฀ the฀carbon฀dating฀method.฀One฀argument฀against฀the฀results฀of฀the฀radiocarbon฀tests฀ was฀a฀bacterial฀contamination,฀which฀was฀unknown฀during฀the฀1988฀testing.฀There฀ are฀examples฀of฀ancient฀textiles฀that฀have฀been฀grossly฀misdated,฀especially฀in฀the฀ earliest฀days฀of฀radiocarbon฀testing฀(the฀father฀of฀modern฀14C฀testing฀was฀Harry฀Gove).฀ Most฀ notable฀ of฀ these฀ is฀ mummy฀ 1770฀ of฀ the฀ British฀ Museum,฀ whose฀ bones฀ were฀ dated฀some฀800฀to฀1000฀years฀earlier฀than฀its฀cloth฀wrappings.฀The฀skewed฀results฀ were฀thought฀to฀be฀caused฀by฀organic฀contaminants฀on฀the฀wrappings฀similar฀to฀those฀ proposed฀for฀the฀shroud.฀Also,฀the฀result฀of฀the฀ 14C฀dating฀of฀the฀Turin฀shroud฀was฀ probably฀ caused฀ by฀ the฀ effects฀ of฀ high฀ temperature฀ in฀ the฀ 1532฀ fire฀ (and฀ another฀฀ series฀of฀small฀burns).฀ A฀follow-up฀analysis฀published฀in฀2005,฀however,฀indicated฀that฀the฀sample฀dated฀by฀ the฀teams฀was฀taken฀from฀an฀area฀of฀the฀shroud฀that฀was฀not฀a฀part฀of฀the฀original฀ cloth.฀ Remark฀13฀(Art฀forgeries)฀During฀World฀War฀II,฀many฀paintings฀of฀famous฀artists฀were฀

lost.฀Several฀works฀of฀art฀were฀found฀in฀strange฀locations฀just฀after฀the฀war.฀Some฀of฀

English++ the฀paintings฀discovered฀were฀actually฀art฀forgeries฀and฀scientists฀often฀had฀difficulty฀ proving฀that฀a฀painting฀was฀authentic.฀Using฀modeling฀based฀on฀a฀differential฀equation,฀ a฀ method฀ was฀ discovered฀ to฀ distinguish฀ between฀ a฀ painting฀ dating฀ back฀ 300฀ years฀and฀one฀painted฀only฀20฀years฀ago.฀It฀turns฀out฀that฀a฀small฀amount฀of฀lead-210฀ is฀present฀in฀all฀paintings.฀This฀element฀is฀found฀in฀lead฀oxide฀(commonly฀known฀as฀ white฀lead),฀which฀is฀a฀pigment฀artists฀have฀used฀for฀more฀than฀2000฀years.฀White฀ lead฀is฀made฀from฀lead฀metal฀which฀in฀turn฀is฀extracted฀from฀lead฀ore฀in฀a฀process฀ called฀smelting.฀An฀analysis฀based฀on฀a฀first-order฀differential฀equation฀(where฀the฀ unknown฀function฀is฀the฀amount฀of฀lead-210฀per฀gram฀of฀white฀lead)฀makes฀it฀possible฀to฀ estimate฀the฀age฀of฀a฀work฀of฀art฀and฀check฀whether฀a฀painting฀is฀a฀modern฀forgery.฀ It฀was฀also฀observed฀that฀lead-210฀is฀a฀difficult฀element฀to฀measure฀and฀that฀polonium210,฀a฀much฀easier฀element฀to฀measure,฀has฀the฀same฀half-life฀as฀lead-210.฀Therefore฀ a฀substitution฀of฀the฀two฀can฀be฀made฀in฀the฀analysis.฀ Remark฀14฀(Phosphorus)฀Six฀radioactive฀isotopes฀of฀phosphorus฀are฀known.฀One฀ra-

dioactive฀isotope,฀ 32P,฀has฀applications฀in฀medicine,฀industry,฀and฀tracer฀studies.฀An฀ isotopic฀ tracer฀ (called฀ also฀ an฀ isotopic฀ marker฀ or฀ an฀ isotopic฀ label)฀ is฀ a฀ radioactive฀ isotope฀whose฀presence฀in฀a฀system฀can฀easily฀be฀detected.฀The฀isotope฀is฀injected฀into฀ the฀system,฀where฀it฀gives฀off฀radiation.฀The฀radiation฀is฀followed฀by฀means฀of฀detectors฀฀ placed฀ around฀ the฀ system.฀ Phosphorus-32฀ is฀ especially฀ useful฀ in฀ medical฀ studies,฀฀ because฀phosphorus฀occurs฀in฀many฀parts฀of฀the฀body.฀Radioactive฀phosphorus฀can฀be฀ used฀as฀a฀tracer฀to฀study฀parts฀of฀the฀body฀as฀well฀as฀chemical฀changes฀inside฀the฀body.฀฀ Radioactive฀phosphorus฀can฀also฀determine฀how฀much฀blood฀is฀in฀a฀person’s฀body.฀ It฀can฀also฀help฀locate฀the฀presence฀of฀tumors฀in฀the฀brain,฀eyes,฀breasts,฀and฀skin.฀฀ Finally,฀it฀is฀sometimes฀used฀to฀treat฀certain฀forms฀of฀cancer.฀Radiation฀given฀off฀by฀the฀ 32P฀may฀kill฀cancer฀cells฀and฀help฀slow฀or฀stop฀the฀disease.฀This฀isotope฀is฀important฀฀

in฀a฀variety฀of฀scientific฀studies.฀For฀example,฀it฀is฀added฀to฀tires฀when฀they฀are฀made.฀ Then,฀the฀radiation฀it฀gives฀off฀can฀be฀studied฀as฀the฀tires฀are฀used.฀This฀information฀ indicates฀where฀the฀tire฀wears฀out฀and฀how฀long฀it฀takes฀to฀wear฀out.฀

4 Population dynamics Find฀ the฀ dependence฀ of฀ the฀ population฀ on฀ time฀ assuming฀ that฀ the฀ growth฀ rate฀ is฀฀ proportional฀to฀the฀population฀present.฀ Let฀p(t)฀be฀the฀population฀at฀time฀t.฀We฀may฀think฀about฀a฀single฀population฀of฀a฀species฀ contained฀ in฀ a฀ compartment฀ (a฀ petri฀ dish,฀ an฀ island,฀ a฀ country).฀ The฀ population฀ is฀฀ always฀a฀natural฀number,฀it฀is฀usually฀large฀enough฀so฀that฀very฀little฀error฀is฀introduced฀in฀assuming฀that฀p(t)฀is฀a฀continuous฀function.฀ Consider฀a฀population฀of฀bacteria฀that฀reproduce฀by฀simple฀cell฀division,฀i.e.฀the฀parent฀

cell฀does฀not฀die,฀but฀becomes฀two฀new฀cells฀(the฀death฀rate฀is฀zero).฀In฀this฀model฀

English++ assumption฀that฀the฀growth฀rate฀is฀proportional฀to฀the฀existing฀population฀is฀consistent฀ with฀observations฀of฀bacteria฀growth.฀The฀initial฀value฀problem฀is฀ ฀฀

฀

฀ dp฀=฀kp฀ dt

฀

(7)฀

p(0)฀=฀p0,

฀

where฀k฀is฀the฀proportionality฀constant฀(called฀population฀growth฀constant)฀and฀฀p0฀>฀0฀ is฀the฀population฀at฀time฀012.฀This฀model฀is฀called฀the฀Malthusian13฀or฀exponential฀ law฀of฀population฀growth.฀The฀equation฀in฀(7)฀is฀linear฀and฀separable,฀and฀the฀solution฀ of฀(7)฀is฀given฀by฀ ฀

฀

p(t)฀=฀p0ekt.฀฀

฀

(8)฀

When฀we฀consider฀the฀initial฀condition฀of฀the฀form฀p(t0)฀=฀p0,฀the฀solution฀to฀the฀ above฀model฀is฀of฀the฀form฀ ฀฀

฀

฀฀฀฀฀฀

p(t)฀=฀p0ek(t-t0).฀฀฀ ฀

฀

(9)

Example฀ 15฀ (Population฀ of฀ the฀ world)฀ According฀ to฀ the฀ 2007฀ UNFPA14฀ Report,฀ the฀

number฀of฀people฀of฀the฀world฀was:฀1800฀-฀1.0฀·฀109,฀1960฀-฀3.0฀·฀109฀and฀2007฀-฀6.5฀·฀109.฀ Use฀the฀exponential฀law฀of฀population฀growth฀to฀estimate฀the฀population฀in฀2050.฀ Solution.฀We฀will฀use฀formula฀(9).฀First,฀we฀estimate฀the฀population฀constant฀k฀and฀ subsequently฀we฀estimate฀the฀size฀of฀the฀human฀population.฀From฀(9)฀we฀easily฀deduce฀ p(t)฀ ln฀฀ ฀฀฀฀฀฀p0

k฀=฀฀ ฀฀t฀-฀t0 ฀฀฀฀฀฀฀฀฀

The฀estimation฀of฀k฀can฀be฀done฀in฀the฀following฀two฀ways.฀ 10)฀Let฀t0฀=฀0,฀p0฀=฀1.0฀·฀109,฀t฀=฀1960฀-฀1800฀=฀160฀and฀p(160)฀=฀3.0฀·฀109.฀Then฀ p(t)฀ ln฀฀ ฀฀฀฀฀฀p0 ln฀3 k฀=฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀=฀฀ ฀฀฀฀ ฀0.006866฀ ฀฀t฀-฀t0฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀160 ฀฀฀฀฀฀฀฀฀ which฀means฀that฀in฀1800–1960฀the฀population฀increased฀by฀0.6866%฀per฀year.฀ 20)฀Let฀t0฀=฀0,฀p0฀=฀3.0฀·฀109,฀t฀=฀2007฀-฀1960฀=฀47฀and฀p(47)฀=฀6.5฀·฀109.฀Then฀ p(t)฀ ln฀฀ ฀฀฀฀฀฀p0 ln฀6,53฀-฀ln฀3.0 k฀=฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀=฀฀ ฀฀฀฀ ฀0.01645 ฀฀t฀-฀t0฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀47 ฀฀฀฀฀฀฀฀฀ 12฀Analogously,฀we฀can฀treat฀the฀problem฀with฀p(t )฀=฀p .฀ 0 0 13฀Thomas฀Robert฀Malthus฀(1766–1834),฀the฀English฀demographer฀and฀political฀economist.฀ 14฀United฀Nations฀Fund฀for฀Population฀Activities.฀

English++ which฀means฀that฀in฀1960–2007฀the฀population฀increased฀by฀1.645%฀per฀year.฀ From฀ the฀ form฀ of฀ solution฀ (9),฀ we฀ can฀ estimate฀ the฀ world฀ population฀ in฀ 2007฀ and฀฀ 2050฀using฀different฀population฀constants.฀For฀k฀=฀0.006866,฀we฀have฀ ฀

฀

p(2007)฀=฀3.0฀·฀109฀·฀e0.006866(2007-1960)฀ ฀฀4.16฀·฀109฀

while฀for฀k฀=฀0.01645,฀we฀get฀ ฀

฀

p(2050)฀=฀6.5฀·฀109฀·฀e0.01645(2005-2007)฀ ฀฀13.18฀·฀109.฀

These฀results฀are฀estimated฀by฀the฀Malthusian฀model฀only฀and฀do฀not฀take฀into฀account฀many฀important฀factors฀for฀the฀human฀population15.฀ Remark฀16฀There฀are฀populations฀(like฀the฀human฀one)฀for฀which฀the฀assumption฀

that฀the฀death฀rate฀is฀zero฀is฀certainly฀wrong.฀However,฀we฀may฀revise฀the฀Malthusian฀ model฀to฀incorporate฀only฀death฀by฀natural฀causes.฀It฀might฀be฀expected฀that฀the฀death฀ rate฀is฀also฀proportional฀to฀the฀size฀of฀the฀population.฀This฀leads฀to฀the฀equation฀ ฀

฀

dp ~ ฀ ฀฀=฀kp-฀k ฀ dp฀=฀(k฀-฀k ฀ ฀ k฀p d)p฀= dt฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀

฀

฀(10)฀

where฀k฀=฀k฀-฀kd฀and฀kd฀is฀the฀proportionality฀constant฀for฀the฀death฀rate.฀Assuming฀ k฀>฀kd,฀so฀that฀k฀>฀0,฀we฀again฀obtain฀the฀Malthusian฀model.฀ Bearing฀in฀mind฀solution฀(8)฀of฀the฀exponential฀model,฀we฀conclude฀the฀following.฀ If฀k฀>฀0,฀then฀the฀population฀grows฀and฀continues฀to฀expand฀to฀infinity,฀that฀is,฀ ฀lim฀฀p(t)=฀+ t฀–›฀฀+ ฀฀ If฀k฀฀0,฀is฀not฀adequate฀and฀the฀model฀can฀be฀dropped.฀ The฀main฀argument฀for฀this฀has฀to฀do฀with฀environmental฀limitations.฀The฀complication฀is฀that฀population฀growth฀is฀eventually฀limited฀by฀some฀factor,฀usually฀one฀from฀ among฀many฀essential฀resources.฀When฀a฀population฀is฀far฀from฀its฀limits฀of฀growth฀it฀ can฀grow฀exponentially.฀However,฀when฀nearing฀its฀limits,฀population฀size฀can฀fluctuate,฀even฀chaotically.฀ Another฀model฀was฀proposed฀to฀remedy฀this฀flaw฀in฀the฀exponential฀model.฀It฀is฀called฀ the฀logistic฀model฀(also฀called฀Verhulst-Pearl฀model16)฀and฀it฀takes฀into฀account฀factors฀ (like฀premature฀deaths฀due฀to฀malnutrition,฀inadequate฀medical฀supplies,฀wars,฀communicable฀ diseases,฀ violent฀ crimes,฀ etc.)฀ involving฀ competition฀ within฀ the฀ population.฀In฀order฀to฀justify฀the฀logistic฀model,฀we฀assume฀there฀is฀another฀component฀ 15฀฀According฀to฀the฀UNFPA฀the฀population฀estimate฀for฀2050฀is฀8.9฀bilion.฀ 16฀฀P.F.฀Verhulst฀(1804–1849),฀a฀mathematician฀and฀a฀doctor฀in฀number฀theory฀from฀the฀฀

฀฀฀฀University฀฀of฀Ghent.฀

English++ of฀ the฀ death฀ rate฀ that฀ is฀ proportional฀ to฀ the฀ number฀ of฀ two-party฀ interactions.฀ For฀฀ population฀of฀size฀p,฀there฀are฀p(p฀-฀1)/2฀such฀interactions.฀We฀may฀suppose฀the฀death฀ rate฀due฀to฀intraspecies฀competition฀is฀ p(p฀-1) kc฀฀ 2 ฀฀฀฀฀฀฀฀฀฀ ฀฀฀฀฀฀฀฀฀ where฀ kc฀ is฀ another฀ proportionality฀ constant฀ (the฀ competition฀ constant).฀ Together฀

with฀equation฀(10),฀this฀leads฀to฀ p(p฀-1) p p2 ฀=฀kp฀-฀kdp฀+฀kc฀ ฀=฀kp฀-฀kdp฀+฀kc฀ ฀-฀kc dt฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀2฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀2฀฀฀฀฀฀฀2 dp

The฀logistic฀model฀is฀the฀following฀initial฀value฀problem฀ dp ฀=฀ap฀-฀bp2 dt฀฀฀ p(0)฀=฀p0

where฀a฀=฀k-kd฀+฀ ฀and฀b฀=฀ ฀.฀The฀equation฀is฀autonomous฀(hence฀separable)฀and฀ nonlinear฀because฀of฀the฀presence฀of฀p2.฀ We฀observe฀that฀the฀equation฀dp/dt฀=฀ap฀-฀bp2฀has฀two฀constant฀solutions฀p฀ ฀0฀฀and฀฀ p฀ ฀ a/b.฀ The฀ non-constant฀ solutions฀ may฀ obtained฀ by฀ separating฀ the฀ variables฀ and฀฀ using฀a฀partial฀fractions฀expansion:฀ ฀

฀

฀฀฀฀฀฀1฀฀฀฀฀฀฀ ฀ ฀ ฀ dp฀=฀฀฀dt p(a฀-฀bp)

฀

(11)

-b฀฀฀ 1฀฀฀฀฀฀฀dp 1 dp฀=฀฀฀dt ฀-฀ ฀฀฀฀฀฀฀ a฀฀฀฀฀฀฀฀p฀฀฀฀a฀฀฀฀฀a-bp

1฀ln฀|p|฀-฀1฀ln฀|a฀-฀bp|฀=฀t฀+฀C 1 a฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀a p฀฀ ฀ln฀฀฀฀฀฀ ฀฀฀฀=฀at฀+฀C2 a฀-฀bp ฀฀฀฀฀฀฀

p฀฀ ฀฀฀฀ ฀฀฀฀=฀C3eat.฀ a฀-฀bp

Solving฀for฀p,฀we฀have฀ ฀

฀

฀ aC ฀฀ aC eat฀฀ ฀฀฀=฀฀฀฀฀ 3 ฀p(t)฀=฀฀฀ 3 ฀ ฀ ฀ ฀ -at at ฀฀฀฀฀bC3e +1฀฀฀฀฀฀bC3+e

฀฀฀฀฀฀฀ Using฀the฀initial฀condition฀in฀(11)฀(assuming฀that฀p0฀is฀not฀equal฀to฀both฀0฀or฀a/b),฀we฀ get฀

p ฀฀ C3=฀฀฀฀฀ 0 ฀฀฀฀฀ a฀-฀bp0 ฀฀฀฀฀฀฀฀฀

English++ which,฀once฀substituted฀into฀the฀expression฀for฀p(t)฀and฀simplified,฀we฀find฀ ap ฀฀ p(t)฀=฀฀฀฀฀฀฀฀฀฀฀฀ 0 ฀฀฀฀฀ ฀ ฀ ฀ ฀ ฀ ฀ ฀ ฀(12) ฀฀฀฀bp +(a฀-฀bp )e-at฀ 0

฀฀฀฀฀฀฀ This฀function฀is฀called฀the฀logistic฀function฀and฀its฀graph฀is฀called฀the฀logistic฀curve.฀ An฀important฀property฀of฀the฀logistic฀function฀is฀that฀ ฀฀

฀

a ฀฀฀฀฀฀lim฀p(t)=฀฀ ฀฀if฀p0฀>฀0. t฀–›฀฀+ ฀ ฀ b

฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀ The฀ quantity฀ a/b฀ is฀ a฀ limiting฀ size฀ for฀ the฀ population฀ (also฀ called฀ the฀ carrying฀฀ capacity).฀Consequently,฀any฀population฀which฀follows฀the฀logistic฀model฀will฀remain฀ bounded.฀Namely,฀when฀p0฀>฀a/b,฀the฀population฀will฀decrease฀toward฀a/b฀and฀when฀ the฀initial฀population฀p0฀฀0.฀The฀proportionality฀constant฀in฀(13)฀is฀negative฀since฀the฀temperatures฀

17฀฀The฀interested฀reader฀can฀sketch฀the฀graphs฀of฀the฀logistic฀curve฀for฀0฀฀M.฀The฀equation฀(13)฀is฀ ฀ a฀separable฀ODE.฀We฀assume฀that฀the฀initial฀temperature฀of฀the฀object฀is฀prescribed฀฀

decrease฀in฀time฀and฀the฀derivative฀

฀

T(t0)฀=฀T0฀

฀

฀(14)฀

where฀T0฀stands฀for฀the฀initial฀temperature฀of฀the฀object.฀Thus,฀the฀dependence฀of฀the฀ temperature฀of฀the฀object฀on฀time฀is฀described฀by฀the฀initial฀value฀problem฀(13)฀and฀ (14).฀Its฀solution฀has฀a฀form19฀ ฀

฀

฀฀฀฀T(t)฀=฀M฀+฀(T0–M)e–kt.฀฀

฀

(15)

Example฀17฀(Hot฀coffee)฀A฀cup฀of฀coffee฀initially฀at฀950C฀cools฀to฀800C฀in฀5฀minutes฀

while฀ sitting฀ in฀ a฀ room฀ of฀ temperature฀ 210C฀ 20.฀ Using฀ the฀ Newton฀ law฀ of฀ cooling,฀฀ determine฀when฀the฀temperature฀of฀the฀coffee฀will฀be฀a฀nice฀500C.฀ Solution฀Let฀T0฀=฀95,฀M฀=฀21,฀t฀=฀5฀and฀T(5)฀=฀80.฀We฀proceed฀in฀two฀steps฀and฀ make฀use฀of฀formula฀(15).฀First,฀we฀find฀the฀value฀of฀the฀coefficient฀k฀which฀can฀be฀ calculated฀ ฀ 1 ฀฀T -M฀฀฀ ln฀74฀-฀ln฀59 k฀=฀ ฀฀ln฀฀ 0 =฀ ฀฀ ฀0.045305. t฀฀฀฀฀฀฀฀T(t)฀-฀M฀฀฀฀฀฀฀฀฀฀฀฀฀5 ฀฀฀฀฀฀฀฀ ฀ Then,฀ knowing฀ the฀ value฀ of฀ k,฀ we฀ are฀ able฀ to฀ find฀ a฀ time฀ instant฀ t1฀ at฀ which฀ the฀฀ temperature฀of฀the฀coffee฀will฀be฀T(t1)฀=฀50.฀ 1 ฀฀T -M฀฀฀฀ ln฀74฀-฀ln฀29 ฀฀ t1฀=฀ ฀฀ln฀฀ 0 =฀ ฀ ฀20.676. k฀฀฀฀฀฀฀T(t1)฀-฀M฀฀฀฀฀฀฀฀฀฀฀฀฀k ฀฀฀฀฀฀฀฀ Hence,฀the฀temperature฀of฀the฀coffee฀will฀be฀500C฀after฀20.7฀minutes฀from฀the฀initial฀ time฀instant.฀ ฀ Example฀18฀(Time฀of฀death)฀It฀was฀noon฀on฀a฀cold฀May฀day฀in฀Krakow:฀160C.฀Detective฀

John฀Kowalski฀arrived฀at฀the฀crime฀scene฀in฀a฀hotel฀room฀to฀find฀the฀sergeant฀leaning฀over฀ the฀body.฀The฀sergeant฀said฀there฀were฀several฀suspects.฀If฀they฀knew฀the฀exact฀time฀of฀ death,฀then฀they฀could฀narrow฀the฀list.฀Kowalski฀took฀out฀a฀thermometer฀and฀measured฀ the฀temperature฀of฀the฀corpse:฀34.50C.฀He฀then฀left฀for฀lunch.฀Upon฀returning฀at฀1:00pm,฀ he฀found฀the฀body฀temperature฀to฀be฀33.70C.฀Find฀the฀time฀the฀murder฀occured.฀฀ Solution.฀As฀in฀Example฀17,฀we฀proceed฀in฀two฀steps.฀Let฀T0฀=฀34.5,฀M฀=฀16,฀t฀=฀60฀ and฀T(60)฀=฀33.7.฀First,฀we฀find฀the฀value฀of฀the฀coefficient฀k฀as฀follows฀ ฀ 1฀฀ T –M฀฀฀ ln฀8.5–ln฀17.7฀ –4฀ 0 k=฀t฀ln฀T(t)–M฀=฀฀฀฀฀฀฀฀60฀฀฀฀฀฀฀฀฀฀฀฀฀ 7.3677฀·฀10 .

19฀This฀can฀easily฀be฀checked฀by฀the฀reader.฀

20฀This฀is฀not฀always฀attained฀in฀the฀Jagiellonian฀University฀buildings.

English++ In฀other฀words,฀we฀have฀determined฀k฀from฀the฀information฀on฀two฀temperatures฀ measured฀by฀Kowalski,฀at฀the฀point฀T0฀=฀34.5฀and฀the฀point฀T(60)฀=฀33.7.฀ Knowing฀the฀value฀of฀k,฀we฀are฀able฀to฀find฀a฀time฀instant฀td฀at฀which฀the฀crime฀happened.฀ To฀this฀end฀we฀take฀into฀account฀other฀two฀points฀T(0)฀=฀3721฀and฀T(td)฀=฀34.5.

฀ ฀฀1฀฀฀ ฀T(0)–M฀฀฀฀฀฀฀ln฀(37–16)–ln฀(34,5–16) ln฀21–ln฀18,5 172.036. =฀ td฀=฀k฀฀ln฀T(t )–M฀=฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀k฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀k฀฀฀฀฀฀฀฀฀฀฀฀ d

Therefore฀the฀murder฀occured฀about฀172฀minutes฀before฀noon,฀that฀is,฀around฀9:08am.฀฀ We฀conclude฀that฀in฀order฀to฀find฀the฀time฀of฀death฀it฀is฀necessary฀to฀measure฀the฀ body฀temperature฀twice22.฀ Remark฀19฀(Heating฀and฀cooling฀of฀buildings)฀Newton’s฀law฀can฀be฀used฀to฀formulate฀

a฀model฀that฀describes฀the฀temperature฀profile฀inside฀a฀building฀as฀a฀function฀of฀฀the฀ ouside฀temperature,฀the฀heat฀generated฀inside฀the฀building,฀and฀the฀furnace฀heating฀ or฀air฀conditioning฀cooling.฀The฀resulting฀Cauchy฀problem฀can฀be฀formulated฀as฀in฀ Chapter฀3.3฀of฀[5]฀and฀reads฀as฀follows฀ ฀

฀

dT ฀ ฀=฀-฀k(T(t)฀-฀M(t))฀+฀H(t)฀+฀U(t) ฀ ฀ ฀ ฀ dt฀฀฀ T(t0)฀=฀T0.฀

฀

(16)

The฀unknown฀function฀T(t)฀represents฀the฀temperature฀inside฀the฀building฀at฀time฀ t฀ and,฀ viewing฀ the฀ building฀ as฀ a฀ single฀ compartment,฀ M(t)฀ is฀ the฀ outside฀ temperature,฀H(t)฀is฀the฀additional฀heating฀rate฀(in฀terms฀of฀energy฀per฀unit฀time),฀U(t)฀is฀the฀ furnace฀heating฀or฀air฀conditioner฀cooling฀rate,฀k฀is฀a฀positive฀constant฀and฀T0฀is฀the฀ initial฀temperature฀at฀time฀t0.฀ This฀linear฀model฀(16)฀is฀a฀generalization฀of฀the฀problem฀(13)฀and฀(14).฀The฀constant฀

฀is฀called฀the฀time฀constant฀for฀the฀building฀and฀it฀is฀one฀of฀the฀characteristics฀of฀ buildings23.฀More฀details฀on฀this฀model฀can฀be฀found฀in฀[5].฀

6 Stefan’s law of thermal radiation The฀Stefan฀law฀of฀thermal฀radiation฀states฀that฀the฀rate฀of฀change฀in฀the฀temperature฀ of฀a฀body฀at฀T(t)฀degrees฀in฀a฀medium฀at฀temperature฀M฀degrees฀is฀proportional฀to฀the฀ quantity฀M4฀-฀T4฀.฀

21฀Assuming฀the฀dead฀person฀was฀not฀sick฀and฀had฀a฀temperature฀of฀370C.฀The฀interested฀฀

฀฀฀฀reader฀฀may฀estimate฀the฀time฀of฀death,฀if฀instead฀of฀370C฀we฀suppose฀36.60C.฀

22฀Remember฀this฀method฀unless฀you฀are฀sergeant฀Colombo.฀ 23฀The฀building฀owners฀should฀know฀this฀constant฀for฀economic฀reasons.฀

English++ As฀before,฀we฀denote฀by฀T(t)฀the฀temperature฀of฀the฀body฀at฀time฀instant฀t฀and฀by฀ M฀the฀constant฀temperature฀of฀the฀surrounding฀medium.฀We฀obtain฀the฀following฀฀ nonlinear฀differential฀equation฀of฀the฀first฀order฀ ฀

฀

dT ฀ ฀=฀-k(T฀4฀-M4), ฀ dt฀฀฀

฀

(17)฀

฀where฀k฀>฀0.฀Equation฀(17)฀is฀a฀separable฀ODE.฀Stefan’s฀and฀Newton’s฀laws฀are฀nearly฀ the฀same฀when฀T฀is฀close฀to฀M,฀cf.฀Chapter฀3฀of฀[5].฀

7 An epidemiology model The฀spread฀of฀diseases฀can฀be฀assessed฀by฀using฀differential฀equations.฀A฀simple฀model฀ for฀ the฀ number฀ of฀ people฀ infected฀ with฀ a฀ particular฀ disease,฀ say฀ chicken฀ pox,฀ in฀ a฀ closed฀environment,฀like฀a฀university,฀is฀as฀follows.฀ ฀

฀

I’(t)฀=฀rI(t)฀-฀aI(t)฀฀฀

฀

(18)฀

where:฀ ฀

·฀t฀is฀time฀measured฀in฀days;฀

฀

·฀I(t)฀is฀the฀number฀of฀infected฀people฀with฀the฀disease฀at฀time฀t;฀

฀

·฀ r฀ >฀ 0฀ is฀ a฀ parameter฀ measuring฀ the฀ rate฀ at฀ which฀ people฀ are฀ infected฀ by฀ an฀฀ ฀฀฀infectious฀person฀(how฀many฀people฀an฀infected฀person฀infects฀per฀day);฀

฀

·฀a฀>฀0฀is฀a฀parameter฀measuring฀the฀rate฀of฀removal,฀that฀is,฀the฀rate฀at฀which฀฀ ฀฀฀people฀cease฀to฀be฀infectious;฀they฀either฀recover฀or฀die฀(1/the฀number฀of฀days฀a฀฀ ฀฀฀person฀is฀infectious)฀

Of฀course฀this฀equation฀can฀be฀written฀as฀I’(t)฀=฀(r฀-฀a)I(t)฀and฀therefore฀r฀-฀a฀can฀be฀considered฀ as฀a฀parameter฀of฀this฀equation.฀The฀general฀solution฀to฀(18)฀is฀an฀exponential฀function฀ ฀

฀

฀฀฀฀฀฀฀I(t)฀=฀Ce(r-a)t฀with฀C฀ ฀R.฀

However,฀the฀negative฀constant฀C฀is฀not฀acceptable฀in฀the฀solution฀since฀the฀function฀ I,฀the฀infected฀population,฀can฀never฀be฀negative.฀As฀can฀be฀seen฀from฀the฀previous฀ examples,฀the฀character฀of฀this฀solution฀depends฀on฀the฀parameter฀r-a.฀The฀infection฀ rate฀r฀will฀vary฀based฀on฀several฀factors,฀including฀the฀nature฀of฀the฀disease฀and฀the฀ nature฀of฀contact฀between฀people.฀The฀removal฀rate฀a฀also฀depends฀on฀several฀factors,฀ including฀how฀fast฀people฀are฀diagnosed฀(so฀they฀can฀be฀told฀to฀stay฀at฀home),฀and฀ how฀quickly฀they฀get฀better฀(so฀they฀are฀no฀longer฀infectious).฀Interestingly,฀another฀ way฀people฀can฀be฀“removed”฀from฀the฀infectious฀population฀is฀to฀die.฀ Consider฀ now฀ an฀ initial฀ condition.฀ At฀ time฀ t฀ =฀ 0,฀ we฀ start฀ with฀ a฀ certain฀ number฀ of฀sick฀people,฀I0.฀We฀may฀think฀of฀t฀=฀0฀as฀the฀start฀of฀time฀that฀we฀get฀involved,฀฀ t฀is฀negative฀in฀the฀past,฀and฀t฀is฀positive฀in฀the฀future.฀The฀solution฀now฀looks฀as฀ follows:฀

English++ ฀

฀

I(t)฀=฀I0e(r-a)t.฀

If฀I0฀=฀0,฀then฀I(t)฀is฀always฀zero฀for฀all฀time฀t.฀It฀is฀easy฀to฀see฀that฀if฀r฀>฀a,฀we฀have฀ growth,฀and฀if฀r฀฀0.฀This฀happens฀if฀and฀only฀if฀r฀>฀a.฀The฀specific฀changes฀in฀r฀and฀a฀could฀prevent฀an฀epidemic.฀This฀simple฀model฀helps฀to฀predict฀ the฀number฀of฀infected฀people฀I(t).฀

8 Free fall An฀object฀falls฀through฀the฀air฀toward฀Earth.฀Assuming฀that฀the฀only฀forces฀acting฀on฀ the฀object฀are฀gravity฀and฀air฀resistance,฀find฀the฀velocity฀of฀the฀object฀as฀a฀function฀ of฀time.฀ Newton’s฀second฀law฀states฀that฀force฀is฀equal฀to฀mass฀times฀acceleration,฀i.e.฀ ฀

฀

F฀=฀m฀

฀,฀

where฀F฀represents฀the฀total฀force฀on฀the฀object,฀m฀is฀the฀mass฀of฀the฀object฀and฀the฀ acceleration฀is฀expressed฀as฀the฀derivative฀of฀the฀velocity฀v฀with฀respect฀to฀time฀t.฀ Near฀the฀Earth’s฀surface,฀the฀force฀due฀to฀gravity฀(being฀just฀the฀weight฀of฀the฀object)฀ is฀given฀by฀mg,฀where฀g฀is฀the฀acceleration฀due฀to฀gravity24.฀On฀the฀other฀hand,฀there฀ is฀no฀general฀law฀that฀precisely฀models฀the฀air฀resistance฀acting฀on฀the฀object.฀The฀ air฀resistence฀is฀a฀force฀that฀can฀be฀represented฀by฀-kv,฀which฀means฀that฀it฀is฀proportional฀to฀the฀velocity฀of฀the฀object฀and฀it฀opposes฀the฀motion.฀The฀positive฀constant฀k฀ depends฀on฀the฀density฀of฀air฀and฀shape฀of฀the฀object.฀Therefore,฀the฀total฀force฀acting฀ on฀the฀object฀is฀mg฀-฀kv.฀This฀leads฀to฀the฀following฀ordinary฀differential฀equation:฀ ฀

฀

m฀

฀฀=฀mg฀-฀kv.฀฀

฀

(19)

This฀equation฀is฀linear,฀homogeneous฀and฀autonomous,฀so฀it฀is฀separable.฀Exploiting฀ the฀separation฀of฀variables25฀we฀solve฀this฀equation฀and฀find฀ ฀

฀

v(t)฀=฀

฀-฀

฀e-kt/m฀with฀C฀ ฀R.฀฀ ฀

฀

฀(20)

This฀is฀a฀general฀solution฀to฀equation฀(19)฀and฀every฀solution฀to฀(19)฀is฀of฀the฀form฀ (20).฀ Assuming฀ that฀ the฀ initial฀ velocity฀ of฀ the฀ object฀ is฀ v0,฀ we฀ obtain฀ the฀ following฀ initial฀value฀problem

24฀Recall฀that฀on฀Earth฀g฀=฀9.81m/s2.฀

25฀This฀was฀already฀used฀in฀the฀radioactive฀model.฀

English++ dv ฀ =฀ mg฀ -฀ kv฀฀ ฀฀฀ dt ฀฀฀฀฀ v(0)฀=฀v0. ฀ ฀ ฀ m฀

฀

(21)

Substituting฀t฀=฀0฀in฀the฀general฀solution฀and฀using฀the฀initial฀datum,฀easy฀algebraic฀ manipulations฀give฀C฀=฀mg฀-฀kv0.฀The฀solution฀of฀(21)฀is฀the฀following:฀ ฀

฀

v(t)฀=฀

฀ ฀฀e-kt/m฀฀฀฀

฀+฀ v0฀-฀

฀

(22)฀

We฀make฀certain฀observations.฀Since฀ ฀

฀

฀v(t)฀=฀

฀,฀

it฀appears฀that,฀regardless฀of฀the฀initial฀velocity฀v0,฀the฀velocity฀of฀the฀object฀approaches฀฀ mg/k.฀ The฀ value฀ mg/k฀ is฀ the฀ horizontal฀ asymptote฀ for฀ v(t).฀ The฀ constant฀ mg/k฀ is฀฀ referred฀to฀as฀the฀limiting฀or฀terminal฀velocity฀of฀the฀object฀and฀it฀is฀approximately฀ the฀weight,฀mg,฀divided฀by฀the฀coefficient฀of฀air฀resistance,฀k.฀Hence,฀the฀heavier฀the฀ object,฀the฀faster฀it฀will฀fall,฀assuming฀shapes฀and฀sizes฀are฀the฀same.฀Also,฀when฀the฀ air฀resistance฀is฀reduced฀(k฀is฀made฀smaller),฀the฀object฀will฀fall฀faster.฀These฀observations฀agree฀with฀our฀experience.฀ Example฀20฀(Bungee฀jumper)฀The฀jumper฀jumps฀off฀a฀very฀high฀bridge฀with฀a฀long฀

elastic฀rope฀tied฀to฀his฀legs,฀so฀that฀the฀rope฀pulls฀him฀back฀before฀he฀hits฀the฀ground.฀ Assuming฀only฀air฀resistance฀and฀gravity฀acting฀on฀the฀jumper,฀find฀his฀terminal฀velocity฀just฀before฀the฀rope฀pulls฀him฀back,฀provided฀m฀=฀100kg,฀k฀=฀5kg/s฀and฀v(0)฀ =฀10m/s.฀ Solution.฀The฀terminal฀velocity฀of฀the฀jumper฀is฀independent฀of฀his฀initial฀velocity฀ and฀is฀equal฀to฀฀ ฀

฀

฀=฀

฀=196.2฀

฀.

The฀model฀discussed฀above฀can฀be฀extended฀to฀determine฀the฀equation฀of฀motion฀of฀฀ falling฀object.฀ This฀can฀be฀done฀as฀follows.฀Let฀us฀denote฀by฀s(t)฀the฀distance฀the฀object฀has฀fallen฀in฀ time฀t.฀The฀position฀s(t)฀is฀found฀by฀integrating฀the฀equation฀ ฀

฀

=฀v(t).

From฀(22)฀we฀obtain฀ ฀

฀

s(t)฀=฀ v(t)฀dt฀=฀

฀t฀-฀

฀ v0฀-฀

฀ ฀e-kt/m฀+฀C฀฀฀฀฀ ฀

฀

฀ where฀C฀is฀a฀constant.฀Setting฀s(0)฀=฀0,฀we฀find฀that฀

English++ ฀

฀

฀ v0฀-฀

C฀=฀

฀ ฀.

Hence฀the฀equation฀of฀motion฀is฀ ฀

฀

s(t)฀=฀฀

฀t฀+฀

฀ ฀฀(฀1฀-฀e-kt/m).฀

฀ v0฀-฀

Example฀21฀(Bungee฀jumper,฀continued)฀Consider฀the฀bungee฀jumper฀from฀Example฀

20.฀Suppose฀additionally฀that฀the฀bridge฀is฀500m฀above฀the฀ground.฀Determine฀when฀ the฀jumper฀will฀strike฀the฀ground฀if฀the฀rope฀is฀broken.฀฀ Solution.฀We฀can฀use฀(23).฀Because฀the฀jumper฀is฀released฀500฀m฀above฀the฀ground,we฀ determine฀when฀he฀strikes฀the฀ground฀by฀setting฀s(t)฀=฀500฀and฀solving฀the฀following฀ equation฀for฀t฀ ฀

฀

s(t)฀=฀฀

฀t฀+฀

฀ ฀฀(฀1฀-฀e-kt/m).

฀ v0฀-฀

Unfortunately,฀this฀equation฀can฀not฀be฀solved฀explicitely฀for฀t.฀In฀general฀we฀might฀ try฀to฀find฀t฀by฀using,฀for฀instance,฀the฀Newton฀approximation฀method.฀However,฀in฀ this฀case฀it฀is฀not฀necessary฀since฀the฀term฀e-t฀will฀be฀very฀small฀for฀t฀near฀the฀time฀we฀ are฀looking฀for.฀We฀simply฀ignore฀the฀term฀e-t฀and฀obtain฀a฀linear฀equation฀ ฀

฀

฀฀฀฀฀s(t)฀=฀฀

฀t฀+฀

฀ v0฀-฀

฀ ฀฀

which฀we฀easily฀solve฀for฀t:฀ ฀

฀

t฀=฀

฀-฀

฀+฀

฀=฀2.54s฀-฀1.01s฀+฀20s฀=฀21.52s.฀

This฀means฀that฀the฀jumper฀will฀reach฀the฀ground฀within฀21.52฀s.฀Ignoring฀the฀term฀ e-t฀we฀made฀a฀reasonable฀approximation฀since฀e-t฀near฀t฀=฀21.52฀is฀very฀small฀(e-21.52฀ ฀0.45฀·฀10-9).฀ Example฀22฀(Parachutist)฀A฀parachutist฀whose฀mass฀is฀75฀kg฀drops฀from฀a฀helicopter฀

hovering฀4000฀m฀above฀the฀earth฀and฀falls฀toward฀the฀ground฀under฀the฀influence฀of฀ gravity.฀Assume฀the฀gravitational฀force฀is฀constant฀and฀the฀force฀due฀to฀air฀resistance฀ is฀proportional฀to฀the฀velocity฀of฀the฀parachutist,฀with฀the฀proportionality฀constant฀ k1฀=฀15 ฀when฀the฀chute฀is฀closed฀and฀with฀constant฀k2฀=฀105 ฀when฀the฀chute฀ is฀open.฀If฀the฀chute฀does฀not฀open฀until฀1฀minute฀after฀the฀parachutist฀leaves฀the฀฀ helicopter,฀after฀how฀many฀seconds฀will฀he฀hit฀the฀ground?฀ Solution.฀We฀use฀equations฀(22)฀and฀(23).฀We฀first฀consider฀the฀motion฀before฀the฀ chute฀opens฀and฀then฀when฀the฀chute฀is฀open.฀We฀denote฀m฀=฀75฀kg,฀h฀=฀4000฀m,฀฀ g฀=฀9.81 ฀,฀t฀=฀60฀s฀and฀v฀฀=฀0.฀ Phase฀1:฀the฀chute฀is฀closed.฀From฀equations฀(22)฀and฀(23),฀we฀find฀the฀velocity฀

v1(t)฀=฀

฀+฀ v0฀-฀

฀ ฀฀e-k1t/m=฀

฀-฀

฀exp(

)฀=฀49.5

฀

English++ and฀the฀distance฀the฀parachutist฀has฀fallen฀in฀t฀seconds฀ ฀

฀

฀฀฀฀฀฀฀฀=

฀t฀+฀

฀฀฀฀฀s1(t)=

฀ ฀(฀1฀-฀e-k1t/m)฀=

฀฀ v0-฀

฀.฀

฀-฀

·฀(1฀-฀e-12)฀=฀2697.75m.฀฀

Hence,฀after฀t฀=฀60฀s฀the฀parachutist฀is฀s2฀=฀h฀-฀s1฀=฀4000฀-฀2697.75฀=฀1302.25฀m฀above฀ the฀ground฀traveling฀at฀a฀velocity฀of฀49.05

฀

Phase฀2:฀the฀chute฀is฀open.฀In฀order฀to฀determine฀when฀the฀parachutist฀will฀hit฀the฀ ground,฀we฀employ฀the฀equation฀ ฀฀฀฀

฀

฀฀฀s2(t)=

฀t฀+฀

฀฀ v0-฀

฀ ฀(฀1฀-฀e-k2t/m),

where฀s2฀=฀1302.25฀m฀is฀the฀distance฀to฀the฀ground,฀and฀v0฀is฀the฀initial฀velocity฀at฀ the฀time฀the฀chute฀opens.฀We฀would฀like฀to฀solve฀this฀equation฀for฀t.฀As฀in฀Example฀ 21,฀this฀nonlinear฀equation฀cannot฀be฀solved฀explicitely฀for฀t.฀However,฀since฀the฀term฀ e-k2t/m฀will฀be฀very฀small฀for฀t฀near฀the฀time฀we฀are฀looking฀for,฀we฀ignore฀this฀term฀ and฀obtain฀a฀linear฀equation฀ ฀฀

฀

s2(t)=

฀t฀+฀

฀฀ v0-฀

฀

Solving฀the฀latter฀for฀t,฀we฀have฀ ฀

฀

฀-฀

฀+฀

฀=฀185.84฀-฀5.04฀+฀0.71฀=฀181.51s.

This฀ means฀ that฀ the฀ parachutist฀ will฀ strike฀ the฀ earth฀ 181.51฀ s฀ after฀ the฀ parachute฀ opens฀or฀241.51฀s฀after฀dropping฀from฀the฀helicopter.฀The฀ignored฀term฀e-k2t/m฀near฀t฀ =฀181.51฀is฀very฀small฀( e-254.2)฀hence฀negligible฀and฀thus฀the฀approximation฀we฀have฀ made฀is฀reasonable.฀ We฀also฀remark฀that฀the฀velocity฀of฀the฀parachutist฀at฀impact฀is฀ ฀

฀

฀฀=฀

฀

฀=฀7.01

which฀is฀the฀limiting฀velocity฀for฀his฀fall฀with฀the฀chute฀open.฀

9 Continuous compounding A฀bank฀used฀to฀compound฀interest฀continuously.฀Show฀that฀the฀amount฀P(t)฀of฀dollars฀ in฀a฀savings฀bank฀account฀at฀time฀instant฀t฀satisfies฀the฀ordinary฀differential฀equation฀ ฀

฀

where฀r฀denotes฀the฀nominal฀annual฀interest฀rate฀and฀t฀is฀the฀total฀time฀in฀years.฀

English++ Compound฀ interest฀ is฀ the฀ concept฀ of฀ adding฀ accumulated฀ interest฀ back฀ to฀ the฀฀ principal,฀so฀that฀interest฀is฀earned฀on฀interest฀from฀that฀moment฀on.฀The฀effect฀of฀ compounding฀depends฀on฀the฀frequency฀with฀which฀interest฀is฀compounded฀and฀the฀ periodic฀interest฀rate฀which฀is฀applied.฀ When฀computers฀were฀scarce,฀banks฀used฀to฀compound฀interest฀periodically,฀often฀ quarterly.฀That฀meant฀that฀four฀times฀a฀year฀they฀would฀have฀an฀“interest฀day”,฀when฀ everybody’s฀balance฀got฀bumped฀up฀by฀one฀fourth฀of฀the฀going฀interest฀rate.฀If฀you฀ held฀an฀account฀in฀those฀days,฀every฀year฀your฀balance฀would฀increase฀by฀a฀factor฀of฀(1฀ +฀r/4)4,฀where฀r฀is฀the฀nominal฀annual฀interest฀rate.฀Today฀it฀is฀possible฀to฀compound฀ interest฀monthly,฀daily,฀and฀in฀the฀limiting฀case,฀continuously,฀meaning฀that฀your฀balance฀grows฀by฀a฀small฀amount฀every฀time฀instant.฀ To฀find฀the฀formula฀we฀will฀start฀out฀with฀interest฀compounded฀n฀times฀per฀year.฀Let฀P0฀ =฀P(0)฀be฀an฀initial฀amount฀in฀a฀savings฀bank฀account.฀The฀future฀value฀after฀t฀years฀is฀ ฀

฀

nt฀ r P0฀ 1+฀฀฀ ฀฀฀฀ ฀ .฀ 100n

Note฀that฀the฀total฀number฀of฀compounding฀periods฀is฀nt.฀Continuous฀compounding฀can฀ be฀thought฀as฀making฀the฀compounding฀period฀infinitely฀small,฀therefore฀achieved฀ by฀taking฀the฀limit฀of฀n฀to฀infinity.฀Thus,฀continuous฀compounding฀is฀the฀limit฀as฀the฀ compounding฀period฀approaches฀zero.฀We฀have ฀

P(t)฀=฀

nt฀ r ฀P0฀ 1+฀฀฀ ฀฀฀฀ ฀ =฀฀P0฀ 100n

r฀฀ n/r rt/100 ฀฀ ฀ ฀ ฀ ฀฀ ฀฀ 1+฀฀฀ =฀P0e0.01rt฀ 100n

The฀number฀e฀is฀the฀base฀of฀the฀natural฀logarithm฀(the฀Euler26฀number)฀and฀the฀limit฀ of฀the฀following฀sequence฀ ฀

฀฀฀฀

฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀e฀=฀

฀฀ 1฀+ ฀

฀2.7182818284…฀

We฀conclude฀that฀as฀n฀increases,฀the฀rate฀approaches฀an฀upper฀limit฀of฀er.฀This฀rate฀is฀ called฀continuous฀compounding.฀Since฀P’(t)฀=฀P0฀

฀e0.01rt฀=฀

฀P(t),฀the฀function฀

P(t)฀is฀the฀solution฀of฀the฀desired฀differential฀equation.฀ Example฀23฀(The฀Rule฀of฀72฀for฀compound฀interest)฀The฀continuous฀investment฀of฀

of฀money฀can฀be฀described฀by฀the฀ordinary฀differential฀equation฀P’(t)฀=฀0.01฀r฀P(t),฀ where฀P(t)฀is฀the฀amount฀of฀savings฀at฀time฀t฀and฀r฀is฀the฀nominal฀annual฀interest฀rate.฀ Investors฀often฀use฀a฀method฀called฀“the฀rule฀of฀72”฀which฀says฀that฀a฀number฀of฀years฀ needed฀to฀retain฀an฀investment฀before฀it฀doubles฀in฀value฀with฀the฀annual฀interest฀rate฀ r,฀is฀equal฀to฀72/r.฀Show฀that฀the฀above฀rule฀of฀72฀merely฀gives฀an฀approximation฀of฀the฀ time฀needed฀and฀find฀the฀precise฀time.฀

26฀L.฀Euler฀(1707–1783),฀a฀Swiss฀mathematician฀and฀physicist.฀

English++ Solution.฀The฀solution฀of฀the฀differential฀equation฀is฀of฀the฀form฀P(t)฀=฀P(0)e0.01rt.The฀ condition฀when฀the฀investment฀doubles฀in฀value฀at฀time฀t฀is฀written฀as฀P(t)฀=฀2P(0).฀ Hence,฀ ฀

฀

฀฀฀฀฀฀฀฀2P(0)฀=฀P(0)e0.01rt฀

which฀implies฀ln฀2฀=฀0.01rt฀and ฀

฀

฀=

฀฀฀฀฀t฀=฀

.฀

Therefore,฀according฀to฀the฀mathematical฀model,฀the฀rule฀of฀72฀should฀be฀replaced฀by฀ the฀rule฀of฀69.315.฀ Example฀24฀(Compound฀interest)฀A฀bank฀pays฀a฀yearly฀interest฀rate฀of฀5%฀compounded฀

continuously,฀the฀initial฀amount฀is฀P(0)฀=฀1000฀PLN฀ 27฀and฀no฀monies฀are฀withdrawn.฀ How฀much฀will฀be฀in฀the฀account฀after฀2฀years?฀When฀will฀the฀account฀reach฀4000฀PLN?฀ Solution.฀The฀solution฀of฀the฀differential฀equation฀is฀of฀the฀form฀P(t)฀=฀P(0)e0.01rt.฀For฀ r฀=฀5,฀P(0)฀=฀1000฀and฀t฀=฀2,฀we฀have฀ ฀

฀

฀฀฀฀฀฀P(2)฀=฀1000e0.01·5·2฀=฀1000e0.1฀=฀1105.2.฀

So,฀after฀2฀years฀there฀will฀be฀1105.2฀PLN฀in฀the฀account.฀To฀answer฀the฀second฀question,฀from฀the฀equality฀P(t)฀=฀P(0)e0.01rt฀we฀calculate฀time฀t฀and฀get฀ ฀

฀

t฀=฀

฀฀=฀20฀ln฀4฀ ฀27.73.฀฀

฀=฀

The฀account฀will฀reach฀4000฀PLN฀after฀27.73฀years.฀

10 Escape velocity Consider฀ a฀ projectile฀ of฀ constant฀ mass฀ m฀ being฀ fired฀ vertically฀ from฀ Earth.฀ Find฀ a฀ differential฀ equation฀ that฀ governs฀ the฀ motion฀ of฀ the฀ projectile฀ under฀ the฀ Earth฀฀ gravitational฀force.฀ We฀use฀Newton’s฀law฀of฀gravitation฀which฀says฀that฀the฀attractive฀force฀between฀two฀ objects฀varies฀inversely฀as฀the฀square฀of฀the฀distance฀between฀them,฀i.e.฀ ฀

฀

Fg฀=฀G฀

฀’

where฀m1฀and฀m2฀are฀the฀masses฀of฀the฀objects,฀r฀is฀the฀distance฀between฀them฀(center฀฀ to฀center),฀G฀is฀the฀constant฀of฀proportionality฀and฀Fg฀is฀the฀attractive฀force.฀ Denote฀ by฀ r฀ the฀ distance฀ between฀ the฀ projectile฀ and฀ the฀ center฀ of฀ Earth,฀ R฀ is฀ the฀฀ radius฀of฀Earth฀and฀M฀is฀the฀mass฀of฀Earth.฀Let฀t฀represent฀time฀and฀m,฀v฀the฀mass฀and฀ the฀velocity฀of฀the฀projectile฀respectively.฀From฀the฀equation฀F฀=฀-Fg,฀where฀ 27฀฀฀Polish฀zloty,฀PLN,฀is฀still฀the฀currency฀of฀Poland.฀

English++ ฀

฀

฀฀฀฀F฀=฀m฀

฀

฀฀and฀Fg฀=฀G฀

we฀have฀ ฀

฀

฀฀฀

฀฀=฀-฀

Introducing฀the฀acceleration฀due฀to฀gravity฀for฀the฀Earth฀g฀=฀

฀,฀we฀obtain฀that฀the฀

motion฀of฀projectile฀is฀governed฀by฀the฀equation฀ ฀

฀

฀฀฀

฀฀=฀-฀

฀.฀

It฀is฀useful฀to฀find฀the฀velocity฀v฀as฀a฀function฀of฀the฀distance฀r฀of฀the฀projectile฀to฀the฀ center฀of฀the฀Earth.฀Using฀the฀fact฀that฀v฀=฀ ฀from฀the฀above฀equation,฀we฀obtain฀ ฀

฀

v฀

฀=฀-฀

Integrating฀the฀equation,฀we฀find฀ ฀

฀

฀฀฀฀฀฀฀฀฀฀฀ v฀dv฀=฀-฀gR2฀

฀.

so฀its฀general฀solution฀ ฀฀

฀

฀v2(r)฀=฀

฀+฀C฀with฀C฀ ฀R.฀฀

When฀the฀projectile฀leaves฀the฀Earth’s฀surface฀with฀velocity฀v0,฀from฀the฀initial฀condition฀ v(R)฀=฀v0,฀we฀find฀C฀=฀v02-฀2gR฀and฀the฀solution฀ ฀

฀

v2(r)฀=฀฀

฀+฀v02฀-฀2gR.฀

It฀is฀clear฀that฀the฀velocity฀of฀the฀projectile฀remains฀positive฀if฀and฀only฀if฀C฀=฀v02฀-฀2gR฀>฀0.฀ The฀velocity฀ ฀

฀

ve฀=฀฀฀฀2gR

฀

is฀called฀the฀escape฀velocity฀of฀Earth.฀Assuming฀g฀=฀9.81 ฀and฀R฀=฀6370฀km,฀we฀obtain฀฀ the฀Earth฀escape฀velocity฀ ฀

฀

ve฀=฀฀฀2฀·฀9.81฀·฀637฀·฀1002฀=฀11179.31 ฀=฀11.18฀ .฀

Analogous฀calculations฀for฀the฀moon฀(the฀acceleration฀due฀to฀gravity฀for฀the฀moon฀is฀ gm฀=฀g/6฀and฀the฀radius฀of฀the฀moon฀is฀Rm฀=฀1738฀km)฀give฀ ฀฀฀฀฀฀฀฀ve฀=฀฀฀2gmRm฀=฀฀฀2฀·฀

฀·฀Rm฀=฀฀฀3.27฀·฀฀฀173.8฀·฀100฀=฀2383.93฀

฀=฀2.38฀

฀.

11 Atmospheric pressure The฀atmospheric฀pressure฀on฀Earth฀can฀be฀modeled฀assuming฀the฀rate฀of฀its฀change฀ with฀respect฀to฀the฀height฀above฀sea฀level฀is฀proportional฀to฀the฀pressure.฀Determine฀

a฀differential฀equation฀that฀governs฀this฀phenomenon.฀

English++ We฀denote฀the฀height฀above฀sea฀level฀by฀h฀and฀the฀atmospheric฀pressure฀by฀p(h).฀A฀ reasoning฀ analogous฀ to฀ that฀ presented฀ in฀ Section฀ 3฀ leads฀ to฀ the฀ following฀ Cauchy฀ problem฀for฀an฀ordinary฀differential฀equation฀of฀the฀first฀order฀ ฀

฀

฀฀฀฀฀฀฀

dp ฀=฀-kp dh฀฀ ฀฀฀฀฀฀฀฀฀฀฀ p(0)฀=฀p0

฀฀ ฀

฀

(24)฀

where฀k฀is฀a฀positive฀constant฀and฀p0฀is฀the฀pressure฀on฀sea฀level฀(where฀h฀=฀0).฀The฀ unique฀solution฀to฀(24)฀is฀the฀following฀function28฀ ฀

฀

p(h)฀=฀p0฀e-kh.฀

Example฀25฀Suppose฀that฀at฀sea฀level฀the฀atmospheric฀pressure฀is฀1013฀mbar29฀and฀

at฀an฀altitude฀of฀20฀km฀it฀is฀equal฀to฀50฀mbar.฀(a)฀Find฀the฀atmospheric฀pressure฀at฀an฀ altitude฀of฀50฀km.฀(b)฀Find฀the฀altitude฀at฀which฀the฀pressure฀is฀900฀mbar.฀ Solution.฀Let฀p0฀=฀1013,฀h฀=฀20฀and฀p(20)฀=฀50.฀We฀will฀be฀able฀to฀answer฀the฀questions฀after฀calculating฀the฀coeffcient฀k.฀From฀the฀equation฀p(h)฀=฀p0฀e-kh,฀we฀find฀ ฀

฀

k=฀

฀=฀

฀=฀0.1504km-1.฀฀

(a)฀Having฀the฀value฀of฀the฀constant฀k,฀we฀have฀ ฀

฀

p(50)฀=฀p0e-50·k฀=฀1013฀·฀e-0.1504·50฀=฀0.5484฀

which฀means฀that฀the฀atmospheric฀pressure฀at฀an฀altitude฀of฀50฀km฀is฀equal฀to฀0.55฀ mbar.฀ (b)฀The฀altitude฀can฀be฀easily฀found฀from฀the฀equation฀ ฀

฀

h฀=฀

฀=฀฀

฀=฀0.4668.฀

The฀height฀above฀sea฀level฀at฀which฀the฀pressure฀is฀900฀mbar฀is฀about฀467฀m.฀

12 Other models We฀list฀below฀a฀few฀other฀phenomena฀which฀can฀be฀modeled฀by฀differential฀equations฀of฀the฀first฀order.฀For฀more฀details,฀see฀[5].฀ Mixing฀problem.฀The฀problem฀of฀mixing฀the฀fluid฀in฀a฀tank฀is฀an฀example฀of฀a฀onecompartment฀system.฀Let฀x(t)฀denote฀the฀amount฀of฀a฀substance฀in฀a฀tank฀at฀time฀t.฀ Since฀the฀derivative฀of฀x฀with฀respect฀to฀t฀can฀be฀interpreted฀as฀the฀rate฀of฀change฀in฀the฀ amount฀of฀the฀substance฀in฀the฀tank,฀the฀problem฀is฀described฀by฀the฀following฀model฀

28฀Cf.฀also฀the฀solution฀to฀the฀equation฀of฀radioactive฀decay฀given฀by฀(4).฀ 29฀฀Recall฀that฀1฀mbar฀(millibar)฀equals฀to฀1฀hPa฀(hectopascal).฀

English++ ฀

฀

=฀input฀rate฀-฀rate฀of฀exit.฀

฀

In฀mixing฀problems,฀one฀is฀often฀given฀the฀rate฀at฀which฀a฀fluid฀containing฀the฀substance฀ flows฀ into฀ the฀ tank,฀ along฀ with฀ the฀ concentration฀ of฀ the฀ substance฀ in฀ that฀ fluid.฀The฀input฀rate฀is฀the฀product฀of฀the฀flow฀rate฀by฀the฀concentration.฀The฀output฀ rate฀of฀the฀substance฀is฀usually฀more฀difficult฀to฀determine.฀It฀is฀possible฀in฀many฀฀ practical฀problems,฀cf.฀Section฀3.2฀of฀[5].฀ Aquaculture.฀ Aquaculture฀ is฀ the฀ art฀ of฀ cultivating฀ plants฀ and฀ animals฀ indigenous฀ to฀฀ water.฀ For฀ example,฀ we฀ can฀ consider฀ a฀ batch฀ of฀ catfish฀ raised฀ in฀ a฀ pond.฀ We฀ are฀฀ interested฀ in฀ finding฀ the฀ best฀ time฀ for฀ harvesting฀ the฀ fish฀ so฀ that฀ the฀ cost฀ per฀฀ kilogram฀of฀raising฀the฀fish฀is฀minimized.฀The฀growth฀of฀fish฀can฀be฀modeled฀by฀a฀ differential฀equation฀of฀the฀form฀ ฀

฀

฀=฀kWα฀

where฀W(t)฀is฀the฀weight฀of฀the฀fish฀at฀time฀t,฀k฀and฀α฀are฀empirically฀determined฀ growth฀constants.฀ Curve฀of฀pursuit.฀An฀interesting฀geometric฀model฀arises฀when฀one฀tries฀to฀find฀the฀ path฀of฀ a฀ pursuer฀chasing฀its฀ prey.฀This฀ path฀is฀ called฀the฀ curve฀ of฀ pursuit.฀These฀ problems฀were฀analyzed฀using฀methods฀of฀the฀calculus฀of฀variations30.฀The฀simplest฀ problem฀is฀to฀determine฀the฀curve฀along฀which฀a฀vessel฀moves฀in฀pursuing฀another฀฀ vessel฀that฀flees฀along฀a฀stright฀line,฀supposing฀the฀speeds฀of฀two฀vessels฀are฀constant.฀ Secretion฀ of฀ hormones.฀ The฀ secretion฀ of฀ hormones฀ into฀ blood฀ is฀ often฀ a฀ periodic฀ activity.฀If฀a฀hormone฀is฀secreted฀on฀a฀24-hr฀cycle,฀then฀the฀rate฀of฀change฀of฀the฀level฀ of฀the฀hormone฀in฀the฀blood฀may฀be฀represented฀by฀the฀following฀Cauchy฀problem฀

฀

dx ฀=฀α -฀β cos฀ ฀-฀kx dt฀฀ ฀ x(0)฀=฀x0 , ฀

where฀x(t)฀is฀the฀amount฀of฀the฀hormone฀in฀the฀blood฀at฀time฀t,฀฀α฀is฀the฀average฀secretion฀฀ rate,฀β฀is฀the฀amount฀of฀daily฀variation฀in฀the฀secretion,฀and฀k฀is฀a฀positive฀constant฀ reflecting฀the฀rate฀at฀which฀the฀body฀removes฀the฀hormone฀from฀the฀blood.฀

30฀It฀was฀Leonardo฀da฀Vinci฀(1452-1519)฀who฀considered฀this฀problem.฀

English++ References฀ [1]฀Z.฀Denkowski,฀S.฀Migórski฀and฀N.S.฀Papageorgiou,฀ An฀Introduction฀to฀Nonlinear฀

Analysis:฀Theory.฀Kluwer฀Academic/Plenum฀Publishers,฀Boston,฀Dordrecht,฀London,฀ New฀York฀(2003).฀ [2]฀ Z.฀ Denkowski,฀ S.Migórski฀ and฀ N.S.฀ Papageorgiou,฀ An฀ Introduction฀ to฀ Nonlinear฀

Analysis:฀ Applications.฀ Kluwer฀ Academic/Plenum฀ Publishers,฀ Boston,฀ Dordrecht,฀฀ London,฀New฀York฀(2003).฀ [3]฀G.฀Duvaut฀and฀J.฀L.฀Lions,฀Inequalities฀in฀Mechanics฀and฀Physics,฀Springer฀Verlag,฀ Berlin฀(1976).฀ [4]฀N.฀Garcia฀and฀A.฀C.฀Damask,฀Physics฀for฀Computer฀Science฀Students,฀John฀Wiley฀&฀ Sons,฀New฀York,฀NY฀(1986).฀ [5]฀R.฀K.฀Nagle฀and฀E.฀B.฀Saff,฀ Fundamentals฀of฀Differential฀Equations฀and฀Boundary฀

Value฀Problems,฀Addison-Wesley,฀Reading,฀MA฀(1999).฀

English++

Exercises Pre-reading questions 1.฀Do฀you฀know฀how฀to฀build฀a฀mathematical฀model? •฀ Clearly฀state฀the฀assumptions฀on฀which฀the฀model฀will฀be฀based.฀These฀assumptions฀ should฀describe฀the฀relationships฀between฀the฀quantities฀to฀be฀studied.฀ •฀ Completely฀describe฀the฀parameters฀and฀variables฀to฀be฀used฀in฀the฀model.฀ •฀ Use฀the฀assumptions฀from฀step฀1฀to฀derive฀mathematical฀equations฀relating฀the฀ parameters฀and฀variables฀from฀step฀2.฀ 2.฀฀Do฀you฀think฀that฀theoretical฀mathematical฀model฀can฀be฀applied฀to฀solve฀practical฀ problems?

Comprehension questions 1.฀How฀can฀we฀check฀a฀model฀for฀system฀correctness?฀ •฀ In฀ general,฀ once฀ we฀ have฀ built฀ a฀ set฀ of฀ equations,฀ we฀ compare฀ the฀ data฀ generated฀by฀the฀equations฀with฀real฀data฀collected฀from฀the฀system฀(by฀measurement).฀ When฀the฀two฀sets฀of฀data฀”agree”฀(or฀are฀”sufficiently”฀close),฀฀we฀gain฀confidence฀ that฀the฀set฀of฀equations฀will฀lead฀to฀a฀good฀description฀of฀the฀real-world฀system.฀ 2.฀In฀what฀situation฀is฀the฀use฀of฀differential฀equations฀obvious?฀ •฀ Whenever฀a฀mathematical฀model฀involves฀the฀rate฀of฀change฀of฀one฀variable฀with฀ respect฀to฀another.฀ 3.฀What฀does฀Newton’s฀law฀of฀cooling฀state?฀ •฀ It฀is฀known฀from฀experimental฀observations฀that฀the฀surface฀temperature฀of฀an฀ object฀changes฀at฀a฀rate฀proportional฀to฀its฀relative฀temperature.฀The฀latter฀is฀the฀ difference฀between฀its฀temperature฀and฀the฀temperature฀of฀the฀surrounding฀environment.฀฀฀

Further reading The฀whole฀article฀is฀located฀on฀English++฀webpage.

English++

Writing Software Patterns Martin Fowler Number฀of฀words฀฀

980฀(selected฀part)

Computer฀science฀content฀฀

Medium฀

Business฀content฀฀

Medium฀

English฀language฀complexity฀฀

Medium฀

Sub-areas covered ฀Software฀engineering •฀ Object-oriented฀programming฀

Learning objectives •฀ to฀understand฀what฀design฀patterns฀are •฀ to฀see฀why฀patterns฀are฀so฀important฀in฀software฀development •฀ to฀be฀aware฀of฀the฀basic฀characteristics฀of฀patterns

Keywords •฀ design฀pattern฀-฀a฀general฀repeatable฀solution฀to฀a฀commonly฀occurring฀problem฀in฀ software฀design.฀A฀design฀pattern฀is฀not฀a฀finished฀design฀that฀can฀be฀transformed฀ directly฀into฀code.฀It฀is฀a฀description฀or฀template฀for฀how฀to฀solve฀a฀problem฀that฀ can฀be฀used฀in฀many฀different฀situations.฀ •฀ cookbook฀-฀a฀book฀of฀recipes฀and฀solutions฀for฀different฀problems฀on฀writing฀฀software,฀฀ usually฀connected฀with฀a฀particular฀programming฀language฀and฀platform฀ •฀ patterns฀book฀-฀a฀book฀on฀design฀patterns฀ •฀ identity฀map฀-฀a฀database฀access฀design฀pattern฀used฀to฀improve฀performance฀by฀ providing฀a฀context-specific฀in-memory฀cache฀to฀prevent฀duplicate฀retrieval฀of฀the฀ same฀object฀data฀from฀the฀database฀ •฀ decorator฀pattern฀-฀a฀design฀pattern฀that฀allows฀new/additional฀behaviour฀to฀be฀ added฀to฀an฀existing฀class฀dynamically฀

Summary Martin฀Fowler฀is฀a฀famous฀author฀and฀international฀speaker฀on฀software฀architecture,฀ specializing฀in฀object-oriented฀analysis฀and฀design,฀UML,฀patterns,฀and฀agile฀software฀ development฀methodologies,฀including฀extreme฀programming.฀His฀article฀is฀a฀kind฀of฀ introduction฀to฀the฀software฀design฀process.฀He฀is฀trying฀to฀show,฀with฀a฀handful฀of฀ examples,฀why฀design฀patterns฀are฀important฀in฀software฀engineering.฀

English++ Martin฀ Fowler,฀ autor฀ licznych฀ prac฀ związanych฀ z฀ inżynierią฀ oprogramowania,฀ specjalizujący฀się฀między฀innymi฀w฀projektowaniu฀i฀programowaniu฀obiektowo-orientowanym,฀UML,฀wzorcach฀projektowych฀i฀“zwinnych”฀technikach฀wytwarzania฀oprogramowania฀ (agile฀ software฀ development฀ methodologies),฀ w฀ tym฀ także฀ w฀ technice฀ programowania฀“ekstremalnego”.฀Jego฀artykuł฀stanowi฀rodzaj฀wstępu฀do฀opisu฀procesu฀ projektowania฀ oprogramowania.฀ Autor฀ wyjaśnia฀ znaczenie฀ wzorców฀ projektowych฀฀ w฀tym฀procesie,฀popierając฀swoją฀wypowiedź฀licznymi฀przykładami.฀

Pre-reading questions 1.฀What฀do฀you฀think฀might฀help฀in฀building฀software?฀What฀could฀make฀this฀process฀ faster฀and฀more฀effective? 2.฀Do฀you฀think฀that฀using฀ordinary฀solutions฀might฀help฀or฀would฀that฀be฀useless฀in฀ a฀specific฀task? 3.฀What฀types฀of฀software฀patterns฀do฀you฀know?฀Which฀one฀is฀your฀favourite฀and฀ why?

English++

Writing Software Patterns What is a Pattern? A฀common฀definition฀of฀a฀pattern฀is฀that฀it฀is฀a฀solution฀to฀a฀problem฀in฀a฀context.฀

identity฀map

That’s฀a฀definition฀that’s฀always฀struck฀me฀as฀being฀rather฀unhelpful.฀

a฀database฀access฀

For฀me,฀a฀pattern฀is฀primarily฀a฀way฀to฀chunk฀up฀advice฀about฀a฀topic.฀Chunking฀is฀฀ important฀because฀there’s฀such฀a฀huge฀amount฀of฀knowledge฀you฀need฀to฀write฀software.฀฀ As฀a฀result฀there฀needs฀be฀ways฀to฀divide฀knowledge฀up฀so฀you฀don’t฀need฀to฀remember฀฀ it฀all฀-฀what฀you฀need฀is฀to฀be฀able฀to฀get฀at฀a฀particular฀chunk฀of฀knowledge฀when฀you฀ need฀it.฀Only฀then฀do฀you฀need฀details.฀

design฀pattern฀used฀to฀ improve฀performance฀ by฀providing฀ a฀context-specific฀ in-memory฀cache฀ to฀prevent฀

The฀solution฀provides฀a฀useful฀focus฀for฀the฀chunking.฀With฀some฀young฀eager฀pro-

duplicate฀retrieval฀of฀the฀

grammer฀ asking฀ some฀ grizzly฀ veteran฀ (i.e.฀ anyone฀ over฀ thirty)฀ how฀ to฀ deal฀ with฀ a฀

same฀object฀data฀

particular฀situation฀and฀hear฀the฀veteran฀say฀“oh฀-฀you’ll฀need฀an฀identity฀map฀there”.฀

from฀the฀database

The฀colleague฀can฀then฀look฀up฀identity฀map฀in฀some฀suitable฀patterns฀book.฀ So฀to฀make฀this฀chunking฀work฀each฀pattern฀should฀name฀a฀solution.฀This฀solution฀ should฀be฀concrete,฀at฀least฀at฀the฀level฀of฀discussion฀we฀are฀talking฀about.฀You฀should฀ be฀ able฀ to฀ go฀ away฀ and฀ use฀ the฀ pattern฀ once฀ you’re฀ given฀ the฀ reference.฀ If฀ you’re฀฀ successful฀the฀name฀should฀enter฀the฀vocabulary฀of฀the฀profession.฀It฀can฀take฀a฀while฀

patterns฀book

to฀do฀this,฀but฀when฀you฀say฀‘decorator’฀any฀reasonable฀professional฀should฀know฀

a฀book฀on฀design฀patterns

what฀you฀mean.฀ Patterns฀should฀have฀recurrence,฀which฀means฀the฀solution฀must฀be฀applicable฀in฀lots฀ of฀different฀situations.฀If฀you฀are฀talking฀about฀something฀that’s฀a฀one-off,฀then฀it’s฀ not฀adding฀the฀name฀to฀the฀profession’s฀vocabulary.฀ One฀ of฀ the฀ interesting฀ things฀ here฀ is฀ that฀ a฀ singular฀ solution฀ can฀ often฀ lead฀ to฀ a฀฀ recurrent฀pattern.฀This฀usually฀crops฀up฀when฀you฀see฀two฀different฀singular฀solutions฀฀ which฀look฀completely฀different฀on฀the฀surface,฀yet฀have฀a฀deeper฀similarity฀-฀what฀ Christopher฀Alexander*฀refers฀to฀as฀the฀“core฀of฀the฀solution”.฀Let฀me฀give฀an฀example฀฀ for฀this.฀I฀was฀looking฀at฀one฀of฀our฀early฀Java฀web฀projects.฀On฀this฀project฀the฀team฀

*฀ Christopher฀ Alexander฀ (born฀ October฀ 4,฀ 1936฀ in฀ Vienna,฀ Austria)฀ is฀ an฀ architect฀ noted฀ for฀ his฀theories฀about฀design.฀฀He฀concluded฀that฀many฀design฀problems฀are฀so฀complex฀and฀so฀฀ ancient฀that฀they฀are฀best฀resolved฀by฀learning฀from฀solutions฀which฀have฀proved฀successful฀over฀ an฀endless฀period฀of฀time.฀He฀describes฀these฀solutions฀as฀‘archetypes’฀or฀‘patterns’.฀They฀are฀฀ particularly฀useful฀in฀outdoor฀design,฀where฀patterns฀are฀comparatively฀easy฀to฀identify฀and฀ difficult฀ to฀ explain.฀ He฀ characterizes฀ this฀ approach฀ in฀ the฀ following฀ words:฀ “Each฀ pattern฀฀ describes฀a฀problem฀which฀occurs฀over฀and฀over฀again฀in฀our฀environment,฀and฀then฀describes฀ the฀core฀of฀the฀solution฀to฀that฀problem฀in฀such฀a฀way฀that฀you฀can฀use฀this฀solution฀a฀million฀times฀over,฀without฀ever฀doing฀it฀the฀same฀way฀twice”฀:฀http://www.lih.gre.ac.uk/resource/฀ archetype.htm

English++ wasn’t฀allowed฀to฀use฀JSPs.฀So฀they฀wrote฀a฀set฀of฀Java฀classes฀which฀walked฀through฀ a฀structure฀of฀domain฀objects,฀and฀produced฀the฀appropriate฀HTML฀for฀a฀particular฀ domain฀object.฀They฀noticed฀they฀were฀getting฀duplication฀in฀the฀code฀for฀spitting฀ design฀pattern

out฀common฀HTML฀structures฀for฀fields,฀tables,฀etc.฀So฀they฀pulled฀all฀of฀the฀HTML฀

a฀general฀repeatable฀

spitting฀code฀out฀into฀a฀second฀utility฀class฀that฀had฀methods฀like฀renderField฀(String฀

solution฀to฀a฀commonly฀

label).฀When฀they฀did฀this฀they฀noticed฀that฀they฀could฀make฀drastic฀changes฀to฀the฀

occurring฀problem ฀in฀software฀design.฀ A฀design฀pattern฀is฀not฀ a฀finished฀design฀ that฀can฀be฀transformed฀ directly฀into฀code.฀ It฀is฀a฀description฀฀

entire฀web฀application’s฀appearance฀just฀by฀altering฀code฀in฀the฀utility฀class.฀ Later฀ on฀ I฀ saw฀ a฀ different฀ project.฀ They฀ were฀ using฀ XSLT฀ to฀ turn฀ XML฀ into฀ HTML฀ pages,฀much฀as฀I฀do฀on฀this฀site.฀But฀they฀needed฀to฀support฀multiple฀organizations฀ who฀wanted฀the฀same฀data฀displayed฀in฀their฀own฀format.฀So฀they฀split฀the฀transformation฀into฀two฀steps,฀first฀producing฀an฀intermediate฀XML฀with฀elements฀like฀field฀ and฀table,฀with฀the฀second฀stage฀actually฀producing฀the฀HTML.฀They฀would฀have฀a฀ different฀second฀stage฀for฀each฀organization.฀

or฀template฀for฀how฀to฀ solve฀a฀problem฀that฀

Although฀it฀seems฀obvious฀as฀I฀write฀it฀now,฀฀when฀I฀first฀saw฀these฀two฀projects฀I฀

can฀be฀used฀in฀many฀

sensed฀there฀was฀something฀similar฀in฀their฀approaches.฀However,฀it฀took฀me฀several฀

different฀situations.฀

months฀to฀understand฀the฀key฀point฀-฀splitting฀a฀transformation฀into฀two฀steps:฀logical฀฀ page฀and฀physical฀(HTML)฀page.฀This฀is฀the฀“core฀of฀the฀solution”฀which฀I฀wrote฀up฀ as฀Two฀Step฀View.฀One฀of฀the฀great฀intellectual฀challenges฀of฀patterns฀is฀finding฀and฀ isolating฀this฀core฀amongst฀all฀the฀surrounding฀stuff฀that’s฀needed฀on฀real฀projects.฀

Patterns versus Recipes decorator฀pattern

A฀popular,฀and฀very฀effective,฀form฀of฀technical฀writing฀is฀the฀cookbook฀style฀(eg฀The฀Perl฀

a฀design฀pattern฀

Cookbook,฀Rails฀Recipes).฀There฀is฀a฀lot฀of฀similarity฀between฀cookbooks฀and฀patterns฀฀

that฀allows฀new/additional฀ behaviour฀to฀be฀added฀ to฀an฀existing฀class฀ dynamically

books.฀Both฀emphasize฀a฀problem-solution฀style.฀ I฀see฀the฀big฀difference฀between฀the฀two฀in฀the฀notion฀of฀building฀a฀vocabulary.฀Recipes฀฀ tend฀ to฀ be฀ more฀ particular,฀ usually฀ tied฀ to฀ a฀ particular฀ programming฀ language฀ and฀ platform.฀Even฀when฀patterns฀are฀tied฀to฀a฀platform,฀they฀try฀to฀describe฀more฀general฀ concepts.฀ As฀ a฀ consequence฀ of฀ this฀ recipes฀ have฀ a฀ stronger฀ problem฀ focus฀ than฀ the฀ solution฀ focus฀in฀patterns.฀ Although฀my฀writing฀interest฀is฀in฀patterns,฀this฀reflects฀my฀interest฀in฀general฀design฀ principles฀rather฀than฀a฀judgment฀on฀the฀relative฀usefulness฀of฀the฀two฀styles.฀Both฀are฀ effective฀for฀same฀basic฀reason฀-฀they฀chunk฀based฀on฀a฀concrete฀thing฀somebody฀wants฀ to฀get฀done฀today.฀As฀a฀result฀I฀find฀both฀very฀effective.฀You฀can฀also฀learn฀great฀principles฀฀ from฀them,฀but฀it’s฀the฀answers฀to฀particular฀questions฀that฀bring฀you฀to฀the฀table.฀

100

English++ Why are Patterns important? One฀of฀the฀quotes฀that฀I฀find฀particularly฀appealing฀when฀I฀think฀about฀the฀need฀for฀

cookbook

patterns฀that฀that฀part฀of฀interest฀in฀patterns฀came฀from฀“…observations฀that฀projects฀

a฀book฀of฀recipes฀

fail฀despite฀the฀latest฀technology฀for฀lack฀of฀ordinary฀solutions”[PLoPD฀1].฀Patterns฀

and฀solutions฀

provide฀a฀way฀to฀organize฀and฀name฀those฀ordinary฀solutions฀to฀make฀it฀easier฀for฀

for฀different฀problems฀

people฀to฀use฀them.฀

on฀writing฀software,฀

Since฀ these฀ solutions฀ are฀ ordinary,฀ it’s฀ common฀ that฀ experts฀ in฀ a฀ field฀ won’t฀ find฀฀ anything฀new฀in฀a฀patterns฀book.฀For฀such฀people฀the฀biggest฀value฀of฀a฀patterns฀book฀ is฀to฀help฀them฀to฀pass฀on฀the฀solutions฀to฀their฀colleagues.฀

usually฀connected฀with฀ a฀particular฀programming฀ language฀and฀platform.฀

Despite฀my฀liking฀for฀patterns,฀I฀don’t฀think฀that฀patterns฀are฀the฀right฀approach฀for฀ all฀situations.฀Even฀in฀my฀own฀latest฀patterns฀book,฀I฀used฀a฀mixture฀of฀patterns฀and฀ narrative฀text.฀I฀think฀the฀patterns฀helped฀focus฀the฀narrative฀and฀provided฀a฀good฀ way฀ for฀ me฀ to฀ separate฀ the฀ details฀ of฀ the฀ solutions฀ from฀ the฀ overview฀ discussion฀฀ of฀ them.฀ Patterns฀ are฀ a฀ communication฀ medium,฀ and฀ like฀ any฀ communication฀฀ technique฀ there฀ are฀ situations฀ where฀ they฀ work฀ well฀ and฀ those฀ where฀ they฀ work฀ badly.฀Practice฀and฀familiarity฀help฀you฀tell฀the฀difference.฀

101

English++

Exercises Pre-reading questions 1.฀What฀do฀you฀think฀might฀help฀in฀building฀software?฀What฀could฀make฀this฀process฀ faster฀and฀more฀effective? 2.฀Do฀you฀think฀that฀using฀ordinary฀solutions฀might฀help฀or฀would฀that฀be฀useless฀in฀ a฀specific฀task? 3.฀What฀types฀of฀software฀patterns฀do฀you฀know?฀Which฀one฀is฀your฀favourite฀and฀ why?

Comprehension questions 1.฀What฀are฀the฀differences฀and฀similarities฀between฀cookbooks฀and฀pattern฀books? 2.฀What฀are฀the฀main฀characteristics฀of฀patterns?฀Name฀at฀least฀three฀key฀features฀ of฀them.฀ •฀ chunking฀information,฀naming฀a฀solution,฀recurrence/core฀of฀the฀solution฀ 3.฀What฀do฀you฀understand฀by: a.฀recurrence฀of฀the฀pattern?฀ •฀ solution฀must฀be฀applicable฀in฀different฀situations b.฀core฀of฀the฀solution?฀ •฀ a฀deeper฀similarity฀of฀problems 4.฀Why฀are฀ordinary฀solutions฀so฀important?฀How฀can฀they฀help฀in฀writing฀software?฀ •฀ e.g.฀by฀providing฀well-known฀and฀tested฀solutions฀for฀new฀problems 5.฀Explain฀how฀patterns฀can฀be฀used฀as฀a฀communication฀technique.

Further exercises •฀฀Are฀the฀following฀statements฀TRUE฀or฀FALSE? 1.฀The฀author฀defines฀a฀pattern฀as฀the฀solution฀to฀a฀problem฀in฀a฀context.฀ ฀

(FALSE)

2.฀ According฀ to฀ the฀ author฀ of฀ the฀ text,฀ dividing฀ knowledge฀ up฀ simplifies฀ writing฀฀ software.฀ ฀

(TRUE)

3.฀If฀you฀find฀a฀solution฀to฀a฀singular฀problem฀it’s฀completely฀useless฀as฀a฀pattern.฀ (FALSE,฀you฀can฀evolve฀it฀into฀a฀wide-context฀solution) 4.฀ In฀ the฀ author’s฀ opinion,฀ recipes฀ are฀ more฀ general฀ than฀ patterns฀ and฀ you฀ can฀฀ basically฀learn฀principles฀from฀them.฀ ฀

(FALSE)฀

5.฀ The฀ main฀ similarity฀ between฀ recipes฀ and฀ patterns฀ is฀ the฀ idea฀ of฀ chunking฀฀ information฀to฀make฀finding฀answers฀for฀particular฀questions฀easier.฀ ฀

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(TRUE)

6.฀The฀author฀recommends฀using฀patterns฀in฀all฀possible฀situations.฀ ฀

(FALSE)

English++ •฀Find฀words฀or฀phrases฀in฀the฀text฀that฀match฀the฀folowing฀meanings: 1.฀break฀up,฀divide฀up฀something฀(e.g.฀information,฀text);฀[chunk฀up] 2.฀to฀try฀to฀find฀a฀piece฀of฀information฀in฀a฀book฀or฀on฀a฀computer;฀[look฀up] 3.฀affecting฀or฀relating฀to฀a฀person฀or฀thing;฀[applicable] 4.฀make฀a฀useful฀contribution฀to฀a฀discussion;฀[bring฀to฀the฀table] 5.฀release฀(e.g.฀results);฀[spit฀out] 6.฀belief฀or฀idea,฀approach฀to฀some฀problem฀[notion]

Possible topics for discussion •฀ What฀are฀design฀patterns฀in฀architecture?฀ •฀ What฀could฀this฀term฀refer฀to฀in฀software฀engineering?฀ •฀ Which฀design฀patterns฀have฀you฀met฀so฀far?฀(e.g.฀MVC฀-฀Model-View-Controller)฀

Possible difﬁculties No฀difficulties฀should฀be฀found฀in฀that฀part฀of฀the฀article.

Reading suggestions •฀ http://en.wikipedia.org/wiki/Design_pattern_(computer_science)฀ •฀ Erich฀Gamma,฀Richard฀Helm,฀Ralph฀Johnson฀and฀John฀Vlissides:฀Design฀Patterns:฀ Elements฀of฀Reusable฀Object-Oriented฀Software฀

Possible links to other topics •฀ SoftwareEntropy฀ •฀ SoftwareDevelopmentProcess฀ •฀ ExtremeProgramming฀฀

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English++

Cyber Warfare: Reality or Box Ofﬁce Hit? Randy Nash Number฀of฀words฀฀

฀

1600

Computer฀science฀content฀฀

Medium

English฀language฀complexity฀฀

Medium

Learning objectives •฀ to฀acquire฀basic฀knowledge฀about฀cyber฀threats •฀ to฀acquire฀knowledge฀about฀types฀of฀cyber฀attacks

Sub-areas covered •฀ Network฀safety •฀ ฀cyber฀attacks

Keywords •฀ cyber฀war฀-฀the฀usage฀of฀computers฀and฀the฀Internet฀in฀conducting฀warfare฀in฀the฀ cyberspace •฀ cyber฀vandalism฀฀-฀cyber฀attacks฀that฀deface฀web฀pages •฀ hacktivism฀-฀combination฀of฀words:฀“hack(er)”฀and฀“activism”฀ •฀ Denial฀of฀Service฀-฀a฀kind฀of฀cyber฀attack฀which฀results฀in฀unavailability฀of฀service.฀ It฀uses฀two฀methods:฀forcing฀the฀targeted฀computer(s)฀to฀reset,฀thus฀consuming฀ its฀resources฀so฀that฀it฀can฀no฀longer฀provide฀its฀intended฀service;฀or฀obstructing฀฀ the฀ communication฀ media฀ between฀ the฀ intended฀ users฀ and฀ the฀ victim฀ so฀ that฀ they฀can฀no฀longer฀communicate฀adequately.฀ •฀ mainframe฀-฀computer฀used฀by฀large฀companies฀for฀critical฀operations฀like฀financial฀฀ transaction฀processing฀ •฀ bot฀-฀a฀program฀used฀on฀the฀Internet฀that฀performs฀a฀repetitive฀function฀such฀as฀ posting฀a฀message฀to฀multiple฀newsgroups฀or฀searching฀for฀information฀or฀news •฀ botnet฀-฀a฀collection฀of฀software฀robots,฀or฀bots฀linked฀and฀cooperating฀฀with฀each฀ other

Summary A฀short฀text,฀which฀is฀a฀good฀introduction฀to฀the฀topic฀of฀network฀security.฀There฀is฀

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a฀presentation฀of฀cyberterrorism฀as฀a฀new฀threat.฀The฀majority฀of฀people฀are฀not฀yet฀ aware฀of฀how฀dangerous฀this฀phenomenon฀is.฀The฀author฀gives฀examples฀of฀the฀largest฀฀

English++ attacks฀in฀the฀past฀and฀describes฀the฀most฀popular฀techniques.฀The฀article฀is฀also฀a฀ good฀introduction฀to฀a฀long฀discussion฀about฀prevention,฀awareness฀of฀the฀threat฀and฀ the฀future. Krótki฀tekst฀wprowadzający฀w฀tematykę฀bezpieczeństwa฀w฀sieci.฀Przedstawia฀wizję฀ zupełnie฀nowego฀rodzaju฀zagrożenia฀jakim฀jest฀cyberterroryzm.฀Autorem฀jest฀Randy฀ Nash,฀który฀oprócz฀kilku฀artykułów฀na฀portalu฀InformIT.com,฀prowadzi฀swój฀własny฀ blog฀ nt฀ związane฀ z฀ bezpieczeństwem฀ w฀ sieci.฀ Autor฀ podaje฀ przykłady฀ największych฀ ataków฀w฀historii฀i฀opisuje฀pokrótce฀kilka฀najpopularniejszych฀technik.฀Artykuł฀ponad-฀ to฀prowokuje฀do฀dyskusji฀o฀świadomości฀zagrożenia,฀prewencji฀i฀przyszłości.

Pre-reading questions 1.฀ What฀does฀the฀threat฀of฀cyber฀terrorism฀mean฀to฀you?฀ 2.฀ Where,฀in฀your฀opinion,฀does฀the฀main฀threat฀of฀cyber฀terrorism฀come฀from? 3.฀ Have฀you฀thought฀about฀the฀threat฀of฀cyber฀terrorism?

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English++

Cyber Warfare: Reality or Box Ofﬁce Hit? The฀ specter฀ of฀ cyber฀ warfare฀ has฀ reared฀ its฀ ugly฀ head฀ in฀ the฀ media฀ again.฀ Some฀฀ experts฀seem฀to฀think฀that฀the฀future฀is฀here,฀and฀battles฀will฀be฀fought฀and฀won฀via฀ the฀Internet.฀But฀how฀much฀of฀this฀can฀be฀considered฀actual฀warfare,฀and฀how฀much฀ is฀hype?฀Randy฀Nash฀searches฀for฀a฀working฀definition฀of฀cyber฀warfare,฀looks฀at฀the฀ historical฀ profile฀ of฀ attacks,฀ and฀ discusses฀ the฀ potential฀ of฀ a฀ devastating฀ electronic฀ Pearl฀Harbor.฀ cyber฀war the฀usage฀of฀computers฀

The฀threat฀of฀cyber฀warfare฀has฀been฀brought฀forth฀again฀by฀the฀media;฀not฀only฀in฀news฀ outlets฀but฀also฀in฀the฀entertainment฀industry.฀But฀is฀this฀threat฀real฀or฀imagined?฀

and฀the฀Internet฀ in฀conducting฀warfare฀ in฀the฀cyberspace

What Is Cyber Warfare? To฀properly฀assess฀the฀risk,฀we฀first฀need฀a฀working฀definition฀of฀what฀cyber฀war฀is฀ and฀how฀it฀might฀manifest.฀There฀is฀much฀disagreement฀about฀the฀term฀and฀its฀actual฀

cyber฀vandalism cyber฀attacks฀ that฀deface฀web฀pages

definition,฀and฀varying฀degrees฀in฀the฀types฀of฀cyber฀attacks฀that฀might฀be฀perpetrated.฀฀ I฀ think฀ cyber฀ warfare฀ has฀ some฀ critical฀ characteristics.฀ First,฀ warfare฀ is฀ considered฀ the฀process฀of฀military฀struggle฀between฀two฀nations฀or฀groups฀of฀nations.฀Warfare฀ generally฀includes฀attacks฀against฀critical฀communications฀channels,฀and฀against฀the฀ military฀and฀civilian฀population฀resulting฀in฀loss฀of฀life.฀Next,฀the฀cyber฀aspect฀can฀ be฀considered฀to฀refer฀to฀the฀realm฀of฀electronic฀communication.฀So฀I฀think฀we฀can฀฀ summarize฀the฀definition฀of฀cyber฀war฀as฀follows:฀cyber฀war฀(Cyber฀warfare):฀the฀process฀฀ of฀military฀struggle฀between฀two฀nations฀or฀groups฀of฀nations฀conducted฀via฀various฀ forms฀of฀electronic฀communications,฀or฀the฀Internet,฀resulting฀in฀the฀disruption฀of฀ communications฀and/or฀loss฀of฀life.฀

What Is It Not? Okay,฀we฀have฀a฀definition฀of฀cyber฀war,฀but฀what฀are฀other฀forms฀of฀cyber฀threats฀ that฀would฀not฀fit฀into฀the฀definition฀of฀cyber฀warfare?฀Here’s฀a฀list฀of฀some฀online฀ threats฀that฀I฀don’t฀feel฀fall฀into฀the฀warfare฀category:฀ Cyber฀vandalism:฀This฀is฀primarily฀the฀“script฀kiddies”฀that฀consider฀defacing฀a฀website฀ to฀be฀“hacking.”฀I฀think฀of฀this฀as฀electronic฀graffiti.฀This฀is฀low-level฀harassment. Civil฀disobedience฀or฀hacktivism:฀Hacktivism฀or฀Electronic฀Civil฀Disobedience฀(ECD)฀ generally฀takes฀some฀form฀of฀Denial฀of฀Service฀(DoS)฀attack฀against฀the฀website฀of฀ some฀ target,฀ usually฀ political฀ in฀ nature.฀ Those฀ who฀ consider฀ themselves฀ hactivists฀ claim฀that฀hacktivism฀is฀the฀fusion฀of฀hacking฀and฀activism;฀politics฀and฀technology.฀ More฀specifically,฀hacktivism฀is฀described฀as฀hacking฀for฀a฀political฀cause.฀Furthermore,฀฀ hacktivists฀ claim฀ that฀ Electronic฀ Civil฀ Disobedience฀ (ECD)฀ is฀ a฀ legitimate฀ form฀ of฀฀

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nonviolent,฀direct฀action฀utilized฀to฀bring฀pressure฀on฀institutions฀engaged฀in฀unethical฀฀ or฀ criminal฀ actions.฀ Within฀ the฀ electronic฀ environment,฀ ECD฀ aims฀ to฀ disrupt฀ the฀

English++ operation฀of฀information฀and฀capital฀flows฀of฀carefully฀selected฀target฀sites฀without฀ causing฀serious฀damage.฀ Cyber฀crime:฀Cyber฀crime฀can฀take฀many฀different฀forms;฀theft฀of฀intellectual฀property,฀฀ extortion฀based฀on฀the฀threat฀of฀DDOS฀attacks,฀fraud฀based฀on฀identity฀theft,฀espionage,฀฀

฀

and฀so฀on.฀ While฀ each฀ of฀ these฀ types฀ of฀ activities฀ is฀ criminal฀ in฀ nature฀ and฀ might฀ constitute฀ an฀aspect฀of฀cyber฀warfare฀actions,฀they฀do฀not฀constitute฀cyber฀war฀by฀themselves.฀ These฀actions,฀while฀criminal฀in฀nature,฀are฀generally฀not฀going฀to฀cost฀lives฀or฀affect฀ military฀operations.฀

What is the Real Threat?

Denial฀of฀Service

The฀threat฀comes฀primarily฀from฀nation฀states฀with฀the฀will,฀motive,฀and฀technology฀฀

a฀kind฀of฀cyber฀attack฀

to฀ launch฀ attacks฀ against฀ the฀ United฀ States.฀ In฀ fact,฀ nations฀ that฀ do฀ not฀ possess฀ a฀

which฀results฀in฀

powerful฀ military฀ are฀ probably฀ more฀ likely฀ to฀ choose฀ this฀ form฀ of฀ attack฀ because฀

unavailability฀of฀service.฀

of฀its฀much฀lower฀cost฀of฀implementation฀(think฀“asymmetric฀warfare”).฀The฀most฀฀

It฀uses฀two฀methods:฀

obvious฀avenues฀of฀attack฀would฀be฀against฀our฀nation’s฀critical฀infrastructure,฀so฀the฀

forcing฀the฀targeted฀

government฀formed฀a฀body฀to฀analyze฀any฀threats฀against฀our฀infrastructure.฀This฀body,฀

computer(s)฀to฀reset,฀

originally฀known฀as฀the฀President’s฀Critical฀Infrastructure฀Protection฀Board฀(PCCIB),฀฀

thus฀consuming฀

is฀now฀known฀as฀the฀National฀Infrastructure฀Advisory฀Council฀(NIAC)฀and฀operates฀

its฀resources฀so฀that฀

within฀the฀U.S.฀Department฀of฀Homeland฀Security.฀This฀council฀provides฀the฀President฀฀

it฀can฀no฀longer฀provide฀

with฀advice฀on฀the฀security฀of฀the฀critical฀infrastructure฀sectors฀and฀their฀information฀

its฀intended฀service;฀

systems.฀Over฀time,฀the฀sectors฀identified฀as฀belonging฀to฀the฀critical฀infrastructure฀

or฀obstructing฀

have฀changed.฀

the฀communication฀media฀ between฀the฀intended฀

Historical Precedents Just฀as฀our฀understanding฀of฀this฀critical฀infrastructure฀has฀changed฀and฀matured฀over฀ time,฀so฀has฀the฀threat.฀These฀threats฀have฀existed฀for฀some฀time.฀Back฀in฀May฀1998,฀ all฀seven฀members฀of฀the฀L0pht฀(Brian฀Oblivion,฀Kingpin,฀Mudge,฀Space฀Rogue,฀Stefan฀

users฀and฀the฀victim฀so฀ that฀they฀can฀ no฀longer฀communicate฀ adequately.

Von฀Neumann,฀John฀Tan,฀and฀Weld฀Pond)฀famously฀testified฀before฀the฀Congress฀of฀ the฀United฀States฀that฀they฀could฀shut฀down฀the฀entire฀Internet฀in฀30฀minutes.฀ NOTE฀Selected฀transcripts฀are฀in฀the฀section฀entitled฀“WEAK฀COMPUTER฀SECURITY฀ IN฀GOVERNMENT:฀IS฀THE฀PUBLIC฀AT฀RISK?”฀MAY฀19–20,฀1998—COMMITTEE฀ON฀ GOVERNMENTAL฀AFFAIRS.฀ Shortly฀ after฀ this฀ testimony,฀ the฀ first฀ distributed฀ denial-of-service฀ (DDoS)฀ attacks฀฀ appeared.฀The฀first฀well-documented฀DDoS฀attack฀appears฀to฀have฀occurred฀in฀August฀ 1999,฀ when฀ a฀ DDoS฀ tool฀ called฀ Trinoo฀ (described฀ below)฀ was฀ deployed฀ in฀ at฀ least฀ 227฀systems,฀of฀which฀at฀least฀114฀were฀on฀Internet2,฀to฀flood฀a฀single฀University฀of฀฀

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English++ Minnesota฀computer.฀This฀system฀was฀knocked฀off฀the฀air฀for฀more฀than฀two฀days.฀ In฀the฀following฀months,฀Yahoo!,฀Amazon,฀Buy.com,฀CNN,฀and฀eBay฀were฀all฀hit฀with฀ similar฀ attacks.฀ These฀ commerce฀ sites฀ suffered฀ large฀ financial฀ losses฀ during฀ the฀฀ downtime฀because฀of฀these฀attacks.฀Today,฀incredibly฀large฀and฀complex฀botnets฀exist฀ that฀can฀be฀used฀to฀launch฀a฀variety฀of฀attacks฀against฀multiple฀targets.฀ mainframe

The฀current฀focus฀of฀these฀botnets฀appears฀to฀be฀primarily฀SPAM฀and฀DDoS฀attacks,฀

฀computer฀used฀

but฀ they฀ could฀ easily฀ be฀ used฀ in฀ cyber฀ warfare฀ activities.฀ Other฀ attacks฀ of฀ historic฀฀

by฀large฀companies฀f or฀critical฀operations฀ like฀financial฀transaction฀ processing฀

significance฀include฀the฀following:฀ Solar฀Sunrise:฀Solar฀Sunrise฀is฀the฀name฀given฀to฀a฀series฀of฀attacks฀against฀the฀Pentagon฀฀ and฀MIT฀in฀February฀1998.฀The฀Department฀of฀Defense฀called฀these฀attacks฀“the฀most฀ organized฀and฀systematic฀attack฀to฀date.”฀The฀DoD฀actually฀declared฀the฀U.S.฀to฀be฀in฀ a฀state฀of฀“cyber฀war.”฀These฀attacks฀appeared฀to฀be฀originating฀from฀Russian-owned฀ IP฀address฀space,฀so฀the฀attack฀was฀considered฀to฀be฀“state-sponsored.”฀ Moonlight฀ Maze:฀ Moonlight฀ Maze฀ refers฀ to฀ an฀ incident฀ in฀ which฀ U.S.฀ officials฀฀ accidentally฀discovered฀a฀pattern฀of฀probing฀of฀computer฀systems฀at฀the฀Pentagon,฀ NASA,฀Energy฀Department,฀private฀universities,฀and฀research฀labs฀that฀began฀in฀March฀ 1998฀and฀went฀on฀for฀nearly฀two฀years.฀It฀seems฀that฀these฀hackers฀had฀been฀able฀ to฀access฀tens฀of฀thousands฀of฀files฀(including฀maps฀of฀military฀installations,฀troop฀ configurations,฀and฀military฀hardware฀designs).฀The฀Defense฀Department฀traced฀the฀ attacks฀back฀to฀a฀mainframe฀computer฀in฀the฀former฀Soviet฀Union.฀

bot a฀program฀used฀ on฀the฀Internet฀that฀ performs฀a฀repetitive฀ function฀such฀as฀posting฀

Titan฀Rain:฀Titan฀Rain฀is฀the฀name฀given฀to฀a฀well-organized฀Chinese฀military฀hacking฀฀ effort฀ against฀ the฀ U.S.฀ military.฀ The฀ hackers,฀ believed฀ to฀ have฀ been฀ based฀ in฀ the฀฀ Chinese฀ province฀ of฀ Guangdong,฀ are฀ thought฀ to฀ have฀ stolen฀ U.S.฀ military฀ secrets,฀฀ including฀aviation฀specifications฀and฀flight-planning฀software.฀These฀attacks฀apparently฀฀ started฀in฀2003฀and฀lasted฀until฀2005.฀

a฀message฀to฀multiple฀ newsgroups฀or฀searching฀

Current Situations

for฀information฀or฀news

Much฀of฀the฀news฀related฀to฀cyber฀warfare฀tends฀to฀be฀a฀bit฀“sensational”.฀For฀example:฀ Russia฀accused฀of฀unleashing฀cyber฀war฀to฀disable฀Estonia,฀Estonia฀hit฀by฀“Moscow฀ cyber฀war”,฀Cyber฀war:฀Russia฀vs.฀Estonia.฀ All฀this฀sounds฀very฀dramatic฀and฀serious,฀but฀let’s฀look฀at฀the฀details.฀On฀April฀27,฀฀ officials฀ in฀ Estonia฀ relocated฀ the฀ “Bronze฀ Soldier,”฀ a฀ Soviet-era฀ war฀ memorial฀฀ commemorating฀an฀unknown฀Russian฀who฀died฀fighting฀the฀Nazis.฀This฀led฀to฀political฀฀ furor฀among฀ethnic฀Russians฀and฀to฀the฀blockading฀of฀the฀Estonian฀Embassy฀in฀Moscow.฀ The฀event฀also฀marked฀the฀beginning฀of฀a฀large฀and฀sustained฀distributed฀denial-of฀

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-service฀attack฀on฀several฀Estonian฀national฀Web฀sites,฀including฀those฀of฀government฀

English++ ministries฀and฀the฀prime฀minister’s฀Reform฀Party.฀There฀were฀no฀attacks฀against฀any฀ critical฀infrastructure฀or฀services.฀This฀was฀simply฀a฀political฀statement.฀At฀the฀most,฀ I’d฀refer฀to฀this฀event฀as฀hacktivism,฀and฀most฀likely฀launched฀by฀a฀group฀of฀hackers฀ that฀have฀no฀affiliation฀with฀any฀government฀agency.฀It฀seems฀there฀was฀no฀cyber฀war฀ after฀all.฀But฀wait,฀that’s฀not฀all:฀America฀prepares฀for฀“cyber฀war”฀with฀China!฀ Is฀Cyber฀war฀really฀that฀imminent?฀Are฀we฀about฀to฀fall฀under฀an฀attack฀of฀bits฀and฀ bytes?฀A฀report฀in฀the฀UK฀branch฀of฀ZDNet฀proclaimed฀Cyber฀warfare฀“a฀reality฀in฀12฀ months.”฀ Unfortunately,฀that฀report฀was฀back฀in฀January฀2004.฀The฀article฀is฀a฀good฀source฀of฀

botnet

information฀about฀the฀types฀of฀vulnerable฀systems฀that฀may฀be฀attacked,฀but฀their฀

a฀collection฀of฀

predicted฀timeline฀is฀way฀off.฀.

software฀robots,฀

Cyber฀Warfare—An฀analysis฀of฀the฀means฀and฀motivations฀of฀selected฀nation฀states฀ For฀ a฀ more฀ measured฀ appraisal,฀ I฀ recommend฀ this฀ report,฀ which฀ was฀ written฀ in฀฀ response฀to฀a฀grant฀provided฀by฀the฀Department฀of฀Homeland฀Security.฀This฀report฀

or฀bots฀linked฀ and฀cooperating฀฀ with฀each฀other฀

is฀ an฀ assessment฀ of฀ potential฀ foreign฀ computer฀ threats฀ to฀ information฀ technology฀ networks฀in฀the฀United฀States.฀This฀is฀one฀of฀the฀most฀level-headed฀write-ups฀I’ve฀ seen฀to-date.฀

Looking to the Future There฀should฀be฀little฀doubt฀that฀future฀wars฀will฀inevitably฀include฀cyber฀warfare฀ tactics.฀It฀is฀increasingly฀apparent฀that฀other฀nations฀are฀gearing฀up฀to฀take฀advantage฀ of฀the฀ever-increasing฀complexity฀and฀inter-connected฀nature฀of฀various฀national฀infrastructures.฀ Current฀ efforts฀ at฀ security฀ computer฀ systems฀ and฀ networks฀ will฀ likely฀ prove฀ to฀ be฀฀

hacktivism

insufficient฀ to฀ prevent฀ such฀ future฀ attacks.฀ The฀ U.S.฀ military฀ has฀ been฀ developing฀

combination฀of฀words:฀

cyber฀warfare฀strategies฀for฀some฀time.฀

“hack(er)”฀

It฀appears฀that฀even฀Al฀Qaeda฀has฀been฀developing฀cyber฀war฀capabilities.฀With฀our฀

and฀“activism”

enemies฀ working฀ toward฀ this฀ goal,฀ we฀ obviously฀ cannot฀ overlook฀ the฀ possibilities.฀ The฀ scenario฀ in฀ the฀ movie฀ Live฀ Free฀ or฀ Die฀ Hard฀ might฀ seem฀ farfetched,฀ but฀ the฀฀ potential฀exists฀for฀some฀of฀the฀attacks฀portrayed฀in฀that฀movie฀(although฀it฀won’t฀be฀ nearly฀as฀easy฀as฀it฀seemed฀on฀the฀big฀screen).฀I’m฀hoping฀that฀somewhere฀in฀either฀ our฀government฀or฀military฀cyberdefense฀forces฀we฀have฀our฀own฀John฀McClane?

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English++

Exercises Pre-reading questions 1.฀ What฀does฀the฀threat฀of฀cyber฀terrorism฀mean฀to฀you?฀ •฀ dangerous฀financial฀transactions •฀ theft฀data฀from฀hard฀disk •฀ eavesdrop฀traffic฀in฀network฀ 2.฀ Where,฀in฀your฀opinion,฀does฀the฀main฀threat฀of฀cyber฀terrorism฀come฀from? •฀ nowadays฀-฀hackers฀acted฀individually,฀usually฀want฀to฀prove฀their฀skills •฀ in฀the฀future฀–฀very฀good฀organised฀teams฀of฀specialists,฀supported฀by฀government฀ institutions 3.฀ Have฀you฀thought฀about฀the฀threat฀of฀cyber฀terrorism?

Comprehension questions 1.฀ ฀Using฀the฀information฀in฀the฀text฀about฀the฀first฀DDoS฀attack฀and฀your฀own฀ knowledge,฀try฀to฀explain฀how฀DDoS฀works? •฀ A฀distributed฀denial฀of฀service฀attack฀occurs฀when฀multiple฀compromised฀systems฀ flood฀the฀bandwidth฀or฀resources฀of฀a฀targeted฀system,฀usually฀one฀or฀more฀web฀ servers.฀It฀uses฀two฀methods:฀forcing฀the฀targeted฀computer(s)฀to฀reset,฀consume฀ its฀resources฀such฀that฀it฀can฀no฀longer฀provide฀its฀intended฀service฀or฀obstructing฀฀ the฀ communication฀ media฀ between฀ the฀ intended฀ users฀ and฀ the฀ victim฀ so฀ that฀ they฀can฀no฀longer฀communicate฀adequately. 2.฀ ฀Can฀you฀name฀the฀large-scale฀attacks฀and฀who฀they฀were฀directed฀against? •฀ Solar฀Sunrise:฀Solar฀Sunrise฀is฀the฀name฀given฀to฀a฀series฀of฀attacks฀against฀the฀ Pentagon฀and฀MIT฀in฀February฀1998. •฀ Moonlight฀ Maze:฀ Moonlight฀ Maze฀ refers฀ to฀ an฀ incident฀ in฀ which฀ U.S.฀ officials฀฀ accidentally฀discovered฀a฀pattern฀of฀probing฀of฀computer฀systems฀at฀the฀Pentagon,฀ NASA,฀Energy฀Department,฀private฀universities,฀and฀research฀labs฀that฀began฀in฀ March฀1998฀and฀went฀on฀for฀nearly฀two฀years. •฀ Titan฀ Rain:฀ Titan฀ Rain฀ is฀ the฀ name฀ given฀ to฀ a฀ well-organized฀ Chinese฀ military฀ hacking฀effort฀against฀the฀U.S.฀military.

Further exercises In฀groups,฀explain฀the฀meaning฀of฀these฀words:฀ •฀ hacktivism฀ •฀ mainframe฀ •฀ cyberdefense฀ •฀ bot฀ •฀ botnet฀

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Compare฀your฀answers฀with฀other฀groups.฀฀

English++

Possible topics for discussion 1.฀ Do฀you฀know฀of฀any฀other฀kinds฀of฀cyber฀attacks฀or฀threats?฀Which฀do฀you฀think,฀ are฀the฀most฀dangerous฀for฀you? 2.฀ Are฀you฀afraid฀of฀this฀kind฀of฀threat?฀Do฀you฀think฀you฀might฀lose฀something฀in฀a฀ cyber฀attack?

Possible difﬁculties The฀article฀contains฀a฀lot฀of฀factual฀information,฀but฀it฀should฀make฀it฀easier฀to฀read.฀฀

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English++

Evolutionary Database Design Martin Fowler & Pramod Sadalage Number฀of฀words฀฀฀

4345฀

Computer฀science฀content฀฀

Medium฀

English฀language฀complexity฀฀

Medium฀

Sub-areas covered •฀ database฀design฀ •฀ agile฀methodologies

Learning objectives •฀ to฀understand฀the฀differences฀between฀up-front฀and฀agile฀methodologies •฀ to฀see฀why฀team฀communication฀is฀so฀important฀while฀working฀on฀a฀project •฀ to฀understand฀what฀is฀meant฀by฀฀refactoring฀

Keywords database฀-฀software฀designed฀for฀holding฀large฀amounts฀of฀data database฀schema฀-฀a฀description฀of฀the฀tables฀and฀views฀in฀a฀database฀together฀with฀ the฀relationships฀between฀them Agile฀ Methodology฀ -฀ a฀ particular฀ method฀ of฀ producing฀ software,฀ emphasising฀฀ self-organizing฀teams฀and฀broad฀customer-programmer฀contact XP฀ (extreme฀ programming)฀ -฀ a฀ programing฀ methodology฀ which฀ is฀ very฀ closely฀฀ connected฀with฀the฀Agile฀style฀ up-front฀designing฀-฀describes฀a฀method฀in฀which฀the฀design฀phase฀of฀a฀project฀is฀ completed฀before฀the฀coding฀of฀the฀project฀begins DBA฀-฀database฀administrator;฀the฀main฀role฀of฀a฀database฀administrator฀has฀to฀do฀ with฀ overseeing฀ the฀ installation฀ and฀ ongoing฀ function฀ of฀ software฀ on฀ a฀ system฀ designed฀for฀use฀by฀a฀number฀of฀users refactoring฀ -฀ making฀ changes฀ to฀ a฀ computer฀ system฀ (e.g.฀ source฀ code,฀ database)฀ that฀improve฀its฀readability฀and฀฀simplify฀its฀structure฀without฀adding฀any฀new฀฀ functionality;฀for฀example,฀changing฀the฀names฀of฀variables฀to฀be฀more฀readable฀

Summary Martin฀ Fowler฀ is฀ a฀ widely฀ acknowledged฀ expert฀ in฀ the฀ areas฀ of฀ software฀ design,฀฀ methodologies฀ and฀ design฀ patterns.฀ In฀ this฀ article฀ he฀ introduces฀ an฀ alternative฀ (to฀฀

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waterfall฀ methodology)฀ method฀ of฀ developing฀ databases฀ and฀ programs.฀ The฀ main฀

English++ idea฀is฀to฀regard฀database฀design฀as฀an฀evolutionary฀process.฀ Tekst,฀choć฀dość฀długi,฀ciekawie฀przedstawia฀podejście฀do฀projektowania฀baz฀danych฀฀ w฀ sposób฀ podobny฀ do฀ zwinnego฀ programowania.฀ Artykuł฀ wprowadza฀ w฀ tematykę฀ tej฀nowej฀metodologii,฀jako฀alternatywy฀dla฀tzw.฀metodologii฀“waterfall”.฀Dostajemy฀ wiele฀ informacji฀ na฀ temat฀ tego฀ jak฀ traktować฀ projektowanie฀ baz฀ danych฀ w฀ sposób฀ jakby฀to฀był฀duży฀ewoluujący฀obiekt.฀

Pre-reading questions 1.฀Have฀you฀heard฀about฀Agile฀Methodology?฀What฀are฀they฀used฀for? 2.฀What฀does฀DBA฀stand฀for? 3.฀What฀are฀DBA’s฀functions?

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English++

Evolutionary Database Design Abstract database

Over฀ the฀ last฀ few฀ years฀ the฀ authors฀ have฀ developed฀ a฀ number฀ of฀ techniques฀ that฀฀

software฀

allow฀a฀database฀design฀to฀evolve฀as฀an฀application฀develops.฀This฀is฀a฀very฀important฀฀

designed฀for฀holding฀

capability฀ for฀ agile฀ methodologies.฀ The฀ techniques฀ rely฀ on฀ applying฀ continuous฀฀

large฀amounts฀of฀data฀

integration฀and฀automated฀refactoring฀to฀database฀development,฀together฀with฀a฀close฀ collaboration฀between฀DBAs฀and฀application฀developers.฀The฀techniques฀work฀in฀both฀ pre-production฀and฀released฀systems.฀ In฀the฀last฀few฀years,฀we’ve฀seen฀the฀rise฀of฀a฀new฀breed฀of฀software฀methodologies,฀ the฀agile฀methodologies.฀These฀make฀some฀new฀and฀significant฀demands฀on฀database฀ design.฀One฀of฀the฀most฀central฀of฀these฀demands฀is฀the฀idea฀of฀evolutionary฀design.฀ On฀an฀agile฀project฀you฀assume฀that฀you฀cannot฀fix฀the฀requirements฀of฀the฀system฀ up-front.฀ As฀ a฀ result฀ having฀ a฀ detailed฀ design฀ phase฀ at฀ the฀ beginning฀ of฀ a฀ project฀฀ becomes฀ impractical.฀ The฀ design฀ of฀ the฀ system฀ has฀ to฀ evolve฀ through฀ the฀ various฀ iterations฀of฀the฀software.฀Agile฀methods,฀in฀particular฀extreme฀programming฀(XP),฀ have฀a฀number฀of฀practices฀that฀make฀this฀evolutionary฀design฀practical.฀ Many฀people฀have฀questioned฀whether฀evolutionary฀design฀can฀be฀applied฀to฀a฀system฀ ฀with฀a฀large฀database฀component.฀Indeed฀many฀people฀told฀us฀that฀it฀was฀impossible฀ -฀a฀troubling฀thought฀as฀ThoughtWorks฀embarked฀on฀a฀large฀database-oriented฀project฀ using฀many฀agile฀and฀XP฀techniques.฀ This฀article฀describes฀the฀practices฀that฀we’ve฀used฀to฀allow฀us฀to฀do฀this฀impossible฀ thing.฀We฀won’t฀say฀that฀we’ve฀completely฀solved฀the฀database฀evolution฀problem,฀ but฀we฀do฀think฀we’ve฀demonstrated฀a฀set฀of฀techniques฀that฀many฀people฀will฀find฀ useful.฀

Dealing with Change One฀of฀the฀primary฀features฀of฀agile฀methods฀is฀their฀attitude฀towards฀change.฀Most฀ of฀the฀thinking฀about฀software฀process฀is฀about฀understanding฀requirements฀early,฀ signing฀ off฀ on฀ these฀ requirements,฀ using฀ the฀ requirements฀ as฀ a฀ basis฀ for฀ design,฀฀ signing฀ off฀ on฀ that,฀ and฀ then฀ proceeding฀ with฀ construction.฀ This฀ is฀ a฀ plan-driven฀฀ cycle,฀often฀referred฀to฀(usually฀with฀derision)฀as฀the฀waterfall฀approach.฀฀ Such฀approaches฀look฀to฀minimize฀changes฀by฀doing฀extensive฀up-front฀work.฀Once฀the฀ early฀work฀is฀done,฀changes฀cause฀significant฀problems.฀As฀a฀result฀such฀approaches฀฀ run฀into฀trouble฀if฀requirements฀are฀changing,฀and฀requirements฀churn฀is฀a฀big฀problem฀฀ for฀such฀processes.฀

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English++ Agile฀processes฀approach฀change฀differently.฀They฀seek฀to฀embrace฀change,฀allowing฀ changes฀ to฀ occur฀ even฀ late฀ in฀ a฀ development฀ project.฀ Changes฀ are฀ controlled,฀ but฀ the฀attitude฀of฀the฀process฀is฀to฀enable฀change฀as฀much฀as฀possible.฀Partly฀this฀is฀in฀ response฀to฀the฀inherent฀instability฀of฀requirements฀in฀many฀projects,฀partly฀it฀is฀to฀ better฀ support฀ dynamic฀ business฀ environments฀ by฀ helping฀ them฀ change฀ with฀ the฀ competitive฀pressures.฀ In฀order฀to฀make฀this฀work,฀you฀need฀a฀different฀attitude฀to฀design.฀Instead฀of฀thinking฀฀ of฀design฀as฀a฀phase,฀which฀is฀mostly฀completed฀before฀you฀begin฀construction,฀you฀

database฀schema

look฀at฀design฀as฀an฀on-going฀process฀that฀is฀interleaved฀with฀construction,฀testing,฀

a฀description฀of฀the฀tables฀

and฀even฀delivery.฀This฀is฀the฀contrast฀between฀planned฀and฀evolutionary฀design.฀One฀

and฀views฀

of฀the฀vital฀contributions฀of฀agile฀methods฀is฀that฀they฀have฀come฀up฀with฀practices฀฀

in฀a฀database฀together฀

that฀allow฀evolutionary฀design฀to฀work฀in฀a฀controlled฀manner.฀So฀instead฀of฀the฀common฀฀

with฀the฀relationships฀

chaos฀that฀often฀happens฀when฀design฀isn’t฀planned฀up-front,฀these฀methods฀provide฀

between฀them

techniques฀to฀control฀evolutionary฀design฀and฀make฀them฀practical.฀ An฀ important฀ part฀ of฀ this฀ approach฀ is฀ iterative฀ development,฀ where฀ you฀ run฀ the฀฀ entire฀software฀life-cycle฀many฀times฀during฀the฀life฀of฀a฀project.฀Agile฀processes฀run฀ complete฀life฀cycles฀in฀each฀iteration,฀completing฀the฀iteration฀with฀working,฀tested,฀ integrated฀code฀for฀a฀small฀subset฀of฀the฀requirements฀of฀the฀final฀product.฀These฀ iterations฀are฀short,฀usually฀running฀between฀a฀week฀and฀a฀couple฀of฀months,฀with฀a฀ preference฀towards฀shorter฀iterations.฀ While฀these฀techniques฀have฀grown฀in฀use฀and฀interest,฀one฀of฀the฀biggest฀questions฀ is฀how฀to฀make฀evolutionary฀design฀work฀for฀databases.฀Most฀people฀consider฀that฀ database฀design฀is฀something฀that฀absolutely฀needs฀up-front฀planning.฀Changing฀the฀ database฀ schema฀ late฀ in฀ the฀ development฀ tends฀ to฀ cause฀ widespread฀ breakages฀ in฀ application฀ software.฀ Furthermore฀ changing฀ a฀ schema฀ after฀ deployment฀ results฀ in฀ painful฀data฀migration฀problems.฀ Over฀the฀course฀of฀the฀last฀three฀years฀we’ve฀been฀involved฀in฀a฀large฀project฀(called฀ Atlas)฀ that฀ has฀ used฀ evolutionary฀ database฀ design฀ and฀ made฀ it฀ work.฀ The฀ project฀฀ involved฀almost฀100฀people฀in฀multiple฀sites฀world-wide฀(US,฀Australia,฀and฀India).฀It฀ is฀around฀half฀a฀million฀lines฀of฀code฀and฀has฀over฀200฀tables.฀The฀database฀evolved฀฀ during฀a฀year฀and฀a฀half฀of฀initial฀development฀and฀continues฀to฀evolve฀even฀though฀it’s฀ in฀production฀for฀multiple฀customers.฀During฀this฀project฀we฀started฀with฀iterations฀฀ of฀a฀month,฀but฀after฀a฀few฀months฀changed฀to฀two฀week฀iterations฀which฀worked฀ better.฀ The฀ techniques฀ we฀ describe฀ here฀ are฀ the฀ ones฀ that฀ we฀ (or฀ more฀ accurately฀ Pramod)฀used฀to฀make฀this฀work.฀ Since฀that฀project฀got฀going฀we’ve฀spread฀these฀techniques฀over฀more฀of฀our฀projects,฀ gaining฀more฀experience฀from฀more฀cases.฀We’ve฀also฀found฀inspiration,฀ideas,฀and฀ experience฀from฀other฀agile฀projects.฀

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English++ Limitations Before฀we฀dive฀into฀the฀techniques,฀it’s฀important฀to฀state฀that฀we฀haven’t฀solved฀all฀ the฀problems฀of฀evolutionary฀database฀design.฀In฀particular:฀ •฀ We฀ developed฀ an฀ application฀ database฀ for฀ a฀ single฀ application฀ rather฀ than฀ an฀฀ integration฀database฀that฀tries฀to฀integrate฀multiple฀databases.฀ •฀ We฀don’t฀have฀to฀keep฀the฀production฀databases฀up฀24/7฀ We฀don’t฀consider฀these฀problems฀to฀be฀inherently฀unsolvable,฀after฀all฀many฀people฀ believed฀we฀couldn’t฀solve฀this฀one.฀But฀until฀we฀do,฀we฀won’t฀claim฀we฀can฀solve฀ them฀either.฀

The Practices Our฀ approach฀ to฀ evolutionary฀ database฀ design฀ depends฀ on฀ a฀ handful฀ of฀ important฀ practices.฀

DBAs collaborate closely with developers One฀of฀the฀tenets฀of฀agile฀methods฀is฀that฀people฀with฀different฀skills฀and฀backgrounds฀ need฀to฀collaborate฀very฀closely฀together.฀They฀can’t฀communicate฀mainly฀through฀ formal฀meetings฀and฀documents.฀Instead฀they฀need฀to฀be฀out฀talking฀with฀each฀other฀ and฀working฀with฀each฀other฀all฀the฀time.Everybody฀is฀affected฀by฀this:฀analysts,฀PMs,฀ domain฀experts,฀developers…฀and฀DBAs.฀ Every฀task฀that฀a฀developer฀works฀on฀potentially฀needs฀a฀DBA’s฀help.฀Both฀the฀developers฀฀ and฀the฀DBA฀need฀to฀consider฀whether฀a฀development฀task฀is฀going฀to฀make฀a฀significant฀฀ change฀to฀the฀database฀schema.฀If฀so฀the฀developer฀needs฀to฀consult฀with฀the฀DBA฀ to฀decide฀how฀to฀make฀the฀change.฀The฀developer฀knows฀what฀new฀functionality฀is฀ needed,฀and฀the฀DBA฀has฀a฀global฀view฀of฀the฀data฀in฀the฀application.฀ To฀make฀this฀happen฀the฀DBA฀has฀to฀make฀himself฀approachable฀and฀available.฀Make฀ it฀easy฀for฀a฀developer฀to฀just฀pop฀over฀for฀a฀few฀minutes฀and฀ask฀some฀questions.฀ Make฀ sure฀ the฀ DBAs฀ and฀ developers฀ sit฀ close฀ to฀ each฀ other฀ so฀ they฀ can฀ easily฀ get฀ together.฀Ensure฀that฀application฀design฀sessions฀are฀known฀about฀so฀the฀DBA฀can฀ pop฀ in฀ easily.฀ In฀ many฀ environments฀ we฀ see฀ people฀ erecting฀ barriers฀ between฀ the฀ DBA฀and฀application฀development฀functions.฀These฀barriers฀must฀come฀down฀for฀an฀ evolutionary฀database฀design฀process฀to฀work.฀

Everybody gets their own database instance Evolutionary฀design฀recognizes฀that฀people฀learn฀by฀trying฀things฀out.฀In฀programming฀฀ terms฀developers฀experiment฀with฀how฀to฀implement฀a฀certain฀feature฀and฀may฀make฀ a฀few฀attempts฀before฀settling฀down฀to฀a฀preferred฀alternative.฀Database฀design฀can฀be฀

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English++ like฀that฀too.฀As฀a฀result฀it’s฀important฀for฀each฀developer฀to฀have฀their฀own฀sandbox฀ where฀they฀can฀experiment,฀and฀not฀have฀their฀changes฀affect฀anyone฀else.฀ Many฀DBA฀experts฀see฀multiple฀databases฀as฀anathema,฀too฀difficult฀to฀work฀in฀practice,฀฀ but฀we’ve฀found฀that฀you฀can฀easily฀manage฀a฀hundred฀or฀so฀database฀instances.฀The฀ vital฀thing฀is฀to฀have฀to฀tools฀to฀allow฀you฀to฀manipulate฀databases฀much฀as฀you฀would฀ manipulate฀files.฀

Developers frequently integrate into a shared master Although฀developers฀can฀experiment฀frequently฀in฀their฀own฀area,฀it’s฀important฀to฀ bring฀the฀different฀approaches฀back฀together฀again฀frequently.฀An฀application฀needs฀ a฀shared฀master฀database฀that฀all฀work฀flows฀from.฀When฀a฀developer฀begins฀a฀task฀ they฀copy฀the฀master฀into฀their฀own฀workspace,฀manipulate,฀and฀then฀integrate฀their฀ changes฀back฀into฀the฀master.฀As฀a฀rule฀of฀ thumb฀each฀developer฀should฀integrate฀ once฀a฀day.฀

DBA

Let’s฀take฀an฀example฀where฀Mike฀starts฀a฀development฀task฀at฀10am฀(assuming฀he฀

database฀administrator;฀

actually฀comes฀in฀that฀early).฀As฀part฀of฀this฀task฀he฀needs฀to฀change฀the฀database฀

the฀main฀role฀

schema.฀If฀the฀change฀is฀easy,฀like฀adding฀a฀column,฀he฀just฀decides฀how฀to฀make฀the฀

of฀a฀database฀administrator฀

change฀himself,฀Mike฀also฀makes฀sure฀the฀column฀he฀wants฀to฀add฀does฀not฀already฀

has฀to฀do฀with฀

exist฀ in฀ the฀ database,฀ with฀ the฀ help฀ of฀ the฀ data฀ dictionary฀ (discussed฀ later).฀ If฀ it’s฀

overseeing฀the฀installation฀

more฀complicated฀then฀he฀grabs฀the฀DBA฀and฀talks฀over฀the฀likely฀changes฀with฀him.฀

and฀ongoing฀function฀

Once฀he’s฀ready฀to฀begin฀he฀takes฀a฀copy฀of฀the฀database฀master฀and฀can฀modify฀both฀ the฀database฀schema฀and฀code฀freely.฀As฀he’s฀in฀a฀sandbox฀any฀changes฀he฀makes฀don’t฀ impact฀anyone฀else’s.฀At฀some฀point,฀say฀around฀3pm,฀he’s฀pretty฀comfortable฀that฀he฀ knows฀what฀the฀database฀change฀needs฀to฀be,฀even฀though฀he’s฀not฀completely฀done฀

of฀software฀ on฀a฀system฀designed฀ for฀use฀by฀a฀number฀ of฀users

with฀his฀programming฀task.฀At฀that฀point฀he฀grabs฀the฀DBA,฀and฀tells฀him฀about฀the฀ change.฀At฀this฀point฀the฀DBA฀can฀raise฀any฀issues฀that฀Mike฀hasn’t฀considered.฀Most฀ of฀the฀time฀all฀is฀well฀and฀the฀DBA฀goes฀off฀and฀makes฀the฀change฀(by฀applying฀one฀or฀ more฀database฀refactorings,฀which฀we’ll฀come฀to฀below).฀The฀DBA฀makes฀the฀changes฀ right฀away฀(unless฀they฀are฀destructive฀changes฀-฀again฀more฀on฀that฀below).฀Mike฀can฀ continue฀to฀work฀on฀his฀task฀and฀commit฀his฀code฀any฀time฀he฀likes฀once฀the฀DBA฀has฀ applied฀these฀changes฀to฀the฀master.฀ You฀may฀well฀recognize฀this฀principle฀as฀similar฀to฀the฀practice฀of฀Continuous฀Integration,฀฀ which฀is฀applied฀to฀source฀code฀management.฀Indeed฀this฀is฀really฀about฀treating฀the฀ database฀as฀another฀piece฀of฀source฀code.฀As฀such฀the฀master฀database฀is฀kept฀under฀ configuration฀management฀in฀much฀the฀same฀way฀as฀the฀source฀code.฀Whenever฀we฀ have฀a฀successful฀build,฀the฀database฀is฀checked฀into฀the฀configuration฀management฀ system฀together฀with฀the฀code,฀so฀that฀we฀have฀a฀complete฀and฀synchronized฀version฀ history฀of฀both.฀

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English++ With฀source฀code,฀much฀of฀the฀pain฀of฀integration฀is฀handled฀by฀source฀code฀control฀ systems.฀For฀databases฀there’s฀a฀bit฀more฀effort฀involved.฀Any฀changes฀to฀the฀database฀฀ need฀to฀done฀properly,฀as฀automated฀database฀refactorings,฀which฀we’ll฀discuss฀shortly.฀฀ In฀addition฀the฀DBA฀needs฀to฀look฀at฀any฀database฀changes฀and฀ensure฀that฀they฀fit฀ within฀ the฀ overall฀ scheme฀ of฀ the฀ database฀ schema.฀ For฀ this฀ to฀ work฀ smoothly,฀ big฀ changes฀shouldn’t฀come฀as฀surprises฀at฀integration฀time฀-฀hence฀the฀need฀for฀the฀DBA฀ to฀collaborate฀closely฀with฀the฀developers.฀ up-front฀designing

We฀emphasize฀integrating฀frequently฀because฀we’ve฀found฀that฀it’s฀much฀easier฀to฀

฀describes฀a฀method฀

do฀ frequent฀ small฀ integrations฀ rather฀ than฀ infrequent฀ large฀ integrations.฀ It฀ seems฀

in฀which฀the฀design฀phase฀

that฀the฀pain฀of฀integration฀increases฀exponentially฀with฀the฀size฀of฀the฀integration.฀

of฀a฀project฀is฀completed฀

As฀such฀doing฀many฀small฀changes฀is฀much฀easier฀in฀practice,฀even฀though฀it฀often฀

before฀the฀coding฀

seems฀counter-intuitive฀to฀many.฀This฀same฀effect’s฀been฀noticed฀by฀people฀in฀the฀

of฀the฀project฀begins

Software฀Configuration฀Management฀community฀for฀source฀code.฀

A database consists of schema and test data When฀we฀talk฀about฀a฀database฀here,฀we฀mean฀not฀just฀the฀schema฀of฀the฀database,฀ but฀also฀a฀fair฀amount฀of฀data.฀This฀data฀consists฀of฀common฀standing฀data฀for฀the฀ application,฀such฀as฀the฀inevitable฀list฀of฀all฀the฀states฀in฀the฀US,฀and฀also฀sample฀test฀ data฀such฀as฀a฀few฀sample฀customers.฀ The฀ data฀ is฀ there฀ for฀ a฀ number฀ of฀ reasons.฀ The฀ main฀ reason฀ is฀ to฀ enable฀ testing.฀ We฀are฀great฀believers฀in฀using฀a฀large฀body฀of฀automated฀tests฀to฀help฀stabilize฀the฀ development฀of฀an฀application.฀Such฀a฀body฀of฀tests฀is฀a฀common฀approach฀in฀agile฀ methods.฀For฀these฀tests฀to฀work฀efficiently,฀it฀makes฀sense฀to฀work฀on฀a฀database฀that฀ is฀seeded฀with฀some฀sample฀test฀data,฀which฀all฀tests฀can฀assume฀is฀in฀place฀before฀ they฀run.฀ As฀well฀as฀helping฀test฀the฀code,฀this฀sample฀test฀data฀also฀allows฀to฀test฀our฀migrations฀฀ as฀we฀alter฀the฀schema฀of฀the฀database.฀By฀having฀sample฀data,฀we฀are฀forced฀to฀ensure฀฀ that฀any฀schema฀changes฀also฀handle฀sample฀data.฀ In฀most฀projects฀we’ve฀seen฀this฀sample฀data฀be฀fictional.฀However฀in฀a฀few฀projects฀ we’ve฀ seen฀ people฀ use฀ real฀ data฀ for฀ the฀ samples.฀ In฀ these฀ cases฀ this฀ data’s฀ been฀฀ extracted฀from฀prior฀legacy฀systems฀with฀automated฀data฀migration฀scripts.฀Obviously฀ you฀can’t฀migrate฀all฀the฀data฀right฀away,฀as฀in฀early฀iterations฀only฀a฀small฀part฀of฀the฀ database฀is฀actually฀built.฀But฀the฀idea฀is฀to฀iteratively฀develop฀the฀migration฀scripts฀ just฀as฀the฀application฀and฀the฀database฀are฀developed฀iteratively.฀Not฀only฀does฀this฀ help฀flush฀out฀migration฀problems฀early,฀it฀makes฀it฀much฀easier฀for฀domain฀experts฀ to฀work฀with฀the฀growing฀system฀as฀they฀are฀familiar฀with฀the฀data฀they฀are฀looking฀

118

at฀and฀can฀often฀help฀to฀identify฀problem฀cases฀that฀may฀cause฀problems฀for฀the฀da-

English++ tabase฀and฀application฀design.฀As฀a฀result฀we฀are฀now฀of฀the฀view฀that฀you฀should฀try฀ to฀introduce฀real฀data฀from฀the฀very฀first฀iteration฀of฀your฀project.฀

All changes are database refactorings The฀technique฀of฀refactoring฀is฀all฀about฀applying฀disciplined฀and฀controlled฀techniques฀฀ to฀ changing฀ an฀ existing฀ code฀ base.฀ Similarly฀ we’ve฀ identified฀ several฀ database฀฀ refactorings฀that฀provide฀similar฀control฀and฀discipline฀to฀changing฀a฀database.฀ One฀ of฀ the฀ big฀ differences฀ about฀ database฀ refactorings฀ is฀ that฀ they฀ involve฀ three฀฀ different฀changes฀that฀have฀to฀be฀done฀together฀ •฀ Changing฀the฀database฀schema฀ •฀ Migrating฀the฀data฀in฀the฀database฀ •฀ Changing฀the฀database฀access฀code฀ Thus฀ whenever฀ we฀ describe฀ a฀ database฀ refactoring,฀ we฀ have฀ to฀ describe฀ all฀ three฀฀ aspects฀of฀the฀change฀and฀ensure฀that฀all฀three฀are฀applied฀before฀we฀apply฀any฀other฀ refactorings.฀ We฀are฀still฀in฀the฀process฀of฀documenting฀the฀various฀database฀refactorings,฀so฀we฀ aren’t฀ able฀ to฀ go฀ into฀ detail฀ on฀ them฀ yet.฀ However฀ there฀ are฀ a฀ few฀ things฀ we฀ can฀ point฀out.฀Like฀code฀refactorings,฀database฀refactorings฀are฀very฀small.฀The฀concept฀of฀ chaining฀together฀a฀sequence฀of฀very฀small฀changes฀is฀much฀the฀same฀for฀databases฀ as฀it฀is฀for฀code.฀The฀triple฀nature฀of฀the฀change฀makes฀it฀all฀the฀more฀important฀to฀ keep฀to฀small฀changes.฀ Many฀database฀refactorings,฀such฀as฀adding฀a฀column,฀can฀be฀done฀without฀having฀to฀ update฀all฀the฀code฀that฀accesses฀the฀system.฀If฀code฀uses฀the฀new฀schema฀without฀ being฀aware฀of฀it,฀the฀column฀will฀just฀go฀unused.฀Many฀changes,฀however฀don’t฀have฀ this฀property.฀We฀call฀these฀destructive฀changes,฀an฀example฀of฀which฀is฀making฀an฀ existing฀nullable฀column฀not฀null.฀ Destructive฀changes฀need฀a฀bit฀more฀care,฀the฀degree฀of฀which฀depends฀on฀the฀degree฀ of฀destruction฀involved.฀An฀example฀of฀a฀minor฀destructive฀change฀is฀that฀of฀changing฀ a฀column฀from฀nullable฀to฀not฀null.฀In฀this฀case฀you฀can฀probably฀just฀go฀ahead฀and฀ do฀it.฀The฀refactoring฀will฀take฀care฀of฀any฀data฀in฀the฀database฀that’s฀null.฀Usually฀the฀ only฀developer฀who฀cares฀about฀this฀property฀is฀the฀one฀who฀requested฀the฀change,฀ and฀that฀developer฀will฀update฀the฀database฀mapping฀code.฀As฀a฀result฀the฀update฀ won’t฀break฀anyone฀else’s฀code฀and฀if฀by฀some฀strange฀chance฀it฀does,฀they฀find฀out฀ as฀soon฀as฀they฀run฀a฀build฀and฀use฀their฀tests.฀(On฀our฀large฀project฀we฀gave฀ourselves฀ some฀extra฀breathing฀space฀by฀waiting฀a฀week฀before฀making฀the฀database฀change.)฀ Splitting฀a฀heavily฀used฀table฀into฀two฀however฀is฀a฀rather฀more฀complicated฀case.฀In฀ this฀case฀it’s฀important฀to฀let฀everyone฀know฀that฀the฀change฀is฀coming฀up฀so฀they฀can฀

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English++ prepare฀themselves฀for฀it.฀In฀addition฀it’s฀worth฀waiting฀for฀a฀safer฀moment฀to฀make฀ the฀change.฀(These฀kinds฀of฀changes฀we฀would฀defer฀until฀the฀start฀of฀a฀new฀iteration฀ -฀we฀like฀to฀use฀iterations฀of฀two฀weeks฀or฀less).฀ The฀important฀thing฀here฀is฀to฀choose฀a฀procedure฀that’s฀appropriate฀for฀the฀kind฀of฀ change฀that฀you’re฀making.฀If฀in฀doubt฀try฀to฀err฀on฀the฀side฀of฀making฀changes฀easier.฀ Our฀experience฀is฀that฀we฀got฀burned฀much฀less฀frequently฀than฀many฀people฀would฀ think,฀and฀with฀a฀strong฀configuration฀control฀of฀the฀entire฀system฀it’s฀not฀difficult฀to฀ revert฀should฀the฀worst฀happen.฀

Automate the refactorings Agile฀Methodology

In฀the฀world฀of฀code฀we฀are฀seeing฀tools฀for฀some฀languages฀to฀automate฀many฀of฀

a฀particular฀method฀

the฀identified฀refactorings.฀Such฀automation฀is฀essential฀for฀databases;฀at฀least฀in฀the฀

of฀producing฀software,฀ emphasising฀ self-organizing฀teams฀ and฀broad฀ customer-programmer฀ contact

areas฀of฀schema฀changes฀and฀data฀migration.฀ As฀a฀result฀every฀database฀refactoring฀is฀automated฀by฀writing฀it฀in฀the฀form฀of฀SQL฀ DDL฀(for฀the฀schema฀change)฀and฀DML฀(for฀the฀data฀migration).฀These฀changes฀are฀ never฀applied฀manually,฀instead฀they฀are฀applied฀to฀the฀master฀by฀running฀a฀small฀ SQL฀script฀to฀perform฀the฀changes.฀ Once฀done,฀we฀keep฀hold฀of฀these฀script฀files฀to฀produce฀a฀complete฀change฀log฀of฀all฀ the฀alterations฀done฀to฀the฀database฀as฀a฀result฀of฀database฀refactorings.฀We฀can฀then฀ update฀any฀database฀instance฀to฀the฀latest฀master฀by฀running฀the฀change฀log฀of฀all฀the฀ changes฀since฀we฀copied฀the฀master฀to฀produce฀the฀older฀database฀instance.฀ This฀ability฀to฀sequence฀automated฀changes฀is฀an฀essential฀tool฀both฀for฀the฀continuous฀฀ integration฀process฀in฀development,฀and฀for฀migrating฀production฀databases฀to฀a฀new฀ release.฀ For฀production฀databases฀we฀don’t฀make฀changes฀during฀the฀usual฀iteration฀cycles.฀ Once฀we฀do฀a฀release,฀which฀may฀occur฀at฀the฀end฀of฀any฀iteration,฀we฀apply฀the฀full฀ change฀log฀of฀database฀refactorings฀since฀the฀previous฀release.฀This฀is฀a฀big฀change,฀ and฀one฀that฀so฀far฀we’ve฀only฀done฀by฀taking฀the฀application฀offline.฀(We฀have฀some฀ ideas฀for฀doing฀this฀in฀a฀24/7฀environment,฀but฀we฀haven’t฀actually฀had฀to฀do฀it฀yet.)฀ It’s฀also฀wise฀to฀test฀this฀migration฀schema฀before฀applying฀it฀to฀the฀live฀database.฀So฀ far,฀we’ve฀found฀that฀this฀technique฀has฀worked฀remarkably฀well.฀By฀breaking฀down฀ all฀the฀database฀changes฀into฀a฀sequence฀of฀small,฀simple฀changes;฀we’ve฀been฀able฀to฀ make฀quite฀large฀changes฀to฀production฀data฀without฀getting฀ourselves฀in฀trouble.฀ As฀ well฀ as฀ automating฀ the฀ forward฀ changes,฀ you฀ can฀ consider฀ automating฀ reverse฀ changes฀for฀each฀refactoring.฀If฀you฀do฀this฀you’ll฀be฀able฀to฀back฀out฀changes฀to฀a฀

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database฀in฀the฀same฀automated฀way.฀We฀haven’t฀done฀this฀yet,฀as฀we’ve฀not฀had฀a฀ much฀demand฀for฀it,฀but฀it’s฀the฀same฀basic฀principle.฀

English++ (A฀similar฀thing฀that฀we฀have฀done฀is฀to฀support฀an฀old฀version฀of฀an฀application฀with฀ an฀updated฀version฀of฀the฀database.฀This฀involved฀writing฀a฀compatibility฀layer฀that฀ allowed฀the฀application฀to฀think฀it฀was฀talking฀to฀the฀older฀version฀of฀the฀database฀ even฀though฀it฀was฀actually฀talking฀to฀the฀newer฀one.)฀

Automatically Update all Database Developers It’s฀all฀very฀well฀for฀people฀to฀make฀changes฀and฀update฀the฀master,฀but฀how฀do฀they฀

refactoring

find฀out฀the฀master฀has฀changed?฀In฀a฀traditional฀continuous฀integration฀environment฀฀

making฀changes฀

with฀source฀code,฀developers฀update฀to฀the฀master฀before฀doing฀a฀commit.฀That฀way฀

to฀a฀computer฀system฀

they฀ can฀ resolve฀ any฀ build฀ issues฀ on฀ their฀ own฀ machine฀ before฀ committing฀ their฀

(e.g.฀source฀code,฀database)฀

changes฀to฀the฀shared฀master.฀There’s฀no฀reason฀you฀can’t฀do฀that฀with฀the฀database,฀

that฀improve฀

but฀we฀found฀a฀better฀way.฀

its฀readability฀and฀฀

We฀automatically฀update฀everyone฀on฀the฀project฀whenever฀a฀change฀is฀made฀to฀the฀ database฀master.฀The฀same฀refactoring฀script฀that฀updates฀the฀master฀automatically฀฀ updates฀ everyone’s฀ databases.฀ When฀ we’ve฀ described฀ this,฀ people฀ are฀ usually฀฀ concerned฀that฀automatically฀updating฀developers’฀databases฀underneath฀them฀will฀ cause฀a฀problem,฀but฀we฀found฀it฀worked฀just฀fine.฀

simplify฀its฀structure฀with out฀adding฀ any฀new฀functionality.฀ For฀example,฀changing฀the฀ names฀of฀variables ฀to฀be฀more฀readable฀

This฀ only฀ worked฀ when฀ people฀ were฀ connected฀ to฀ the฀ network.฀ If฀ they฀ worked฀฀ offline,฀such฀as฀on฀an฀airplane,฀then฀they฀had฀to฀resync฀with฀the฀master฀manually฀ once฀they฀got฀back฀to฀the฀office.฀

Clearly separate all database access code To฀understand฀the฀consequences฀of฀database฀refactorings,฀it’s฀important฀to฀be฀able฀to฀ see฀how฀the฀database฀is฀used฀by฀the฀application.฀If฀SQL฀is฀scattered฀willy-nilly฀around฀ the฀code฀base,฀this฀is฀very฀hard฀to฀do.฀As฀a฀result฀it’s฀important฀to฀have฀a฀clear฀database฀฀ access฀layer฀to฀show฀where฀the฀database฀is฀being฀used฀and฀how.฀To฀do฀this฀we฀suggest฀ following฀one฀of฀the฀data฀source฀architectural฀patterns฀from฀P฀of฀EAA.฀ Having฀a฀clear฀database฀layer฀has฀a฀number฀of฀valuable฀side฀benefits.฀It฀minimizes฀the฀ areas฀of฀the฀system฀where฀developers฀need฀SQL฀knowledge฀to฀manipulate฀the฀database,฀฀ which฀ makes฀ life฀ easier฀ to฀ developers฀ who฀ often฀ are฀ not฀ particularly฀ skilled฀ with฀ SQL.฀For฀the฀DBA฀it฀provides฀a฀clear฀section฀of฀the฀code฀that฀he฀can฀look฀at฀to฀see฀how฀ the฀database฀is฀being฀used.฀This฀helps฀in฀preparing฀indexes,฀database฀optimization,฀฀ and฀also฀looking฀at฀the฀SQL฀to฀see฀how฀it฀could฀be฀reformulated฀to฀perform฀better.฀ This฀allows฀the฀DBA฀to฀get฀a฀better฀understanding฀of฀how฀the฀database฀is฀used.฀

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English++ Variations Like฀ any฀ set฀ of฀ practices,฀ these฀ should฀ be฀ varied฀ depending฀ on฀ your฀ specific฀฀ circumstances.฀These฀practices฀are฀still฀pretty฀new,฀so฀we฀haven’t฀come฀across฀that฀ many฀variations,฀but฀here฀are฀some฀we฀have.฀

Keeping multiple database lineages extreme฀programming฀(XP)

A฀simple฀project฀can฀survive฀with฀just฀a฀single฀database฀master฀in฀the฀repository.฀With฀

a฀programing฀methodology฀

more฀ complex฀ projects฀ there’s฀ a฀ need฀ to฀ support฀ multiple฀ varieties฀ of฀ the฀ project฀

which฀is฀very฀closely฀

database,฀which฀we฀refer฀to฀as฀database฀lineages.฀We฀may฀create฀a฀new฀lineage฀if฀we฀

connected฀with฀the฀

have฀to฀branch฀an฀application฀that’s฀put฀into฀production.฀In฀essence฀creating฀a฀new฀

Agile฀style.฀

database฀lineage฀is฀much฀the฀same฀as฀branching฀the฀source฀code฀on฀the฀application,฀ with฀the฀added฀twist฀that฀you฀also฀make฀a฀lineage฀when฀you฀need฀a฀different฀set฀of฀ sample฀data,฀such฀as฀if฀you฀need฀a฀lot฀of฀data฀for฀performance฀testing.฀ When฀a฀developer฀takes฀a฀copy฀of฀a฀master฀they฀need฀to฀register฀which฀lineage฀they฀ are฀modifying.฀As฀the฀DBA฀applies฀updates฀to฀a฀master฀for฀a฀particular฀lineage฀the฀ updates฀propagate฀to฀all฀the฀developers฀who฀are฀registered฀for฀that฀lineage.฀

You don’t need a DBA All฀of฀this฀sounds฀like฀it฀would฀be฀a฀lot฀of฀work,฀but฀in฀fact฀it฀doesn’t฀require฀a฀huge฀ amount฀of฀manpower.฀On฀the฀Atlas฀project฀we฀had฀thirty-odd฀developers฀and฀a฀team฀ size฀(including,฀QA,฀analysts฀and฀management)฀of฀close฀to฀a฀hundred.฀On฀any฀given฀฀ day฀ we฀ would฀ have฀ a฀ hundred฀ or฀ so฀ copies฀ of฀ various฀ lineages฀ out฀ on฀ people’s฀฀ workstations.฀Yet฀all฀this฀activity฀needed฀only฀one฀full฀time฀DBA฀(Pramod)฀with฀a฀couple฀฀ of฀developers฀doing฀some฀part-time฀assistance฀and฀cover.฀ On฀smaller฀projects฀even฀that฀isn’t฀needed.฀We’ve฀been฀using฀these฀techniques฀on฀a฀ number฀of฀smaller฀projects฀(about฀a฀dozen฀people)฀and฀we฀find฀these฀projects฀don’t฀ need฀a฀full฀time฀DBA.฀Instead฀we฀rely฀on฀a฀couple฀of฀developers฀with฀an฀interest฀in฀ DB฀issues฀who฀handle฀the฀DBA฀tasks฀part-time.฀ The฀reason฀for฀this฀is฀automation.฀If฀you฀are฀determined฀to฀automate฀every฀task,฀you฀ can฀handle฀a฀lot฀of฀work฀with฀much฀less฀people.฀

Tools to Help Doing฀ this฀ kind฀ of฀ thing฀ requires฀ a฀ lot฀ of฀ repetitive฀ tasks.฀ The฀ good฀ news฀ is฀ that฀฀ whenever฀ you฀ run฀ into฀ repetitive฀ tasks฀ in฀ software฀ development฀ you฀ are฀ ideally฀ placed฀to฀automate฀them.฀As฀a฀result฀we’ve฀developed฀a฀fair฀amount฀of฀often฀simple฀ tools฀to฀help฀us.฀

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English++ One฀of฀the฀most฀valuable฀pieces฀of฀automation฀is฀a฀simple฀set฀of฀scripts฀for฀common฀ database฀tasks.฀ •฀ Bring฀a฀user฀up฀to฀date฀with฀the฀current฀master.฀ •฀ Create฀a฀new฀user฀ •฀ Copy฀ a฀ database฀ schema,฀ for฀ example฀ Sue฀ finds฀ a฀ bug฀ with฀ her฀ database,฀ now฀ Mike฀can฀copy฀Sue’s฀database฀and฀try฀to฀debug฀the฀application฀ •฀ Move฀a฀database,฀for฀example฀from฀a฀workstation฀to฀a฀different฀workstation,฀this฀ is฀essentially฀Copy฀database฀and฀Delete฀database฀combined฀as฀one฀ •฀ Drop฀a฀user฀ •฀ Export฀ a฀ user฀ so฀ team฀ members฀ can฀ make฀ offline฀ backups฀ of฀ the฀ database฀ that฀ they฀are฀working฀with.฀ •฀ Import฀a฀user,฀so฀if฀the฀team฀members฀have฀a฀backup฀copy฀of฀the฀database,฀they฀ can฀import฀the฀backup฀and฀create฀a฀new฀schema.฀ •฀ Export฀a฀baseline฀-฀make฀a฀backup฀copy฀of฀the฀master฀database.฀This฀is฀a฀specialized฀฀ case฀of฀Export฀a฀User฀ •฀ Create฀a฀difference฀report฀of฀any฀number฀of฀schemas,฀so฀that฀Mike฀can฀find฀out฀ what฀is฀different฀structurally฀between฀his฀database฀and฀Sue’s.฀ •฀ Diff฀a฀schema฀against฀the฀master,฀so฀that฀developers฀can฀compare฀their฀local฀copy฀ against฀the฀master.฀ •฀ List฀all฀the฀users฀ Analysts฀and฀QA฀folks฀often฀need฀to฀look฀at฀the฀test฀data฀in฀the฀database฀and฀to฀be฀able฀ to฀easily฀change฀it.฀For฀that฀we฀created฀an฀Excel฀application฀with฀VBA฀scripts฀to฀pull฀ data฀down฀from฀the฀database฀into฀an฀excel฀file,฀allow฀people฀to฀edit฀the฀file,฀and฀send฀ the฀data฀back฀up฀to฀the฀database.฀Although฀other฀tools฀exist฀for฀viewing฀and฀editing฀฀ the฀contents฀of฀a฀database,฀excel฀works฀well฀because฀so฀many฀people฀are฀familiar฀with฀it.฀ Everybody฀on฀the฀project฀needs฀to฀be฀able฀to฀explore฀the฀database฀design฀easily,฀that฀ way฀they฀can฀find฀out฀what฀tables฀are฀available฀and฀how฀they฀are฀used.฀We฀built฀an฀ HTML฀based฀tool฀to฀do฀this฀that฀used฀servlets฀to฀query฀database฀metadata.฀So฀Mike฀ before฀ adding฀ the฀ column฀ to฀ a฀ table,฀ could฀ go฀ look฀ up฀ if฀ the฀ column฀ he฀ is฀ adding฀฀ already฀exists,฀by฀searching฀the฀metadata฀of฀the฀tables฀and฀columns.฀We฀did฀the฀data฀ modeling฀using฀ERwin฀and฀pulled฀data฀from฀ERwin฀into฀our฀own฀metadata฀tables.฀

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English++

Exercises Pre-reading questions 1.฀Have฀you฀heard฀about฀Agile฀Methodology?฀What฀are฀they฀used฀for? 2.฀What฀does฀DBA฀stand฀for? 3.฀What฀are฀DBA’s฀functions?

Comprehension questions Dealing with Change 1.฀What฀are฀the฀main฀advantages฀of฀Agile฀Methodology?฀ •฀ higher฀ flexibility฀ to฀ change฀ of฀ development฀ plans฀ -฀ changes฀ ฀ to฀ a฀ system฀ are฀฀ controlled฀at฀each฀stage฀of฀a฀project฀ •฀ higher฀quality฀through฀earlier฀feedback฀from฀customers฀ •฀ shortened฀development฀cycle฀time฀ •฀ higher฀stability฀of฀workloads฀ 2.฀What฀is฀the฀main฀difference฀between฀planned฀and฀evolutionary฀design?฀ •฀ in฀planned฀methodology:฀treat฀design฀as฀a฀independent฀phase฀of฀project฀development฀฀ before฀implementation฀and฀testing฀ •฀ evolutionary฀design:฀run฀the฀entire฀software฀life-cycle฀many฀times฀during฀the฀life฀ of฀a฀project฀ 3.฀Why฀does฀agile฀methodology฀appear,฀at฀first฀glance,฀unsuitable฀for฀database฀design?฀ •฀ “Most฀people฀consider฀that฀database฀design฀is฀something฀that฀absolutely฀needs฀ up-front฀planning.฀Changing฀the฀database฀schema฀late฀in฀the฀development฀tends฀ to฀cause฀widespread฀breakages฀in฀application฀software.฀Furthermore,฀changing฀a฀ schema฀after฀deployment฀result฀in฀painful฀data฀migration฀problems.”฀ 4.฀What฀limitations฀do฀the฀authors฀admit฀to฀in฀using฀an฀evolutionary฀approach฀to฀ database฀design?฀ •฀ ฀They฀developed฀an฀application฀database฀for฀a฀single฀application฀rather฀than฀an฀ integration฀database฀that฀tries฀to฀integrate฀multiple฀databases.฀ •฀ ฀They฀don’t฀฀have฀to฀keep฀the฀production฀databases฀up฀24/7฀

The Practices 1.฀Why฀is฀close฀contact฀between฀฀developers฀and฀DBAs฀essential?฀ •฀ “฀Every฀task฀that฀a฀developer฀works฀on฀potentially฀needs฀a฀DBA’s฀help.฀Both฀the฀ developers฀and฀the฀DBA฀need฀to฀consider฀whether฀a฀development฀task฀is฀going฀to฀ make฀a฀significant฀change฀to฀the฀database฀schema.฀If฀so฀the฀developer฀needs฀to฀ consult฀with฀the฀DBA฀to฀decide฀how฀to฀make฀the฀change.฀The฀developer฀knows฀ what฀new฀functionality฀is฀needed,฀and฀the฀DBA฀has฀a฀global฀view฀of฀the฀data฀in฀

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the฀application.฀To฀make฀this฀happen฀the฀DBA฀has฀to฀make฀himself฀approachable฀

English++ and฀available.฀Make฀it฀easy฀for฀a฀developer฀to฀just฀pop฀over฀for฀a฀few฀minutes฀and฀ ask฀some฀questions.฀Make฀sure฀the฀DBAs฀and฀developers฀sit฀close฀to฀each฀other฀so฀ they฀can฀easily฀get฀together.฀Ensure฀that฀application฀design฀sessions฀are฀known฀ about฀so฀the฀DBA฀can฀pop฀in฀easily.“฀ 2.฀What฀allows฀individual฀programmers฀to฀independently฀test฀their฀own฀solutions฀ on฀a฀database฀without฀negative฀consequences฀for฀the฀project?฀ •฀ “It’s฀ important฀ for฀ each฀ developer฀ to฀ have฀ their฀ own฀ sandbox฀ where฀ they฀ can฀ experiment,฀ and฀ not฀ have฀ their฀ changes฀ affect฀ anyone฀ else.฀ Many฀ DBA฀ experts฀ see฀multiple฀databases฀as฀anathema,฀too฀difficult฀to฀work฀in฀practice,฀but฀we’ve฀ found฀that฀you฀can฀easily฀manage฀a฀hundred฀or฀so฀database฀instances.฀The฀vital฀ thing฀is฀to฀have฀to฀tools฀to฀allow฀you฀to฀manipulate฀databases฀much฀as฀you฀would฀ manipulate฀files.”฀ 3.฀ What฀is฀the฀difference฀between฀a฀source฀code฀and฀database฀integration? •฀ “With฀source฀code,฀much฀of฀the฀pain฀of฀integration฀is฀handled฀by฀source฀code฀control฀฀ systems.฀ For฀ databases฀ there’s฀ a฀ bit฀ more฀ effort฀ involved.฀ Any฀ changes฀ to฀ the฀฀ database฀need฀to฀done฀properly,฀as฀automated฀database฀refactorings.฀In฀addition฀฀ the฀DBA฀needs฀to฀look฀at฀any฀database฀changes฀and฀ensure฀that฀it฀fits฀within฀the฀ overall฀scheme฀of฀the฀database฀schema.฀For฀this฀to฀work฀smoothly,฀big฀changes฀ shouldn’t฀come฀as฀surprises฀at฀integration฀time฀-฀hence฀the฀need฀for฀the฀DBA฀to฀ collaborate฀closely฀with฀the฀developers.”฀ 4.฀What฀is฀the฀purpose฀of฀having฀test฀data?฀ •฀ “฀ The฀ main฀ reason฀ is฀ to฀ enable฀ testing.฀ We฀ are฀ great฀ believers฀ in฀ using฀ a฀ large฀ body฀of฀automated฀tests฀to฀help฀stabilize฀the฀development฀of฀an฀application.฀Such฀ a฀body฀of฀tests฀is฀a฀common฀approach฀in฀agile฀methods.฀For฀these฀tests฀to฀work฀฀ efficiently,฀it฀makes฀sense฀to฀work฀on฀a฀database฀that฀is฀seeded฀with฀some฀sample฀ test฀data,฀which฀all฀tests฀can฀assume฀is฀in฀place฀before฀they฀run.”฀ •฀ It฀allows฀the฀testing฀of฀migrations฀as฀the฀schema฀of฀the฀database฀are฀altered.฀ 5.฀How฀are฀automated฀changes฀in฀databases฀accomplished?฀฀฀ “Every฀database฀refactoring฀is฀automated฀by฀writing฀it฀in฀the฀form฀of฀SQL฀DDL฀(for฀ the฀schema฀change)฀and฀DML฀(for฀the฀data฀migration).฀These฀changes฀are฀never฀ applied฀manually,฀instead฀they฀are฀applied฀to฀the฀master฀by฀running฀a฀small฀SQL฀ script฀to฀perform฀the฀changes.฀Once฀done,฀we฀keep฀hold฀of฀these฀script฀files฀to฀produce฀a฀complete฀change฀log฀of฀all฀the฀alterations฀done฀to฀the฀database฀as฀a฀result฀ of฀database฀refactorings.฀We฀can฀then฀update฀any฀database฀instance฀to฀the฀latest฀ master฀by฀running฀the฀change฀log฀of฀all฀the฀changes฀since฀we฀copied฀the฀master฀to฀ produce฀the฀older฀database฀instance.”฀ 6.฀What฀are฀the฀advantages฀of฀separating฀the฀database฀layer฀from฀the฀code฀base?฀ •฀ It฀minimizes฀the฀areas฀of฀the฀system฀where฀developers฀need฀SQL฀knowledge฀to฀ manipulate฀the฀database,฀which฀makes฀life฀easier฀to฀developers฀who฀often฀are฀not฀ particularly฀skilled฀with฀SQL.

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English++ •฀ It฀provides฀DBA฀with฀a฀clear฀section฀of฀the฀code฀that฀he฀can฀look฀at฀to฀see฀how฀the฀ database฀is฀being฀used.฀ •฀ It฀helps฀in฀preparing฀indexes,฀database฀optimization,฀and฀also฀looking฀at฀the฀SQL฀ to฀see฀how฀it฀could฀be฀reformulated฀to฀perform฀better.฀฀

Possible topics for discussion •฀ What฀other฀methodologies฀do฀you฀know?฀ •฀ What฀ are฀ the฀ possible฀ advantages฀ of฀ these฀ methodologies?฀ Do฀ they฀ have฀ any฀฀ drawbacks?฀ •฀ How฀do฀you฀usually฀design฀your฀programs?฀

Possible difﬁculties It฀is฀quite฀a฀long฀text฀but฀it฀can฀be฀read฀quite฀easily.฀

Reading suggestions •฀ Wikipedia฀has฀an฀interesting฀page฀about฀agile฀development.฀ •฀ Martin฀Fowler฀has฀a฀very฀nice฀web฀page฀with฀a฀lot฀of฀articles฀worth฀reading.฀Be฀ Make฀sure฀to฀visit฀it.฀ •฀ If฀you฀want฀to฀find฀out฀more฀about฀Agile฀take฀a฀look฀at฀Agile฀Alliance.฀

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English++

Lord Palmerston on Programming Joel Spolsky Number฀of฀words฀฀

2230฀

Computer฀science฀content฀฀

Medium฀

Business฀content฀฀

Low฀

English฀language฀complexity฀฀

High฀

Sub-areas covered •฀ self-developing฀ •฀ learning฀ •฀ programmers’฀culture฀ •฀ programming฀expertise฀

Learning objectives •฀ to฀understand฀what฀is฀important฀in฀a฀programmer’s฀work •฀ to฀฀recognize฀practical฀attitudes฀towards฀programming฀and฀work •฀ to฀be฀aware฀of฀the฀kind฀of฀problems฀programmers฀have฀to฀face

Keywords regexp฀-฀an฀abbreviation฀for฀regular฀expressions.฀In฀computing,฀regular฀expressions฀ provide฀a฀concise฀and฀flexible฀means฀for฀identifying฀strings฀of฀text฀of฀฀interest,฀ such฀as฀particular฀characters,฀words,฀or฀patterns฀of฀characters฀ Windows฀-฀an฀operating฀system฀ Api฀(Application฀programming฀interface)฀-฀a฀source฀code฀interface฀that฀an฀operating฀฀ system,฀library฀or฀service฀provides฀to฀support฀requests฀made฀by฀computer฀programs฀ ASP฀(Action฀Server฀Pages)฀-฀Microsoft’s฀first฀server-side฀script฀engine฀for฀dynamically฀ -generated฀web฀pages฀ GUI฀(Graphical฀User฀Interface)฀-฀a฀type฀of฀user฀interface฀which฀allows฀people฀to฀interact฀ ฀with฀a฀computer฀and฀computer-controlled฀devices฀ VBScript฀-฀an฀Active฀Scripting฀language฀developed฀by฀Microsoft฀

Summary This฀article฀is฀about฀different฀computer฀programming฀“worlds”฀and฀how฀much฀they฀differ฀฀ from฀one฀another.฀The฀author฀suggests฀that฀the฀difference฀between฀programming฀“worlds”฀ is฀ so฀ big฀ that฀ it฀ is฀ ฀ almost฀ impossible฀ for฀ one฀ person฀ to฀ understand฀ and฀ compare฀฀ them.฀฀He฀also฀stresses฀the฀need฀for฀a฀programmer฀to฀never฀stop฀learning฀so฀as฀to฀stay฀

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English++ proficient฀in฀his/her฀computer฀programming฀“world”.฀ Artykuł฀traktuje฀o฀konieczności฀ciągłego฀uczenia฀się฀dla฀zachowania฀statusu฀eksperta฀ w฀ programowaniu.฀ Rozległość฀ wiedzy,฀ którą฀ powinien฀ posiąść฀ programista฀ rośnie฀ coraz฀ szybciej฀ i฀ tam,฀ gdzie฀ kiedyś฀ wystarczyło฀ przeczytać฀ jedną฀ książkę฀ by฀ wiedzieć฀ wszystko,฀ teraz฀ nie฀ wystarczają฀ kilkuletnie฀ studia.฀ Autor฀ podkreśla฀ również฀ wagę฀ praktycznego฀doświadczenia฀przy฀pracach฀programistycznych.฀

Pre-reading questions 1.฀ What฀does฀the฀phrase฀“a฀good฀programmer”฀mean฀to฀you?฀ 2.฀ What฀abilities/skills฀should฀a฀good฀programmer฀have?฀ 3.฀ Api฀or฀library?฀Which฀is฀more฀important?฀ 4.฀ Give฀some฀examples฀of฀the฀main฀programming฀areas.฀ 5.฀ Which฀programming฀languages฀are฀important฀now?฀

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English++

Lord Palmerston on Programming

There฀ was฀ a฀ time฀ when฀ if฀ you฀ read฀ one฀ book฀ by฀ Peter฀ Norton,฀ you฀ literally฀ knew฀฀ everything฀there฀was฀to฀know฀about฀programming฀the฀IBM-PC.฀Over฀the฀last฀20฀years,฀ programmers฀around฀the฀world฀have฀been฀hard฀at฀work฀building฀abstraction฀upon฀ abstraction฀on฀top฀of฀the฀IBM-PC฀to฀make฀it฀easier฀to฀program฀and฀more฀powerful.฀ But฀the฀law฀of฀leaky฀abstractions฀means฀that฀even฀as฀they฀built฀the฀abstractions฀that฀

Windows

are฀supposed฀to฀make฀programming฀easier,฀the฀sheer฀amount฀of฀stuff฀you฀have฀to฀

an฀operating฀system

know฀to฀be฀a฀great฀programmer฀is฀expanding฀all฀the฀time.฀ Becoming฀ proficient,฀ really฀ proficient,฀ in฀ just฀ one฀ programming฀ world฀ takes฀ years.฀ Sure,฀lots฀of฀bright฀teenagers฀learn฀Delphi฀one฀week฀and฀Python฀the฀next฀week฀and฀

฀

Perl฀the฀next฀week฀and฀think฀they฀are฀proficient.฀Yet฀they฀don’t฀have฀the฀foggiest฀clue฀

Api

how฀much฀they’re฀missing.฀

application฀programming฀

I’ve฀been฀working฀with฀ASP฀and฀VBScript฀since฀it฀first฀came฀out.฀VBScript฀is฀the฀dinkiest฀฀ language฀on฀earth฀and฀ASP฀programming฀consists฀of฀learning฀about฀5฀classes,฀only฀ two฀of฀which฀you฀use฀very฀often.฀And฀only฀now฀do฀I฀finally฀feel฀like฀I฀know฀the฀best฀ way฀to฀architect฀an฀ASP/VBScript฀application.฀I฀finally฀think฀I฀know฀where฀the฀best฀ place฀to฀put฀database฀access฀code฀is,฀the฀best฀way฀to฀use฀ADO฀to฀get฀recordsets,฀the฀ best฀way฀to฀separate฀HTML฀and฀code,฀etc.฀And฀I฀finally฀use฀regexps฀instead฀of฀one-off฀ string฀manipulation฀functions.฀Only฀last฀week,฀I฀learned฀how฀to฀get฀COM฀objects฀out฀ of฀memory฀so฀you฀can฀recompile฀them฀(without฀restarting฀the฀whole฀web฀server).฀

interface฀ -฀a฀source฀code฀interface฀ that฀an฀operating฀ system,฀library฀or฀฀฀ ฀service฀provides฀ to฀support฀requests฀ made฀by฀computer฀ programs.฀฀

Fog฀Creek฀is฀too฀small฀to฀have฀specialists,฀so฀when฀I฀needed฀to฀write฀a฀really฀good฀ installer฀ for฀ FogBUGZ,฀ our฀ ASP/VBScript฀ based฀ product,฀ I฀ drew฀ on฀ several฀ years฀ of฀ C++/MFC฀experience,฀and฀years฀of฀experience฀with฀Windows฀APIs,฀and฀good฀Corel฀ Photopaint฀ skills฀ to฀ create฀ a฀ neat฀ picture฀ in฀ the฀ corner฀ of฀ the฀ wizard.฀ Then฀ to฀ get฀ FogBUGZ฀to฀work฀perfectly฀with฀Unicode,฀I฀had฀to฀write฀a฀little฀ActiveX฀control฀using฀ C++฀and฀ATL,฀which฀drew฀upon฀years฀of฀C++฀and฀COM฀experience฀and฀a฀week฀or฀ so฀learning฀about฀character฀encodings฀when฀I฀implemented฀that฀code฀in฀CityDesk.฀฀฀

129

English++ So฀when฀we฀had฀a฀weird฀NT฀4.0-only฀bug,฀it฀took฀me฀3฀minutes฀to฀debug,฀because฀I฀ knew฀how฀to฀use฀VMWare,฀and฀I฀had฀a฀clean฀NT฀4.0฀machine฀set฀up฀in฀VMWare,฀and฀ I฀knew฀how฀to฀do฀remote฀debugging฀with฀Visual฀C++,฀and฀I฀knew฀to฀look฀in฀the฀EAX฀ register฀to฀get฀the฀return฀value฀from฀a฀function.฀Someone฀who฀was฀new฀to฀this฀all฀ might฀have฀taken฀an฀hour฀or฀more฀to฀debug฀the฀same฀problem,฀but฀I฀already฀knew฀a฀ tremendous฀amount฀of฀“stuff”฀that฀I’ve฀been฀learning,฀basically,฀since฀1982฀when฀I฀ got฀my฀first฀IBM-PC฀and฀that฀Norton฀book.฀ Leaky฀abstractions฀mean฀that฀we฀live฀with฀a฀hockey฀stick฀learning฀curve:฀you฀can฀learn฀ 90%฀of฀what฀you฀use฀day฀by฀day฀with฀a฀week฀of฀learning.฀But฀the฀other฀10%฀might฀take฀ you฀a฀couple฀of฀years฀catching฀up.฀That’s฀where฀the฀really฀experienced฀programmers฀ will฀shine฀over฀the฀people฀who฀say฀“whatever฀you฀want฀me฀to฀do,฀I฀can฀just฀pick฀up฀ the฀book฀and฀learn฀how฀to฀do฀it.”฀If฀you’re฀building฀a฀team,฀it’s฀OK฀to฀have฀a฀lot฀of฀less฀ experienced฀programmers฀cranking฀out฀big฀blocks฀of฀code฀using฀the฀abstract฀tools,฀but฀ the฀team฀is฀not฀going฀to฀work฀if฀you฀don’t฀have฀some฀really฀experienced฀members฀to฀ do฀the฀really฀hard฀stuff.฀ There฀are฀a฀lot฀of฀programming฀worlds,฀each฀of฀which฀requires฀a฀tremendous฀amount฀ of฀knowledge฀for฀real฀proficiency.฀Here฀are฀the฀three฀I฀personally฀know฀best:฀ •฀ MFC/C++/Windows฀ Regexp an฀abbreviation฀

•฀ VBScript/ASP฀ •฀ Visual฀Basic฀

for฀regular฀expressions.฀

All,฀basically,฀what฀you฀would฀call฀Windows฀programming.฀Yes,฀I’ve฀written฀Unix฀code฀

In฀computing,฀

and฀Java฀code,฀but฀not฀very฀much.฀My฀proficiency฀in฀Windows฀programming฀comes฀from฀

regular฀expressions฀

knowing฀not฀just฀the฀basic฀technologies฀but฀also฀the฀whole฀supporting฀infrastructure.฀฀

provide฀a฀concise฀

So,฀I฀claim,฀I’m฀really฀good฀at฀Windows฀programming฀because฀I฀also฀know฀COM,฀ATL,฀

and฀flexible฀means฀

C++,฀ 80×86฀ Assembler,฀ Windows฀ APIs,฀ IDispatch฀ (OLE฀ Automation),฀ HTML,฀ the฀

for฀identifying฀strings฀

DOM,฀the฀Internet฀Explorer฀object฀model,฀Windows฀NT฀and฀Windows฀95฀internals,฀

of฀text฀of฀฀interest,฀

LAN฀Manager฀and฀NT฀networking,฀including฀security฀(ACEs,฀ACLs,฀and฀all฀that฀stuff),฀

such฀as฀particular฀

SQL฀and฀SQL฀Server,฀Jet฀and฀Access,฀JavaScript,฀XML,฀and฀a฀few฀other฀cheerful฀facts฀

characters,฀words,฀

about฀the฀square฀of฀the฀hypotenuse.฀When฀I฀can’t฀get฀the฀StrConv฀฀function฀in฀VB฀to฀

or฀patterns฀of฀characters

do฀what฀I฀want,฀I฀bang฀out฀an฀COM฀control฀so฀I฀can฀drop฀into฀C++฀with฀ATL฀and฀call฀ the฀MLang฀functions฀without฀dropping฀a฀beat.฀It฀took฀me฀years฀to฀get฀to฀this฀point.฀

฀

There฀are฀lots฀of฀other฀programming฀worlds.฀There’s฀the฀world฀of฀people฀developing฀ for฀BEA฀Weblogic฀who฀know฀J2EE,฀Oracle,฀and฀all฀kinds฀of฀Java฀things฀that฀I฀don’t฀ even฀know฀enough฀about฀to฀enumerate.฀There฀are฀hard฀core฀Macintosh฀developers฀ who฀know฀CodeWarrior,฀MPW,฀Toolbox฀programming฀in฀System฀6฀through฀X,฀Cocoa,฀ Carbon,฀and฀even฀nice฀obsolete฀things฀like฀OpenDoc฀฀that฀don’t฀help฀any฀more.฀

130

English++ Very฀few฀people,฀though,฀know฀more฀than฀one฀or฀two฀worlds,฀because฀there’s฀just฀so฀ much฀to฀learn฀that฀unless฀you฀have฀to฀work฀in฀one฀of฀these฀worlds฀for฀more฀than฀a฀ couple฀of฀years,฀you฀don’t฀really฀grok฀it฀all.฀

But learn you must People฀get฀kind฀of฀miffed฀when฀they฀go฀on฀job฀interviews฀and฀get฀rejected฀because,฀for฀฀

VBScript

example,฀they฀don’t฀have฀Win32฀(or฀J2EE,฀or฀Mac฀programming,฀or฀whatever)฀experience.฀฀

an฀Active฀Scripting฀

Or฀they฀get฀annoyed฀because฀idiot฀recruiters,฀who฀would฀not฀know฀an฀MSMQ฀if฀it฀bit฀

language฀developed฀by฀

them฀in฀the฀tailbone,฀call฀them฀up฀and฀ask฀if฀they฀“have฀5฀years฀MSMQ.”฀

Microsoft฀

Until฀you’ve฀done฀Windows฀programming฀for฀a฀while,฀you฀may฀think฀that฀Win32฀is฀ just฀a฀library,฀like฀any฀other฀library,฀you’ll฀read฀the฀book฀and฀learn฀it฀and฀call฀it฀when฀ you฀need฀to.฀You฀might฀think฀that฀basic฀programming,฀say,฀your฀expert฀C++฀skills,฀ are฀the฀90%฀and฀all฀the฀APIs฀are฀the฀10%฀fluff฀you฀can฀catch฀up฀on฀in฀a฀few฀weeks.฀To฀ these฀people฀I฀humbly฀suggest:฀times฀have฀changed.฀The฀ratio฀has฀reversed.฀ Very฀few฀people฀get฀to฀work฀on฀low฀level฀C฀algorithms฀that฀just฀move฀bytes฀around฀ any฀more.฀Most฀of฀us฀spend฀all฀our฀time฀these฀days฀calling฀APIs,฀not฀moving฀bytes.฀ Someone฀who฀is฀a฀fantastic฀C++฀coder฀with฀no฀API฀experience฀only฀knows฀about฀10%฀ of฀what฀you฀use฀every฀day฀writing฀code฀that฀runs฀on฀an฀API.฀When฀the฀economy฀is฀ doing฀well,฀this฀doesn’t฀matter.฀You฀still฀get฀jobs,฀and฀employers฀pay฀the฀cost฀of฀your฀ getting฀up฀to฀speed฀on฀the฀platform.฀But฀when฀the฀economy฀is฀a฀mess฀and฀600฀people฀ apply฀ for฀ every฀ job฀ opening,฀ employers฀ have฀ the฀ luxury฀ of฀ choosing฀ programmers฀฀ who฀are฀already฀experts฀at฀the฀platform฀in฀question.฀Like฀programmers฀who฀can฀name฀ four฀ways฀to฀FTP฀a฀file฀from฀Visual฀Basic฀code฀and฀the฀pros฀and฀cons฀of฀each.฀ The฀huge฀surface฀area฀of฀all฀these฀worlds฀of฀programming฀leads฀to฀pointless฀flame฀ wars฀over฀whose฀world฀is฀better.฀Here’s฀a฀smug฀comment฀somebody฀anonymously฀ made฀on฀my฀discussion฀board:฀ “Just฀one฀more฀reason฀why฀I’m฀glad฀to฀be฀living฀in฀the฀‘free฀world.’฀Free฀as฀in฀speech฀ (almost)฀and฀freedom฀from฀pandering฀to฀things฀like฀setup฀programs฀and฀the฀registry฀ -฀just฀to฀name฀a฀few.”฀ I฀think฀this฀person฀was฀trying฀to฀say฀that฀in฀the฀Linux฀world฀they฀don’t฀write฀setup฀ programs.฀Well,฀I฀hate฀to฀disappoint฀you,฀but฀you฀have฀something฀just฀as฀complicated:฀ imake,฀make,฀config฀files,฀and฀all฀that฀stuff,฀and฀when฀you’re฀done,฀you฀still฀distribute฀ applications฀with฀a฀20KB฀INSTALL฀file฀full฀of฀witty฀instructions฀like฀“You’re฀going฀to฀ need฀zlib”฀(what’s฀that?)฀or฀“This฀may฀take฀a฀while.฀Go฀get฀some฀runts.”฀(Runts฀are฀a฀ kind฀of฀candy,฀I฀think.)฀And฀the฀registry฀–฀instead฀of฀one฀big฀organized฀hive฀of฀name/ value฀ pairs,฀ you฀ have฀ a฀ thousand฀ different฀ file฀ formats,฀ one฀ per฀ application,฀ with฀ .whateverrc฀and฀foo.conf฀files฀living฀all฀over฀the฀place.฀And฀emacs฀wants฀you฀to฀learn฀

131

English++ how฀to฀program฀lisp฀if฀you’re฀going฀to฀change฀settings,฀and฀each฀shell฀wants฀you฀to฀ learn฀its฀personal฀dialect฀of฀shell฀script฀programming฀if฀you฀want฀to฀change฀settings,฀ and฀on฀and฀on.฀ GUI฀

People฀ who฀ only฀ know฀ one฀ world฀ get฀ really฀ smarmy,฀ and฀ every฀ time฀ they฀ hear฀

(Graphical฀User฀Interface)฀

about฀ the฀ complications฀ in฀ the฀ other฀ world,฀ it฀ makes฀ them฀ think฀ that฀ their฀ world฀

a฀type฀of฀user฀interface฀

doesn’t฀ have฀ complications.฀ But฀ they฀ do.฀ You’ve฀ just฀ moved฀ beyond฀ them฀ because฀

which฀allows฀people฀to฀

you฀are฀proficient฀in฀them.฀These฀worlds฀are฀just฀too฀big฀and฀complicated฀to฀com-

interact฀with฀a฀computer฀

pare฀any฀more.฀Lord฀Palmerston:฀“The฀Schleswig-Holstein฀question฀is฀so฀complicated,฀

and฀computer-controlled฀

only฀three฀men฀in฀Europe฀have฀ever฀understood฀it.฀One฀was฀Prince฀Albert,฀who฀is฀

devices

dead.฀The฀second฀was฀a฀German฀professor฀who฀became฀mad.฀I฀am฀the฀third฀and฀I฀ have฀forgotten฀all฀about฀it.”฀The฀software฀worlds฀are฀so฀huge฀and฀complicated฀and฀฀ multifaceted฀that฀when฀I฀see฀otherwise฀intelligent฀people฀writing฀blog฀entries฀saying฀฀ something฀ vacuous฀ like฀ “Microsoft฀ is฀ bad฀ at฀ operating฀ systems,”฀ frankly,฀ they฀ just฀ look฀ dumb.฀ Imagine฀ trying฀ to฀ summarize฀ millions฀ of฀ lines฀ of฀ code฀ with฀ hundreds฀ of฀major฀feature฀areas฀created฀by฀thousands฀of฀programmers฀over฀a฀decade฀or฀two,฀ where฀no฀one฀person฀can฀begin฀to฀understand฀even฀a฀large฀portion฀of฀it.฀I’m฀not฀even฀ defending฀Microsoft,฀I’m฀just฀saying฀that฀big฀handwavy฀generalizations฀made฀from฀a฀ position฀of฀deep฀ignorance฀is฀one฀of฀the฀biggest฀wastes฀of฀time฀on฀the฀net฀today.฀ Frequent฀readers,฀by฀now,฀have฀noticed฀that฀I’ve฀been฀thinking฀of฀the฀problem฀of฀how฀ one฀might฀deliver฀an฀application฀on฀Linux,฀Macintosh,฀and฀Windows฀without฀paying฀ disproportionately฀ for฀ the฀ Linux฀ and฀ Macintosh฀ versions.฀ For฀ this฀ you฀ need฀ some฀ kind฀of฀cross-platform฀library.฀ Java฀ attempted฀ this฀ but฀ Sun฀ didn’t฀ grok฀ GUIs฀ well฀ enough฀ to฀ deliver฀ really฀ slick฀฀ native-feeling฀applications.฀Like฀the฀space฀alien฀in฀Star฀Trek฀watching฀Earth฀through฀ a฀telescope,฀they฀knew฀exactly฀what฀human฀food฀was฀supposed฀to฀look฀like฀but฀they฀ didn’t฀realize฀it฀was฀supposed฀to฀taste฀like฀something.฀Java฀apps฀have฀menus฀in฀the฀ right฀places฀but฀there฀are฀all฀these฀keyboard฀things฀that฀don’t฀work฀the฀same฀way฀as฀ every฀other฀Windows฀app฀and฀their฀tabbed฀dialogs฀look฀a฀little฀scary.฀And฀there฀is฀no฀ way,฀no฀matter฀how฀hard฀you฀try,฀to฀make฀their฀menubars฀look฀exactly฀like฀Excel’s฀ menubars.฀Why?฀Because฀Java฀doesn’t฀give฀you฀a฀very฀good฀way฀to฀drop฀down฀to฀the฀ native฀facilities฀whenever฀the฀abstraction฀fails.฀When฀you’re฀programming฀in฀AWT,฀you฀ can’t฀ figure฀ out฀ the฀ HWND฀ of฀ a฀ window,฀ you฀ can’t฀ call฀ the฀ Microsoft฀ APIs,฀ and฀ you฀ certainly฀can’t฀intercept฀WM_PAINT฀and฀do฀it฀differently.฀And฀Sun฀made฀it฀plenty฀clear฀ that฀if฀you฀tried฀to฀do฀that,฀you฀weren’t฀Pure.฀You฀were฀Polluted,฀and฀to฀hell฀with฀you.฀ After฀a฀number฀of฀highly฀publicized฀failures฀to฀build฀GUIs฀with฀Java฀(e.g.฀Corel’s฀Java฀ Office฀suite฀and฀Netscape’s฀Javagator),฀enough฀people฀know฀to฀stay฀away฀from฀this฀ world.฀Eclipse฀built฀their฀own฀windowing฀library฀from฀the฀ground฀up฀using฀native฀

132

widgets฀just฀so฀they฀could฀write฀Java฀code฀that฀had฀a฀reasonably฀native฀look฀and฀feel.฀

English++ The฀Mozilla฀engineers฀decided฀to฀address฀the฀cross฀platform฀problem฀with฀their฀own฀ invention฀called฀XUL.฀So฀far,฀I’m฀impressed.฀Mozilla฀finally฀got฀to฀the฀point฀where฀it฀ tastes฀like฀real฀food.฀Even฀my฀favorite฀bugaboo,฀Alt+Space฀N฀to฀minimize฀a฀window,฀ works฀in฀Mozilla;฀it฀took฀them฀long฀enough฀but฀they฀did฀it.฀ Mitch฀Kapor,฀who฀founded฀Lotus฀and฀created฀123,฀decided฀for฀his฀next฀application฀to฀ go฀with฀something฀called฀wxWindows฀and฀wxPython฀for฀cross฀platform฀support.฀ Which฀is฀better,฀XUL,฀Eclipse’s฀SWT,฀or฀wxWindows?฀I฀don’t฀know.฀They฀are฀all฀such฀

ASP฀(Action฀server฀pages)฀

huge฀worlds฀that฀I฀couldn’t฀really฀evaluate฀them฀and฀tell.฀It’s฀not฀enough฀to฀read฀the฀

Microsoft’s฀first฀

tutorials.฀You฀have฀to฀sweat฀and฀bleed฀with฀the฀thing฀for฀a฀year฀or฀two฀before฀you฀

server-side฀script฀engine฀

really฀know฀it’s฀good฀enough฀or฀realize฀that฀no฀matter฀how฀hard฀you฀try฀you฀can’t฀

for฀dynamically-generated฀

make฀your฀UI฀taste฀like฀real฀food.฀Unfortunately,฀for฀most฀projects,฀you฀have฀to฀decide฀

web฀pages฀

on฀which฀world฀to฀use฀before฀you฀can฀write฀the฀first฀line฀of฀code,฀which฀is฀precisely฀ the฀moment฀when฀you฀have฀the฀least฀information.฀At฀a฀previous฀job฀we฀had฀to฀live฀ with฀some฀pretty฀bad฀architecture฀because฀the฀first฀programmers฀used฀the฀project฀to฀ teach฀themselves฀C++฀and฀Windows฀programming฀at฀the฀same฀time.฀Some฀of฀the฀ oldest฀code฀was฀written฀without฀any฀comprehension฀of฀event-driven฀programming.฀ The฀core฀string฀class฀(of฀course,฀we฀had฀our฀own฀string฀class)฀was฀a฀textbook฀example฀ of฀all฀the฀mistakes฀you฀could฀make฀in฀designing฀a฀C++฀class.฀Eventually฀we฀cleaned฀ up฀and฀refactored฀a฀lot฀of฀that฀old฀code฀but฀it฀haunted฀us฀for฀a฀while.฀ So฀for฀now,฀my฀advice฀is฀this:฀don’t฀start฀a฀new฀project฀without฀at฀least฀one฀architect฀ with฀several฀years฀of฀solid฀experience฀in฀the฀language,฀classes,฀APIs,฀and฀platforms฀ you’re฀building฀on.฀If฀you฀have฀a฀choice฀of฀platforms,฀use฀the฀one฀your฀team฀has฀the฀ most฀skills฀with,฀even฀if฀it’s฀not฀the฀trendiest฀or฀nominally฀the฀most฀productive.฀And฀ when฀you’re฀designing฀abstractions฀or฀programming฀tools,฀go฀the฀extra฀mile฀to฀make฀ them฀leak฀proof.฀฀

133

English++

Exercises Pre-reading questions 1.฀ What฀does฀the฀phrase฀“a฀good฀programmer”฀mean฀to฀you?฀ 2.฀ What฀abilities/skills฀should฀a฀good฀programmer฀have?฀ 3.฀ Api฀or฀library?฀Which฀is฀more฀important?฀ 4.฀ Give฀some฀examples฀of฀the฀main฀programming฀areas.฀ 5.฀ Which฀programming฀languages฀are฀important฀now?฀

Comprehension questions 1.฀ What฀is฀a฀“programming฀world”?฀ ฀A฀programming฀area฀like฀windows฀api,฀networking,฀multimedia,฀games,฀etc.฀฀ 2.฀ Which฀IT฀areas฀is฀the฀author฀proficient฀in?฀ Windows฀and฀web฀programming฀ 3.฀ According฀to฀the฀article,฀what฀is฀the฀90/10฀rule?฀ •฀ You฀can฀learn฀90%฀of฀what฀you฀use฀day฀by฀day฀with฀a฀week฀of฀learning.฀But฀the฀other฀ 10%฀might฀take฀you฀a฀couple฀of฀years฀of฀catching฀up.฀Or฀the฀second฀version:฀90%฀of฀ programming฀skills฀is฀the฀knowledge฀of฀different฀Api’s;฀10%฀฀is฀the฀languages฀ 4.฀ Why฀was฀the฀Java฀GUI฀system฀not฀very฀popular?฀ •฀ Because฀the฀Sun฀company฀didn’t฀put฀the฀proper฀“taste”฀in฀it,฀it฀฀isn’t฀as฀native฀as฀ Windows฀controls฀Because฀ultimately฀it฀was฀not฀compatible฀with฀native฀Windows฀ facilities.฀The฀explanation฀is฀in฀the฀paragraph฀beginning:฀‘Java฀attempted฀this฀…‘.฀ 5.฀ What฀should฀every฀฀good฀programming฀team฀include?฀ •฀ There฀should฀be฀at฀least฀one฀very฀experienced฀programmer.฀

Further exercises: Match฀the฀languages฀to฀the฀technologies.฀ •฀ C++฀with฀Windows,฀JavaScript฀with฀Web,฀etc฀

Possible topics for discussion 1.฀ How฀do฀you฀see฀the฀future฀of฀programming?฀ 2.฀ What฀kind฀of฀programming฀experience฀is฀most฀important฀in฀the฀job฀market?฀฀

Reading suggestions Joel’s฀blog฀is฀a฀well-known฀source฀of฀articles฀about฀programming฀and฀programming฀ culture.฀It฀is฀certainly฀worth฀reading,฀as฀are฀his฀books.

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English++

Quake – Game Engine Wikipedia

Number฀of฀words฀฀

700

Computer฀science฀content฀฀

Medium

Math฀content฀฀

Low

English฀language฀complexity฀฀

Medium

Learning objectives •฀ to฀understand฀pre-rendering฀process฀ •฀ to฀acquire฀technical฀vocabulary฀associated฀with฀computer฀graphics •฀ to฀recognize฀differences฀between฀true฀3D฀games฀and฀the฀earliest฀2D฀or฀pseudo-3D฀ games฀ •฀ to฀learn฀why฀Quake฀became฀a฀milestone฀in฀game฀history

Sub-areas covered •฀ Computer฀graphics฀ •฀ Computer฀games฀ •฀ Computer฀animation฀ •฀ Game฀engine฀

Keywords •฀ rendering฀-฀the฀process฀of฀generating฀an฀image฀from฀a฀three฀dimensional฀object฀by฀ means฀of฀computer฀programs •฀ to฀prune฀-฀to฀cut฀parts฀of฀the฀map฀invisible฀for฀the฀player฀ •฀ skybox฀-฀a฀method฀to฀create฀a฀background฀to฀make฀a฀computer฀and฀video฀game฀ location฀look฀bigger฀than฀it฀really฀is •฀ sector-based฀static฀lighting฀–฀the฀texture฀with฀information฀about฀lighting฀which฀ is฀not฀affected฀by฀the฀angle฀or฀position฀of฀the฀light฀source฀ •฀ CAD฀-฀Computer฀Aided฀Design฀

Summary The฀text฀describes฀new฀solutions฀to฀graphical฀problems฀in฀computer฀games฀delivered฀ in฀“Quake”.฀It฀introduces฀the฀idea฀of฀displaying฀only฀those฀elements฀which฀are฀visible฀ to฀the฀player฀and฀calculating฀the฀light฀depending฀on฀its฀angle.฀The฀article฀explains฀the฀ “mouselook฀option”,฀which฀appears฀in฀the฀game.

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English++ Tekst฀opisuje฀nowe฀rozwiązania฀problemów฀związanych฀z฀grafiką฀w฀grach฀komputerowych,฀ wprowadzone฀ w฀ kultowej฀ grze฀ “Quake”.฀ Przybliża฀ ideę฀ wyświetlania฀ tylko฀ tych฀ elementów,฀ które฀ są฀ bezpośrednio฀ widoczne฀ dla฀ gracza,฀ wprowadza฀ w฀ zagadnienie฀obliczania฀światła฀w฀zależności฀od฀jego฀kąta฀padania.฀W฀tekście฀zaznaczono,฀że฀ “Quake”฀był฀jedną฀z฀pierwszych฀gier฀wykorzystujących฀sprzęt฀do฀wspierania฀grafiki฀ trójwymiarowej,฀a฀także฀przedstawiono฀jej฀wpływ฀na฀proces฀projektowania฀gier฀komputerowych.฀ Artykuł฀ wyjaśnia฀ także,฀ na฀ czym฀ polega฀ pojawiająca฀ się฀ w฀ grze฀ opcja฀ “mouselook”.฀

Pre-reading questions What฀you฀know฀about฀the฀following: 1.฀ the฀difference฀between฀true฀3D฀and฀“2.5D”฀games฀ 2.฀ optimizing฀the฀rendering฀process 3.฀ preprocessing฀the฀rendered฀world 4.฀ hardware฀acceleration฀ 5.฀ various฀problems฀in฀games฀modelling฀and฀scientific฀design฀฀

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English++

Quake – game engine

Quake฀popularized฀several฀major฀advances฀in฀the฀3D฀game฀genre:฀it฀uses฀3-dimensional฀฀ models฀ for฀ players฀ and฀ monsters฀ instead฀ of฀ 2-dimensional฀ sprites;฀ and฀ the฀ world฀ in฀ which฀ play฀ takes฀ place฀ is฀ created฀ as฀ a฀ true฀ 3-dimensional฀ space,฀ rather฀ than฀ a฀ 2-dimensional฀map.฀Some฀previous฀3D฀games,฀such฀as฀Duke฀Nukem฀3D,฀Doom฀and฀ Wolfenstein฀3D฀used฀some฀mathematical฀tricks฀to฀simulate฀the฀3-dimensional฀world.฀ This฀allowed฀a฀true฀3D฀view,฀but฀was฀so฀restricted฀that฀only฀looking฀straight฀ahead฀ would฀give฀a฀sense฀of฀3฀dimensions.฀

rendering the฀process฀of฀generating฀ an฀image฀from฀a฀three฀ dimensional฀object฀ by฀means฀of฀computer฀ programs

Reducing 3D complexity to increase speed Quake฀was฀the฀first฀true฀3D฀game฀to฀use฀a฀special฀map฀design฀system฀that฀preprocessed฀ and฀pre-rendered฀the฀3D฀environment฀to฀reduce฀the฀load฀when฀playing฀the฀game฀on฀ the฀50-75฀MHz฀CPUs฀of฀the฀time.฀The฀3D฀environment฀in฀which฀the฀game฀takes฀place฀

to฀prune

is฀referred฀to฀as฀a฀map,฀even฀though฀it฀is฀three-dimensional฀in฀nature฀rather฀than฀a฀

to฀cut฀parts฀of฀the฀map฀

flat฀2D฀space.฀The฀map฀editor฀program฀uses฀a฀number฀of฀simple฀convex฀3D฀geometric฀

invisible฀for฀the฀player฀

objects฀known฀as฀brushes฀that฀are฀sized฀and฀rotated฀to฀build฀the฀environment.฀The฀ brushes฀are฀overlapped฀in฀order฀to฀create฀an฀enclosed,฀empty,฀volumetric฀space,฀and฀ when฀ the฀ design฀ is฀ complete฀ the฀ map฀ is฀ run฀ through฀ the฀ rendering฀ preprocessor.฀ The฀preprocessor฀is฀used฀to฀locate฀two฀types฀of฀empty฀space฀in฀the฀map,฀the฀empty฀ space฀enclosed฀by฀brushes฀where฀the฀game฀will฀be฀played,฀and฀the฀other฀empty฀space฀฀ outside฀the฀brushes฀that฀the฀player฀will฀never฀see.฀The฀preprocessor฀then฀strips฀away฀ the฀back-faces฀of฀the฀individual฀brushes฀which฀are฀outside฀the฀game-space,฀leaving฀ only฀the฀few฀polygons฀that฀define฀the฀outer฀perimeter฀of฀the฀enclosed฀game฀space.

EXIT

INSIDE

START

EXIT

START

OUTSIDE

1.฀฀Use฀brushes฀to฀ make฀an฀฀ enclosed฀play฀ area

2.฀฀Preprocessor฀ finds฀the฀inside฀ and฀outside ฀฀ spaces

3.฀฀Preprocessor฀ cuts฀away฀faces฀ not฀visible฀inside฀maps

4.฀฀Finished฀ ฀ low-polygon,฀ fast-rendering฀ game฀map

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English++ skybox

It฀was฀possible฀to฀edit฀a฀processed฀map฀by฀opening฀it฀in฀a฀special฀vertex฀editor฀and฀

a฀method฀to฀create฀

editing฀ the฀ raw฀ vertex฀ data,฀ or฀ to฀ add฀ or฀ remove฀ individual฀ triangle฀ faces.฀ Though฀฀

a฀background฀to฀make฀

difficult,฀this฀technique฀was฀occasionally฀used฀by฀cheaters฀to฀create฀windows฀in฀walls,฀

a฀computer฀and฀video฀

to฀see฀normally฀hidden฀enemies฀approaching฀from฀behind฀doors฀and฀walls,฀and฀resulted฀฀

game฀location฀look฀bigger฀

in฀an฀anti-cheat฀mechanism฀used฀in฀recent฀3D฀games฀that฀calculates฀a฀checksum฀for฀

than฀it฀really฀is

each฀file฀used฀in฀the฀game,฀to฀detect฀players฀using฀potentially฀hacked฀map฀files. Once฀the฀map฀had฀been฀pruned฀of฀excess฀faces฀that฀the฀player฀inside฀will฀never฀see฀ anyway,฀the฀polygon฀count฀can฀be฀reduced฀by฀50%฀to฀80%฀compared฀to฀an฀original฀฀ unprocessed฀map.฀On฀the฀50-75฀MHz฀PCs฀of฀the฀time,฀it฀was฀common฀for฀this฀pruning฀ step฀to฀take฀many฀hours฀to฀complete฀on฀a฀map,฀often฀running฀overnight฀if฀the฀map฀

sector-based฀static฀lighting

design฀was฀extremely฀complex.฀

the฀texture฀with฀ information฀about฀lighting฀

Hardware 3D acceleration

which฀is฀not฀affected฀by฀

Quake฀was฀also฀one฀of฀the฀first฀games฀to฀support฀3D฀hardware฀acceleration.฀While฀

the฀angle฀or฀position฀

initially฀ released฀ with฀ only฀ software฀ rendering,฀ John฀ Carmack฀ created฀ a฀ version฀

of฀the฀light฀source฀

of฀ the฀ Quake฀ executable฀ that฀ took฀ advantage฀ of฀ Rendition’s฀ Vérité฀ 1000฀ graphics฀ chip.฀OpenGL฀support฀was฀soon฀added฀in฀the฀form฀of฀the฀GLQuake฀executable฀for฀฀ Windows฀ 95฀ and฀ higher.฀ Many฀ believe฀ that฀ this฀ kick-started฀ the฀ independent฀ 3D฀

CAD

graphics฀card฀revolution,฀“GLQuake”฀being฀the฀first฀application฀to฀truly฀demonstrate฀

Computer฀Aided฀Design

the฀capabilities฀of฀the฀3dfx฀“Voodoo”฀chipset฀at฀the฀time.฀The฀only฀two฀other฀cards฀ capable฀ of฀ rendering฀ GLQuake฀ were฀ a฀ professional฀ (very฀ expensive)฀ Integraph฀ 3D฀ OpenGL฀card,฀and,฀later,฀the฀PowerVR฀cards.฀

Impact on modern game design Nearly฀all฀the฀games฀created฀after฀Quake฀have฀used฀this฀3D฀preprocessing฀optimization,฀ which฀enhanced฀the฀speed฀of฀the฀game฀on฀a฀personal฀computer฀or฀gaming฀console.฀ 3D฀games฀are฀therefore฀able฀to฀push฀the฀limits฀of฀visual฀styles฀and฀effects฀because฀so฀ much฀excess฀modelling฀data฀was฀stripped฀out฀before฀the฀end-user฀ever฀saw฀the฀game.฀ In฀ this฀ way,฀ most฀ games฀ are฀ significantly฀ different฀ from฀ professional฀ 3D฀ CAD฀ and฀ design฀problems,฀where฀there฀is฀no฀time฀available฀to฀do฀preprocessing฀between฀an฀ engineer฀making฀a฀change฀and฀seeing฀it฀on฀the฀screen.฀Nothing฀can฀be฀thrown฀away฀ to฀increase฀the฀rendering฀speed฀of฀a฀3D฀engineering฀model,฀since฀any฀part฀of฀the฀design฀can฀change฀at฀any฀moment.฀For฀this฀reason,฀professional฀3D฀graphics฀cards฀are฀฀ significantly฀ more฀ expensive฀ and฀ powerful฀ than฀ the฀ 3D฀ cards฀ used฀ in฀ home฀฀ computers฀ simply฀ for฀ playing฀ games,฀ because฀ the฀ professional฀ 3D฀ card฀ needs฀ far฀ greater฀processing฀power฀to฀deal฀with฀the฀full฀complexity฀of฀an฀un-preprocessed฀3D฀ render฀space.฀

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Exercises Pre-reading questions What฀you฀know฀about฀the฀following: 1.฀ ฀The฀difference฀between฀true฀3D฀and฀“2.5D”฀games.฀ •฀ using฀2-dimensional฀sprites฀instead฀of฀3D฀models •฀ using฀some฀mathematical฀tricks฀to฀simulate฀the฀3-D฀world 2.฀ Optimizing฀the฀rendering฀process. •฀ avoid฀rendering฀unnecessary฀polygons฀ •฀ avoid฀rendering฀invariable฀polygons •฀ take฀care฀on฀number฀of฀details 3.฀ Preprocessing฀the฀rendered฀world •฀ reducing฀number฀of฀polygons,฀which฀should฀be฀displayed •฀ increase฀quality฀of฀frame฀using฀some฀mathematical฀tricks,฀just฀before฀the฀frame฀is฀ showed฀to฀user 4.฀ Hardware฀acceleration฀ •฀ using฀special฀graphic฀chips฀to฀increase฀speed฀of฀rendering฀scenes •฀ Quake฀was฀first฀game฀to฀support฀hardware฀acceleration 5.฀ Various฀problems฀in฀games฀modelling฀and฀scientific฀design฀฀ •฀ time฀available฀to฀render฀prepared฀scenes •฀ the฀oldest฀problem฀–฀graphics฀quality/application฀speed •฀ optimization

Comprehension questions 1.฀ ฀What฀did฀“shooter”฀games฀look฀like฀before฀the฀Quake฀revolution?฀฀ •฀ There฀ were฀ 2-dimensional฀ sprites฀ instead฀ of฀ full฀ 3D฀ models฀ and฀ 2D฀ maps.฀ In฀ Quake,฀ a฀ player฀ can฀ move฀ to฀ each฀ direction;฀ earlier฀ games฀ used฀ mathematical฀ tricks฀to฀simulate฀a฀3D฀world.฀฀ 2.฀ What฀is฀graphic฀preprocessing฀in฀general?฀ •฀ Preparing฀a฀picture฀before฀it฀is฀shown.฀The฀main฀aim฀of฀this฀process฀is฀to฀improve฀ the฀efficiency฀and฀quality฀of฀the฀rendered฀picture. 3.฀ How฀could฀players฀see฀their฀opponents฀through฀a฀wall?฀ •฀ It฀was฀possible฀to฀edit฀a฀processed฀map฀by฀opening฀it฀in฀a฀special฀vertex฀editor฀and฀ editing฀the฀raw฀vertex฀data,฀or฀to฀add฀or฀remove฀individual฀triangle฀faces.฀ 4.฀ What฀does฀the฀Quake฀pre-rendering฀process฀depend฀on?฀ •฀ The฀map฀editor฀program฀uses฀a฀number฀of฀simple฀convex฀3D฀geometric฀objects฀ known฀as฀brushes฀that฀are฀sized฀and฀rotated฀to฀build฀the฀environment.฀The฀brushes฀฀ are฀overlapped฀in฀order฀to฀create฀an฀enclosed,฀empty,฀volumetric฀space,฀and฀when฀ the฀design฀is฀complete฀the฀map฀is฀run฀through฀the฀rendering฀preprocessor.฀The฀pre-

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English++ processor฀is฀used฀to฀locate฀two฀types฀of฀empty฀space฀in฀the฀map,฀the฀empty฀space฀ enclosed฀by฀brushes฀where฀the฀game฀will฀be฀played,฀and฀the฀other฀empty฀space฀ outside฀the฀brushes฀that฀the฀player฀will฀never฀see.฀The฀preprocessor฀then฀strips฀ away฀the฀back-faces฀of฀the฀individual฀brushes฀which฀are฀outside฀the฀game-space,฀฀ leaving฀ only฀ the฀ few฀ polygons฀ that฀ define฀ the฀ outer฀ perimeter฀ of฀ the฀ enclosed฀ game฀space.

Possible topics for discussion 1.฀ Which฀games,฀in฀your฀opinion,฀were฀a฀milestone฀in฀game฀development฀and฀why?฀ ฀

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English++

Mechanical Models of Artery Walls Chapter 3: History of Artery Wall Modelling Piotr Kalita and Robert Schaefer

Number฀of฀words฀

860฀(selected฀part)

Computer฀science฀content฀

Low

Math฀content฀

Low

English฀language฀complexity฀

High

Learning objectives •฀ to฀understand฀the฀basic฀structure฀of฀฀the฀cardiovascular฀system •฀ to฀learn฀the฀terminology฀associated฀with฀the฀cardiovascular฀system •฀ to฀learn฀about฀mechanical฀models฀of฀artery฀walls •฀ to฀learn฀about฀possible฀application฀of฀computer฀science฀in฀medicine

Main sub-areas covered •฀ cardiovascular฀models

Keywords •฀ artery฀-฀one฀of฀the฀tubes฀that฀carries฀blood฀from฀the฀heart฀to฀the฀rest฀of฀the฀body •฀ Windkessel฀-฀(air฀kettle),฀one฀of฀the฀models฀presented฀in฀the฀article •฀ ODE฀-฀Ordinary฀Differential฀Equations •฀ PDE฀-฀Partial฀Differential฀Equations฀ •฀ heterogenous฀-฀consisting฀of฀various฀parts฀that฀are฀very฀different฀from฀each฀other

Summary This฀is฀the฀third฀chapter฀of฀an฀article฀on฀mechanical฀models฀of฀artery฀walls,฀presenting฀฀ a฀ short฀ review฀ of฀ artery฀ wall฀ modeling฀ history.฀ It฀ starts฀ with฀ the฀ derivation฀ of฀ the฀ word฀artery.฀Next,฀the฀authors฀present฀models฀of฀blood฀circulation,฀describing฀their฀ characteristics฀and฀their฀advantages฀and฀disadvantages. Jest฀to฀trzeci฀rozdział฀pracy฀poświęconej฀mechanicznemu฀modelowaniu฀ścianek฀tętnic,฀฀ w฀którym฀autorzy฀skoncentrowali฀się฀na฀krótkim฀przedstawieniu฀historii฀tego฀zagadnienia.฀ Ta฀część฀rozpoczyna฀się฀od฀wyprowadzenia฀znaczenia฀słowa฀artery฀(tętnica),฀a฀następnie฀ zaprezentowane฀zostają฀kolejne฀modele฀układu฀krwionośnego฀wraz฀z฀ich฀opisami.

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English++

Pre-reading exercises 1.฀ Draw฀a฀simple฀model฀of฀the฀cardiovascular฀system฀and฀name฀its฀main฀parts฀(arteries,฀฀ veins,฀heart฀etc.) 2.฀ Think฀about฀a฀model฀of฀the฀system฀as฀tree฀with฀the฀heart฀as฀its฀root

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English++

History of Artery Wall Modelling

The฀word฀artery฀comes฀from฀Greek,฀it฀means฀air฀pipe฀(aer฀is฀air฀and฀terein฀means฀to฀ keep฀in฀Greek)฀as฀in฀ancient฀Greece฀it฀was฀believed฀that฀arteries฀carry฀air.฀This฀was฀ corrected฀by฀Galen฀in฀the฀2nd฀century฀AD฀but฀he฀still฀did฀not฀recognize฀that฀blood฀ circulates฀and฀฀฀he฀also฀did฀not฀connect฀the฀pulse฀in฀arteries฀with฀the฀beating฀of฀the฀ heart.฀The฀circulation฀of฀blood฀and฀the฀role฀of฀the฀heart฀as฀a฀pump฀was฀discovered฀in฀ the฀18th฀century฀by฀William฀Harvey.฀However,฀the฀first฀to฀consider฀the฀elasticity฀of฀ artery฀walls฀and฀its฀significance฀in฀the฀pulsatile฀character฀of฀blood฀flow฀was฀Stephen฀ Hales฀ (1733),฀ who฀ originated฀ the฀ Windkessel฀ (air฀ kettle)฀ theory฀ later฀ developed฀ by฀ Otto฀Frank฀near฀the฀end฀of,฀the฀19th฀century฀(Otto฀Frank฀is฀actually฀the฀originator฀of฀ the฀name฀Windkessel).฀In฀this฀theory,฀the฀฀artery฀walls฀serve฀as฀฀a฀reservoir฀of฀energy,฀

artery฀ one฀of฀the฀tubes฀ that฀carries฀blood฀ from฀the฀heart฀ to฀the฀rest฀of฀the฀body

which฀is฀stored฀in฀their฀deformation฀during฀the฀systole฀by฀the฀stretching฀of฀the฀walls฀ and฀then,฀during฀the฀diastole,฀is฀restored฀to฀the฀blood,฀which฀is฀thereby฀pumped฀to฀ the฀capillaries฀in฀a฀constant฀and฀non-฀pulsatory฀way฀(as฀it฀is฀from฀the฀heart฀to฀the฀ arteries).฀Pure฀Windkessel฀theory฀leads฀to฀ODEs฀that฀do฀not฀take฀spatial฀relations฀into฀ account.฀In฀particular,฀they฀do฀not฀reflect฀the฀fact฀that฀due฀to฀its฀wavelike฀character,฀ the฀pulse฀propagates฀along฀the฀arterial฀tree฀and฀is฀able฀to฀reflect.฀Further฀development฀ of฀artery฀wall฀models฀followed฀the฀development฀of฀mechanics฀and฀throughout฀the฀ 19th฀century฀important฀contributions฀to฀the฀field฀were฀added฀by฀Young,฀Poiseuille,฀ Hagenbach,฀Moens฀and฀Korteweg.

Windkessel฀(air฀kettle) one฀of฀the฀models฀ presented฀in฀the฀article

PDE฀models฀which฀take฀into฀account฀the฀dependence฀of฀variables฀on฀both฀space฀and฀ time฀have฀been฀in฀existence฀since฀the฀19th฀century;฀however,฀their฀use฀has฀been฀boosted฀ by฀the฀use฀of฀computers฀and฀the฀increase฀in฀their฀computational฀capabilities฀as฀well฀as฀ the฀development฀of฀medical฀measurement฀techniques฀from฀the฀1940s฀to฀the฀present฀ day..฀ (Timmons฀ [131]฀ claims฀ that฀ “we฀ can฀ expect฀ highly฀ detailed฀ models฀ emerging฀฀ within฀ the฀ next฀ few฀ years฀ as฀ parallel฀ computers฀ become฀ economical”).฀ Two฀฀ developments฀important฀for฀artery฀wall฀modeling฀took฀place฀in฀the฀50s฀and฀60s:฀modern฀฀ nonlinear฀ mechanics,฀ the฀ theoretical฀ framework฀ most฀ commonly฀ used฀ for฀ artery฀ models฀ today;฀ and฀ the฀ Finite฀ Element฀ Method฀ (FEM),฀ which฀ is฀ used฀ to฀ formulate฀฀ relatively฀ simple฀ algorithms฀ for฀ numerical฀ solutions฀ of฀ the฀ underlying฀ problems.฀ From฀the฀60s฀to฀the฀80s฀various฀models฀based฀on฀nonlinear฀mechanics฀were฀used฀to฀

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English++ reflect฀artery฀wall฀behavior.฀The฀leading฀researcher฀in฀this฀area฀was฀(and฀still฀is)฀Yuan฀ Cheng฀Fung,฀who฀is฀known฀as฀the฀father฀of฀biomechanics. Windkessel฀based฀models,฀being฀simple฀and฀fairly฀accurate,฀remain฀popular฀for฀global฀considerations,฀although฀one฀has฀to฀keep฀in฀mind฀that฀they฀are฀insufficient฀for฀฀ quantitative฀ physiological฀ predictions.฀ For฀ local฀ approaches,฀ on฀ the฀ other฀ hand,฀฀ ODE

complex฀cardiovascular฀PDE฀models฀are฀used.฀PDE฀models฀range฀from฀the฀1D฀models฀in฀

Ordinary

which฀the฀unknown฀is฀the฀cross฀section฀area฀of฀the฀vessel฀(see฀Sect.฀4฀in฀this฀article)฀to฀

Differential฀Equations

the฀most฀detailed฀3D฀models,฀by฀which฀one฀can฀find฀the฀distribution฀of฀displacement฀฀ of฀the฀wall฀in฀time฀and฀space฀(see฀Sects.฀7฀and฀8).฀Often฀PDE฀systems฀are฀considered฀ with฀equations฀of฀hydrodynamics฀for฀flow฀coupled฀with฀equations฀of฀elasticity฀for฀the฀ wall.฀Such฀approaches฀are฀the฀most฀accurate฀but฀the฀underlying฀problems฀are฀very฀ complex:฀equations฀are฀highly฀nonlinear,฀difficult฀in฀theoretical฀considerations,฀and฀ require฀very฀large฀computational฀power฀for฀numeric฀solution.

PDE Partial Differential฀Equations฀

The฀ complex฀ 3D฀ models฀ are฀ also฀ sensitive฀ to฀ parameters฀ like฀ the฀ geometry฀ of฀ the฀฀ domain,฀initial฀and฀boundary฀conditions฀and฀physical฀parameters฀of฀the฀equations฀ and฀all฀these฀quantities฀are฀still฀difficult฀to฀determine฀using฀present฀measurement฀ techniques.฀Furthermore,฀the฀development฀of฀models฀is฀limited฀by฀the฀complexity฀ of฀ the฀ underlying฀ physiology.฀ New฀ physiological฀ phenomena฀ are฀ constantly฀ being฀฀ discovered,฀ including฀ sophisticated฀ control฀ and฀ self-regulation฀ mechanisms,฀ the฀฀ presence฀of฀stresses฀and฀strains฀in฀unloaded฀arteries฀(residual฀stresses)฀and฀the฀structure฀฀ and฀function฀of฀various฀components฀of฀the฀wall฀which฀determine฀its฀heterogeneous฀ and฀anisotropic฀behavior.฀Models฀reflecting฀these฀phenomena฀include฀a฀large฀number฀ of฀parameters฀and฀one฀must฀keep฀in฀mind฀that฀fitting฀the฀models฀to฀the฀measurement฀฀ data฀in฀such฀cases฀is฀susceptible฀to฀mistakes฀and,฀furthermore,฀it฀is฀sometimes฀possible฀฀ that฀a฀model฀which฀is฀actually฀inaccurate฀can฀be฀made฀to฀fit฀the฀tests฀in฀some฀limited฀ measurement฀regime.

heterogenous

Because฀of฀these฀limitations,฀the฀simulations฀which฀are฀global฀(i.e.฀involve฀relations฀

consisting฀of฀various฀parts฀

between฀various฀organs฀of฀the฀body)฀use฀only฀simplified฀cardiovascular฀models฀(like฀

that฀are฀very฀different฀

the฀Windkessel฀or฀its฀extensions).฀On฀the฀other฀hand,฀local฀specialized฀models฀are฀

from฀each฀other

available฀for฀specialized฀purposes฀only:฀for฀instance฀they฀are฀used฀in฀the฀design฀of฀ stents฀and฀grafts฀as฀well฀as฀the฀prediction฀and฀treatment฀of฀atherosclerosis฀Among฀ the฀complex฀phenomena฀which฀have฀been฀intensively฀investigated฀and฀incorporated฀ into฀cardiovascular฀models฀in฀the฀last฀ten฀years฀are:฀ –฀including฀the฀residual฀stresses –฀modelling฀the฀fluid฀structure฀interaction –฀considering฀the฀tissue฀anisotropy฀and฀the฀presence฀of฀protein฀fibres –฀considering฀the฀heterogeneity฀and฀layered฀structure฀of฀the฀wall

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–฀investigating฀the฀multiscale฀models฀which฀involve฀coupling฀the฀simple฀1d฀PDE฀or฀ ODE฀models฀with฀complex฀3d฀models฀(see฀[109]).

English++

Exercises Pre-reading questions 1.฀ Draw฀a฀simple฀model฀of฀the฀cardiovascular฀system฀and฀name฀its฀main฀parts฀(arteries,฀฀ veins,฀heart฀etc.) 2.฀ Think฀about฀a฀model฀of฀the฀system฀a฀tree฀with฀the฀heart฀as฀its฀root

Comprehension questions 1.฀ What฀is฀the฀meaning฀of฀the฀words฀systole฀and฀diastole?฀ •฀ the฀contraction฀of฀heart฀chambers,฀driving฀blood฀out฀of฀the฀chambers •฀ the฀period฀of฀time฀when฀the฀heart฀relaxes฀after฀systole฀(contraction) 2.฀ What฀do฀ODE฀and฀PDE฀stand฀for฀(as฀they’re฀not฀explained฀in฀the฀article)? •฀ ODE฀-฀Ordinary฀Differential฀Equations •฀ PDE฀-฀Partial฀Differential฀Equations 3.฀ What฀is฀the฀role฀of฀the฀artery฀walls฀in฀the฀Windkessel฀theory? •฀ a฀reservoir฀of฀energy

Possible topics for discussion 1.฀ Do฀you฀think฀it฀is฀possible฀to฀create฀a฀mathematical฀model฀of฀the฀cardiovascular฀ system฀that฀will฀perfectly฀match฀the฀real฀one?

Possible difﬁculty A฀difficult฀text฀as฀far฀as฀English฀goes฀but฀with฀relatively฀low฀computer฀science฀content;฀ requires฀minimum฀medical฀knowledge.

Further reading The฀whole฀article฀is฀located฀on฀English++฀webpage.

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English++

The Pitch Correction Algorithm: an Overview Robert Ahlﬁnger, Brenton Cheeseman, Patrick Doody

Number฀of฀words฀฀

1100

Computer฀science฀content฀฀

High

Math฀content฀฀

High

English฀language฀complexity฀฀

High

Learning objectives •฀ to฀acquire฀advanced฀mathematical฀vocabulary •฀ to฀develop฀reading฀skills฀by฀identifying฀the฀most฀relevant฀information, •฀ to฀become฀familiar฀with฀scientific฀jargon฀

Sub-areas covered •฀ Sound฀modification •฀ Wave฀modification •฀ Sound฀clearing

Keywords •฀ DFT฀-฀Discrete฀Fourier฀Transform •฀ FFT฀-฀Fast฀Fourier฀transform •฀ matrix฀-฀a฀rectangular฀table฀of฀elements฀(or฀entries),฀which฀may฀be฀numbers฀or,฀ more฀generally,฀any฀abstract฀quantities฀that฀can฀be฀added฀and฀multiplied •฀ matricize฀-฀changing฀sound฀into฀parts฀and฀writing฀into฀a฀matrix

Summary This฀is฀an฀introduction฀to฀the฀specific฀techniques฀involved฀in฀the฀creation฀of฀a฀pitch฀ corrector. Artykuł฀ jest฀ wprowadzeniem฀ do฀ technik฀ związanych฀ z฀ tworzeniem฀ modyfikatora฀ wysokości฀dźwięku.

Pre-reading questions 1.฀ What฀kinds฀of฀digital฀music฀formats฀are฀you฀familiar฀with?

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2.฀ Do฀you฀know฀how฀digital฀audio฀is฀stored? 3.฀ How฀do฀you฀understand฀the฀word฀“pitch”?

English++

The Pitch Correction Algorithm: An Overview 1 Time-Domain vs. Frequency-Domain Clearly,฀the฀goal฀of฀this฀algorithm฀is฀to฀take฀an฀input฀voice฀signal,฀change฀the฀pitch฀of฀

matrix

the฀voice,฀and฀output฀the฀otherwise฀unaltered฀signal.฀In฀order฀to฀do฀so,฀the฀first฀step฀

a฀rectangular฀table฀of฀

is฀to฀decide฀whether฀to฀analyze฀and฀manipulate฀these฀signals฀in฀the฀time฀domain฀or฀

elements฀(or฀entries),฀

the฀ frequency฀ domain.฀ Because฀ our฀ algorithm฀ is฀ primarily฀ concerned฀ with฀ quickly฀฀

which฀may฀be฀numbers฀

identifying฀and฀shifting฀individual฀frequencies,฀we฀worked฀solely฀in฀the฀realm฀of฀the฀

or,฀more฀generally,฀

frequency฀domain.฀Of฀course,฀there฀are฀effective฀ways฀to฀deal฀with฀this฀problem฀without฀฀

any฀abstract฀quantities฀

the฀frequency฀domain.฀However,฀as฀will฀later฀become฀obvious,฀there฀are฀some฀very฀

that฀can฀be฀added฀and฀

useful฀techniques฀we฀developed฀that฀are฀not฀possible฀in฀the฀time฀domain.฀With฀pitch฀

multiplied.

correction฀it฀seems฀that฀Parseval฀has฀made฀a฀mistake;฀there฀is฀simply฀more฀power฀in฀ the฀spectrum.

2 Basic System Model Now฀that฀we฀have฀decided฀how฀to฀look฀at฀our฀signals,฀we฀need฀to฀develop฀a฀general฀ layout฀and฀strategy฀for฀how฀it฀will฀work.

2.1 General Process Summary First,฀the฀signal฀is฀Matricized,฀a฀term฀we฀coined฀to฀describe฀our฀particular฀algorithm฀to฀ break฀up฀the฀signal฀and฀convert฀it฀into฀the฀Fourier฀Domain.฀Basically,฀the฀signal฀comes฀ in฀as฀a฀long฀string฀of฀sampled฀values฀that฀together฀represent฀the฀whole฀sound.฀We,฀in฀ turn,฀convert฀this฀vector฀of฀samples฀into฀a฀matrix฀for฀which฀each฀column฀represents฀ the฀ spectrum฀ of฀ one฀ slice,฀ or฀ chunk,฀ of฀ the฀ signal.฀ Although฀ any฀ chunk฀ size฀ could฀ be฀ used,฀ we฀ found฀ the฀ best฀ performance฀ with฀ chunk฀ sizes฀ of฀ 512฀ samples,฀ which฀฀ represents฀about฀.02฀seconds฀of฀sound฀for฀the฀22฀kHz฀sampling฀rate฀used฀on฀our฀signals.฀฀ Next,฀we฀take฀the฀Discrete฀Fourier฀Transform฀for฀each฀of฀the฀chunks,฀showing฀us฀the฀ frequencies฀present฀at฀every฀given฀moment฀during฀the฀speech.฀These฀DFTs฀are฀then฀ collected฀into฀a฀matrix฀with฀512฀rows฀and฀as฀many฀columns฀as฀there฀are฀.02฀second฀ long฀ chunks฀ in฀ the฀ voice.฀ With฀ a฀ given฀ chunk,฀ our฀ Harmonic฀ Detection฀ algorithm฀ has฀the฀extremely฀difficult฀task฀of฀accurately฀and฀consistently฀identifying฀the฀first฀฀ harmonic฀of฀the฀voice.฀With฀that฀information฀in฀hand,฀the฀program฀reconstructs฀a฀ new฀ DFT฀ representation฀ for฀ the฀ current฀ chunk฀ by฀ first฀ sliding฀ the฀ first฀ harmonic฀ down฀the฀spectrum฀by฀the฀desired฀shift฀in฀pitch,฀and฀then฀following฀up฀with฀all฀of฀ the฀other฀harmonics,฀shifting฀each฀one฀by฀an฀incremental฀multiple฀of฀the฀first฀shift.฀ After฀all฀of฀the฀chunks฀have฀been฀processed฀and฀put฀into฀a฀matrix,฀this฀new฀matrix฀is฀ dematricized฀in฀order฀to฀convert฀the฀information฀back฀into฀the฀time฀domain฀as฀a฀new฀ string฀of฀digital฀samples฀that฀represent฀the฀freshly฀manipulated฀voice.

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English++ 3 Detailed System Model: Step-by-Step DFT Discrete฀

The฀ pitch฀ synthesizer฀ relies฀ on฀ several฀ algorithms฀ to฀ properly฀ alter฀ the฀ pitch฀ of฀ a฀฀ person’s฀voice฀without฀mutilating฀its฀clarity.

Fourier฀Transform

3.1 Matricize First,฀the฀signal฀is฀matricized,฀a฀term฀we฀coined฀to฀represent฀the฀task฀of฀transforming฀ the฀string฀of฀speech฀samples฀into฀a฀matrix฀whose฀columns฀each฀represent฀the฀spectrum฀฀ of฀an฀overlapping฀rectangular฀window,฀or฀chunk,฀of฀the฀signal.฀Each฀portion฀of฀the฀ voice฀is฀contained฀twice฀in฀this฀information฀since฀exactly฀one฀half฀of฀each฀chunk฀is฀ overlapped฀and฀contained฀within฀an฀adjacent฀chunk.฀Next,฀each฀column฀of฀the฀matrix฀ is฀processed฀separately,฀meaning฀we฀attempt฀to฀change฀the฀characteristics฀of฀the฀voice฀ one฀piece฀at฀a฀time฀and฀do฀so฀redundantly.

3.2 Harmonic Detection Now฀that฀we฀have฀isolated฀the฀spectrum฀of฀a฀chunk฀of฀our฀signal,฀we฀use฀a฀harmonic฀ FFT

detector฀to฀find฀the฀first฀harmonic฀of฀the฀voice฀at฀that฀particular฀point฀in฀time.฀This฀

Fast฀Fourier฀transform

task฀is฀harder฀than฀it฀first฀appears฀and฀its฀level฀of฀accuracy฀makes฀the฀single฀biggest฀ contribution฀to฀the฀functionality฀and฀accuracy฀of฀the฀pitch฀synthesizer฀as฀a฀whole.฀ Voiced฀vowel฀noises฀are฀the฀only฀parts฀of฀speech฀that฀contain฀pitch,฀so฀they฀need฀to฀ be฀processed฀differently฀than฀the฀rest฀of฀the฀signal.฀However,฀since฀there฀are฀many฀฀ periods฀of฀noise฀as฀well฀as฀voiced฀(s฀and฀z฀sounds)฀and฀unvoiced฀(like฀f฀and฀t)฀fricatives฀ alongside฀ these฀ important฀ voiced฀ vowel฀ noises,฀ the฀ harmonic฀ detector฀ must฀ wade฀ through฀each฀chunk฀and฀first฀determine฀whether฀or฀not฀it฀is฀dealing฀with฀a฀voiced฀ vowel฀noise.฀If฀so,฀it฀computes฀the฀index฀of฀the฀first฀harmonic฀of฀the฀sample฀by฀taking฀฀ the฀DFT฀of฀the฀first฀half฀of฀the฀magnitude฀of฀the฀DFT฀of฀the฀original฀signal฀chunk.฀ The฀resulting฀spectrum฀will฀have฀a฀very฀large฀DC฀component฀which฀represents฀the฀ grab฀ bag฀ of฀ frequencies฀ present฀ in฀ the฀ original฀ signal,฀ as฀ well฀ as฀ repeating฀ peaks฀฀ corresponding฀to฀the฀only฀periodic฀aspect฀of฀the฀original฀DFT฀the฀signal’s฀harmonics.฀ Therefore,฀the฀harmonic฀detector฀compares฀the฀DC฀amplitude฀with฀the฀next฀biggest฀ peak,฀determining฀simultaneously฀whether฀or฀not฀this฀chunk฀is฀likely฀to฀be฀a฀voiced฀ vowel฀noise฀and฀if฀so฀the฀frequency฀of฀its฀first฀harmonic.

3.3 Frequency Shift With฀ this฀ information฀ in฀ hand,฀ our฀ program฀ determines฀ how฀ far฀ each฀ and฀ every฀฀ frequency฀must฀be฀shifted.฀Since฀you฀interpret฀the฀pitch฀of฀a฀voice฀as฀the฀frequency฀of฀ its฀first฀harmonic,฀the฀first฀harmonic฀is฀shifted฀by฀exactly฀the฀desired฀result.฀In฀turn,฀ the฀frequency฀of฀every฀harmonic฀is฀a฀multiple฀of฀the฀first,฀so฀the฀second฀harmonic฀

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must฀be฀shifted฀twice฀as฀far฀as฀the฀first;฀the฀third฀is฀shifted฀three฀times฀as฀far,฀and฀so฀

English++ on.฀In฀fact,฀we฀use฀the฀index฀of฀the฀first฀harmonic฀to฀determine฀how฀much฀each฀and฀ every฀frequency฀in฀the฀original฀chunk฀will฀shift฀to฀build฀up฀the฀first฀half฀of฀the฀DFT฀ for฀our฀new,฀processed฀chunk.฀We฀are฀trying฀to฀alter฀the฀pitch฀without฀affecting฀the฀

matricize฀

length฀of฀the฀sound,฀so฀this฀stretched฀out฀DFT฀must฀be฀cut฀off฀at฀half฀the฀length฀of฀the฀

changing฀sound฀

original฀DFT,฀at฀which฀point฀we฀have฀the฀completed฀version฀of฀the฀front฀half฀of฀the฀

into฀parts฀and฀writing฀

new฀DFT.฀To฀complete฀the฀second฀half,฀we฀rely฀on฀the฀DFT’s฀symmetry฀properties,฀฀

into฀a฀matrix

noting฀that฀our฀original฀and฀final฀sound฀signals฀are฀both฀purely฀real.฀Therefore,฀the฀ real฀portion฀of฀the฀DFT฀is฀mirrored฀about฀the฀middle,฀and฀the฀imaginary฀portion฀is฀ mirrored฀and฀flipped.฀Finally฀we฀have฀completely฀processed฀the฀given฀window฀of฀the฀ original฀signal.

3.4 Reconstruction To฀ reconstruct฀ the฀ original฀ signal,฀ these฀ processed฀ DFT’s฀ each฀ become฀ a฀ column฀ of฀฀ another฀matrix฀which฀is฀then฀dematricized฀by฀taking฀the฀inverse฀FFT฀of฀each฀spectrum฀ and฀placing฀them฀side฀by฀side฀into฀a฀new฀signal฀that฀has฀the฀same฀length฀as฀the฀original.฀฀ The฀only฀difference฀of฀course฀being฀that฀the฀voice฀in฀the฀signal฀has฀become฀as฀high฀or฀ as฀low฀as฀the฀desired฀shift.

Pitch Shifted Speech Examples ฀

฀

Unaltered฀voice฀

Original

฀

Pitch฀Shifted฀Voice฀

Up฀Down฀

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Exercises Pre-reading questions 1.฀฀฀What฀kinds฀of฀digital฀music฀formats฀are฀you฀familiar฀with? •฀ Kinds฀of฀digital฀music฀which฀I฀am฀familiar฀with฀are฀as฀follows:฀wav,฀ogg,฀mpc,฀flac,฀aiff,฀ raw,฀au,฀gsm,฀dct,฀vox,฀acc,฀mp4/m4a,฀mp3,฀wma,฀wav,฀ra,฀ram,฀dss,฀msv,฀dvf,฀mp4. 2.฀ Do฀you฀know฀how฀digital฀audio฀is฀stored? •฀ Though฀a฀WAV฀file฀can฀hold฀compressed฀audio,฀the฀most฀common฀WAV฀format฀ contains฀uncompressed฀audio฀in฀the฀pulse-code฀modulation฀(PCM)฀format.฀PCM฀ audio฀is฀the฀standard฀audio฀file฀format฀for฀CDs,฀containing฀two฀channels฀of฀44,100฀ samples฀per฀second,฀16฀bits฀per฀sample.฀Since฀PCM฀uses฀an฀uncompressed,฀lossless฀฀ storage฀method,฀which฀keeps฀all฀the฀samples฀of฀an฀audio฀track,฀professional฀users฀ or฀audio฀experts฀may฀use฀the฀WAV฀format฀for฀maximum฀audio฀quality.฀WAV฀audio฀ can฀also฀be฀edited฀and฀manipulated฀with฀relative฀ease฀using฀software.฀ 3.฀ How฀do฀you฀understand฀the฀word฀“pitch”? •฀ to฀set฀at฀a฀particular฀pitch,฀or฀determine฀the฀key฀or฀keynote฀of฀(a฀melody), •฀ the฀degree฀of฀height฀or฀depth฀of฀a฀tone฀or฀of฀sound,฀depending฀upon฀the฀relative฀ rapidity฀of฀the฀vibrations฀by฀which฀it฀is฀produced, •฀ the฀particular฀tonal฀standard฀with฀which฀given฀tones฀may฀be฀compared฀in฀respect฀ to฀their฀relative฀level, •฀ apparent฀predominant฀frequency฀sounded฀by฀an฀acoustic฀source.

Comprehension questions 1.฀ Explain฀these฀words: •฀ to฀(de)matricize฀ ฀

to฀change฀linear฀into฀matrix

•฀ harmonic ฀

pertaining฀to฀harmony,฀as฀distinguished฀from฀melody฀and฀rhythm;฀an฀acoustical฀ frequency฀that฀is฀higher฀in฀frequency฀than฀the฀fundamental.฀

2.฀ What฀is฀the฀pitch฀correction฀algorithm฀used฀for? •฀ It฀is฀used฀for฀changing฀the฀pitch฀of฀voice฀signals.฀ 3.฀ What฀are฀the฀only฀parts฀of฀speech฀that฀contain฀pitch? •฀ Vowels. 4.฀ Explain฀the฀abbreviations฀DFT,฀FFT,฀DC •฀ DFT฀-฀Discrete฀Fourier฀Transform •฀ FFT฀-฀Fast฀Fourier฀Transform •฀ DC฀-฀Direct฀Current

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Possible topics for discussion 1.฀ ฀In฀what฀kinds฀of฀situations฀do฀you฀think฀this฀algorithm฀might฀be฀used? •฀ Pitch฀correction฀has฀numerous฀applications฀and฀is฀commonly฀used฀to฀add฀harmony฀฀ to฀ certain฀ words฀ or฀ phrases฀ without฀ re-recording฀ those฀ words฀ or฀ phrases฀ again฀ and฀again฀at฀the฀necessary฀pitches.฀Depending฀on฀the฀specific฀model฀used,฀various฀฀ vocal฀effects฀can฀be฀added฀

Possible difﬁculties ฀

The฀article฀contains฀a฀lot฀of฀field฀specific฀information.฀

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Software Development Process Wikipedia

Number฀of฀words฀฀

2330

Computer฀science฀content฀฀

High

Math฀content฀฀

Low

Business฀content฀฀

Medium

English฀language฀complexity฀฀

High

Learning objectives •฀ to฀recognize฀differences฀between฀the฀Iterative฀and฀Waterfall฀Process฀of฀software฀ development •฀ to฀be฀able฀to฀give฀examples฀of฀the฀Iterative฀Process •฀ to฀understand฀the฀whole฀process฀from฀the฀customer’s฀order฀to฀implementation฀ •฀ to฀acquire฀basic฀vocabulary฀linked฀with฀the฀software฀development฀process

Sub-areas covered •฀ Software฀engineering฀ •฀ Software฀development฀methodologies฀

Keywords •฀ software฀-฀in฀general,฀computer฀programs฀ •฀ hardware฀-฀all฀the฀physical฀parts฀of฀the฀computer฀ •฀ developer฀-฀person฀who฀develops฀the฀software฀ •฀ agile฀development฀-฀a฀way฀of฀building฀software฀ •฀ code฀ -฀ (coding)฀ refers฀ to฀ the฀ process฀ of฀ transforming฀ a฀ concept฀ into฀ a฀ program฀ code฀ •฀ maintenance฀-฀“looking฀after”฀the฀written฀software฀ •฀ bug฀-฀an฀error฀in฀software,฀something฀that฀spoils฀the฀flow฀of฀the฀program฀ •฀ up-front฀(design,฀analysis,฀requirements)฀-฀the฀oldest฀method฀of฀building฀software

Summary The฀ text฀ deals฀ with฀ the฀ problem฀ of฀ software฀ development.฀ It฀ starts฀ with฀ a฀ short฀ description฀ of฀ some฀ standards฀ (methodologies)฀ that฀ were฀ introduced฀ to฀ unify฀ the฀ process฀ of฀ creating฀ software.฀ In฀ a฀ section฀ entitled:฀ “The฀ Main฀ Steps฀ of฀ Software฀฀ Development”,฀ the฀ reader฀ is฀ introduced฀ to฀ the฀ typical฀ steps฀ that฀ a฀ team฀ follows฀

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while฀developing฀software.฀For฀each฀step฀in฀the฀process,฀there฀is฀a฀brief฀description฀฀ of฀ its฀ basic฀ characteristics.฀ Then฀ the฀ text฀ describes฀ two฀ different฀ approaches฀ to฀฀

English++ software฀development,฀in฀which฀the฀previously฀listed฀steps฀are฀applied.฀The฀final฀part฀฀ discusses฀the฀iterative฀development฀process฀and฀its฀three฀main฀types.฀This฀section฀ also฀presents฀some฀advantages฀and฀disadvantages฀of฀the฀iterative฀process฀compared฀ with฀the฀“Waterfall฀Process”฀model฀of฀design,฀described฀earlier฀in฀the฀text. Tekst฀dotyczy฀problematyki฀tworzenia฀oprogramowania.฀Na฀wstępie,฀opisane฀są฀standardy฀(metodologie)฀jakie฀zostały฀wprowadzone฀by฀ujednolicić฀ten฀proces.฀W฀następnej฀ części,฀ zatytułowanej฀ “Main฀ Steps฀ Of฀ The฀ Software฀ Development”,฀ przybliżone฀ zostają฀główne฀kroki,฀którymi฀zwykle฀podąża฀zespół฀tworzący฀oprogramowanie.฀Kroki฀ te฀opatrzone฀są฀krótkimi฀opisami฀ich฀cech฀lub฀problemów,฀jakie฀ze฀sobą฀niosą.฀Dwie฀ ostatnie฀ części฀ tekstu฀ opisują฀ dwa฀ różne฀ podejścia฀ do฀ tworzenia฀ oprogramowania,฀฀ w฀których฀wykorzystane฀są฀opisane฀wcześniej฀kroki.฀W฀ostatniej฀części,฀opisującej฀iteracyjny฀proces฀projektowania฀przedstawione฀są฀trzy฀spośród฀jego฀najważniejszych฀odmian฀(Agile฀Software฀Development,฀Extreme฀Programming฀i฀Test฀Driven฀Development).฀฀ Część฀ta฀przedstawia฀także฀niektóre฀zalety฀oraz฀wady฀iteracyjnego฀procesu฀projektowania฀ w฀ zestawieniu฀ w฀ modelem฀ projektowania฀ “Waterfall฀ Processes”฀ opisanym฀ wcześniej.฀

Pre-reading questions 1.฀ What฀kind฀of฀job฀do฀you฀see฀yourself฀holding฀five฀years฀from฀now?฀ 2.฀ Do฀you฀know฀any฀companies฀developing฀software?฀Would฀you฀like฀to฀join฀any฀of฀them?฀ 3.฀ How฀ do฀ you฀ imagine฀ work฀ is฀ organized฀ in฀ these฀ companies?฀ What฀ software฀฀ development฀methods฀do฀you฀know?฀ 4.฀ Have฀you฀used฀any฀of฀these฀methods฀so฀far?฀

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Software Development Process

A฀ software฀ development฀ process฀ is฀ a฀ structure฀ imposed฀ on฀ the฀ development฀ of฀ a฀฀ software฀product.฀Synonyms฀include฀software฀life฀cycle฀and฀software฀process.฀There฀ are฀several฀models฀for฀such฀processes,฀each฀describing฀approaches฀to฀a฀variety฀of฀tasks฀ or฀activities฀that฀take฀place฀during฀the฀process.฀ A฀ growing฀ body฀ of฀ software฀ development฀ organizations฀ implement฀ process฀฀ methodologies.฀Many฀of฀them฀are฀in฀the฀defense฀industry,฀which฀in฀the฀U.S.฀requires฀ a฀rating฀based฀on฀‘process฀models’฀to฀obtain฀contracts.฀The฀international฀standard฀for฀ describing฀the฀method฀of฀selecting,฀implementing฀and฀monitoring฀the฀life฀cycle฀for฀ software฀is฀ISO฀12207.฀ software

The฀ Capability฀ Maturity฀ Model฀ (CMM)฀ is฀ one฀ of฀ the฀ leading฀ models.฀ Independent฀฀

in฀general฀

assessments฀grade฀organizations฀on฀how฀well฀they฀follow฀their฀defined฀processes,฀not฀

computer฀programs฀

on฀the฀quality฀of฀those฀processes฀or฀the฀software฀produced.฀CMM฀is฀gradually฀being฀ replaced฀by฀CMMI.฀ISO฀9000฀describes฀standards฀for฀formally฀organizing฀processes฀ with฀documentation.฀ ISO฀15504,฀also฀known฀as฀Software฀Process฀Improvement฀Capability฀Determination฀ (SPICE),฀is฀a฀“framework฀for฀the฀assessment฀of฀software฀processes”.฀This฀standard฀is฀ aimed฀at฀setting฀out฀a฀clear฀model฀for฀process฀comparison.฀SPICE฀is฀used฀much฀like฀ CMM฀and฀CMMI.฀It฀models฀processes฀to฀manage,฀control,฀guide฀and฀monitor฀software฀ development.฀ This฀ model฀ is฀ then฀ used฀ to฀ measure฀ what฀ a฀ development฀ organization฀or฀project฀team฀actually฀does฀during฀software฀development.฀This฀information฀is฀฀ analyzed฀to฀identify฀weaknesses฀and฀drive฀improvement.฀It฀also฀identifies฀strengths฀that฀ can฀be฀continued฀or฀integrated฀into฀common฀practice฀for฀that฀organization฀or฀team.฀ Six฀Sigma฀is฀a฀methodology฀to฀manage฀process฀variations฀that฀uses฀data฀and฀statistical฀ analysis฀to฀measure฀and฀improve฀a฀company’s฀operational฀performance.฀It฀works฀by฀ identifying฀and฀eliminating฀defects฀in฀manufacturing฀and฀service-related฀processes.฀ The฀ maximum฀ permissible฀ defects฀ is฀ 3.4฀ per฀ one฀ million฀ opportunities.฀ However,฀ Six฀Sigma฀is฀manufacturing-oriented฀and฀needs฀further฀research฀on฀its฀relevance฀to฀

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software฀development.฀

English++ The Main Steps of Software Development Domain Analysis Often฀the฀first฀step฀in฀attempting฀to฀design฀a฀new฀piece฀of฀software,฀whether฀it฀be฀

hardware

an฀addition฀to฀an฀existing฀software,฀a฀new฀application,฀a฀new฀subsystem฀or฀a฀whole฀

all฀the฀physical฀parts฀

new฀system,฀is,฀what฀is฀generally฀referred฀to฀as฀“Domain฀Analysis”.฀Assuming฀that฀the฀

of฀the฀computer฀

developers฀(including฀the฀analysts)฀are฀not฀sufficiently฀knowledgeable฀in฀the฀subject฀ area฀of฀the฀new฀software,฀the฀first฀task฀is฀to฀investigate฀the฀so-called฀“domain”฀of฀the฀ software.฀The฀more฀knowledgeable฀they฀are฀about฀the฀domain฀already,฀the฀less฀the฀ work฀required.฀Another฀objective฀of฀this฀work฀is฀to฀get฀the฀analysts฀(who฀will฀later฀ try฀to฀elicit฀and฀gather฀the฀requirements฀from฀the฀area)฀experts฀or฀professionals฀to฀ speak฀with฀them฀in฀the฀domain’s฀own฀terminology฀and฀to฀better฀understand฀what฀is฀ being฀said฀by฀these฀people,฀otherwise฀they฀will฀not฀be฀taken฀seriously.฀So,฀this฀phase฀ is฀an฀important฀prelude฀to฀extracting฀and฀gathering฀the฀requirements.฀The฀following฀ quote฀captures฀the฀kind฀of฀situation฀an฀analyst฀who฀hasn’t฀done฀his฀homework฀well฀ may฀face฀in฀speaking฀with฀a฀professional฀from฀the฀domain:฀“I฀know฀you฀believe฀you฀ understood฀what฀you฀think฀I฀said,฀but฀I฀am฀not฀sure฀you฀realize฀what฀you฀heard฀is฀not฀ what฀I฀meant.”฀

Software Elements Analysis The฀most฀important฀task฀in฀creating฀a฀software฀product฀is฀extracting฀the฀requirements.฀฀ Customers฀typically฀know฀what฀they฀want,฀but฀not฀what฀software฀should฀do,฀while฀ incomplete,฀ambiguous฀or฀contradictory฀requirements฀are฀recognized฀by฀skilled฀and฀ experienced฀software฀engineers.฀Frequently฀demonstrating฀live฀code฀may฀help฀reduce฀ the฀risk฀that฀the฀requirements฀are฀incorrect.฀

Speciﬁcation Specification฀is฀the฀task฀of฀precisely฀describing฀the฀software฀to฀be฀written,฀possibly฀in฀ a฀rigorous฀way.฀In฀practice,฀most฀successful฀specifications฀are฀written฀to฀understand฀ and฀fine-tune฀applications฀that฀were฀already฀well-developed,฀although฀safety-critical฀฀ software฀ systems฀ are฀ often฀ carefully฀ specified฀ prior฀ to฀ application฀ development.฀฀ Specifications฀are฀most฀important฀for฀external฀interfaces฀that฀must฀remain฀stable.฀

Software architecture The฀ architecture฀ of฀ a฀ software฀ system฀ refers฀ to฀ an฀ abstract฀ representation฀ of฀ that฀ system.฀Architecture฀is฀concerned฀with฀making฀sure฀the฀software฀system฀will฀meet฀ the฀requirements฀of฀the฀product,฀as฀well฀as฀ensuring฀that฀future฀requirements฀can฀ be฀addressed.฀The฀architecture฀step฀also฀addresses฀interfaces฀between฀the฀software฀

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English++ system฀and฀other฀software฀products,฀as฀well฀as฀the฀underlying฀hardware฀or฀the฀host฀ operating฀system.฀

Implementation (or coding) Reducing฀a฀design฀to฀code฀may฀be฀the฀most฀obvious฀part฀of฀the฀software฀engineering฀ job,฀but฀it฀is฀not฀necessarily฀the฀largest฀portion.฀

Testing Testing฀of฀parts฀of฀software,฀especially฀where฀code฀by฀two฀different฀engineers฀must฀ work฀together,฀falls฀to฀the฀software฀engineer.฀

Documentation An฀ important฀ (and฀ often฀ overlooked)฀ task฀ is฀ documenting฀ the฀ internal฀ design฀ of฀฀ software฀for฀the฀purpose฀of฀future฀maintenance฀and฀enhancement.฀Documentation฀ is฀most฀important฀for฀external฀interfaces.฀

Software Training and Support developer

A฀large฀percentage฀of฀software฀projects฀fail฀because฀the฀developers฀fail฀to฀realize฀that฀it฀

person฀who฀develops฀

doesn’t฀matter฀how฀much฀time฀and฀planning฀a฀development฀team฀puts฀into฀creating฀฀

the฀software฀

software฀if฀nobody฀in฀an฀organization฀ends฀up฀using฀it.฀People฀are฀occasionally฀resistant฀฀ to฀change฀and฀avoid฀venturing฀into฀an฀unfamiliar฀area฀so,฀as฀a฀part฀of฀the฀deployment฀ phase,฀ it฀ is฀ very฀ important฀ to฀ have฀ training฀ classes฀ for฀ the฀ most฀ enthusiastic฀ software฀users,฀shifting฀the฀training฀towards฀the฀neutral฀users฀intermixed฀with฀the฀avid฀฀ supporters,฀and฀finally฀incorporate฀the฀rest฀of฀the฀organization฀into฀adopting฀the฀new฀ software.฀Users฀will฀have฀lots฀of฀questions฀and฀software฀problems฀which฀leads฀to฀the฀ next฀phase฀of฀software.฀

Maintenance Maintaining฀and฀enhancing฀software฀to฀cope฀with฀newly฀discovered฀problems฀or฀new฀ requirements฀can฀take฀far฀more฀time฀than฀the฀initial฀development฀of฀the฀software.฀ Not฀only฀may฀it฀be฀necessary฀to฀add฀code฀that฀does฀not฀fit฀the฀original฀design฀but฀just฀ determining฀ how฀ software฀ works฀ at฀ some฀ point฀ after฀ it฀ is฀ completed฀ may฀ require฀฀ significant฀effort฀by฀a฀software฀engineer.฀About฀60%฀of฀all฀software฀engineering฀work฀ is฀maintenance,฀but฀this฀statistic฀can฀be฀misleading.฀A฀small฀part฀of฀that฀is฀fixing฀bugs.฀ Most฀maintenance฀is฀extending฀systems฀to฀do฀new฀things,฀which฀in฀many฀ways฀can฀ be฀considered฀new฀work.฀

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English++ Waterfall processes The฀best-known฀and฀oldest฀process฀is฀the฀waterfall฀model,฀where฀developers฀(roughly)฀฀ follow฀these฀steps฀in฀order:฀ •฀ state฀requirements฀ •฀ analyze฀requirements฀ •฀ design฀a฀solution฀approach฀

agile฀development ฀a฀way฀of฀building฀software฀

•฀ architect฀a฀software฀framework฀for฀that฀solution฀ •฀ develop฀code฀ •฀ test฀(perhaps฀unit฀tests฀then฀system฀tests)฀ •฀ deploy฀ •฀ post-implementation.฀ After฀ each฀ step฀ is฀ finished,฀ the฀ process฀ proceeds฀ to฀ the฀ next฀ step,฀ just฀ as฀ builders฀ don’t฀revise฀the฀foundation฀of฀a฀house฀after฀the฀framing฀has฀been฀erected.฀There฀is฀a฀ misconception฀that฀the฀process฀has฀no฀provision฀for฀correcting฀errors฀in฀early฀steps฀ (for฀example,฀in฀the฀requirements).฀In฀fact฀this฀is฀where฀the฀domain฀of฀requirements฀ management฀comes฀in฀which฀includes฀change฀control.฀This฀approach฀is฀used฀in฀high฀ risk฀projects,฀particularly฀large฀defense฀contracts.฀The฀problems฀in฀waterfall฀do฀not฀ arise฀ from฀ “immature฀ engineering฀ practices,฀ particularly฀ in฀ requirements฀ analysis฀ and฀ requirements฀ management”.฀ Studies฀ of฀ the฀ failure฀ rate฀ of฀ the฀ DOD-STD-2167฀ specification,฀which฀enforced฀waterfall,฀have฀shown฀that฀the฀more฀closely฀a฀project฀ follows฀its฀process,฀specifically฀in฀up-front฀requirements฀gathering,฀the฀more฀likely฀ the฀project฀is฀to฀release฀features฀that฀are฀not฀used฀in฀their฀current฀form.฀

Iterative processes Iterative฀ development฀ prescribes฀ the฀ construction฀ of฀ initially฀ small฀ but฀ ever฀ larger฀ portions฀of฀a฀software฀project฀to฀help฀all฀those฀involved฀to฀uncover฀important฀issues฀ early฀before฀problems฀or฀faulty฀assumptions฀can฀lead฀to฀disaster.฀Iterative฀processes฀ are฀preferred฀by฀commercial฀developers฀because฀it฀allows฀a฀potential฀of฀reaching฀the฀ design฀goals฀of฀a฀customer฀who฀does฀not฀know฀how฀to฀define฀what฀they฀want.฀ Agile฀ software฀ development฀ processes฀ are฀ built฀ on฀ the฀ foundation฀ of฀ iterative฀฀ development.฀To฀that฀foundation฀they฀add฀a฀lighter,฀more฀people-centric฀viewpoint฀ than฀traditional฀approaches.฀Agile฀processes฀use฀feedback,฀rather฀than฀planning,฀as฀ their฀primary฀control฀mechanism.฀The฀feedback฀is฀driven฀by฀regular฀tests฀and฀releases฀ of฀the฀evolving฀software.฀ Agile฀ processes฀ seem฀ to฀ be฀ more฀ efficient฀ than฀ older฀ methodologies,฀ using฀ less฀฀ programmer฀time฀to฀produce฀more฀functional,฀higher฀quality฀software,฀but฀have฀the฀ drawback฀from฀a฀business฀perspective฀that฀they฀do฀not฀provide฀long-term฀planning฀฀ capability.฀ However,฀ polls฀ show฀ gains,฀ sometimes฀ significant.฀ For฀ example,฀ a฀ sur-

157

English++ vey,฀ published฀ in฀ August฀ 2006฀ by฀ Version฀ One฀ and฀ Agile฀ Alliance฀ and฀ based฀ on฀ polling฀ more฀ than฀ 700฀ companies฀ shows฀ the฀ following฀ benefits฀ of฀ Agile฀ approach฀ (http://www.agilejournal.com/articles/from-the-editor/agile-survey-results%3a-solid฀ -experience-and-real-results.html).฀ The฀ survey฀ was฀ repeated฀ in฀ August฀ 2007฀ with฀ about฀ 1,700฀ respondents฀ (http://www.agilejournal.com/articles/from-the-editor/฀ agile-survey-results%3a-widespread-adoption,-emphasis-on-productivity-and-quality. html).฀Here฀are฀some฀results:฀ code฀(coding)฀ refers฀

1. Accelerated time to market.

to฀the฀process฀of฀

1.฀ 2006:฀10%฀or฀higher฀improvements฀reported฀by฀86%฀of฀respondents฀

transforming฀a฀concept฀

2.฀ 2007:฀10%฀or฀higher฀improvements฀reported฀by฀90%฀of฀respondents฀

into฀a฀program฀code

3.฀ 2006:฀25%฀or฀higher฀improvements฀reported฀by฀60%฀of฀respondents฀ 4.฀ 2007:฀25%฀or฀higher฀improvements฀reported฀by฀54%฀of฀respondents฀

2. Increased productivity. 1.฀ 2006:฀10%฀or฀higher฀improvements฀reported฀by฀87%฀of฀respondents฀ 2.฀ 2007:฀10%฀or฀higher฀improvements฀reported฀by฀83%฀of฀respondents฀ 3.฀ 2006:฀25%฀or฀higher฀improvements฀reported฀by฀55%฀of฀respondents฀ 4.฀ 2007:฀25%฀or฀higher฀improvements฀reported฀by฀55%฀of฀respondents฀

3. Reduced software defects. 1.฀ 2006:฀10%฀or฀higher฀improvements฀reported฀by฀86%฀of฀respondents฀ 2.฀ 2007:฀10%฀or฀higher฀improvements฀reported฀by฀85%฀of฀respondents฀ 3.฀ 2006:฀25%฀or฀higher฀improvements฀reported฀by฀55%฀of฀respondents฀ 4.฀ 2007:฀25%฀or฀higher฀improvements฀reported฀by฀54%฀of฀respondents฀

4. Reduced cost. 1.฀ 2006:฀10%฀or฀higher฀improvements฀reported฀by฀63%฀of฀respondents฀ 2.฀ 2007:฀10%฀or฀higher฀improvements฀reported฀by฀28%฀of฀respondents฀ 3.฀ 2006:฀25%฀or฀higher฀improvements฀reported฀by฀26%฀of฀respondents฀ 4.฀ 2007:฀25%฀or฀higher฀improvements฀reported฀by฀28%฀of฀respondents฀ The฀stability฀of฀results฀on฀a฀broader฀set฀of฀respondents฀suggests฀that฀we฀see฀the฀actual฀ trend.฀

Among other interesting improvements reported were: •฀Enhanced฀ability฀to฀manage฀changing฀priorities฀ •฀Alignment฀between฀IT฀and฀business฀goals฀ •฀Improved฀team฀morale฀

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•฀Reduced฀project฀risk฀

English++ There฀is฀also฀an฀interesting฀chart฀at฀http://versionone.com/Resources/฀AgileBenefits. asp฀ that฀ shows฀ Agile฀ development฀ value฀ proposition฀ in฀ comparison฀ to฀ traditional฀ development.฀ Extreme฀Programming,฀XP,฀is฀the฀best-known฀iterative฀process.฀In฀XP,฀the฀phases฀are฀ carried฀out฀in฀extremely฀small฀(or฀“continuous”)฀steps฀compared฀to฀the฀older,฀“batch”฀ processes.฀The฀(intentionally฀incomplete)฀first฀pass฀through฀the฀steps฀might฀take฀a฀ day฀or฀a฀week,฀rather฀than฀the฀months฀or฀years฀of฀each฀complete฀step฀in฀the฀Waterfall฀model.฀First,฀one฀writes฀automated฀tests,฀to฀provide฀concrete฀goals฀for฀development.฀Next฀is฀coding฀(by฀a฀pair฀of฀programmers),฀which฀is฀complete฀when฀all฀the฀tests฀

maintenance฀

pass,฀and฀the฀programmers฀can’t฀think฀of฀any฀more฀tests฀that฀are฀needed.฀Design฀and฀฀

“looking฀after”฀

architecture฀emerge฀out฀of฀refactoring,฀and฀come฀after฀coding.฀Design฀is฀done฀by฀the฀

the฀written฀software฀

same฀people฀who฀do฀the฀coding.฀(Only฀the฀last฀feature฀-฀merging฀design฀and฀code฀-฀is฀ common฀to฀all฀the฀other฀agile฀processes.)฀The฀incomplete฀but฀functional฀system฀is฀ deployed฀or฀demonstrated฀for฀(some฀subset฀of)฀the฀users฀(at฀least฀one฀of฀which฀is฀on฀ the฀development฀team).฀At฀this฀point,฀the฀practitioners฀start฀again฀on฀writing฀tests฀for฀ the฀next฀most฀important฀part฀of฀the฀system.฀ Test฀ Driven฀ Development฀ (TDD)฀ is฀ a฀ useful฀ output฀ of฀ the฀ Agile฀ camp฀ but฀ raises฀ a฀ conundrum.฀TDD฀requires฀that฀a฀unit฀test฀be฀written฀for฀a฀class฀before฀the฀class฀is฀ written.฀Therefore,฀the฀class฀firstly฀has฀to฀be฀“discovered”฀and฀secondly฀defined฀in฀ sufficient฀ detail฀ to฀ allow฀ the฀ write-test-once-and-code-until-class-passes฀ model฀ that฀ TDD฀actually฀uses.฀This฀is฀actually฀counter฀to฀Agile฀approaches,฀particularly฀(so-called)฀ Agile฀Modeling,฀where฀developers฀are฀still฀encouraged฀to฀code฀early,฀with฀light฀design.฀฀ Obviously,฀ to฀ get฀ the฀ claimed฀ benefits฀ of฀ TDD,฀ a฀ full฀ design฀ down฀ to฀ class฀ and฀฀

bug

responsibilities฀(captured฀using,฀for฀example,฀Design฀By฀Contract)฀is฀necessary.฀This฀

an฀error฀in฀software,฀

counts฀towards฀iterative฀development,฀with฀a฀design฀locked฀down,฀but฀not฀iterative฀

something฀that฀spoils

design฀-฀as฀heavy฀refactoring฀and฀re-engineering฀negate฀the฀usefulness฀of฀TDD.฀

฀the฀flow฀of฀the฀program฀

While฀iterative฀development฀approaches฀have฀their฀advantages,฀software฀architects฀ are฀ still฀ faced฀ with฀ the฀ challenge฀ of฀ creating฀ a฀ reliable฀ foundation฀ upon฀ which฀ to฀ develop.฀ Such฀ a฀ foundation฀ often฀ requires฀ a฀ fair฀ amount฀ of฀ up-front฀ analysis฀ and฀฀ prototyping฀ to฀ build฀ a฀ development฀ model.฀ The฀ development฀ model฀ often฀ relies฀ upon฀specific฀design฀patterns฀and฀entity฀relationship฀diagrams฀(ERD).฀Without฀this฀ upfront฀foundation,฀iterative฀development฀can฀create฀long฀term฀challenges฀that฀are฀ significant฀in฀terms฀of฀cost฀and฀quality.฀ Critics฀of฀iterative฀development฀approaches฀point฀out฀that฀these฀processes฀place฀what฀ may฀be฀an฀unreasonable฀expectation฀upon฀the฀recipient฀of฀the฀software:฀that฀they฀ must฀ possess฀ the฀ skills฀ and฀ experience฀ of฀ a฀ seasoned฀ software฀ developer.฀ The฀ approach฀can฀also฀be฀very฀expensive฀if฀iterations฀are฀not฀small฀enough฀to฀mitigate฀risk;฀ akin฀ to…฀ “If฀ you฀ don’t฀ know฀ what฀ kind฀ of฀ house฀ you฀ want,฀ let฀ me฀ build฀ you฀ one฀

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English++ and฀ see฀ if฀ you฀ like฀ it.฀ If฀ you฀ don’t,฀ we’ll฀ tear฀ it฀ all฀ down฀ and฀ start฀ over”.฀ By฀ analogy฀the฀critic฀argues฀that฀up-front฀design฀is฀as฀necessary฀for฀software฀development฀ as฀it฀is฀for฀architecture.฀The฀problem฀with฀this฀criticism฀is฀that฀the฀whole฀point฀of฀฀ up-front฀(design,฀analysis,฀

iterative฀programming฀is฀that฀you฀don’t฀have฀to฀build฀the฀whole฀house฀before฀you฀get฀฀

requirements)

feedback฀from฀the฀recipient.฀Indeed,฀in฀a฀sense฀conventional฀programming฀places฀more฀

฀–฀the฀oldest฀method฀of฀

of฀this฀burden฀on฀the฀recipient,฀as฀the฀requirements฀and฀planning฀phases฀take฀place฀

building฀software

entirely฀before฀the฀development฀begins,฀and฀testing฀only฀occurs฀after฀development฀฀ is฀officially฀over.฀ In฀fact,฀a฀relatively฀quiet฀turn฀around฀in฀the฀Agile฀community฀has฀occurred฀on฀the฀ notion฀of฀“evolving”฀the฀software฀without฀the฀requirements฀locked฀down.฀In฀the฀old฀ world฀ this฀ was฀ called฀ requirements฀ creep฀ and฀ never฀ made฀ commercial฀ sense.฀ The฀ Agile฀community฀has฀similarly฀been฀“burnt”฀because,฀in฀the฀end,฀when฀the฀customer฀ asks฀for฀something฀that฀breaks฀the฀architecture,฀and฀won’t฀pay฀for฀the฀re-work,฀the฀ project฀terminates฀in฀an฀Agile฀manner.฀ These฀ approaches฀ have฀ been฀ developed฀ along฀ with฀ web฀ based฀ technologies.฀ As฀ such,฀they฀are฀actually฀more฀akin฀to฀maintenance฀life฀cycles฀given฀that฀most฀of฀the฀฀ architecture฀ and฀ capability฀ of฀ the฀ solutions฀ is฀ embodied฀ within฀ the฀ technology฀฀ selected฀as฀the฀back฀bone฀of฀the฀application.฀

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Exercises Pre-reading questions 1.฀ What฀kind฀of฀job฀do฀you฀see฀yourself฀holding฀five฀years฀from฀now?฀ •฀ computer฀programmer/software฀developer,฀graphic฀designer,฀scientist฀ 2.฀ Do฀you฀know฀any฀companies฀developing฀software?฀Would฀you฀like฀to฀join฀any฀of฀ them?฀ •฀ IBM,฀Google,฀Microsoft,฀Sabre,฀Motorola,฀Onet,฀Interia฀ 3.฀ How฀ do฀ you฀ imagine฀ work฀ is฀ organized฀ in฀ these฀ companies?฀ What฀ software฀฀ development฀methods฀do฀you฀know?฀ •฀ methods:฀for฀example,฀iterative฀(extreme฀programming) 4.฀ Have฀you฀used฀any฀of฀these฀methods฀so฀far?฀

Comprehension questions 1.฀ What฀is฀the฀idea฀behind฀Test฀Driven฀Development?฀ •฀ Writing฀tests฀for฀all฀the฀steps฀of฀software฀development,฀from฀planning฀to฀coding.฀ 2.฀ What฀are฀the฀main฀benefits฀of฀using฀Agile฀Methods?฀ •฀ Better฀productivity,฀reduction฀of฀software฀defects,฀cost฀reduction,฀reduced฀project฀ risk.฀ 3.฀ What฀is฀the฀main฀aim฀of฀introducing฀the฀SPICE฀standard?฀ •฀ ฀To฀simplify฀the฀comparison฀of฀different฀development฀models.฀ 4.฀ What฀is฀the฀aim฀of฀utilizing฀the฀Six฀Sigma฀methodology,฀and฀how฀can฀it฀help฀the฀ performance฀of฀some฀kinds฀of฀companies?฀ •฀ The฀aim฀of฀using฀the฀Six฀Sigma฀methodology฀is฀to฀improve฀the฀performance฀of฀ a฀ company.฀ The฀ use฀ of฀ this฀ methodology฀ can฀ identify฀ and฀ eliminate฀ defects฀ in฀ manufacturing฀and฀service-related฀processes.฀ 5.฀ Which฀ of฀ the฀ software฀ development฀ steps฀ involve฀ most฀ contact฀ with฀ the฀฀ customer?฀(possible฀topic฀for฀discussion)฀ •฀ Software฀elements฀analysis,฀Specification,฀Software฀training฀and฀support. 6.฀ What฀ kind฀ of฀ projects฀ often฀ requires฀ the฀ use฀ of฀ the฀ Waterfall฀ Process฀ of฀฀ software฀development?฀ •฀ Usually฀high-risk฀projects.฀ 7.฀ What฀is฀the฀function฀of฀requirements฀management,฀mentioned฀in฀reference฀to฀ Waterfall฀Process?฀ •฀ ฀To฀control฀changes฀and฀correct฀mistakes฀during฀requirements฀establishing.฀ 8.฀ With฀reference฀to฀iterative฀processes,฀what฀is฀agile฀development฀mainly฀based฀on?฀ •฀ It฀ is฀ mainly฀ based฀ on฀ the฀ feedback฀ given฀ by฀ the฀ customer,฀ who฀ is฀ repeatedly฀฀ provided฀with฀constantly฀evolving฀software.฀ 9.฀ What฀condition฀must฀the฀coding฀process฀fulfil฀before฀it฀can฀be฀completed?฀ •฀ The฀implemented฀part฀has฀to฀pass฀all฀the฀tests฀designed฀before฀coding.฀

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English++ Further exercises 1.฀ Students฀work฀in฀two฀teams:฀A/B.฀Group฀A฀are฀the฀customers,฀group฀B฀the฀developers.฀฀ Imagine฀how฀the฀iterative฀process฀of฀development฀works฀on฀any฀application฀(e.g.฀ building฀a฀house)฀and฀simulate฀it.฀Prepare฀a฀very฀short฀report฀which฀sums฀up฀the฀ negotiations฀between฀the฀teams.฀ 2.฀ Prepare฀a฀comparison฀between฀iterative฀and฀waterfall฀processes.฀Write฀it฀down฀in฀ table฀form.฀Focusing฀on฀the฀differences,฀answer฀the฀following฀questions:฀ •฀ Which฀features฀of฀these฀techniques฀do฀you฀think฀are฀better?฀ •฀ Do฀you฀use฀any฀of฀them?฀Which฀ones฀and฀why?฀

Possible topics for discussion 1.฀ Do฀you฀agree฀with฀the฀critics฀of฀the฀iterative฀processes?฀ 2.฀ What฀are฀the฀steps฀of฀software฀development฀that฀are฀indispensable฀for฀creating฀a฀ good฀academic฀project?฀ 3.฀ Imagine฀that฀you฀are฀the฀manager฀of฀a฀team฀of฀several฀people.฀Write฀the฀outline฀ of฀a฀project฀that฀you฀have฀heard฀about฀during฀your฀studies.฀How฀would฀you฀divide฀ the฀work฀within฀your฀team฀to฀make฀the฀final฀product฀perfect?฀

Possible difﬁculties In฀ some฀ parts฀ of฀ the฀ text฀ the฀ language฀ is฀ complicated,฀ so฀ intensive฀ reading฀ is฀฀ required.

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English++

English++ English for Computer Science Students

Listening Chapter

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What is Artiﬁcial Intelligence? Basic Questions John McCarthy

Running฀time฀฀

17’41

Computer฀science฀content฀฀

Medium

Math฀content฀฀

Low

English฀language฀complexity฀฀

Medium

Learning objectives •฀ to฀understand฀what฀exactly฀is฀meant฀by฀the฀term฀artificial฀intelligence฀(AI) •฀ to฀be฀aware฀of฀the฀current฀situation฀in฀AI฀systems฀and฀the฀possibilities฀for฀future฀ development฀ •฀ to฀understand฀general฀AI฀theories฀

Keywords •฀ confine฀-฀to฀define฀boundaries;฀to฀limit฀the฀extent฀(of฀an฀activity) •฀ computational฀-฀adj.1.฀involving฀computers,฀2.฀that฀can฀be฀computed฀ •฀ correlate฀-฀to฀have฀a฀close฀similarity,฀connection฀or฀causal฀relationship฀with฀ •฀ heuristic฀hypothesis฀-฀a฀hypothesis฀that฀has฀a฀very฀high฀probability฀of฀being฀true฀ on฀the฀basis฀of฀reasoning฀and฀past฀experience •฀ cognitive฀science฀-฀the฀scientific฀study฀of฀mind฀or฀intelligence฀based฀on฀relevant฀ fields,฀including฀psychology,฀philosophy,฀neuroscience,฀linguistics,฀anthropology,฀ computer฀science,฀and฀biology •฀ incoherent฀-฀confused฀and฀inconsistent;฀illogical฀ •฀ computational฀complexity฀-฀an฀area฀of฀computer฀design฀dealing฀with฀the฀problems฀฀ of฀algorithms฀and฀their฀ability฀to฀solve฀a฀given฀problem฀

Pre-listening questions 1.฀ How฀would฀you฀define฀“intelligence”?฀ 2.฀ Have฀you฀ever฀thought฀of฀computer฀programs฀as฀being฀“intelligent”?฀ 3.฀ Do฀you฀think฀that฀computers฀or฀machines฀will฀ever฀be฀as฀intelligent฀as฀humans?฀ 4.฀ Are฀ you฀ afraid฀ of฀ the฀ nightmare฀ scenario฀ in฀ which฀ machines฀ have฀ control฀ over฀ people,฀possibly฀leading฀to฀the฀annihilation฀of฀the฀human฀race?฀

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Summary This฀text,฀in฀the฀form฀of฀an฀interview,฀is฀written฀by฀Prof.฀John฀McCarthy฀of฀Stanford฀ University,฀who฀is฀an฀authority฀in฀the฀฀field฀of฀AI฀and฀was฀the฀first฀to฀use฀this฀term.฀ It฀covers฀the฀main฀ideas฀of฀AI฀and฀its฀differences฀from฀human฀intelligence฀as฀well฀as฀฀ describing฀AI฀in฀the฀context฀of฀biology,฀psychology฀and฀even฀philosophy.฀In฀the฀interview฀฀ Professor฀McCarthy฀answers฀basic฀questions฀about฀artificial฀intelligence.฀ Ciekawy฀ tekst฀ opisujący฀ podstawowe฀ i฀ bardzo฀ ogólne฀ zagadnienia฀ z฀ problemu฀฀ sztucznej฀inteligencji.฀Jego฀niewątpliwym฀walorem฀jest฀fakt,฀iż฀pomimo฀ogólnej฀treści฀ dotyka฀on฀dziedzin฀takich฀jak:฀psychologia,฀nauki฀kognitywne฀czy฀złożoność฀obliczeniowa.฀Można฀w฀nim฀znaleźć฀pytania,฀które฀mógłby฀zadać฀całkowity฀laik฀i฀zadowolić฀ się฀ich฀odpowiedzią,฀jednocześnie฀interesując฀i฀informatyków.฀Dodatkowo,฀ponieważ฀ tekst฀jest฀tak฀ogólny,฀może฀zachęcić฀studentów฀do฀poszukiwania฀bardziej฀zaawansowanych฀tekstów฀na฀temat฀AI.฀Tekst฀jest฀napisany฀w฀formie฀FAQ,฀i฀może฀służyć฀jako฀ przybliżenie฀tej฀formy฀pisanego฀tekstu.฀

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English++ Transcript

What is Artiﬁcial Intelligence? Basic Questions Q.฀What฀is฀artificial฀intelligence?฀ A.฀ It฀ is฀ the฀ science฀ and฀ engineering฀ of฀ making฀ intelligent฀ machines,฀ especially฀฀

correlate฀

intelligent฀computer฀programs.฀It฀is฀related฀to฀the฀similar฀task฀of฀using฀computers฀to฀

to฀have฀a฀close฀similarity,฀

understand฀human฀intelligence,฀but฀AI฀does฀not฀have฀to฀confine฀itself฀to฀methods฀

connection฀or฀causal฀

that฀are฀biologically฀observable.฀

relationship฀with฀

Q.฀Yes,฀but฀what฀is฀intelligence?฀ A.฀Intelligence฀is฀the฀computational฀part฀of฀the฀ability฀to฀achieve฀goals฀in฀the฀world.฀ Varying฀kinds฀and฀degrees฀of฀intelligence฀occur฀in฀people,฀many฀animals฀and฀some฀ machines.฀ Q.฀Isn’t฀there฀a฀solid฀definition฀of฀intelligence฀that฀doesn’t฀depend฀on฀relating฀it฀ to฀human฀intelligence?฀ A.฀Not฀yet.฀The฀problem฀is฀that฀we฀cannot฀yet฀characterize฀in฀general฀what฀kinds฀of฀ computational฀ procedures฀ we฀ want฀ to฀ call฀ intelligent.฀ We฀ understand฀ some฀ of฀ the฀ mechanisms฀of฀intelligence฀and฀not฀others.฀ Q.฀Is฀intelligence฀a฀single฀thing฀so฀that฀one฀can฀ask฀a฀yes฀or฀no฀question฀Is฀this฀ machine฀intelligent฀or฀not?฀ A.฀ No.฀ Intelligence฀ involves฀ mechanisms,฀ and฀ AI฀ research฀ has฀ discovered฀ how฀ to฀ make฀ computers฀ carry฀ out฀ some฀ of฀ them฀ and฀ not฀ others.฀ If฀ doing฀ a฀ task฀ requires฀ only฀mechanisms฀that฀are฀well฀understood฀today,฀computer฀programs฀can฀give฀very฀ impressive฀performances฀on฀these฀tasks.฀Such฀programs฀should฀be฀considered฀somewhat฀intelligent.฀ Q.฀Isn’t฀AI฀about฀simulating฀human฀intelligence?฀ A.฀Sometimes฀but฀not฀always฀or฀even฀usually.฀On฀the฀one฀hand,฀we฀can฀learn฀something฀฀ about฀how฀to฀make฀machines฀solve฀problems฀by฀observing฀other฀people฀or฀just฀by฀฀ observing฀our฀own฀methods.฀On฀the฀other฀hand,฀most฀work฀in฀AI฀involves฀studying฀the฀ problems฀the฀world฀presents฀to฀intelligence฀rather฀than฀studying฀people฀or฀animals.฀฀ AI฀researchers฀are฀free฀to฀use฀methods฀that฀are฀not฀observed฀in฀people฀or฀that฀involve฀ much฀more฀computing฀than฀people฀can฀do.฀ Q.฀What฀about฀IQ?฀Do฀computer฀programs฀have฀IQs?฀ A.฀No.฀IQ฀is฀based฀on฀the฀rates฀at฀which฀intelligence฀develops฀in฀children.฀It฀is฀the฀ ratio฀of฀the฀age฀at฀which฀a฀child฀normally฀makes฀a฀certain฀score฀to฀the฀child’s฀age.฀

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English++ The฀ scale฀ is฀ extended฀ to฀ adults฀ in฀ a฀ suitable฀ way.฀ IQ฀ correlates฀ well฀ with฀ various฀ measures฀of฀success฀or฀failure฀in฀life,฀but฀making฀computers฀that฀can฀score฀high฀on฀ IQ฀tests฀would฀be฀weakly฀correlated฀with฀their฀usefulness.฀For฀example,฀the฀ability฀of฀ a฀child฀to฀repeat฀back฀a฀long฀sequence฀of฀digits฀correlates฀well฀with฀other฀intellectual฀ abilities,฀perhaps฀because฀it฀measures฀how฀much฀information฀the฀child฀can฀compute฀ with฀ at฀ once.฀ However,฀ digit฀ span฀ is฀ trivial฀ for฀ even฀ extremely฀ limited฀ computers.฀ However,฀some฀of฀the฀problems฀on฀IQ฀tests฀are฀useful฀challenges฀for฀AI.฀ Q.฀What฀about฀other฀comparisons฀between฀human฀and฀computer฀intelligence?฀ Arthur฀ R.฀ Jensen฀ [Jen98],฀ a฀ leading฀ researcher฀ in฀ human฀ intelligence,฀ suggests฀ as฀ a฀฀ heuristic฀hypothesis฀that฀all฀normal฀humans฀have฀the฀same฀intellectual฀mechanisms฀and฀ that฀differences฀in฀intelligence฀are฀related฀to฀quantitative฀biochemical฀and฀physiological฀ conditions.฀I฀see฀them฀as฀speed,฀short฀term฀memory,฀and฀the฀ability฀to฀form฀accurate฀ and฀retrievable฀long฀term฀memories.฀Whether฀or฀not฀Jensen฀is฀right฀about฀human฀intelligence,฀the฀situation฀in฀AI฀today฀is฀the฀reverse.฀Computer฀programs฀have฀plenty฀of฀speed฀ and฀memory฀but฀their฀abilities฀correspond฀to฀the฀intellectual฀mechanisms฀that฀program฀฀ designers฀ understand฀ well฀ enough฀ to฀ put฀ in฀ programs.฀ Some฀ abilities฀ that฀ children฀฀ normally฀don’t฀develop฀till฀they฀are฀teenagers฀may฀be฀in,฀and฀some฀abilities฀possessed฀by฀ two฀year฀olds฀are฀still฀out.฀The฀matter฀is฀further฀complicated฀by฀the฀fact฀that฀the฀cognitive฀฀ sciences฀still฀have฀not฀succeeded฀in฀determining฀exactly฀what฀the฀human฀abilities฀are.฀Very฀ likely฀the฀organization฀of฀the฀intellectual฀mechanisms฀for฀AI฀can฀usefully฀be฀different฀฀ from฀ that฀ in฀ people.฀ Whenever฀ people฀ do฀ better฀ than฀ computers฀ on฀ some฀ task฀ or฀฀ computers฀use฀a฀lot฀of฀computation฀to฀do฀as฀well฀as฀people,฀this฀demonstrates฀that฀the฀฀ program฀designers฀lack฀understanding฀of฀the฀intellectual฀mechanisms฀required฀to฀do฀the฀task฀฀ efficiently.฀ Q.฀When฀did฀AI฀research฀start?฀ heuristic฀hypothesis

A.฀ After฀ WW฀ II,฀ a฀ number฀ of฀ people฀ independently฀ started฀ to฀ work฀ on฀ intelligent฀

a฀hypothesis฀that฀

machines.฀The฀English฀mathematician฀Alan฀Turing฀may฀have฀been฀the฀first.฀He฀gave฀

has฀a฀very฀high฀probability฀

a฀lecture฀on฀it฀in฀1947.฀He฀also฀may฀have฀been฀the฀first฀to฀decide฀that฀AI฀was฀best฀

of฀being฀true฀

researched฀by฀programming฀computers฀rather฀than฀by฀building฀machines.฀By฀the฀late฀

on฀the฀basis฀of฀reasoning฀

1950s,฀there฀were฀many฀researchers฀on฀AI,฀and฀most฀of฀them฀were฀basing฀their฀work฀

and฀past฀experience

on฀programming฀computers.฀ Q.฀Does฀AI฀aim฀to฀put฀the฀human฀mind฀into฀the฀computer?฀ A.฀Some฀researchers฀say฀they฀have฀that฀objective,฀but฀maybe฀they฀are฀using฀the฀phrase฀ metaphorically.฀The฀human฀mind฀has฀a฀lot฀of฀peculiarities,฀and฀I’m฀not฀sure฀anyone฀ is฀serious฀about฀imitating฀all฀of฀them.฀

168

English++ Q.฀What฀is฀the฀Turing฀test?฀ A.฀ Alan฀ Turing’s฀ 1950฀ article฀ Computing฀ Machinery฀ and฀ Intelligence฀ [Tur50]฀฀ discussed฀conditions฀for฀considering฀a฀machine฀to฀be฀intelligent.฀He฀argued฀that฀if฀the฀ machine฀could฀successfully฀pretend฀to฀be฀human฀to฀a฀knowledgeable฀observer฀then฀ you฀certainly฀should฀consider฀it฀intelligent.฀This฀test฀would฀satisfy฀most฀people฀but฀ not฀all฀philosophers.฀The฀observer฀could฀interact฀with฀the฀machine฀and฀a฀human฀by฀ teletype฀(to฀avoid฀requiring฀that฀the฀machine฀imitate฀the฀appearance฀or฀voice฀of฀the฀ person),฀and฀the฀human฀would฀try฀to฀persuade฀the฀observer฀that฀it฀was฀human฀and฀ the฀machine฀would฀try฀to฀fool฀the฀observer.฀ The฀Turing฀test฀is฀a฀one-sided฀test.฀A฀machine฀that฀passes฀the฀test฀should฀certainly฀

computational฀complexity฀

be฀considered฀intelligent,฀but฀a฀machine฀could฀still฀be฀considered฀intelligent฀without฀฀

฀an฀area฀of฀

knowing฀ enough฀ about฀ humans฀ to฀ imitate฀ a฀ human.฀ Daniel฀ Dennett’s฀ book฀฀

computer฀design฀

Brainchildren฀[Den98]฀has฀an฀excellent฀discussion฀of฀the฀Turing฀test฀and฀the฀various฀

dealing฀with฀the฀problems฀

partial฀Turing฀tests฀that฀have฀been฀implemented,฀i.e.฀with฀restrictions฀on฀the฀observer’s฀฀

of฀algorithms฀

knowledge฀of฀AI฀and฀the฀subject฀matter฀of฀questioning.฀It฀turns฀out฀that฀some฀people฀

and฀their฀ability฀

are฀easily฀led฀into฀believing฀that฀a฀rather฀dumb฀program฀is฀intelligent.฀

to฀solve฀a฀given฀problem฀

Q.฀Does฀AI฀aim฀at฀human-level฀intelligence?฀ A.฀Yes.฀The฀ultimate฀effort฀is฀to฀make฀computer฀programs฀that฀can฀solve฀problems฀ and฀achieve฀goals฀in฀the฀world฀as฀well฀as฀humans.฀However,฀many฀people฀involved฀in฀ particular฀research฀areas฀are฀much฀less฀ambitious.฀ Q.฀How฀far฀is฀AI฀from฀reaching฀human-level฀intelligence?฀When฀will฀it฀happen?฀ A.฀A฀few฀people฀think฀that฀human-level฀intelligence฀can฀be฀achieved฀by฀writing฀large฀ numbers฀of฀programs฀of฀the฀kind฀people฀are฀now฀writing฀and฀assembling฀vast฀knowledge฀ bases฀of฀facts฀in฀the฀languages฀now฀used฀for฀expressing฀knowledge.฀However,฀most฀AI฀ researchers฀believe฀that฀new฀fundamental฀ideas฀are฀required,฀and฀therefore฀it฀cannot฀ be฀predicted฀when฀human-level฀intelligence฀will฀be฀achieved.฀ Q.฀Are฀computers฀the฀right฀kind฀of฀machine฀to฀be฀made฀intelligent?฀ A.฀Computers฀can฀be฀programmed฀to฀simulate฀any฀kind฀of฀machine.฀Many฀researchers฀฀ invented฀non-computer฀machines,฀hoping฀that฀they฀would฀be฀intelligent฀in฀different฀ ways฀ than฀ the฀ computer฀ programs฀ could฀ be.฀ However,฀ they฀ usually฀ simulate฀ their฀ invented฀machines฀on฀a฀computer฀and฀come฀to฀doubt฀that฀the฀new฀machine฀is฀worth฀ building.฀Because฀many฀billions฀of฀dollars฀have฀been฀spent฀in฀making฀computers฀faster฀฀ and฀faster,฀another฀kind฀of฀machine฀would฀have฀to฀be฀very฀fast฀to฀perform฀better฀than฀ a฀program฀on฀a฀computer฀simulating฀the฀machine.฀

169

English++ Q.฀Are฀computers฀fast฀enough฀to฀be฀intelligent?฀ A.฀Some฀people฀think฀much฀faster฀computers฀are฀required฀as฀well฀as฀new฀ideas.฀My฀ own฀opinion฀is฀that฀the฀computers฀of฀30฀years฀ago฀were฀fast฀enough฀if฀only฀we฀knew฀ how฀to฀program฀them.฀Of฀course,฀quite฀apart฀from฀the฀ambitions฀of฀AI฀researchers,฀ computers฀will฀keep฀getting฀faster.฀ Q.฀What฀about฀parallel฀machines?฀ A.฀ Machines฀ with฀ many฀ processors฀ are฀ much฀ faster฀ than฀ single฀ processors฀ can฀ be.฀฀ Parallelism฀itself฀presents฀no฀advantages,฀and฀parallel฀machines฀are฀somewhat฀awkward฀ to฀program.฀When฀extreme฀speed฀is฀required,฀it฀is฀necessary฀to฀face฀this฀awkwardness.฀ Q.฀ What฀ about฀ making฀ a฀ child฀ machine฀ that฀ could฀ improve฀ by฀ reading฀ and฀ by฀ learning฀from฀experience?฀ cognitive฀science฀

A.฀This฀idea฀has฀been฀proposed฀many฀times,฀starting฀in฀the฀1940s.฀Eventually,฀it฀will฀

the฀scientific฀study฀

be฀made฀to฀work.฀However,฀AI฀programs฀haven’t฀yet฀reached฀the฀level฀of฀being฀able฀to฀

of฀mind฀or฀intelligence฀

learn฀much฀of฀what฀a฀child฀learns฀from฀physical฀experience.฀Nor฀do฀present฀programs฀

based฀on฀ relevant฀fields,฀ including฀psychology,฀ philosophy,฀neuroscience,฀ linguistics,฀ anthropology,฀ computer฀science,฀ and฀biology

understand฀language฀well฀enough฀to฀learn฀much฀by฀reading.฀ Q.฀ Might฀ an฀ AI฀ system฀ be฀ able฀ to฀ bootstrap฀ itself฀ to฀ higher฀ and฀ higher฀ level฀฀ intelligence฀by฀thinking฀about฀AI?฀ A.฀I฀think฀yes,฀but฀we฀aren’t฀yet฀at฀a฀level฀of฀AI฀at฀which฀this฀process฀can฀begin.฀ Q.฀What฀about฀chess?฀ A.฀ Alexander฀ Kronrod,฀a฀ Russian฀ AI฀ researcher,฀ said฀Chess฀ is฀the฀ Drosophila฀of฀ AI.฀ He฀was฀making฀an฀analogy฀with฀geneticists’฀use฀of฀that฀fruit฀fly฀to฀study฀inheritance.฀฀ Playing฀chess฀requires฀certain฀intellectual฀mechanisms฀and฀not฀others.฀Chess฀programs฀฀ now฀play฀at฀grandmaster฀level,฀but฀they฀do฀it฀with฀limited฀intellectual฀mechanisms฀ compared฀ to฀ those฀ used฀ by฀ a฀ human฀ chess฀ player,฀ substituting฀ large฀ amounts฀ of฀฀ computation฀for฀understanding.฀Once฀we฀understand฀these฀mechanisms฀better,฀we฀can฀ build฀human-level฀chess฀programs฀that฀do฀far฀less฀computation฀than฀do฀present฀programs.฀Unfortunately,฀the฀competitive฀and฀commercial฀aspects฀of฀making฀computers฀฀ play฀chess฀have฀taken฀precedence฀over฀using฀chess฀as฀a฀scientific฀domain.฀It฀is฀as฀if฀ the฀geneticists฀after฀1910฀had฀organized฀fruit฀fly฀races฀and฀concentrated฀their฀efforts฀ on฀breeding฀fruit฀flies฀that฀could฀win฀these฀races.฀ Q.฀What฀about฀Go?฀ A.฀The฀Chinese฀and฀Japanese฀game฀of฀Go฀is฀also฀a฀board฀game฀in฀which฀the฀players฀ take฀ turns฀ moving.฀ Go฀ exposes฀ the฀ weakness฀ of฀ our฀ present฀ understanding฀ of฀ the฀

170

intellectual฀mechanisms฀involved฀in฀human฀game฀playing.฀Go฀programs฀are฀very฀bad฀ players,฀in฀spite฀of฀considerable฀effort฀(not฀as฀much฀as฀for฀chess).฀The฀problem฀seems฀

English++ to฀be฀that฀a฀position฀in฀Go฀has฀to฀be฀divided฀mentally฀into฀a฀collection฀of฀sub-positions฀฀ which฀ are฀ first฀ analyzed฀ separately฀ followed฀ by฀ an฀ analysis฀ of฀ their฀ interaction.฀฀ Humans฀use฀this฀in฀chess฀also,฀but฀chess฀programs฀consider฀the฀position฀as฀a฀whole.฀ Chess฀ programs฀ compensate฀ for฀ the฀ lack฀ of฀ this฀ intellectual฀ mechanism฀ by฀ doing฀ thousands฀or,฀in฀the฀case฀of฀Deep฀Blue,฀many฀millions฀of฀times฀as฀much฀computation.฀ Sooner฀or฀later,฀AI฀research฀will฀overcome฀this฀scandalous฀weakness.฀ Q.฀Don’t฀some฀people฀say฀that฀AI฀is฀a฀bad฀idea?฀ A.฀ The฀ philosopher฀ John฀ Searle฀ says฀ that฀ the฀ idea฀ of฀ a฀ non-biological฀ machine฀ be-

confine฀

ing฀intelligent฀is฀incoherent.฀He฀proposes฀the฀Chinese฀room฀argument฀www-formal.฀

to฀define฀boundaries;฀

stanford.edu/jmc/chinese.html฀ The฀ philosopher฀ Hubert฀ Dreyfus฀ says฀ that฀ AI฀ is฀฀

to฀limit฀the฀extent฀

impossible.฀ The฀ computer฀ scientist฀ Joseph฀ Weizenbaum฀ says฀ the฀ idea฀ is฀ obscene,฀

(of฀an฀activity)

anti-human฀and฀immoral.฀Various฀people฀have฀said฀that฀since฀artificial฀intelligence฀ hasn’t฀ reached฀ human฀ level฀ by฀ now,฀ it฀ must฀ be฀ impossible.฀ Still฀ other฀ people฀ are฀฀ disappointed฀that฀companies฀they฀invested฀in฀went฀bankrupt.฀ Q.฀ Aren’t฀ computability฀ theory฀ and฀ computational฀ complexity฀ the฀ keys฀ to฀ AI?฀ [Note฀to฀the฀layman฀and฀beginners฀in฀computer฀science:฀These฀are฀quite฀technical฀ branches฀of฀mathematical฀logic฀and฀computer฀science,฀and฀the฀answer฀to฀the฀question฀

computational฀ 1.฀involving฀computers฀ 2.฀that฀can฀be฀computed฀

has฀to฀be฀somewhat฀technical.]฀ A.฀No.฀These฀theories฀are฀relevant฀but฀don’t฀address฀the฀fundamental฀problems฀of฀ AI.฀In฀the฀1930s฀mathematical฀logicians,฀especially฀Kurt฀Gödel฀and฀Alan฀Turing,฀established฀that฀there฀did฀not฀exist฀algorithms฀that฀were฀guaranteed฀to฀solve฀all฀problems฀ in฀certain฀important฀mathematical฀domains.฀Whether฀a฀sentence฀of฀first฀order฀logic฀ is฀a฀theorem฀is฀one฀example,฀and฀whether฀a฀polynomial฀equation฀in฀several฀variables฀ has฀integer฀solutions฀is฀another.฀Humans฀solve฀problems฀in฀these฀domains฀all฀the฀ time,฀and฀this฀has฀been฀offered฀as฀an฀argument฀(usually฀with฀some฀decorations)฀that฀ computers฀are฀intrinsically฀incapable฀of฀doing฀what฀people฀do.฀Roger฀Penrose฀claims฀ this.฀However,฀people฀can’t฀guarantee฀to฀solve฀arbitrary฀problems฀in฀these฀domains฀ either.฀See฀my฀Review฀of฀The฀Emperor’s฀New฀Mind฀by฀Roger฀Penrose.฀More฀essays฀ and฀reviews฀defending฀AI฀research฀are฀in฀my฀book฀Concepts฀of฀Logical฀AI฀[McC96a].฀ In฀the฀1960s฀computer฀scientists,฀especially฀Steve฀Cook฀and฀Richard฀Karp฀developed฀ the฀theory฀of฀NP-complete฀problem฀domains.฀Problems฀in฀these฀domains฀are฀solvable,฀฀ but฀seem฀to฀take฀time฀exponential฀in฀the฀size฀of฀the฀problem.฀Which฀sentences฀of฀ propositional฀calculus฀are฀satisfiable฀is฀a฀basic฀example฀of฀an฀NP-complete฀problem฀฀ domain.฀Humans฀often฀solve฀problems฀in฀NP-complete฀domains฀in฀times฀much฀shorter฀฀ than฀is฀guaranteed฀by฀the฀general฀algorithms,฀but฀can’t฀solve฀them฀quickly฀in฀general.฀ What฀is฀important฀for฀AI฀is฀to฀have฀algorithms฀as฀capable฀as฀people฀at฀solving฀problems.฀ The฀identification฀of฀subdomains฀for฀which฀good฀algorithms฀exist฀is฀important,฀but฀a฀

171

English++ lot฀of฀AI฀problem฀solvers฀are฀not฀associated฀with฀readily฀identified฀subdomains.฀ incoherent

The฀ theory฀ of฀ the฀ difficulty฀ of฀ general฀ classes฀ of฀ problems฀ is฀ called฀ computational฀

confused฀

complexity.฀So฀far฀this฀theory฀hasn’t฀interacted฀with฀AI฀as฀much฀as฀might฀have฀been฀

and฀inconsistent;฀illogical฀

hoped.฀Success฀in฀problem฀solving฀by฀humans฀and฀by฀AI฀programs฀seems฀to฀rely฀on฀ properties฀of฀problems฀and฀problem฀solving฀methods฀that฀the฀neither฀the฀complexity฀ researchers฀nor฀the฀AI฀community฀have฀been฀able฀to฀identify฀precisely.฀Algorithmic฀complexity฀theory฀as฀developed฀by฀Solomonoff,฀Kolmogorov฀and฀Chaitin฀(independently฀฀ of฀one฀another)฀is฀also฀relevant.฀It฀defines฀the฀complexity฀of฀a฀symbolic฀object฀as฀the฀ length฀of฀the฀shortest฀program฀that฀will฀generate฀it.฀Proving฀that฀a฀candidate฀program฀ is฀ the฀ shortest฀ or฀ close฀ to฀ the฀ shortest฀ is฀ an฀ unsolvable฀ problem,฀ but฀ representing฀ objects฀by฀short฀programs฀that฀generate฀them฀should฀sometimes฀be฀illuminating฀even฀ when฀you฀can’t฀prove฀that฀the฀program฀is฀the฀shortest.฀฀

172

English++

Exercises Pre-listening questions 1.฀ How฀would฀you฀define฀“intelligence”?฀ 2.฀ Have฀you฀ever฀thought฀of฀computer฀programs฀as฀being฀“intelligent”?฀ 3.฀ Do฀you฀think฀that฀computers฀or฀machines฀will฀ever฀be฀as฀intelligent฀as฀humans?฀ 4.฀ Are฀ you฀ afraid฀ of฀ the฀ nightmare฀ scenario฀ in฀ which฀ machines฀ have฀ control฀ over฀ people,฀possibly฀leading฀to฀the฀annihilation฀of฀the฀human฀race?฀ •฀Note฀taking฀exercises. ฀฀฀Listen฀to฀the฀recording฀and฀answer฀the฀following฀questions: 1.฀ What฀does฀human฀intelligence฀depend฀on?฀ •฀ “Arthur฀R.฀Jensen,฀a฀leading฀researcher฀in฀human฀intelligence,฀suggests฀as฀a฀heuristic฀ hypothesis฀that฀all฀normal฀humans฀have฀the฀same฀intellectual฀mechanisms฀and฀that฀ differences฀in฀intelligence฀are฀related฀to฀quantitative฀biochemical฀and฀physiological฀ conditions.฀I฀see฀them฀as฀speed,฀short฀term฀memory,฀and฀the฀ability฀to฀form฀accurate฀ and฀retrievable฀long฀term฀memories.”฀ 2.฀ What฀is฀the฀main฀advantage฀of฀computers฀over฀people฀and฀vice฀versa?฀ •฀ computation฀power฀(computer)฀ •฀ abstract฀thinking฀(human) 3.฀ What฀is฀the฀main฀aim฀of฀the฀Turing฀test?฀ •฀ “Alan฀ Turing’s฀ 1950฀ article฀ Computing฀ Machinery฀ and฀ Intelligence฀ [Tur50]฀฀ discussed฀conditions฀for฀considering฀a฀machine฀to฀be฀intelligent.฀He฀argued฀that฀if฀ the฀machine฀could฀successfully฀pretend฀to฀be฀human฀to฀a฀knowledgeable฀observer฀ then฀you฀certainly฀should฀consider฀it฀intelligent.฀This฀test฀would฀satisfy฀most฀people฀฀ but฀ not฀ all฀ philosophers.฀ The฀ observer฀ could฀ interact฀ with฀ the฀ machine฀ and฀ a฀ human฀by฀teletype฀(to฀avoid฀requiring฀that฀the฀machine฀imitate฀the฀appearance฀ or฀voice฀of฀the฀person),฀and฀the฀human฀would฀try฀to฀persuade฀the฀observer฀that฀ it฀was฀human฀and฀the฀machine฀would฀try฀to฀fool฀the฀observer.฀The฀Turing฀test฀is฀ a฀one-sided฀test.฀A฀machine฀that฀passes฀the฀test฀should฀certainly฀be฀considered฀ intelligent,฀but฀a฀machine฀could฀still฀be฀considered฀intelligent฀without฀knowing฀ enough฀about฀humans฀to฀imitate฀a฀human.” 4.฀ ฀In฀what฀ways฀have฀researchers฀tried฀to฀build฀an฀AI฀system฀similar฀to฀human฀฀ intelligence?฀ •฀ “A฀few฀people฀think฀that฀human-level฀intelligence฀can฀be฀achieved฀by฀writing฀large฀฀ numbers฀of฀programs฀of฀the฀kind฀people฀are฀now฀writing฀and฀assembling฀vast฀knowledge฀฀ bases฀of฀facts฀in฀the฀languages฀now฀used฀for฀expressing฀knowledge.฀However,฀most฀ AI฀researchers฀believe฀that฀new฀fundamental฀ideas฀are฀required,฀and฀therefore฀it฀ cannot฀be฀predicted฀when฀human-level฀intelligence฀will฀be฀achieved.”฀

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English++ The฀same฀questions฀can฀be฀asked฀฀when฀the฀text฀is฀used฀for฀a฀reading฀exercise.

Possible topics for discussion 1.฀ How฀has฀AI฀been฀depicted฀in฀books฀and฀films?฀(s-f) 2.฀ Is฀AI฀an฀ethical฀or฀moral฀issue?฀(ethical) 3.฀ What฀effect฀could฀AI฀have฀on฀religion?฀ 4.฀ Do฀ you฀ think฀ machines฀ with฀ AI฀ could฀ ever฀ be฀ programmed฀ to฀ have฀ religious฀฀ consciousness฀or฀religious฀feelings?฀

Reading suggestions Artificial฀ Intelligence฀ by฀ Patrick฀ Henry฀ Winston,฀ 2003,฀ Addison฀ Wesley฀ Publishing฀ Company.฀

Possible difﬁculties Although฀in฀this฀interview฀the฀questions฀are฀basic,฀the฀answers฀are฀quite฀dense฀and฀ formal.฀

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Agile Software Development from IT Conversation

Running฀time฀

5’36

Computer฀science฀content฀

Medium

Business฀content฀

฀Medium

English฀language฀complexity฀

Medium

Learning objectives •฀ to฀become฀familiar฀with฀certain฀characteristics฀of฀Agile฀methodology฀in฀comparison฀ with฀others฀used฀in฀the฀software฀development฀process •฀ to฀ ฀ understand฀ ฀ how฀ the฀ introduction฀ of฀ Agile฀ methodology฀ can฀ influence฀ a฀฀ company’s฀work฀

Sub-areas covered •฀ Software฀development •฀ Agile฀Methodology

Keywords •฀ software฀-฀programs฀which฀run฀on฀a฀computer฀ •฀ Agile฀Software฀Development฀-฀a฀conceptual฀framework฀for฀software฀development฀ which฀promotes฀development฀iterations฀throughout฀the฀life-cycle฀of฀the฀project฀ •฀ software฀development฀process฀-฀a฀structure฀imposed฀on฀the฀development฀of฀a฀ software฀ product.฀ Synonyms฀ include฀ software฀ life฀ cycle฀ and฀ software฀ process.฀ There฀are฀several฀models฀for฀such฀processes,฀each฀describing฀approaches฀to฀a฀variety฀of฀tasks฀or฀activities฀which฀take฀place฀during฀the฀process.฀ •฀ pair฀programming฀-฀a฀software฀development฀technique฀in฀which฀two฀programmers฀ work฀together฀at฀one฀keyboard.฀One฀types฀in฀code฀while฀the฀other฀reviews฀each฀ line฀of฀code฀as฀it฀is฀typed฀in.฀The฀person฀typing฀is฀called฀the฀driver.฀The฀person฀฀ reviewing฀ the฀ code฀ is฀ called฀ the฀ observer฀ or฀ navigator.฀ The฀ two฀ programmers฀ switch฀roles฀frequently.฀ •฀ contract฀-฀a฀legally฀binding฀exchange฀of฀promises฀or฀agreement฀between฀parties฀ which฀is฀enforceable฀by฀law฀ •฀ software฀documentation฀(or฀source฀code฀documentation)฀-฀written฀text฀which฀ accompanies฀computer฀software.฀It฀explains฀either฀how฀it฀operates฀or฀how฀to฀use฀ it,฀and฀may฀mean฀different฀things฀to฀people฀in฀different฀roles.

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Pre-listening questions 1.฀ How฀do฀you฀start฀your฀software฀projects?฀Do฀you฀have฀a฀plan฀or฀do฀you฀simply฀ start฀coding?฀ 2.฀ Do฀you฀know฀any฀software฀development฀methodologies?฀Describe฀them.฀ 3.฀ How฀would฀you฀imagine฀collaborating฀with฀customers฀in฀software฀projects?฀

Summary This฀ recording฀ is฀ ฀ part฀ of฀ an฀ interview฀ with฀ Alistair฀ Cockburn฀ conducted฀ by฀ Doug฀ Kaye.฀ Alistair฀ Cockburn฀ talks฀ about฀ the฀ main฀ characteristics฀ of฀ Agile฀ methodology฀ used฀ in฀ ฀ ฀ software฀ development.฀ He฀ also฀ points฀ out฀ the฀ differences฀ between฀ this฀ methodology฀and฀others฀utilized฀in฀software฀production.฀Being฀an฀expert฀in฀designing฀ with฀Agile฀methodology,฀he฀suggests฀some฀practices฀he฀has฀developed฀himself.฀

Audio clip I In฀this฀clip฀Alistair฀Cockburn฀emphasizes฀the฀importance฀of฀communication,฀cooperation฀฀ and฀ good฀ interaction฀ between฀ people฀ during฀ the฀ process฀ of฀ creating฀ a฀ project.฀ He฀฀ mentions฀tools฀supporting฀good฀communication฀and฀฀explains฀how฀to฀฀plan฀and฀design฀฀ projects฀using฀Agile฀methodology.

Audio clip II This฀concerns฀collaboration฀with฀customers฀and฀how฀to฀make฀contracts.฀

Audio clip III Alistair฀Cockburn฀฀explains฀how฀to฀make฀plans฀and฀be฀flexible฀about฀adjusting฀them฀ to฀changing฀situations฀during฀a฀project.฀

Audio clip IV This฀part฀of฀the฀interview฀discusses฀the฀importance฀of฀documentation฀in฀capturing฀the฀ intent฀of฀the฀developers.฀Alistair฀Cockburn฀mentions฀different฀forms฀of฀documentation฀฀ and฀gives฀the฀example฀of฀making฀video฀recordings฀of฀developers’฀discussions.฀ Nagranie฀ jest฀ fragmentem฀ wywiadu฀ z฀ Alistairem฀ Cockburnem฀ przeprowadzonym฀ przez฀Douga฀Kayea.฀Alistair฀Cockburn฀mówi฀o฀głównych฀cechach฀metodologii฀Agile฀฀ w฀zastosowaniach฀w฀rozwoju฀oprogramowania.฀Podkreśla฀tym฀samym฀różnice฀między฀ tą฀ metodologią฀ a฀ innymi,฀ znajdującymi฀ zastosowanie฀ w฀ wytwarzaniu฀ oprogramowania.฀ Jako฀ osoba฀ o฀ dużym฀ doświadczeniu฀ w฀ projektowaniu฀ z฀ wykorzystaniem฀ tej฀ metodologii,฀zaleca฀on฀również฀wypracowane฀przez฀siebie฀praktyki.฀

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English++ Fragment I W฀ tym฀ fragmencie฀ Alistair฀ Cockburn฀ podkreśla฀ znaczenie฀ komunikacji฀ i฀ kooperacji฀ pomiędzy฀ twórcami฀ projektu฀ i฀ podaje฀ przykłady฀ narzędzi฀ wspierających฀ dobrą฀ komunikację.฀Opowiada฀on฀także฀o฀sposobach฀planowania฀i฀projektowania฀w฀metodologii฀Agile.

Fragment II Fragment฀traktuje฀o฀współpracy฀z฀klientami฀i฀o฀sposobach฀zawierania฀umów.฀

Fragment III Alistair฀ Cockburn฀ mówi฀ o฀ sposobie฀ planowania฀ i฀ elastycznego฀ dostosowywania฀ planów฀do฀zmieniającej฀się฀sytuacji฀w฀czasie฀trwania฀projektu.฀

Fragment IV Ten฀fragment฀wywiadu฀traktuje฀o฀znaczeniu฀robienia฀dokumentacji฀w฀celu฀uchwycenia฀intencji฀twórców.฀Alistair฀Cockburn฀wymienia฀różne฀formy฀dokumentacji฀i฀podaje฀ przykład฀nagrania฀video฀dyskutujących฀programistów.฀

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English++ software programs฀which฀run฀ on฀a฀computer

Transcript

Audio clip I We฀value฀individuals฀and฀interactions฀over฀processes฀and฀tools.฀The฀idea฀there฀is,฀uh,฀

฀Agile

you฀know,฀it’s฀funny,฀if฀you฀look฀at฀the฀arguments฀in฀the฀Agile฀world,฀they’re฀all฀over฀

฀Software฀Development

process,฀the฀XP฀process,฀the฀Scrum฀process,฀the฀Crystal฀process,฀whatever.฀So฀we฀do฀talk฀

฀a฀conceptual฀framework฀

about฀process,฀and฀we฀cherry-pick฀our฀tools฀very฀carefully.฀And฀I฀just฀wrote฀an฀article฀฀

for฀software฀develop-

for฀ Crosstalk฀ Magazine฀ on฀ the฀ Agile฀ toolkit;฀ cherry-pick฀ them฀ very฀ carefully,฀ want฀

ment฀which฀promotes฀

them฀very฀pointed฀and฀very฀efficient฀with฀clearly฀demonstrated฀value฀and฀so฀on.฀But,฀

development฀iterations฀

when฀we฀get฀down฀to฀it,฀the฀heart฀of฀what฀makes฀a฀good฀project฀work฀is฀not฀just฀the฀

throughout฀

individual฀people฀that฀you฀have฀there,฀but฀the฀way฀in฀which฀they฀interact฀with฀each฀

the฀life-cycle฀of฀the฀project฀

other.฀So฀we฀highlight฀individuals’฀interactions฀and฀so฀we฀talk฀a฀lot฀about฀collocation,฀ collaboration.฀I฀talk฀a฀lot฀about฀morale,฀amicability,฀community.฀If฀you฀go฀to฀the฀toolset,฀฀

Software฀

now฀you฀want฀collaboration฀tools฀that฀allow฀multiple฀modes฀of฀communication,฀you฀

development฀process

want฀sound,฀you฀want฀video,฀you฀want฀archiving,฀you฀want฀online฀chat;฀you฀want฀

฀a฀structure฀imposed฀on฀

all฀of฀these฀things฀at฀the฀same฀time.฀So฀you’re฀watching฀it;฀there’s฀a฀lot฀of฀workshop-

the฀development฀

based฀activities฀in฀Agile฀Development.฀Planning฀is฀not฀done฀by฀the฀project฀manager฀

of฀a฀software฀product.฀

sitting฀alone฀in฀a฀room,฀but฀it’s฀is฀done฀by฀the฀entire฀group฀of฀people฀who,฀whether฀

Synonyms฀include฀

it’s฀coarse฀grain฀or฀fine฀grain,฀you’re฀looking฀at฀the฀set฀of฀things฀that฀need฀to฀be฀done฀

software฀life฀cycle฀

and฀jostling฀each฀other฀either฀to฀think฀of฀something฀new฀or฀to฀change฀their฀estimates฀

and฀software฀process.฀

or฀suggest฀solutions฀or฀something฀like฀that.฀That’s฀done฀in฀design,฀also.฀There’s฀pair฀

There฀are฀several฀

programming,฀ there’s฀ all฀ sorts฀ of฀ things,฀ but฀ the฀ emphasis฀ is฀ very,฀ very฀ strong฀ on฀฀

models฀for฀such฀ processes,฀each฀describing฀ approaches฀to฀a฀variety฀ of฀tasks฀or฀activities฀ which฀take฀place฀ during฀the฀process.฀

increasing,฀if฀you฀will,฀the฀brain-to-brain฀communication.

sound

Audio clip II Customer฀ collaboration฀ over฀ contract฀ negotiation.฀ So,฀ yeah,฀ there’s฀ a฀ place฀ for฀฀ contracts,฀ not฀ to฀ pretend฀ like฀ you฀ can’t฀ ever฀ do฀ contracts,฀ but฀ even฀ better฀ than฀ a฀฀ contract฀ is฀ if฀ everybody฀ gets฀ on฀ the฀ same฀ side฀ of฀ the฀ table฀ and฀ they฀ work฀ together.฀ So฀ this฀ idea฀ of฀ collaboration฀ not฀ just฀ within฀ the฀ team,฀ but฀ collaboration฀ across฀฀ organizational฀boundaries,฀in฀particular฀with฀the฀sponsors฀and฀end฀users,฀then฀you฀ can฀ actually฀ optimize,฀ for฀ instance,฀ the฀ requirements.฀ You฀ could฀ discover฀ that฀ the฀ requirements฀as฀written฀aren’t฀what฀the฀people฀really฀want.฀So฀now฀if฀you’re฀out฀here฀ in฀a฀contract฀situation,฀you฀have฀to฀talk฀about฀changing฀the฀contract.฀If฀you’re฀in฀a฀ customer-collaboration-system฀situation,฀you฀can฀work฀together฀and฀decide฀whether฀ to฀make฀a฀change฀in฀the฀requirements฀or฀not.฀That’s฀customer฀collaboration.

sound

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Audio clip III

pair฀programming฀

Responding฀to฀change฀over฀following฀a฀plan.฀So฀while฀we฀all฀agree฀that฀planning฀is฀a฀

a฀software฀development฀

useful฀activity,฀the฀plan฀rarely฀survives,฀sort฀of,฀฀three฀days฀into฀the฀project.฀It’s฀most฀

technique฀in฀which฀

of฀the฀time฀between฀three฀days฀and฀a฀week฀after฀the฀plan฀is฀built,฀it’s฀out฀of฀date,฀

two฀programmers฀

something’s฀happened.฀And฀so฀this฀responding-to-change฀idea฀is฀what฀I฀call฀paying฀

work฀together฀

attention฀to฀current฀reality.฀You฀come฀into฀the฀project฀one฀day฀–฀you฀know,฀whatever฀

at฀one฀keyboard.฀

you’re฀faced฀with,฀it฀could฀be฀anything฀-฀we฀don’t฀get฀hung฀up฀on,฀say:฀well,฀but฀the฀

One฀types฀in฀code฀

plan฀said฀something;฀we฀go,฀hmmm!฀Okay,฀so฀what’s฀the฀best฀thing฀to฀do฀now฀in฀the฀

while฀the฀other฀

current฀situation?฀Do฀we,฀in฀fact,฀follow฀the฀plan฀or฀do฀we฀change฀the฀plan,฀or฀what฀do฀

reviews฀each฀line฀of฀code฀

we฀do?฀So฀responding฀to฀change฀over฀following฀the฀plan฀actually฀has฀an฀implication฀

as฀it฀is฀typed฀in.฀

that฀we฀do฀a฀lot฀more฀planning,฀but฀we฀do฀it฀collaborative,฀quick฀and฀either฀typically฀

The฀person฀typing

short-time฀horizon,฀fine-grained฀and฀sometimes฀long-time฀horizon฀coarse-grained,฀if฀

฀is฀called฀the฀driver.฀

that฀makes฀sense฀to฀you

The฀person฀reviewing฀ the฀code฀is฀called฀the฀

sound

observer฀or฀navigator.฀ The฀two฀programmers฀

Audio clip IV

switch฀roles฀frequently.

Alistair฀ Cockburn:฀ And฀ ‘adequate’฀ now฀ becomes฀ the฀ question.฀ So฀ what฀ would฀ be฀ a฀ barely฀ sufficient฀ amount฀ of฀ documentation?฀ When฀ would฀ it฀ be฀ done?฀ What฀ would฀

฀

it฀look฀like฀to฀help฀the฀future฀people฀come฀on?฀That฀is฀a฀really฀tough฀question,฀it’s฀

Contract

a฀ really฀ ugly฀ one฀ and,฀ typically,฀ people฀ don’t฀ do฀ enough.฀ So฀ I’m฀ looking฀ for฀ really฀฀

a฀legally฀binding฀

inexpensive฀ways฀to฀do฀this,฀and฀I฀think฀white-board฀photos,฀videotapes฀of฀designers฀฀

exchange฀of฀promises฀

discussing฀at฀the฀white฀board,฀that฀kind฀of฀thing,฀may฀give฀us฀a฀handle฀on฀getting฀this.฀

or฀agreement between฀parties,฀

Doug฀Kaye:฀That฀also฀has฀the฀advantage฀that฀it฀captures฀the฀intent฀of฀the฀developers,฀

which฀is฀enforceable

which฀sometimes฀can฀be฀more฀valuable฀than฀the฀actual฀code.฀After฀all,฀the฀code฀is฀

by฀law฀

there.฀ Alistair฀Cockburn:฀Classically,฀classically฀impossible฀to฀catch.฀I฀don’t฀know฀how฀many฀

Software฀documentation฀

research฀projects฀I’ve฀seen฀where฀they฀have฀as฀an฀intent฀to฀find฀a฀way฀to฀capture฀that.฀

(or฀source฀code฀

But฀if฀you฀have,฀for฀instance,฀somebody฀from฀the฀team฀who’s฀got฀the฀software฀and฀

documentation)

somebody฀from฀a฀different฀team฀who฀doesn’t฀know฀the฀software,฀and฀they฀take฀some฀

written฀text฀which฀

aspect฀of฀the฀system฀and฀they฀go฀over฀the฀design฀for฀it,฀what’ll฀happen฀is฀the฀person฀

accompanies฀

who฀knows฀the฀design฀will฀say,฀“Well,฀basically฀it฀works฀like฀this”,฀and฀sketch฀some฀

computer฀software.฀

stuff฀ out.฀ And฀ then฀ the฀ other฀ person฀ will฀ interrupt฀ and฀ ask฀ questions,฀ “Well,฀ why฀

It฀explains฀either฀how฀it฀

not฀this,฀and฀why฀not฀that,฀and฀what฀about฀this,฀and฀what฀about฀that?”,฀just฀as฀the฀

operates฀or฀how฀to฀use฀it,฀

newcomer฀developer฀would฀want฀to฀ask,฀too.฀And฀then฀the฀conversation฀gets฀more฀

and฀may฀mean฀different฀

convoluted฀ and฀ complex฀ and฀ deeper฀ as฀ they฀ go.฀ And฀ if฀ you฀ have฀ that฀ all฀ on฀ video฀

things฀to฀people฀

tape,฀then฀in฀a฀sense฀you’ve฀got฀this฀very฀rich฀conversation฀into฀the฀future฀that฀you฀

in฀different฀roles.

can฀archive.฀

sound฀

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Exercises Pre-listening questions 1.฀ How฀do฀you฀start฀your฀software฀projects?฀Do฀you฀have฀a฀plan฀or฀do฀you฀simply฀ start฀coding?฀ 2.฀ Do฀you฀know฀any฀software฀development฀methodologies?฀Describe฀them.฀ 3.฀ How฀would฀you฀imagine฀collaborating฀with฀customers฀in฀software฀projects?฀

Comprehension questions Audio clip 1 1.฀ What฀is฀the฀basis฀of฀creating฀a฀good฀project?฀ ฀•฀ interaction,฀collaboration,฀morale,฀a฀sense฀of฀community 2.฀ How฀is฀the฀idea฀of฀interaction฀realized฀during: ฀

a.฀planning?฀(working฀as฀a฀group;฀brain฀storming,฀etc.)฀

฀

b.฀design?฀(pair฀programming)

3.฀ Which฀tools฀are฀used฀to฀help฀communication?฀ •฀ sound,฀video,฀archiving,฀online฀chat,฀etc.

Audio clip 2 4.฀ What฀does฀the฀idea฀of฀customer฀collaboration฀focus฀on? •฀ working฀out฀the฀contract฀in฀co-operation฀with฀customer

Audio clip 3 5.฀ ฀Is฀the฀plan฀for฀a฀project฀unchangeable?฀฀What฀happens฀if฀the฀situation฀during฀ a฀project฀changes?฀ •฀ no;฀there฀needs฀to฀be฀flexible฀adjustment฀to฀the฀situation฀and฀quick฀re-planning฀

Audio clip 4 6.฀ What฀are฀the฀different฀forms฀of฀฀documentation฀during฀a฀project?฀Give฀examples.฀ (white-board฀ photos,฀ videotapes฀ of฀ designers฀ discussing฀ at฀ the฀ white฀ board,฀traditional฀written฀documentation)฀ 7.฀ What฀is฀the฀main฀purpose฀of฀doing฀documentation? •฀ capturing฀the฀intentions฀of฀a฀developer

Possibile topics for discussion 1.฀ Is฀Agile฀software฀development฀always฀the฀best฀way฀to฀make฀software?฀ ฀

(advantages/disadvantages)฀

2.฀ One฀of฀the฀priorities฀in฀Agile฀is฀customer฀collaboration.฀How฀would฀you฀imagine฀this฀

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collaboration฀if฀you฀were฀developing฀software฀for฀billions฀of฀people฀around฀the฀globe?฀ 3.฀ How฀would฀you฀design฀the฀process฀of฀preparing฀documentation฀to฀make฀this฀less฀ time-consuming?฀

English++

Open News Episode 25 from A Weekly Open Source News Podcast Running฀time฀

4’05

Computer฀science฀content฀

High

Business฀content฀

Medium

English฀language฀complexity฀

Medium

Learning objectives •฀ to฀become฀familiar฀with฀the฀spectrum฀of฀Google’s฀business฀activity •฀ to฀understand฀the฀importance฀of฀copyright฀law฀and฀what฀may฀be฀the฀consequences฀ of฀breaking฀it฀

Sub-areas covered •฀ Operating฀systems •฀ Copyright฀law฀

Keywords •฀ software฀-฀programs฀run฀on฀a฀computer฀ •฀ Google฀-฀an฀American฀public฀corporation฀whose฀domain฀is฀open-source฀software฀฀ and฀whose฀earning฀revenue฀from฀advertising฀related฀to฀its฀Internet฀search,฀webbased฀ e-mail,฀ online฀ mapping,฀ office฀ productivity,฀ social฀ networking฀ and฀ video฀ sharing฀activities. •฀ desktop฀(computer)฀-฀a฀personal฀computer฀used฀at฀home฀or฀work฀(stationary)฀ •฀ bug฀-฀an฀error฀in฀software,฀something฀that฀interferes฀with฀the฀flow฀of฀the฀program฀ •฀ downloading฀ -฀ getting/transferring฀ files฀ (software,฀ music,฀ films,฀ etc.)฀ from฀ a฀฀ remote฀computer฀via฀the฀Internet฀ •฀ OS฀(Operating฀System)฀-฀a฀piece฀of฀software฀that฀is฀responsible฀for฀the฀management฀of฀a฀computer฀and,฀฀above฀all,฀running฀programs฀(examples:฀MS฀Windows,฀ Linux,฀Mac฀OS)฀ •฀ BitTorrent฀-฀a฀protocol฀for฀sharing฀and฀distributing฀computer฀files฀via฀the฀Internet฀

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English++

Summary Part 1 Goobuntu Conﬁrmed This฀audio฀clip฀is฀about฀the฀introduction฀of฀the฀operating฀system฀designed฀by฀Google฀ to฀the฀market.฀

Part 2 Windows As Punishment This฀audio฀clip฀tells฀the฀story฀of฀the฀man฀who฀was฀convicted฀of฀illegally฀downloading฀ a฀film฀via฀the฀Internet฀and฀then฀forced฀to฀use฀the฀MS฀Windows฀operating฀system฀as฀ part฀of฀his฀sentence.฀

Część 1 Goobuntu Conﬁrmed Treścią฀nagrania฀jest฀informacja฀o฀wprowadzanym฀na฀rynek฀przez฀firmę฀Google฀systemie฀operacyjnym.฀

Część 2 Windows As Punishment Nagranie฀ opowiada฀ historię฀ osoby,฀ która฀ będąc฀ oskarżoną฀ o฀ nielegalne฀ ฀ ściągnięcie฀ filmu฀przez฀Internet,฀฀została฀zmuszona฀do฀używania฀SO฀Windows,฀co฀było฀rezultatem฀ wyroku.

Pre-listening questions 1.฀What฀is฀the฀main฀area฀of฀Google’s฀business฀activity?฀ 2.฀Who฀are฀the฀main฀rivals฀of฀Microsoft’s฀Windows฀operating฀system?฀What฀makes฀ them฀ever฀more฀popular?฀

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English++ Transcript

software programs฀run฀on฀

Goobuntu Conﬁrmed There฀have฀been฀rumors฀floating฀around฀for฀years฀now฀that฀Google฀would฀release฀its฀

a฀computer฀

own฀desktop฀operating฀system฀to฀compete฀with฀Microsoft฀Windows.฀Well฀now฀the฀ existence฀of฀Google฀operating฀system฀has฀been฀confirmed.฀According฀to฀theregister. co.uk,฀ Google฀ is฀ preparing฀ its฀ own฀ distribution฀ of฀ Linux฀ for฀ the฀ desktop฀ in฀ a฀ possible฀bid฀to฀take฀on฀Microsoft฀in฀its฀core฀business฀-฀desktop฀software.฀A฀version฀of฀ the฀ increasingly฀ popular฀ Ubuntu฀ desktop฀ Linux฀ distribution,฀ based฀ on฀ Debian฀ and฀ the฀Gnome฀desktop,฀it฀is฀known฀internally฀as฀‘Goobuntu’.฀Google฀has฀confirmed฀it฀is฀ working฀on฀a฀desktop฀Linux฀project฀called฀Goobuntu,฀but฀declined฀to฀supply฀further฀ details,฀including฀what฀the฀project฀is฀for.฀It’s฀possible฀that฀it’s฀just฀one฀of฀the฀toys฀Googleplex฀engineers฀play฀with฀on฀Fridays,฀when฀they฀get฀time฀off฀from฀buffing฀the฀search฀ engine฀code฀or฀filtering฀out฀entries฀about฀Tiananmen฀Square.฀It฀could฀be฀for฀wider฀deployments฀on฀the฀company’s฀own฀desktops,฀as฀an฀alternative฀to฀Microsoft,฀but฀still฀for฀ internal฀use฀only.฀But฀it’s฀possible฀Google฀plans฀to฀distribute฀it฀to฀the฀general฀public,฀as฀a฀ free฀alternative฀to฀Windows.฀Google฀has฀already฀demonstrated฀an฀interest฀in฀building฀a฀ presence฀on฀the฀desktop.฀At฀CES฀Las฀Vegas฀last฀month,฀it฀announced฀the฀Google฀Pack,฀a฀ collection฀of฀desktop฀software฀bundled฀together฀for฀easy฀downloading.฀Whatever฀Google’s฀intentions,฀the฀input฀of฀Google฀engineers฀and฀developers,฀writing฀new฀features฀and฀ fixing฀bugs,฀will฀be฀a฀huge฀boost฀to฀the฀Ubuntu฀project.฀

Google an฀American฀public฀ corporation฀whose฀domain฀ is฀open-source฀software and฀whose฀earning฀ revenue฀from฀ advertising฀related฀ to฀its฀Internet฀search,฀ web-based฀e-mail,฀ online฀mapping,฀ office฀productivity,฀ social฀networking฀ and฀video฀sharing฀ activities.

sound

Windows As Punishment Many฀Linux฀users฀still฀use฀Microsoft฀Windows฀in฀one฀form฀or฀another.฀Some฀of฀us,฀ including฀myself,฀use฀Windows฀strictly฀for฀gaming.฀Others฀are฀forced฀to฀use฀Windows฀ at฀work.฀But฀what฀if฀you฀were฀legally฀required฀to฀use฀Windows฀and฀only฀Windows?฀ Well฀ that’s฀ what฀ happened฀ this฀ week,฀ according฀ to฀ vnunet.com.฀ An฀ article฀ by฀ Iain฀

desktop฀(computer) a฀personal฀computer฀ used฀at฀home฀or฀work฀ (stationary฀computer)฀

Thomson฀states:฀ A฀man฀convicted฀of฀illegally฀downloading฀an฀episode฀of฀Star฀Wars฀has฀been฀told฀that฀ he฀can฀no฀longer฀use฀his฀computer฀with฀an฀Ubuntu฀Linux฀operating฀system.฀Scott฀McCausland฀pleaded฀guilty฀last฀year฀to฀‘conspiracy฀to฀commit฀copyright฀infringement’฀

bug฀

and฀‘criminal฀copyright฀infringement’฀by฀downloading฀Star฀Wars:฀Episode฀III฀illegally.฀

an฀error฀in฀software,฀

He฀served฀five฀months฀in฀prison฀and฀is฀now฀on฀฀

something฀that฀

probation,฀but฀has฀been฀told฀that฀฀

he฀cannot฀use฀his฀Linux฀computer.฀ “I฀had฀a฀meeting฀with฀my฀probation฀officer฀today฀and฀he฀told฀me฀that฀he฀had฀to฀install฀

interferes฀with฀the฀flow฀ of฀the฀program฀

monitoring฀software฀on฀my฀PC.฀No฀big฀deal฀to฀me;฀that’s฀part฀of฀my฀sentence,”฀he฀ wrote฀on฀his฀Lost฀and฀Alone฀blog.฀“However,฀the฀monitoring฀software฀doesn’t฀support฀฀

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English++ downloading

Linux.฀So฀he฀told฀me฀that฀if฀I฀want฀to฀use฀a฀computer,฀I฀would฀have฀to฀use฀an฀OS฀that฀

getting/transferring฀files

the฀software฀can฀be฀installed฀on,฀which฀basically฀฀ means฀Microsoft฀and฀monitoring฀

(software,฀music,฀films,฀etc.)฀

software฀or฀no฀computer.฀I฀use฀Ubuntu฀7.04฀now,฀and฀they฀are฀trying฀to฀force฀me฀to฀

from฀a฀remote฀computer฀

switch.”฀

via฀the฀Internet฀ OS฀(Operating฀System) a฀piece฀of฀software฀ that฀is฀responsible฀

McCausland,฀also฀known฀as฀‘sk0t’,฀(or฀S-K-zero-T),฀was฀the฀first฀person฀to฀฀be฀jailed฀for฀ BitTorrent฀use฀and฀was฀a฀member฀of฀the฀Elitetorrents฀site฀that฀was฀shut฀down฀by฀the฀ FBI฀in฀2005.฀He฀claimed฀that฀he’s฀not฀trying฀to฀subvert฀restrictions฀placed฀on฀him,฀but฀ does฀not฀see฀why฀he฀should฀have฀to฀buy฀a฀whole฀฀ new฀฀operating฀system฀to฀do฀so.฀

for฀the฀management฀

“The฀terms฀of฀my฀plea฀state:฀‘I฀consent฀to฀periodic฀checks฀of฀my฀PC฀by฀my฀฀probation฀

of฀a฀computer฀and,฀฀

officer฀and/or฀the฀installation฀of฀software฀to฀monitor฀my฀internet฀activity,’”฀he฀wrote.฀

above฀all,฀

“I฀am฀consenting฀to฀all฀of฀it,฀but฀it฀just฀so฀happens฀that฀the฀OS฀I฀use฀might฀not฀be฀฀

running฀programs฀(examples:฀

supported฀ by฀ the฀ software฀ they฀ use฀ to฀ monitor.฀ So฀ I฀ do฀ not฀ feel฀ (neither฀ does฀ my฀฀

MS฀Windows,฀Linux,฀

lawyer)฀that฀the฀government฀can฀force฀me฀to฀switch฀OS.”฀

Mac฀OS)฀

McCausland฀ has฀ now฀ started฀ an฀ appeal฀ on฀ his฀ website฀ to฀ cover฀ the฀ cost฀ of฀ buying฀ Windows.฀

BitTorrent a฀protocol฀for฀sharing฀ and฀distributing฀ computer฀files via฀the฀Internet฀

184

sound

English++

Exercises Goobontu conﬁrmed Pre-listening questions 1.฀What฀is฀the฀main฀area฀of฀Google’s฀business฀activity?฀ •฀ development฀of฀the฀Internet฀search฀engine,฀web฀services฀such฀as฀Gmail,฀Google฀ News,฀ iGoogle฀ and฀ stand-alone฀ applications฀ like฀ Google฀ Earth,฀ Google฀ Desktop,฀ Hello,฀Picasa฀and฀so฀on฀ 2.฀Who฀are฀the฀main฀rivals฀of฀Microsoft’s฀Windows฀operating฀system?฀What฀makes฀ them฀ever฀more฀popular?฀ •฀ the฀main฀rivals฀are฀Unix-based฀systems฀and฀Mac฀OS฀-฀their฀growing฀popularity฀can฀ be฀attributed฀to฀their฀security฀and฀ease฀of฀use฀

Comprehension questions 1.฀฀What฀system฀is฀the฀Google฀OS฀based฀on?฀ •฀ It฀is฀based฀on฀Ubuntu฀Linux฀distribution.฀ 2.฀ What฀ does฀ the฀ speaker฀ imply฀ when฀ he฀ mentions฀ filtering฀ out฀ entries฀ about฀ Tiananmen฀Square?฀ •฀ He฀implies฀that฀Google฀agreed฀to฀blue-pencil฀the฀information฀about฀the฀tragedy฀in฀ Tiananmen฀Square฀when฀entering฀the฀Chinese฀market).฀ 3.฀Does฀Goobuntu฀present฀an฀immediate฀threat฀to฀the฀current฀popularity฀of฀the฀฀ Microsoft฀Windows฀operating฀system?฀ •฀ No,฀because฀this฀system฀[Goobuntu]฀is฀designed฀only฀for฀internal฀use฀within฀Google฀ and฀so฀far฀there฀is฀only฀a฀possibility฀that฀it฀will฀be฀distributed฀it฀to฀the฀general฀ public).฀ 4.฀Which฀product฀will฀enable฀Google฀to฀play฀a฀more฀important฀role฀in฀the฀desktop฀ applications฀market?฀ •฀ Google฀Pack,฀the฀collection฀of฀free,฀useful฀desktop฀applications฀

Possible topics for discussion 1.฀ What฀is฀the฀role฀of฀competition฀in฀the฀domestic฀and฀global฀market? 2.฀ Would฀Google’s฀operating฀system฀have฀a฀chance฀of฀winning฀a฀competition฀with฀฀ Windows?฀Discuss฀how฀Google฀could฀make฀this฀happen.฀

Windows as punishment Pre-listening questions 1.฀What฀are฀the฀means฀by฀which฀a฀government฀can฀protect฀copyright฀law฀on฀the฀฀ Internet?฀

185

English++ •฀ It฀can,฀for฀example,฀take฀away฀a฀person’s฀computer฀and฀search฀it฀for฀software฀or฀ files฀that฀the฀owner฀does฀not฀have฀the฀right฀to฀use.฀It฀can฀also฀install฀monitoring฀ software฀ on฀ someone’s฀ PC฀ or฀ monitor฀ Internet฀ traffic฀ in฀ a฀ specific฀ network฀ to฀ watch฀out฀for฀people฀downloading฀illegally.฀

Comprehension questions 1.What฀was฀Scott฀McCausland฀accused฀of?฀ •฀ he฀was฀accused฀of฀violating฀copyright฀law฀by฀downloading฀Star฀Wars฀Episode฀III฀ illegally.฀ 2.฀How฀long฀did฀McCausland฀spend฀in฀prison? •฀ five฀months.฀ 3.฀Why฀was฀McCausland฀forced฀to฀use฀the฀Microsoft฀Windows฀operating฀system?฀ •฀ he฀had฀to฀have฀monitoring฀software฀฀installed฀฀on฀his฀computer฀฀which฀was฀compatible฀only฀with฀Windows.฀ 4.฀What฀had฀Scott฀McCausland฀been฀accused฀of?฀ •฀ illegal฀BitTorrent฀use.฀

Possible topics for discussion 1.฀What฀is฀your฀opinion฀about฀the฀sentence฀that฀force฀people฀to฀buy฀something?฀฀ ฀

฀

186

฀

English++

Open News Episode 29 from A Weekly Open Source News Podcast

Running฀time฀

6’23

Computer฀science฀content฀

High

Business฀content฀

Medium

English฀language฀complexity฀

High

Learning objectives •฀ to฀become฀familiar฀with฀recent฀developments฀in฀open฀source฀software •฀ to฀understand฀the฀importance฀of฀patents฀for฀software •฀ to฀know฀how฀the฀OSI฀institute฀works฀in฀particular฀cases

Sub-areas covered •฀ News฀from฀the฀IT฀world •฀ Open฀source฀technologies.฀

Keywords •฀ Suse,฀Red฀Hat,฀Ubuntu฀-฀examples฀of฀linux฀distributions฀ •฀ SCO฀ -฀ a฀ software฀ company฀ formerly฀ called฀ Caldera฀ Systems฀ and฀ Caldera฀ Inter-฀ national.฀After฀acquiring฀the฀Santa฀Cruz฀Operation’s฀Server฀Software฀and฀Services฀฀ divisions,฀ as฀ well฀ as฀ UnixWare฀ and฀ OpenServer฀ technologies,฀ the฀ company฀ changed฀its฀focus฀to฀UNIX.฀Later฀on,฀Caldera฀changed฀its฀name฀to฀The฀SCO฀Group฀ to฀reflect฀that฀change฀in฀focus. •฀ user฀interface฀-฀the฀aggregate฀of฀means฀by฀which฀people,฀the฀users,฀interact฀with฀ the฀ system,฀ a฀ particular฀ machine,฀ device,฀ computer฀ program฀ or฀ other฀ complex฀ tools.฀The฀user฀interface฀provides฀means฀of฀input,฀allowing฀the฀users฀to฀manipulate฀a฀system฀and฀output,฀allowing฀the฀system฀to฀produce฀the฀effects฀of฀the฀users’฀ manipulation.฀ •฀ software฀license฀(UK฀spelling:฀licence)฀-฀there฀are฀several฀important฀IT฀licenses฀ like฀GNU฀GPL(open฀source),฀Mozilla฀Public฀License฀or฀Microsoft฀Public฀License฀ •฀ Firefox฀-฀one฀of฀the฀most฀popular฀web฀browsers฀(after฀Internet฀Explorer)฀ •฀ MPL฀-฀Microsoft฀Public฀Licence •฀ MRL฀-฀Microsoft฀Reciprocal฀Licence

187

English++

Summary This฀ is฀ a฀ podcast฀ with฀ interesting฀ news฀ from฀ the฀ open฀ source฀ community.฀ In฀ this฀ recording฀we฀hear฀about:฀ •฀ some฀recent฀developments฀in฀brief฀ •฀ Patents฀(the฀legal฀battle฀between฀MS฀and฀RedHat) •฀ Mozilla’s฀plans฀to฀develop฀a฀mobile฀browser฀ •฀ OSI’s฀approval฀of฀MS฀licenses

Jest฀to฀podcast฀z฀ciekawymi฀informacjami฀ze฀świata฀open฀source.฀W฀tym฀materiale฀ możemy฀usłyszeć฀kilka฀krótkich฀wiadomości:฀ •฀ patenty฀i฀wojna฀pomiędzy฀MS฀a฀RedHatem฀ •฀ Mozilla฀chce฀wyprodukować฀wersję฀przeglądarki฀na฀telefony฀komórkowe฀ •฀ OSI฀akceptuje฀licencje฀Microsoftu฀

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English++ Transcript

software฀license฀ (UK฀spelling:฀licence)฀

First,฀here฀are฀some฀news฀briefs.

there฀are฀several฀ important฀IT฀licenses฀

If฀ you’ve฀ been฀ wanting฀ to฀ learn฀ more฀ about฀ Ubuntu,฀ now’s฀ your฀ chance.฀ Ubuntu฀

like฀GNU฀GPL฀

this฀week฀announced฀Ubuntu฀Open฀Week,฀“a฀week-long฀series฀of฀online฀workshops”,฀

(open฀source),฀

where฀you฀can฀chat฀with฀developers,฀attend฀training฀sessions,฀and฀even฀talk฀to฀Mark฀

Mozilla฀Public฀License฀

Shuttleworth฀ himself.฀ You฀ can฀ find฀ out฀ more฀ at฀ wiki.ubuntu.com/UbuntuOpen-

or฀Microsoft฀Public฀License฀

Week.฀ It฀appears฀that฀Firefox฀is฀gaining฀ground฀on฀Internet฀Explorer,฀at฀least฀if฀you’re฀a฀BitTorrent฀user.฀Isohunt,฀a฀popular฀BitTorrent฀indexing฀site,฀reported฀on฀their฀blog฀this฀ week฀that฀Firefox฀users฀on฀isohunt.com฀edged฀out฀IE฀users฀for฀the฀first฀time฀since฀ they฀have฀been฀monitoring.฀

Firefox one฀of฀the฀most฀popular฀

Apparently฀ officials฀ in฀ Amsterdam฀ have฀ been฀ testing฀ Open฀ Source฀ applications฀ to฀

web฀browsers฀

see฀if฀they฀are฀ready฀for฀prime฀time.฀This฀week฀the฀testing฀committee฀gave฀the฀green฀

(after฀Internet฀Explorer)฀

light฀and฀now฀over฀10,000฀PCs฀can฀start฀using฀Open฀Source฀software.฀Any฀incremental฀ costs฀of฀running฀the฀open฀source฀software฀will฀be฀offset฀by฀savings฀in฀license฀fees฀that฀ would฀have฀been฀paid฀to฀Microsoft. And฀now฀on฀to฀the฀main฀stories฀of฀the฀week. It฀was฀a฀big฀week฀for฀patent฀litigation฀and฀it฀all฀started฀with฀more฀threatening฀words฀

MPL฀

from฀Steve฀Ballmer฀of฀Microsoft.฀According฀to฀Tom฀Sanders฀on฀vnunet.com,฀Microsoft฀

Microsoft฀Public฀Licence

chief฀executive฀Steve฀Ballmer฀has฀warned฀users฀of฀Red฀Hat฀Linux฀that฀they฀will฀have฀ to฀pay฀Microsoft฀for฀its฀intellectual฀property.฀“People฀who฀use฀Red฀Hat,฀at฀least฀with฀ respect฀to฀our฀intellectual฀property,฀in฀a฀sense฀have฀an฀obligation฀to฀compensate฀us,”฀ Ballmer฀said฀last฀week฀at฀a฀company฀event฀in฀London฀discussing฀online฀services฀in฀ the฀UK.฀Red฀Hat฀has฀repeatedly฀stated฀that฀it฀will฀not฀engage฀in฀a฀patent฀licensing฀

Suse,฀Red฀Hat,฀Ubuntu฀

deal฀similar฀to฀the฀Novell-Microsoft฀partnership,฀referring฀to฀it฀as฀an฀‘innovation฀tax’.฀

฀examples฀of฀linux฀

Microsoft฀has฀been฀the฀second฀most฀aggressive฀party฀in฀pursuing฀alleged฀intellectual฀

distributions฀

property฀ claims฀ against฀ Linux฀ and฀ open฀ source฀ in฀ general.฀ The฀ firm฀ ranks฀ behind฀ SCO,฀ which฀ failed฀ in฀ its฀ attempt฀ to฀ prove฀ that฀ it฀ owns฀ the฀ intellectual฀ property฀ to฀ Linux฀and฀now฀faces฀bankruptcy.฀Microsoft฀inked฀a฀partnership฀with฀Novell฀last฀year฀ in฀which฀Novell฀agreed฀to฀license฀Microsoft’s฀intellectual฀property฀in฀exchange฀for฀ a฀ patent฀ pledge฀ to฀ users฀ of฀ Novell’s฀ SuSE฀ Linux.฀ Ballmer฀ praised฀ Novell฀ at฀ the฀ UK฀

MRL฀

event฀for฀valuing฀intellectual฀property,฀and฀suggested฀that฀open฀source฀vendors฀will฀

Microsoft฀

be฀forced฀to฀strike฀similar฀deals฀with฀other฀patent฀holders.฀

Reciprocal฀Licence

sound Mozilla,฀the฀company฀behind฀popular฀open฀source฀applications฀like฀Firefox฀and฀Thunderbird,฀ announced฀ this฀ week฀ that฀ it฀ will฀ develop฀ a฀ mobile฀ browser฀ for฀ cell฀ phones฀

189

English++ and฀other฀devices.฀According฀to฀an฀article฀by฀Cade฀Metz฀on฀regdeveloper.co.uk,฀Mozilla฀ SCO

is฀ prepping฀ a฀ mobile฀ version฀ of฀ Firefox,฀ the฀ world’s฀ most฀ popular฀ open-source฀ web฀

฀a฀software฀company฀

browser.฀“People฀ask฀us฀all฀the฀time฀what฀Mozilla’s฀going฀to฀do฀about฀the฀mobile฀web,”฀

formerly฀called฀Caldera฀

reads฀a฀blog฀post฀from฀Vice-President฀of฀engineering฀Mike฀Schroepfer,฀“and฀I’m฀very฀

Systems฀and฀Caldera฀

excited฀to฀announce฀that฀we฀plan฀to฀rock฀it.”฀He฀says฀the฀company฀will฀introduce฀a฀

International.฀

mobile฀version฀of฀Firefox฀at฀some฀unspecified฀date฀after฀December฀31,฀2007.฀It฀will฀

After฀acquiring฀the฀

run฀Firefox฀extensions,฀and฀developers฀will฀have฀the฀power฀to฀build฀their฀own฀apps฀for฀

Santa฀Cruz฀Operation’s฀

the฀browser฀via฀Mozilla’s฀user฀interface฀language,฀called฀XUL.฀As฀Schroepfer฀points฀out,฀

Server฀Software฀and฀

a฀Mozilla-based฀browser฀is฀already฀available฀for฀Nokia’s฀N800฀wireless฀handheld.฀But฀

Services฀divisions,฀ as฀well฀as฀UnixWare฀ and฀OpenServer฀

the฀company฀has฀yet฀to฀decide฀which฀devices฀Mobile฀Firefox฀will฀run฀on.฀

sound

technologies,฀the฀company฀

It฀ was฀ announced฀ yesterday฀ that฀ the฀ OSI฀ has฀ approved฀ two฀ Microsoft฀ licenses฀ as฀

changed฀its฀focus฀to฀UNIX.฀

open฀ source฀ licenses.฀ According฀ to฀ infoworld.com,฀ the฀ board฀ of฀ the฀ Open฀ Source฀฀

Later฀on,฀Caldera฀changed฀

Initiative,฀ or฀ OSI,฀ ฀ has฀ approved฀ two฀ Microsoft฀ licenses฀ that฀ will฀ allow฀ proprietary฀

its฀name฀to฀The฀SCO฀

source฀code฀to฀be฀shared,฀a฀move฀that฀is฀likely฀to฀inspire฀protest฀and฀spur฀controversy฀

Group฀to฀reflect฀that฀

for฀die-hard฀open฀source฀proponents.฀The฀Microsoft฀Public฀License,฀or฀MPL,฀and฀the฀

change฀in฀focus

Microsoft฀Reciprocal฀License,฀or฀MRL,฀two฀of฀Microsoft’s฀“shared฀source”฀licenses,฀are฀ now฀viable฀OSI฀licenses฀for฀distributing฀open฀source฀code฀alongside฀more฀widely฀used฀

user฀interface฀

community฀licenses฀such฀as฀the฀GNU฀General฀Public฀License฀and฀the฀Mozilla฀Public฀

the฀aggregate฀of฀means฀

License.฀“Today’s฀approval฀by฀the฀OSI฀concludes฀a฀tremendous฀learning฀experience฀

by฀which฀people,฀

for฀Microsoft,฀and฀I฀look฀forward฀to฀our฀continuing฀participation฀in฀the฀open฀source฀

the฀users,฀interact฀with฀

community,”฀ said฀ Microsoft฀ general฀ manager฀ of฀ Windows฀ Server฀ Marketing฀ and฀฀

the฀system,฀a฀particular฀

Platform฀Strategy฀Bill฀Hilf฀in฀a฀press฀statement.฀Red฀Hat฀executive฀Michael฀Tiemann,฀

machine,฀device,฀

who฀also฀serves฀as฀president฀of฀the฀OSI,฀said฀Tuesday฀that฀while฀some฀in฀the฀com-

computer฀program฀

munity฀ balked฀ at฀ the฀ OSI฀ accepting฀ licenses฀ from฀ a฀ company฀ that฀ historically฀ has฀

or฀other฀complex฀tools.฀

not฀been฀open฀source฀friendly,฀in฀the฀end,฀the฀licenses฀spoke฀for฀themselves.฀“They฀

The฀user฀interface฀

do฀have฀two฀licenses฀that฀went฀through฀the฀community฀process฀and฀did฀sustain฀the฀

provides฀means฀of฀input,฀

open฀source฀definition,”฀he฀said.฀“I’ve฀received฀three฀e-mails฀in฀the฀last฀hour฀from฀

allowing฀the฀users฀to฀

people฀who฀say,฀‘To฀heck฀with฀the฀OSI,฀you฀guys฀are฀just฀now฀pawns฀in฀Microsoft’s฀

manipulate฀a฀system฀and฀

game.฀ You฀ have฀ made฀ a฀ deal฀ with฀ the฀ devil,’”฀ he฀ said.฀ However,฀ Tiemann฀ believes฀

output,฀allowing฀the฀

the฀OSI฀had฀a฀responsibility฀to฀be฀fair฀and฀impartial฀in฀letting฀Microsoft฀submit฀its฀li-

system฀to฀produce฀the฀

censes.฀“What฀would฀you฀think฀of฀a฀club฀that฀would฀say,฀‘We฀won’t฀take฀any฀members฀

effects฀of฀the฀users’฀

that฀come฀from฀the฀city฀of฀Chicago,฀even฀if฀two฀people฀in฀Chicago฀meet฀the฀criteria฀

manipulation.฀

for฀entry?’”฀he฀posited.฀“We฀said฀from฀the฀outset฀that฀we฀would฀be฀fair฀and,฀to฀be฀ honest,฀some฀people฀said,฀‘No,฀you฀don’t’”.฀Tiemann฀said฀it฀remains฀to฀be฀seen฀if฀any฀ companies฀other฀than฀Microsoft฀will฀license฀code฀under฀MPL฀or฀MRL.฀“However,”฀฀he฀ said,฀“if฀Microsoft฀plans฀to฀embed฀patented฀technology฀in฀software฀licensed฀under฀an฀ OSI-approved฀license฀and฀฀call฀it฀open฀source฀-฀as฀some฀open฀source฀proponents฀fear฀

190

-฀they฀had฀better฀think฀twice.”฀

English++

Exercises •฀฀฀Answer

the following questions

1.฀ Who฀will฀be฀using฀open฀source฀software฀in฀Amsterdam?฀ •฀ ฀officials฀ 2.฀ What฀is฀Steve฀Ballmer’s฀position฀in฀Microsoft?฀ •฀ Microsoft฀chief฀executive฀ 3.฀ When฀does฀Mozilla฀plan฀to฀introduce฀a฀new฀version฀of฀฀their฀web฀browser?฀ •฀ some฀time฀after฀the฀31st฀December฀2007฀ 4.฀ Name฀some฀open฀source฀licenses.฀ •฀ GNU฀GPL฀ •฀ Mozilla฀Public฀License฀ •฀ Microsoft฀Public฀License฀ 5.฀ What฀is฀the฀OSI?฀ •฀ The฀Open฀Source฀Initiative •฀฀฀Listen

to the recording and ﬁll the gaps

News฀in฀brief฀ 1.฀ Ubuntu฀this฀week฀announced฀Ubuntu฀Open฀Week,฀“a฀week-long฀series฀of฀[online฀ workshops]”฀ 2.฀ It฀appears฀that฀Firefox฀is฀gaining฀ground฀on฀Internet฀Explorer,฀at฀least฀if฀you’re฀a฀ [BitTorrent]฀user.฀ 3.฀ Isohunt,฀a฀popular฀BitTorrent฀indexing฀site,฀reported฀on฀their฀blog฀this฀week฀that฀ Firefox฀users฀on฀[isohunt.com]฀edged฀out฀IE฀users. 4.฀ Any฀incremental฀costs฀of฀running฀the฀open฀source฀software฀will฀be฀offset฀by฀savings฀in฀[license฀fees]฀that฀would฀have฀been฀paid฀to฀Microsoft.฀

Story฀One฀ 1.฀ People฀who฀use฀Red฀Hat,฀at฀least฀with฀respect฀to฀our฀[intellectual฀property],฀ 2.฀ Red฀Hat฀has฀repeatedly฀stated฀that฀it฀will฀not฀engage฀in฀a฀[patent฀licensing฀deal]฀ similar฀to฀the฀Novell-Microsoft฀partnership,฀referring฀to฀it฀as฀an฀[innovation฀tax]. 3.฀ The฀firm฀ranks฀behind฀SCO,฀which฀failed฀in฀its฀attempt฀to฀prove฀that฀it฀owns฀the฀ intellectual฀property฀to฀Linux฀and฀now฀faces฀[bankruptcy].฀

191

English++ Story฀Two 1.฀ Mozilla฀is฀prepping฀a฀mobile฀version฀of฀[Firefox],฀the฀world’s฀most฀popular฀[opensource]฀web฀browser.฀ 2.฀ People฀ ask฀ us฀ all฀ the฀ time฀ about฀ what฀ Mozilla’s฀ going฀ to฀ do฀ about฀ the฀ [mobile฀ web].฀ 3.฀ It฀will฀run฀Firefox฀[extensions],฀and฀developers฀will฀have฀the฀power฀to฀build฀their฀ own฀apps฀for฀the฀browser฀via฀Mozilla’s฀[user฀interface฀language],฀called฀XUL.฀ 4.฀ As฀Schroepfer฀points฀out,฀a฀Mozilla-based฀browser฀is฀already฀available฀for฀Nokia’s฀ N800฀[wireless฀handheld].฀

Story฀Three 1.฀ The฀board฀of฀the฀[Open฀Source฀Initiative],฀or฀OSI,฀has฀approved฀two฀Microsoft฀ licenses…฀ 2.฀ The฀Microsoft฀Public฀License,฀or฀MPL,฀and฀the฀[Microsoft฀Reciprocal฀License],฀r฀ MRL,฀two฀of฀Microsoft’s฀“shared฀source”฀licenses…฀ 3.฀ …said฀ Microsoft฀ general฀ manager฀ of฀ Windows฀ Server฀ Marketing฀ and฀ [Platform฀ Strategy]฀Bill฀Hilf฀in฀a฀press฀statement.฀ 4.฀ They฀do฀have฀two฀licenses฀that฀went฀through฀the฀[community฀process]฀and฀did฀ sustain฀the฀open฀source฀definition฀ 5.฀ However,฀he฀said฀if฀Microsoft฀plans฀to฀embed฀[patented฀technology]฀in฀software฀ licensed฀under฀an฀OSI-approved฀license฀and฀call฀it฀open฀source฀…฀

Possible topics for discussion •฀ What฀do฀you฀know฀about฀the฀GPL฀or฀MPL฀licenses?฀ •฀ Do฀you฀like฀using฀free฀software?฀Yes,฀why.฀No,฀why.

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English++

Open News Episode 31 from A Weekly Open Source News Podcast

Running฀time฀

6’04

Computer฀science฀content฀

Medium

Business฀content฀

฀Medium

English฀language฀complexity฀

Medium/High

Learning objectives •฀ to฀acquire฀knowledge฀on฀open฀source฀software฀usage •฀ to฀become฀familiar฀with฀licencing฀and฀what฀effect฀it฀may฀have฀on฀open฀source

Sub-areas covered •฀ Open฀source฀issues •฀ FOSS฀software฀

Keywords •฀ Podcast฀-฀a฀series฀of฀digital-media฀files฀which฀are฀distributed฀over฀the฀Internet฀using฀฀ syndication฀feeds฀for฀playback฀on฀portable฀media฀players฀and฀computers฀ •฀ Gnome฀-฀one฀of฀the฀biggest฀window฀managers฀for฀Linux฀ •฀ FOSS฀ -฀ the฀ acronym฀ for฀ Free฀ and฀ Open฀ Source฀ Software,฀ ฀ software฀ that฀ can฀ be฀ used,฀studied,฀and฀modified฀without฀restriction •฀ OHA฀-฀Open฀Handset฀Alliance™,฀a฀group฀of฀more฀than฀30฀technology฀and฀mobile฀ companies฀who฀have฀developed฀Android,฀the฀first฀complete,฀open,฀and฀free฀mobile฀ platform •฀ LiSP฀-฀The฀Linux฀Phone฀Standards฀Forum,฀a฀consortium฀founded฀by฀a฀group฀of฀฀ telephony฀ operators,฀ device฀ manufacturers,฀ silicon฀ and฀ software฀ vendors฀ who฀ have฀a฀strategic฀focus฀on฀Linux฀telephony

193

English++

Summary This฀is฀an฀audio฀podcast฀with฀news฀from฀the฀FOSS฀world. Clip฀1.฀ This฀ clip฀ is฀ about฀ film-makers฀ using฀ open-source฀ software฀ ฀ and฀ the฀ main฀ reasons฀฀for฀them฀doing฀so. Clip฀ 2.฀ ฀ This฀ is฀ about฀ Google’s฀ purchase฀ of฀ the฀ mobile฀ phone฀ platform฀ company฀฀ Android.฀It฀contains฀different฀opinions฀about฀this฀development฀and฀฀discusses฀the฀ possible฀consequences฀and฀significance฀for฀the฀mobile฀Linux฀community. Clip฀3.฀ This฀ is฀ a฀ report฀ on฀ running฀ the฀ Linux฀ system฀ on฀ school฀ computers฀ in฀฀ Macedonia. Jest฀to฀audio฀podcast฀z฀wiadomościami฀ze฀świata฀wolnego฀oprogramowania฀ Fragment฀ 1.฀ W฀ tym฀ fragmencie฀ zawarto฀ informację฀ o฀ używaniu฀ oprogramowania฀ open-source฀ przez฀ twórców฀ filmów,฀ a฀ także฀ przedstawiono฀ główne฀ przyczyny฀ takiej฀ tendencji. Fragment฀2.฀฀Ten฀fragment฀donosi฀o฀zakupieniu฀platformy฀telefonii฀komórkowej฀przez฀ firmę฀Google.฀Przedstawiono฀w฀nim฀różne฀opinie฀na฀ten฀temat,฀a฀także฀znaczenie฀i฀moż-฀ liwe฀konsekwencje฀tego฀faktu฀dla฀społeczności฀twórców฀wolnego฀oprogramowania. Fragment฀ 3.฀ Ten฀ fragment฀ zawiera฀ informację฀ o฀ wprowadzeniu฀ systemu฀ Linux฀฀ w฀szkolnych฀komputerach฀w฀całej฀Macedonii.

194

English++ Transcript More฀and฀more฀film-makers฀are฀turning฀to฀open-source฀software฀to฀meet฀the฀demanding฀

Podcast

needs฀of฀their฀production฀environments.฀฀Lisa฀Hoover,฀in฀an฀article฀on฀linuxinsider.

a฀series฀of฀digital-media฀

com,฀writes:฀’Since฀the฀advent฀of฀the฀music฀(The฀speaker฀says฀‘music’฀but฀this฀is฀a฀

files฀which฀are฀distributed฀

mistake฀for฀‘movie’.)฀industry,฀the฀process฀has฀remained฀largely฀unchanged.฀A฀writer฀

over฀the฀Internet฀using฀

creates฀a฀script,฀finds฀someone฀willing฀to฀invest฀money฀in฀producing฀it,฀and฀a฀director฀

syndication฀feeds฀

is฀brought฀in฀to฀oversee฀the฀film’s฀production.’฀While฀that฀process฀is฀still฀typical฀of฀

for฀playback฀on฀portable฀

most฀movie-making฀ventures,฀more฀and฀more฀independent฀filmmakers฀are฀turning฀

media฀players฀

toward฀open฀source฀tools฀and฀methods฀to฀produce฀their฀projects.฀For฀many฀filmmakers,฀

and฀computers

the฀economics฀alone฀make฀open฀source฀film฀making฀an฀attractive฀option.฀When฀free฀ or฀low-cost฀production฀tools฀like฀CinePaint฀and฀Blender฀are฀combined฀with฀free฀hosting฀services฀like฀Internet฀Archive,฀writers฀and฀filmmakers฀are฀free฀to฀focus฀on฀film฀ production฀ rather฀ than฀ financing.฀ Some฀ filmmakers฀ are฀ even฀ going฀ beyond฀ simply฀ sharing฀ideas,฀and฀are฀also฀sharing฀the฀footage฀they’ve฀shot.฀“It฀makes฀sense฀when฀ resources฀can฀be฀shared฀and฀costs฀can฀be฀cut,”฀writer฀and฀independent฀film฀director฀฀ Valentin฀ Spirik฀ told฀ LinuxInsider.฀ “I฀ also฀ see฀ a฀ lot฀ of฀ potential฀ for฀ remix-related฀ projects฀where฀the฀source฀footage฀is฀used฀in฀many฀different฀productions.฀Right฀now฀

Gnome

this฀is฀a฀niche฀genre฀online,฀but฀it฀might฀just฀be฀the฀future฀of฀interactive฀storytelling.”฀

one฀of฀the฀biggest฀

sound

window฀managers฀for฀ Linux฀

You฀may฀have฀heard฀recently฀that฀Google฀purchased฀the฀mobile฀phone฀platform฀company฀ Android,฀but฀what฀does฀that฀mean฀for฀comapnies฀like฀Open฀Moco฀and฀Tratec,฀who฀are฀ trying฀to฀develop฀their฀own฀platforms฀based฀on฀open-source฀software.฀According฀to฀a฀ story฀by฀Phil฀Manchester฀at฀regdeveloper.co.uk:฀While฀the฀mobile฀Linux฀community฀ has฀reacted฀positively฀to฀Google’s฀Android,฀the฀new฀platform฀has฀also฀given฀฀some฀ cause฀for฀concern.฀The฀arrival฀of฀a฀giant฀player฀with฀very฀clear฀ideas฀of฀roles฀it฀wants฀ mobile฀Linux฀to฀fill฀was฀bound฀to฀ruffle฀a฀few฀feathers฀and,฀despite฀public฀proclamations฀of฀welcome฀and฀support฀,฀the฀Linux฀establishment฀is฀showing฀a฀few฀cracks.฀Like฀

FOSS

it฀or฀not,฀Google฀has฀achieved฀something฀that฀none฀of฀the฀established฀knitting฀circles฀

the฀acronym฀for฀Free฀

has฀managed฀so฀far:฀it฀has฀created฀a฀single฀target฀platform฀for฀developers฀to฀aim฀for.฀

and฀Open฀Source฀

But฀ a฀ unified฀ standard฀ does฀ not฀ necessarily฀ play฀ well฀ with฀ the฀ established฀ mobile฀

Software,฀฀

Linux฀players.฀The฀LiPS฀or฀L-i-P-S฀Forum,฀for฀example,฀says฀that฀it฀“regards฀OHA฀as฀

software฀that฀can฀be฀used,฀

complementary”฀and฀acknowledges฀that฀Android฀and฀the฀OHA฀have฀confirmed฀the฀

studied,฀and฀modified฀

popularity฀of฀Linux฀in฀mobile฀and฀embedded฀applications.฀LiPS฀also฀says฀that฀Android฀

without฀restriction.฀For฀

shares฀its฀mission฀“to฀reduce฀fragmentation฀among฀Linux-based฀mobile฀platforms”฀

further฀info฀see฀wikipedia

-฀only฀with฀a฀different฀approach.฀While฀LiPS฀aims฀to฀unify฀the฀development฀of฀mobile฀ Linux฀through฀open฀standards,฀it฀sees฀the฀Android฀and฀OHA฀team฀as฀working฀to฀the฀ same฀end฀with฀shared฀code.฀But฀elsewhere฀LiPS฀general฀manager฀Bill฀Weinberg฀has฀ expressed฀concerns฀about฀the฀limitations฀of฀Google’s฀use฀of฀the฀Apache฀license฀for฀ Android฀and฀suggests฀that฀far฀from฀reducing฀fragmentation,฀Android฀might฀increase฀

195

English++ OHA฀

it.฀Morgan฀Gillis,฀executive฀director฀of฀the฀LiMo฀Foundation,฀said฀publicly฀that฀he฀wel-

Open฀Handset฀Alliance™,฀

comed฀Google’s฀move฀and฀also฀sees฀the฀role฀of฀the฀OHA฀as฀complementary.฀“Google’s฀฀

a฀group฀of฀more฀than฀

angle฀is,”฀he฀said,฀“focused฀on฀the฀end-user฀experience฀and฀bringing฀the฀Web฀to฀mobile฀฀

30฀technology฀and฀

devices฀while฀the฀LiMo฀Foundation฀wants฀to฀create฀a฀common฀middleware฀platform฀

mobile฀companies฀

to฀ underpin฀ mobile฀ applications.”฀ But฀ in฀ the฀ same฀ interview฀ he฀ pointed฀ out฀ that฀

who฀have฀developed฀

those฀in฀the฀mobile฀Linux฀area฀have฀a฀stark฀choice:฀“Work฀with฀Google,฀or฀think฀very฀

Android,฀

seriously฀about฀how฀to฀achieve฀the฀next-generation฀mobile฀internet฀experience฀for฀

the฀first฀complete,฀open,฀

their฀customers฀on฀their฀own.”฀The฀next฀six฀months฀will฀certainly฀be฀critical฀in฀the฀

and฀free฀mobile฀

growth฀of฀Android฀ecosystem.฀It฀could฀have฀the฀same฀galvanising฀effect฀on฀mobile฀

platform

application฀ development฀ that฀ Windows฀ had฀ on฀ PC฀ applications฀ in฀ the฀ late฀ 1980s.฀ Developers฀ need฀ to฀ pick฀ it฀ up฀ and฀ create฀ some฀ compelling฀ applications฀ to฀ match฀ the฀appeal฀of,฀say,฀Apple’s฀iPhone.฀But฀despite฀the฀concerns฀over฀licensing฀and฀the฀฀ possibilities฀ of฀ a฀ broader฀ long-term฀ agenda฀ from฀ Google,฀ it฀ would฀ be฀ hard฀ (and,฀฀ perhaps,฀foolish)฀to฀bet฀against฀it.฀

sound Apparently,฀the฀Macedonian฀government฀is฀going฀for฀Linux฀in฀a฀big฀way.฀According฀ to฀an฀article฀on฀the฀ubuntu.com฀website,฀the฀Macedonia฀Ministry฀of฀Education฀and฀ LiSP฀ The฀Linux฀Phone฀ Standards฀Forum,฀ a฀consortium฀founded฀ by฀a฀group฀of฀telephony฀ operators,฀device฀ manufacturers,฀silicon฀and฀ software฀vendors฀who฀ have฀a฀strategic฀focus฀ on฀Linux฀telephony

Science฀will฀deploy฀more฀than฀180,000฀workstations฀running฀Canonical’s฀ubuntu฀7.04฀ as฀part฀of฀its฀“Computer฀for฀Every฀Child”฀project.฀ The฀Macedonia฀“Computer฀for฀Every฀Child”฀project฀is฀one฀of฀the฀largest฀known฀thin฀ client฀ and฀ desktop฀ Linux฀ deployments฀ ever฀ undertaken.฀ Half฀ of฀ elementary฀ and฀฀ secondary฀ Macedonia฀ students฀ attend฀ school฀ in฀ the฀ morning,฀ and฀ half฀ attend฀ in฀ the฀ afternoon,฀ so฀ 180,000฀ workstations฀ will฀ allow฀ for฀ one฀ classroom฀ computing฀฀ device฀per฀student฀for฀the฀entire฀Republic’s฀public฀school฀population.฀The฀first฀7000฀฀ computers฀ pre-installed฀ with฀ Ubuntu฀ were฀ shipped฀ on฀ September฀ 4th฀ 2007.฀ The฀ Ubuntu฀operating฀system฀will฀run฀on฀160,000฀virtual฀PC฀terminals฀and฀20,000฀PCs฀ (which฀ also฀ support฀ a฀ student฀ on฀ the฀ attached฀ monitor)฀ supplied฀ by฀ NComputing฀ and฀procured฀and฀installed฀by฀The฀Haier฀Company,฀a฀diversified฀manufacturer฀and฀ PC฀maker฀based฀in฀China.฀The฀project฀will฀enable฀a฀range฀of฀innovative฀educational฀ programs,฀including฀interactive฀web-based฀classes฀in฀which฀specialized฀experts฀teach฀ lessons฀ in฀ such฀ areas฀ as฀ mathematics,฀ biology,฀ chemistry฀ and฀ physics฀ to฀ multiple฀ schools฀and฀classrooms฀around฀the฀country.฀

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Exercises •฀฀฀Answer

the following questions

1.฀What฀are฀film-makers฀increasingly฀using฀to฀smooth฀the฀way฀for฀their฀projects?฀ •฀ open฀source฀software฀ 2.฀Which฀open฀source฀฀tools฀and฀services฀are฀mentioned฀as฀being฀used฀by฀filmmakers?.฀฀What฀functions฀do฀they฀perform?฀฀Do฀you฀know฀of฀any฀other฀examples?฀ ฀

Examples฀from฀listening:฀

•฀ Cine฀Paint฀-฀open฀source฀painting฀and฀image฀retouching฀program฀designed฀to฀work฀ best฀with฀35mm฀film฀and฀other฀high฀resolution฀high฀dynamic฀range฀images.฀ •฀ Blender฀-฀open฀source,฀cross฀platform฀suite฀of฀tools฀for฀3D฀creation.฀ •฀ Internet฀Archive฀-฀nonprofit฀organisation฀established฀to฀preserve฀websites฀by฀taking฀regular฀“snapshots”.฀The฀Wayback฀Machine฀provides฀links฀to฀older฀versions฀of฀ a฀webpage.฀ •฀฀฀Listen

to the recording and ﬁll the gaps

1.฀ While฀the฀mobile฀Linux฀community฀has฀reacted฀positively฀to฀[Google’s฀Android].฀ 2.฀ Like฀it฀or฀not,฀Google฀has฀achieved฀something฀that฀none฀of฀the฀established฀[knitting฀circles]฀has฀managed฀so฀far.฀LiPS฀also฀says฀that฀Android฀shares฀its฀mission฀to฀ reduce฀[fragmentation฀among฀Linux-based]฀mobile฀platforms฀ 3.฀ While฀LiPS฀aims฀to฀[unify]฀the฀development฀of฀mobile฀Linux฀through฀open฀standards 4.฀ ฀Morgan฀Gillis,฀executive฀director฀of฀the฀[LiMo฀Foundation]฀… 5.฀ mobile฀devices฀while฀the฀LiMo฀Foundation฀wants฀to฀create฀a฀common฀[middleware฀platform]฀to฀underpin฀mobile฀applications.฀ 6.฀ The฀next฀six฀months฀will฀certainly฀be฀critical฀in฀the฀growth฀of฀[Android฀ecosystem].฀ 7.฀ Developers฀need฀to฀pick฀it฀up฀and฀create฀some฀[compelling฀applications]฀to฀match฀ the฀appeal฀of,฀say,฀Apple’s฀iPhone.฀ •฀฀฀Listen

to the recording and ﬁll the gaps

1.฀ The฀Macedonia฀Ministry฀of฀Education฀and฀Science฀will฀deploy฀more฀than฀180,000฀ workstations฀running฀Canonical’s฀฀Ubuntu฀7.04฀as฀part฀of฀its฀[Computer฀for฀Every฀ Child]฀project.฀ 2.฀ The฀Macedonia฀“Computer฀for฀Every฀Child”฀project฀is฀one฀of฀the฀largest฀known฀ thin฀client฀and฀[desktop฀Linux]฀deployments฀ever฀undertaken฀ 3.฀ The฀first฀7000฀computers฀[pre-installed]฀with฀Ubuntu฀were฀shipped฀on฀September฀4th฀2007฀ 4.฀ The฀ Ubuntu฀ operating฀ system฀ will฀ run฀ on฀ [160,000฀ virtual฀ PC฀ terminals]฀ and฀ 20,000฀PCs฀

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English++ 5.฀ The฀ project฀ will฀ enable฀ a฀ range฀ of฀ innovative฀ educational฀ programs,฀ including฀฀ interactive฀[web-based฀classes]฀

Possible topics for discussion 1.฀Should฀film-makers฀use฀open฀source฀rather฀than฀commercial฀software?฀฀

฀

2.฀Is฀open-source฀software฀the฀best฀choice฀for฀school฀computers?฀Give฀arguments฀for฀ and฀against฀this฀proposal.

฀

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English++

English++ English for Computer Science Students

Presentation Chapter

199

English++

200

English++

Presentation Chapter This฀chapter฀deals฀briefly฀with฀a฀difficult฀task฀of฀speaking฀in฀public. We฀hope฀that฀the฀tips฀which฀we฀worked฀out฀during฀our฀English฀classes฀will฀be฀helpful฀ to฀those฀of฀you฀who฀are฀planning฀to฀make฀presentations฀in฀English.฀To฀make฀that฀task฀ easier฀a฀repertoire฀of฀‘presentation฀phrases’฀is฀included.฀You฀can฀make฀a฀reasonable฀ selection฀of฀useful฀phrases฀to฀start฀your฀presentation,฀develop฀its฀main฀points฀and฀ finish฀it฀successfully.฀ This฀ part฀ of฀ the฀ book฀ is฀ accompanied฀ by฀ a฀ DVD฀ with฀ a฀ slide฀ show฀ produced฀฀ by฀ English++฀ team.฀ “Successful฀ presentations.฀ A฀ few฀ tips฀ from฀ English++”฀฀ presents฀ examples฀ of฀ well-prepared฀ and฀ well-done฀ presentations.฀ Obviously,฀ you฀฀ can฀always฀improve฀one฀thing฀or฀another,฀but฀the฀point฀is฀not฀to฀criticize,฀but฀learn.฀ As฀English++฀project฀leader฀I฀am฀grateful฀to฀those฀who฀let฀us฀use฀their฀own฀material฀ for฀the฀purpose฀of฀the฀this฀book. The฀ slide฀ show฀ also฀ includes฀ some฀ clips฀ which฀ show฀ a฀ little฀ bit฀ less฀ effective฀฀ productions.฀Why?฀See฀for฀yourself.฀Naturally,฀you฀should฀take฀them฀with฀a฀pinch฀of฀฀ salt,฀but฀perhaps฀there฀is฀something฀in฀it.

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English++

How to Give a Successful Presentation? Practical information Pre-preparation. Selecting the topic and materials An฀ essential฀ task฀ in฀ a฀ pre-preparatory฀ phase฀ is฀ to฀ ask฀ yourself฀ the฀ following฀฀ questions:฀฀฀฀ •฀ What฀is฀the฀purpose฀of฀my฀presentation?฀ •฀ What฀are฀the฀main฀points฀that฀I฀would฀like฀to฀get฀across?฀ Start฀getting฀ready฀for฀your฀presentation฀a฀few฀weeks฀before฀you฀are฀due฀to฀speak.฀ Collect฀the฀materials฀on฀the฀basis฀of฀which฀you฀would฀like฀to฀prepare฀the฀presentation.฀ Make฀a฀wise฀choice฀out฀of฀the฀collected฀materials.฀ Prepare฀reliable฀bibliography฀(the฀author’s฀name,฀the฀title฀of฀the฀article/book,฀a฀year฀of฀ its฀publication,฀the฀website฀address,฀when฀the฀material฀was฀retrieved,฀etc.).฀ From฀the฀material฀select฀the฀keywords฀for฀your฀presentation฀and฀do฀not฀forget฀to฀put฀ them฀on฀the฀handout.฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀

Preparation •฀ Make฀the฀first฀plan฀of฀the฀presentation฀(you฀can฀modify฀it฀later)฀ •฀ Remember฀about฀a฀logical฀structure฀of฀the฀presentation:฀ ฀

Introduction฀-฀say,฀what฀you’re฀going฀to฀say฀

฀

Main฀Body฀-฀say฀it;฀develop฀the฀above฀mentioned฀issue(s).฀

฀

Conclusions฀-฀sum฀up฀what฀you’ve฀just฀said฀฀

•฀ Make฀the฀first฀draft฀of฀your฀presentation.฀Read฀it฀carefully.฀If฀there฀is฀information฀ not฀related฀to฀the฀topic,฀remove฀it.฀ •฀ If฀there฀are฀issues฀which฀you฀cannot฀express฀in฀a฀precise฀or฀clear฀way,฀probably฀it฀ is฀because฀you฀do฀not฀really฀understand฀them฀yourself.฀So฀it฀is฀better฀not฀to฀talk฀ about฀them.฀ •฀ Never฀read฀from฀your฀notes.฀You฀should฀know฀well฀the฀material฀you฀want฀to฀present.฀ If฀you฀do฀not฀know฀it,฀maybe฀you฀should฀not฀go฀for฀giving฀a฀presentation.฀ •฀ Prepare฀a฀set฀of฀numbered฀clue฀cards,฀on฀which฀you฀can฀write฀the฀main฀points฀or/ and฀keywords฀and฀which฀will฀help฀you฀during฀the฀presentation.฀Make฀sure฀that฀on฀

202

your฀clue฀cards฀you’ve฀marked฀an฀appropriate฀visual฀aid฀(a฀transparency฀or฀slide),฀ which฀you฀are฀going฀to฀refer฀to฀in฀your฀presentation.

English++ ฀•฀ Find฀time฀to฀rehearse฀again฀and฀again!฀ ฀By฀doing฀that฀you฀are฀going฀to฀make฀yourself฀฀familiar฀with฀your฀own฀voice,฀to฀ check฀and฀adjust฀the฀presenting฀time,฀to฀see฀whether฀visual฀aids฀(if฀you฀use฀them)฀ actually฀illustrate฀your฀presentation฀and฀whether฀you฀coordinate฀well฀their฀usage฀ with฀what฀you฀say.฀If฀you฀have฀problems฀with฀a฀foreign฀language฀in฀which฀you฀ present฀ the฀ material,฀ it฀ could฀ be฀ better฀ not฀ to฀ use฀ visuals฀ at฀ all.฀ Otherwise฀ the฀ chance฀that฀something฀goes฀wrong฀is฀฀bigger฀than฀when฀you฀concentrate฀solely฀on฀ the฀oral฀aspect฀of฀the฀presentation.฀ •฀ Keep฀to฀the฀time!฀Do฀not฀exceed฀the฀time฀limit. ฀

It฀is฀better฀to฀shorten฀the฀presentation฀by฀two฀minutes฀rather฀than฀extend฀it฀by฀ two฀minutes.฀Remember฀that฀exceeding฀the฀time฀limit฀may฀mean฀taking฀the฀next฀ speaker’s฀time.฀฀And฀this฀is฀really฀unfair!

•฀ Follow฀the฀plan฀of฀your฀presentation!฀ ฀

Do฀ not฀ digress!฀ Usually฀ digressions฀ take฀ more฀ time฀ than฀ we฀ think.฀ Successful฀฀ presenters฀have฀“spontaneous฀digressions”฀well฀thought฀over฀and฀well฀planned.฀฀฀฀฀฀฀฀฀

•฀ Leave฀time฀for฀questions฀from฀the฀audience.฀ ฀

Questions฀may฀help฀you฀to฀get฀your฀message฀across฀better.

•฀ Design฀good฀visuals฀to฀help฀you฀get฀your฀message฀across฀more฀efficiently. ฀

Remember฀that฀tatty฀visuals฀will฀leave฀a฀similar฀impression฀on฀the฀listeners.฀฀

฀

Visual฀ aids฀ should฀ speak฀ for฀ themselves฀ illustrating฀ your฀ point.฀ Give฀ listeners฀ time฀to฀take฀them฀in.฀ Reading฀ out฀ what฀ you฀ have฀ written฀ on฀ a฀ transparency฀ or฀ slide฀is฀counterproductive.฀Visuals฀are฀always฀welcomed฀–฀they฀may฀help฀to฀catch฀the฀฀ audience’s฀attention,฀but฀if฀you฀do฀not฀feel฀comfortable฀with฀them,฀give฀yourself฀more฀ time฀for฀practice.฀

Visual aids There฀are฀different฀types฀of฀visuals.฀The฀choice฀depends฀on฀the฀type฀of฀presentation฀ and฀your฀needs.฀ •฀ OHP฀transparencies฀-฀overhead฀projector฀transparencies฀ •฀ Presentations฀in฀PowerPoint฀ •฀ Flipcharts฀ •฀ Whiteboard฀and฀marker฀ •฀ Video •฀ Short฀episodes฀or฀scenes฀from฀films •฀ ฀35฀mm฀slides฀ •฀ Real฀objects,฀which฀you฀can฀provide฀listeners฀with฀฀to฀explore฀them฀ Remember฀that฀badly฀prepared฀and/or฀badly฀used฀visuals฀can฀ruin฀your฀presentation!฀ Make฀sure฀you฀know฀in฀advance฀how฀to฀connect฀the฀equipment฀and฀what฀to฀do฀to฀ have฀a฀desired฀slide฀or฀diagram฀on฀the฀screen.฀Sometimes,฀during฀real฀presentations฀

203

English++ a฀technician฀is฀designated฀to฀operate฀the฀equipment.฀In฀that฀case฀make฀sure฀that฀he฀ understands฀your฀signals,฀which฀you฀are฀going฀to฀send฀when฀you฀wish,฀for฀example,฀ to฀change฀a฀slide.฀ Slides฀and฀transparencies฀should฀contain฀minimum฀information฀which฀is฀needed฀to฀ illustrate฀your฀point.฀Too฀much฀on฀a฀slide฀makes฀it฀unreadable฀and฀diverts฀audience’s฀ attention฀from฀what฀you฀say.฀ A฀slide฀is฀said฀to฀be฀readable฀if฀it฀contains฀no฀more฀than฀ten฀words฀in฀18pt฀Times฀฀ Roman฀font฀or฀bigger฀and฀which฀can฀be฀read฀without฀a฀projector฀from฀the฀distance฀of฀ two฀meters.฀Never฀use฀as฀your฀visuals฀pages฀photocopied฀from฀books฀or฀other฀materials.฀฀ They฀are฀not฀adapted฀for฀such฀usage,฀not฀to฀mention฀the฀fact฀that฀they฀don฀not฀฀prove฀ your฀professionalism.฀ For฀transparencies,฀use฀multiple฀colours,฀but฀be฀careful฀with฀orange฀and฀yellow฀-฀they฀ do฀not฀come฀out฀well฀on฀the฀screen.฀On฀slides,฀the฀text฀is฀often฀in฀yellow฀or฀white฀ colour฀ on฀ the฀ blue฀ background.฀ Avoid฀ adding/drawing฀ information฀ on฀ a฀ presented฀ transparency.฀While฀speaking฀avoid฀indicating฀with฀your฀finger฀or฀a฀marker.฀A฀pointer฀ and฀the฀screen฀do฀that฀job฀much฀better.฀ Turn฀off฀a฀projector฀if฀you฀do฀not฀need฀it฀for฀the฀next฀few฀minutes.฀Two฀minutes฀is฀the฀ maximum฀time฀that฀the฀same฀slide฀should฀be฀shown฀on฀the฀screen.฀

Presentation – dress rehearsal Presentation฀should฀not฀take฀place฀without฀practicing฀it฀earlier฀a฀lot฀of฀times฀in฀front฀ of฀a฀mirror฀or/and฀with฀a฀tape฀recorder.฀Observing฀yourself฀and฀listening฀to฀yourself฀ “in฀action”฀is฀stressful,฀but฀very฀formative.฀It฀provides฀you฀with฀the฀material฀on฀which฀ you฀can฀gradually฀develop฀your฀presentational฀skills฀and฀competencies.฀ A฀couple฀of฀final฀tips: •฀ Speak฀clearly.฀ •฀ Avoid฀raised฀voice,฀whispering฀or฀mumbling฀“under฀your฀nose”.฀ •฀ Try฀to฀maintain฀your฀natural฀pace฀of฀speaking฀typical฀for฀an฀official,฀not฀everyday฀ situation.฀ •฀ Make฀pauses฀in฀places฀which฀you฀consider฀critical฀฀for฀your฀presentation;฀this฀treatment฀฀ emphasizes฀the฀crucial฀information฀you฀wish฀to฀transmit฀to฀the฀audience. •฀ Try฀to฀control฀your฀body฀language;฀avoid฀excessive฀gesticulation.฀ •฀ Keep฀an฀eye฀contact฀with฀your฀listeners฀but฀do฀not฀focus฀on฀one฀person฀only.฀ •฀ Don’t฀turn฀back฀to฀the฀audience฀if฀you฀want฀to฀show฀something฀on฀the฀screen฀and฀ don’t฀‘talk฀to฀the฀screen’฀either.฀ •฀ Don’t฀stand฀in฀the฀light฀of฀a฀projector฀covering฀the฀screen.฀฀

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•฀ Observe฀your฀audience’s฀reactions฀–฀maybe฀you฀should฀shorten฀the฀presentation฀

English++ by฀two฀minutes฀and฀move฀on฀to฀conclusions.฀ •฀ Don’t฀forget฀to฀thank฀the฀audience฀for฀their฀attention฀and฀encourage฀them฀to฀ask฀ questions.฀If฀you฀are฀not฀sure฀about฀the฀answer฀of฀if฀you฀simply฀do฀not฀know฀it,฀ don’t฀be฀afraid฀to฀admit฀that,฀but฀suggest฀the฀source฀in฀which฀the฀answer฀can฀be฀ found.฀ •฀ Enjoy฀your฀presentation.฀Try฀to฀treat฀it฀as฀your฀new฀experience฀and฀show฀your฀ enthusiasm! Good฀luck!

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English++

Repertoire of presentation phrases Part one – introduction 1. Signaling the start OK,฀then,฀shall฀we฀start? OK,฀then,฀I’d฀like฀to฀begin. Let’s฀start฀…

2. Greeting Good฀morning/afternoon,฀ladies฀and฀gentlemen/everyone. Thank฀you฀for฀coming. I’m฀very฀happy฀that฀you’ve฀come฀here฀today.

3. Self-introduction First฀of฀all,฀I’d฀like฀to฀introduce฀myself.฀ My฀name฀is฀… Let฀me฀start฀with฀just฀a฀few฀words฀about฀myself/my฀own฀background. I’m฀…………….(name)฀from฀……………(country/city). I’m฀from฀………..(organisation). I฀work฀as฀a฀…………..(job)฀for฀…………….(organisation). I฀study฀………(subject)฀at฀…………….(university).฀I’m฀in฀my฀third฀year. I฀represent฀…………/฀I’m฀a฀representative฀of฀…

4.Introducing the subject Today,฀I’m฀going฀to฀talk฀about… I’d฀like฀to฀talk฀to฀you฀today฀about฀… I’m฀going฀to฀present฀the฀recent฀…/inform฀you฀about฀…/describe฀… The฀subject/focus/topic฀of฀my฀talk/presentation/speech฀is฀…

5. Stating the purpose We฀are฀here฀today฀to฀decide/learn฀about/discuss฀… The฀aim/objective/purpose฀today฀is฀to฀update฀you฀on฀…/give฀you฀the฀background฀ to฀… In฀my฀presentation฀today฀I’ll฀be฀discussing฀…/I’m฀going฀to฀explain฀… What฀I’d฀like฀to฀do฀today฀is฀to฀present฀…

6. Outline (main points/sequencing/length) 206

I’ve฀divided฀my฀presentation฀into฀four฀parts/sections.฀They฀are฀… My฀presentation฀will฀consist฀of฀…

English++ Right,฀I’d฀like฀to฀begin฀with฀my฀first฀point. Firstly/First฀of฀all฀………………..I฀will฀… Secondly/then/next฀…………….I฀would฀like฀to฀… Thirdly฀/฀and฀then฀we฀come฀to฀… After฀that/later……………………I’m฀going฀to฀talk฀about฀/฀look฀at฀… Finally/lastly/last฀of฀all฀I’d฀like฀to฀analyze/discuss/look฀at/consider/explain/tell฀you฀ about/฀show฀you฀how/speak฀to฀you฀about฀…

7. Inviting questions I’d฀be฀glad฀to฀answer฀any฀questions฀at฀the฀end฀of฀my฀talk. If฀you฀have฀any฀questions,฀please฀feel฀free฀to฀interrupt.

Part two – main body 1. Ordering A฀reaching฀the฀end฀of฀one฀point Right,฀I’ve฀talked฀about/฀mentioned…฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀ We’ve฀looked฀at฀… That’s฀all฀I฀have฀to฀say฀about฀…฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀ That฀covers฀… B฀moving฀on฀to฀the฀next฀point Now฀we฀come฀to฀…฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀That฀brings฀us฀to฀… I’d฀like฀to฀move฀on/draw฀your฀attention฀to฀my฀next฀point. Let’s฀move฀on฀to฀… Let’s฀look฀now฀at฀…The฀next฀thing฀I’d฀like฀to฀talk฀about฀is฀…

2. Giving reasons The฀main฀explanation฀for฀this฀is฀… There฀are฀two฀reasons/explanations฀for฀this.฀First,…฀Second,…฀ This฀can฀be฀explained฀by฀two฀factors.฀Firstly,฀…฀Secondly,฀… This฀is฀due฀to฀…฀฀฀฀฀฀฀฀฀฀฀฀฀฀ One฀reason฀for฀this฀is฀…฀฀฀฀฀฀ Another฀reason฀is฀…

3. Developing the point Where฀does฀that฀take฀us?฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀ Let’s฀look฀at฀this฀in฀more฀detail. What฀does฀that฀mean฀for฀us?

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English++ 4. Giving examples A฀good฀example฀of฀this฀is฀… To฀illustrate฀this฀point,฀… To฀support฀what฀I’ve฀said฀… I’d฀like฀to฀give฀you฀some฀examples฀… for฀instance฀…฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀for฀example฀…฀฀฀฀฀฀฀฀฀฀฀฀฀such฀as฀…฀฀฀฀฀฀฀฀฀฀฀฀฀฀like…

5. Referring to visuals Take/Have฀a… Let’s… I’d฀like฀you฀to฀look฀at฀this฀transparency/graph/table/pie฀chart/flow฀chart/bar฀chart/ diagram/chart฀ I’d฀like฀to฀draw฀your฀attention฀to฀… This฀shows/represents฀… As฀you฀can฀see฀… If฀you฀look฀at฀…you฀can฀see฀from฀the฀transparency,฀etc.฀that฀… Let฀me฀show฀you฀…฀ Could฀you฀look฀at฀your฀handouts฀… The฀next฀slide/picture/graph฀shows฀…

6. Relating ideas A showing consequence therefore฀…฀฀฀฀฀฀฀฀so฀…฀฀฀฀฀฀฀฀฀consequently฀…฀฀฀฀฀because฀of฀this฀…฀฀฀฀฀฀฀฀as฀a฀result฀….

B comparing similarly฀…฀฀฀฀฀฀฀฀฀฀฀฀฀in฀the฀same฀way฀… one฀similarity/difference฀between฀………฀is฀that฀…

C contrasting but฀…฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀however฀…฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀although฀…฀฀฀฀฀฀฀฀฀฀฀฀฀฀nevertheless…฀฀฀ even฀though฀…฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀despite฀/฀in฀spite฀(of฀the฀fact฀that)฀…฀฀฀฀whereas/ while… in฀contrast฀to฀…฀฀฀฀฀฀฀฀฀฀฀฀฀฀by฀contrast฀with฀…฀฀฀฀฀฀฀฀฀฀฀฀on฀the฀other฀hand…

D highlighting in฀particular฀…฀฀฀฀฀฀฀especially฀… –฀changing฀the฀word฀order,฀e.g.:฀‘What฀was฀important฀was฀the฀final฀conclusion.’฀ (instead฀of:฀‘The฀final฀conclusion฀was฀important.’)

208

English++ –฀repeating฀key฀words,฀e.g.:฀‘We฀need฀to฀compare฀past฀achievements฀and฀present฀ achievements.’฀ (instead฀ of฀ ‘We฀ need฀ to฀ compare฀ past฀ and฀ present฀ achievements.’)

E showing an additional argument moreover฀…฀฀฀฀฀฀฀in฀addition฀to฀this฀…฀฀฀฀฀฀not฀only฀…฀but฀also฀฀฀฀฀฀furthermore…

Part three – ending 1. Signaling the end That฀brings฀me฀to฀the฀end฀of฀my฀presentation. That฀completes฀my฀presentation. That฀covers฀all฀I฀want/wanted฀to฀say฀today. Before฀I฀stop/finish,฀let฀me฀just฀say฀…

2. Summarizing Let฀me฀just฀run฀over฀the฀key฀points฀again. I’ll฀briefly฀summarize฀the฀main฀issues. To฀sum฀up… Let’s฀recap,฀shall฀we? If฀I฀can฀just฀sum฀up฀the฀main฀points฀… Finally,฀I’d฀like฀to฀go฀over/review฀… Firstly,฀I฀talked฀about฀………฀Secondly,฀I฀discussed……Thirdly,฀I฀looked฀at฀……

3. Concluding In฀conclusion฀… I’d฀like฀to฀conclude฀by฀saying฀… As฀a฀conclusion,฀I’d฀like฀to฀… I’d฀like฀to฀leave฀you฀with฀the฀following฀thought/idea.

4. Closing Thank฀you฀for฀your฀attention฀/฀being฀so฀attentive/listening. It฀was฀pleasure฀talking฀to฀you฀… I฀will฀be฀giving฀you฀handouts. You฀will฀find฀handouts฀at฀the฀entrance. There฀are฀copies฀on฀the฀table.

209

English++ 5. Inviting questions Are฀there฀any฀questions? Have฀you฀got฀any฀questions?

6. Asking questions Could฀I฀go฀back฀to฀the฀point฀you฀made฀about…? I฀was฀interested฀in฀your฀comment฀on฀… You฀said฀that฀… Could฀you฀say฀a฀little฀more฀about฀that? Could฀you฀clarify฀what฀you฀said฀about฀…? I‘d฀like฀to฀ask฀about฀… May฀I฀ask฀you฀a฀question? I’m฀interested฀in฀your฀opinion฀about฀… Do฀you฀mind฀if฀I฀ask฀you… I’m฀interested฀to฀know฀…

7. Handling questions A clarifying If฀I฀understand฀you฀correctly,฀you฀are฀saying/asking฀… I฀didn’t฀quite฀catch฀that. Could฀you฀go฀over฀that฀again? I’m฀not฀sure฀what฀you’re฀getting฀at. Sorry,฀I’m฀not฀sure฀what฀you฀mean.

B playing for time That’s฀a฀good/interesting/difficult฀point/question/comment. I’m฀glad฀you฀raised฀that฀point.

C saying you don’t know I’m฀sorry฀I฀don’t฀have฀that฀information฀at฀this฀moment. I’m฀afraid฀I฀don’t฀know฀at฀the฀moment.

D avoiding giving answers Perhaps฀we฀could฀deal฀with฀that฀later. Can฀we฀talk฀about฀that฀on฀another฀occasion? I’m฀afraid฀that’s฀not฀my฀field. I฀don’t฀have฀the฀figures฀with฀me. I’m฀sure฀Mr/Ms฀…฀could฀answer฀this฀question.

210

I’ll฀get฀back฀to฀you฀if฀time฀permits.

English++ E checking if the questioner is satisﬁed Does฀that฀answer฀your฀question? Is฀that฀clear? Can฀we฀go฀on?

F concluding the questions Right,฀if฀nobody฀wants฀to฀ask฀anything฀else,฀I฀think฀we฀can฀finish฀here. Right,฀if฀there฀are฀no฀more฀questions฀…฀ Thank฀you.

211

English++

212

English++

English++ English for Computer Science Students

Appendixes

213

English++

214

English++

Appendix A

Mathematical terminology

Listen to the recording ฀ algebra฀

algebra

algorithm฀

algorytm

analyze฀฀฀analytical฀

analizować฀฀฀฀฀฀฀analityczny฀฀฀฀฀฀฀obliczeniowy

approximation฀

przybliżenie฀฀฀฀฀฀฀฀฀฀฀aproksymacja

arc฀

łuk

area฀

pole฀฀฀฀฀obszar

argument฀

argument฀w฀sensie:฀dowód,฀argument฀(funkcji)

assert฀

dowieść

assumption฀

założenie

average฀฀฀฀฀฀฀฀฀฀mean฀

średnia

axis฀฀฀฀฀฀฀฀฀฀฀฀฀axes฀(pl)฀

oś

ball฀฀฀฀฀฀฀฀฀฀unit฀ball฀

kula฀฀฀฀฀฀฀฀฀฀฀฀฀kula฀jednostkowa

binomial฀

dwumian฀(Newtona)

brace฀

{}

square฀bracket฀

[฀฀]

cancel฀

anulować,฀skreślić

common฀fraction฀

ułamek฀zwykły

complex฀number฀฀

liczba฀zespolona

cube฀

sześcian฀[podnieść฀do฀sześcianu]

cube฀root฀

pierwiastek฀sześcienny

curve฀

krzywa

data฀

dane

215

English++

216

decimal฀fraction฀

ułamek฀dziesiętny

deduce฀

wywnioskować฀฀฀฀฀฀฀฀฀฀wydedukować

฀ derive฀(v)฀฀฀฀derivation฀(n) ฀

wyprowadzać฀(np.฀wzór)฀

derivative฀฀(n,฀adj)฀

pochodna฀฀฀฀฀฀฀฀฀฀฀฀฀฀pochodny฀

diagonal฀฀฀(n,฀adj)฀฀

przekątna฀฀฀฀฀฀฀diagonalny฀฀฀฀฀przekątny฀

dimension฀

wymiar

divide฀

dzielić

differential฀฀(n,฀adj)฀

różniczka฀฀฀฀฀฀฀฀฀฀฀różniczkowy

domain฀(of฀a฀function)฀

dziedzina฀funkcji

edge฀

krawędź

equivalent฀

równoważny

estimate฀(v,฀n)฀

szacować฀฀฀฀฀฀฀฀szacunek฀฀฀฀฀฀฀liczba฀szacunkowa

even฀

parzysty฀(o฀liczbie)

exponent฀

wykładnik฀(potęgowy)

exponential฀function฀

funkcja฀wykładnicza

factor฀

czynnik฀฀฀฀฀฀฀฀współczynnik฀฀฀฀฀฀฀฀฀mnożnik

factorial฀

silnia

finite฀

skończony

fraction฀

ułamek

hypotenuse฀฀

przeciwprostokątna

image฀of฀a฀function฀

obraz฀funkcji

imaginary฀number฀

liczba฀urojona

infinite฀(set)฀

nieskończony฀(zbiór)

infinity฀

nieskończoność

integer฀

liczba฀całkowita

integral฀(n,฀adj)฀฀

całka฀฀฀฀฀฀฀฀฀฀฀całkowy

interval฀

interwał฀฀฀฀฀฀przedział

leg฀฀

bok฀trójkąta฀równoramiennego

฀฀฀฀

฀

obliczanie฀pochodnej

English++ logarithm฀

logarytm

logarithmic฀(function)฀

funkcja฀logarytmiczna

mapping฀ (one-to-one฀mapping)฀

odwzorowanie฀(wzajemnie฀jednoznaczne)

matrix฀฀฀฀฀฀matrices฀(pl)฀

macierz

median฀

mediana

meeting฀point฀

punkt฀przecięcia

midpoint฀

środek

minus฀

minus฀฀฀฀฀฀znak฀odejmowania

multiplication฀

mnożenie

numerator฀

licznik฀(ułamka)

oblique฀

ukośny

obtuse฀angle฀

kąt฀rozwarty

obtuse-฀angled฀triangle฀

trójkąt฀rozwartokątny

odd฀

nieparzysty฀(o฀liczbie)

parallel฀

równoległy

per฀cent฀

procent

permutation฀

permutacja

plane฀(n,฀adj)฀

płaszczyzna฀฀฀฀płaski฀

plane฀figure฀

figura฀płaska

polygon฀

wielobok฀฀฀฀฀฀฀฀฀wielokąt

polynominal฀

wielomian

proposition฀

twierdzenie฀฀฀฀฀teza

probability฀

prawdopodobieństwo

pyramid฀

ostrosłup

sphere฀

sfera

quadrangle฀

czworokąt

quadrant฀

ćwiartka

quotient฀

iloraz

217

English++ raise฀to฀the฀x-th฀power฀

podnieść฀do฀x-tej฀potęgi

real฀number฀฀

liczba฀rzeczywista฀

rhomb฀฀฀rhombus฀

romb

right฀angle฀

kąt฀prosty

root฀

pierwiastek

round฀brackets parentheses฀ trapezium฀

trapez

vertex฀

wierzchołek

sine฀

sinus

cosine฀

cosinus

tangent฀(n,฀adj)฀

styczna฀฀฀฀฀styczny

tangent฀of฀an฀angle฀

tangens฀kąta

cotangent฀of฀an฀angle฀

cotangens฀kąta฀฀

฀ Abbreviations:฀ n-noun-rzeczownik v-verb-czasownik adj-adjective-przymiotnik pl-plural-liczba฀mnoga

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(฀฀฀)

English++

Appendix B

Mathematical formulas

Many฀universities฀stress฀the฀importance฀of฀studying฀mathematics฀during฀computer฀ science฀courses,฀mainly฀in฀the฀first฀year.฀The฀point฀is฀simply฀not฀to฀make฀students฀ ^ learn฀something฀difficult฀and฀perhaps,฀somewhat฀boring฀but฀to฀give฀them฀the฀ability฀ to฀use฀the฀universal฀language฀of฀mathematics,฀without฀which฀computer฀science฀could฀ not฀exist.฀So,฀why฀not฀to฀learn฀mathematical฀formulas฀in฀English฀to฀enable฀you฀to฀use฀ them฀in฀the฀global฀world฀of฀science?

Listen to the recording ฀ 1.฀ ฀

a฀+฀b฀

฀

a฀plus฀b฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀

addition

2.฀ ฀

a฀-฀b฀

฀

a฀minus฀b฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀฀

฀subtraction

3.฀ ฀

a฀*฀b฀

฀

a฀multiplied฀by฀b฀฀฀฀฀฀฀

฀multiplication฀฀฀฀฀

4.฀ ฀

a฀/฀b฀

฀

a฀divided฀by฀b฀฀฀฀฀฀฀฀฀฀฀

division

5.฀ ฀

฀ ฀a฀

฀

not฀a

6.฀ ฀

a฀^฀b฀

฀

a฀and฀b

7.฀ ฀

a฀ ฀b฀

฀

a฀or฀b

8.฀ ฀

a฀ ฀b฀฀

฀

a฀is฀orthogonal/perpendicular฀to฀b

9.฀ ฀

a฀||฀b฀

฀

a฀is฀parallel฀to฀b

10.฀฀

a฀ ฀A฀

฀

a฀is฀contained฀in฀A฀

11.฀฀

a2฀

฀

a฀raised฀to฀the฀second฀power฀฀฀฀฀฀฀฀a฀squared

12.฀฀

ax฀

฀

a฀raised฀to฀the฀xth฀power฀฀฀a฀to฀the฀power฀of฀x

13.฀฀

a฀ ฀b฀

฀

a฀is฀less฀than฀or฀equal฀to฀b

14.฀฀

a฀>฀c฀

฀

a฀is฀greater฀than฀c

15.฀฀

2x฀+฀4฀=฀8฀

฀

2฀x฀plus฀4฀equals฀/is฀equal฀to฀8

16.฀฀

2/8฀=฀1/4฀

฀

2฀over฀8฀equals฀1฀over฀4

17.฀฀

|฀-5|฀=฀5฀

฀

the฀absolute฀value฀of฀-5฀equals฀5฀

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English++ 18.฀฀

log฀a฀b฀=฀c฀

฀

the฀logarithm฀of฀b฀to฀the฀base฀a฀equals฀c

19.฀฀

A฀ ฀B฀

฀

A฀includes฀B฀฀฀฀฀฀฀฀฀฀B฀is฀a฀subset฀of฀A

20.฀฀

฀x฀ ฀A฀฀฀x฀ ฀B฀ ฀

21.฀฀฀ 22.฀฀

220

฀฀฀฀ an฀

฀฀฀

for฀all฀x฀in฀A฀฀฀฀x฀is฀contained฀in฀฀฀B฀x฀is฀in฀B฀฀฀x฀lies฀in฀B

฀

the฀nth฀root฀of฀a฀฀฀฀฀฀฀฀฀฀square฀root฀฀฀฀฀฀฀฀฀฀

฀

a฀sub฀n

English++

Appendix C

Greek alphabet The฀Greek฀alphabet฀is฀the฀basis฀of฀what฀used฀to฀be฀a฀very฀important฀and,฀in฀some฀ways,฀ universal฀language฀in฀ancient฀Europe.฀Nowadays,฀this฀alphabet฀constitutes฀a฀significant฀ part฀of฀the฀universal฀language฀of฀mathematics.฀As฀mathematics฀is฀fundamental฀to฀most฀ modern฀sciences,฀with฀computer฀sc฀ience฀foremost฀among฀them,฀it฀is฀vital฀to฀be฀familiar฀฀ with฀it.

Listen to the recording ฀ Greek฀letter฀

English฀name

Α α฀

Alpha

Β β฀ Γ γ฀

∆ δ฀ Ε ε฀

Ζ ζ฀

Η η฀ Θ θ฀ Ιι฀

Κ κ฀ Λ λ฀

Μ µ฀ Ν ν฀ Ξ ξ฀

Ο ο฀

Π π฀ Ρ ρ฀

Beta Gamma Delta Epsilon Zeta Eta Theta Iota Kappa Lambda Mu Nu Xi Omicron Pi Rho

221

English++ Σ σ ς฀ Τ τ฀

Υ υ฀

Φ φ฀ Χ χ฀

Ψ ψ฀ Ω ω฀

222

Sigma Tau Upsilon Phi Chi Psi Omega

English++

English++ English for Computer Science Students

Glossary

223

English++

224

English++

English++ Glossary This฀ glossary฀ contains฀ entries฀ for฀ the฀ keywords฀ or฀ key฀ terms฀ cited฀ in฀ bold฀ in฀฀ English++฀book.฀They฀have฀been฀selected฀from฀the฀reading฀and฀listening฀texts฀and฀ then฀their฀definitions฀have฀been฀provided฀by฀the฀members฀of฀English++฀team.฀฀฀

agile฀development฀-฀a฀way฀of฀building฀ software฀

autonomous฀differential฀equation ฀

Agile฀Methodology฀-฀a฀particular฀฀

equations฀which฀does฀not฀depend฀on฀ the฀independent฀variable฀

method฀of฀producing฀software,฀฀ emphasizing฀self-organizing฀teams฀

-฀a฀system฀of฀ordinary฀differential฀

bandwidth฀-฀฀the฀amount฀of฀data฀that฀

and฀broad฀customer-programmer฀

can฀be฀transferred฀through฀a฀specific฀

contact

path฀in฀the฀network฀(usually฀฀

Agile฀Software฀Development฀-฀a฀conceptual฀

expressed฀in฀kb/s฀[kilo฀bits฀฀ per฀second])฀

framework฀for฀software฀development฀ which฀promotes฀development฀฀

Barok฀trojan฀-฀this฀trojan฀horse฀gathers฀

iterations฀throughout฀the฀life-cycle฀฀

information฀such฀as฀user฀name,฀IP฀฀

of฀the฀project฀

address฀and฀passwords,฀and฀attempts฀

alignment฀-฀the฀adjustment฀of฀an฀object฀

to฀send฀the฀information฀to฀the฀฀ creator฀of฀the฀virus

in฀relation฀to฀other฀objects,฀or฀a฀static฀ orientation฀of฀some฀object฀or฀set฀of฀

binary฀code฀-฀code฀using฀a฀string฀of฀฀ 8฀binary฀digits฀to฀represent฀characters

objects฀in฀relation฀to฀others฀ Api฀-฀a฀source฀code฀interface฀that฀an฀฀

BitTorrent฀-฀a฀protocol฀for฀sharing฀฀

operating฀system,฀library฀or฀service฀

and฀distributing฀computer฀files฀฀

provides฀to฀support฀requests฀made฀

via฀the฀Internet฀

by฀computer฀programs฀฀

bot฀-฀a฀program฀used฀on฀the฀Internet฀

artery฀-฀one฀of฀the฀tubes฀that฀carries฀

that฀performs฀a฀repetitive฀function฀ such฀as฀posting฀a฀message฀to

blood฀from฀the฀heart฀to฀the฀rest฀of฀ the฀body ASP฀(Action฀Server฀Pages)฀-฀Microsoft’s฀

฀

multiple฀฀news-groups฀or฀searching฀ for฀information฀or฀news

first฀server-side฀script฀engine฀for฀฀

botnet฀-฀a฀collection฀of฀software฀robots,฀

dynamically-generated฀web฀pages

or฀bots฀linked฀and฀cooperating฀with฀ each฀other

฀

225

English++ broadcast฀-฀the฀action฀of฀sending฀data฀ by฀one฀computer฀in฀the฀network฀to฀

in฀films,฀television฀programs,฀฀

all฀other฀computers฀that฀are฀available฀

commercials฀and฀simulation

inside฀the฀network฀ buffer฀-฀a฀region฀of฀memory฀used฀to฀฀

computer฀vision฀-฀a฀branch฀of฀artificial฀ intelligence฀that฀deals฀with฀computer฀

temporarily฀hold฀data฀while฀it฀is฀being฀

processing฀of฀images฀from฀the฀real฀

moved฀from฀one฀place฀to฀another

world

buffer฀cache฀-฀a฀collection฀of฀data฀฀ duplicating฀original฀values฀stored฀

confine฀-฀to฀define฀boundaries;฀to฀limit฀ the฀extent฀(of฀an฀activity)

elsewhere฀or฀computed฀earlier,฀where฀

contract฀-฀a฀legally฀binding฀exchange฀of฀

the฀original฀data฀is฀expensive฀to฀fetch฀

promises฀or฀agreement฀between฀฀

(owing฀to฀longer฀access฀time)฀or฀to฀

parties฀which฀is฀enforceable฀by฀law฀

compute,฀compared฀to฀the฀cost฀of฀฀ reading฀the฀cache bug฀-฀an฀error฀in฀software,฀something฀ that฀spoils฀the฀flow฀of฀the฀program฀ CAD฀-฀Computer฀Aided฀Design฀ Cauchy฀problem฀-฀see฀IVP circuit฀switching฀network฀-฀a฀network฀ in฀which฀computers฀establish฀a฀constant฀bandwidth฀connection฀before฀ they฀start฀to฀share฀any฀data฀ code,฀coding฀-฀refers฀to฀the฀process฀of฀

cookbook฀-฀a฀book฀of฀recipes฀and฀solutions฀ for฀different฀problems฀on฀writing฀ software,฀usually฀connected฀with฀a฀ particular฀programming฀language฀ and฀platform฀ correlate฀(with)฀-฀to฀have฀a฀close฀฀ similarity,฀connection฀or฀causal฀฀ relationship฀with฀ cyber฀vandalism฀-฀cyber฀attacks฀that฀฀ deface฀web฀pages cyber฀war฀-฀the฀usage฀of฀computers฀and฀

transforming฀a฀concept฀into฀a฀pro-

the฀Internet฀in฀conducting฀warfare฀in฀

gram฀code฀

the฀cyberspace

cognitive฀science฀-฀the฀scientific฀study฀ of฀mind฀or฀intelligence฀based฀on฀฀ relevant฀fields,฀including฀psychology,฀

database฀-฀฀software฀designed฀for฀฀ holding฀large฀amounts฀of฀data database฀schema฀-฀a฀description฀of฀the฀฀

philosophy,฀neuroscience,฀linguistics,฀

tables฀and฀views฀in฀a฀database฀฀

anthropology,฀computer฀science,฀and฀

together฀with฀the฀relationships฀฀

biology

between฀them฀

computational฀-฀adj.1.฀involving฀฀ computers,฀2.฀that฀can฀be฀computed฀ computational฀complexity฀-฀an฀area฀of฀

DBA฀-฀database฀administrator;฀the฀main฀ role฀of฀a฀database฀administrator฀has฀ to฀do฀with฀overseeing฀the฀installation฀

computer฀฀design฀dealing฀with฀the฀฀

and฀ongoing฀function฀of฀software฀

problems฀of฀algorithms฀and฀their฀฀

on฀a฀system฀designed฀for฀use฀by฀a฀

ability฀to฀solve฀a฀given฀problem฀

number฀of฀users

Computer฀Generated฀Imagery฀(CGI)฀-฀an฀

226

computer฀graphics)฀to฀special฀effects฀฀

decorator฀pattern฀-฀a฀design฀pattern฀that฀

application฀of฀the฀field฀of฀computer฀

allows฀new/additional฀behaviour฀to฀be฀

graphics฀(or,฀more฀specifically,฀3D฀

added฀to฀an฀existing฀class฀dynamically฀

English++ Denial฀of฀Service฀-฀a฀kind฀of฀cyber฀attack฀฀ -฀a฀programming฀methodology฀which฀is฀ which฀results฀in฀unavailability฀of฀฀

very฀closely฀connected฀with฀the฀Agile฀

service;฀it฀uses฀two฀methods:฀forcing฀

style฀

the฀targeted฀computer(s)฀to฀reset,฀thus฀

FFT฀-฀Fast฀Fourier฀transform

consuming฀its฀resources฀such฀that฀it฀

Firefox฀-฀one฀of฀the฀most฀popular฀web฀

can฀no฀longer฀provide฀its฀intended฀ service;฀or฀obstructing฀the฀฀

browsers฀(after฀Internet฀Explorer)฀ FOSS฀-฀the฀acronym฀for฀Free฀and฀Open฀

communication฀media฀between฀the฀

Source฀Software;฀the฀software฀that฀

intended฀users฀and฀the฀victim฀so฀

can฀be฀used,฀studied,฀and฀modified฀

that฀they฀can฀no฀longer฀communicate฀

without฀restriction฀

adequately฀ design฀pattern฀-฀a฀general฀repeatable฀฀

gamut฀-฀a฀complete฀range฀or฀฀extent฀ general฀solution฀-฀a฀general฀solution฀of฀

solution฀to฀a฀commonly฀occurring฀

a฀differential฀equation฀is฀the฀set฀of฀

problem฀in฀software฀design;฀a฀design฀

all฀of฀its฀particular฀solutions,฀often฀

pattern฀is฀not฀a฀finished฀design฀that฀

expressed฀using฀a฀constant฀C฀(or฀K)฀

can฀be฀transformed฀directly฀into฀

which฀could฀have฀any฀fixed฀value฀฀

code;฀it฀is฀a฀description฀or฀template฀ for฀how฀to฀solve฀a฀problem฀that฀can฀ be฀used฀in฀many฀different฀situations฀ desktop฀-฀a฀personal฀computer฀฀

Gnome฀-฀one฀of฀the฀biggest฀window฀฀ managers฀for฀Linux฀ GNU฀-฀a฀computer฀operating฀system฀฀ composed฀entirely฀of฀free฀software,฀

used฀at฀home฀or฀work฀(stationary)฀

initiated฀in฀1984฀by฀Richard฀Stallman฀

developer฀-฀person฀who฀develops฀the฀

Google฀-฀an฀American฀public฀corporation฀฀

software฀

whose฀domain฀is฀open-source฀฀

DFT฀-฀Discrete฀Fourier฀Transform

software฀and฀whose฀earning฀revenue฀

differentiable฀-฀a฀real฀function฀is฀said฀฀

from฀advertising฀related฀to฀its฀฀

to฀be฀differentiable฀at฀a฀point฀if฀its฀฀

Internet฀search,฀web-based฀e-mail,฀

derivative฀exists฀at฀that฀point฀

online฀mapping,฀office฀productivity,฀

differential฀equation฀-฀a฀mathematical฀ equation฀for฀an฀unknown฀function฀of฀ one฀or฀several฀variables฀that฀relates฀

social฀networking฀and฀video฀sharing฀ activities฀ GPL฀-฀a฀widely฀used฀free฀software฀

the฀values฀of฀the฀function฀itself฀and฀

license,฀originally฀written฀by฀Richard฀

of฀its฀derivatives

Stallman฀for฀the฀GNU฀project฀

discrete฀-฀not฀supporting฀or฀requiring฀

GUI฀(Graphical฀User฀Interface)฀-฀a฀type฀

the฀notion฀of฀continuity;฀discrete฀

of฀user฀interface฀which฀allows฀people฀

objects฀are฀countable฀sets฀such฀as฀

to฀interact฀with฀a฀computer฀and฀com-

integers

puter-controlled฀devices฀

downloading฀-฀getting/transferring฀files฀ (software,฀music,฀films,฀etc.)฀from฀a฀ remote฀computer฀via฀the฀Internet฀ extreme฀programming฀(XP)฀

hacktivism฀-฀combination฀of฀words:฀ “hack(er)”฀and฀“activism”฀ hardware฀-฀all฀the฀physical฀parts฀of฀the฀ computer฀

227

English++ heterogenous฀฀-฀consisting฀of฀various฀ parts฀that฀are฀very฀different฀from฀each฀ other heuristic฀hypothesis฀-฀a฀hypothesis฀that฀

kernel฀-฀the฀central฀component฀of฀most฀ computer฀operating฀systems฀(OS);฀ its฀functions฀include฀managing฀the฀

has฀a฀very฀high฀probability฀of฀being฀

system’s฀resources฀(the฀฀

true฀on฀the฀basis฀of฀reasoning฀and฀

communication฀between฀hardware฀

past฀experience

and฀software฀components)฀

homogeneous฀linear฀differential฀฀

keyframe฀-฀(or฀key฀frame)฀in฀animation฀

equation฀-฀a฀differential฀equation฀

and฀film฀making฀is฀a฀drawing฀which฀

is฀said฀to฀be฀homogeneous฀if฀there฀

defines฀the฀starting฀and฀ending฀

is฀no฀isolated฀constant฀term฀in฀the฀

points฀of฀any฀smooth฀transition฀

equation,฀e.g.,฀each฀term฀in฀฀

texture฀-฀a฀bitmap฀image฀a฀plied฀to฀a฀

a฀differential฀equation฀for฀y฀has฀y฀or฀

surface฀in฀computer฀graphics฀

some฀derivative฀of฀y฀in฀each฀term฀ identity฀map฀-฀a฀database฀access฀design฀ pattern฀used฀to฀improve฀performance฀

Linux฀kernel฀-฀Unix-like฀฀ operating฀system฀kernel฀ LiSP฀-฀The฀Linux฀Phone฀Standards฀

by฀providing฀a฀context-specific฀฀

Forum,฀a฀consortium฀founded฀by฀a฀

in-memory฀cache฀to฀prevent฀฀

group฀of฀telephony฀operators,฀device฀

duplicate฀retrieval฀of฀the฀same฀object฀

manufacturers,฀silicon฀and฀software฀

data฀from฀the฀database฀

vendors฀who฀have฀a฀strategic฀focus฀

incoherent฀-฀confused฀and฀inconsistent,฀ illogical฀ IVP฀(initial฀value฀problem)฀-฀an฀ordinary฀ differential฀equation฀together฀with฀฀ specified฀value,฀called฀the฀initial฀฀ condition,฀of฀the฀unknown฀function฀ at฀a฀given฀point฀in฀the฀domain฀of฀the฀ solution฀ Internet฀-฀a฀global฀network฀connecting฀ millions฀of฀computers฀ Internet฀provider฀-฀a฀company฀that฀sells฀ bandwidth฀and฀access฀to฀the฀Internet฀ interval฀-฀฀a฀set฀of฀real฀numbers฀with฀the฀ property฀that฀any฀number฀that฀lies฀฀ between฀two฀numbers฀in฀the฀set฀is฀ also฀included฀in฀the฀set;฀for฀example,฀

228

positive฀numbers฀is฀also฀an฀interval฀

on฀Linux฀telephony mainframe฀-฀computer฀used฀by฀large฀ companies฀for฀critical฀operations฀like฀ financial฀transaction฀processing฀ maintenance฀-฀“looking฀after”฀the฀written฀ software฀ malware฀-฀software฀designed฀to฀infiltrate฀ or฀damage฀a฀computer฀system฀฀ without฀the฀owner’s฀informed฀฀ consent mathematical฀model฀-฀an฀abstract฀model฀ that฀uses฀mathematical฀language฀to฀ describe฀a฀system matricize฀-฀changing฀sound฀into฀parts฀ and฀writing฀into฀a฀matrix matrix฀-฀a฀rectangular฀table฀of฀elements฀

the฀set฀of฀all฀numbers฀x฀satisfying฀0฀

(or฀entries),฀which฀may฀be฀numbers฀

RS agarwal quantitative aptitude book.pdf

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Form Mak 04 Keputusan Dan Umpan Balik Asesmen

Form Mak 04 Keputusan Dan Umpan Balik Asesmen
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Lembaga Sertifikasi Profesi – LSP BLK SURABAYA

FR-MAK- 04 : KEPUTUSAN DAN UMPAN BALIK ASESMEN Skema Sertifikasi

Pengoperasian Piranti Lunak

Administrasi Nomor Skema Sertifikasi

Nama Asesi : Tim Asesor :

Tanggal/Waktu Tempat

: :

Penjelasan untuk Asesor : 1. Asesor mengorganisasikan pelaksanaan asesmen berdasarkan metoda dan instrumen/sumber-sumber asesmen seperti yang tercantum dalam perencanaan asesmen. 2. Asesor melaksanakan kegiatan pengumpulan bukti serta mendokumentasikan seluruh bukti pendukung yang dapat ditunjukkan oleh Asesi sesuai dengan kriteria unjuk kerja yang dipersyaratkan. 3. Asesor membuat keputusan apakah Asesi sudah Kompeten (K), Belum kompeten (BK) atau Asesmen Lanjut (AL), untuk setiap kriteria unjuk kerja berdasarkan bukti-bukti. 4. Asesor memberikan umpan balik kepada Asesi mengenai pencapaian unjuk kerja dan Asesi juga diminta untuk memberikan umpan balik terhadap proses asesmen yang dilaksanakan (kuesioner). 5. Asesor dan Asesi bersama-sama menandatangani pelaksanaan asesmen. 6. Beri tanda ( ) pada kolom yang dipilih dengan simbul (*).

PENCAPAIAN KOMPETENSI: Judul Unit Kompetensi : TIK.OP01.001.01 Kode Unit Kompetensi : Mengetik Pada Papan Ketik (Keyboard) Standar

Elemen Kompeten si

1. Menggunakan keyboard komputer

Kriteria Unjuk Kerja

Bukti – Bukti (beri tanda √ bila tersedia dan X bila tidak tersedia/tidak mencukupi) Bukti Langsun g

Bukti Tidak Langsun g

Bukti Tambah an

Keputu san K

B PL K

1.1 Komponen keyboard komputer standar dapat diidentifikasi. 1.2 Penggunaan tombol huruf/angka dan tombol-tombol fungsi pada keyboard dapat dideskripsikan. 1.3 Pengetikan menggunakan keyboard dapat dilakukan.

2. Posisi jari tangan

2.1 Posisi jari tangan pada keyboard dapat dideskripsikan. 2.2 Teknik pengetikan dengan 10 jari dapat diidentifikasi. 2.3 Pengetikan dengan 10 jari dapat dipraktekkan.

3. Mengoperasikan fungsi lanjut pengetikan.

3.1 Pengetikan huruf besar (kapitalisasi) dan huruf kecil dapat dilakukan. 3.2

Pengetikan tanda baca dapat dilakukan.

KOMISI SERTIFIKASI BNSP-IA/2015

FORM MAK-04

Lembaga Sertifikasi Profesi – LSP BLK SURABAYA

3.3

Pengetikan simbol dapat dilakukan.

3.4

Mengetik cepat dapat dilakukan.

Judul Unit Kompetensi : TIK.OP02.002.01 Kode Unit Kompetensi : Mengoperasikan Printer

Elemen Kompeten si

1. Mempersiapkan pra- penyalaan komputer

Kriteria Unjuk Kerja

Bukti – Bukti (beri tanda √ bila tersedia dan X bila tidak tersedia/tidak mencukupi) Bukti Langsun g

1.1

Bukti Tidak Langsun g

Bukti Tambah an

Keputu san K

B PL K

Koneksi catu daya sudah tersambung.

1.2 Perangkat protektif seperti UPS dan stabilizer (jika ada) sudah dinyalakan. 1.3 Printer sudah tersambung dengan PC dan atau perangkat lain sesuai dengan petunjuk pada petunjuk penggunaan. 1.4 Semua peralatan sudah disiapkan untuk kondisi penyalaan normal (default).

2. Menyalakan dan menyiapkan penggunaan printer

2.1 Indikator penyalaan seperti lampu dan atau suara muncul secara benar sesuai dengan petunjuk penggunaan. 2.2 Tahapan inisialisasi berjalan sampai dengan kondisi yang menandakan printer siap pakai sesuai dengan petunjuk penggunaan. 2.3 Penyiapan lokasi objek operasi dari printer seperti tempat masuk dan keluarnya kertas. 2.4 Pemasangan kertas/transparan pada printer. 2.5 Pemasangan /penggantian pita/toner pada printer sesuai dengan petunjuk pada petunjuk penggunaan. 2.6 Pemilihan opsi atau penyesuaian (customization) melalui panel menu/tombol pada printer dapat dialkukan sesuai kebutuhan pemakaian printer.

3. Pengoperasian printer.

3.1 Printer sudah diaktifkan melalui alat piranti lunak (software tools) yang digunakan. 3.2 Pemilihan opsi, penyesuaian dan konfigurasi properti dapat dilakukan sesuai kebutuhan pemakaian printer melalui alat piranti lunak yang digunakan. 3.3 Printer dapat dioperasikan sesuai petunjuk penggunaan.

4. Mematikan printer, dan mengamati proses de-aktifasi hingga selesai

4.1 Semua kondisi/ setting pheriperal sudah dikembalikan untuk pematian secara normal/default sesuai dengan petunjuk penggunaan. 4.2 Tahapan de-aktifasi berjalan sampai dengan kondisi yang menandakan pheriperal yang digunakan sudah dalam kondisi mati. 4.3 Indikator seperti lampu dan atau suara akan tampak/terdengar secara benar sesuai dengan petunjuk penggunaan.

Judul Unit Kompetensi : TIK.OP02.004.01 Kode Unit Kompetensi : Mengoperasikan Piranti Lunak Pengolah Kata – Tingkat Dasar

KOMISI SERTIFIKASI BNSP-IA/2015

FORM MAK-04

Lembaga Sertifikasi Profesi – LSP BLK SURABAYA

Elemen Kompeten si

1. Mempersiapkan piranti lunak pengolah kata

2. Mengenali menu, membuat, membuka, menyimpan dokumen

Kriteria Unjuk Kerja

Bukti – Bukti (beri tanda √ bila tersedia dan X bila tidak tersedia/tidak mencukupi) Bukti Langsun g

Bukti Tidak Langsun g

Bukti Tambah an

Keputu san K

B PL K

1.1 Piranti lunak pengolah kata telah terinstalasi dan dapat berjalan normal. 1.2 Petunjuk penggunaan piranti lunak pengolah kata telah disediakan dan dipelajari. 1.3

Perangkat komputer sudah dinyalakan.

1.4

Piranti lunak pengolah kata dijalankan.

2.1 Menu-menu yang disediakan beserta tombol penyingkat (shortcut)-nya dikenali.

2.2 Fitur-fitur pengelolaan file/dokumen dapat digunakan, seperti: buat (create/new), simpan, buka, simpan dengan nama lain (save as). 2.3 Penyimpanan file/ dokumen menggunakan berbagai format yang dikenal, seperti: rtf, html, text. 3. Melakukan editing sederhana, isian berulang.

3.1 Fitur-fitur editing sederhana digunakan, seperti: mengetik huruf/ kata/ kalimat, memformat huruf/font, penjajaran teks (text alignment), penomoran, bullet, penggantian halaman, penggunaan kolom. 3.2 Fitur-fitur untuk bagian berulang pada dokumen dapat digunakan, seperti: header, footer, page numbering.

4. Mencetak dokumen

4.1 Dokumen dapat dicetak dengan parameter standar, seperti: seluruhnya, halaman tertentu saja, halaman yang sedang diedit, urutan halaman pencetakan. 4.2 Fitur-fitur pencetakan dapat digunakan, seperti: page setup, printer setup, print preview.

5. Membuat tabel.

5.1 Membuat (create), menambah/menghapus baris (insert/delete row), menambah/menghapus kolom (insert/delete column), tinggi baris (row high), lebar kolom (column width), dipahami dan diaplikasikan. 5.2 Membuat garis dengan berbagai jenis dan ukuran serta warna, membuat arsiran/shading dengan berbagai jenis dan warna serta motif.

Judul Unit Kompetensi : TIK.OP02.005.01 Kode Unit Kompetensi : Mengoperasikan Piranti Lunak Lembar Sebar (spreadsheet) – Tingkat Dasar Elemen Kompeten si

1. Mempersiapkan piranti lunak spreadsheet

Kriteria Unjuk Kerja

Bukti – Bukti (beri tanda √ bila tersedia dan X bila tidak tersedia/tidak mencukupi) Bukti Langsun g

Bukti Tidak Langsun g

Bukti Tambah an

Keputu san K

B PL K

1.1 Piranti lunak spreadsheet telah terinstalasi dan dapat berjalan normal 1.2 Petunjuk penggunaan piranti lunak spreadsheet sudah disediakan dan dipahami.

KOMISI SERTIFIKASI BNSP-IA/2015

FORM MAK-04

Lembaga Sertifikasi Profesi – LSP BLK SURABAYA

1.3 Perangkat komputer sudah dinyalakan dengan sistem operasi dan persyaratan sesuai dengan Manual Instalasi. 1.4 2. Mengenali menu, membuat, membuka, menyimpan file

Piranti lunak spreadsheet dijalankan.

2.1 Menu-menu yang disediakan beserta shortcut-nya dikenali. 2.2 Fitur-fitur pengelolaan file/spreadsheet dapat digunakan, seperti: buat (create/new), simpan, buka, simpan dengan nama lain (save as). 2.3 Penyimpanan file spreadsheet menggunakan berbagai format standar.

3. Melakukan editing sederhana, kolom dan baris.

3.1 Fitur-fitur pengubahan (editing) sederhana digunakan, seperti: mengetik huruf/kata/kalimat/angka, memformat huruf (font), text alignment, format data (text, date, number) dan presisi (tanda ribuan dan pecahan). 3.2 Fitur-fitur kolom dan baris dipahami dan diaplikasikan, seperti: menentukan lebar kolom, menentukan tinggi baris, membuat garis (border) dan arsiran atau warna (shading). 3.3 Fitur-fitur copy, cut dan paste diaplikasikan dengan berbagai pilihan, seperti: isi (value), format, formula atau semuanya. 3.4 Formula dan fungsi sederhana (yang sering digunakan), seperti: +, -, *, /, sum, avg.

4. Mencetak dokumen

4.1

Bagian yang ingin dicetak ditentukan

4.2 Lembar kerja dapat dicetak dengan menggunakan berbagai parameter, seperti: seluruhnya, area tertentu saja, area yang sedang diedit, urutan pencetakan. 4.3 Fitur-fitur pencetakan dapat digunakan, seperti: page setup, printer setup, header dan footer, print preview.

Umpan balik terhadap pencapaian unjuk kerja :

Identifikasi kesenjangan pencapaian unjuk kerja :

Saran tindak lanjut hasil asesmen :

Rekomendasi Asesor :

KOMISI SERTIFIKASI BNSP-IA/2015

Asesi : Nama

FORM MAK-04

Lembaga Sertifikasi Profesi – LSP BLK SURABAYA

Tanda Tangan & Tanggal

Asesor : Nama No. Reg. Tanda Tangan & Tanggal

KOMISI SERTIFIKASI BNSP-IA/2015

FORM MAK-04

Antena dan Propagasi Gelombang
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Napkin Folding Styles
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Republic of the Philippines ST. JOSEPH VOCATIONAL AND TECHNICAL TRAINING AND ASSESSMENT CENTER INC. The Tech-Voc School of the Archdiocese of Capiz Brgy. Lawaan, Roxas City A Detailed Lesson Plan in Technology and Livelihood Education (FOOD AND BEVERAGE SERVICES)

I. OBJECTIVES At the end of the lesson, the students should be able to: 1. Identify the different styles of napkin folding. 2. Perform the different styles of napkin folding 3. Appreciate the importance of different styles of napkin folding.

II. SUBJECT MATTER NAPKIN FOLDING STYLES III. TEACHING MATERIALS Instructional Materials: PowerPoint, Visual Aids, Pictures, Model Reference: Food and Beverage Services NC II Module IV. PROCEDURE Teacher’s Activity

Student’s Activity

A. Preparation 1. Daily Routine: a. Cleaning the room b. Opening Prayer c. Checking the attendance d. Energizer B. Motivation (Groupings) Kindly group your selves into 2 groups. We will have a group activity: (4 pics 1 word) Instruction: I have an envelope to be given in each group and that will be your “4 pics 1 word” activity. I will give you 2 minutes to do the task. Each group who got the correct answer will be given plus points to your quiz.

Yes Ma’am (Group Activity) Yes mam, about Napkin folding In table setting

Showing different styles of napkin folding and followed by asking question: 1. Do you have any idea what is our topic for today? Very Good! 2. Where are you usually seen this set-up? 3. Who among you already know how to make this napkin folds?

Napkin folding actually is the art of folding table napkins for neatness and beauty uses.

3 different sizes: small, medium and large.

C. Presentation Today we are going to learn about different styles of napkin folding.

20”x 20” square

Any idea what is napkin folding? Very Good and also A crisp, starched napkin folded in an interesting shape often makes dining more festive. Do you have any idea what are the sizes of table napkin we use? Very Good! It depends upon the uses of table napkin. Example the tea napkin, breakfast table napkin and formal/ Dinner table napkin. Any idea what is the size of table napkin we use in formal dinner? Very good NAPKIN FOLDING STYLES a. Candle b. Pyramid c. Rose bud d. Heart Fold e. Tree Fold f. Diamond g. Envelope Now let’s start with the : 1. Candle ( The teacher demonstrate step by step and students read the instruction and will also follow) Kindly read the steps?

1. Fold napkin in half diagonally. 2. Fold down base 1/3 of the way. 3. Turn napkin over and roll from bottom to top. 4. Tuck corners inside cuff at base of fold and stand. 5. Turn one layer of point down. 1. 2. 3. 4.

Fold napkin in half diagonally. Fold corners to meet top point. Turn napkin over and fold in half. Pick up at centre and stand on base of triangle

1. Fold napkin in half diagonally. 2. Fold corners to meet at top point. 3. Turn napkin over and fold bottom 2/3 way up. 4. Turn napkin around and bring corners together, tucking one into the other. 5. Turn napkin around and stand on base. 6. And set on base. 1. Iron the napkin flat

2. Pyramid

3. Rosebud

4. Heart Fold

2. Fold the napkin in half 3. Fold the napkin in half again 4. Fold the right hand side up vertically. Repeat with the left side.

1. Fold it twice to get a smaller square. 2. Fold up each layer to the top and be sure to leave one inch between each fold. 3. Flip the whole thing over, holding the folds. Fold both sides together and align the top of each panel to form a triangular space at the top of the napkin 4. Flip back the napkin (remember to hold it tight so it doesn’t unfold). 5. Fold the upper layer to the top to form a peak of your tree. Hide lower layers’ tips underneath the upper folds.

5. Tree Fold

6. Diamond

7. Envelope

1. Lay the napkin face-down in front of you. 2. Fold the napkin in half and orient the open end toward you. 3. Fold the napkin into quarters. 4. Fold the top-most layer of the napkin in half diagonally – up and to the left. 5. Fold the next layer of napkin diagonally up to the left, stopping slightly before the last fold to create an even, staggered effect. 6. Repeat by folding up next layer of napkin to a point just before the last one. 7. And one last time with one last layer. Keep them as uniform as you can. 8. Fold both sides of the napkin under and in to create an even, staggered diamond effect on then napkin. 1. Iron the napkin flat. 2. Fold the napkin in half so that the open end is facing away from you. 3. On the right hand side of the napkin, fold both corner edges towards the center to form two triangles. 4. Fold the left side of the napkin over in half to meet the right. 5. Take both triangle layers and fold both over to create the napkin envelope fold.

IV. Generalization: 1. What is Napkin Folding? 2. What size of table napkin use in formal dinner? 3. What are the different styles of napkin folding you’ve learned?

V. Application: Students will practice and perform different kinds of napkin folds as many as they can and only in 2 minutes.

VI. Evaluation: In evaluating your Napkin Folds is guided with the score of the following: Scale: 1 = Needs Improvement 5 = Best

Criteria Number of Napkin Folds Crisp, neat folds Visual appeal Demonstration fold same as display Total Score

VII. Assignment: 1. What is silverware? 2. Give some care of silverware. 3. Cut pictures of silverware.

Scores 3 2

Prepared by: MAY S. BONITA. LPT TLE Applicant

Letter of Cancellation-Atp
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06/28/2019 To, Ms. Corazon R. Balinas Revenue District Officer Bureau of Internal Revenue (RDO.041) Boni Avenue, Mandaluyong City

Subject: Cancellation of Authority to Print

Dear Ms. Balinas,

This letter is written to you to inform the cancellation of Authority to Print with your organization dated (——–) with reference of______ The reason for ATP cancellation is our Certificate of Registration was amended from Non-VAT to Vatable entity. I request you to take call the necessary actions as soon as possible. Please consider this letter as our notice for ATP cancellation between your organization and our organization.

Feel free to contact me for any further clarifications. (942-4821)

Thanking you, Sincerely,

Jeffrey G. Navarro Property Manager Tivoli Garden Residences Corporation #69 Coronado St., Brgy. Hulo, Mandaluyong City

Oh Pretty Woman
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Author/Uploader: Jose Henao

Roy Orbison – Oh, Pretty Woman Introdução: E|—————————————————–| B|—————————————————–| G|—————————————————–| D|———0—————0—————————| A|——-2—————2—————————–| E|-0-0-4———–0-0-4——————————-| E|—————————————————–| B|—————————————————–| G|—————————————————–| D|———0-4-2-0———0-4-2-0———————| A|——-2—————2—————————–| E|-0-0-4———–0-0-4——————————-| E|—————————————————–| B|—————————————————–| G|—————————————————–| D|———0-4-2-0———0-4-2-0———————| A|——-2—————2—————————–| E|-0-0-4———–0-0-4——————————-| Primeira Parte: A Pretty woman F#m Walkin’ down the street A Pretty woman F#m The kind I like to meet D Pretty woman E I don’t believe you You’re not the truth No one could look as good as you Mercy A Pretty woman F#m Won’t you pardon me A Pretty woman F#m I couldn’t help but see D Pretty woman E That you look lovely

(Riff)

As can be Are you lonely just like me? Segunda Parte: Dm

Pretty woman G Stop awhile C Pretty woman Am Talk awhile Dm Pretty woman G C Give your smile to me Dm Pretty woman G Yeah, yeah, yeah C Pretty woman Am Look my way Dm Pretty woman G C Say you’ll stay with me Terceira Parte: F#m ‘Cuz I need you D E I’ll treat you right A F#m Come with me baby D E Be mine tonight (Riff) Quarta Parte: A Pretty woman F#m Don’t walk on by A Pretty woman F#m Don’t make me cry D

(Riff)

Pretty woman E Don’t walk away, hey, ok If that’s the way it must be, ok I guess I’ll go on home, it’s late There’ll be tomorrow night, but wait What do I see? (Riff) Is she walkin’ back to me? Yeah, she’s walkin’ back to me Oh, oh, pretty woman —————– Acordes —————-A = X 0 2 2 2 0 Am = X 0 2 2 1 0 C = X 3 2 0 1 0 D = X X 0 2 3 2 Dm = X X 0 2 3 1 E = 0 2 2 1 0 0 F#m = 2 4 4 2 2 2 G = 3 2 0 0 0 3

MAS 06 Budgeting With Probability Analysis

MAS 06 Budgeting With Probability Analysis
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ReSA – THE REVIEW SCHOOL OF ACCOUNTANCY CPA Review Batch 41  May 2021 CPA Licensure Examination  Week No. 6

MANAGEMENT ADVISORY SERVICES

C.P. Lee  E.S Arañas  K.L. Manuel

MAS-06: BUDGETING WITH PROBABILITY ANALYSIS BUDGET – is a realistic quantitative plan useful for planning and controlling company expenses, cash flows and earnings for a specific period. The term budgeting refers to the process of coming up with budgets. BUDGET PERIOD

The length of time for which a budget is to be prepared and implemented

BUDGET COMMITTEE

Key management personnel responsible for drafting the budget manual, and coordinating/approving budgets submitted by managers.

BUDGET MANUAL

A written description on how to prepare budgets that includes a planning calendar and distribution instructions for budget schedules.

AUTHORITATIVE BUDGETING (Top-Down Budgeting)

A process wherein budgets are prepared by top management with little or no inputs from operating personnel (i.e., imposed budgeting)

PARTICIPATORY BUDGETING (Bottom-Up Budgeting)

A process wherein budgets are developed through joint decisions by top management and operating personnel (i.e., consensus budgeting)

ZERO-BASED BUDGETING

A process of starting over each budget and justifying each budgeted item as if the programs involved were being proposed for the first time every period

CONTINUOUS BUDGET (Rolling Budget)

An incremental budget that adds the current period and drops the older period to maintain a constant budget period of usually 12 months.

KAIZEN BUDGETING

A process that assumes continuous improvement of products and/or processes so that budgets are not based on existing system but on changes to be made.

ACTIVITY BASED BUDGETING

A process that applies mostly Activity-Based Costing (ABC) principles and procedures to come up with budgets A process wherein a product’s revenues and expenses are budgeted over its entire life cycle from R&D to production to marketing to customer service. A long-term budget based on the identifications of action plans to achieve company goals and, ultimately, its mission.

LIFE-CYCLE BUDGETING STRATEGIC BUDGET BUDGETARY SLACK

A practice of underestimating revenues or overestimating costs to make budget targets easily achievable in order to project a seemingly “good” performance.

STATIC BUDGET (Fixed Budget)

A budget prepared for a single level of activity that does not change even when actual activity differs from planned activity.

FLEXIBLE BUDGET (Variable Budget)

A budget that adjusts revenues and costs when actual activity differs from the planned activity stated in the fixed budget.

MASTER BUDGET (Pro-Forma Budget) (Comprehensive Budget)

A static budget that is based on the comprehensive plan for the overall activities of a company. The major components of a master budget are:  OPERATING budget – sales forecast, sales budget, production budget, inventory budget, CGS budget, selling & administrative expense budget  FINANCIAL budget – cash budget, working capital budget, capital expenditures budget*, pro-forma balance sheet, pro-forma statement of cash flows * The capital expenditures budget, prepared mainly for the acquisition and maintenance of long-term assets, may be shown as a separate major component of the master budget, alongside operating and financial budgets. Forced Planning  Coordination  Communication  Motivation  Efficient Allocation of Resources  Progress Check  Benchmark for Performance Evaluation

USES of BUDGETS

PROBABILITY ANALYSIS  PROBABILITY is a mathematical expression of doubt or assurance about the occurrence of a chance event.  The probability of a particular event ranges from 0 (never) to 1 (always).  A probability of 0 means the event cannot occur; a probability of 1 means the event is certain to occur.  PROBABILITY ANALYSIS is commonly used in planning to determine the likelihood of a specific event occurring when several outcomes are possible in order to reduce the level of uncertainty in decision making  EXPECTED VALUE uses probabilities as weights in computing the average or mean of possible outcomes.  JOINT PROBABILITY, determined by multiplying the probability of the first event by the conditional probability of the second event, is the probability of an event occurring given that another event has already occurred.  Decision-making under CERTAINTY: for each decision alternative, there is only one event with 100% chance.  Decision-making under conditions of RISK: the probability distribution of possible future events is known.  Decision-making under conditions of UNCERTAINTY: each decision alternative has several possible outcomes and the probability distribution of possible future events is not known and must be determined subjectively.  DECISION TREE is a diagram that shows decision alternatives and the possible outcomes of each decision along with their associated expected values and probabilities.  DECISION (Pay-off) TABLE shows the decision, outcomes with their probabilities and the monetary values of all possible decision-outcome combinations.  PERFECT INFORMATION is the knowledge that a future event will occur with certainty.  EXPECTED VALUE (EV) of PERFECT INFORMATION is the difference between expected value with perfect information (i.e., best results given perfect information) and expected value without perfect information. EV of Perfect Information = EV with Perfect Information – EV without Perfect Information

Page 1 of 10

0915-2303213  www.resacpareview.com

MAS-06

ReSA – THE REVIEW SCHOOL OF ACCOUNTANCY Week No. 6: BUDGETING with PROBABILITY ANALYSIS EXERCISES: BUDGETING with PROBABILITY ANALYSIS

1. Production & Inventory Budget DMD Company has budgeted sales at P 100,000 and expects a profit of 10% of the sales. Expenses are estimated as follows: selling = 10% of sales; administrative = 15% of sales. Labor is expected to be 40% of the total manufacturing costs. Factory overhead is to be applied at 75% of direct labor costs. Inventories are to be as follows: January 1 December 31 Materials Work-in-process Finished goods

P 4,000 2,500 5,000

P 1,500 7,500 10,000

REQUIRED: Determine the budgeted amount for: A) Cost of goods sold C) Factory overhead B) Total manufacturing cost D) Materials purchases 2. Sales & Accounts Receivable Budget Past collections experienced by BJS Company indicate that 60% of the sales billed in a month are collected during the month of sales, 30% are collected in the following month, and 10% are collected in the second following month. The following are the projected sales for next year: January P 480,000 February P 420,000 March P 500,000 April P 550,000 May P 600,000 REQUIRED: Determine the following: A) Budgeted collections during the month of B) Budgeted collections during the month of C) Projected accounts receivable balance on D) Projected accounts receivable balance on

March. May. April 1. June 1.

3. Merchandise Purchases Budget CIT Merchandising has budgeted the following sales for the 2 nd quarter of 2021: April P 123,500 May 156,000 June 208,000 Other budgeted estimates are:  All merchandises are to sell at its invoice cost plus 30% mark-up.  Beginning inventories of each month are budgeted at 40% of that particular month’s projected cost of goods sold. REQUIRED: Determine the projected amount for: A) Merchandise purchases in April. B) Merchandise purchases in May. 4. Pro-forma Statement of Cash Flows Sugbu Company presents these data to be used as basis for the pro-forma Statement of Cash Flows. 1) Customer sales receipts for P 870,000 2) Purchase of machinery and equipment for P 125,000 cash. 3) Settlement of income taxes of P 110,000 4) Sale of investment securities for P 500,000. 5) Payment of dividends of P 600,000. 6) Receipt of rentals of P 105,000. 7) Issuance of 500 shares of common stock for P 250,000. 8) Payment of P 100,000 due to suppliers and payroll to employees. 9) Purchase of land for plant site for P 550,000 cash that was borrowed from a bank. 10) Payment of P 450,000 for treasury shares. REQUIRED: Determine the projected amounts of the following: A) Net cash provided by operating activities C) Net cash used in financing activities B) Net cash used in investing activities D) Net cash increase or decrease 5. Expected Value SDA Company prepared the following probability distribution describing the relative likelihood of monthly sales volume levels and related profit (loss) for its lone product that sells for P 50 per unit: Sales volume Probability Profit (Loss) 5,000 10% (P 70,000) 12,000 20% 10,000 18,000 40% 60,000 24,000 20% 100,000 30,000 10% 140,000 REQUIRED: Using the expected value approach, A) How much is the budgeted sales for the month? B) What is the expected value of the monthly profit?

Page 2 of 10

MAS-06

ReSA – THE REVIEW SCHOOL OF ACCOUNTANCY Week No. 6: BUDGETING with PROBABILITY ANALYSIS

6. Indifference Point under Probability Analysis Eloy Company plans to introduce a new product that requires an initial cash investment of P 440. If the product becomes successful, the net cash inflow is forecasted at P 800. However, if the product becomes a failure, net cash inflow is estimated at P 200. REQUIRED: A) If the success rate is 70%, what is the value of act “to invest?” B) What probability-percentages should be assigned to the events ‘success’ and ‘failure’ to be indifferent between the two actions “to invest” and “not to invest?” 7. Joint Probability CGH Company has three sales departments, each contributing the following percentages of total sales: clothing, 50%; grocery, 30%; and hardware, 20%. Each department has had the following average annual damaged goods rates: clothing, 2%; grocery, 10%; and hardware, 5%. A random corporate audit has found a weekly damaged goods rate of sufficient magnitude to alarm CGH’s management. REQUIRED: Determine the probability in percentage that the damage occurred in the: A) Clothing department B) Grocery department C) Hardware department 8. Decision Tree A wine maker must decide whether to harvest grapes now or in four weeks. Harvesting now will yield 100,000 bottles of wine, netting P 2 per bottle. If the wine maker waits for four weeks and weather turns cold (probability: 20%), the yield will be cut in half but net P 3 per bottle. If the weather does not turn cold, the yield depends on rain. With rain (probability: 50%), a full yield netting P 4 per bottle will result. Without rain, there will still be a full 100,000-bottle yield, but the net amount will be P 3 per bottle only. REQUIRED: Determine the optimal expected value.

NOW

________________

D LATER (4 weeks)

COLD (

): __________________

NOT ( COLD

)

RAIN (

): __________________

NO ( RAIN

): _____________________

9. Decision (Payoff) Table ESA Dealers, Inc. is contemplating on how many units of cars to order to meet the customer demands for the month based on the following projection: Demand Probability 0 unit 10% 1 unit 50% 2 units 40% The profit for each unit sold is P 200,000 while the carrying cost for each unit of unsold car is P 50,000. REQUIRED: How many units of cars should ESA order and why?

Decision Alternative Stock 0 unit Stock 1 unit Stock 2 units

States of Nature (based on demand) 0 unit (10%) 1 unit (50%) 2 units (40%)

Expected Value

10. Perfect Information Assume that ESA Dealers in No. 9 would maximize profits if the company were able to obtain additional information that can determine exactly what all potential customers intended to do for this month (i.e., ESA has perfect information). REQUIRED: A) What is the expected value with perfect information? B) What is the expected value of perfect information? C) What maximum amount is ESA willing to pay for the additional information?

Page 3 of 10

MAS-06

ReSA – THE REVIEW SCHOOL OF ACCOUNTANCY Week No. 6: BUDGETING with PROBABILITY ANALYSIS

WRAP-UP EXERCISES 1. In a typical planning process, which of the following would be completed last? a. Vision and mission c. Tactical goals b. Strategic objectives d. Operational plans 2. In the budgeting process, top management a. Should only be involved in the approval process b. Needs to be involved, including using the budget process to communicate goals c. Lacks the detailed knowledge of the daily operations and should limit their involvement d. Need to separate the budgeting process and business planning process into two separate processes 3. Coordinating the preparation of budget is the responsibility assigned to which of the following? a. Top management c. Accounting department b. Budget committee d. Lower levels of management 4. Which is an advantage of authoritative budgeting over participative budgeting? a. Longer time cycle in the budgeting process b. Stronger commitment from lower level of management c. Greater flow of information from bottom to top management d. More emphasis on strategic plans and avoidance of budgetary slacks 5. The master budget usually begins with the a. Production budget c. Financial budget b. Operating budget d. Sales forecast 6. The production budget process usually begins with the a. Sales budget c. Direct materials budget b. Direct labor budget d. Manufacturing overhead budget 7. Which of these budgets is usually prepared first? a. Production budget c. Cash disbursements budget b. Materials purchases budget d. Cash budget 8. All of the following are considered operating budgets, EXCEPT a. Cash budget c. Purchases budget b. Sales budget d. Production budget 9. Which of the following budgets is based on many other master budget components? a. Direct labor budget c. Sales budget b. Overhead budget d. Cash budget 10. Biden Inc. has projected sales to be P 260,000 in June, P 270,000 in July and P 300,000 in August. Biden collects 30% of a month’s sales in the month of sale, 50% in the month following the sale, and 20% in the second month following the sale. What is the accounts receivable balance on August 31? a. P 90,000 c. P 264,000 b. P 210,000 d. Some other number 11. Dems Inc. has projected sales: February, P 10,000; March, P 9,000; April, P 8,000; May, P 10,000; and June, P 11,000. Dems has 30% cash sales and 70% sales on account. Accounts are collected 40% in the month following the sale and 55% collected the second month. What would be the total cash receipts in May? a. P 3,000 c. P 8,705 b. P 8,150 d. Some other number 12. Donald Company has the following historical pattern on its credit sales: 70% collected in the month of sale 15% collected in the first month after sale 10% collected in the second month after sale 4% collected in the third month after sale 1% uncollectible The sales on open account have been budgeted for the last six months of 2021 are shown below: July P 60,000 August 70,000 September 80,000 October 90,000 November 100,000 December 85,000 What would be the estimated total cash collections during the fourth calendar quarter from sales made on open account within the fourth calendar quarter? a. P 172,500 c. P 251,400 b. P 230,000 d. P 265,400 13. Nevada Company manufactures a single product. The company keeps inventory of raw materials at 50% of the coming month’s budgeted production. Each unit of product requires 3 pounds of materials. The production budget is (in units): May, 1,000; June, 1,200; July, 1,300; August, 1,600. Determine the raw materials purchases in July. a. 1,450 pounds c. b. 2,400 pounds d.

Page 4 of 10

3,900 pounds Some other number

MAS-06

ReSA – THE REVIEW SCHOOL OF ACCOUNTANCY Week No. 6: BUDGETING with PROBABILITY ANALYSIS

14. Trump Company has budgeted sales of 24,000 finished units for the forthcoming 6-month period. It takes 4 lbs. of direct materials to make one finished unit. Given the following: Finished Units Direct Materials (pounds) Beginning inventory 14,000 44,000 Target ending inventory 12,000 48,000 How many pounds of direct materials should be budgeted for purchase during the 6-month period? a. 88,000 c. 96,000 b. 92,000 d. 100,000 15. GOP Co. has projected sales to be P 60,000 in January, P 75,000 in February, and P 80,000 in March. GOP wants to have 25% of next month’s sales needs on hand at the end of a month. If GOP has an average gross profit of 40%, what are the February purchases? a. P 30,500 c. P 46,250 b. P 45,750 d. P 76,250 16. Red Co. is preparing its cash budget for the next month based on the following projections: Sales P 1,500,000 Gross Profit Rate 25% Decrease in Inventories P 70,000 Decrease in Accounts Payable for Inventories P 120,000 What will be the estimated cash disbursements for inventories? a. P 935,000 c. P 1,055,000 b. P 1,050,000 d. P 1,175,000 17. Blue Company has prepared the flexible budget formula for production costs: costs = 340,000 + 9X, where X is the number of units produced. Blue produced 20,000 units at a total cost of P 490,000. What is the variance of actual costs from budgeted costs (i.e., budget variance)? a. P 150,000 favorable c. P 30,000 unfavorable b. P 30,000 favorable d. P 90,000 unfavorable 18. The use of standard costs in the budgeting process signifies that an organization has most likely implemented a a. Capital budget c. Zero-based budget b. Flexible budget d. Static budget SELF-TEST QUESTIONS – with suggested answers (Sources: CMA/CIA/RPCPA/AICPA/Various test banks) D

2. A 3. A

C D

4. 5.

Which of the following is NOT an advantage of budgeting? a. It requires managers to state their objectives. b. It facilitates control by permitting comparisons of budgeted and actual results. c. It facilitates performance evaluation by comparing budgets with actual results. d. It provides a check-up device that allows managers to keep close tabs on their subordinates. Budgets are a necessary component of financial decision making because they provide a (n) a. Efficient allocation of resources c. Means to check managerial discretion b. Means to use all the firm’s resources d. Automatic corrective mechanism for errors In an organization that plans by using comprehensive budgeting, the master budget is a. A compilation of all the separate operational and financial budget schedules of the organization b. The booklet containing budget guidelines, policies and forms to use in the budgeting process c. The current budget updated for operations for part of the current year d. A budget for a non-profit entity after it is approved by the appropriate authoritative body The sales budget is classified as a. A financial budget c. An operating budget b. A flexible budget d. A program budget Using the concept of ‘expected value’ in sales forecasting means that the sales forecast to be used is a. Developed using the indicator method. b. The sum of the sales expected by individual c. Based on expected selling prices of the products d. Based on probabilities Ohio Company developed the following sales forecasts and associated probabilities.

Sales Forecast P P P P

B 7. D

600,000 650,000 700,000 800,000

Probability 10% 50% 35% 5%

What is the expected value of sales? a. P 650,000 c. P 667,500 b. P 670,000 d. P 800,000 Which of the following equations can be used to budget purchases? (BI = Beginning inventory, EI = ending inventory desired, CGS = Budgeted cost of goods sold) a. Budgeted purchases = CGS + BI – EI c. Budgeted purchases = CGS + EI + BI b. Budgeted purchases = CGS + BI d. Budgeted purchases = CGS + EI – BI

Page 5 of 10

ReSA – THE REVIEW SCHOOL OF ACCOUNTANCY

MAS-06

Week No. 6: BUDGETING with PROBABILITY ANALYSIS 8. C 9. D 10. B 11.

D 12.

B 13.

C 14.

B 15.

D 16. B

17. D 18.

Colorado Company desires an ending inventory of P 60,000. It expects sales of P 120,000 and has a beginning inventory of P 40,000. Cost of sales is 60% of sales. Budgeted purchases are a. P 60,000 c. P 92,000 b. P 72,000 d. P 132,000 Individual budget schedules are prepared to develop an annual comprehensive or master budget. The budget schedule that would provide the necessary input data for the direct labor budget would be the a. Sales forecast c. Schedule of cash receipts and disbursements b. Raw materials purchases budget d. Production budget South Dakota Company budgets sales of 22,000 units for January, 30,000 for February. The budgeted beginning inventory for January 1 was 7,000 units. South Dakota desires an ending inventory equal to one-half of the following month’s sales needs. What is the budgeted production for January? a. 37,000 units c. 26,000 units b. 30,000 units d. 14,000 units New Mexico Company plans to sell 24,000 units of Product A in July and 30,000 units in August. Sales of Product A during June were 25,000 units. Past experience has shown that end-of-month inventory must equal 3,000 units plus 30% of the next month’s sales. On June 30, this requirement was met. Based on these data, how many units of Product A must be produced during the month of July? a. 28,800 c. 24,000 b. 22,200 d. 25,800 Florida keeps its inventory of finished goods at 75% of the coming month’s budgeted sales and inventory of raw materials at 50% of the coming month’s budgeted production needs. Each unit of product requires 2 pounds of materials. The production budget is, in units: May, 1,000; June, 1,200; July, 1,300; August, 1,600. What would be the raw material purchases in June? a. 1,525 pounds c. 2,800 pounds b. 2,500 pounds d. 3,050 pounds New Jersey Co. is budgeting sales of 53,000 units of product A1 for 2021. The manufacture of one unit of A1 requires 4 kilos of chemical Z5. During 2021, New Jersey plans to reduce the inventory of Z5 by 50,000 kilos and increase the finished goods inventory of A1 by 6,000 units. There is no work-in-process inventory. How many kilos of Z5 is New Jersey budgeting to purchase in 2021? a. 138,000 c. 186,000 b. 162,000 d. 238,000 Washington Company has the following 2021 budget data: Beginning finished goods inventory 40,000 units Sales 70,000 units Ending finished goods inventory 30,000 units Direct materials P 10 per unit Direct labor P 20 per unit Variable factory overhead P 5 per unit Fixed factory overhead P 80,000 What are the 2021 total budgeted production costs? a. P 2,100,000 c. P 2,240,000 b. P 2,180,000 d. P 2,320,000 Montana Company’s budget contains the following information: Units Beginning finished goods inventory 85 Beginning work-in-process in equivalent units 10 Desired ending finished goods inventory 100 Desired ending work-in-process in equivalent units 40 Projected sales 1,800 How many equivalent units should Montana plan to produce? a. 1565 c. 1815 b. 1800 d. 1845 The information contained in a cost of goods manufactured budget most directly relates to the a. Materials used, direct labor, overhead applied, and ending work-in-process b. Materials used, direct labor, overhead applied, and work-in-process inventories budgets c. Materials used, direct labor, overhead applied, and work-in-process inventories, and finished goods inventories budgets d. Materials used, direct labor, overhead applied, and finished goods inventories budgets Maine Co. makes payments for purchases 30% during the month of purchase and the remainder the following month. April purchases are projected to be P 80,000; May purchases will be P 120,000. What will be the cash payments on account for May? a. P 36,000 c. P 84,000 b. P 54,000 d. P 92,000 Nebraska Company, a merchandising firm, is preparing its master budget and has gathered the following data to help budget cash disbursements: Cost of goods sold P 1,680,000 Desired decrease in inventories 70,000 Desired decrease in accounts payable 150,000 All of the accounts payables are for inventory purchases and all inventories are purchased on account. What are the estimated cash disbursements for inventories for the budget period? a. P 1,460,000 c. P 1,900,000 b. P 1,600,000 d. P 1,760,000

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MAS-06

ReSA – THE REVIEW SCHOOL OF ACCOUNTANCY Week No. 6: BUDGETING with PROBABILITY ANALYSIS

Items 19 and 20 are based on the following information Operational budgets are used for planning and controlling its business activities. Data regarding a company’s sales for the last 6 months of the year and its projected collection patterns are shown below: Forecasted sales July P 775,000 August 750,000 September 825,000 October 800,000 November 850,000 December 900,000 Types of sales Cash sales Credit sales

19. C 20. B 21.

C D

22. 23.

D 24. C 25. B

26.

27. D

20% 80%

Collection Pattern for Credit Sales In the month of sale 40% In the first month following the sale 57% Uncollectible 3% The cost of merchandise averages 40% of its selling price. The company’s policy is to maintain an inventory equal to 25% of the next month’s forecasted sales. The inventory balance at cost is P 80,000 as of June 30. The budgeted cost of the company’s purchases for the month of August would be a. P 302,500 c. P 307,500 b. P 305,000 d. P 318,750 The company’s total cash receipts from sales and collections on account that would be budgeted for the month of September would be a. P 757,500 c. P 793,800 b. P 771,000 d. P 856,500 Alabama Consortium is constructing a corporate planning model. Cash sales are 30% of the company’s sales, with the remainder subject to the following collection pattern: One month after sale 60% Two months after sale 30% Three months after sale 8% Uncollectible 2% If Sn is defined as total sales in month ‘n,’ which one of the following expressions correctly describes Alabama’s collection on account in any given month? a. 0.6 S n-1 + 0.3 S n-2 + 0.08 S n-3 c. 0.42 S n-1 + 0.21 S n-2 + 0.056 S n-3 b. 0.42 S n+1 + 0.21 S n+2 + 0.056 S n+3 d. 0.6 S n-1 + 0.3 S n-2 + 0.08 S n-3 – 0.02 S The cash receipts budget includes a. Funded depreciation c. Extinguishment of debt b. Operating supplies d. Loan proceeds The Pennsylvania Company is preparing its cash budget for the month of May. The following information is available concerning its accounts receivable: Estimated credit sales for May P 200,000 Actual credit sales for April 150,000 Estimated collections in May for credit sales in May 20% Estimated collections in May for credit sales in April 70% Estimated collections in May for credit sales prior to April P 12,000 Estimated write-offs in May for uncollectible credit sales 8,000 Estimated provision for bad debts in May for credit sales in May 7,000 What are the estimated cash receipts from accounts receivable collections in May? a. P 142,000 c. P 150,000 b. P 149,000 d. P 157,000 Which one of the following budgets is the last item to be prepared under a normal budget preparation process? a. Direct labor budget c. Cash budget b. Cost of goods sold budget d. Manufacturing overhead budget The cash budget should help to ensure a. That enough cash is on hand at all times to satisfy maximum cash requirements b. Sufficient liquidity without an excess amount of idle cash c. That cash dividends can be paid every quarter d. That sufficient cash is available to pay salaries, even if it means borrowing the money The cash budget for 2021 would be affected in some way by all of the following, except a. A cash dividend declared in 2020 for payment in 2021. b. A cash dividend declared in 2021 for payment in 2022. c. Interest expense on loans taken out and repaid during 2021. d. The sales forecast for the first month in 2022. A company has prepared a cash budget for January through June of 2021. Which of the following, discovered in February 2021, is LEAST likely to require revising the cash budget? a. February sales are lower than budgeted. b. The interest rate on short-term borrowing is higher than budgeted. c. The company increased from 10% to 20% the down payment it requires from customers. d. The company changed inventory methods from LIFO to FIFO.

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ReSA – THE REVIEW SCHOOL OF ACCOUNTANCY

MAS-06

Week No. 6: BUDGETING with PROBABILITY ANALYSIS

B D

B B

D B C

28. The last pro forma statement prepared under a typical budgeting process is the a. Income statement c. Statement of cash flows b. Statement of cost of goods sold d. Statement of manufacturing costs 29. In the preparation of a cash budget with clear-cut information on sources and uses of funds, all of the following would classified as a cash flow under investing activities, EXCEPT: a. Collection of a loan from subsidiary c. Sale of plant assets b. Purchase of a patent from an inventor d. Dividends received on stock investment 30. In the preparation of a cash budget with clear-cut information on sources and uses of funds, all of the following would classified as a cash flow under financing activities, EXCEPT: a. The conversion of the company’s own preferred stock into common stock b. The declaration and payment of a cash dividend on the company’s own common stock c. The repayment of principal on a mortgage d. The sale of the company’s own preferred stock for cash 31. North Carolina projects the following activities related to its financial operations: a. Issuance of shares of company’s own common stock: P 170,000 b. Dividends to be paid to the company’s own shareholders: P 7,000 c. Dividends to be received from investments in other companies’ shares: P 4,000 d. Interest to be paid on the company’s own bonds: P 11,000 e. Repayment of principal on the company’s own bonds: P 40,000 f. Proceeds from sale of the company’s used equipment: P 23,000 In cash financial budget, the net cash used by financing activities should be projected to be a. P 375,000 c. P 112,000 b. P 123,000 d. P 19,000 32. The budget that describes the long-term position, goals, and objectives of an entity is the a. Capital budget c. Cash management budget b. Operating budget d. Strategic budget 33. The budgeting process should be one that motivates managers and employees to work toward organizational goals. Which one of the following is LEAST likely to motivate managers? a. Participation by subordinates in the budgetary process b. Having top management set budget levels c. Use of management by exception d. Holding subordinates accountable for the items they control 34. Comparing actual results with a budget based on achieved (actual) volume is possible with the use of a a. Monthly budget c. Rolling budget b. Master budget d. Flexible budget 35. Which one of the following budgeting methodologies would be most appropriate for a firm facing a significant level of uncertainty in unit sales volumes next year? a. Static budgeting c. Top-down budgeting b. Flexible budgeting d. Life-cycle budgeting 36. A flexible budget is a. One that can be changed whenever a manager so desires. b. Adjusted to reflect expected costs at the actual level of activity. c. One that uses the formula ‘total cost = cost per unit x units produced’ d. The same as a continuous budget. 37. Which of the following is a difference between a static budget and a flexible budget? a. A flexible budget includes only variable costs; a static budget includes only fixed costs. b. A flexible budget includes all costs; a static budget includes only fixed costs. c. A flexible budget gives allowances for different levels of activity while a static budget does not. d. None of the above. 38. A company has developed the budget formula below for estimating its shipping expenses. Shipments have historically averaged 12 pounds per shipment. Shipping costs = P 18,000 + (P 0.60 x pounds shipped) The planned and actual activity regarding orders and shipments for the month are given in the following schedule: Plan Actual Sales orders 800 780 Shipments 800 820 Units shipped 8,000 9,000 Sales P 120,000 P 144,000 Total pounds shipped 9,600 12,500 The actual shipping costs for the month amounted to P 21,000. What should be the appropriate monthly flexible budget allowance for shipping costs for the purpose of performance evaluation? a. P 18,000 c. P 23,760 b. P 18,492 d. P 25,500 39. The difference between the actual amounts and the flexible budget amounts for the actual output achieved is the a. Production volume variance c. Sales volume variance b. Flexible budget variance d. Standard cost variance 40. ‘Kaizen’ budgeting refers to the budgeting process where a. The budget is based on only one level of activity b. The budget is based on many levels of activity so that budget may be adjusted based on actual activity c. The budget is based not on the existing system, but on changes or improvements that are to be made d. A product’s revenues and expenses are estimated over its entire life cycle (i.e., from R&D phase to customer support phase)

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ReSA – THE REVIEW SCHOOL OF ACCOUNTANCY

MAS-06

Week No. 6: BUDGETING with PROBABILITY ANALYSIS

C B

B A B

B C A

41. The budget method that maintains a constant twelve month planning horizon by adding a new month on the end as the current month is completed is called a. An operating budget c. A continuous budget b. A capital budget d. A master budget 42. A company that uses zero-based budgeting has a. An expense budget of zero. b. Zero as the starting point of budgeting the coming year’s expenses. c. A zero variance between budgeted and actual performance. d. An assumed sales level of zero. 43. A decision maker is operating in an environment wherein all the facts surrounding a decision are known exactly, & each alternative is associated only with one possible outcome. The environment is known as: a. Certainty c. Uncertainty b. Risk d. Conflict Items 44 and 45 are based on the following information A store sells four computer models designated as P100, A200, R300, and T400. The store manager has made random number assignments to represent customer choices based on past sales data. The assignments are: Model Random Numbers P100 0-1 A200 2-6 R300 7-8 T400 9 44. What is the probability that a customer will select model P100? a. 10% c. 50% b. 20% d. Cannot be determined from given information SOLUTION: 2 {0,1} out of 10 {0,1,2,3,4,5,6,7,8,9} = 20% 45. In running a simulation of the computer demand, the following numbers are drawn in sequence: 2, 8 and 6. The simulation indicates that the third customer will purchase a. Model P100 c. Model R300 b. Model A200 d. Model T400 46. A quantitative technique useful in projecting a firm’s sales and profits is the a. Probability distribution theory c. Learning curves b. Gantt chart d. Queuing theory 47. Expected value in decision analysis is a. A standard deviation using the probabilities as weights. b. An arithmetic mean using the probabilities as weights. c. A standard deviation divided by the coefficient of variation. d. A measure of the difference between best possible outcome and outcome of the original decision 48. The term ‘expected value’ refers to the a. Value which would be assigned to a variable if problem were to be treated in a deterministic manner b. Most likely single outcome selected from among a number of possible alternatives c. Tails of a normal probability distribution d. Mean value of a variable Items 49 to 51 are based on the following information A group of kids sells sweet candies at a basketball game. The candies are sold for P 1.00 each, and the cost per candy is P 0.30. Any unsold candies are discarded because they will be stale before the next basketball game. The frequency distribution of the demand for candies per basketball game is: Unit sales volume Probability 2,000 candies 0.10 3,000 candies 0.15 4,000 candies 0.20 5,000 candies 0.35 6,000 candies 0.20 49. What is the estimated demand for candies at the next game using an expected value approach? a. 4,000 candies c. 5,000 candies b. 4,400 candies d. 6,000 candies 50. What is the estimated demand for candies at the next game using a deterministic approach (highest probability)? a. 4,000 candies c. 5,000 candies b. 4,400 candies d. 6,000 candies 51. The conditional profit per game of having 4,000 candies available but only selling 3,000 candies is a. P 1,800 c. P 2,800 b. P 2,100 d. P 4,000 SOLUTION: 3,000 (1.00) – 4,000 (0.3) 52. Raspberry Enterprises, distributor of compact disks (CDs), is developing its budgeted cost of goods sold for 2021. Raspberry has developed the following range of sales estimates and associated probabilities: Sales estimate Probability P 60,000 25% 85,000 40% 100,000 35% The cost of goods sold averages 80% of sales. What is 2021’s expected value of cost of goods sold? a. P 67,200 c. P 84,000 b. P 68,000 d. P 85,000

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ReSA – THE REVIEW SCHOOL OF ACCOUNTANCY

MAS-06

Week No. 6: BUDGETING with PROBABILITY ANALYSIS

D A

A B

B C

53. The Pineapple Company produces its product in batches of 100 units. The units each batch are then tested. The results from testing the most recent 200 batches are shown below: Units Failed per Batch Number of Batches 0 50 1 40 2 40 3 30 4 40 Total 200 What is the expected value of the number of failed units per batch? a. 0 c. 2.00 b. 1.85 d. 13.33 54. Cherry Distributors has decided to increase its daily muffin purchases of 100 boxes. A box of muffins costs P 2.00 and sells for P 3.00 through regular stores. Any boxes not sold through regular store are sold through thrift store for P 1.00. Cherry assigns the following probabilities to selling additional boxes: Additional sales Probability 60 60% 100 40% What is the expected value of Cherry’s decision to buy 100 additional boxes of muffins? a. P 28 c. P 52 b. P 40 d. P 68 SOLUTION: 60 (60%) + 100 (40%) = 76 Expected value of 100 boxes: [76 (3 – 2)] + [24 (1 – 2)] Items 55 and 56 are based on the following information The probabilities shown in the table represent the estimate of sales for a new product: Sales (unit) Probability 0 – 200 15% 201 – 400 45% 401 – 600 25% 601 – 800 15% 55. What is the probability of selling between 201 and 600 units of the product? a. 0% c. 25% b. 11.25% d. 70% 56. What is the best estimate of the expected sales of the new product? (Hint: compute average of range) a. 380 c. 480 b. 400 d. 800 57. Mango Company uses two major inputs in its production. To prepare its manufacturing operations budget, the company has to project the cost changes of these material inputs. The cost changes are independent of one another. The purchasing department provides the following probabilities associated with projected cost changes: Cost Change Material 1 Material 2 3% increase 30% 50% 5% increase 50% 40% 10% increase 20% 10% What is the probability of a 3% increase in the cost of both Material 1 and Material 2? a. 15% c. 80% b. 40% d. 20% 58. It is used for situations involving a sequence of events with several possible outcomes associated with each event. a. Network analysis c. Queuing theory b. Decision tree analysis d. Linear programming 59. A contractor has been invited to submit a bid on a large and complicated construction project. The preparation of the bid proposal will cost about P 20,000. Management feels that if the company bids low, enough to result in a net profit of P 50,000, there would be a 60% chance of getting the job. If the company bids high, enough to result in a P 100,000 net profit, the chance of getting the contract would be only 20%. What should the company do? a. Bid low, enough to allow for P 50,000 profit since the expected value of payoff is P 22,000 b. Bid high, enough to allow for a P 100,000 profit since the expected value of payoff is P 4,000 c. Bid high, enough to allow for a P 100,000 profit since the expected value of payoff is P 20,000 d. Make no bid. Items 60 to 62 are based on the following information A beverage stand can sell either soft drinks or coffee on any given day. If the stand sells soft drinks and the weather is hot, it will make P 2,500; if the weather is cold, the profit will be P 1,000. If the stand sells coffee and the weather is hot, it will make P 1,900; if the weather is cold, the profit will be P 2,000. The probability of cold weather on a given day at this time is 60%. 60. What is the expected payoff for selling coffee? a. P 1,360 c. P 2,200 b. P 1,960 d. P 3,900 61. What is the expected payoff if the vendor has perfect information? a. P 1,360 c. P 2,200 b. P 1,960 d. P 3,900 62. Considering only the information given, if the probability of hot weather given a hot weather forecast is 50%, then how much would the vendor be willing to pay for the forecast? a. P 300 c. P 600 b. P 500 d. P 1,000 SOLUTION: 50% (2,500 – 1,900)

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ALKALOID VÀ DƯỢC LIỆU CHỨA ALKALOID Bài giảng Học phần Dược liệu 2 Chương trình đại học

PGS. TS. TRẦN HÙNG ĐẠI HỌC Y DƯỢC THÀNH PHỐ HỒ CHÍ MINH 3 – 2022

I. LỊCH SỬ VÀ ĐỊNH NGHĨA ALKALOID

1. Lịch sử của hóa học alkaloid

2. Định nghĩa alkaloid 3. Tên gọi các alkaloid

1. LỊCH SỬ • Các cây cỏ có alkaloid đã được con người biết và sử dụng từ rất sớm bởi tác dụng sinh lý mạnh của chúng – Thuốc phiện (Papaver somniferum)

– Mã tiền (Strycnos nux-vomica…) – Ma hoàng (Ephedra sinica) – Ô đầu (Aconitum napellus) – Curare (Strychnos toxifera, Chondrodendron tomentosum…) – Canhkina (Cinchona spp.)

– Coca (Erythoroxylon coca) – Độc cần (Conium muculatum)

1. LỊCH SỬ • Paracelsus: khái niệm về các chất tinh túy. • K. W. Scheele: các acid hữu cơ / thực vật, các base hữu cơ trong động vật. • Fourcroy (1792): chất kiềm dạng nhựa từ vỏ Canh ki na nhưng không tiếp tục NC.

• Derosne (1803) hỗn hợp narcotin + morphin trong opium → “muối thuốc phiện” và cho rằng tính kiềm của hỗn hợp là do quá trình chiết xuất có dủng chất kiềm vô cơ • Seguin (1804) cũng đã chiết xuất được morphin.

1. LỊCH SỬ • Serturner (1805): “principium opii ” đặt tên là morphium (1817) sau đó Gay Lussac → morphinium. • Pelletier & Caventou (1817-1826): strychnin, emetin (1817) brucin, caffein, piperin (1819) quinin, colchicine (1820) coniin (1826) • Gomes (1821): cinchonin

2. ĐỊNH NGHĨA ALKALOID Meissner (1819): sử dụng thuật ngữ “alkaloid” từ chữ Latin alkali = chất kiềm (từ chữ Ả rập al-qalwī: tro) oid = giống như (từ chữ Hy lạp ειδος) Alkaloid là những hợp chất hữu cơ có chứa nitơ, có phản ứng kiềm và được lấy ra từ thực vật. Thuật ngữ alkaloid chỉ được sử dụng rộng rãi từ những năm 1880 bởi tổng quan về các hợp chất này của Jacobsen.

2. ĐỊNH NGHĨA ALKALOID König (1880): “Alkaloid là những base hữu cơ tìm thấy trong tự nhiên có chứa nhân pyridin” Ladenburg: “Alkaloid là những hợp chất hữu cơ có chứa ít nhất một nguyên tử nitơ trong nhân dị vòng”. Winterstein và Trier (1910): “Alkaloid là những chất kiềm có chứa nitơ phân bố trong cả thực và động vật”. ‘Alkaloid proper’: “là những hợp chất có chứa nitơ dị vòng, ít nhiều có tính kiềm và có cấu trúc phức tạp. Những chất này giới hạn trong thực vật và phân bố rời rạc trong một số chi họ nào đó, hiếm khi hiện diện rộng rãi trong một nhóm lớn thực vật. Tất cả những chất này đều có tác động dược lý”

2. ĐỊNH NGHĨA ALKALOID Theo Polonovski (1910): Alkaloid là những hợp chất hữu cơ – có chứa nitơ, đa số có nhân dị vòng, – có phản ứng kiềm, – thường gặp trong thực vật, đôi khi gặp trong động vật, – thường có dược lực tính mạnh và – cho phản ứng hoá học với một số thuốc thử gọi là thuốc thử chung của alkaloid.

2. ĐỊNH NGHĨA ALKALOID • Dược lực tính mạnh của alkaloid – Liều dùng tối đa 1 lần (uống) • Aconitin: 0,2 mg • Arecolin, hyoscyamin: 0,5mg • Scopolamin: 1mg • Strychnin: 2 mg • Các chất chứa nitơ – Tổng hợp: Không được xem là các alkaloid • Promethazin, quinolon v.v… – Có cấu trúc tương tự: alkaloid • Homatropin, procain v.v…

2. ĐỊNH NGHĨA ALKALOID Các ngoại lệ: • Một số alkaloid: tính kiềm rất yếu → không còn. – Ricinin (Ricinus communis)

– cafein, theobromin (Coffea, Camelia, Theobroma…) – Colchicin (Colchicum) • Alkaloid gặp trong động vật: – muscopiridin (Moschus berezovski), – samandarin, samanin (Salamadra maculosa, S. atra),

– bufotenin, bufotenidin (Bufo), • Alkaloid gặp trong vi khuẩn – Pseudomonas

3. TÊN GỌI CỦA ALKALOID Tên alkaloid = gốc từ + in Tên của loài thực vật + ~in (~ine) – Tên chi • Papaverin (Papaver) · Atropin (Atropa) • Strychnin (Strychnos) · Hyoscyamin (Hyocyamus) – Tên loài • Cocain (E. coca) · Rotundin (S. rotunda) • Palmatin (J. palmata) · Serpentin (R. serpentina) – Tên thông thường • Curarin, tubocurarin (Curare) • Hyndarin (Hyndaru) • Fanchinolin (Fanchi) • Liensimin (Lianzixin)

3. TÊN GỌI ALKALOID Tên người (rất hiếm gặp) – Pelletierin (Tanret – Areca catachu), – Hörhamericin (Tabernemontana holstii), Tên các nhân vật thần thoại – Morphin (Morpheus) Theo một tác dụng nào đó của nó – Emetin (emetos – εμετος) v.v… Chú ý: – Nicotin, cinchonin – Atropin, – Febrifugin,

3. TÊN GỌI ALKALOID Các alkaloid có cấu trúc tương tự thường được gọi tên theo alkaloid chính trong cây với các tiếp vĩ ngữ – ~idin: cinchonidin, quinidin – ~inin: ergosinin, ergocryptinin – ~ilin: reserpilin – ~icin: ajmalicin – ~amin: cinchonamin, emetamin, rescinamin – ~alin: anhalin

3. TÊN GỌI ALKALOID Các đồng phân thường được gọi với tiếp đầu ngữ – pseudo~: pseudoephedrin, pseudotropin

– iso~: isopelletierin, isoajmalin – epi~: epistephanin, epilupinin – allo~: allocryptopin, allosedamin – neo~: neostrychnin, neoberanidin – nor~: norchelidonoin, norlaudanosin – homo~: homolycorin

II. CẤU TRÚC VÀ PHÂN LOẠI ALKALOID

1. Sinh nguyên của các alkaloid

2. Phân loại các alkaloid 3. Các đặc điểm về cấu trúc

1. SINH NGUYÊN CỦA CÁC ALKALOID

1. SINH NGUYÊN CỦA CÁC ALKALOID Nhóm alkaloid Pyrrolidin

Cấu trúc

Tiền chất Acid aspartic, ornithin

Pyrrolizidin

Ornithin

Tropan

Ornithin

Quinolizidin

Lysin Lysin, Acetat

Piperidin N

Isoquinolein

Tyrosin, Phenylalanin Tryptophan, acid anthanilic

Quinolein N

Indol

Tryptophan

2. PHÂN LOẠI CÁC ALKALOID

2.1. Các cách phân loại alkaloid 2.2. Phân loại alkaloid 2.2.1. Proalkaloid (Alkaloid không nhân dị vòng)

2.2.2. Alkaloid thực (Alkaloid có nhân dị vòng) 2.2.3. Pseudoalkaloid

2.1. CÁC CÁCH PHÂN LOẠI CÁC ALKALOID • Phân loại theo tác dụng dược lý • Phân loại alkaloid theo địa lý – khí hậu

• Phân loại alkaloid theo dạng cây. • Phân loại theo nguồn gốc thực vật – Alkaloid chung nguồn gốc thực vật thường có cấu trúc đặc trưng. • alkaloid họ Amaryllidaceae,

• alkaloid họ Buxaceae, • alkaloid chi Solanum, – Còn ít nhiều được sử dụng trong các chuyên khảo.

2.1. CÁC CÁCH PHÂN LOẠI CÁC ALKALOID • Phân loại theo cấu trúc hóa học – Alkaloid được chia thành nhóm có cùng khung cơ bản.

– Những khung này có cấu trúc đơn giản chỉ có 1 hay 2 vòng – Trong mỗi nhóm alkaloid có thể được chia thành những nhóm nhỏ hơn. – Tương đối logic và tiện dụng.

– Tuy nhiên không luôn luôn phản ánh đúng mối liên hệ giữa các alkaloid trong các taxon thực vật. – Thường được các nhà hoá học sử dụng.

2.1. CÁC CÁCH PHÂN LOẠI CÁC ALKALOID • Phân loại theo sinh nguyên: – Phân loại alkaloid theo nguồn gốc phát sinh. • Alkaloid dẫn xuất từ tyrosin,

• Alkaloid dẫn xuất từ tryptophan, • Alkaloid dẫn xuất từ ornithin v.v… – Thấy sự liên hệ giữa các loài trong hệ thống tiến hóa. – Được các nhà sinh lý, sinh hóa thực vật sử dụng. – Tuy nhiên, không luôn đủ bằng chứng thực nghiệm.

– Theo con đường sinh tổng hợp người ta phân ra: • Protoalkaloid. • Alkaloid “thực”.

• Pseudoalkaloid.

2.1. CÁC CÁCH PHÂN LOẠI CÁC ALKALOID • Protoalkaloid (tiền alkaloid) – Là sản phẩm của sự decarboxyl hóa acid amin và dẫn chất. • Alkaloid “thực” (alkaloid proper) – Là những alkaloid sinh tổng hợp từ các acid amin và dẫn

chất. – Có nitơ trong dị vòng.

• Pseudoalkaloid (alcaloida imperfecta) – Tổng hợp từ tiền chất không phải acid amin. – Nguyên tử nitơ được đưa vào sau này.

2.1. CÁC CÁCH PHÂN LOẠI CÁC ALKALOID • Phân loại theo sinh nguyên và cấu trúc hóa học – Kết hợp giữa phân loại theo sinh nguyên và hóa học.

– Các nhóm lớn được xếp thành theo sinh nguyên – Các phân nhóm chia theo cấu trúc hóa học. – Không khác nhiều với phân loại hóa học. Trừ một vài trường hợp cùng cấu trúc – khác sinh nguyên. – Hiện sử dụng nhiều. Đơn giản và logic hơn, đảm bảo tính chất tự nhiên về nguồn gốc.

2.2. PHÂN LOẠI CÁC ALKALOID 2.2.1. Proalkaloid (Alkaloid không có nhân dị vòng) 2.2.2. Alkaloid thực (Alkaloid có nhân dị vòng) 2.2.2.1. Alkaloid có nhân pyrol – pyrolidin 2.2.2.2. Alkaloid có nhân tropan 2.2.2.3. Alkaloid có nhân pyrolizidin 2.2.2.4. Alkaloid có nhân indolizidin 2.2.2.5. Alkaloid có nhân quinolizidin 2.2.2.6. Alkaloid có nhân pyridin – piperidin 2.2.2.7. Alkaloid có nhân indol – indolin … 2.2.3. Pseudoalkaloid 2.2.3.1. Alkaloid có nhân purin 2.2.3.2. Alkaloid có cấu trúc terpen …

2.2.1. PROTOALKALOID • Cấu trúc đơn giản, là Δ’ decarboxyl của acid amin. • Thường là hợp chất thơm có nitơ ngoài mạch nhánh.

• Cũng được xem là các amin thơm • Không có mùi và thường có hoạt tính sinh lý mạnh.

• Một số thấy trong cả thực vật và động vật. – Noradrenalin và serotonin.

• Cũng có tác giả không coi là các alkaloid. • Vài tác giả vẫn xếp amin mạch thẳng vào alkaloid.

2.2.1.1. Alkaloid phenyl alkylamin Alkaloid có cấu trúc phenyl alkylamin COOH

COOH NH2

NH2

Phenyl alanin

NH2

HO Tyramin

Capsella bursa-pastoris

Tyrosin MeO

OMe

Hordenin (anhalin)

OMe Mescalin

Hordeum vulgare

Lolophora williamsii O

OH MeO HN

NH2

Ephedrin

Capsaicin

Ephedra sinica

Capsicum annum

2.2.1.2. Alkaloid indol đơn giản Alkaloid indol đơn giản

– Tryptamin, serotonin, gramin, abrin…

2.2.1.3. Alkaloid có nhân tropolon Alkaloid có cấu trúc tropolon

3.2.2. ALKALOID THỰC •

Alkaloid thực (chính thức): – Có nitơ nằm trong nhân dị vòng

– Sinh tổng hợp từ các tiền chất là các acid amin. – Là nhóm lớn và quan trọng nhất. •

Tuỳ theo cấu trúc cơ bản của dị vòng nitơ – Chia thành nhiều nhóm. – Trong các nhóm có thể có các phân nhóm

3.2.2. ALKALOID THỰC 3.2.1.1. Alkaloid nhân pyrol và pyrolidin 3.2.1.2. Alkaloid nhân tropan

3.2.1.3. Alkaloid nhân pyrrolizidin 3.2.1.4. Alkaloid nhân indolizidin 3.2.1.5. Alkaloid nhân quinolizidin 3.2.1.6. Alkaloid nhân pyridin và piperidin 3.2.1.7. Alkaloid nhân indol và indolin

3.2.1.8. Alkaloid nhân nhân quinolein 3.2.1.9. Alkaloid nhân quinazolin 3.2.1.10. Alkaloid nhân isoquinolein 3.2.1.11. Alkaloid nhân imidazol

3.2.2.1. Alkaloid pyrol và pyrolidin

N H

Pyrrol

Pyrrolidin O

O N N-Methyl pyrrolidin

N Hygrin

Erythroxylon coca

Cuscohygrin (belladonoin)

Atropa belladonna Datura metel

3.2.2.2. Alkaloid tropan N

Tropan

Tropanol – tropin OOC

Hyoscyamin

O OH

Scopanol – scopin OOC

Scopolamin

Atropa, Hyoscyamus, Datura, Scopolia… COOCH3

COOH N Ecgonin

OOC Cocain

Erythroxylon coca

3.2.2.3. Alkaloid pyrrolizidin

Pyrrolizidin

Retronecin

CH 2OH

Senecio, Heliotropium

3.2.2.4. Alkaloid indolizidin HO

OH H

N N

HO Castanospermin

Indolizidin (Fabaceae)

O N O Elaeocarpceae alkaloid

Phenanthroidipyrrolizidin (Asclepiadaceae)

3.2.2.5. Alkaloid quinolizidin

H N

N H

Quinolizidin

Spartein

Sarothamnus scoparius

3.2.2.6. Alkaloid pyridin và pipreridin Pyridin

Piperidin N

N H

COOCH3

N Arecolin

Areca catechu

N H

Isopelletierin

Nicotin

Punica granatum Nicotiana tabacum O

O N Lobelin

Lobelia inflata

3.2.2.7. Alkaloid indol và indolin COOH NH2 N H Tryptophan

N Indol H

N Indolin H

Các indolalkylamin Me

R NH2

N Tryptamin R = H Acacia Serotonin R = OH Juglans regia N

N Abrin

Me COOH

Abrus precatorius

N Me

N Gramin Graminae OR

Me + N Me

N Psilocin R = H Psilocibin R = HPO3-

Psylocib aztecorum

3.2.2.7. Alkaloid indol và indolin • Alkaloid kiểu eserin

Me N

N O

N N Me Me

Eserin (Physostigmin) • Alkaloid kiểu b-carbolin

N b-cabolin

Physostigma

Harmin Me

Passiflora

3.2.2.7. Alkaloid indol và indolin • Alkaloid kiểu ergolin

Me HOOC

CH2OH

N Me

N Acid lysergic

N Ergolin

• Alkaloid kiểu strychnan

N Ergobasin

Clavicep purpurea H N

R1 N

H R2

N O

O Strychnan

H O

H Strychnin R1 = R2 = H Brucin R1 = R2 = OMe

Strycnos nux-vomica

3.2.2.7. Alkaloid indol và indolin • Alkaloid kiểu yohimban

N H

MeO

MeO H

N H

MeO

OMe

O O

O OH Yohimbin

Yohimban

OMe

Reserpin

Yohimba

OMe

Rauwolfia serpentina

• Alkaloid heteroyohimban

MeO

Heteroyohimban

MeO Ajmalicin

H H O

H O OMe

3.2.2.8. Alkaloid quinolein

N Quinolein Alkaloid của Canhkina HO

R N Quinin : R = OCH3 Cinchonin : R = H

N Quinidin : R = OCH3 Cinchonidin : R = H

Alkaloid có nhân acridin N Acridin

3.2.2.9. Alkaloid quinazolin

N N Quinazolin O

O N

N N O HO

b-Dichroin

-Dichroin

Dichroa febrifuga

3.2.2.10. Alkaloid isoquinolein

N • Các isoquinolein đơn giản

Meo

Meo OMe

N Me Salsolin

OMe

N OH Me Anhalonidin

3.2.2.10. Alkaloid isoquinolein • Benzylisoquinolein

MeO

MeO N

MeO

Benzylisoquinolein

Papaverin

• Bisbenzylisoquinolein Me N

N Me

MeO OMe OMe

OMe

Laudanosin

OMe

MeO OMe O O OMe Tetrandrin

N Me

3.2.2.10. Alkaloid isoquinolein • Aporphin OMe N R

Aporphin

O N Me

OMe

Nuciferin

N Me

Roemerin HO

• Morphinan O HO N R Khung morphinan

N R Morphin : R = H Codein : R = CH3

3.2.2.10. Alkaloid isoquinolein • Protoberberin O N

N OMe OMe

Protoberberin

Berberin

• Protopin N

Tetrahydro protoberberin

Khung protopin

3.2.2.10. Alkaloid isoquinolein • Phtalidisoquinolein O

N O

N Me O O

O OMe

Phthalidisoquinolein

OMe OMe

Narcotin

• Benzophenanthridin O

N R Benzophenanthridin

N Me O Sanguinarin

3.2.2.10. Alkaloid isoquinolein • Emetin MeO N

MeO

OMe OMe

H N Khung emetin

H N Emetin

Cephaelis ipecacuanha

3.2.2.11. Alkaloid imidazol N N H Imidazol Me

N N

Pilocarpin

N N

Isopilocarpin

Pilocarpus jaborandi

3.2.3. PSEUDO ALKALOID

3.2.3.1. Alkaloid nhân purin 3.2.3.2. Alkaloid nhân mono và diterpen

3.2.3.3. Alkaloid nhân steroid 3.2.3.4. Alkaloid có cấu trúc peptid

3.2.3. PSEUDO ALKALOID 3.2.3.1. Alkaloid nhân purin O Me N O

N N

Theobromine Theobroma cacao

Me O

Me N

N N

Theophyllin Theobroma cacao

N N

Cafein Camellia sinensis Coffea spp.

3.2.3. PSEUDO ALKALOID 3.2.3.2. Alkaloid nhân mono và diterpen

Paclitaxel (Taxol) Taxus spp.

3.2.3. PSEUDO ALKALOID 3.2.3.3. Alkaloid nhân steroid

3.2.3. PSEUDO ALKALOID 3.2.3.4. Alkaloid có cấu trúc peptid

3. ĐẶC ĐIỂM CHUNG VỀ CẤU TRÚC CỦA ALKALOID Đa dạng về cấu trúc, các đặc điểm chung nhất: • Sinh nguyên: – Là các chất chuyển hóa bậc II có nitơ. – Phần lớn tổng hợp từ acid amin (alkaloid thực). • Cấu tạo:

– M: 100-900 (cao hơn ở các peptid alkaloid). – Công thức cấu tạo chung là CxHyNz(Ow),

– Ða số có oxy, môt số ít alkaloid chỉ có CxHyNz. – Một số alkaloid có S, Cl, hay P trong phân tử.

3. ĐẶC ĐIỂM CHUNG VỀ CẤU TRÚC CỦA ALKALOID

• Cấu tạo:

– Có 1-2 nguyên tử nitơ, có thể hơn (alkaloid dimer). – Là các hợp chất có mạch vòng • Dị vòng (phần lớn) • Vòng carbon (protoalkaloid)

– Số lượng vòng • 1 vòng (ít, thường là protoalkaloid) • 2 – 5 vòng (phần lớn). • Có thể tới 14 (dimer). Không vòng – không alkaloid!

3. ĐẶC ĐIỂM CHUNG VỀ CẤU TRÚC CỦA ALKALOID • Không được xem là alkaloid – Các chất đã xếp vào nhóm khác theo truyền thống.

• Vitamin B1, histamin, acid amin v.v… – Các base động vật

• Nucleosid. • Ngoại lệ: serotonin…

– Các chất tổng hợp (trừ Δ’ alkaloid).

NH2

N N

Histamin

3. ĐẶC ĐIỂM CHUNG VỀ CẤU TRÚC CỦA ALKALOID • Nguyên tử nitơ trong alkaloid – Nitơ bậc I, II, III hay IV, thường nhất là bậc III.

– Nitơ thường liên kết với carbon hay hydro. – N liên kết với oxy → genalkaloid = alkaloid N→oxid. • Genalkaloid thường gặp: nitơ bậc III. • Có trong cây song song với alkaloid thông thường. • Được tạo thành khi oxy hóa NIII bằng hydroperoxid. • Khử hóa sẽ thu được alkaloid ban đầu.

III. TÍNH CHẤT CỦA ALKALOID 1. Tính chất vật lý của alkaloid 1.1. Các đặc điểm cảm quan 1.2. Điểm chảy, khả năng quay cực 1.3. Các đặc điểm phổ học 1.4. Tính tan của alkaloid 2. Tinh chất hoá học của alkaloid 2.1. Tính kiềm của alkaloid 2.2. Phản ứng oxy hoá – khử 2.3. Phản ứng với thuốc thử chung 2.4. Phản ứng với các màu acid

1. TÍNH CHẤT VẬT LÝ CỦA ALKALOID 1.1. Các đặc điểm cảm quan 1.1.1. Thể chất Thể rắn • Các alkaloid có oxy: chất rắn kết tinh. – Lỏng: arecolin (C8H13NO2), pilocarpidin (C10H14N2O2). • Các alkaloid không có oxy: lỏng sánh, mùi mạnh:

nicotin (C10H14N2), coniin (C8H17N), spartein (C15H26N2). – Rắn: conessin (C24H40N2), sempervirin (C19H16N2).

1. TÍNH CHẤT VẬT LÝ CỦA ALKALOID 1.1.2. Màu sắc, mùi vị Không màu, không mùi, vị đắng. • Một số alkaloid: vàng nhạt tới cam hay đỏ. – berberin, palmatin, chelidonin có màu vàng, – jatrorrhizin có màu đỏ cam v.v…

• Alkaloid ở thể lỏng: mùi mạnh. • Một số alkaloid có thể có vị cay, nóng: – piperin (Piper nigrum), – capsaicin (Capsicum annum), – aconitin (Aconitum).

1. TÍNH CHẤT VẬT LÝ CỦA ALKALOID 1.2. Ðiểm chảy, khả năng quay cực và phổ tử ngoại 1.2.1. Ðiểm chảy • Điểm chảy cao và rõ ràng. • Một số chất bị phân hủy trước khi chảy. • Alkaloid lỏng: bay hơi, bền nhiệt, cất kéo hơi nước. • Vài alkaloid: thăng hoa ở 1 atm (cafein, ephedrin) 1.2.2. Năng quay cực • Tả triền (quay trái, đồng phân l-), – Quay phải: cinchonin, quinidin, aconitin, pilocarpin. – Một số chất: racemic: atropin, atropamin – Vài alkaloid không quay cực: piperin, papaverin, narcein, berberin, palmatin, jatrorrhizin. • Dạng tả triền thường có tác dụng sinh lý mạnh hơn.

1. TÍNH CHẤT VẬT LÝ CỦA ALKALOID 1.2. Ðiểm chảy, khả năng quay cực và phổ tử ngoại 1.2.3. Phổ hấp thu tử ngoại

• Hầu hết alkaloid: lmax 250-310 nm • Một số alkaloid: vùng sóng dài hơn → khả kiến • Ứng dụng: phát hiện sắc ký, định tính, định lượng. 1.2.4. Huỳnh quang • Một số alkaloid: xanh lơ, xanh lá mạ, vàng • Ứng dụng: phát hiện, phân biệt, định lượng.

Oil Spill Response Contingency Plan For Mumbai & JNPT Harbour

Oil Spill Response Contingency Plan For Mumbai & JNPT Harbour
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OIL SPILL RESPONSE CONTINGENCY PLAN MUMBAI & JNPT HARBOUR

Prepared by SADHAV SHIPPING LTD

RECORD OF AMANDMENTS DATE

AMANDMENT NUMBER

SECTION/PARA/ SUBPARA

PAGE NO

INITIALS OF ISSUING OFFICER

NOTE 1. Amandment to Plan is to be carried out by replacing the text, information or data contained in the relevent section, para or sub para. 2. The old text is to be removed from ring binder file and replaced by amanded data, text or information.

Page i of xi

INDEX

CONTENTS

PAGE NO.

CONTINGENCY PLANNING 1.1. PURPOSE AND OBJECTIVES 1.2. AIMS OF CONTIGENCY PLAN

PLAN ELEMENTS 1.3.1. Hazards and Identification 1.3.2. Vulnerability / Sensitivity Analysis 1.3.3. Risk Assessment 1.3.4. Response Actions / Resources RESPONSE POLICIES LOCATION BASED RESPONSE

INTEGRATION WITH WIDER AREA OPERATIONS

PLAN FACTORS

PART I 1.0

1.3.

1.4. 1.5. 1.6. 1.7. 1.8. 1.9.

REVIEW, REVISION AND UPDATES

INTERFACE WITH OTHER PLANS 2.0 PLANNING AND ADMINISTRATION 2.1 AREA LAYOUT 2.2 MUMBAI PORT 2.2.1 Cargo Handling 2.2.2 Cargo Statistics

Page ii of xi

2.3

JNPT 2.3.1 Cargo Handling 2.3.2 Liquid Cargo Berths 2.4 POL CARGO 2.4.1 Chemical Characteristics of Different Oil and their Implications 3.0 RISK & SPILL ASSESSMENT 3.1 HAZARD RATING 3.2 CAUSES OF OIL SPILL 3.2.1 Location of Spill within the scope of the Plan 3.3 OIL SPILLS – HISTORIC DATA 3.3.1 Analysis and figures 3.4 RISK FACTOR FOR OIL SPILLS ‐ TERMINAL OPS 3.4.1 Failure frequencies – Pipelines 3.4.2 Cargo Operations or Transfer spills frequencies 3.4.3 Spill Volume Calculations 3.4.4 ONGC Pipeline Damage 3.4.5 ONGC Pipeline Spill estimates 3.5 SHIP ACCIDENTS AND FREQUENCY OF OIL SPILLS 3.5.1 Collision 3.5.2 Vessel contact 3.6 MAXIMUM CREDIBLE SPILL VOLUMES 3.6.1 Volumes for maximum credible case scenario 3.6.2 Maximum credible spill volumes – Vessel spill 3.7 WORST CASE SCENERIO ‐ OIL RELEASE FROM GROUNDING

3.8

OR COLLISSION SPILL IN Mumbai HARBOUR – Model studies

27 28

Page iii of xi

3.9 3.10 3.11

MOVEMENT AND TRAJECTORY STUDIES ‐ Jawahar Dweep and Pir Pau jetty 3.9.1 Location 3.9.2 Spill Scenarios 3.9.3 Oil Types 3.9.4 SW Monsoon Period ( May – September ) 3.9.5 NE Monsoon ( December – February ) 3.9.6 Post Monsoon

MOVEMENT AND TRAJECTORY MODEL – JNPT 3.10.1 Spill Location 3.10.2 Oil Type 3.10.3 Pre Monsoon ( January ) 3.10.4 Monsoon Period ( July ) 3.10.5 Post Monsoon ( October )

MODEL PREDICTIONS – ICMAM and NIO

4.0

FATE OF SPILLED OIL AND SPILL ANALYSIS 4.1 WEATHERING PROCESS AND TIME SCALE 4.1.1 Calculation of Weathering Losses 4.2 OIL THICKNESS AND APPEARANCE OF SLICK 4.3 MOVEMENT OF OIL 5.0 CLIMATIC CONDITIONS 5.1 TEMPERATURE AND RAINFALL 5.2 WINDS 5.3 VISIBILITY 5.4 pH VOLUME 5.5 TOTAL DISSOLVED SOLIDS

Page iv of xi

5.6

WAVES

5.7

TIDES

5.8

CURRENT

5.8.1 5.8.2 5.9

Tidal Streams (Currents) an approaches to Mumbai Port Tidal Streams (Currents) in Mumbai Harbour

MODEL SIMULATION AND VALIDATION

6.0 ENVIRONMENTAL SENSITIVITY 6.1 ENVIRONMENTAL SENSITIVITY MAPPING 6.2 GEOGRAPHICAL & TOPOGRAPHICAL SENSITIVITY 6.3 SHORELINE SENSITIVITY 6.4 OBSERVATIONS 6.5 PROTECTION PRIORITIES

PART II 7.0 OPERATIONS AND RESPONSE STRATEGIES 7.1 RESPONSE ACTIONS 7.2 OPERATIONAL PRIORITIES 7.3 OPERATIONS MANUAL / FIELD GUIDES 7.4 LIMITING AND ADVERESE CONDITIONS 7.5 RESPONSE STRATEGY 7.5.1 Jetty / Terminal Response Page v of xi

7.5.2 On Water Response 7.5.3 Use of Dispersant 7.5.4 Coastal shoreline Cleanup 8.0 EQUIPMENT, SUPPLIES AND SERVICES 8.1 LOCATION 90 8.2 ADDITIONAL EQUIPMENT AND RESPONSE 91 91 8.3 INSPECTION, MAINTAINANCES AND TRAINING 8.3.1 Exercises 9.0 ORGANISATION 9.1 MANAGEMENT AND MANPOWER 95 9.1.1 Major function of CMT 9.1.2 Functional Designations 9.2 EXECUTION OF PLAN 97 9.2.1 Crisis Management Team and Assembly 9.2.2 Incident Response Team / Teams 9.2.3 Afloat Operation Response Teams 9.2.4 Shoreline Cleanup Team 9.3 DUTIES OF CMT AND OTHER STAFF 102 9.3.1 Crisis Management Team / Incident Co‐ordination 9.3.2 Additional Responsibility of Team Members 9.3.3 Responsibilities of On Scene Co‐ordinator 9.3.4 Responsibilities of Incident Manager / Oil Spill Response Organization Manager 9.3.5 Responsibilities and functions of Response Team 9.3.6 Common Duties Page vi of xi

10.0 10.1 10.2 10.3 10.4 11.0 11.1

OPERATIONS CONTROL AND COMMUNICATION OPERATIONS AND COMMUNICATION CENTER

113

EQUIPMENT AND PUBLICATIONS

114

ACTIONS REQUIRED OF COMMUNICATION AND OPERATIONS CENTER

114

INFORMATION DISPLAY

115

REPORTING SPILL AND PLAN ACTIVATION

11.2

ACTIVATION 117 11.1.1 Actions by Port Control/OSRO Control Room or HM on receipt of incident information 11.1.2 Numbering of Incident Log COMMON DUTIES OF PORT CONTROL / COC & HM 119

11.3

TEAM ACTIVATION

11.4

SPILL DETAILS 11.4.1 Additional Information

119

11.5 INFORMATION TO PUBLIC AUTHORITY

121

11.6 INFORMATION TO MEDIA 12.0

TERMINATION AND COMPLETIONS OF OPERATIONS 12.1 COMPLETION AND STANDING DOWN

123

12.2 REVIEW OF PLAN AND PROCEDURES

124

125

13.0

DISPOSAL

Page vii of xi

DATA DIRECTORY

Appendix No

PAGE NO

126

OILS HANDLED AT MUMBAI HARBOUR

BROAD CLASSIFICATION OF OILS AS PER MARPOL 73/78

127

CHARECTERISTICS OF DIFFERENT OILS

128

ONGC PIPELINE LEAK SPILL VOLUMES (m3)

129

WEATHERING PROCESS AND TIME SCALES

130

CALCULATION OF WEATHERING LOSSES – ADIOS SPILL CALCULATOR

131

CALCULATION OF QUANTITY OF SPILLED OIL AS PER SLICK

133

CHARACTERISTICS 8

SHORELINE TYPES, RANKING AND COLOUR CODE

134

BIOLOGICAL RESOURCES ESI SYMBOLS

137

ESI POINT SYMBOLS BIOLOGICAL RESOURCES

138

ESI HUMAN USE RESOURCES SYMBOLS

139

ESI MAP – THAAL KNOB TO NAVAPADA

140

11A

ESI MAP – NAVAPADA TO MORA JETTY

141

11B

ESI MAP – MORA TO JUNA SHEVA ROAD, JNPT

142

11C

ESI MAP‐ JNPT( NHAVA) TO SOUTH ENTRANCE TO PANVEL CREEK

143

11D

ESI MAP ‐ SECTOR 51 TO VASHI VILLAGE

11E

VASHI VILLAGE ( E BANK OF THANE CREEK) TO VIKHROLI

144

145

( W BANK OF THANE CREEK ) 11F

ESI MAP ‐ VIKHROLI TO BPCL REFINERY TO HAJI BANDAR

146

11G

ESI MAP ‐ VIKHROLI TO BPCL REFINERY TO HAJI BANDAR

147

11H

ESI MAP‐ HAJI BUNDER TO COLABA, NAVY NAGAR

148

PORT‐ VESSEL POLLUTION EMERGENCY INTERPHASE

149

Page viii of xi

LIST OF DISPERSANTS APPROVED FOR APPLICATION

BY COAST GUARD

150

EQUIPMENT DETAILS AND LOCATION

151

ADDITIONAL EQUIPMENT AND LOCATION

152

LIST OF INTERNATIONAL OSROs

153

ORGANISATIONAL CHART

154

COMPOSITION OF CMT – MbPT

155

18A

COMPOSITION OF CMT – JNPT

156

18B

COMPOSITION OF CMT ‐ ONGC

157

PERSONAL LOG

158

IC/OSC/VESSEL MASTER DAILY LOG

159

INCIDENT LOG

OIL SPILL REPORT FORM

22A

160

162

CONTACT DETAILS OF SPILL INFORMATION CENTER

163

CONTACT DETAILS OF LOCAL ADMINISTRATIVE AUTHORITIES

164

MEDIA COMMUNICATIONS

166

Page ix of xi

ACRONYMS

BPCL

Bharat Petroleum Corporation Ltd

DNV

Det Norske Veritas

COC

Communication and Operations Center

ESI

Environmental Sensitivity Index

Harbor Master

HPCL

Hindustan Petroleum Corporation Ltd

Incident Controller

Incident Manager

IMO

International Maritime Organisation

IOCL

Indian Oil Corporation

IPIECA

International Petroleum Industry Environmental Conservation Association

ITOPF

International Tanker Owners Pollution Fund

Jawahar Dweep

JNPT

Jawahar Lal Nehru Port

MARPOL 73/78

International Convention for the Prevention of Pollution from Ships 1973 as modified by the Protocol of 1978

MbPT

Mumbai Port Trust

NFPA

National Fire Protection Association

NOS‐DCP

National Oil Spill Disaster Contingency Plan

Page x of xi

ONGC

Oil and Natural Gas Corporation

OPRC Convention

International Convention on Oil Pollution Preparedness, Response and Co‐operation 1990

OSC

On Scene Coordinator

OSD

Oil Spill Dispersant

OSR

Oil Spill Response

OSRO

Oil Spill Response Organisation

OSRO‐M

Oil Spill Response Organisation ‐ Manager

OSRO‐S

Oil Spill Response Organisation – Specialist

Port Control

POL

Petroleum, oil and lubricants

RIL

Reliance Industries Limited

SRV

Spill Response Vessel

UNCLOS

United Nations Convention on Laws of the Sea

TPC

Tata Power Corporation

Page xi of xi

1.0

CONTINGENCY PLANNING

In spite of best intentions to avoid oil spills through best and safe practices and rigid enforcement of good intentions in work place, the spills still occur and will keep on occurring. The next best post spill activity, then, is to address them in terms of containment and recovery within shortest possible time and through best available means that need to be planned and kept ready in advance and spelled through a Contingency Plan for the facility or area handling oil, oil products or other pollutants. Increase in density of marine traffic, especially oil tankers and petroleum based installations along the Indian coast has increased the risks for occurrence of spills in harbour, coastal waters and during terminal operations apart from spills that could occur from collision, grounding of vessels and stranding. To address the fallout of incidents and accidents that could lead to pollution of marine environment, all countries handling polluting agents are required to have capabilities and create infrastructure and set up means that could handle the pollution response activity in case of any spill. The working parameters and strategy to address the response activities are spelled through a Contingency Plan. 1.1

PURPOSE AND OBJECTIVES OF CONTINGENCY PLAN

India being signatory to number of International agreements and conventions aimed at controlling marine pollution through measures and rules applicable to marine facilities or surface units, is under an obligation to honour and implement the same through municipal legislation and through adopting means, practices and rules in accordance with Article I of the Convention 73 and Protocol 78 i.e MARPOL 73/78. The article has placed an obligation on the parties to the convention including India “to give effect to the provisions of the present convention and those Annexes Page 1 of 167

thereto by which they are bound, in order to prevent the pollution of the marine environment by the discharge of harmful substances or effluents containing such substances in contravention of the convention”. Apart from the specific obligations imposed by MARPOL, being a signatory to UN Convention on the Laws of the Sea ( UNCLOS ) , India has an obligation to protect and preserve the marine environment in addition to obligations under International Convention on Oil Pollution Preparedness, Response and Co‐operation 1990 ( OPRC Convention ). Accordingly, India too had to formulate rules or administrative directions giving effect to international procedures through structures to be developed by ports and facilities handling vessels and oil cargo. While, regulatory procedures are expected to be put in place through rules‐ implementing the various provisions and annexure of MARPOL 73/78, the practical aspects of marine pollution to set up a mechanism on the ground are dealt by OPRC – National Oil Spill Disaster Contingency Plan being an instrument for the same. NOS‐DCP has its origin in IMO convention OPRC – 1990, ratified by India. As per the convention it is imperative upon each signatory state to have laws and mechanisms to respond to oil spills in its waters. National Oil Spill Disaster Contingency Plan is aimed at coordination of resource agencies to combat an oil spill in Indian waters and also spells the actions required of oil handling facilities i.e to prepare contingency plans for respective facilities and to develop Tier I response capabilities and also to report oil spills. NOSDCP mandates a number of resource agencies comprising of 03 ministries and 15 departments apart from oil industry, off shore terminals etc. to an obligation to: Page 2 of 167

Render resources for pollution response when called for,

Report Oil Spills,

Prepare contingency plans for respective spill scenario,

Set up Tier I response facilities and

Use of Oil Spill dispersants (OSD) in accordance with Plan. Of the three tiers of response envisaged and planned to handle a spill situation in

consonance with quantum of spill, Tier 1 is the primary and first step of responses, to be mounted by the facility where the spill takes place.

While, NOS‐DCP outlines the response activities as per Tier system of

addressal of spill, the facility plan is the instrument to address the spill scenario at local level. Tier 1 being the first and primary response level has to be executed and undertaken by the facility handling polluting cargo, for which purpose drafting of a CP is the primary requirement. The National Oil Spill Disaster Contingency Plan was first drafted in India by Coast Guard during 1996 with an objective to put in place the machinery and mechanisms to combat oil spills in Maritime zones of India. The Plan has since been updated in 2002. 1.2

AIMS OF CONTINGENCY PLAN

The aims and objectives of the Oil Spill Response Contingency Plan (here after termed the Plan or CP ) of a port or facility are to draw a methodology and strategy to indicate actions required to be taken by responders to: •

Ensure availability of timely, measured and effective response to incidents of oil spill in waters under jurisdiction of the port or facility,

Page 3 of 167

•

Take measures to control the spill within minimum area,

•

Minimise volume of spill by securing the source in most appropriate way,

•

Minimise extent of movement of released oil from the source by timely containment,

•

Minimise environmental impact by timely containment and recovery response,

•

Maximise effectiveness of recovery actions through selection of appropriate equipment and techniques,

•

Maximize response effectiveness through trained and competent, operational and response teams,

•

Guide response personnel through the process of managing a spill originating within their area of operation,

•

Mitigate consequences of oil pollution incidents ,

•

Allow those involved in rsponse to rapidly disseminate information to parties involved and to ensure optimum deployement of available equipment. 1.3 PLAN ELEMENTS This Plan is a set of guidelines and instructions that outlines the steps that should

be taken before, during and after an oil spill emergency. The Plan has to accordingly, pay attention to all the possibilities that could go wrong and “contingent” upon actual events, has the contacts, resource lists, and strategies to assist in response to the spill. As incumbent by a reasonably workable plan, this Plan provides details of actions required to be initiated and taken to prepare for and respond to spills and address different situations that may arise during or after a spill. The Plan is structured on four major elements , viz: Page 4 of 167

1.3.1 Hazard Identification While, it is impossible to know when an oil spill is going to happen and how much oil is likely to be spilled, however, it is possible to identify where oil is stored, the corridors through which it travels and the industries that use large quantities of oil. Since, different situations can affect the ability of response personnel to contain and clean up an oil spill, such as weather and geographic conditions and spill size, this Plan has attempted to address actions and activities to be undertaken under different conditions. The following information has been put into use as a part of hazard identification: • Types of oils received, stored in or transported through the area of operation, • Locations where oil is received in large quantities and mode of transportation used to receive the oil, such as vessels and pipelines etc, • Weather conditions that would affect response operations in the area during different times of the year, • Location of response equipment, trained personnel and other resources that could be called in for response to the spill. 1.3.2 Vulnerability / Sensitivity Analysis The vulnerability analysis section of the Plan is an attempt to collate and provide information about resources and communities that could be harmed in the event of a spill. This information helps personnel involved in clean up operations to exercise identified reasonable, well‐informed choices on protecting areas of high sensitivity ‐ biological, economical and public utilities, that are vulnerable and of concern for public

Page 5 of 167

health and environment. Vulnerability information taken into account for this Plan includes the following that have been indicated on concerned area maps ‐ •

Shoreline types and ranking based on sensitivity to oil,

•

Biological resources sensitive to oil or emergency response actions,

•

Human use resources sensitive to oil or useful during response operations, 1.3.3 Risk Assessment As required of a Contingency Plan, this Plan has tried to compare the hazard and

vulnerability in a particular location to see the kind of risk that are posed and then to addresses those problems by determining how best to control the spill, how to prevent certain ecological elements or environments from exposure to oil, and how best to advise the local civil authority of the dangers that could be posed by the spill and how to address them and to repair the damage done by the spill. 1.3.4 Response Actions / Resources As a part of this Plan, the port, facility or the identified OSRO is responsible to undertake spill mitigation operations apart from managing, acquiring and maintaining oil spill response equipment and resources appropriate for response. Equipment, resources and personnel will be stockpiled at one or more suitable location/s as necessary to meet response requirements within shortest period. The team nominated by the executing authority ( in this case the Chairman, Mumbai Port ) or any OSRO nominated by the executing authority will give effect to all the response mechanisms and procedures identified by the Plan and maintain trained personnel to undertake the operations. Page 6 of 167

1.4

RESPONSE POLICIES ‐ GIVING EFFECT TO PLAN

Objectives and aims of the Plan are achieved through formulation of oil spill response strategy for the area of operation and oil spill response plan to be addressed through Operations Manual. While, this Plan includes reference to wider concerns like Environmental Sensitivity etc, the Operations Manual will be the response activity guide along with other documents to ensure execution of each part of response and implementation . The key deliverables to give effect to the Plan are: ( i )

Action Planning ‐ Tactical action strategies including initial containment

and control procedures and locations for Tier 1 events are developed on geographic basis with resources located strategically within the area of operation at one or multiple sites. ( ii ) Environmental Sensitivity Factors ‐ Environmental sensitivity and risk factors having been taken into account through observations, secondary information sources and studies, the results are integrated into identification of high‐risk areas / features and protection/cleanup priorities and selection of appropriate response procedures, resources and resource staging areas. ( iii ) Response or Field Guide manuals ‐ Describing procedures for containment and control actions, the manuals contain information on deployment of equipment etc as per the location of spill and safe practices that need to be adhered to by responders. ( iv ) Availability of equipment, and employment and training – Response personal being the main key and element in any response, their expertise and knowledge of procedures and handling of spill is spelled through the CP. Page 7 of 167

1.5

LOCATION BASED RESPONSE

THE SCOPE OF THIS PLAN EXTENDS TO FOLLOWING LOCATIONS AND FACILITIES STRETCHED OVER A GEOGRAPHICAL AREA OF MORE THAN 400 SQ KMS WITH MULTIPLE OPS GOING ON AT THE SAME TIME ‐

PORTS OF MMB AND JNPT

‐

TRANSHIPMENT FACILITIES AT JAWAHAR DWEEP, PIR PAU, MUMBAI HARBOUR AND JNPT

‐

ONGC FACILITIES AT NHAVA AND LANDFALL POINT FOR URAN REFINERY

Protection of these areas requires rapid and well‐planned tactical

response actions. Considering the size and complexity of the area, the Plan has divided the area into manageable geographic segments. (Individual or multiple areas may be grouped into functional response zones, based on logistical issues including accessibility and driving times from resource bases). Geographical areas of concern in this Plan are : ( i ) Anchorage/ Lighterage area (ii )

Alongside cargo berths at MbPT and JNPT

(iii) Jawahar Dweep (iv )

Pir Pau

(v )

JNPT oil berths at Nhava and Sheva

1.6

INTEGERATION WITH WIDER AREA OPERATIONS ( Spill classification

and Tier Response ) This Plan is based on internationally accepted standards of Tier classification and response concept to describe different categories of oil spill events based on their severity and availability of response resources. Tier classifications are determined in

Page 8 of 167

consideration of spill volume, sensitivity of threatened resources and other factors that can only be determined at the time of the incident.

This Plan, is first of the actions in the series to combat oil spill and is open

to call for a bigger response activity at national level and is meant to address a spill of up to 7oo tonnes as per Tier 1. Accordingly, all calculations and illustrations in this Plan are as per a spill of 700 tonnes. Oil Spill Classification Standard (Tiers) definitions are: Tier 1 (Minor Spills): The events include small operational spills, which can be dealt on site by local staff and contractors. Study of available spill data indicates that Tier 1 spills occur largely during operations such as bunker ops, refuelling, pig launching and receiving, valve and flange leaks, and routine operation and maintenance activities and are classified as spills up to 700 tonnes. In most cases, containment and clean up is effected using the equipment held by facility operator or OSRO and also by use of Spill Response Kits maintained at the facility. All requirements of notification etc to Central authority are observed, though support from outside agencies is not required. Tier 2 (Major Spills): Tier 2 incidents include larger spills that would require additional local (in‐country) resources and manpower. Tier 2 spills usually result from large fuel losses, loading hose failure or small to medium pipe failures (hole size up to 50 mm). Cleanup is effected by dedicated oil spill equipment from in country sources, equipment stockpiles, in‐country oil spill response contractors and by sharing equipment held with other operators. In the event of Tier 2, support from the Central spill controller would be required to be called for. Tier 3 (Crisis Event): Tier 3 incidents include very large, possibly ongoing spills, that would require additional resources from outside the country. Such spills are expected to be rare and may occur as a result of events such as full diameter pipe Page 9 of 167

rupture or an uncontrolled tank failure or a large tanker grounding. Response operation utilize all available in‐country Tier 2 resources, augmented by additional assets from outside the country. Extensive support from the Central authority would be required in such an event. 1.7

PLAN FACTORS

The following factors are taken into account for the purpose of studying the risks and for preparation of the Contingency or response plan . •

Geographic location, coastline, area sensivity

•

Type of oil/product, volume of traffic, quantities of cargo handled, frequency of handling

•

Types of operation, terminal design, condition of facilities

•

Quality of shipping/vessel types

•

Weather, sea conditions, time of day, navigation hazards

•

Response strategies, training programmes

1.8

REVIEW, REVISION AND UPDATES

Contingency Plan being a sequence and layout of dynamic operating

procedures and parameters is subject to revision due changes in operational parameters of port, cargo, equipment innovations and changing response strategies. Exercises and real time drills being operational tasks might also necessitate a review of plan to be undertaken to incorporate the observations made, apart from the above mentioned.

Accordingly, a study in detail of observations made during every response

operation would be undertaken by CMT with a view to incorporate the observations into the Plan for easy and flaw less implementation. Page 10 of 167

1.9

INTERFACE WITH OTHER PLANS

A spill situation may be, one of the emergencies arising out of an incident

or a number of incidents. Such incidents could be natural or man‐made leading to emergencies like fire, gas leak, threats or chemical spills. In the event of multiple emergencies, while the spill response will be undertaken as per this Plan, response to other emergencies will be as per the Disaster Management Plan of the particular facility, port, installation or terminal. Page 11 of 167

2.0 PLANNING AND ADMINISTRATION In accordance with the National Oil Spill Disaster Contingency Plan (NOS‐DCP) all Ports or facilities handling oil and oil products are required to maintain Tier‐I Oil Spill Response (OSR) capabilities to undertake response activity within their area of operation. Accordingly, the ports of Mumbai and Jawaharlal Nehru Port are required to set up and sustain Tier‐I OSR facilities in Mumbai / JNPT Harbour in co‐ordination with oil companies operating at these Ports. For this purpose, MbPT, JNPT and other Participating Oil Companies (POCs) viz. ONGC, BPCL, HPCL, IOCL, CTTL, TPC & RIL have executed a Memorandum of Understanding (MOU) for sustenance of Tier‐1 OSR facilities for combating oil spills at and in surrounding area within Mumbai / JNPT Harbour. Under the said MOU, it has been decided to put in place Tier‐I Oil Spill Response Services in Mumbai and JNPT Harbour for conduct of oil spill operations and mitigation of pollution within the identified area of operation. 2.1

AREA LAYOUT

Since, the fall outs of any accident being addressed by any Contingency Plan cannot be confined and limited to geographical boundaries within the area of jurisdiction and are likely to have an impact on areas beyond the area of addressal, it is desirable to have a knowledge of the area. The area of operation of this Plan is a part of Mumbai Harbour an area encompassing Mumbai estuary. Mumbai Harbour or Front Bay (Figure 2.1) is a natural deep‐water harbour in the southern portion of Ulhas River estuary. The harbour is spread over 400 square kilometers (150 sq mi) and is protected by the mainland of Konkan to east and north Page 12 of 167

and the island city of Mumbai to west. The harbour opens to south to Arabian Sea. The narrower, northern part of the estuary is called Thane Creek . Front Bay is the official name of the harbor, so named because the city started as a tiny settlement facing the harbor. The water body behind the original settlement, forming an arc between the former Colaba island and Bombay island, up to Malabar Hill promontory or peninsula, is called Back Bay. Front Bay is home to Mumbai Port, which lies in the south section of the western edge of the harbor. Jawaharlal Nehru Port and Navi Mumbai lie to the east on the Konkan mainland, and the city of Mumbai lies to the west on Salsette Island. There are six islands in Mumbai Harbor, a number of which are within the area of operation and are active in port activities. ( i )

Butcher Island, also known as Jawahar Dweep , is used as an oil terminal

by Mumbai Port. It has jetties for tankers and various other infrastructure for offloading crude oil and for loading refined petroleum products. The island is restricted to port employees, and not open to public. Crude oil is stored in tanks on the island and is piped to Wadala for refining . Most of the island is covered with dense vegetation with a hillock rising from the centre of the island. It is located 8.25 kilometres (5.13 mi) from Gateway of India. ( ii )

The second island named, Cross Island is a small, uninhabited islet just

off the coast of Dockyard Road. ( iii ) Gharapuri Island, also known as Elephanta Island, is the best known of the islands in Mumbai Harbor and is a popular tourist destination because of the island’s Elephanta Caves, that have been carved out of rock. The island has an area of 16 km2 (6.2 sq mi) and is located at approximately 18.95°N 72.93°E. The area comes

Page 13 of 167

under the jurisdiction of Raigad district and is thickly wooded with palm, mango, and tamarind trees. The island is accessible by ferry from Mumbai, being about 10 kilometres (6.2 mi) from the south east coast of the island city. From the boat landing stage on the island, a walkway leads to steps that go up to the famous caves. There is also a narrow‐gauge toy train from the boat area on the dock to the base of the steps leading up to the caves (about 600 meters). ( iv ) Middle Ground is a small islet off Naval harbour. It features an antique coastal gun battery of the Indian navy. Gun salutes are exchanged with Indian Naval vessels as per ceremonials ( V ) Oyster Rock is a small group of rock outcroppings in the harbor. The area has restricted access and is used for naval exercises. ( vi ) Salsette Island is the largest island on which the cities of Mumbai and Thane are located. It is separated from the Konkan mainland by Vasai creek and the Ulhas river. Creeks The area is marked by a number of creeks that open into the harbour. The creek areas are ecologically sensitive and have thick mangrove vegetation and are navigable to some distances. The shallow mudflats stretch long distances all along the banks. 2.2.

MUMBAI PORT

The Port of Mumbai is situated almost midway (Latitude 18o 54’ N, Longitude 72o 49’ E) on the West coast of India and is a natural deep water Harbour of about 400 square kilometres protected by the mainland of Konkan on its East and Island of Mumbai on its West. The deep waters in the Harbour provide shelter for shipping throughout the year. The approaches to the Harbour are well lighted, with Prongs Lighthouse to the Page 14 of 167

North, visible 27 kilometres and Kennery Light House to the south visible 29 kms. The entrance to the Harbour which has approaches from the South‐west is between Prongs Reef and Thall Reef lying off the mainland to the South‐east, a distance of about 9 kilometres. Figure 2.1 MUMBAI HARBOUR

Fig 2.1 Mumbai Harbour

Page 15 of 167

The main navigational Channel is, for the most part, a natural deep‐water fairway. The channel has been deepened to 11 meters. With a mean high water neap tide of 3.3 meters, the channel is adequate to meet the requirement of a large number of cargo vessels, passenger ships and deep draft tankers. With good lighting arrangements navigation is allowed at the port round the clock. The port is administered by Mumbai Port Trust ( Mb PT ), an autonomous corporation. The port is primarily used for bulk cargo, while most container traffic is directed to Jawaharlal Nehru Port (Nhava Sheva) across the harbour. The first of the present‐day docks of Mumbai Port were built in the 1870s. Bombay Port Trust (BPT) was established as a corporation on June 26, 1873. The port and the corporation took their present names in the 1990s. Over decades, the port has undergone tremendous expansion, with addition of berths and cargo handling capacities. Mumbai’s expanding growth and population pressure has led to the establishment of Jawaharlal Nehru Port across Mumbai Harbour in Navi Mumbai on the Konkan mainland. This port began operations in 1989 and handles most of the container traffic.

Page 16 of 167

Figu ure 2.2 ‐ Mu umbai PORT T 2.2.1 Cargo Han ndling The p port handless both dry aand liquid caargo at diffeerent jettiess and locatio ons apart frrom undertaaking Lighteerage operaations throu ugh barges. Page 1 17 of 167

( i )

Indira Dock

Indira Dock having a total water area of 24.04 hectares and a quay length of about 4000 meters is an enclosed wet dock . The Dock has an Entrance Lock 228.6 meters long and 30.5 meters wide though which vessels can enter or leave the docks at any state of tide. There are 21 berths inside the basin and 5 berths along the harbour wall with a designed depth of 9.14 meters and 7.5 meters respectively. Berthing depths inside the basin can be increased by 1.20 meters by pumping water.

The two berths on the Southward extension of East arm of Indira Dock are

Ballard Pier Station and Ballard Pier Extension. Ballard Pier Extension berth is 244 meters long and has a modern passenger Terminal Building. It has a designed depth of 9.75 meters. Ballard Pier Station berth caters to container vessels and has a designed depth of 9.1 meters. ( ii ) Liquid Cargo Terminal ‐ Jawahar Dweep There are four jetties at the island Jawahar Dweep for handling Crude oil and Petroleum products. One of the jetties at Jawahar Dweep, which was commissioned in 1984 can handle tankers with a maximum loaded draft of 12.5 meters corresponding to 125,000 Displacement tons. Two of the jetties ( J‐1 and J –3 ) can accommodate tankers up to 70,000 Displacement Tons and 228.6 m length, while, the third jetty can berth tankers of 213.4 m length and up to 48,000 Displacement Tons. The berthing dimensions and permissible parameters are as per table 2.1.

Page 18 of 167

Dock

Dimension

JD marine Oil Terminal ( 3 Berths )

Max. Normal Dimensions

Max

LOA

225.55

237.75

Beam

39.62

Draft ( designed ) 10.97 to 11.58 (with tide ) Max. Disp

JD 4th Berth

oversize

70,000 Tons (Berths1 &3)

LOA

300.00

Beam

39.62

Draft ( designed )

12.25 to 14.30

Max

1,25,000 tons

Table 2.1 ‐ PERMISSABLE BERTHING PARAMETERS at JD Jetty 1, 2 and 3 are provided with pipelines to handle both crude and products, namely, HSD, Naphtha, FO/LDO, SKO , ATF etc. The details are as per table 2.2. Product

No of headers

Size ( inches) & psi

No & dia of pipeline ( inches )

Crude

10” / 150

2 / 24”

FO/ LDO

10” / 150

1 / 24”

Naphtha

8” / 150

1 / 16”

HSD

8” / 150

I / 16”

White oil

8” / 150

1 / 12”

Dirty ballast

8” / 150

1 / 16”

Table 2.2 ‐

Product handling infrastructure

( iii ) Liquid Cargo Terminal – Pir Pau Chemical and POL products are handled at two jetties at Pir Pau. Old Pir Pau jetty can accommodate tankers of 170.69 m length, while, the new jetty commissioned in Page 19 of 167

December 1996 can handle tankers with a length of 197 m and a draft of 12.0 m. All the jetties are connected to Oil Refineries by a network of pipelines. Dock

Dimensions

Pir Pau ( Old )

Pir Pau ( New)

Max normal

Max. Oversize

LOA ( Day light )

170.69

178.30

Beam

25.91

28.96

Draft

6.40 to 7.5

Max Displacement

19,000 tons

LOA ( Day Time )

191.0

Beam

28.0

Draft

11.0

9.5 ( Night )

47,000 tons

Max displacement

Table 2.3 ‐ PERMISSABLE BERTHING PARAMETERS at Pir Pau

The cargo handled at Pir Pau and line sizes are as per table 2.4.

Product

Line size

Operated by

Lube Oil

8”

IOBL

LPG

8”

BPCL

LSHS

12”

BPCL

Chemicals

6”

AEGIS

6”

CTTL

8” and 4”

RCF

Table 2.4 – Cargo and line sizes at Pir Pau jetty ( iv ) Bunders Besides the wet docks, there are along the harbour front a number of bunders and open wharves where the traffic carried by barges/sailing vessels is handled. Page 20 of 167

( v ) Storage Theree are transitt sheds at m most of the b berths and a number o of warehousses in the P Port area for r storage of waiting carrgo and pre‐‐shipment storage of exxport cargo..

Figure 2.3 Jawahar Dw weep 2.2.2 Cargo Stattistics h respect to o number of o vessels an nd cargo haandled for the t years The figures with 2007‐2014 aat MbPT aree as per table 2.5. Page 2 21 of 167

YEAR(Apr – March)

Vessels

POL vessels

POL

2013‐2014

35982

2012‐2013

1949

1018

34785

2011‐2012

2057

1102

33314

2010‐2011

2156

1027

33229

2009‐2010

1639

870

34496

2008‐2009

1612

902

34371

2007‐2008

1709

927

37074

2006‐2007

2236

970

32171

2006‐ 2005

2153

834

cargo

Table 2. 5 ‐ Vessels and volumes of oil cargo handleded at MbPT 2.3 JAWAHALAL NEHRU PORT ( JNPT ) The port lies along the eastern shore of Mumbai harbour off Elephanta Island on the Konkan mainland in location 18 56’43” North and 72 56’24” East . The port shares a common 22.0 Km long main harbour channel with Mumbai Port up to No. 4 berth of Jawahar Dweep ( J D) Terminal which is presently maintained to a depth of 10.7 to 11 mtrs. below Chart Datum. The approach channel from J D to JNPT is 7.2 kms in length with maintained depths of 11 mtrs below Chart Datum with a width 350 meters at entry point i.e 460 meters off the berths. The available depth off the berths is 13.5 meters (Below Chart Datum) Making use of tidal window, large size vessels having a draught up to 12.5 mtrs. are able to navigate through Mumbai harbour main channel and JNP channel. The Port is deepening and widening the existing channel to accommodate up to 14 mtrs. Page 22 of 167

2.3.1 Cargo handling The cargo handling berths comprise of anchorage berth of 600 meters diameter and 2000 meter of quay length for Container Berth apart from 445 meters of quay length for Feeder Container / Cement / Project Cargo Ships. Most of the container cargo is handled from this port only. Details of POL vessels and cargo handled at JNPT are as per table 2.6. YEAR(Apr– March)

Vessels handled POL vessels

POL cargo (‘ooo

2013‐2014

4566

2012‐2013

2588

468

4125

2011‐2012

2916

445

4926

2010‐2011

3100

479

5135

2009‐2010

3096

496

4916

2008‐2009

2973

408

4552

2007‐2008

3106

312

2189

2006‐2007

2775

321

2625

2006‐ 2005

2395

356

Table 2.6 ‐ Vessel and volumes of oil cargo handled at JNPT 2.3.2 Liquid Cargo Berths

The port handles POL cargo for BPCL, IOC and ONGC through dedicated

berths. Cargo for BPCL and IOC is handled at Sheva, while, ONGC handles its Mumbai High supplies and vessels from Nhava. Page 23 of 167

( i )

Sheva

Liquid cargo is handled through the twin berth cargo jetty developed by M/s Bharat Petroleum Corporation Limited and Indian Oil Company Limited for handling liquid cargo including POL products. The jetty is 300 mtrs long with a width of 40.5 mtrs having capacity to accommodate twovessels of 85,000 DWT on seaside berth and 30,000 DWT on shore side berth. Three dock lines are provided for white and black oil with a capacity of 5.5 million tonnes per annum. Jetty is provided wth six 12’ marine loading and unloading arma ( 3each on sea and shore side ) for working cargo. The deredged draught on seaside is 13.5 mtrs and 12 mtrs on shore side. ( ii ) Nhava and Uran

Nhava is the main center for ONGC Mumbai High operations . The vessels

operating in the High receive stores, fuel and lubricants from Nhava. The vessels calling Nhava are largely restricted to OSVs.

ONGC off shore facility – refinery and tank farm, is located at Uran and was established in 1974. The site is about 12 km east of Mumbai and is approachable by all‐ weather motor able roads. The facility receives entire oil and part of natural gas produced in Mumbai offshore oil fields. Both the oil and gas received from offshore is processed at various units for producing value added products like LPG, C2‐C3, LAN, apart from processing, storage and transportation of oil. The unstabilized crude oil is received from offshore platforms through 3 oil trunk lines. 30″ MUT oil pipeline from Mumbai High and 24″ HUT oil pipeline from satellite off‐ Page 24 of 167

sh hore platforrm are the principal feeed stock to o plant. Pro ocessed pro oduct is shipped out th hrough Jawaahar Dweep p.

Figure 2.4

2.4

JAWAHA AR LAL NEHR RU PORT

POL CARGO

Mumb bai Port an nd JNPT aree handling varied v oil and a oil prod duct cargo including i im mported cru ude. List o of oil being h handled at M Mumbai witthin the areea of ops of this Plan are placed att Appendix x 1. Page 2 25 of 167

2.4.1 Chemical characteristics of different oils and their implications Though, chemical characteristics of crude oil and gasoline remain confined within a small range of variations , yet different oils within the category of that ‘ oil’ have a particular chemical signature defining the chemical properties of that class of oils. This signature is of great help to responders while planning response strategy. The processes that the oil would undergo post spill in terms of weathering processes depends on these base properties and weather conditions in the area at the time of spill. The base properties of an oil will determine the physical and chemical changes that would occur when the oil is spilled onto water and will account for its persistence and toxicity. For this reason it is essential to have handy the list of properties of oils being handled in the area. Many oils have a tendency to incorporate seawater and form a water‐in‐oil emulsion, which can increase the volume by a factor of three or four, and the viscosity by several orders of magnitude. Oils with asphaltene contents greater than 0.5 per cent tend to form stable emulsions, called ‘chocolate mousse’, which are particularly difficult to handle. To study the probable behaviour on water and implications regarding effectiveness of different types of on‐water recovery devices and chemical dispersants, all particulars of oil are required to be available to responders. Broad classification of oils as per MARPOL 73/78 is placed at Appendix 2.( The list is not to be considered comprehensive ). Major characteristics of different classes of oil are placed at Appendix 3. Page 26 of 167

3.0 3.1

RISK AND SPILL ASSESSMENT

HAZARD RATING

National Fire Protection Association (NFPA ) has accorded ratings with respect to degree of hazard posed by chemicals being handled in port. The rating is in numbers with respect to flammability ( Nf), health hazard ( Nh) and reactivity ( Nr) . The rating of hydrocarbons ( higher number being more hazardous ) are as per table 3.1 ‐ Product

HIGH SPEED DIESEL

CRUDE OIL

GAS OIL

SKO

NAPHTHA

3 1 Table 3.1 ‐ Hazard Ratings

MOTOR SPIRIT

Flammability (Nf) 3 – Liquids and solids that can be ignited under almost all ambient temperature conditions 2 – Materials that must be moderately heated or exposed to relatively high ambient temperatures before ignition can occur Health ( Nh )

0 ‐ Materials which on exposure under fire conditions would offer no hazard beyond that of ordinary combustible material 1 – materials which on exposure would cause irritation but only minor residual injury if no treatment is given

Page 27 of 167

Reactivity ( Nr )

0 – materials which in themselves are normally stable, even under fire exposure conditions and which are not reactive with water

It is apparent that risks to human life in terms of flammability, health and reactivity are not very significant and can be handled with some degree of expertise. 3.2

CAUSES OF OIL SPILL

The common causes of spill are •

Cargo operations‐ loading, discharge

•

Ship collision, or grounding

•

Bunker/ fuelling operations

•

Ship distress / sinking

•

Pipeline ruptures /accidental spills from sub‐sea/over the sea/shore approach (in the tidal zone) pipelines

3.2.1 Location of spill within the scope of this Plan

Based on the location of vessel at the particular time of incident within the area of operation, the likely spill could occure at any of the following locations ( i )

Sea or in channel due collission etc during passage

(ii )

Close shore due grounding or

( iii ) Alongside at jetty or at the terminal during cargo operations Not withstanding the above locations, it is possible that an eventuality occuring at sea like a collission or mechanical failure could lead to a situation where the consequences would be felt in some other location at a coastal location.

Page 28 of 167

3.3 OIL SPILLS ‐ HISTORIC DATA

Historic data, oil properties, climate, local meteorology and environmental sensitivities are important factors in assessing the risk, behavior, fate and potential consequences of spilled oil. Historic data being secondary data available in public domain is a good measure of causes, probabilities and averages of the happening of any scenario. Historic data is of great help to responders and Contingency Planners since the study of this data helps in identifying trends and causes of spills which in turn help in identifying and implementing remedial approaches as per the gravity and frequency of incidents and plan appropriate response . 3.3.1 Analysis and figures ITOPF has carried out extensive studies on all aspects of oil spill and compiled statistics over number of years. The causes have been annalyised under two heads viz. operations and accidents. The data establishes that most spills from tankers result during routine operations such as loading, discharge of cargo, bunkering and normally occur in ports or at oil terminals and the majority of these operational spills are small, with some 92% involving quantities of less than 7 tonnes. Accidents involving collisions and groundings generally give rise to much larger spills involving quantities in excess of 700 tonnes. Figures for the period 1974 to 2013 for spills of

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Materi PPT B3 Zat Pewarna
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Materi PPT B3 Zat Pewarna I.

II.

Tujuan : • Memberi kesan menarik bagi konsumen • Menyeragamkan warna pangan • Menstabilkan warna • Menutupi perubahan warna selama proses pengolahan • Mengatasi perubahan warna selama penyimpanan Zat pewarna dibagi menjadi dua macam, yaitu zat pewarna alami dan zat pewarna sintetis. a. Zat pewarna alami   Karamel, yaitu pewarna alami berwarna coklat yang dapat digunakan untuk mewarnai jem/jeli (200 mg/kg), acar ketimun dalam botol (300 mg/kg, dan yogurt beraroma (150 mg/kg)  Beta-karoten, yaitu pewarna alami berwarna merah-oranye yang dapat digunakan untuk mewarnai acar ketimun dalam botol (300 mg/kg), es krim (100 mg/kg), keju (600 mg/k, dan lemak dan minyak makan (secukupnya).  Klorofil, yaitu pewarna alami berwarna hijau yang digunakan untuk mewarnai jem/jeli (200 mg/kg) atau keju (secukupnya).  Kurkumin, yaitu pewarna alami berwarna kuning-oranye yang dapat digunakan untuk mewarnai es krrm dan sejenisnya (50 mg/kg), atau lemak dan minyak makan (secukupnya).

b. Zat pewarna sintesis  merupakan bahan kimia yang dengan sengaja ditambahkan pada makanan untuk memberikan tambahan warna yang diinginkan karena warna semula hilang selama proses pengolahan atau karena seseorang menginginkan adanya warna tertentu.



Bahan berbahaya yang dilarang untuk makanan dan minuman menurut PerMenKes RI No. 239/Menkes/Per/V/1985 ada 30. Contoh :

Tartrazine (E102 atau Yellow 5)

Pewarna kuning yang banyak digunakan dalam makanan dan obat-obatan. Selain berpotensi meningkatkan hiperaktivitas anak , pada sekitar 1-10 dari 10.000 orang, Tartrazine menimbulkan efek samping langsung seperti urtikaria (ruam kulit). Rhinitis (hidung meler), asma, purpura (kulit lebam). Intoleransi ini lebih umum pada penderita asma atau orang yangsensitive terhadap aspirin. 2.

Sunset Yellow (E110, Orange Yellow/Yellow 6)

Pewarna yang dapat ditemukan dalam makanan seperti jus jeruk, es krim, ikan kalengan, keju, jeli, minuman soda dan banyak obat-obatan. Untuk sekelompok kecil individu, konsumsi pewarna adiktif ini dapat menimbulkan urtikaria, rinitis, alergi, hiperaktivitas, sakit perut, mual dan muntah 3.

Ponceau 4R (E124 atau SX Purple)

Pewarna merah hati yang digunakan dalam berbagai produk, termasuk selai, kue, agar-agar dan minuman ringan. Selain berpotensi memicu hiperaktivitas pada anak, pewarna ini dianggap karsinogenik (penyebab kanker) di beberapa Negara. 4.

Allura Red (E129)

Pewarna sintetis merah jingga yang banyak digunakan pada permen dan minuman. Pewarna ini sudah banyak dilarang di banyak Negara. 5.

Quinoline Yellow (E104)

Pewarna makanan kuning ini digunakan dalam produk seperti es krim dan minuman energy. Zat ini sudah dilarang di banyak Negara karena dianggap maningkatkan resiko hiperaktivitas dan serangan asma. 6.

Metanil Yellow

Pewarna makanan ini juga merupakan salah satu zat pewarna yang tidak diizinkan untuk ditambahkan ke dalam bahan makanan. Metanil Yellowdigunakan sebagai pewarna untuk produk-produk tekstil (pakaian), cat kayu, dan cat lukis. Efeknya sama seperti Rhodamin B.

III.   IV. –

Dampak Dampak jangka pendek  mengakibatkan reaksi alergi seperti nafas pendek, dada sesak, sakit kepala, dan iritasi kulit. Dampak jangka panjang  Menyebabkan Sarkoma (sejenis tumor) dan kanker payudara : Black 7984 dan Auramine Pencetus kanker Kanker kandung kemih Tumor seperti kelenjar pada paru-paru dan kanker limfa Kerusakan lapisan luar adrenalin Merusak hati dan ginjal Cara Mendeteksi Warna mencolok dan cerah mengkilap. Warna tidak merata, ada yang menggumpal. Rasa sedikit pahit. Cenderung menimbulkan bau aneh. Tenggorokan terasa gatal saat memakannya. Biasanya tidak mencantumkan kode, label, merek, atau identitas produsen.

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CITRA WANITA DALAM KARYA SENI RUPA-Muhajir Nadhiputro (Universitas Negeri Surabaya)

CITRA WANITA DALAM KARYA SENI RUPA-Muhajir Nadhiputro (Universitas Negeri Surabaya)
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URNA, Jurnal Seni Rupa merupakan jurnal ilmiah yang diterbitkan oleh Jurusan Pendidikan Seni Rupa, Universitas Negeri Surabaya. URNA berisikan artikel konseptual, resume penelitian, dan tinjauan buku. Bertujuan untuk mengembangkan dan mengomunikasikan secara luas perkembangan seni rupa dan pendidikan seni rupa baik yang sifatnya teoretis maupun pragmatis. Terbit dua kali setahun, tiap bulan Juni dan Desember.

Penanggung Jawab

: Eko A.B. Oemar

Ketua Penyunting

: I Nyoman Lodra

Wakil Ketua Penyunting : Asy Syams Elya Ahmad Penyunting Ahli

: Djuli Djatiprambudi (Universitas Negeri Surabaya) Martadi (Universitas Negeri Surabaya) Sofyan Salam (Universitas Negeri Makassar) Tjetjep Rohendi Rohidi (Universitas Negeri Semarang)

Penyunting Pelaksana

: Salamun Kaulam Asidigisianti Surya Patria Muhajir Nadhiputro Marsudi

Sekretaris

: Nova Kristiana

Administrasi

: Fera Ratyaningrum

Alamat Redaksi: Jurusan Pendidikan Seni Rupa, Universitas Negeri Surabaya Gedung T3 Lt. 2, Kampus Lidah Wetan Surabaya 64732 Telp/Fax. 031-7530865 | E-mail: [email protected] [email protected] | Website: htp://www.urna-jurnalsenirupa.org

Gambar sampul depan: Wajah. Lukisan karya Salamun Kaulam (2007).

ISSN 2301–8135 Vol. 1, No. 1 (Juni 2012): 1–105

daftar isi Artikel: PENDEKATAN KONSTRUKTIVIS DALAM PEMBELAJARAN SENI BUDAYA

Martadi (Universitas Negeri Surabaya)

PERLINDUNGAN PENGETAHUAN TRADISIONAL DAN PRAKTIK HAK KEKAYAAN INTELEKTUAL

I Nyoman Lodra (Universitas Negeri Surabaya)

NILAI ESTETIKA DALAM KOMODIFIKASI WADAH DI MASYARAKAT HINDU BALI

I Ketut Side Arsa (Institut Seni Indonesia Denpasar)

PROSES APRESIASI DAN KREASI DALAM TRITUNGGAL SENI

M. Sattar (Universitas Negeri Surabaya)

PENGGUNAAN UNSUR-UNSUR BUDAYA BALI DALAM BOG-BOG BALI CARTOON MAGAZINE

I Wayan Swandi (Institut Seni Indonesia Denpasar)

CITRA WANITA DALAM KARYA SENI RUPA

Muhajir Nadhiputro (Universitas Negeri Surabaya)

MAKNA SIMBOLIS RAGAM HIAS PENDAPA TERAS CANDI PANATARAN Rustarmadi (Universitas Negeri Surabaya)

ISSN 2301–8135 Vol. 1, No. 1 (Juni 2012): 1–105

Resume Penelitian: PERSEPSI GENDER GAMBAR ILUSTRASI DALAM BUKU SEKOLAH ELEKTRONIK PELAJARAN ILMU PENGETAHUAN SOSIAL SEKOLAH DASAR KELAS I – III

Asidigisianti Surya Patria (Universitas Negeri Surabaya)

PENGEMBANGAN MEDIA DIGITAL KRIYA TOPENG MALANG UNTUK PEMBELAJARAN SENI BUDAYA SEKOLAH MENENGAH PERTAMA

Marsudi (Universitas Negeri Surabaya)

Tinjauan Buku: BUKU PENTING DI TENGAH DUNIA SENI RUPA YANG GENTING Djuli Djatiprambudi (Universitas Negeri Surabaya)

101

CITRA WANITA DALAM KARYA SENI RUPA

Muhajir Nadhiputro

Abstrak: Pencitraan wanita dalam karya seni rupa beraneka ragam, bergantung pada latar belakang penciptaan karya tersebut. Kajian atas sejumlah karya seni rupa ini menyimpulkan beberapa jenis pencitraan antara lain wanita sebagai simbol kesuburan, feminin, sifat keibuan, manusia lemah, penghias dunia lelaki, keagungan dari wanita sempurna, simbol kepahlawanan dan didekonstruksi. Abstract: Imaging of women in art works really vary, depending on the background of the creation of the works. This study concerning a number of art works concluded several types of imaging such: as a symbol of fertility, feminine, maternal love, a delicate human being, a ornament to the world of men, the glory of perfect women a symbol of heroism, deconsrtucted as an unatractive human being. Kata kunci: citra, wanita, karya seni rupa

Banyak cara untuk mencitrakan wanita, dalam tradisi Jawa wanita dicitrakan sebagai sumber keberuntungan atau kesuburan (Dewi Sri). Wanita juga sering disimbolkan sebagai bumi yang mengayomi (Dewi Pratiwi). Tetapi di samping citra positif, dalam perspektif gender, wanita lazim pula dicitrakan secara negatif, sebagai sosok inferior di bawah subordinasi laki-laki. Wanita atau perempuan, dalam masyarakat patriarkhi “didudukkan” lebih rendah daripada laki-laki. Dalam perspektif gender atribut-atribut kewanitaan seperti lemah lembut, pasif, patuh, ketergantungan dan sifat-sifat femininitas yang lain bukanlah kodrat akan tetapi konstruksi sosial yang dikreasi oleh kaum laki-laki. Tiap-tiap pencitraan wanita mulanya muncul dari seting yang bersifat kontekstual, dari latar belakang sosial budaya tertentu dan untuk tujuan tertentu pula yang kemudian menjadi mitos. Karena itu, maka tidak terlalu berbeda dasar kewanitaannya antara dewi Tamara, raja putri dari Kaukasia, Hatsjepsut dari Mesir Kuno, Nyi Roro Kidul dalam mitologi Jawa dengan kupu-kupu malam di pinggir jalan. Bedanya hanya yang satu penakluk para raja sedang yang lain penakluk para hidung belang. Barangkali selamanya wanita tinggal sebuah misteri. Apakah ia

Muhajir Nadhiputro adalah Staf Pengajar pada Jurusan Pendidikan Seni Rupa, Fakultas Bahasa dan Seni, Universitas Negeri Surabaya. e-mail: [email protected]

akan dianggap sebagai dewi yang agung dan keramat, ataukah dipandang sebagai setan penggoda, tergantung dari kasus dan tradisinya. Citra wanita tidak hanya lazim diungkapkan secara verbal melalui karya sastra, tetapi acap pula terekspresikan dalam bentuk visual seperti yang dilakukan oleh para perupa. Baik citra kewanitaan yang terungkap lewat bahasa verbal maupun lewat bahasa rupa pada dasarnya adalah merupakan perwujudan dari konsep kewanitaan suatu bangsa, kelompok etnis, atau bahkan perorangan semata yang karena itu maka beraneka ragam pula bentuknya. Berangkat dari latar belakang tersebut tulisan ini mencoba memaparkan pencitraan wanita oleh para perupa yang terjabarkan lewat karya-karyanya. Data diperoleh dari literatur yang memuat gambar-gambar (reproduksi wanita) yang diambil sesuai kebutuhan dan tujuan. PATUNG DAN LUKISAN “VENUS” Patung Venus dari Willendorf boleh jadi merupakan perwujudan patung tertua yang menggambarkan igur wanita. Patung ini berasal dari masa prasejarah Eropa, dari era Paleolitikum sekitar 20.000 tahun sebelum masehi. Di dalam sejarah Romawi Venus dikenal sebagai dewi kecantikan, cinta, dan perjodohan. Venus juga diidentikkan dengan Aprodit, yang hidup dalam mitologi Yunani.

Gambar 1. Patung Venus dari Willendorf

Mengamati patung ini dengan menggunakan kriteria kecantikan kita era sekarang tidak akan menemukan hasil yang memuaskan, karena tidak dapat dijumpai citra kecantikan seorang dewi di dalamnya. Secara bentuk patung ini dapat dikatakan tidak ideal, sebab postur tubuhnya terlalu gendut cenderung bulat. Agaknya Venus dari Willendorf ini merupakan perwujudan dewi kesuburan. Deskripsi

MUHAJIR N., Citra Wanita dalam Karya Seni Rupa •

patung tersebut ialah kepala besar yang seolah-olah tidak memiliki leher, dengan berhiaskan rambut keriting. Dengan kata lain, bagian kepala langsung berhubungan dengan tubuh yang didominasi oleh menggelembungnya buah dada dan perut besar, dengan central point bagian pusar. Dalam keadaan demikian, patung bugil ini jelas tidak memiliki pinggang langsing. Lebih lanjut kesan gendutnya disokong pula oleh pangkal paha yang besar, sementara ujung kakinya teramat kecil. Agaknya, karena sebagai lambang kesuburan, maka pengerjaan teknis patung Venus dari Willendorf dipusatkan pada organ-organ tubuh yang secara fungsional mendukung aspek reproduksi, yakni buah dada, perut dan wilayah sekitarnya. Raut muka, tangan dan kaki nyaris tidak dikerjakan.

Gambar 2. Lukisan Venus karya Sandro Boticelli

Salah satu karya unggulan Sandro Boticelli ialah Venus yang berangka tahun 1486 (Monteverdi, 1985: 220). Bila dibandingkan antara lukisan Venus kreasi Botticelli dengan patung Venus dari Willendorf terdapat persamaan dan perbedaan sebagai berikut, persamaannya, dua karya tersebut diungkapkan secara telanjang badan dan sama-sama berkesan agung. Sedang perbedaannya, Venus Willendorf lebih memancarkan keagungan esoteric (keagungan dalam), sedang Venus-nya Boticelli adalah perpaduan antara keagungan esoteric dan “keanggunan eksoterik” yang secara nyata terjabar lewat “kesempurnaan” bentuk lahiriahnya. Membandingkan keduanya secara tata lahiriah memang berbeda kontras. Karakteristik bentuk visual Venus dari Willendorf sebagaimana telah disebutkan serba tambun kebulat-bulatan (identik dengan kesuburan), sedangkan Venus Boticelli digambarkan sebagai sosok wanita (dewi), dengan kullit kuning langsat (mulus) dan rambut terurai panjang hingga bagian ujungnya dimanfaatkan untuk menutupi

52 • URNA, Jurnal Seni Rupa: Vol. 1, No. 1 (Juni 2012): 50–62

alat kelaminnya. Kesan secara keseluruhan lukisan Venus Boticelli ialah Feminin. Venus lainnya adalah yang dilukis oleh Francois Boucher (1703–1770). Dibandingkan dengan Venus-venus terdahulu, Venus karya Boucher terkesan sama sekali tidak memancarkan keagungan esoterik. Ia dapat dikatakan lebih menyinarkan kecantikan eksoterik yang cenderung artiisial kulit dangkal. Dalam menggali hakikat kewanitaan agaknya Boucher sangat dipengaruhi oleh gemerlapnya kehidupan para putri bangsawan Perancis yang sangat mewah. Maka lahirlah dari tangannya Venus ratu glamour, yang oleh van Peursen (1976) disindir lebih menyerupai seorang wanita muda yang puas diri dan sedang melamun, kenes dan terbuai dalam kecantikannya. Adegan ini seolah-olah dipandang oleh seorang seniman yang wawasan spiritualnya kurang mendalam, sehingga kendatipun sosok ini digambarkan dengan beberapa identitas Venus, seperi kulit kerang dan burung-burung dara namun tetap saja kurang memancarkan keagungan seorang dewi. MADONNA KARYA PARMIGIANINO Dalam tradisi kesenian Kristen tokoh Madonna (Perawan Suci Maria) banyak digambarkan oleh para seniman. Salah satu di antaranya ialah The Madonna of the Long Neck, karya Francisco Parmigianino (Monteverdi, 1985: 263).

Gambar 3. Madonna, lukisan karya F. Parmigianino

Ditilik dari teknik pengerjaannya, lukisan ini, seperti halnya lukisan-lukisan lain dari era Renaissance-Baroque (yang bersifat naturalis) tergolong mapan, dengan komposisi balance asimetri. Upaya menokohkan Madonna dilakukan dengan cara menempatkan tokoh tersebut di tengah-tengah komposisi, dengan menerapkan hukum “perspektif kepentingan.” Madonna, karena dianggap penting maka

MUHAJIR N., Citra Wanita dalam Karya Seni Rupa •

selain ditempatkan di tengah-tengah komposisi, juga digambarkan lebih besar dari objek pelengkap lainnya. Proporsi tubuh Madonna ini serba kepanjang-panjangan, terutama bagian lehernya. Sikap kaki, tangan, dan tubuh Madonna yang tengah memangku bayi (Yesus?) seolah-olah mengalirkan sifat-sifat perawan suci Maria yang agung dan penuh kasih. WANITA DALAM LUKISAN EUGENE DELACROIX, PIETRO DA CORTANA, DAN MANET Eugene Delacroix pada tahun 1827 berhasil menciptakan karya yang menggemparkan berjudul Kematian Sardanapalus. Lukisan itu menggambarkan adegan peperangan antara bangsa Yunani versus orang-orang Turki. Sebagai seniman, Delacroix menaruh interes berat terhadap kesenian dan literatur-literatur Inggris, terutama karya-karya sastra Shakespeare, Scot, dan Byron. Lukisan tentang kematian Sardanapalus adalah karya besarnya yang diilhami oleh dongeng sastranya Byron.

Gambar 4. Kematian Sardanapalus, lukisan karya Eugene Delacroix

Lukisan tersebut selain menegaskan tentang pertarungan isik juga mengeksploitasi bentuk pornograi yang terjabar dalam wanita-wanita telanjang/setengah telanjang tak berdaya menghadapi perlakuan garang dari para lelaki perampas kehormatan. Suasana garang ditunjang pula oleh pemilihan warna yang tepat, coklat bernuansa kemerah-merahan (Janson, 1984: 128). Posisi wanita dalam subordinasi pria, sebagai makhluk yang lemah, yang tak mampu melindungi dirinya sendiri, bahkan tak berani melakukan perlawanan terhadap bahaya yang mengancamnya. Adegan serupa Kematian Sardanapalus dapat disimak pada karya Pietro Da

54 • URNA, Jurnal Seni Rupa: Vol. 1, No. 1 (Juni 2012): 50–62

Cortana berjudul The Rape of the Sabine Women (Monteverdi, 1985: 285). Adegan yang menggambarkan perkosaan terhadap wanita Sabina ini berangka tahun 1629, termasuk dalam era Barok. Memang Pietro da Cortana adalah seorang pelukis dekoratif Barok yang memiliki reputasi besar pada jamannya. Ia sangat mengagumi, dan karenanya terpengaruh oleh karya-karya Titian yang kaya akan warna. Karya-karya masterpiece-nya berupa fresco banyak menghiasi ceiling (langit-langit) istana Barberini di Roma. Hal ini tidak mengherankan karena Paus VIII, seorang patron kuat Pietro berasal dari keluarga Barberini. Mario Monteverdi menggambarkan kepiawaian Pietro: “…agaknya Pietro adalah eksponen gaya Lukisan Dekoratif Barok yang amat tipikal dan spektakuler. Kecakapan teknik tinggi dengan keberanian membuat komposisi warna vibrant (bersemangat, bergetar) adalah ciri khasnya (Monteverdi, 1985: 125). Kembali pada persoalan The Rape of the Sabine Women, lukisan ini menyuguhkan keperkasaan para lelaki yang tengah menjarah tubuh-tubuh wanita. Visualisasi wanita-wanita sintal yang meronta-ronta, didukung dengan warna-warna vibrant mampu menggetarkan syahwat para pemirsa. Dengan demikian suasana dalam lukisan ini sangat tepat dengan tema/judulnya. Kendatipun igur-igur wanita dalam lukisan ini tidak sepasrah wanita-wanita dalam “Kematian Sardanapalus,”—karena berusaha melawan dengan cara merontaronta—tetap saja menempatkan wanita dalam posisi subordinasi pria. Dengan kata lain ketidaksetaraan gender telah berhasil digambarkan secara gemilang.

Gambar 5. Le De Jeuner Sur I’Herbe, karya Manet

Dari mazhab Impresionis kita jumpai Edouard Manet (1832-1883) yang hobi melukis adegan telanjang. Salah satu yang kontroversial ialah Le De Jeuner Sur I’Herbe (Bowness, Alan, 1985: 130), yang menggambarkan suasana kesenangan di

MUHAJIR N., Citra Wanita dalam Karya Seni Rupa •

kebun raya, menampilkan dua pasang lelaki-perempuan dengan teknik pengerjaan naturalis-impressionistis. Dua sosok lelaki dandy nampak sedang merayu pasangannya. Ironisnya, yang lelaki digambarkan berbusana lengkap (parlente), sedang dua ceweknya disuguhkan secara bugil dan setengah bugil. Terasa sekali bahwa dalam adegan tersebut citra wanita tak lebih sebagai penghias dunia lelaki. Berbeda dengan wanita-wanita dalam “Kematian Sardanapalus” dan wanita-wanita dalam “Pemerkosaan wanita-wanita Sabina,” (yang berada dalam suasana ketakutan), wanita-wanita dalam bingkai lukisan Manet ini justeru berada dalam suasana seolah-olah seperti sang putri yang tengah bersanding dengan sang pangeran, yang penuh kenyamanan, keakraban dan kehangatan. Kondisi dan keberadaannya bersama lelaki di perkebunan bukan atas keputusan superior sang lelaki perampas, akan tetapi keputusan yang diprogramkan bersama, dalam posisi tawar yang setara. Namun demikian, tetap saja, seperti kodrat umum yang berlaku, keberadaannya sebagai penghias, pelengkap. WANITA-WANITA DALAM KARYA PICASSO. Pablo Ruis Picasso (1881-1973), pelukis asal Barcelona yang pertama kali belajar corat-coret kepada ayahnya, sebelum menjalani studi formalnya di Barcelona School of Art ini, lebih banyak dikenal sebagai tokoh yang berkutat dalam aliran Kubisme daripada sebagai seniman petualang yang selalu gelisah mencipta dan berinovasi. Padahal selain melukis, Picasso juga membuat karya-karya patung dan grais yang seluruhnya ditaksir mencapai 20.000 karya.

Gambar 6. Marie Therese Walter, lukisan karya Picasso

56 • URNA, Jurnal Seni Rupa: Vol. 1, No. 1 (Juni 2012): 50–62

Ada satu hal lagi yang mungkin terlewat dari pengamatan kita, yaitu kenyataan bahwa Picasso banyak mengangkat objek wanita dalam karya-karyanya. Kebesaran nama Picasso (terutama diukur dari segi materi) bukanlah karena dia bapak Kubisme, akan tetapi lebih disebabkan oleh semangat “menggarap wanita.” Misalnya berkat perkenalannya dengan wanita bernama Fernande Oliver, maka mengalirlah sejumlah lukisan dengan objek wanita (periode merah jambu) yang amat terkenal itu. Begitu pun ketika Picasso melompat dan memantapkan diri dalam Kubisme tetap kita jumpai karya-karyanya yang menampilkan objek-objek wanita. Beberapa contoh yang bisa disebutkan antara lain Les Demosseles de Avignon (Perawan-perawan dari Avignon) kreasi tahun 1907 dan Perenang (wanita) sedang duduk (1930), serta Marie Theresa Walter. Perawan-perawan Avignon menggambarkan lima sosok wanita PSK bugil dalam berbagai gaya, perenang menggambarkan wanita bugil dalam pose duduk bersantai, sedang Marie Theresa Walter menggambarkan kekasih gelap kepercayaan Picasso. Tiga lukisan tersebut diwujudkan dalam gaya Kubisme yang cenderung membelah-belah objek. Berkenaan dengan ini Salvador Dali berujar bahwa Picasso adalah seniman genius abad ke-20, yang telah menghancurkan keindahan. PATUNG IBU DAN ANAK DARI SUMATERA Pelacakan sosok wanita dalam karya seni rupa dari dalam negeri menjumpai igur patung batu dari Sumatera Utara yang menggambarkan sosok ibu sedang memangku/merangkul dua anaknya. Patung ini berasal dari masa Prasejarah Megalitikum, suatu periode yang ditandai dengan ciptaan-ciptaan karya dari material batu berukuran besar. Mengamati patung tersebut dapat dibuat deskripsi sebagai berikut (1) patung ini nampak massif dan berat, (2) tampak sederhana, kaku, hanya mengutamakan esensi bentuk, (3) tanpa ornamen alias polos, (4) ukuran telinga terlampau besar, (5) menggambarkan seorang ibu sedang memangku dua orang bocah, (6) bentuk bocah tersebut tidak seperti anak-anak, akan tetapi lebih menyerupai orang dewasa yang diperkecil ukurannya. Kesan secara keseluruhan yang dapat dirasakan atas citra wanita dalam patung ini ialah sifat keibuan yang penuh kasih sayang dan perlindungan. PRAJNAPARAMITA Pada abad XIII—dalam sejarah kesenian Indonesia kurun waktu tersebut termasuk Masa Klasik/masa pengaruh Hindu-Budha dari India—dapat dijumpai sebuah patung legendaris Sang Primadona Prajnaparamita. Tingkat kemashyuran patung ini dapat disejajarkan dengan patung Nefertiti dari Kesenian Mesir Kuno, atau Monalisa karya Leonardo da Vinci dari era Renaissance Itali. Prajnaparamita dalam ajaran agama Budha dikenal sebagai dewi kebijaksanaan, yang oleh banyak orang dipandang sebagai perwujudan Ken Dedes, istri pendiri Wangsa Singasari (Soedarso, SP (Ed), 1992: 11). Analisis rupa terhadap

MUHAJIR N., Citra Wanita dalam Karya Seni Rupa •

patung Prajnaparamita dapat dipaparkan sebagai berikut (1) tokoh digambarkan dalam posisi duduk bersila di atas padmasana, (2) menunjukkan teknik pengerjaan naturalis tingkat tinggi dengan komposisi simetri, (3) kaya ornamen, namun secara keseluruhan tetap menunjukkan kesan tenang dan anggun, atau dapat dikatakan perpaduan antara pancaran keagungan esoterik dengan keindahan eksoterik, (4) semua ciri tersebut menunjukkan karakteristik patung Klasik Jawa Hindu.

Gambar 7. Patung Prajnaparamita dari Singosari

PATUNG DURGA DARI CANDI JAWI Dalam masa yang sama dengan patung Prajnaparamita, yaitu masa Pengaruh Hindu dapat dijumpai sejumlah patung wanita bernama Dewi Durgamahes Suramardini. Salah satu di antaranya, yang akan dibahas ialah patung Durga yang berasal dari candi Jawi, di Kabupaten Pasuruan Jawa Timur. Personiikasi Durga dalam bentuk patung pada umumnya berupa seorang dewi berdiri di atas kerbau “njerum” (mendekam). Konon kerbau tersebut merupakan penjelmaan Asura, yang suatu saat pernah menjarah dan menguasai kerajaan para dewa. Untuk mematahkan kekuatan bala tentara Asura maka para dewa bersekutu mengerahkan saktinya, yang kemudian terjelmalah Dewi Durga (Holt, 2000). Analisis terhadap dewi Durgamahesa Suramardini dapat dikemukakan sebagai berikut (1) patung durga digambarkan dalam sikap berdiri di atas kerbau Asura yang sedang mendekam, (2) Durga digambarkan dengan atribut lengkap seperti mahkota, telinga berhiaskan kendala yang memanjang dan mewah, kalung mutiara yang berangkap-rangkap, memakai gelang dan binggel, (3) tangannya berjumlah delapan: tangan sebelah kanan menarik ekor kerbau, sedang tangan kirinya “menjambak” (menarik paksa) rambut Asura (4) tangan yang lain memegang senjata cakra, sangkha, dhanu,

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khadga, trisula, angkusa, khetela, dan sara, (5) komposisi bentuk nyaris simetri, (6) teknik naturalis, dengan kualitas pengerjaan satu tingkat di bawah patung Prajnaparamita di atas. WANITA DALAM LUKISAN KARYA BASUKI ABDULLAH DAN HENDRA GUNAWAN, Dalam khasanah seni rupa modern Indonesia dapat dijumpai beberapa pencitraan wanita yang cukup menarik disimak. Tokoh pelukis Indonesia yang banyak melukis wanita ialah Basuki Abdullah. Seniman lamboyan yang oleh istrinya sendiri dikenal sebagai pengagum wanita cantik ini sangat produktif melukis dan antusias mengangkat harkat keindahan wanita dalam karya-karyanya. Wanita yang ia garap mulai dari para ibu Negara hingga artis papan atas. Dari Ratu Juliana, Tien Soeharto, Ranta Sari Dewi, Mahacakri Sirindorn hingga Cintami Atmanegara dan Yenny Rachman. Dari yang berbusana resmi seperti Ibu Tien Soeharto sampai yang resmi tidak berbusana seperti karyanya yang berjudul “Telanjang” dan “Kembali ke Alam.” Tampaknya Basuki Abdullah pria bertipe romantik yang amat menyenangi keindahan. Dan sifat itu agaknya berpengaruh kuat untuk selalu memperindah (mempercantik) objek-objek dalam lukisannya. Ungkapan klise untuk Basuki Abdullah mengatakan bahwa pelukis ini mampu melukis wanita jelek menjadi agak cantik, yang cantik menjadi sangat cantik, seperti iklan Fuji Film: ”Lebih indah dari warna aslinya.” Ungkapan tersebut sering berlanjut menjadi ledekan bahwa karyakarya Basuki cenderung turistik, yang memberikan kepuasan kulit luar.

Gambar 8. Tiga Pelacur, karya Hendra Gunawan

Gambar 9. Ratnasari Dewi, karya Basuki Abdullah

Pilihan berikutnya ialah Hendra Gunawan (1917-1983). Pelukis kelahiran Bandung ini ditinjau dari segi usia seangkatan dengan Basuki Abdullah. Namun ditilik dari kemampuan teknik melukis Naturalis-Turistik, jelas berbeda rumpun. Hendra tidak pernah “kepencut” terhadap karya-karya manis. Ia lebih banyak

MUHAJIR N., Citra Wanita dalam Karya Seni Rupa •

menggali tema-tema sosial dari kelas dan suasana kerakyatan, seperti “Sekaten,” “Petan” (Mencari Kutu), Kerokan, Menyusui Anak Tetangga, Tiga Pelacur. Lukisan Sekaten menggambarkan tiga sosok wanita (mungkin ibu dan anak) berada di latar depan, sedang latar belakangnya adalah suasana keramaian pasar malam. Lukisan Petan juga menggambarkan tiga sosok wanita (tiga generasi?) yang komposisinya diatur secara vertikal, sedang Tiga Pelacur menggambarkan Pekerja Seks Komersial (PSK) tengah menghias diri. Karakteristik karya-karya Hendra selain tampak pada tema juga kelihatan pada proporsi bentuk yang agak kepanjang-panjangan, teknik pewarnaannya datar (opaque) menyala, yang seolah-olah tak mau disibuki oleh kecermatan detil. Sifat-sifat demikian ini oleh Claire Holt (2000: 220) dipandang mengingatkan pada karya-karya Gauguin. WANITA DESA DALAM KARYA SUDARSO Selanjutnya, kesempatan jatuh pada Sudarso (1914-2006). Pelukis kelahiran Purwokerto ini mengembangkan karir kesenimanannya di kota Gudeg, Yogyakarta. Sudarso pernah bergabung dengan “Kelompok Lima”, yang terdiri atas Afandi, Hendra Gunawan, Barli S, Wahdi Sumanta dan Sudarso sendiri. Pelukis satu ini kesetiaannya terhadap objek wanita tidak pernah ingkar janji. Objek wanita yang diangkat pada kanvasnya selama bertahun-tahun mayoritas ialah wanita desa dengan busana kebaya yang bersahaja. Untuk mendukung citra kedesaannya, maka cara mengenakan kain nampak tidak formal. Artinya, kain jarit yang dikenakan tidak mengenal wiru dan lagi “cingkrang” (kurang panjang). Dalam keadaan betisnya hanya tertutup setengah lutut itu justru dimanfaatkan oleh Sudarso untuk menggarap bagian kaki (kebetulan selalu tanpa alas) sebaik mungkin. Satu pertanyaan yang sering dilontarkan terkait hal ini ialah mengapa Sudarso selalu melukis wanita dalam gaya, bentuk, adegan, dan suasana yang nyaris sama, yaitu wanita Jawa, dalam seting desa, tengah duduk sendiri, dalam suasana sunyi. Misalnya Dik Kedah, Tinah, dan Dik Tiul. WANITA BERMATA BOLONG JEIHAN Jeihan Sukmantoro lahir di Solo pada tahun 1938. Ia belajar di HBS (Himpunan Budaya Surakarta) tahun 1953-1955, dan menimba ilmu di ITB (Institut Teknologi Bandung) pada 1960-1966. Jeihan kemudian mengembangkan karir sebagai seniman professional, menetap dan berkarya di Bandung. Sebagian besar karya lukisan Jeihan menggambarkan sosok-sosok manusia, terutama wanita sederhana, dalam suasana santai, tidak sedang melakukan ativitas, dalam posisi duduk, atau tidur. Secara isikal, karakteristik karya-karya Jeihan tampak pada penggambaran objek manusia yang diungkapkan secara datar (lat), dengan warna biru, abu-abu, keputih-putihan yang disokong dengan kontur wana gelap kehitam-hitaman. Sosok-sosok wanita yang ditampilakan Jeihan lazimnya berpostur langsing, sementara bagian mata dibuat gelap seolah-olah berlubang (bolong) seperti menatap

60 • URNA, Jurnal Seni Rupa: Vol. 1, No. 1 (Juni 2012): 50–62

dengan pandangan kosong. Nyaris serupa dengan karya-karya Sudarso, wanitawanita Jeihan lazimnya juga dalam seting kesendirian, sunyi, memendam rindu, seperti yang berjudul Arifah (1987).

Gambar10. Arifah, lukisan karya Jeihan

GAYA KUBIS PADA LUKISAN WANITA IDA HADJAR Ida Hadjar (1942-2004) belajar melukis di ASRI (Akademi Seni Rupa Indonesia) Yogyakarta. Karya-karya nya mendapat pengaruh karya Picasso yang kubistis dan karya pelukis Mexico Diego Rivera yang bervisi Realisme Sosial. Pada tahun 1967 Ida Hadjar menerima penghargaan dari Wendy Sorenson Memorial, New York, dan tahun 1992 menerima penghargaan “Canting Emas,” dari Yogyakarta, sebuah penghargaan di bidang lukisan Batik. Berkenaan dengan kepiawaiannya melukis dengan medium batik, pada tahun 1983-1985 Ida Hadjar hijrah sementara ke Amerik dan mengajar melukis batik di Ann Arbor Art Association & The International Neighbours di Michigan. Sebagai pelukis wanita, tampaknya Ida Hadjar ingin melawan stereotipe wanita sebagai makhluk yang lembek, sebaliknya ia membangun citra wanita yang “struggle” penuh perjuangan hidup. Kesan itu dinyatakan dalam igur-igur wanita yang kuat, dalam gaya kubis dengan kontur tebal, gelap, dan tegas, seperti karyanya yang menggambarkan empat sosok wanita, berjudul “Pergi ke Pasar.” KESIMPULAN Dari paparan di atas dapat disimpulkan bahwa pencitraan wanita dalam karya seni rupa beraneka ragam, bergantung pada latar belakang penciptaan karya tersebut, terutama tekait dengan visi dan pemaknaan atas wanita yang digambarkan. Pertama, pencitraan wanita sebagai simbol kesuburan. Karena itu penonjolan

MUHAJIR N., Citra Wanita dalam Karya Seni Rupa •

bentuk pada aspek-aspek pendukung fungsi reproduksi, seperti buah dada perut dan pusar menjadi penting, misalnya patung Venus dari Willendorf. Kedua, mencitrakan sifat kewanitaan yang terjabar lewat kecantikan paras, keelokan tubuh, lemah lembut, anggun dan sifat-sifat lain yang mengarah pada feminitas. Misalnya lukisan Venus karya Boticelli dan Venus karya Francois Boucher. Ketiga, Sifat keibuan yang penuh kasih sayang, perawatan dan pengasuhan terhadap buah hatinya, seperti pada lukisan Madonna karya Parmigianino dan sosok patung batu prasejarah dari Sumatra Utara. Keempat, Citra wanita sebagai makhluk lemah, makhluk yang bahkan tak berdaya melindungi dirinya sendiri terhadap kekuatan, keperkasaan, dan kegarangan lelaki yang hendak merampas kewanitaannya. Citra ini tampak pada karya Delacroix “Kematian Sardanapalus” dan karya Da Cortana “Pemerkosaan Wanita-wanita Sabina” yang memposisikan wanita dalam suasana tercekam/ketakutan. Kelima, citra wanita dalam posisi dan suasana hati tersanjung, dikagumi, digandrungi sekaligus sebagai penghias dunia lelaki, seperti karya Manet dan karya-karya Basuki Abdullah. Keenam Citra keagungan wanita “sempurna” yang merupakan perpaduan antara keelokan rupa, derajad kebangsawanan dan kekuatan spiritual, seperti pada patung Prajna Paramita. Ketujuh, penggambaran wanita sebagai simbol kepahlawanan seperti patung Dewi Durgamahesa Suramardini. Sifat kepahlawanan dan keperkasaannya tergambar pada sikap badan dan kakinya yang dalam posisi siaga serta sejumlah senjata yang berada dalam genggaman tangannya. Kedelapan, citra ironi wanita, maksudnya wanita yang secara generik dicitrakan sebagai simbol keindahan/kecantikan, justru didekonstruksi bentuknya menjadi sosok yang kurang menarik, tidak menarik, bahkan menakutkan. Pencitraan serupa ini misalnya tampak pada karya-karya Picasso, Hendra Gunawan, dan Ida Hadjar. Dalam banyak kasus visualisasi dan pencitraan wanita dalam karya seni rupa ternyata sejalan dengan perspektif/teori gender yang memposisikan wanita/ perempuan sebagai sosok inferior, tersubordinasi oleh laki-laki. Kesejalanan tersebut boleh jadi karena ketimpangan gender adalah merupakan produk konstruksi kaum laki-laki, sama halnya pencitraan/visualisasi wanita dalam karya seni rupa juga merupakan konstruksi/kreasi laki-laki. DAFTAR PUSTAKA Bowness, Alan, ed. 1985. Book of Art Volume 7: Impressionists and Post-Impressionists. Grolier. Holt, Claire. 2000. Melacak Jejak Perkembangan Seni di Indonesia. Terjemahan Soedarso RM. Bandung: Arti.Line. Janson, H.W. 1984. History of Art. New York: Harry N. Abrams, INC. Monteverdi, Mario ed. 1985. The Book of Art Volume 2: Italian Art to 1850. Grolier Soedarso, S.P. (Ed), 1992, Seni Patung Indonesia, BP ISI Yogyakarta. van Peursen, C.A. 1976. Strategi Kebudayaan. Yogyakarta: Kanisius.

62 • URNA, Jurnal Seni Rupa: Vol. 1, No. 1 (Juni 2012): 50–62

Eurofighter Spanish
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File size 3MB
Author/Uploader: William Monteiro

www.PaperAircrafts.com

PaperAircrafts.com

Eurofighter Typhoon

Ala 11 Escuadron 113 Fuerza Aerea Española Build an easy paper jet model with your hands, some scissors, two rules and some glue ! Check your handiwork skill ! Challenge a child to build it ! Assemble one as a gift for someone ! Collect the most famous jets in the world ! Once built, fly it ! Print in sheet 1 pages 7 and opposite 7, in sheet 2 page 8, in sheet 3 page 9 and in sheet 4 page 10. Cut the pieces, bend on the lines to give shape and paste with glue. The plane is balanced and should fly with minor aerodynamic adjustments. Whole process from assembly to flying is detailed in this document.

PaperAircrafts.com presents a flying paper-plane that attempts to replicate as simple as possible the famous Eurofighter decorated as Spanish Air Force Sq.113. Built by BAE Systems, EADS Germany, Alenia and EADS Spain, the Eurofighter is an air superiority, multi-role, twin engine, single or two seat, delta wing and canard configurated fighter. First planes were delivered in 2003.

Enjoy !

www.PaperAircrafts.com

Index How to build it…………………3 Parts……………………………7 Assembling………………….11 How to fly it…………..………17 Note about printing Parts…..23

Copyright Notice All rights reserved. No part of this document may be reproduced or transmitted in any form or by any means, electronic or mechanical. Any unauthorized use, sharing, reproduction, or distribution of parts herein is strictly prohibited. The buyer of this ebook may print as many copies as he want for his personal use. Legal Notice While attempts have been made to verify the correctness and reliability of the information provided in this document, the author do not assume any responsibilities for errors, omissions, or contradictory information contained in this publication. The reader of this book assumes all responsibility and liability for the use of the information and materials described in it, (like glue or scissors). 2

www.PaperAircrafts.com

How to build it

tools

www.PaperAircrafts.com

Note about Glue

Before start pasteing the aircraft, check your glue: Spread some glue in a sheet of paper and wait some minutes. If the paper gets wrinkled or wavy, then, that glue is not valid for paper; the aircraft would be deformed. Suitable glues could be “transparent contact glue” usually for repairing shoes.

√

X 4

www.PaperAircrafts.com Print pages 7, 8, 9 and 10 in common paper A4 or Regular Letter. Print at scale 100% to avoid parts distortion and using option ”Auto-rotate and center pages”. Do not “fit to page” or “shrink to page”. Cut parts over the external lines.

Fold over the lines with the help of the rules to achieve the shape of each part. Note that you can bend the paper on the lines with the help of the rules, (to the opposite side) and after it, with your fingers, on the same line, to the correct side to achieve the final piece shape. 5

www.PaperAircrafts.com Paste the parts puting glue in the overlaping surfaces.

X Put little amount of glue. Otherwise, the aircraft would look ugly and it would weight too much.

√ 6

www.PaperAircrafts.com

rudder

How to fly it ailerons

leading edge flaps (LE flaps) Elevator (Canard)

Aerodynamic cleanness

√ X

If the surfaces are bent, force the paper with your fingers trying to straighten them. The aircraft could have defects, but they must be symmetrical.

www.PaperAircrafts.com

2 Aircraft balanced

Rest the aircraft on two fingers so that the wing’s circles get positioned just over them. If it keeps levelled and does not fall…it is balanced.

√

Ready to fly

If it falls forward, the nose is too heavy. Remove part or whole piece 10

If it falls backward, it needs more weight in the nose. Did you paste parts 10,11,12 and 13 ? Add part or a whole piece 10.

www.PaperAircrafts.com It is easier to throw the aircraft keeping it on the sight line and impelling it on his longitudinal axis.

Throwing

√ X 1.

Once the easy throwing is well trained, try to launch over head for a longer flight

X 3.

√ 19

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Correcting the flight path: Pitch

If the aircraft pitchs down going to the ground, deflect downward gently the elevators. Repeat the flight. If it keeps going down, deflect the elevators downward a little more until the aircraft went straight gliding.

If the gliding path osciles like above… the elevators may be too much deflected downward. Reduce the elevators downward deflection.

In this case the nose still needs a little more weight. Cut a triangular piece of paper and paste it in the nose

www.PaperAircrafts.com

+ If you achieve to stabilize the glide path but it is too inclined downward… the nose may be too heavy. Remove part of piece 10 and reduce the elevators downward deflection.

Correcting the flight path: direction

√

To correct the turn, deflect the ailerons asymmetricaly like each picture shows but very gently. The deflection in the pictures is exaggerated; you would obtain the opposite efect. 21

www.PaperAircrafts.com In case of little corrections in direction, you can use the rudder. Deflect it very gently.

Correct left turns deflecting the rudder right

Correct right turns deflecting the rudder left.

5 Advanced Flight Once you have calibrated the glide path in pitch and direction, you can try different aircraft performances.

“Cruise”:

The aircraft will pitch down, oppose it, deflecting down the elevators a little.

Deflect down the LE flaps a little.

The aircraft will fly more smoothly

www.PaperAircrafts.com

Note about printing Parts There are five pages with the parts to be printed on four sheets of paper. Page opposite 7 must be printed behind page 7 in order to the plane was correctly decorated. Check option “Auto-rotate and center pages” but do not “fit to page” or “shrink to page”. Pages 7, 8, 9 and 10 must be printed with 100% scale to avoid parts distortion. If you want to print the rest of pages use “fit to page” option.

Page 7

Page 9

Sheet 1

Sheet 3

Page opposite 7

Sheet 2

Page 8

Page 10

Sheet 4

If you want to build a static model (not to fly) you could print on a high quality paper in high resolution. But if you want a flying model it is better to use normal paper printed in low resolution for saving weight and avoiding wrinkling the paper with excess of ink. 23

ASKEP PADA KLIEN FRAKTUR
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Lingkungan Dan Klasifikasi Penelitian Bisnis

Lingkungan Dan Klasifikasi Penelitian Bisnis
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BAB 1 PENDAHULUAN

1.1

Latar Belakang Penelitian bisnis yaitu proses pengumpulan dan analisis data yang sitematis dan obyektif untuk membantu pembuatan keputusan–keputusn bisnis perbedaan penelitian bisnis dengan penelitian lainnya adalah terletak pada jenis dan sifat fakta yang diuji. Kebutuhan informasi yang valid dan andal sebagai dasar untuk pembuatan keputusan manajemen, mendorong perkembangan dan kebutuhan penelitian bisnis termasuk diantaranya adalah penelitian manajemen dan akuntansi. Penelitian bisnis mengalami perkembangan yang sangat pesat sejalan dengan perkembangan lingkungan bisnis kemauan teknologi komputer, komunikasi,transportasi dan pemanufakturan merupakan faktor utama yang menyebabkan perubahan lingkungan bisnis yang cepat dan mengarah pada kompetisi bisnis yang ketat dalam skala global. Fungsi utama manajemen sebagai pembuat keputusan dan fungsi penyediaan informasi (keungan) oleh akuntansi, merupakan fingsi-fungsi yang memegang peran penting dalam organisasi bisnis untuk memperoleh keunggulan bersaing . Kegiatan penelitian yang dilakukan pada berbagi disipli ilmu pada dasarnya mengunakan metode–metode penelitian yang relatif tidak berbeda. Suatu kegiatan penelitian yang dalam praktingnya kemungkinan merupsksn kombinasi penerapan dari beberapa metode penelitian. Penelitian

dapat

diklasifikasi

berdasarkan

bebagi

sudut

pandang,diantaranya berdasarkan tujuan penelitian, karakteristik masalah, dan jenis data.

BAB 2 LINGKUP DAN KLASIFIKASI PENELITIAN BISNIS 1

BAB II PEMBAHASAN

2.1

Pengertian Bisnis Penelitian Bisnis yaitu proses pengumpulan dan analisis data yang sitematis dan obyektif untuk membantu pembuatan keputusan – keputusn bisnis perbedaan penelitian bisnis dengan penelitian lainnya adalah terletak pada jenis dan sifat fakta yang diuji. Kebutuhan informasi yang valid dan andal sebagai dasar untuk pembuatan keputusan manajemen ,mendorong perkembangan dan kebutuhan penelitian bisnis termasuk diantaranya adalah penelitian manajemen dan akuntansi .

2.2

Lingkup Penelitian Manajemen Penelitian manajemen adalah penelitian yang umumnya dilakukan oleh akademisi, mahasiswa yang mengkaji keilmuan manajemen seperti bisnis umum, manajemen pemasaran, manajemen keuangan, manajemen sumber daya manusia dan perilaku organisasi, sistem informasi manajemen, dan manajemen operasional. Penelitian manajemen tergolong kepada penelitian bisnis. Contoh : 1. Bisnis umum : peramlan jangka panjang dan jangka panjang ,tren

bisnis dan industri ,inflasi dan penentuan harga ,akuisisi,ekspor dan perdagangan internasional 2. Pemasaran dan penjualan : potensi pasar bagian dan segmentasi

pasar ,karakteristik pasar konsep produk baru ,penjualan saluran distribusi promo penjualan perilaku konsumen

BAB 2 LINGKUP DAN KLASIFIKASI PENELITIAN BISNIS 2

3. Keuangan : anggaransumber sumber pembiayaan modal kerja

investasi tingkat bunga dan resiko kredit biaya modal penilaian saham dan obligasi protofolio hasil resiko rasio rasio keuangan. 4. Manajemen dan perilaku organisasional : manajemen mutu

terpadu

motivasi dan kepuasan kerja gaya kepemimpinan

produktivitas tenaga kerja,evektivitas organisasional, budaya dan komunikas organisasi studi gera dan waktu ,serikat pekerja. 5. Sistem informasi manajemen : antara laim meliputi studi kasus

sistem dukungan keputusan ,aliansi funsi siste informasi,personal sistem informasi,pemgembangan sistem informasi

2.3

Lingkup Penelitian Akuntansi Lingkup penelitian akuntansi antara lain dalam bidang : akuntamsi keuangan,pasar modal ,akuntansi manajemen ,auditing sistem informasi akuntansi dan perpajakan

Akuntansi keuangan : Teori–teori akuntansi standart akuntansi keuangan, kebijakan dan metode akuntansi, pengukuran dan pengakuan akuntansi sistem pelaporan, pos-pos laporan keuangan rasio-rasio keungan, pengaruh informasi akuntansi, akuntasnsi keuangan internasional

2. Inves dan pasar modal : Efisiensi pasar, saham dan obligasi,penawaran

efe perdana, pemecahan sahm pengumuman dividen, resiko dan hasil ,institusi ursa efek, reksa dana, pengaruh pajak insinder trading 3. Akuntansi manajemen : Anggaran, insentif,pengukuran kinerja,harga

tranfer akuntansi pertanggungjawaban, alokasi biaya, penentuan harga pokok, aktivity based costing, varian varian biaya, manajeman mutu, just in time, pembuatan keputusan manjerial, informasi akuntansi manajemen, analisis biaya volume laba, biaya relevan, keputusan investasi dan penganggaran modal

BAB 2 LINGKUP DAN KLASIFIKASI PENELITIAN BISNIS 3

4. Auditing : Teori audit opini akuntansi

sampel audit, resiko audit,

idependensi, telaah analitis, pengendalian internal, timing & materiality EDP audit, organisasi auditor, audit iternal, jugdment, ksalahan audit (errors), audit trail, kkonfirmasi, pelatihan auditor, perilaku auditor, tanggungjawab profesi. 5. Sistem informasi akuntansi : Desain dan seleksi sistem penerapan dan

evaluasi sistem, pengajuan pengendalian internal, sistem data base,expert system, electronic data interchange, sikap pemakai manajemanan analis, berbagi aplikasi perangakat lunak tertentu pada manajemen keuangan, audit, poses pengajaran, konferensi 6. Perpajakan: Perencanaan pajak, sistem dan tatacra perpajakan, fungsi

pajak, dampak pajak, peraturan perpajakan, pajak penghasilan, pajak pertambahan

nilai,pajak

penjualan

barang

mewah,pajakbumi

dan

bangunan, bea materai, sanksi-sanksi perpajakan, akuntansi pajak pemeriksaan pajak, perilaku wajib pajak.

2.4

Berdasarkan Tujuan Penelitian Penelitian Dasar (basic, pure, fundamental reseach) merupakan tipe penelitian yang berkaitan juga dengan pemecahan personalia, tetapi dalam pengertian yang berbeda yaitu untuk menghasilkan pokok pengetahuan dengan berusaha memahami bagaimana masalah tertentu yang terjadi dalam organisasi dapat diselesaikan. Atau, penelitian dasar adalah penelitian untuk meningkatkan pemahaman terhadap masalah tertentu yang kerap terjadi dalam konteks organisasi dan mencari metode untuk memecahkannya. Penelitian dasar dapat disebut penelitian murni. 

Penelitian Deduktif adalah tipe penelitian yang bertujuan untukmenguji(testing) hipotensis melalui validasi teori atau pengujian aplikasi teori pada keadaan tertentu.tipe penelitian ini menggunakan

hipotensis

apriori

(berdasarkan

teori,

bukan

BAB 2 LINGKUP DAN KLASIFIKASI PENELITIAN BISNIS 4

berdasarkan fakta) sebagai pedoman atau arah untuk memiliki, mengumpul menganalisis data. 

Penelitian Induktif merupakan tipe penelitian yang mempunyai tujuan untuk mengembangkan (generating) teori atau hipotensis melalui pengungkapan fakta (fact fiding ). Tipe penelitian ini menekankanpada kebenaran atau realitas fakta untuk menghindari adanya teori –teori atau opini – opini yang membingungkan

Penelitian Terapan (Applied Research) Pengertian dari penelitian terapan adalah sebuah proses penelitian yang dilakukan dengan cara yang praktis untuk memberikan solusi atas permasalahan tertentu. Penelitian terapan tidak berfokus pada ide, gagasan, teori akan tetapi fokus dari penelitian terapan adalah sebagai penerapan penelitian tersebut untuk kehidupan sehari hari. Cari yang paling mudah kita ketahui ialah , penelitian terapan memiliki nilai abstraksi yang sangat rendah lalu dampak dan manfaatnya dapat dirasakan secara langsung. Penelitian terapan memiliki tiga jenis penelitian , yaitu ; 

Penelitian evaluasi, adalah penelitian yang bertujuan untuk melakukan penilaian terhadap ,setiap tahapan penelitian. mulai dari proses perencanaan sampai proses hasil akhir guna mengetahui sejauh mana kesalahan yang terdapat pada tiap tiap tahapan penelitian.



Penelitian aksi , adalah penelitian yang bertujuan untuk mengembangkan kehidupan dan kondisi dari para subyek yang diteliti. Focus dari penelitian aksi adalah terletak pada tindakan sosial.



Peneiltian mengenai penilaian akan dampak sosial yang akan terjadi , yang membahas mengenai konsekuensi dampak apa yang muncul dari sebuah perencanaan dan beberapa kebijakan yang dipilih. BAB 2 LINGKUP DAN KLASIFIKASI PENELITIAN BISNIS 5

Kelebihan dari penelitian terapan adalah dapat dengan cepat digunakan dalam jangka pendek, praktis tidak memakan banyak waktu yang lama. Karna mudah dan cepatnya hasil yang didapat dari metode penelitian terapan banyak lembaga yang menggunakan metode tersebut serta dari kemudahan dan

efisiensi

metode

yang

diberikannya. Kekurangannya

ialah

apabila

dari

hasil

penelitian tersebut di interpretasikan secara salah, penginterpretasi yang salah dapat menyebabkan dampak yang fatal.

2.5

Berdasarkan Karakteristik Masalah  Penelitian historis (historical )

merupakan penelitian terhadap

masalah–masalah

yang

berkaitan dengan fenomena masa lalu

(historis),

historis rekontruksi

tujuan

adalah

penelitian melekukan

fenomena

masalalu

secara sistmatis, obyekif dan akurat untuk menjelaskan fenomena masa sekarang

atau

fenomena

masa

mengantisipasi yang

akan

datang.sumber data penelitian histori terdiri dari sumber primer dan sumber sekunder BAB 2 LINGKUP DAN KLASIFIKASI PENELITIAN BISNIS 6

 Penelitinan deskriptif (Deskriptive research )

Merupakan penelitian terhadap masalah – masalah berupa fakta-fakta saat ini dari

suatu

populasi. Metode pengumpulan data yang sering di gunakan dalam penelitian adalah metode survai yaitu teknik pengummpulan dan analisi data berupa opini dari subyek yang di teliti (responden ) melalui tanya jawab. Cara metode survai dengan

kuisioner

tertulis)

dan

(pertanyak

wawancara

(pertanyakan lisan )  Studi kasus dan lapangan ( case and field study )

Tujuan studi kasus adalah melakukan penyelidikan secara mendalam mengenai subyek tertentu. Studi kasus cenderung menguji relatif banyak fariabel penelitian dengan metode survai yangcenderung menguji variabel penelitiann dalam jumlah relatif sedikit dengan jumlah sampel ya g relatif banyak. Variabel yaitu segal sesuatu yang dapat diberi bermacam – macam nilai.  Penelitian korelasional

Bertujuan untuk menentukan ada tidaknya korelansi atara variabel atau membuat prediksi berdasarkan korelasi antara variabel. Hubungan antara variabel yang berupa sebab akibat dapat diteliti

BAB 2 LINGKUP DAN KLASIFIKASI PENELITIAN BISNIS 7

melalui tipe penelitian kausal komperatif dan eksperiman  Penelitian kausal komperatif

Merupakan tipe penelitian ex post facto yaitu tipe penelitian terhadap data yang dapat mengidentifikasi fakta atau peristiwa tersebut sebagia variabel yang dipengaruhi

(varuabel

dependen)

dan

melakukan penyelidikan terhadap variabelvariabel

yang

mempengaruhi

(variabel

independen)  Penelitian eksperimen

yaitu mengenai hubungan sebab akibat antara dua variabel atau lebih.dalam penelitian

eksperimen

penelitian

melaukan

manipulasi atau pengendalian (control) terhadap setidaknya satu variabel idependen sedang pada penelitian kausal kemperatif tidak ada prilakku (treatment)dari

penelitian

terhadap

variabel

independen.

2.6

Berdasarkan Jenis Data 

Penelitian opini 1. mengumpulkan informasi faktual secar ditail 2. mengidentifikasi masalh atau justifikasi kondisi kondisi dan praktik praktik saat ini 3. membuat perbandingan dan evaluasi tujuan pandangan ini menyelidiki pandangan persepsi atau penelian responden terhadap masalah tertentu

BAB 2 LINGKUP DAN KLASIFIKASI PENELITIAN BISNIS 8



Penelitian empiris yaitu lebih menekankan pada penyelidikan aspek perilaku dari pada opni.obyek yang diteliti lebih ditekankan pada kejadian yang nyata atau sebenarnya dari pada persepsi mengenai kejadian,studi kasus dan lapangan serta penelitian esperimen tipe penelitian ini.



Penelitian arsip. Dokumen atau arsip yang di teliti berdasarkan sumbernya dapat berasal dari internal yaitu dokumen,arsip dan catatan orisinil yang dioeroleh dari suatu organisasi atu berasal dari data eksternal yaitu publikasi datayang di peroleh melalui orang lain

2.7

Penelitian kualitatif Berdasarkan paradigma penelitian kualifikasi ada beberapa tipe penelitian yang dikalisifikasikan berdasarkan metode pengumpulan dan penelitian yang meliputi keseluruhan terhadap dalam proses penelitian. Beberapa diantaranya adalah: human ethology, ecological psychology, holistic etnography, cognitive antropology, etnography of communication dan

symbolic

interactionism.

Penelitian

kualitatif

dapat

pula

diklasifikiasikan ke dalam beberapa pendekatan dan perspektif, antara lain: pendekatan interpretif, pendekatan artistik, pendekatan sistematis, prespektif antropologis, prespektif sosiologis, studi kasus, studi kognitif dan penelitian historis.

BAB 2 LINGKUP DAN KLASIFIKASI PENELITIAN BISNIS 9

Denah Rumah MR – Dana
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OBYEK 1500 400

250

350

R.CUCI + JEMUR -0.05

TAMAN -0.50

PERUNTUKAN 250

300

250

200

RUMAH TINGGAL

LOKASI

KAMAR PEMBANTU ±0.00

DAPUR ±0.00

250

KAMAR UTAMA ±0.00

PADUKUHAN DESA KECAMATAN

KM / WC K.UTAMA -0.05

R.KELUARGA ±0.00

R.BINATU ±0.00

250

200

PEMILIK BANGUNAN KM / WC K.ANAK -0.05

R.TAMU ±0.00

PENANGGUNG JAWAB GAMBAR

KAMAR TAMU ±0.00 KM / WC -0.05

200

350

KAMAR ANAK ±0.00

1550

100

1550

Mr. Dana

TERAS -0.05

200

PENANGGUNG JAWAB BANGUNAN TAMAN -0.50

CARPORT -0.40

200

195

105

400 1500

200

KETERANGAN

300

TAMAN -0.50

250

150

DENAH RENCANA Skala 1:100

Pedoman Diagnosis Dan Terapi Ugd
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PEDOMAN DIAGNOSIS DAN TERAPI RUANG LAYANAN UGD

PUSKESMAS PAMOLOKAN Jl. KH. Agus Salim No. 25(085259398573) PAMOLOKAN

KATA PENGANTAR Bismillahirrohmanirrohim, puji syukur kami panjatkan karena berkat rahmat Allah Yang Maha Kuasa. Pedoman Diagnosis dan Terapi ruang Umum dapat terselesaikan. Panduan ini berisi panduan dalam penatalaksanaan penyakit berdasarkan 10 penyakit terbanyak yang ada di ruang layanan umum Puskesmas Pamolokan. Harapan kami buku Panduan ini dapat membantu untuk mempermudah dalam memberikan pelayanan kesehatan bagi masyarakat Pamolokan khususnya, sehingga kualitas pelayanan kesehatan akan semakin meningkat. Panduan ini masih sangat jauh dari kata sempurna, sehingga penyempurnaan-penyempurnaan perlu dilakukan dikemudian hari sesuai dengan pengembangan ilmu pengetahuan dibidang kesehatan.

Disahkan di Pamolokan, Agustus 2018 Kepala Puskesmas Pamolokan

dr. Rifmi Utami, M.Kes NIP. 19760826 200501 2 008

DAFTAR ISI

1. Daftar Isi………………………………………………………………………………………… 2. Kata Pengantar ………………………………………………………………………………..

PENDAHULUAN

Triase dalam Pelayanan Gawat Darurat Triase merupakan suatu system yang digunakan dalam mengidentifikasi korban dengan cedera yang mengancam jiwa untuk kemudian diberikan prioritas untuk dirawat atau dievakuasi ke fasilitas kesehatan. Gawat : Suatu keadaan yang mengancam nyawa pasien Darurat : Suatu keadaan yang segera memerlukan pertolongan Prioritas pelayanan kegawatdaruratan pasien di UGD : A. Prioritas Nol ( Hitam ) Pasien meninggal atau cedera parah yang jelas tidak mungkin untuk diselamatkan. B. Prioritas Pertama ( Merah ) Penderita cedera berat dan memerlukan penilaian cepat tindakan medik atau transport segera untuk menyelamatkan hidupnya. Berikut penyakit yang termasuk di PKM Pamolokan : 1. Syok 2. Appendicitis akut 3. Infark Miokard 4. Stroke 5.Status Epileptikus 6. Kejang Demam 7. Status Asmatikus

3. Prioritas Kedua ( Kuning ) Pasien memerlukan bantuan, namun dengan cedera dan tingkat yang kurang berat dan dipastikan tidak akan mengalami ancaman jiwa dalam waktu dekat. Berikut penyakit yang termasuk di PKM Pamolokan : 1. Reaksi Anafilaktik 2. Epistaksis 3. Decomp cordis 4. Fraktur Terbuka 5. Fraktur Tertutup

4. Prioritas Ketiga ( Hijau ) Pasien dengan cedera minor dan tingkat penyakit yang tidak membutuhkan pertolongan segera serta tidak mengancam nyawa dan tidak menimbulkan kecacatan. Berikut penyakit yang termasuk di PKM Pamolokan : 1. Ulkus pada tungkai 2. Vulnus 3. Gastritis 4. Asma Bronkiale 5. Demam Tanpa Penyebab yang Jelas 6. DM tipe 2 7. Influenza 8. Diare 9. HT esensial 10. Demam Tiphoid

GEA Westfalia CC 450-458 Decanter PDF
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Decanter CC 450 / CC 458 Technical Data Clarification of liquids Continuous separation of solids from oil-water mixtures with very high solids content (< 60%) Available for onshore and offshore installation; gastight design

Application and Design Features Frame, hood and drive

Adjustment of differential speed via

The decanter CC 450 / CC 458 from

High separation efficiency

which can be optionally used for the clari-

Gastight design available Gear drive system for independent

removal of solids.

torque starting in star-delta circuit or

or 3-phase decanters achieve high separa-

via frequency converter

Features High capacity range up to 30 m³ / h 2-phase or 3-phase

separation

Easy installation, operation and

maintenance

bowl and scroll speed adjustment 3-phase AC motor for controlled

Depending on the requirements, 2-phase tion efficiencies with solids, oil and water.

Deep pond design

1 and 2, temperature class T3

fication of liquids or the separation of two immiscible liquids with simultaneous

Low energy consumption

Suitable for installation in Ex-zones

GEA Westfalia Separator is a continuously operating horizontal solid wall centrifuge

Benefits

VFD (option)

Additional equipment (at extra cost) Motor control unit

Different cone angles available

Tools and set of spare parts

Westfalia Separator wewatch

Feed pump Every decanter is also available as

condition monitoring for preventive maintenance All parts coming into contact with

a complete unit, including auxiliary

equipment

the product are made of CrNiMo stainless steel

Mechanical Separation / GEA Westfalia Separator

Technical Data CC 450 / CC 458 Operating principles and constructional features 4

2-phase decanter 1

2 4

5 Separation chamber

2 Distributor

6 Solids discharge

3 Bowl

7 Discharge of the clarified liquid phase

4 Scroll

7 3 5

1 Product feed

3-phase decanter 1

Technical data

1 Product feed

5 Separation chamber

2 Distributor

6 Solids discharge

3 Bowl

7 Discharge of the heavy liquid phase

4 Scroll

8 Discharge of the light liquid phase

CC 450

Application

CC 458

Bowl

Waste / used /

Diameter

458 mm

Length / diameter ratio

3.2

4.4

Waste emulsion treatment

Bowl speed

max. 3400 rpm

max. 3000 rpm

Oil sludge treatment

g-force, (z)

max. 2960 g

max. 2304 g

slop oil treatment

(from lagoons, ponds)

Bowl motor

Oily water /

Rating

22 – 53 kW

Speed at 50 Hz / 60 Hz

max. 3000 / max. 3600 rpm

slop water treatment

Shipping data

(Marpol oil, bilgewater) Drain water on rigs

Decanter weight without motor approx. 2440 kg

approx. 2980 kg

Drilling mud / fluids

Motor (22 / 30 / 37 kW)

approx. 160 / 250 / 300 kg

Lime slurry (oil sands)

Secondary motor (11 kW)

approx. 104 kg

Coal tar treatment

Case dimensions

315 x 125 x 160 cm

Components

Option 1

Option 2

Bowl and scroll

Duplex steel

Super duplex steel

Scroll flight hard-facing

Sprayed tungsten carbide

Sintered tungsten carbide tiles

Solids outlet ports

Exchangeable

—

Seals, inner bearings

NBR (Perbunan) / P.T.F.E.

Viton

Drive

Standard drive Hydraulic drive

2-gear drive with adjustable bowl speed via VFD (Variable Frequency Drive)

Solids discharge

Chute

Slide valve

Dimensions in mm

Min. lifting capacity of trolley hoist for service and maintenance: 1500 kg

Mechanical Separation

GEA Westfalia Separator Werner-Habig-Straße 1 · 59302 Oelde (Germany) Phone +49 2522 77-0 · Fax +49 2522 77-1778 [email protected] · www.westfalia-separator.com

The information contained in this brochure merely serves as a non-binding description of our products and is without guarantee. Binding information, in particular relating to capacity data and suitability for specific applications, can only be provided within the framework of concrete inquiries. Printed on chlorine-free bleached paper · Printed in Germany · Subject to modification · www.papp.cc 9997-1696-000/0709 EN

3 5

Nguyen Thi Trang CNDTC
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ĐẠI HỌC ĐÀ NẴNG TRƯỜNG ĐẠI HỌC BÁCH KHOA KHOA CƠ KHÍ GIAO THÔNG

THUYẾT MINH ĐỒ ÁN CÔNG NGHỆ ĐÓNG TÀU Đề tài: THIẾT KẾ QUI TRÌNH CÔNG NGHỆ CHẾ TẠO PHÂN ĐOẠN 238 CỦA TÀU CHỞ HÀNG KHÔ 3200 TẤN Sinh viên thực hiện

Nguyễn Thị Trang

Giảng viên hướng dẫn

TS Nguyễn Văn Minh

MSSV

103180229

Lớp

18KTTT

Nhóm

18.20

TRƯỜNG ĐẠI HỌC BÁCH KHOA KHOA CƠ KHÍ GIAO THÔNG

CỘNG HÒA XÃ HỘI CHỦ NGHĨA VIỆT NAM Độc lập – Tự do – Hạnh phúc

ĐỒ ÁN MÔN HỌC CÔNG NGHỆ ĐÓNG TÀU

(Mã đề: 26) Sinh viên thực hiện: Nguyễn Thị Trang Học kì: 2 MSSV: 103180229 Năm học: 2021 – 2022 Giáo viên hướng dẫn: Ts. Nguyễn Văn Minh Thời gian thực hiện: 07/02/2022 – 29/05/2022 I. TÊN ĐỀ TÀI: Thiết kế qui trình công nghệ chế tạo phân đoạn 238 của tàu chở hang khô 3200 Tấn II. DỮ LIỆU VÀ CÁC THÔNG SỐ CHO TRƯỚC 1. Bản vẽ tuyến hình 2. Bản vẽ kết cấu cơ bản 3. Bản vẽ cụm kết cấu chi tiết 4. Bản vẽ phân chia tổng phân đoạn III. PHẦN NỘI DUNG THỰC HIỆN A. Phần thuyết minh 1. Phân tích kết cấu tổng phân đoạn 2. Khảo sát nhà máy và chuẩn bị để chế tạo phân đoạn 3. Lập qui trình công nghệ chế tạo phân đoạn B. Phần bản vẽ 1. Bản vẽ kết cấu phân đoạn (A0) 2. Bản vẽ qui trình công nghê chế tạo phân đoạn (A0) 3. Bản vẽ khai triển tôn bao và phiếu cắt tôn (A1) Lưu ý: SV phải thực hiện đầy đủ nội dung trên theo thời gian được giao Trưởng bộ môn

Giáo viên hướng dẫn

TS. Trần Văn Luận

TS. Nguyễn Văn Minh

MỤC LỤC LỜI NÓI ĐẦU………………………………………………………………………………………………… 5 CHƯƠNG 1 PHÂN TÍCH KẾT CẤU PHÂN ĐOẠN 238…………………………………….6 1.1. Phân tích kết cấu……………………………………………………………………………………….6 1.1.1. Ví trí phân đoạn đáy 238………………………………………………………………………6 1.2. Phân tích kết cấu phân đoạn 238…………………………………………………………………..8 1.3. Tính toán khối lượng phân đoạn…………………………………………………………………23 CHƯƠNG 2 KHẢO SÁT NHÀ MÁY VÀ CHUẨN BỊ ĐỂ CHẾ TẠO PHÂN ĐOẠN ……………………………………………………………………………………………………………………. 31 2.1 Khảo sát năng lực nhà máy…………………………………………………………………………31 2.1.1 Vị trí địa lý…………………………………………………………………………………………31 2.1.2 Nhiệm vụ chức năng của các phân xưởng………………………………………………31 2.1.3 Nhân lực của Công ty CNTT Phà Rừng………………………………………………….32 2.1.4 Sơ đồ và diện tích mặt bằng nhà máy……………………………………………………..32 2.1.5 Cơ sở hạ tầng, trang thiết bị trong công ty………………………………………………33 2.2. Phân tích lựa chọn phương án thi công……………………………………………………….40 2.3. Khai triển tôn và cơ cấu phân đoạn……………………………………………………………..41 2.3.1 Khai triển tôn đáy trên…………………………………………………………………………41 2.3.2 Khai triển tôn đáy ngoài……………………………………………………………………….42 CHƯƠNG 3: LẬP QUI TRÌNH CÔNG NGHỆ THI CÔNG PHÂN ĐOẠN 238……..48 3.1. Chế tạo khung giàn lắp rắp cho phân đoạn 238…………………………………………….48 3.2. Quy trình gia công các chi tiết và cụm chi tiết………………………………………………48 3.2.1. Các thiết bị sử dụng trong quá trình gia công chi tiết……………………………….48 3.2.2. Xử lý vật liệu…………………………………………………………………………………….49 3.2.3. Các bước chuẩn bị trước khi hàn…………………………………………………………..49 3.2.4. Lấy dấu…………………………………………………………………………………………….. 50 3.3. Gia công tấm tôn phẳng……………………………………………………………………………50 3.3.1. Qui trình chung………………………………………………………………………………….50 3.3.2. Áp dụng cho chi tiết tấm tôn đáy trên……………………………………………………50 3.4. Gia công chi tiết tấm tôn cong…………………………………………………………………..51 3.4.1. Qui trình chung………………………………………………………………………………….51 3.5. Gia công thép hình (L120x120x10)…………………………………………………………….52 3.6. Gia công cụm chi tiết tấm tôn có nẹp gia cường……………………………………………52 3.6.1. Gia công cụm chi tiết đà ngang……………………………………………………………..52 3.7. Gia công cụm chi tiết sông phụ 1……………………………………………………………….54 3

3.8. Lấy dấu các cơ cấu trên tôn đáy trên……………………………………………………………55 3.8.1. Lắp ráp tôn đáy trên……………………………………………………………………………55 3.8.2 Lấy dấu các cơ cấu trên tôn đáy trên………………………………………………………56 3.8.3 Lắp ráp và hàn các cơ cấu lên tôn đáy trên……………………………………………..57 3.8.4 Quy trình lắp rắp tôn đáy dưới………………………………………………………………61 3.9. Cẩu lật……………………………………………………………………………………………………. 61 TÀI LIỆU THAM KHẢO……………………………………………………………………………….63

LỜI NÓI ĐẦU Những năm gần đây, nền kinh tế Việt Nam đang phát triển mạnh. Bên cạnh đó, kĩ thuật của nước ta cũng dần tiến bộ. Trong đó cũng phải kể đến ngành đóng mới và sửa chữa tàu thủy. Để góp phần phát triển ngành, các kĩ sư, chuyên gia về ngành tàu thủy phải không ngừng tìm tòi, sáng tạo, cập nhật những công nghệ tiên tiến từ các nước phát triển ngành tàu thủy lâu đời trên thế giới. Đồ án môn học “công nghệ đóng tàu” như là một bài toán lớn, cho chúng em vận dụng các kiến thức đã học từ trước đến nay. Không những vận dụng mà còn tìm hiểu sâu hơn, nắm vững hơn các môn kết cấu tàu, công nghệ đóng tàu, công nghệ sửa chữa, hệ động lực, quy phạm về tàu thủy, bố trí chung tàu thủy,.. Trong quá trình làm đồ án, em đã có gắng tìm tòi, vận dụng các kiến thức để mong thực hiện đồ án của mình một cách tốt nhất. Nhưng với vốn kinh nghiệm ít ỏi, kiến thức hạn hẹp nên đồ án còn có nhiều thiếu sót, mong các thầy bỏ qua. Cuối cùng, em xin bày tỏ lời cảm ơn đến các thầy đã tận tình chỉ bảo và giúp đỡ em trong lúc hoàn thành đồ án. Cảm ơn thầy Nguyễn Văn Minh, người đã trực tiếp chỉ dẫn em trong suốt thời gian hoàn thành đồ án. Những nhận xét, chỉ bảo của thầy sẽ giúp em ngày càng hoàn thiện kiến thức của mình. Đà Nẵng, ngày

tháng

năm 2022

Sinh viên thực hiện

Nguyễn Thị Trang

CHƯƠNG 1 PHÂN TÍCH KẾT CẤU PHÂN ĐOẠN 238 1.1. Phân tích kết cấu 1.1.1. Ví trí phân đoạn đáy 238  Phân đoạn đáy 238 nằm ở phía mũi tàu.  Hệ thống kết cấu phân đoạn được bố trí bên phải tàu so với mặt phẳng dọc tâm tàu nhìn về phía tàu.  Phân đoạn thiết kế từ sườn 92+100 đến sườn 102-150  Chiều dài phân đoạn: LPđ =6050 (mm).  Chiều cao của phân đoạn: H Pđ =1100 (mm) tính từ đáy tàu.  Chiều rộng của phân đoạn: B pđ cách đường dọc tâm tàu 100 (mm) đến tôn bao.  Khoảng sườn thực tại phân đoạn 238: a = 600 (mm).

a, Hình chiếu bằng

b, Hình chiếu đứng

Hình 1. 1 Hình chiếu phân đoạn 238

Hình 1. 2 Ví trí phân đoạn 238 trên tàu

Phân đoạn đáy 238 bao gồm các nẹp dọc L120x120x10, nẹp dọc phụ L120x120x10 và các sống phụ liên kết với các đà ngang đáy. Tôn đáy dưới có các độ dày bằng 12 mm tại vị trí giữa tàu và bằng 10mm cho phần còn. Tôn đáy trên cũng có độ dày 10 mm.

Hình 1. 3 Kết cấu phân đoạn 238 1.2. Phân tích kết cấu phân đoạn 238  Ví trí phân đoạn 238 từ sườn 92+100 đến sườn 102-150 có các đà ngang đặc tại sườn 95, 97, 99, 101 còn lại là đà ngang hở tại sườn 93, 94, 96, 98, 100.  Tờ tôn đáy trên liên kết với tờ tôn đáy dưới bởi đà ngang, các đà ngang khoét lỗ cho dầm dọc đi qua.  Khoảng cách giữa các đà ngang thực tế bằng khoảng sườn thực 600 mm.  Lỗ người chui với kích thước 400×500 (mm) để thuận lợi cho việc đi lại và kiểm tra ở đáy tàu.  Khoảng cách giữa các dầm dọc đáy là 600 (mm).  R50 là lỗ khoét công nghệ được tiến hành hàn trên đà ngang. 8

 Lỗ khoét công nghệ với kích thước ꬾ200.  Nẹp gia cường đà ngang có kích thước 8×100.  Các sống phụ, nẹp dọc nhằm liên kết các đà ngang lại với nhau.  Đà ngang tại sườn 93

Hình 1. 4 Kết cấu đà ngang tại sườn 93 Bảng 1. 1 Bảng kê khai chi tiết phân đoạn 238 tại sườn 93 STT

Tên gọi

Qui cách (mm)

Số lượng

Mã gia cường cho sống chính

t =10

Mã hông

t=8

8×100

L = 769

8×100

Hình khai triển chi tiết

Nẹp gia cường đà ngang 3

L = 1025

8×100

L = 803

 Đà ngang tại sườn 94

Hình 1. 5 Kết cấu đà ngang tại sườn 94 Bảng 1. 2 Bảng kê khai chi tiết phân đoạn 238 tại sườn 94 STT

Tên gọi

Qui cách (mm)

Số lượng

Mã gia cường cho sống chính

t =10

Mã hông

t=8

Hình khai triển chi tiết

8×100

L = 1011

Nẹp gia cường đà ngang

8×100

L = 803

 Đà ngang tại sườn 95

Hình 1. 6 Kết cấu đà ngang tại sườn 95 Bảng 1. 3 Bảng kê khai chi tiết phân đoạn 238 tại sườn 95 STT

Tên gọi

Qui cách (mm)

Số lượng

Đà ngang

t =8

Đà ngang

t=8

Hình khai triển chi tiết

Mã hông

Tấm ốp khoét

t =8

lỗ

8×100

L = 703 5

Nẹp gia cường đà ngang

8×100

L = 950

 Đà ngang tại sườn 96

Hình 1. 7 Kết cấu đà ngang tại sườn 96

Bảng 1. 4 Bảng kê khai chi tiết phân đoạn 238 tại sườn 96 STT

Tên gọi

Qui cách (mm)

Số lượng

Mã gia cường cho sống chính

t =10

Mã hông

t=8

8×100

L = 953 3

Hình khai triển chi tiết

Nẹp gia cường đà ngang 8×100

L = 803

 Đà ngang tại sườn 97

Hình 1. 8 Kết cấu đà ngang tại sườn 97 Bảng 1. 5 Bảng kê khai chi tiết phân đoạn 238 tại sườn 97 STT

Tên gọi

Qui cách (mm)

Số lượng

Đà ngang

t =8

Đà ngang

t=8

Mã hông

t =8

Hình khai triển chi tiết

Tấm ốp khoét

lỗ

Nẹp đà gia cường ngang

8×100

L = 948

8×100

L = 661

 Đà ngang tại sườn 98

Hình 1. 9 Kết cấu đà ngang tại sườn 98 Bảng 1. 6 Bảng kê khai chi tiết phân đoạn 238 tại sườn 98 STT

Tên gọi

Qui cách (mm)

Số lượng

Mã gia cường cho sống chính

t =10

Hình khai triển chi tiết

Mã hông

t=8

8×100

L = 1000 3

Nẹp gia cường đà ngang 8×100

L = 726

 Đà ngang tại sườn 99

Hình 1. 10 Kết cấu đà ngang tại sườn 99

Bảng 1. 7 Bảng kê khai chi tiết phân đoạn 238 tại sườn 99 STT

Tên gọi

Qui cách (mm)

Số lượng

Đà ngang

t =8

Đà ngang

t=8

Mã hông

Tấm ốp khoét

t =8

lỗ

Hình khai triển chi tiết

8×100

L = 592 5

Nẹp gia cường đà ngang

8×100

L = 933

 Đà ngang tại sườn 100

Hình 1. 11 Kết cấu đà ngang tại sườn 100

Bảng 1. 8 Bảng kê khai chi tiết phân đoạn 238 tại sườn 100 STT

Tên gọi

Qui cách (mm)

Số lượng

Mã gia cường cho sống chính

t =10

Hình khai triển chi tiết

Mã hông

t=8

8×100

L = 716 3

Nẹp gia cường đà ngang

8×100

L = 983

 Đà ngang tại sườn 101

Hình 1. 12 Kết cấu đà ngang tại sườn 101 Bảng 1. 9 Bảng kê khai chi tiết phân đoạn 238 tại sườn 101 STT

Tên gọi

Qui cách (mm)

Số lượng

Đà ngang

t =8

Hình khai triển chi tiết

Đà ngang

t=8

Mã hông

Tấm ốp khoét

t =8

lỗ

8×100

L = 702

Nẹp gia cường đà ngang

8×100

L = 950

 Bao gồm các nẹp dọc 1, 2, 3, 4, 5, 6, 7. Các nẹp dọc phụ 1, 2, 3, 4, 5, 6. Sống phụ 1, 2.  Kết cấu của sống phụ 1, 2: Sống phụ là một tấm phẳng có chiều dày t= 10mm, chiều cao sống phụ bằng chiều cao đáy. Sống phụ được gia cường bằng các nẹp gia cường có quy cách 10×100. Sống phụ được khoét các lỗ khoét người chui

400×500  Sống phụ 1 cách mặt phẳng dọc tâm 1800mm, có chiều dài 6050; sống phụ 2 cách mặt phẳng dọc tâm 4200 mm

Hình 1. 13 Sống phụ 1

Hình 1. 14 Sống phụ 2  Các nẹp dọc dùng để liên kết các đà ngang đáy lại với nhau với quy cách L120 ×120 ×10 .  Nẹp dọc được khoét lỗ thoát khí công nghệ.  Tại các ví trí nẹp dọc xuyên qua đà ngang được gia cường bằng thép với qui cách 100× 8.  Các nẹp dọc khi chạy liên tục qua các đà ngang đáy thì đà ngang được khoét lỗ và có tấm gia cường cho các nẹp.

 Khoảng cách giữa các nẹp dọc là 600 mm. Từ đà ngang sườn 97 đến đà ngang

sườn 101 có thêm các nẹp dọc phụ. Khoảng cách các nẹp dọc phụ là 600 mm, khoảng cách giữa nẹp dọc phụ và nẹp dọc là 300 mm.

Hình 1. 15 Kết cấu nẹp dọc STT

Tên gọi

Quy cách

Sống phụ 1

t = 10, L = 6050

Sống phụ 2

t = 10, L= 6050

Nẹp gia cường sống phụ

100×10 , L=100

Nẹp dọc

Nẹp dọc phụ

Số lượng

Hình khai triển chi tiết

L120×120 ×10

6 22

1.3. Tính toán khối lượng phân đoạn Khối lượng phân đoạn được tính bằng tổng khối lượng tôn tấm và khối lượng thép hình. Khối lượng tôn tấm bao gồm khối lượng tôn dùng chế tạo đà ngang đáy, tôn đáy, sống phụ … Khối lượng tôn được tính bằng tích công thức M1 = Σ ti×Si×ni×7,85 (kg) Trong đó: + M1: Khối lượng tôn (kg) + ti: Chiều dày tôn của chi tiết thứ i (mm) + Si: Diện tích của chi tiết thứ i (m 2) (Si đo trực tiếp trên bản vẽ kết

cấu chi tiết phân đoạn 238) + ni: Số chi tiết giống nhau trong phân đoạn + 7,85: Khối lượng riêng của tôn (T/m3)

Khối lượng thép hình được tính theo công thức: M2= Li×Ki Trong đó: + M2: khối lượng thép hình (kg) + Ki: Khối lượng trên một đơn vị chiều dài (kg/m) + Li: Chiều dài của chi tiết thứ i (m) và được đo trực tiếp trên

bản vẽ kết cấu chi tiết phân đoạn đáy 238  Khối lượng của phân đoạn bằng tổng khối lượng tất cả các cơ cấu của phân đoạn bao gồm: + Khối lượng đà ngang đã trừ lỗ khoét. + Khối lượng sống phụ đã trừ lỗ khoét.

+ Khối lượng mã hông đã trừ lỗ khoét. + Khối lượng các nẹp dọc đáy trên, nẹp dọc đáy dưới. + Khối lượng các nẹp gia cường cho sống phụ và đà. + Khối lượng tôn bao đáy dưới và tôn bao đáy trên.

Bảng 1. 10 Bảng tính khối lượng chi tiết thép tấm TT

Tên CT

Chiều dày (mm)

L (mm)

Số lượng

Diên tích (m2)

Khối lượng

Nẹp GC ĐN93

769

0,0769

4,83

Nẹp GC ĐN93

1025

0,1025

6,44

Nẹp GC ĐN93

803

0,0803

5,04

Nẹp GC ĐN94

1011

0,0703

6,35

Nẹp GC ĐN94

803

0,0803

5,04

Nẹp GC ĐN95

703

0,0703

4,41

Nẹp GC ĐN95

950

0,095

5,97

Nẹp GC ĐN96

953

0,0953

5,98

Nẹp GC ĐN96

803

0,0803

5,04

Nẹp GC ĐN97

948

0,0948

5,95 25

Nẹp GC ĐN97

661

0,0661

4,15

Nẹp GC ĐN98

1000

0,1

6,28

Nẹp GC ĐN98

726

0,0726

4,56

Nẹp GC ĐN99

933

0,0933

5,86

Nẹp GC ĐN99

592

0,0592

3,72

Nẹp GC ĐN100

716

0,0716

4,50

Nẹp GC ĐN100

983

0,0983

6,17

Nẹp GC ĐN101

702

0,0702

4,41

Nẹp GC ĐN101

950

0,095

5,97

Mã GC SC

–

0,587

276,49

Mã hông 93

–

1,746

109,64 26

Mã hông 94

–

1,681

105,58

Mã hông 95

–

1,237

77,68

Mã hông 96

–

1,509

94,77

Mã hông 97

–

1,149

72,15

Mã hông 98

–

1,248

78,38

Mã hông 99

–

1,052

66,06

Mã hông 100

–

1,144

71,85

Mã hông 101

–

1,115

70,00

DN95-1

–

1,466

92,09

DN95-2

–

2,053

128,92

DN97-1

–

2,053

128,92 27

DN97-2

–

1,466

92,09

DN99-1

–

1,466

92,09

DN99-2

–

2,053

128,92

DN101-1

–

1,397

87,74

DN101-2

–

1,511

94,88

Sống phụ 1

–

5,198

408,02

Sống phụ 2

–

4,508

353,86

Nẹp GCSP

–

0,093

58,27

Sống chính

–

6,05

474,93

Nẹp GC sống chính

–

0,56

4,37

Tổng

3350,46 (Kg)

Bảng 1. 11 Khối lượng các chi tiết thép hình STT

Tên chi tiết

Qui cách

Số lượng

Khối lượng trên 1 đợn vị chiều dài Ki (Kg/m)

Khối lượng (Kg)

Nẹp dọc

L120×120 ×10 , L= 6050

18,2

770,77

Nẹp dọc phụ 01

L120×120 ×10 , L= 3150

18,2

57,33

Nẹp dọc phụ 02

L120×120 ×10 , L= 3150

18,2

57,33

Nẹp dọc phụ 03

L120×120 ×10 , L= 3150

18,2

57,33

Nẹp dọc phụ 04

L120×120 ×10 , L= 3150

18,2

57,33

Nẹp dọc phụ 05

L120×120 ×10 , L= 3150

18,2

57,33

Nẹp dọc phụ 06

L120×120 ×10 , L= 2400

18,2

43,68

Tổng

1101,1 (Kg)

CHƯƠNG 2 KHẢO SÁT NHÀ MÁY VÀ CHUẨN BỊ ĐỂ CHẾ TẠO PHÂN ĐOẠN 2.1 Khảo sát năng lực nhà máy 2.1.1 Vị trí địa lý

Hình 2. 1 Tổng công ty CNTT Phà Rừng Địa chỉ: Thị trấn Minh Đức, huyện Thủy Nguyên, thành phố Hải Phòng. Điện thoại: (+84-31) 3875066 Fax: (+84-31) 3875067 Email: [email protected] Tổng công ty CNTT Phà Rừng có vị trí tương đối thuận lợi, nằm tiếp giáp với sông Giá có điều kiện mặt nước là độ sâu lớn thích hợp cho việc đóng mới và sửa chữa các tàu vừa và lớn. 2.1.2 Nhiệm vụ chức năng của các phân xưởng Công ty CNTT Phà Rừng gồm 9 phân xưởng: Phân xưởng vỏ 1, phân xưởng vỏ 2, phân xưởng vỏ 3, phân xưởng ống, phân xưởng bài trí, phân xưởng máy, phân xưởng cơ điện, phân xưởng ụ đà, phân xưởng cơ giới. Nhiệm vụ của từng phân xưởng như sau: + Phân xưởng vỏ 1: Là phân xưởng chủ yếu đảm nhiệm nhiệm vụ sửa chữa các loại tàu và một bộ phận tham gia việc đóng mới. + Phân xưởng vỏ 2: Nhiệm vụ là gia công chi tiết của các tàu đang được thi công của Công ty trên máy CNC đồng thời làm sạch bề mặt tôn tấm, thép hình trước khi gia công. Lắp rắp các chi tiết được gia công thành các phân, tổng đoạn và hoàn thiện hoàn chỉnh các phân, tổng đoạn đó. + Phân xưởng vỏ 3: Lắp rắp các chi tiết được gia công thành các phân, tổng đoạn và hoàn thiện hoàn chỉnh các phân, tổng đoạn đó. Đấu các phân, tổng đoạn đó thành con tàu hoàn chỉnh trên triền hay trong Ụ chìm. + + + + +

+ Phân xưởng ống: Nhiệm vụ là gia công và lắp đặt hệ thống ống trên tàu. + Phân xưởng bài trí: Tham gia vào việc trang trí nội thất trên tàu, đóng các dụng

+ + + +

2.1.3         2.1.4 STT

cụ phục vụ sản xuất như: bàn ghế, thước gỗ.v.v. Làm sạch và sơn các phân, tổng đoạn, sơn hoàn thiện tàu. Phân xưởng máy: Chế tạo các chi tiết máy, lắp đặt hệ thống máy cho tàu. Phân xưởng cơ điện: Quản lý hệ thống điện phục vụ sản xuất, sinh hoạt và sửa chữa các máy móc, thiết bị điện, lắp đặt hệ thống điện cho tàu. Phân xưởng ụ đà: Đảm nhiệm nhiệm vụ căn kê các tổng đoạn, vận chuyển các phân tổng đoạn, phục vụ việc hạ thuỷ tàu trên triền đà, phục vụ tàu ra vào ụ. Đội Cơ giới: Phụ trách các trang thiết bị cẩu giàn, cẩu lốp.., các loại xe phục vụ chuyên chở chi tiết, xe đưa đón CB-CNV. Nhân lực của Công ty CNTT Phà Rừng. Tổng số nhân lực của doanh nghiệp: 2468 người. Công nhân lao động trực tiếp: 1816 người. Kỹ sư chuyên ngành sản xuất chính: 239 người. Kỹ sư ngành nghề khác: 165 người. Công nhân lành nghề từ bậc 5-7/7: 313 người. Thợ hàn vỏ tàu + hàn ống: 522 người. Thợ lắp ráp vỏ tàu + Thợ ống (gia Công lắp ráp): 456 người. Công nhân lành nghề sản xuất chính (thợ bậc cao và có chứng chỉ nghề do cơ quan Đăng kiểm Quốc tế chứng nhận và cấp cho các loại thợ): 145 người Sơ đồ và diện tích mặt bằng nhà máy. Bảng 2. 1 Diện tích mặt bằng Công ty Tên gọi Đơn vị Số lượng

Diện tích mặt đất sử dụng của Công ty

1.076.507

Diện tích mặt nước

55.525

Diện tích mặt nước hạ thủy quay trở tàu

63.516

Đường giao thông nội bộ

3.899

Tổng diện tích nhà xưởng có mái che

34.699

Các công trình cơ bản 1

Diện tích bãi xếp vật tư số 2 (kho tôn tấm)

21.610

Diện tích bãi lắp ráp số 1 (bãi hàn B2)

2.750

Diện tích bãi lắp ráp số 2 (bãi hàn B5)

3.451

Diện tích các nhà kho số 2 (kho đựng mẫu, hạt mài, sơn)

1.332

Diện tích các nhà kho số 3 (kho máy tàu)

2.970

Diện tích các nhà xưởng 32

Phân xưởng vỏ 1

4.260

Phân xưởng vỏ 2

17.628

Phân xưởng vỏ 3 (sông giá)

39.312

Phân xưởng máy (gia công)

2.772

Phân xưởng điện tàu thủy

2.160

Xưởng sữa ô tô nội bộ

342

Phân xưởng ống

2.496

Phân xưởng bài trí

2.160

Nhà phun tổng đoạn (số 1 và số 2)

2.247

Xưởng tổ mộc

288

Nhà điều hành

1.632

2.1.5 Cơ sở hạ tầng, trang thiết bị trong công ty a. Âu tàu + Chiều dài: 156 m + Chiều rộng: 25 m + Sâu: 10,2 m + Trọng tải: 12000 T + Trang thiết bị chính: Cần cẩu chân đế 50T/14m (2 cái)

Hình 2. 2 Âu tàu b. Ụ nổi + Chiều dài: + Chiều rộng: + Chiều cao: + Chiều sâu:

115 m 32 m 18,6 m 10 m 33

+ Trọng tải: 4200 T + Trang thiết bị chính: Cần cẩu chân đế 5T/15m (2 cái)

Hình 2. 3 Ụ nổi c. Triền đà 34.000 T + Chiều dài: 270 m + Chiều rộng: 32 m + Đóng được tàu có trọng tải tới 40.000 tấn. + Trang thiết bị chính: Cần cẩu dàn 200T/63m (1 cái) + Đường đà có tổng chiều dài: Lmax = 270 m + Chiều rộng đà tàu: B = 32 m + Độ dốc đường trượt: i =1/19 + Chiều rộng mặt đường trượt: b =1m.

Hình 2. 4 Triền đà d, Thiết bị nâng hạ 34

Bảng 2. 2 Thiết bị cẩu chuyên dụng STT Tên gọi 1 Xe cần cẩu 2 Cẩu bán cổng trục 3 Cổng trục công sơn 4 Cẩu bán trục trong nhà xưởng 5 Cẩu trục trong nhà xưởng 6 Cẩu trục 2 dầm 7 Cẩu dàn 8 Xe nâng vận chuyển tổng đoạn 9 Xe nâng vận chuyển tổng đoạn e. Cẩu trục 200T + Chiều dài: 270 m. + Rộng: 32 m. + Trọng tải: 30.000T.

Sức nâng tối đa 50T 2x5T 2x5T 5T 16T 40T 100T 100T 190T

Đơn vị cái cái cái cái cái cái cái cái cái

Số lượng 4 10 3 1 3 12 4 1 1

Hình 2. 5 Cẩu trục 200T f. Cẩu trục hai dầm hộp 16T Cẩu trục hai dầm hộp 16T có đặc tính kỹ thuật như sau : + Trọng lượng nâng tối đa : 16 T + Chiều cao nâng: 17 m + Đường chạy ray P43: 171 m + Điện áp 3 pha 380V, 50hz

Hình 2. 6 Cẩu 16T 2.1.6 Thiết bị hàn, cắt a. Máy cắt CNC

Hình 2. 7 Máy CNC Máy cắt CNC có đặc tính kỹ thuật như sau : + Kiểu : Intergraph 7500 DD + Chiều dài tôn cắt được : Tối đa 24,5 m + Chiều rộng tôn cắt được : Tối đa 6,5 m + Chiều dày tôn cắt oxy-gas : Tối đa 100 mm + Tốc độ cắt : 190550 mm/s b. Máy hàn que Máy Hàn Que Jasic ARC350 J99 có đặc tính kĩ thuật như sau: + Hãng sản xuất : Jasic + Nguồn điện : 380V/50Hz + Chi tiết chức năng : Hàn que 36

+ + + + + + +

Dòng điện tiêu thụ : Công suất tiêu thụ : Điện áp không tải : Dải dòng hàn : Đường kính que hàn : Kích thước : Trọng lượng :

22 A 13 kVA 65 V 20-350 A 1,6 mm – 6,0 mm 460 mm-230 mm-410 mm 19 kg

Hình 2. 8 Máy hàn que c. Máy hàn tự động dưới lớp thuốc bảo vệ Máy hàn tự động dưới lớp thuốc được sản xuất và lắp ráp tại Việt Nam. Kết hợp với nguồn MIG/MAG để tạo thành hệ thống hàn tự động dưới lớp thuốc. Sử dụng cho các loại dầm thép H, Y, các loại bồn bể, ống cỡ lớn. Hệ thống điều khiển tích hợp trực tiếp lên rùa, điều chỉnh và vận hành dễ dàng + Nguồn vào :

DC 24V

+ Khả năng hàn :

2.5-4mm

+ Tốc độ hàn :

1-6m/phút

+ Khả năng di chuyển :

trái/phải

+ Khả năng xoay mỏ :

góc 45

Hình 2. 9 Máy hàn tự động c. Máy hàn bán tự động CO2 Có thể hàn dây thường hoặc dây hàn lõi thuốc hoặc chuyển đổi giữa hai loại dây hàn và cung cấp chức năng dừng hồ quang. Bảo vệ ngắn mạch, quá nhiệt và các tính năng bảo vệ khác. Bắn tóe ít, dòng hàn mạnh và ổn định. Thiết kế khối gọn, chống nước và an toàn cao.

Hình 2. 10 Máy hàn bán tự động d. Máy cắt tự động ray thẳng Máy cắt Rùa Koike IK-12 Beetle có những đặc tính kĩ thuật như sau : + Nguồn điện vào : AC220V/50Hz + Chiều dày cắt : 5-50mm + Đường kính cắt : 200 – 2000 mm + Bảo vệ nhiệt : Tấm chắn đơn + Tốc độ cắt : 150 – 800 mm/phút + Kích thước máy : 450 x 170 x 215 mm + Khối lượng : 9,5kg + Hãng sản xuất : Huawei

Hình 2. 11 Máy cắt con rùa 2.1.7 Các thiết bị khác a. Máy lốc tôn 3 trục + Chiều dày tôn lốc được: Tối đa 300 mm + Chiều rộng tôn lốc được: Tối đa 6000 mm + Đường kính lốc nhỏ nhất: 2,8 m + Kích thước máy: dài 8490 mm, rộng 2420 mm, cao 2450 mm.

Hình 2. 12 Máy lốc 3 trục b. Máy dập tạo thép hình.

Hình 2. 13 Máy tạo thép hình Máy tạo thép hình có đặc tính kỹ thuật: + Khả năng uốn thép mỏ bản rộng 120-340 mm (1 chi tiết) + Bán kính uốn nhỏ nhất 1500 mm + Khả năng uốn thép chữ T 340 mm + Bán kính uốn nhỏ nhất 1500 mm  Lực uốn ngang theo hai hướng 250T c. Máy sơn Máy phun sơn Graco TexSpray 5900-HD có những đặc tính kĩ thuật sau: + Áp lực tối đa: 3300 psi + Lưu lượng tối đa: 6,0 l/phút

Hình 2. 14 Máy sơn 2.2. Phân tích lựa chọn phương án thi công Có hai phương pháp lắp rắp tàu từ cụm chi tiết liên khớp với những đặc điểm như sau:  Lắp úp

– Ưu điểm: Khung giàn lắp ráp đơn giản, các đường hàn với tôn bao của cơ cấu

phần lớn là hàn bằng nên dễ hàn. – Nhược điểm: Phải tiến hành cẩu lật nên đòi hỏi nhà máy phải có cần cẩu có sức

nâng lớn.  Lắp ngửa – Ưu điểm: Tạo được hình dáng vỏ bao rất chính xác, biến dạng nhỏ. Phù hợp với

việc lắp ráp tàu nhỏ và tàu có tốc độ cao. – Nhược điểm: Kết cấu khung giàn phức tạp, các đường hàn nối tôn bao cơ cấu phần

lớn là hàn đứng hay hàn trần nên chất lượng không cao. Kết luận: Với phân đoạn 238 là phân đoạn ở đáy phần mối nối tôn bao khá lớn để tránh mối hàn trần và hàn đứng chất lượng không cao ta chọn phương án lắp úp.  Phương pháp tổ chức thi công đóng mới: Lựa chọn phương án tổ chức sản xuất theo dây truyền. – Theo phương pháp này, con tàu trong quá trình lắp ráp trên triền được cố định. Các tổ công nhân cùng trang thiết bị sản xuất được điều đến hoàn thành các công việc nhất định trong thời gian nhất định. – Loại việc, số công nhân của mỗi tổ khác nhau, nhưng thời gian hoàn thành phải như nhau. Khi đó do đảm nhận một loại công việc, nên chất lượng công việc tốt hơn. Dễ dàng trang bị các dụng cụ, thiết bị cơ giới hóa. Do tàu được cố định trong quá trình lắp ráp nên không cần các thiết bị để vận chuyển. – Nhược điểm của phương pháp này là công tác tổ chức sản xuất khá phức tạp và khó phân biệt ranh giới công việc giữa tổ sản xuất này với tổ sản xuất khác. 2.3. Khai triển tôn và cơ cấu phân đoạn 2.3.1 Khai triển tôn đáy trên Từ bản vẽ rải tôn và kết cấu cơ bản, ta có 2 mặt tôn đáy trên như hình bên dưới.

Hình 2. 15 Tôn đáy trên phân đoạn 238

2.3.2 Khai triển tôn đáy ngoài Sử dụng phương pháp khai triển tôn bao của kỹ sư Ê-gô-rốp khai triển tôn hông phân đoạn 238.

Hình 2. 16 Hình chiếu cạnh phân đoạn 238 a. Khai triển khổ tôn T1 Từ bản vẽ tuyến hình ta có biên dạng sườn và từ hình chiếu tấm tôn ta chọn sườn giữa chuẩn và vẽ dây cung, ta vẽ đường thẳng vuông góc với dây cung đó. Đó là đường chuẩn cắt tất cả các sườn trong phạm vi tấm tôn. Kẻ đường thẳng vuông góc 42

với đường chuẩn và song song với đường chuẩn, lấy điểm gốc chuẩn là giao điểm giữa đường chuẩn và đường vuông góc.

Hình 2. 17 Xác định đường chuẩn của khổ T1 b. Khai triển các đường chuẩn của tấm tôn T1 – Trên một vị trí khác của sàn phóng dựng đường thẳng bất kỳ. – Lấy dấu vị trí các sườn thực từ sườn 92 +100 đến 102-150 trên đường thẳng, qua các điểm đó dựng các đường thẳng vuông góc. – Đặt lát gỗ T dọc theo đường chuẩn m, lấy dấu các điểm từ O1 đến O11 lên lát gỗ. – Duỗi thẳng T sau đó đặt T vuông góc O x sao cho điểm K trùng vị trí sườn 92 +100, từ các điểm O1 đến O11 trên T kẻ gióng các đường thẳng song song O x cắt các đường 43

thẳng vuông góc lần lượt tại các điểm tử O’1 đến O’11. Nối các điểm đó lại bằng đường cong trơn đều ta được hình khai triển của đường chuẩn.

Hình 2. 18 Khai triển đường chuẩn Bước 3: Sau khi khai triển được đường chuẩn, đường mép trên ta tiến hành đo biên dạng thật của tôn Ta khai triển được tôn bao T1 của phân đoạn 238 như sau:

Hình 2. 19 Khai triển tôn bao phân đoạn 238

Tương tự với những tấm tôn còn lại ta khai triển ra, ta được tấm tôn bao của cả phân đoạn như hình dưới.

Hình 2. 20 Tờ tôn T2

Hình 2. 21 Tờ tôn T3

Hình 2. 22 Tờ tôn T4

Hình 2. 23 Tờ tôn T5

Bảng 2. 3 Bảng tính khối lượng tôn STT

Tên chi tiết

Quy cách (mm)

Số lượng

10×1480

8510000

0,67

10×1480

8510000

0,67

10×1300

7475000

0,59

t = 10

6095837,9

0,48

t =10

6560747,5

0,52

12×1480

8510000

0,8

12×1480

8510000

0,8

12×1480

8510000

0,8

12×1000

5687715,52

0,54

t =12

9609462,2546

0,96

Diện tích (mm2)

Khối lượng (T)

Tôn đáy trên

9 10

Tôn đáy dưới

Tổng

6,83

CHƯƠNG 3: LẬP QUI TRÌNH CÔNG NGHỆ THI CÔNG PHÂN ĐOẠN 238 3.1. Chế tạo khung giàn lắp rắp cho phân đoạn 238 – Chọn tôn đáy trên của phân đoạn đáy làm chuẩn => Ta sử dụng bộ bệ gia công cố định vững chắc trên nền phẳng sẵn có trong nhà máy sau đó hàn thêm các thanh chống – Các cột chống được làm bằng bê tông hoặc thép. Dầm dọc bệ được làm bằng thép chữ I, đặt cách nhau một khoảng 600 (mm) bằng với khoảng cách khoảng sườn nhằm đặt ví trí các cơ cấu chính xác để lắp ráp. – Chiều cao của bệ tính từ mặt đất lên là 800 mm. Chiều dài, chiều rộng của bệ phụ thuộc vào kích thước của phân đoạn được giao.

2 600 800

1 1. Cột chống

5750

Hình 3. 1 Bệ gia công thiết kế cho phân đoạn 238 2. Dầm dọc làm bằng thép chữ I

3. Thanh ngang

3.2. Quy trình gia công các chi tiết và cụm chi tiết 3.2.1. Các thiết bị sử dụng trong quá trình gia công chi tiết –

Dụng cụ đo lường: gồm các loại thước thẳng, thước gấp, thước cuộn eke…để đo chiều dài, đo góc vuông.

–

Dụng cụ xác định dấu: compa, mũi vạch, quả dọi, dây bật đường thẳng, phấn, sơn… để lấy dấu.

–

Các thiết bị cắt tôn: máy cắt tôn cơ khí, máy cắt tự động CNC.

–

Thiết bị dụng cụ để uốn nắn: Máy lốc tôn, máy thụi, máy uốn cơ khí thép hình, máy uốn tự động thép hình, búa gỗ, đòn bẫy, kích kéo, cột chống, kích thủy lực, pa lăng, mã chữ kết hợp với nêm để ép sát kết cấu với bệ.

–

Dụng cụ để kiểm tra độ thăng bằng.

–

Chuẩn bị diện tích mặt bằng sản xuất của phân xưởng.

–

Đối với thép tấm cần chuẩn bị các loại thép tấm có độ dày là 8mm, 10mm, 12mm.

–

Đối với thép hình cần chuẩn bị thép có quy cách L120x120x10

–

Máy khoan, khoét.

–

Máy hàn tự động, bán tự động.

3.2.2. Xử lý vật liệu –

Làm sạch theo yêu cầu, sơn chống gỉ, lấy dấu lắp ráp.

–

Quá trình xử lý vật liệu có thể chia làm ba bước: nắn thẳng, làm sạch bề mặt vật liệu và sơn chống gỉ.

–

Nắn thẳng nhằm mục đích loại trừ những chỗ lồi lõm trên bề mặt tấm do việc nguội không đồng đều trong quá trình nhiệt luyện, cán thép hoặc do việc vận chuyển bốc xếp, loại trừ ứng suất dư còn lại trong vật liệu, loại trừ một phần các oxit sắt bám trên bề mặt tấm đã bong khỏi tấm sau một thời gian nằm ngoài trời.

–

Làm sạch bề mặt vật liệu nhằm loại trừ lớp oxit sắt, dầu mỡ và các tạp chất khác bám trên bề mặt vật liệu. Nếu không được làm sạch thì dù lớp sơn có chắc chắn đến đâu cũng bị boong ra khỏi bề mặt kim loại cùng với các lớp oxit, khiến vật liệu bị ăn mòn mãnh liệt hơn, làm giảm đi độ bền, tuổi thọ của các kết cấu, chi tiết.

3.2.3. Các bước chuẩn bị trước khi hàn Bước 1: Kiểm tra vật liệu – Loại bỏ các khuyết tật có hại trên bề mặt thép, trên các bề mặt đã qua quá trình cắt. – Vật liệu hàn phải được bảo quản và kiểm soát một cách phù hợp, và có thể sấy nếu cần thiết. Bước 2: Chuẩn bị mép hàn – Rãnh hàn phải được gia công đúng cách thức và đồng dạng. Loại bỏ các khuyết tật trên rãnh hàn. Lau chùi dầu mỡ, bụi, gỉ…trên rãnh hàn và vùng cạnh rãnh hàn. Việc sơn lên trên phần hàn không gây tác hại tới chất lượng mối hàn. Bước 3: Chú ý những vấn đề trong quá trình lắp ghép

– Hình dạng, quy cách và khe hở hàn phải phù hợp với quy định trong quy trình hàn. – Các khuyết tật trên bề mặt cơ cấu chính phải được loại bỏ bằng phương pháp hàn, mài,… – Mối ghép phải không có khe hở, lệch mép và biến dạng quá lớn. – Không được dùng lực quá mạnh để chỉnh lại các mã gá không đặt, sẽ tạo sự biến dạng lớn. 3.2.4. Lấy dấu Yêu cầu: – Chiều sâu mũi đột không vượt quá 1 mm. – Sai lệch đường lấy dấu vị trí cơ cấu so với lí thuyết là 1 mm. – Tất cả các nguyên vật liệu đưa ra vạch dấu đều phải được nắn phẳng, đánh sạch và sơn lót chống gỉ. – Kích thước các chi tiết hoặc kết cấu được vạch dấu theo số liệu lấy từ nhà phóng dạng. – Cần phải vạch dấu các đường sau: Đường lý thuyết, đường kiểm tra, đường bao chi tiết, đường bao lỗ khoét, tâm cung tròn, đường cơ cấu … Phương pháp lấy dấu: Căng dây, bật phấn. Dụng cụ lấy dấu: mũi đột thường, mũi đột định tấm, mũi đột kiểm tra, càng vạch, đường vạch đường kiểm tra, miếng kẹp, móc kẹp vận chuyển, móc kẹp, con vạch đường song song có thể điều chỉnh được, con vạch đường song song có các điểm cố định. 3.3. Gia công tấm tôn phẳng 3.3.1. Qui trình chung –

Bước 1: Nắn phẳng tờ tôn (nếu bị cong vênh)

–

Bước2 : Đưa tờ tôn lên máy cắt CNC cắt theo đúng biên dạng.

–

Bước 3: Vát mép tờ tôn

–

Bước 4: Ghi tên chi tiết, chiều lắp trên bệ.

Yêu cầu: –

Nhiệt độ và tốc độ cắt phải đúng yêu cầu.

– Các chi tiết phải được ghi tên đầy đủ. 50

III.3.2.

Áp dụng cho chi tiết tấm tôn đáy trên

Chuẩn bị: – Thép tấm khổ 12000×3200, 12000×6000, 6000×2000 – Không gian tại tổ gia công của phân xưởng vỏ – Các thiết bị cẩu, máy CNC, máy cắt hơi cầm tay, máy mài cầm tay. Các bước tiến hành – Tấm tôn khi được lấy từ kho được nắn phẳng bằng máy cán nhiều trục, đánh sạch. Sau đó được sơn lót chống gỉ tại nhà sơ chế tôn. – Từ bản vẽ nhập dữ liệu vào máy cắt CNC, tiến hành cắt CNC thu được kích thước thật của tôn đã khai triển, các lỗ khoét cũng được cắt ngay lúc này. – Vát mép tờ tôn và mài. – Ghi kí hiệu tấm tôn, chiều lắp ráp. – Dung sai cho phép: 

Đối với đường thẳng: ±0,5 mm.



Đối với đường cong: ±1,5 mm.

3.4. Gia công chi tiết tấm tôn cong 3.4.1. Qui trình chung – Bước 1: Nắn phẳng tờ tôn. – Bước 2 : Đưa tờ tôn lên máy cắt CNC cắt theo đúng biên dạng đã khai triển. – Bước 3: Lấy dấu vị trí các đường uốn tôn cơ bản, lấy dấu vết đường sườn. – Bước 4: Lốc tờ tôn ( hoặc dùng máy ép thủy lực). Kiểm tra tờ tôn theo dưỡng. Cứ tiếp tục bước này cho đến khi đạt yêu cầu. – Bước 5: Ghi tên chi tiết, chiều lắp trên bệ.

Hình 3. 2 Tờ tôn đáy ngoài 51

Yêu cầu: – Nhiệt độ và tốc độ cắt phải đúng yêu cầu. – Tấm tôn phải cong theo đúng tuyến hình với sai lệch cho phép. – Các chi tiết phải được ghi tên đầy đủ. 3.5. Gia công thép hình (L120x120x10) – Quy trình chế tạo: sơ chế thép ⇒ cắt thép ⇒ vệ sinh mép thép ⇒vận chuyển đến vị trí lắp ráp. – Phương pháp thực hiện:  Thép hình khi lấy từ kho được duỗi thẳng, đánh sạch và sơn lót chống gỉ.  Vạch dấu theo dưỡng.  Được cắt thành các đoạn có kích thước chính xác bằng máy cắt tay hoặc được chấn. – Kiểm tra

 Dùng thước đo chiều dài kiểm tra chiều dài thép được cắt  Sai số chiều dài chi tiết đến 3m: ± 1mm.  Sai số chiều dài chi tiết trên 3m: ± 2,0mm.  Chiều rộng, chiều cao các chi tiết nẹp dọc: ± 1,0mm.  Độ cong bản thành: ± 2,0 mm.

Hình 3. 3 Hình ảnh chi tiết nẹp dọc đáy đã được gia công 3.6. Gia công cụm chi tiết tấm tôn có nẹp gia cường 3.6.1. Gia công cụm chi tiết đà ngang a. Chuẩn bị –

Vật liệu: tấm đà ngang chiều dày 8, các nẹp gia cường.

–

Các bản vẽ kết cấu cơ bản.

b. Các bước tiến hành. Bước 1 : Rải tôn tấm lên bề mặt sàn. 52

– Đặt tấm phẳng lên sàn của phân xưởng. Bước 2: Lấy dấu cơ cấu lên tấm đà ngang – Chuẩn bị: dây bật phấn, thước đo, đột, búa, bút sơn, sơn – Tiến hành vẽ. Đường chuẩn: 1,2,3,4. Đường dấu cơ cấu: 5, 6, 7, 8.

Hình 3. 4 Lấy dấu cơ cấu trên đà ngang 95-1 Bước 3: Lắp ráp và hàn nẹp gia cường lên đà ngang – Chuẩn bị: 1 máy hàn bán tự động. – Quy trình: Đặt cơ cấu nẹp gia cường vào vị trí đã lấy dấu trên đà ngang 95-1, điều chỉnh tư thế nẹp cho vuông góc băng thước góc à hàn đính nẹp dọc với đà ngang. – Hàn chính thức nẹp gia cường với đà ngang bằng máy hàn bán tự động, hàn từ giữa ra hai bên. – Chọn chế độ hàn bán tự động điện cức nóng chảy trong môi trường khí bảo vệ là CO2 (hàn MAG). Bước 4: Xử lý biến dạng – Chuẩn bị:  Thiết bị: láy dấu, xử lý biến dạng  Máy móc: máy cắt, máy mài. Bước 5: Kiểm tra và nghiệm thu. – Kiểm tra toàn bộ cụm chi tiết, nắn sửa cong vênh nếu có. 53

– Ghi tên cụm chi tiết, kí hiệu vị trí lắp ráp, lưu kho.

Hình 3. 5 Chi tiết đa ngang được hoàn thành 3.7. Gia công cụm chi tiết sông phụ 1 Các bước liến hành: Bước 1 : Đặt tôn tấm sống phụ đã được gia công ở trên lên mặt sàn của phân xưởng. Bước 2: Lấy dấu cơ cấu lên tấm sống phụ. –

Đường chuẩn: 1; 2

–

Đường lấy dấu: 3; 4; 5;6;7

Hình 3. 6 Lấy dấu cơ cấu trên sống phụ 1 Bước 3 : Lắp ráp và hàn các nẹp gia cường lên sống phụ 1.

Hình 3. 7 Sơ đồ lắp ráp và hàn nẹp gia cường lên sống phụ 1 1 ; 2 ; 3 ; 4 ; 5 : Thứ tự lắp ráp và hàn nẹp gia cường. Bước 4: Xử lý biến dạng. Bước 5: Kiểm tra và nghiệm thu.

Hình 3. 8 Cụm chi tiết sống phụ 1 sau khi gia công 3.8. Lấy dấu các cơ cấu trên tôn đáy trên 3.8.1. Lắp ráp tôn đáy trên a. Rải và hàn đính tôn.  Chuẩn bị : –

2 máy hàn bán tự động ;

–

Các thiết bị phục vụ cho quá trình ráp như : dụng cụ lấy dấu,…

–

Các tờ tôn đã được vệ sinh, làm sạch.

 Quy trình : –

Lấy dấu vị trí của tôn đáy trong lên bệ.

–

Thứ tự rải tôn như hình 3.9.

–

Cẩu tờ tôn I đặt xuống bệ lắp ráp trùng với vị trí lấy dấu trên bề mặt, căn chỉnh để đường lấy dấu sống chính trên tấm tôn, kéo sát xuống bệ, hàn đính xuống bệ để cố định. Rà mép và lấy tờ tôn này làm chuẩn để lắp ráp các tờ tôn khác.

–

Cẩu tờ tôn II lên bệ khuôn, kéo sát vào tờ tôn I, tiến hành vát mép mối hàn, dùng tăng đơ điều chỉnh khe hở hàn giữ hai tờ tôn, với khoản cách hở là 2±0,5mm,. Hàn đính hai tấm tôn với nhau và hàn đính tấm tôn xuống bệ.

–

Sau khi hàn cố định cách tấm, ta hàn các tấm mồi vào. Các tấm mồi đặt ở hai đâu mối hàn. Giúp cho chất lượng mối hàn được đảm bảo cho hồ quang cháy đều trong suốt quá trình hàn.

Hình 3. 9 Sơ đồ rải và hàn tôn đáy trên 238 Chú thích: I, II, III,… là thứ tự rải tôn; 1, 2, 3, 4: là thứ tự hàn tôn 3.8.2 Lấy dấu các cơ cấu trên tôn đáy trên –

Cơ sở lấy dấu: Dựa theo khoảng cách giữa các cơ cấu.

–

Thiết bị: Dây bật phấn, phấn, compa, eke, thước dây…

–

Quy trình:

+ Trình tự lấy dấu theo hình 3.10. + Vì tôn đáy được cắt bằng CNC, nên độ chính sác về kích thước đường bao đảm

bảo. Ta đo từ mép của tờ tôn đáy trên I một khoẳng bằng 740mm, từ đó kẽ đường thẳng song song với mép từ tôn I ta được đương chuẩn cũng là đường dọc tâm của tàu trên tôn đay trong. + Lấy dấu các vị trí: đường bao phân đoạn, sống phụ, nẹp dọc đáy. + Sau đó căng dây bật phấn để lấy dấu các đường trên.

+ Lấy dấu các vị trí đà ngang, mã hông, mã sống chính => căng dây bật phấn. + Lấy dấu vị trí đường kiểm tra: lấy dấu ở các vị trí có sống phụ, đà ngang, dầm

dọc và các mã. Cách các vị trí đã nêu một khoảng bằng 100mm. + Kiểm tra sau khi lấy dấu: đo và so sánh chéo của các hình chữ nhật. + Dùng bút sơn mau khô kẻ lại các đường bật phấn.

Hình 3. 10 Sơ đồ lấy dấu 3.8.3 Lắp ráp và hàn các cơ cấu lên tôn đáy trên a. Chuẩn bị: –

Thép hình các nẹp dọc, mã sống chính, mã hông, đà ngang, sống phụ đã được gia công trước.

–

Máy hàn hồ quan bán tự động

–

Các thiệt bị phục vụ cho việc lắp ráp: thước góc, tăng đơ, mã.

b. Quy trình:  Lắp ráp và hàn sống phụ –

Lắp ráp và hàn đính: + Cẩu cụm chi tiết sống phụ vào vị trí đã lấy dấu. + Lắp tăng đơ, căn chỉnh theo chiều cao, chiều nghiêng ngang, nghiêng

dọc. 57

+ Lắp đặt thanh chống cố định và gắn các mã định vị sống phụ với tôn đáy

trên. + Kiểm tra đảm bảo về chiều dài theo đường lấy dấu. + Hàn đính các sống phụ với tôn đáy trên.

Hình 3. 11 Thứ tự lắp ráp và hàn sống phụ lên tôn đáy trên Chú thích: 1,2 thứ tự lắp ráp và hàn  Lắp ráp và hàn các nẹp dọc lên tôn đáy trên –

Lắp ráp và hàn đính. + Cẩu thép hình L120x120x10 đặt vào vị trí nẹp dọc đã lấy dấu theo thứ tự

như hình vẽ. + Dùng mã chữ U để ép sát nẹp dọc vào tôn và căn chỉnh theo đường lấy

dấu. + Kiểm tra bằng thước góc và sau đó hàn đính hàn đính với tôn đáy trên.

Hình 3. 12 Thứ tự lắp ráp và hàn nẹp dọc đấy trong –

Hàn chính thức các nẹp dọc vào tôn đáy trên: + Tháo các mã chữ U trước khi hàn chính thức. + Thứ tự hàn theo như hình + Hàn từ giữa ra hai bên.

 Lắp ráp và hàn các đà ngang đáy, mã sống chính, mã hông –

Lắp ráp và hàn đính: + Cẩu các cụm chi tiết nêu trên đặt vào các vị trí đã được lấy dấu. + Thứ tự lắp ráp như hình vẽ. + Lắp tăng đơ, căn chỉnh theo chiều cao, chiều nghiêng ngang, nghiêng

dọc. + Lắp đặt thanh chống cố định. + Kiểm tra bảo đảm chiều dài theo đường dấu. + Hàn đính các cụm chi tiết với sống phụ và với tôn đáy.

Hình 3. 13 Thứ tự lắp ráp, hàn cụm chi tiết đà ngang lên tôn đáy trên  Lắp ráp và hàn nẹp dọc và nẹp dọc phụ đáy dưới –

Lắp ráp từ giữa ra 2 bên theo thứ tự như hình. Đặt các nẹp dọc đày ngoài và các nẹp dọc phụ lên lỗ khoét trên đà đà ngang. Căn chỉnh các nẹp dọc đáy ngoài đúng với vị trí lấy dấu, dùng các thanh chống để tạo độ vững và cân bằng so với nẹp dọc, sau đó tiến hành hàn với các đà ngang

Hình 3. 14 Thứ tự lắp ráp nẹp dọc đáy ngoài 60

3.8.4 Quy trình lắp rắp tôn đáy dưới –

Cẩu tờ tôn số I đặt xuống phân đoạn, căn chỉnh đường tâm tờ tôn trùng với đường tâm sống chính (đường dọc tâm), căn chỉnh tờ tôn theo chiều dài. Dùng tâng đơ kéo sát tờ tôn xuống cơ cấu, hàn đính tờ tôn với cơ cấu. Rà mép và lấy tờ tôn này làm chuẩn để lắp ráp các tờ tôn khác.

–

Cẩu tờ tôn II lên, kéo sát với tôn I sao cho đảm bảo khe hở hàn, rà mép, căn chỉnh theo chiều dài, rộng, ép sát tờ tôn xuống cơ cấu băng tăng đơ.

–

Chuẩn bị mép hàn 2 tờ tôn như hình.

–

Hàn mã răng ngược, hàn đính 2 tờ tôn với nhau.

–

Các tấm tôn III, IV, V, VI lắp ráp tương tự. Chú ý: 1,2,3.. là thứ tự hàn. I, II, III…là thứ tự rải tôn.

Hình 3. 15 Lắp rắp và hàn tôn đáy dưới

3.9. Cẩu lật Sau khi hàn tất cả các chi tiết, ta tiến hành cẩu lật phân đoạn. Trước khi cẩu lật tiến hành hàn các tai cẩu tại vị trí sườn khỏe của phân đoạn.

Hình 3. 16 Qui cách tai cẩu  Yêu cầu – Dùng 4 tai cẩu bố trí tại vị trí cơ cấu khỏe của phân đoạn, mã tai cẩu hàn chắc chắn với tôn bao – Trước khi cẩu lật tháo bỏ các đế kê – Sử dụng các thanh chống cho phân đoạn tránh biến dạng khi cẩu lật.

TÀI LIỆU THAM KHẢO [1] Vũ Ngọc Bích, Huỳnh Văn Chính, Công nghệ đóng tàu – ĐH GTVT TPHCM, 2012. [2] Nguyễn Đức Ân, Hồ Quang Long, Sổ tay kỹ thuật đóng tàu – NXB KHKT, 1978. [3] Cục Đăng Kiểm Việt Nam, Quy chuẩn kỹ thuật quốc gia, quy chuẩn phân cấp đóng tàu biển vỏ thép (QCVN 21:2010/BGTVT). [4] Cục Đăng Kiểm Việt Nam, Hướng dẫn giám sát đóng mới tàu biển – NXB GTVT HN, 2005.

Strutture in C
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STRUTTURE IN C.A.: CONFRONTO DEI RISULTATI TRA NTC2018 E NTC2008 Dallo scorso 22 marzo sono entrate in vigore le nuove norme tecniche per le costruzioni “revisionate” dal DM 17/01/2018. Come avevo anticipato nel precedente articolo adesso entriamo nel dettaglio analizzando le variazioni riscontrate nei risultati di calcolo. Analizziamo a tal proposito una semplice struttura intelaiata in c.a. a tre piani che abbiamo progettato utilizzando le NTC2008. Le colonne sono in maggioranza 30×60 (con alcune 30×30 del portico) e le travi 30×50. Dal punto di vista delle sollecitazioni di calcolo non vi è in pratica alcuna differenza. Il confronto più interessante è però quello in termini di progettazione delle armature. Le problematiche che saltano all’occhio in una prima analisi sono: 1. Mancata verifica della sezione allo spiccato delle fondazioni 2. Mancata verifica della gerarchia delle resistenza per alcuni nodi 3. Diversa armatura dei nodi trave-pilastro 4. Miglior verifica per pilastri “corti

FIgura 1: Zone della struttura interessate dalle problematiche. Non temete: per le parti che non hanno superato le verifiche (in rosso) si trova comunque una soluzione ingegneristicamente applicabile ed accettabile. La figura è utile solo per localizzare le zone dove si potrebbero presentare i problemi. Il confronto verrà comunque fatto tra le due soluzioni (una per NTC2008 e una per NTC2018) che consentono la progettazione della struttura. Approfondiamo quindi i motivi principali delle differenze. 1. Mancata verifica della sezione allo spiccato delle fondazioni Una delle principali novità delle NTC2018 è senz’altro la verifica di duttilità. Essa deve essere effettuata per le sezioni allo spiccato delle fondazioni. Consiste nel confrontare il rapporto tra curvatura ultima (Φu) e curvatura convenzionale di prima plasticizzazione (Φyd), con la domanda di duttilità (μΦ).

Figura 2: a) Esempio di diagramma momento-curvatura – b) Esempio di variabilità del fattore di duttilità con T1 L’esito della verifica è influenzato da:  Sforzo normale Nsd (elevata compressione fa diminuire la duttilità)  quantità di armatura longitudinale (sezioni molto armate sono meno duttili)  armature trasversali (all’aumentare delle staffe aumenta il confinamento e di conseguenza la duttilità)  legature tra le armature longitudinali (più legature incrementano il confinamento) Come già accennato, staffe e legature sono direttamente correlate al modello “confinato” del calcestruzzo. In effetti la maniera più efficace di “progettare” la duttilità è aumentare il confinamento della sezione. Nella figura successiva vediamo come staffe e legature abbiano l’effetto di aumentare sia la resistenza a compressione (fck) sia la deformazione ultima (εcu) del calcestruzzo, incrementando quindi anche la duttilità.

Figura 3: Calcestruzzo confinato: confronto tra modelli “senza staffe”, “con staffe” e “con staffe e legature” A conti fatti, per il piede delle colonne principali, applicando le nuove NTC2018 si passa da un passo delle staffe di 13 cm a passi compresi tra 6 e 13 cm, con valore prevalente pari a 7 cm. Pertanto negli esecutivi che elaboreremo da qui in avanti sarà frequente che il passo delle staffe al piede risulterà più fitto rispetto a quello calcolato con le NTC2008.

Figura 4: Passo delle staffe per la zona critica allo spiccato della fondazione 2. Mancata verifica della gerarchia delle resistenza per alcuni nodi Per la verifica di gerarchia delle resistenze (ora chiamata “Pressoflessione”) le nuove Norme Tecniche risultano più gravose. Il motivo è banale. Come riportato nella tabella 7.2.I del paragrafo 7.2.2 il coefficiente di sovraresistenza γrd passa da 1.10 a 1.30 per classe di duttilità “bassa”. Lo stesso valore è da utilizzare anche per la classe di duttilità “alta”.

Figura 5: Estratto della tabella 7.2.I del DM 17/01/2018 Come ormai risaputo, la verifica della gerarchia si può migliorare in vario modo:   

ridimensionando le sezioni (aumento del pilastro e/o diminuzione delle travi) orientando diversamente le colonne (ruotando le sezioni verso il lato meno utilizzato) aumentando le armature longitudinali delle colonne (in modo da aumentare il momento resistente delle colonne) Quest’ultima opzione è da utilizzare come “ultima spiaggia”, in quanto aumentando le armature longitudinali diminuisce la duttilità, ed aumenta anche la domanda a taglio per l’elemento. Operando un semplice confronto tra le armature longitudinali necessarie per il superamento della verifica, per i pilastri interessati si passa da 20 cm² (8Ø18) delle NTC2008 a 25 cm²(10Ø18) delle NTC2018. 3. Diversa armatura dei nodi trave-pilastro Nelle nuove Norme Tecniche, i nodi trave-pilastro hanno acquisito ancora più importanza. In pratica non vi è differenza di approccio nella progettazione delle armature tra le varie classi di duttilità, al punto che anche per le costruzioni “non dissipative” viene richiesta la progettazione dei nodi come per la CD”B”. Per la CD”A” la verifica risulta leggermente più gravosa in quanto il fattore γrd è pari a 1.20 (1.10 per CD”B”). Nelle NTC2008 per la classe di duttilità “bassa” era solo prescritta una quantità di armatura minima, funzione delle dimensioni geometriche del nodo e delle resistenze dei materiali. Per le NTC2018 invece è da elaborare la verifica del nodo utilizzando le sollecitazioni trasmesse dalle travi e dal pilastro superiore. In termini di confronto dei risultati, in questo caso si nota una marcata variabilità del passo delle staffe tra i vari nodi della struttura, con una prevalenza a valori più elevati (e comodi) per le NTC 2018 (da 8 cm si passa anche a 13 cm).

Figura 6: Confronto in termini di passo delle staffe nei nodi trave-pilastro Questa modifica della norma è da vedere non come una diminuzione della sicurezza, ma come una razionalizzazione della disposizione delle armature all’interno del nodo, differenziando i nodi interni da quelli d’angolo in quanto equilibrati dalla presenza delle travi nei vari lati del nodo. Questa modifica va incontro anche alle difficoltà realizzative di un corretto nodo trave-pilastro. 4. Miglior verifica per pilastri “corti Nelle nuove Norme Tecniche (§7.2.2) è presente un’importante precisazione: “…La domanda di resistenza valutata con i criteri della progettazione in capacità può essere assunta non superiore alla domanda di resistenza valutata per il caso di comportamento strutturale non dissipativo…” Detto in parole semplici, si può assumere come valore massimo della domanda quello derivante dall’analisi della struttura con fattore di comportamento q relativo a quello delle strutture non dissipative (q massimo pari a 1.5). Nel caso dei pilastri la domanda a taglio è funzione dei momenti resistenti e della lunghezza dell’elemento. Al tendere della lunghezza a zero il taglio va ad infinito (funzione iperbole).

Figura 7: Formule della domanda a taglio e confronto con valore limite strutture Non-Dissipative Con questa nuova indicazione, la Norma pone un limite massimo al valore dell’azione tagliante di progetto (V ND in Figura 7), come se la struttura fosse non dissipativa ed oltre il quale non è realistico progettare la resistenza a taglio. Quindi a trarre beneficio da questa nuova definizione sono le colonne corte e le colonne con elevata armatura longitudinale. Nel caso in esame, per una colonna di altezza pari a 1 m le NTC2008 non consentivano di progettare l’elemento, anche se non sollecitato. Con le NTC2018 invece, per la sola verifica a taglio è possibile disporre staffe Ø8 ogni 13 cm. Conclusioni

Con questo semplice esempio, possiamo già fare alcune considerazioni relativamente alle strutture in c.a. Innanzitutto, la norma non stravolge i concetti o l’impianto applicativo. Le differenze riguardano essenzialmente due considerazioni già ampiamente trattate e conosciute: 1. Evitare le rotture fragili (es. taglio) 2. I punti deboli sono i nodi travi-pilastro Per la prima vale la regola “più staffe fanno sempre bene” , cioè è opportuno avere passi delle staffe ridotti o armature a più bracci. A ciò si può abbinare anche l’utilizzo di diametri più grossi, ad esempio come il Ø10 al posto del comune Ø8. Queste considerazioni ci fanno pensare agli errori di approccio commessi nello sviluppo edilizio del dopoguerra, nel quale è stata ampiamente diffusa (sino ai giorni nostri) l’abitudine costruttiva del classico Ø6 o Ø8 ogni 25 cm, magari aggiungendo in cantiere qualche barra longitudinale in più (alla faccia della duttilità). Per la seconda, le nuove norme mettono sullo stesso piano i nodi di tutti i tipi di strutture (CD”B”, CD”A” e non dissipative), a testimonianza che i nodi devono essere progettati per non collassare mai, qualsiasi sia il livello di dissipazione della struttura. A tal proposito è bene sempre ricordare che nell’affrontare la vulnerabilità sismica di edifici esistenti abbiamo a che fare con nodi non armati, e quindi soggetti a rottura fragile. C’è anche una terza considerazione: è fondamentale durante un evento sismico che non venga mai meno l’apporto della sezione alla base della costruzione. La verifica della duttilità serve proprio a questo scopo, garantendo un adeguato confinamento del calcestruzzo. Infine un dato: a parità di sezioni sono stati necessari solo 100 kg di acciaio in più nel caso delle NTC2018 rispetto alle NTC2008 (20 t contro 19.9 t). Come potete vedere la revisione delle norme non è una rivoluzione; è una serie di considerazioni utili ad “aggiustare il tiro” ed a rendere più razionale la progettazione. Tutti questi concetti erano già contenuti negli Eurocodici. Peccato aspettare 10 anni.

Sistem Dinamik Muh. Rifandi
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TUGAS SISTEM DINAMIK

MUH. RIFANDI

PROGRAM PASCA SARJANA UNIVERSITAS NEGERI MAKASSAR 2018

1) Diberikan Sistem: 0

xy 0

y  x  y dengan x, y  R dan nilai delta sesuai nomor urut di absen (no urut 1 nilai delta adalah 1; no urut 2 nilai delta adalah 2; no urut 3 nilai delta adalah 3; no urut 4 nilai delta adalah 4; no urut 5 nilai delta adalah 5 dan seterusnya no urut 10 nilai delta adalah 10; no urut 11 nilai delta adalah -1; no urut 12 nilai delta adalah -2 dan seterusnya no urut 20 nilai delta adalah -10) Tentukan gambar trajektori (Phase Potrait) dari sistem tersebut dengan steps: 1. Tentukan nilai eigen sistem secara manual dan Maple! Penyelesaian: Nomor urut 2, sehingga sistem menjadi: 0

x y 0

y  x  2y Sistem di atas dapat ditulis  0   0 1  x   x0       y   1  3 y    0 1   maka nilai eigen dari A adalah Dimisalkan, A    1  3

A  I  0  0 1  1 0        0  1  3  0 1  0 1   0        0  1  3  0   1       0  1 3   (3   )  1  0

2  3  1  0

1, 2

 b  b 2  4ac  2a

1, 2

 3  (3) 2  4(1)( 1)  2(1)

1, 2 

 3  13 2

3 13  2 2 3 13 3 13 1   ; 2   2 2 2 2 Dengan menggunakan Maple, didapatkan

1, 2 

2. Tentukan solusi umum sistem Maple! Penyelesaian: Solusi Umum dari Sistem Persamaan Linear

3. Gambarkan Phase Potrait sistem!

4. Tentukan jenis kestabilannya! Penyelesaian: Berdasarkan nilai eigen yang didapatkan sebelumnya, yaitu 1 

3 13   0 dan 2 2

3 13   0 berarti 2  0  1 , sehingga tipe titik kritisnya adalah Saddle Point 2 2 dan sistem tersebut tidak stabil.

 2

2) Tentukan solusi umum, fundamental khusus dan manifold center sistem persamaan 0

x  2 x  3 y  y 3 0

, ( x, y)  R 2

y  2x  3y  x 3 Penyelesaian: a. Menentukan Solusi Umum Sistem di atas dapat ditulis  0    2 3  x   y 3   x0          y   2  3  y   x 3     2 3   maka nilai eigen dari A adalah A    2  3

A  I  0   2 3  1 0        0  2  3  0 1   2 3   0        0  2  3  0   3   2     0  3     2 (3   )( 2   )  6  0

2  5  6  6  0 2  5  0  (  5)  0 1  0; 2  5 Mencari vektor eigen diperoleh dengan langkah berikut: Untuk 1  0   2 3  x      0  2  3  y   2x  3y  0 2x  3y  0

Vektor eigen untuk 1  0 adalah

 3 v1     2 Untuk 2  5  3 3  x      0  2 2  y  3x  3 y  0 2x  2 y  0

Vektor eigen untuk 2  5 adalah

  1 v2    1 Jadi, solusi dari sistem persamaan tersebut adalah  3   1 x(t )  C1  e 0t  C2  e 5t  2 1

b. Matriks Fundamental Umum  3e 0t  e 5t  C1     (t )   0t 5t  2 e e   C2  c. Matriks Fundamental Khusus Pilih t 0  0 , akan dicari x (1) dan x ( 2 ) sedemikian sehingga

1  0 x (1) (0)  i    dan x ( 2) (0)  j    1  0 Untuk x (1) , akan dicari C1 dan C2 dengan persamaan 3) Hitung bentuk normal untuk suatu pemetaan dari R 2 di sekitar titik tetap yang mana matriks pelinearan mempunyai bentuk berikut. a 1 J    1 0 Nilai a  1 untuk urutan ganjil dan a  1 untuk urutan genap Penyelesaian: Nomor urut 1 (Ganjil) sehingga matriks menjadi 1 1 J   1 0 Kita mempunyai  x 2   xy   y 2   0   0   0  H 2  span  ,  ,  ,  2 ,  ,  2   0   0   0   x   xy   y  H 2 idem ( x, y ) dicari L j ( H 2 )  x 2  1 L j      0  1  xy  1 L j      0  1

1  x 2   2 x 0 1 1  x   x 2   2 x 2  2 xy    x 2  2 xy                2    0  0   0 0 1 0  y   x 2   0 x    1  xy   y x 1 1  x   xy   x 2  xy  y 2   x 2  y 2                  xy  0  0   0 0 1 0  y   xy   0   

 y 2  1 1  y 2   0 2 y 1 1  x   y 2   2 xy    y 2  2 xy            2       L j     2  1 0 0 0 1 0 y 0 0 0 y y                  

 0  1 L j  2     x  1  0  1 L j      xy  1  0  1 L j  2     y  1

1  0   0     0  x 2   2 x 1  0   0     0  xy   y 1  0   0     0  y 2   0

0 1 1  x   x 2   0  x2               2    0 1 0  y   0   2 x  2 xy    2 x 2  2 xy  0 1 1  x   xy   0 xy            2    2  2 2 x 1 0  y   0   x  xy  y    x  xy  y  0 1 1  x   y 2   0   y 2            2 y 1 0  y   0   2 xy    2 xy 

  x 2  2 xy   x 2  y 2    y 2  2 xy   xy  x2   y 2            L j ( H 2 )  span  , , , ,   xy      2 x 2  2 xy    x 2  xy  y 2 ,   2 xy  x2 y2       

Matriks Transformasi L j :

 1   2  0   1  0   0 

1 0 1 0 0   0 2 0 1 0  1 1 0 0 1   0 0  2 1 0  1 0  2  1  2  0 1 0  1 0  Sehingga diperoleh basis dari matriks L j berikut: 00    10   1  1   ,   00  0    1    10    Dan membentuk vektor  xy  y 2   y 2      y 2 ,   xy     Span sebuah dimensi dua pada H 2 adalah pelengkap untuk L j ( H 2 ) . Bentuk normal orde dua adalah 0

x  y  a1 xy  a2 y 2  O(3) 0

y  a3 xy  a4 y 2  O(3) Dimana a1 , a2 , a3 dan a 4 adalah konstanta.

LAPORAN FISIKA FARMASI F A K U L T A S I L M U K E S E H A T A N U N I V E R S I T A S M U H A M M A D I Y A H P A L A N G K A R A Y A 1 / 2 2 / 2 0 1 6

LAPORAN FISIKA FARMASI F A K U L T A S I L M U K E S E H A T A N U N I V E R S I T A S M U H A M M A D I Y A H P A L A N G K A R A Y A 1 / 2 2 / 2 0 1 6
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LAPORAN FISIKA FARMASI RIZQI CHAIRUNNISA Fisika Fisika adalah ilmu yang mempelajari tentang analisis kualitatif serta kuantitatif senyawa organik dan anorganik yang berhubungan dengan sifat fisikanya

PROGRAM STUDI DIII-FARMASI FAKULTAS ILMU KESEHATAN UNIVERSITAS MUHAMMADIYAH PALANGKARAYA

1/22/2016

LAPORAN PRAKTIKUM PENGUKURAN MASSA BAHAN DENGAN MENGGUNAKAN NERACA ANALITIK & OHAUS Diajukan untuk memenuhi laporan praktikum Fisika Farmasi yang telah dilaksanakan

Dosen Pengampu : Mohammad Rizky Fadhil Pratama, S.Farm.,M.Si., Apt

Disusun Oleh : Rizqi Chairunnisa 14.71.015863

UNIVERSITAS MUHAMMADIYAH PALANGKARAYA FAKULTAS ILMU KESEHATAN PROGRAM STUDI D3 FARMASI 2016

Page | 1 Laporan Praktikum Fisika Farmasi

TUJUAN PRAKTIKUM Tujuan dari praktikum ini adalah agar praktikan dapat mengetahui dan memahami cara pengoperasian alat ukur massa berupa neraca, baik neraca analitik maupun neraca ohaus. Selain itu, praktikan dapat lebih teliti dalam penggunaan neraca ohaus yang tingkat ketelitiannya di bawah neraca analitik, hal ini dilakukan dengan cara membandingkan penimbangan pada neraca ohaus dan penimbangan pada neraca analitik.

II.

DASAR TEORI Mengukur adalah membandingkan sesuatu yang diukur dengan besaran sejenis atau alat ukur yang ditetapkan sebagai satuan. Besaran adalah sesuatu yang dapat diukur, mempunyai nilai yang dapat dinyatakan dengan angka-angka dan memiliki satuan tertentu. Sedangkan satuan adalah pernyataan yang menjelaskan arti dari suatu besaran (Rully Bramasti dan Eko Sujatmiko, 2012). Dalam ilmu terapan seperti kimia dan fisika, pengukuran merupakan aktivitas yang membandingkan kuantitas fisik dari objek dan kejadian dunia-nyata. Alat pengukur adalah alat yang digunakan untuk mengukur benda atau kejadian tersebut (Melia, 2014). Pada dasarnya setiap alat memiliki nama yang menunjukkan kegunaan alat, prinsip kerja atau proses berlangsungnya ketika alat digunakan. Beberapa kegunaan dapat dikenali berdasarkan namanya (Taiyeb, 2006). Sifat-sifat zat biasanya dinyatakan dengan menggunakan tiga dimensi dasar yaitu panjang, bobot, dan waktu. Masing-masing sifat ini menentukan satuan tertentu dan standar pembanding. Dalam sistem metrik, satuannya adalah centimeter (cm), gram (g), dan detik (s), karena itu sering disebut sistem cgs. Suatu standar pembanding adalah satuan dasar yang menghubungkan setiap besaran terukur dengan beberapa konstanta alami atau buatan secara keseluruhan (Sinko, 2006). Massa adalah suatu sifat fisika dari suatu benda yang digunakan untuk menjelaskan berbagai perilaku objek yang terpantau. Dalam kegunaan sehari-hari, massa biasanya disinonimkan dengan berat. Namun, menurut pemahaman ilmiah modern, berat suatu objek diakibatkan adanya interaksi antara massa dengan medan gravitasi (JThorneBOT, 2015). Satuan standar massa adalah kilogram (kg). Kilogram adalah massa balok platinum-iridium yang disimpan di Bureau of Weights and Measures. Satuan praktis massa dalam sistem cgs adalah gram (g), yaitu 1/1000 dari 1 kilogram (Sinko, 2006).

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Untuk menimbang obat dengan presisi dan akurat, farmasis harus memahami kesalahan yang selalu terjadi dalam mengoperasikan neraca. Neraca kelas A yang digunakan untuk meracik resep, hanya dapat digunakan jika dijaga dalam kondisi kerja yang baik dan dicek secara berkala untuk kesamaan panjang lengan, akurasi beam rider, dan kepekaan (Sinko, 2006). Neraca analitik merupakan suatu alat yang sering digunakan dalam laboratorium yang berfungsi menimbang bahan yang akan digunakan. Bahan yang ditimbang biasanya berbentuk padatan, namun tidak menutup kemungkinan untuk menimbang suatu bahan yang berbentuk cairan. Neraca analitik yang digunakan dalam laboratorium merupakan instrumen yang akurat yang mempunyai kemampuan mendeteksi bobot pada kisaran 100 gram sampai dengan kurang lebih 0,0001 gram (Day R.A. dan Underwood A.L., 2002). Neraca analitik terdiri dari beberapa komponen, antara lain waterpass, piringan neraca, dan tombol pengaturan. Waterpass berfungsi sebagai penanda posisi neraca pada saat akan digunakan. Neraca harus dalam posisi yang seimbang pada saat penggunaannya agar data yang dihasilkan akurat. Sedangkan piringan neraca merupakan suatu wadah yang berfungsi sebagai tempat bahan yang akan ditentukan massanya. Biasanya digunakan kaca arloji sebagai wadah bahan sebelum diletakkan pada piringan neraca terebut (Bahtiar, 2011). Sedangkan neraca ohaus adalah neraca yang diperkenalkan oleh Gustav Ohaus yang merupakan seorang ilmuwan asal New Jersey, Amerika Serikat. Ilmuwan kelahiran 30 Agustus 1888 ini mempublikasikan Ohaus Harvard Trip Balance pada tahun 1912 yang kemudian dikenal dengan neraca ohaus tersebut. Neraca ini berguna untuk mengukur massa benda atau logam. Kapasitas beban yang ditimbang dengan menggunakan neraca ini adalah 311 gram dengan batas ketelitian 0,1 gram. Prinsip kerja neraca ini adalah dengan membandingkan antara massa bahan yang ditimbang dengan anak timbangan yang terukur. Neraca ohaus memiliki spesifikasi lagi seperti neraca ohaus dua lengan dan neraca ohaus tiga lengan. Pada neraca ohaus dua lengan terdapat dua lengan yang memiliki piringan neraca, pada lengan satu untuk meletakkan bahan yang akan ditimbang dan lengan lainnya untuk wadah anak timbangan. Sedangkan neraca ohaus tiga lengan adalah neraca yang hanya memiliki satu cawan sebagai tempat bahan dan 3 lengan sebagai penunjuk skala (Putra, 2014).

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III.

METODE Pada praktikum ini dilakukan penimbangan suatu bahan pada neraca ohaus dengan massa yang telah ditentukan yang dilanjutkan pada neraca analitik untuk membandingkan massa sebenarnya secara lebih tepat dan teliti.

IV.

ALAT DAN BAHAN 4.1 Alat 4.1.1 Alumunium foil, berfungsi sebagai penutup atau alas dari suatu bahan. 4.1.2 Sendok tanduk, berfungsi untuk mengambil bahan-bahan berupa padatan. 4.1.3 Neraca ohaus, berfungsi sebagai neraca atau timbangan yang menunjukkan massa bahan secara manual. 4.1.4 Neraca analitik, berfungsi sebagai neraca atau timbangan yang menunjukkan skala massa suatu bahan secara akurat (Agoestia, 2012).

4.2 Bahan Bahan yang digunakan pada praktikum ini adalah amilum manihot (pati singkong) yang berfungsi sebagai bahan yang akan ditimbang dengan neraca ohaus dan neraca analitik sedangkan dalam dunia farmasi amilum berfungsi sebagai bahan penyusun dalam serbuk awur dan sebagai bahan pembantu dalam pembuatan sediaan tablet, bahan pengikat, dan bahan penghancur (Gunawan dan Sri Mulyani, 2004)

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CARA KERJA 5.1 Penimbangan Alumunium Foil dengan Neraca Analitik

Hubungkan neraca digital dengan aliran listrik

Pastikan piringan neraca dalam keadaan bersih dan menunjukkan angka 0 (nol)

Letakkan alumunium foil pada piringan neraca

Baca skala yang tertera pada display digital dalam skala satuan gram

Catat hasil penimbangan alumunium foil tersebut

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5.2 Penimbangan Amilum dengan Neraca Ohaus

Setarakan neraca yang akan digunakan

Pastikan piringan neraca dalam keadaan bersih

Letakkan anak timbangan 5 gram pada piringan neraca sebelah kiri

Letakkan alumunium foil pada piringan neraca sebelah kanan

Tambahkan amilum pada alumunium foil dan angkat tuas pada neraca hingga bobot amilum setara dengan anak timbangan 5 gram tersebut

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5.3 Penimbangan Amilum dengan Neraca Analitik

Hubungkan neraca digital dengan aliran listrik

Pastikan piringan neraca dalam keadaan bersih dan menunjukkan angka 0 (nol)

Letakkan alumunium foil dan amilum yang telah ditimbang sebelumnya pada piringan neraca

Baca skala yang tertera pada display digital dalam skala satuan gram

Catat hasil penimbangan tersebut

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VI.

HASIL DAN PEMBAHASAN 6.1 Hasil Pengamatan Data penimbangan yang diperoleh pada praktikum ini yaitu No

Penimbangan

Massa

Alumunium Foil dengan Neraca Analitik

1,0923 g

Amilum dengan Neraca Ohaus

Amilum dengan Neraca Analitik

5,1420 g

6.2 Pembahasan Definisi massa adalah suatu sifat fisika dari suatu benda yang digunakan untuk menjelaskan berbagai perilaku objek yang terpantau. Dengan kata lain massa adalah ukuran banyaknya materi yang dikandung oleh suatu benda. Massa suatu benda dimanapun dinilai sama, oleh karena itu, massa tidak dipengaruhi oleh gravitasi bumi. Berbeda dengan berat yang merupakan gaya yang disebabkan karena adanya interaksi antara massa suatu benda dengan gaya gravitasi sehingga berat suatu benda tidak akan sama atau dapat berubah sesuai dengan besarnya percepatan gravitasi di tempat benda tersebut berada. Selain itu, massa merupakan besaran skalar yang tidak terpengaruh oleh arah lain halnya dengan berat yang merupakan besaran vektor. Sebagai seorang farmasis, pengukuran massa suatu bahan secara tepat sangatlah krusial dalam peracikan obat, hal ini disebabkan karena adanya dosis yang ingin dicapai namun tidak berlebihan. Dalam hal ini, pengukuran massa yang teliti menjadi tuntutan yang harus dipenuhi untuk mencapai keberhasilan terapi dari suatu obat sekaligus menghindari adanya efek yang tidak diinginkan karena kelebihan dosis dari obat tersebut. Pengukuran massa suatu bahan dapat dilakukan dengan menggunakan neraca, baik secara manual maupun digital. Dalam dunia farmasi neraca ohaus yang merupakan neraca manual sudah tidak asing lagi, neraca ini berfungsi sebagai penunjuk massa dengan membandingkan bahan yang ditimbang dengan anak timbangan yang diletakkan pada piringan neraca sesuai keperluan. Pada neraca ohaus tingkat ketelitiannya masih kurang akurat apabila dibandingkan neraca analitik yang merupakan neraca digital karena pada neraca digital tingkat kepekaan neraca lebih tinggi dengan display yang menunjukkan skala massa dari bahan yang ditimbang. Namun, baik pada neraca ohaus dan neraca digital dalam penggunaan Page | 8 Laporan Praktikum Fisika Farmasi

tetap

diperhatikan

dari

segi

kebersihannya,

hal

ini

dimaksudkan

untuk

meminimalisir kurangnya massa bahan yang ditimbang sehingga tidak sesuai dengan yang seharusnya. Selain itu, sebelum digunakan neraca harus dikalibrasi, yaitu telah diverifikasi secara akurasi bahwa neraca tersebut telah sesuai dengan rancangannya dan dalam kondisi yang baik, apabila suatu neraca telah dikalibrasi maka alat ukur ini ditempatkan pada suatu bidang datar yang posisinya tidak bergeser atau berubah untuk menjaga kesesuaian hasil. Pada praktikum ini, praktikan menimbang suatu bahan pada neraca ohaus yang kemudian ditimbang kembali pada neraca analitik untuk membandingkan ketelitian dalam penimbangan secara manual dan digital. Bahan yang digunakan adalah amilum manihot atau pati singkong. Amilum merupakan suatu senyawa organik yang tersebar luas pada kandungan tanaman. Amilum dihasilkan dari dalam daun-daun hijau sebagai wujud penyimpanan sementara dari produk fotosintesis. Amilum juga tersimpan dalam bahan makanan cadangan yang permanen untuk tanaman, dalam biji, jari-jari teras, kulit batang, akar tanaman menahun, dan umbi (Gunawan dan Sri Mulyani, 2004). Sebagai amilum normal, penggunaannya terbatas dalam industri farmasi. Hal ini disebabkan karakteristiknya yang tidak mendukung seperti daya alir yang kurang baik, tidak mempunyai sifat pengikat sehingga hanya digunakan sebagai pengisi tablet bagi bahan obat yang mempunyai daya alir baik atau sebagai musilago, bahan pengikat dalam pembuatan tablet cara granulasi basah (Anwar, 2004). Mula-mula alumunium foil yang berfungsi sebagai alas saat penimbangan ditimbang terlebih dahulu dengan menggunakan neraca analitik. Penimbangan ini dilakukan dengan menghubungkan neraca pada aliran listrik lalu memastikan piringan neraca dalam keadaan bersih dan skala menunjukkan angka nol (0). Kemudian alumunium foil tersebut diletakkan pada piringan neraca dan display skala menunjukkan massa alumunium foil yaitu 1,0923 gram. Selanjutnya alumunium dipindahkan pada piringan neraca ohaus lengan kanan yang kemudian pada piringan neraca lengan kiri ditambahkan anak timbangan 5 gram. Kemudian amilum manihot ditambahkan pada alumunium foil hingga massanya setara dengan anak timbangan pada lengan kiri, hal ini dipastikan dengan cara memutar tuas neraca sehingga kedua lengan terangkat dan dapat dilihat apakah telah setara atau belum. Apabila telah setara, alumunium foil yang berisi amilum manihot tersebut ditimbang kembali pada neraca analitik dengan prosedur yang sama. Hal ini dimaksudkan Page | 9 Laporan Praktikum Fisika Farmasi

untuk dapat membandingkan ketelitian praktikan saat menimbang menggunakan neraca ohaus. Saat ditimbang pada neraca analitik, massa alumunium foil beserta amilum manihot tersebut adalah 5,1420 gram, dari skala ini sangat terlihat bahwa praktikan tidak tepat menimbang 5 gram saat menggunakan neraca ohaus dan neraca ini pun tidak mencapai ketelitian dari neraca analitik namun skala tersebut tidak terlalu jauh dengan pembulatan desimal yang masih dalam batas massa 5 gram. Seperti yang telah disebutkan, seorang farmasis dituntut untuk teliti saat meracik suatu obat dan berkaitan dengan penimbangan dari suatu bahan yang berpengaruh pada dosis yang diinginkan meskipun menggunakan neraca manual seperti neraca ohaus tersebut.

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VII.

KESIMPULAN Massa adalah ukuran banyaknya materi yang dikandung oleh suatu benda. Massa suatu benda dimanapun dinilai sama, oleh karena itu, massa tidak dipengaruhi oleh gravitasi bumi. Massa termasuk suatu besaran yang merupakan sesuatu yang dapat diukur, mempunyai nilai yang dapat dinyatakan dengan angka-angka dan memiliki satuan tertentu. Sedangkan satuan adalah pernyataan yang menjelaskan arti dari suatu besaran. Pengukuran massa suatu bahan dapat dilakukan dengan menggunakan neraca, baik secara manual maupun digital. Pada neraca ohaus tingkat ketelitiannya masih kurang akurat apabila dibandingkan neraca analitik yang merupakan neraca digital karena pada neraca digital tingkat kepekaan neraca lebih tinggi dengan display yang menunjukkan skala massa dari bahan yang ditimbang. Pada praktikum ini, bahan ditimbang pada neraca ohaus yang kemudian ditimbang kembali pada neraca analitik untuk membandingkan ketelitian dalam penimbangan secara manual dan digital. Bahan yang digunakan adalah amilum manihot atau pati singkong. Mula-mula alumunium foil yang berfungsi sebagai alas saat penimbangan ditimbang terlebih dahulu dengan menggunakan neraca analitik dan diketahui massa alumunium foil yaitu 1,0923 gram. Selanjutnya alumunium dipindahkan pada piringan neraca ohaus kemudian amilum manihot ditambahkan pada alumunium foil hingga massanya setara dengan anak timbangan 5 gram. Namun, saat alumunium foil yang berisi amilum manihot tersebut ditimbang kembali pada neraca analitik massa alumunium foil beserta amilum manihot tersebut adalah 5,1420 gram, dari skala ini sangat terlihat bahwa praktikan tidak tepat menimbang 5 gram saat menggunakan neraca ohaus dan neraca ini pun tidak mencapai ketelitian dari neraca analitik namun skala tersebut tidak terlalu jauh dengan pembulatan desimal yang masih dalam batas massa 5 gram. Oleh karena itu, seorang farmasis dituntut untuk teliti saat meracik suatu obat dan berkaitan dengan penimbangan dari suatu bahan yang berpengaruh pada dosis yang diinginkan meskipun menggunakan neraca manual seperti neraca ohaus tersebut.

Page | 11 Laporan Praktikum Fisika Farmasi

VIII.

DAFTAR PUSTAKA Agoestia, N. (2012, Januari 29). Alat-Alat Laboratorium. Dipetik Januari 19, 2016, dari Blogspot: http://agoestiianeny.blogspot.co.id/ Anwar, E. (2004). Pemanfaatan Maltodekstrin Pati Terigu Sebagai Eksipien dalam Formula Sediaan tablet dan Niosom. Majalah Ilmu Kefarmasian, 34-36. Bahtiar, H. (2011). High Performance Liquid Chromatography (HPLC) dan Neraca Analitik. Bogor: Institut Pertanian Bogor. Day R.A. dan Underwood A.L. (2002). Analisis Kimia Kuantitatif Edisi 6. Jakarta: Erlangga. Gunawan dan Sri Mulyani. (2004). Ilmu Obat Alam (Farmakognosi) Jilid 1. Jakarta: Penebar Swadaya. JThorneBOT. (2015, Maret 10). Massa. Dipetik Januari 19, 2016, dari Wikipedia: http://id.m.wikipedia.org/ Melia. (2014). Laporan Praktikum Kimia Dasar. Pengenalan Neraca Di Laboratorium, 3. Putra, F. A. (2014, November 19). Alat Ukur Neraca. Dipetik Januari 19, 2016, dari WordPress: https://fauzanajiputra.wordpress.com/ Rully Bramasti dan Eko Sujatmiko. (2012). Fisika SMA/MA. Surakarta: Aksarra Sinergi Media. Sinko, P. J. (2006). Martin Farmasi Fisika dan Ilmu Farmasetika Edisi 5. Jakarta: EGC. Taiyeb. (2006). Pengenalan Alat Laboratorium. Makassar: Biologi FMIPA Universitas Negeri Makassar.

Page | 12 Laporan Praktikum Fisika Farmasi

4 Bahasa Asing Pilihan (Prancis)
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Nama Sekolah Bidang Keahlian Program Keahlian Kompetensi Keahlian Mata Pelajaran Durasi (Waktu) KI-3 (Pengetahuan)

KI-4 (Keterampilan

SILABUS MATA PELAJARAN : SMK ………………………………………………… : Pariwisata : Perhotelan dan Jasa Pariwisata : Usaha Perjalanan Wisata : Bahasa Asing Pilihan : 348 JP (@ 45 menit) : memahami, menerapkan, dan menganalisis pengetahuan faktual, konseptual, prosedural, dan metakognitif berdasarkan rasa ingin tahunya tentang ilmu pengetahuan, teknologi, seni, budaya, dan humaniora dengan wawasan kemanusiaan, kebangsaan, kenegaraan, dan peradaban terkait penyebab fenomena dan kejadian, serta menerapkan pengetahuan prosedural pada bidang kajian yang spesifik sesuai dengan bakat dan minatnya untuk memecahkan masalah : mengolah, menalar, dan menyaji dalam ranah konkret dan ranah abstrak terkait dengan pengembangan dari yang dipelajarinya di sekolah secara mandiri, bertindak secara efektif dan kreatif, serta mampu menggunakan metode sesuai kaidah keilmuan

Kompetensi Dasar 3 3.1 mendemonstrasikan tindak tutur untuk menyapa dan berpamitan (Saluer et prendre congé), mengucapkan terimakasih, dan meminta maaf (remercier et s’excuser) dengan memperhatikan fungsi sosial, struktur teks, dan unsur kebahasaan pada teks interpersonal dan teks transaksional tulis dan

Indikator Pencapaian Kompetensi 4 3.1.1 menirukan tindak tutur sesuai konteks 3.1.2 mengenali makna kata sesuai konteks 3.1.3 mengasosikan gambar dan tulisan yang tepat sesuai konteks 3.1.4 menentukan tidak tutur yang tepat sesuai konteks

MATERI POKOK 5 Unsur kebahasaan (1) Tu toiement (2) Vous voiement  Membaca : (1) Dialog sederhana tentang menyapa dan berpamitan, mengcapkan terimakasih, dan meminta maaf  Kosa kata : (1) Saluer: Salut,

Alokasi Waktu (JP) 44

Kegiatan Pembelajaran

Penilaian

6  Menyaksikan, menyimak, meniru, dan berpartisipasi dalam interaksi yang melibatkan tindakan memberi dan meminta informasi terkait materi dengan berfokus pada fungsi sosial, struktur teks, dan unsur kebahasaannya yang sesuai dengan konteks  Bertanya dan mempertanyakan hal-

7 Jenis penilaian: – Tugas individu – Tugas kelompok Bentuk: Lisan Tertulis TMT: membuat dialog

Kompetensi Dasar 3 lisan 4.1menerapkan tindak tutur untuk menyapa dan berpamitan (Saluer et prendre congé), mengucapkan terimakasih dan meminta maaf (remercier et s’excuser) dengan memperhatikan fungsi sosial, struktur teks, dan unsur kebahasaan pada teks interpersonal dan teks transaksional tulis dan lisan 3.2 mendemonstrasikan tindak tutur untuk memperkenalkan diri (se présenter) dengan memperhatikan fungsi sosial, struktur teks, dan unsur kebahasaan pada teks interpersonal dan teks transaksional tulis dan lisan 4.2 menerapkan tindak tutur untuk memperkenalkan diri (se présenter)

Indikator Pencapaian Kompetensi 4 4.1.1 menerapkan tindak tutur sesuai konteks dalam sebuah wacana tulis sederhana 4.1.2 menerapkan tindak tutur sesuai konteks dalam sebuah wacana lisan sederhana

3.2.1 mengenal makna kata sesuai konteks 3.2.2 memahami kata / kalimat sesuai konteks yang diberikan 3.2.3 mendemonstrasikan tindak tutur untuk memperkenalkan diri dengan bantuan gambar 4.2.1 membuat kalimat sederhana untuk memperkenalkan diri 4.2.2 menerapkan tindak

MATERI POKOK

Alokasi Waktu (JP)

5 Bonjour, Bonsoir, etc (2) Remercier: Merci, merci beaucoup, etc (3) Prendre congé: au revoir, salut, à bientôt, etc (4) S’excuser: pardon, Excusez-moi, etc

 Unsur kebahasaan (1) Pronom sujet “je”, “tu”, “vous” (2) Kata kerja “être”, “habiter”, “s’appeler”, “avoir”

 Membaca : (1)Teks sederhana tentang profil seseorang (2) Dialog sederhana 2

Kegiatan Pembelajaran 6 hal yang terkait dengan interaksi yang melibatkan tindakan memberi dan meminta informasi terkait tema dengan berfokus pada fungsi sosial, struktur teks, dan unsur kebahasaannya yang sesuai dengan konteks  Berlatih secara mandiri maupun dengan bimbingan guru untuk berinteraksi dalam memberi dan meminta informasi terkait tema dengan orang-orang di sekelilingnya. dengan berfokus pada fungsi sosial, struktur teks, dan unsur kebahasaannya yang sesuai dengan konteks  Mengidentifikasi persamaan dan perbedaan fungsi social, struktur teks, dan unsur kebahasaan terkait tema dalam konteks yang berbeda (dalam hal topik, moda, dan hubungan fungsional antar

Penilaian 7

Jenis penilaian: – Tugas individu – Tugas kelompok Bentuk: Lisan Tertulis

Kompetensi Dasar 3 dengan memperhatikan fungsi sosial, struktur teks, dan unsur kebahasaan pada teks interpersonal dan teks transaksional tulis dan lisan

3.3 mendemonstrasikan jam, hari, tanggal, bulan, tahun, (heure, jour, date, mois, année) dalam bentuk angka dan huruf dengan memperhatikan fungsi sosial, struktur teks, dan unsur kebahasaan pada teks interpersonal dan teks transaksional tulis dan lisan 4.3 Menerapkan tindak tutur untukmenyatakan dan menanyakan jam, hari,

Indikator Pencapaian MATERI POKOK Kompetensi 4 5 tutur memperkenalkan tentang diri sesuai konteks perkenalan dalam sebuah wacana tulis sederhana  Kosa kata : 4.2.3 menerapkan tindak (1) Nom : Pierre, tutur untuk Jean, Fabien, etc memperkenalkan diri (2) Les villes : Paris, sesuai konteks dalam Jakarta, etc sebuah wacana lisan (3) Les chiffres 1 – sederhana 100 (4) Les profession: lycéen(enne), professeur, acteur, actice, etc  Unsur 3.3.1 mengenal ungkapan kebahasaan: jam, hari, tanggal, (1)Demander et dire bulan, tahun l’heure 3.3.2 menirukan ungkapan (2)Demander et dire menyatakan jam, hari, la date,le mois, tanggal, bulan, tahun l’année 3.3.3 mengasosiasikan kata dengan gambar yang  Membaca tepat (1)Gambar jam 3.3.4 mengasosiasikan (2)Teks sederhana kalimat dengan tentang hari, gambar / konteks yang tanggal, bulan, tepat tahun 4.3.1 menentukan kalimat yang tepat untuk  Kosa kata menyatakan jam, hari, – Les mois : tanggal, bulan, tahun janvier, fevrier, 3

Alokasi Waktu (JP)

Kegiatan Pembelajaran 6 penutur)  Melakukan tindakan terkait tema dengan tujuan tertentu yang berfungsi dalam kehidupan di sekolah dan masyarakat.

Penilaian 7

Jenis penilaian: – Tugas individu – Tugas kelompok Bentuk: Lisan Tertulis TMT: membuat tabel / presentasi nama-nama hari, bulan

Kompetensi Dasar 3 tanggal, bulan, tahun, (heure, jour, date, mois, année) dalam bentuk angka dan huruf dengan memperhatikan fungsi sosial, struktur teks, dan unsur kebahasaan pada teks interpersonal dan teks transaksional tulis dan lisan

3.4 mendemonstrasikan tindak tutur untuk menyatakan jati diri (presenter son identité) dengan memperhatikan fungsi sosial, struktur teks, dan unsur kebahasaan pada teks interpersonal dan teks transaksional tulis dan lisan

Indikator Pencapaian Kompetensi 4 sesuai konteks 4.3.2 menerapkan kalimat yang tepat sesuai gambar/ konteks yang diberikan 4.3.3 menerapkan tindak tutur menyatakn dan menanykan jam, hari, tanggal, bulan, tahun sesuai konteks dalam sebuah wacana tulis sederhana 4.3.4 menerapkan tindak tutur untuk menyatakan dan menanyakan jam, hari, tanggal, bulan, tahun sesuai konteks dalam sebuah wacana lisan sederhana 3.4.1 menirukan tindak tutur untuk menyatakan jati diri 3.4.2 melengkapi kalimat dengan kata yang tepat sesuai konteks 3.4.3 mengasosiasikan gambar / profil seseorang (tokoh terkenal) dengan kalimat yang sesuai

MATERI POKOK

–

Alokasi Waktu (JP)

5 mars, etc Les jours de la semaine: lundi, mardi, mercredi, etc



Unsur kebahasaan: (1)Pronom sujet : “il” , “elle”, “ils”, elles” (2) Verbes : “être”, “habiter”, “avoir”  Membaca (1) Teks sederhana 4

Kegiatan Pembelajaran

Penilaian

Jenis penilaian: – Tugas individu – Tugas kelompok Bentuk: Lisan Tertulis

Kompetensi Dasar 3 4.4 menerapkan tindak tutur untuk menyatakan dan menanyakan jati diri dengan memperhatikan fungsi sosial, struktur teks, dan unsur kebahasaan pada teks interpersonal dan teks transaksional tulis dan lisan

3.5 menggolongkan nama benda dan bangunan publik (des choses et des lieux publics) dengan memperhatikan fungsi sosial, struktur teks, dan unsur kebahasaan pada teks interpersonal dan teks transaksional tulis dan lisan

Indikator Pencapaian Kompetensi 4

MATERI POKOK

Alokasi Waktu (JP)

5 tentang profil seseorang

Kegiatan Pembelajaran

Penilaian

4.4.1 membuat kalimat untuk memperkenalkan  Kosa kata seorang tokoh – Les professions 4.4.2 menerapkan tindak – Les adjectifs: tutur menyatakn dan petit(e), grand(e), menanykan jam, hari, beau, belle, etc tanggal, bulan, tahun sesuai konteks dalam sebuah wacana tulis sederhana 4.4.3 menerapkan tindak tutur untuk menyatakan dan menanyakan jam, hari, tanggal, bulan, tahun sesuai konteks dalam sebuah wacana lisan sederhana 3.5.1 menafsirkan makna kata sesuai konteks 3.5.2 mengasosikan gambar dan tulisan yang tepat sesuai konteks 3.5.3 menentukan artikel yang tepat untuk kata benda

43  Unsur kebahasaan (1)Adjectifs Possessifs (2)Les articles (3)Kata Tanya (4)Ucapan, tekanan kata, intonasi. (5)Ejaan dan tanda 5

 Menyaksikan, menyimak, meniru, dan berpartisipasi dalam interaksi yang melibatkan tindakan memberi dan meminta informasi terkait materi dengan berfokus pada fungsi sosial, struktur teks, dan unsur kebahasaannya yang

Jenis penilaian: – Tugas individu – Tugas kelompok Bentuk: Lisan Tertulis TMT:

Kompetensi Dasar 3 4.5 menerapkan tindak tutur untuk menyatakan dan menanyakan nama benda dan bangunan publik (des choses et des lieux publics) dengan memperhatikan fungsi sosial, struktur teks, dan unsur kebahasaan pada teks interpersonal dan teks transaksional tulis dan lisan

3.6 menggambarkan sifat orang dan benda (caractères de personnes et de choses) dengan memperhatikan fungsi sosial, struktur teks, dan unsur kebahasaan pada teks interpersonal dan teks transaksional tulis dan lisan

Indikator Pencapaian Kompetensi 4 4.5.1 menerapkan kata tanya yang tepat untuk menanyakan benda 4.5.2 membuat kalimat sederhana untuk menyebutkan nama benda dan mtempat publik

3.6.1 menafsirkan makna kata dengan bantuan gambar 3.6.2 menafsirkan makna kata dengan bantuan gesture 3.6.3 memahami kata / kalimat sesuai konteks yang diberikan 3.6.4 mendemonstrasikan sebuah kata sifat dengan bantuan

MATERI POKOK 5 baca.. (6)Kata kerja “aller”  Membaca : (1) Teks sederhana tentang benda dan tempat publik (2) Dialog sederhana tentang benda dan tempat publik  Kosa kata : (1)Vocabulaires à l’école ( un stylo, un livre, une gomme, etc) (2)Les places publics (la poste, la gare, le stade, la boulangerie, etc)  Unsur kebahasaan (1)Adjectifs caractères (phisiques et psicologiuques) (2)Kata kerja : “être” (3) Les accords (masculin >< féminin)

Alokasi Waktu (JP)

Kegiatan Pembelajaran

Penilaian

6 sesuai dengan konteks  Bertanya dan mempertanyakan halhal yang terkait dengan interaksi yang melibatkan tindakan memberi dan meminta informasi terkait tema dengan berfokus pada fungsi sosial, struktur teks, dan unsur kebahasaannya yang sesuai dengan konteks  Berlatih secara mandiri maupun dengan bimbingan guru untuk berinteraksi dalam memberi dan meminta informasi terkait tema dengan orang-orang di sekelilingnya. dengan berfokus pada fungsi sosial, struktur teks, dan unsur kebahasaannya yang sesuai dengan konteks  Mengidentifikasi persamaan dan perbedaan fungsi social, struktur teks, dan unsur kebahasaan

7 membuat dialog tentang benda dan bangunan publik sekitar

Jenis penilaian: – Tugas individu – Tugas kelompok Bentuk: Lisan Tertulis TMT:

Kompetensi Dasar 3 4.6 menerapkan tindak tutur untuk menyatakan dan menanyakan sifat orang dan benda (caractères de personnes et de choses) dengan memperhatikan fungsi sosial, struktur teks, dan unsur kebahasaan pada teks interpersonal dan teks transaksional tulis dan lisan

3.7 menafsirkan instruksi, tanda dan rambu (instructions, signes, panneaux) dengan memperhatikan fungsi sosial, struktur teks, dan unsur kebahasaan pada teks interpersonal dan teks transaksional tulis dan lisan 4.7 menetapkan instruksi,

Indikator Pencapaian Kompetensi 4 gambar / benda

MATERI POKOK

Alokasi Waktu (JP)

5  Membaca : (1) Teks sederhana tentang profil seseorang (2) Dialog sederhana tentang profil seseorang

4.6.1 menggunakan kata sifat yang tepat dalam sebuah kalimat 4.6.2 membuat kalimat sederhana untuk mendeskripsikan benda / seseorang Kosa kata : 4.6.3 membuat kalimat (1) Les adjectifs sederhana untuk caractères menanyakan sifat phisiques (grand, benda / seseorang petit, laid, carée, rectangle, etc) (2) Les adjectifs caractères psicologiques (timide, triste, contente, mechante, drôle, etc)  Unsur 3.7.1 menafsirkan makna kebahasaan: instruksi, tanda, dan (1) Impératif (positif, rambu dengan bantuan negatif) gambar (2) Infinitif 3.7.2 mengasosiasikan kata (3)La forme dengan gambar yang nominale tepat  Membaca (1) Gambar instruksi, tanda, 4.7.1 menentukan 7

Kegiatan Pembelajaran 6 terkait tema dalam konteks yang berbeda (dalam hal topik, moda, dan hubungan fungsional antar penutur)  Melakukan tindakan terkait tema dengan tujuan tertentu yang berfungsi dalam kehidupan di sekolah dan masyarakat.

Penilaian 7 membuat deskripsi tokoh idola TMTT : mengerjkan soal terkait film “Le Petit Nicolas)

Jenis penilaian: – Tugas individu – Tugas kelompok Bentuk: Lisan Tertulis

Kompetensi Dasar 3 tanda dan rambu (instruction, signes, panneaux) dengan memperhatikan fungsi sosial, struktur teks, dan unsur kebahasaan pada teks interpersonal dan teks transaksional tulis dan lisan 3.8 mendemonstrasikan lirik lagu (paroles d’une chanson) berbahasa Perancis dengan memperhatikan fungsi sosial, struktur teks, dan unsur kebahasaan

Indikator Pencapaian Kompetensi 4 instruksi yang tepat sesuai konteks yang diberikan 4.7.2 menggambar papan tanda / instruksi sesuai konteks yang diberikan 4.7.3 menerapkan instruksi ke dalam dialog sederhana 3.8.1 menirukan lirik lagu sederhana 3.8.2 mengucapkan lirik lagu dengan pengucapan yang tepat

MATERI POKOK

Alokasi Waktu (JP)

5 dan rambu 

Kosa kata Verbes: fumer, predre, marcher, faire, etc

Teks lagu sederhana berbahasa Prancis, misal: Hélène, Je ne veux pas travailler, La Seine, etc

Kegiatan Pembelajaran

Penilaian

7 TMT: membuat gambar instruksi dalam bahasa Prancis

Jenis penilaian: – Tugas individu – Tugas kelompok Bentuk: Lisan Tertulis

4.8 menggambarkan lirik lagu (paroles d’une chanson) berbahasa Perancis dengan memperhatikan fungsi sosial, struktur teks, dan unsur kebahasaan

4.8.1 menyanyikan kembali lirik lagu dengan pelafalan dan ekspresi yang tepat 4.8.2 menginterpretasi lirik lagu ke dalam bentuk puisi, dialog, atau bermain peran

TMT: pertunjukan lagu / puisi / drama sederhana dalam bahasa Prancis

CSC Data Interpretation and Analysis Reviewer

CSC Data Interpretation and Analysis Reviewer
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DATA INTERPRETATION AND ANALYSIS 1.

ANALYZING AND COMPUTING VALUES IN CHARTS AND FIGURES TIP:

UNDERSTAND AND INTERPRET DATA VALUES COMPARE USING SIMILAR UNITS

Note: Total Percentage = 100% Percentage formula = portion/total x 100 Percentage increase/decrease = (Current data – Initial Data)/Initial Data Average formula = summation of data points/total no. of data points Pie Graph: Personal Income (2004) PhP 1,249.9 billion

Unde r 25 ye a rs old, 11%

35-44 ye a rs

ove r 44 ye a rs

old, 20%

old, 45%

25-34 ye a rs old, 24%

In 2004, what was the approximate personal income, in billions of pesos, of the age group from 35-44 years: a. d. Answer:

180 280

b. e.

220 310

250

1,249.9 x 0.20 = 249.98

What is the ratio of the personal income of the group over 44 years of age to that of the age group from 35-44 years? a. d. Answer:

2:1 9:4

b. e.

3:2 4:9

45 : 20

45/5 = 9;

5:2

20/5 = 4

If the total personal income in 2004 was 20% greater than it was in 2003, what was the approximate income in 2003, in billions of pesos? a. d. Answer:

920 1040

b. e.

960 1100

1000

1,249.9 / 1.20 = 1041.58 [Percent increase = (current – past)/past x 100]

DATA LIST:

The list below shows the price of oranges at five different stores. Which stores offers the lowest price per oranges? Store A Store B Store C Store D Store E Answer:

: : : : :

99/5 = 25 per piece 100/3 = 200/12 = 40/2 =

5 pieces for P99 25 per piece 3 pieces for P100 P200 a dozen 2 pieces for 40 19.8 per piece 33.33 per piece 16.67 per piece 20 per piece

TABLE: Characteristics of University Students 1988 1992 1996

Gender: Male Female Courses: Tutorial Programs Entrance Tests Review Professional Advancement

2000

2004

550 450

686 714

720 780

920 1080

1150 1350

350 490 160

280 882 238

330 900 270

460 1160 380

575 1425 500

In what year did the female enrollees start to become more than half of the total enrollees? Answer:

female/total enrollees = 714/1400 = 0.51 (more than 51 percent)

In 1992, what fraction of the students are enrolled in tutorial programs? Answer:

tutorial/total enrollees = 280/1400 = 1/5

In 1988, what was the ratio of students enrolled in tutorial programs to those who enrolled in entrance tests review? Answer:

tutorial programs/entrance test review = 350/490 = 5/7

GRAPH: 150

100

A B C 2003

A BC 2004

A BC 2005

In 2004, the number of students of Branch C was approximately how many times of Branch A? Answer:

Twice

For the period shown on the graph, which of the following is true? a. b. c. d. e.

Only Branch B showed a steady rise in number of students. Branch A consistently had the lowest number of students. Only Branch A showed a steady rise in number of students Branch C consistently had the lowest number of students. Branch A and C had nearly the same number of students.

Kertas Kerja Terapi Mobiliti Dan Membeli Belah

Kertas Kerja Terapi Mobiliti Dan Membeli Belah
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SEKOLAH KEBANGSAAN BACHANG KM4. JALAN MALIM, 75250 MELAKA

KERTAS KERJA TERAPI MOBILITI DAN MEMBELI BELAH

TARIKH : 1 NOVEMBER 2018 HARI : KHAMIS TEMPAT : TERMINAL BAS MELAKA SENTRAL DAN MYDIN AYER KEROH MELAKA ANJURAN : PROGRAM PENDIDIKAN KHAS INTEGRASI MASALAH PEMBELAJARAN SEKOLAH KEBANGSAAN BACHANG

1.0 Pengenalan Terapi dalam Pendidikan Khas adalah salah satu kaedah untuk membantu seseorang murid untuk bergerak balas terhadap sesuatu aktiviti atau kemahiran. Ia bertujuan untuk membantu murid- murid berkeperluan khas dalam mencapai perkembangan dari segi kognitif, emosi, sosial dan psikomotor. Program ini adalah selaras dengan Akta Pendidikan 1996, Peraturan- peraturan (Pendidikan Khas) 1997 Bahagian II 3(2) yang menyatakan ‘guru- guru boleh mengubah suai kaedah atau teknik pengajaran dan pembelajaran, masa bagi aktiviti dan susunan aktiviti, mata pelajaran dan bahan bantu mengajar bagi mencapai tujuan dan matlamat Pendidikan Khas. Program ini akan memberi kesedaran kepada murid-murid bahawa mereka juga mempunyai potensi menjadi individu atau masyarakat yang cemerlang dalam kehidupan pada masa hadapan. Mereka haruslah diberi peluang dan pendedahan dalam aktiviti luar kerana ia bertujuan untuk mengeneralisasikan pelajar kearah kehidupan yang sebenar. Aktiviti luar ini juga merupakan sebahagian daripada komponen Pendidikan Jasmani dan Pengurusan Kehidupan di bawah bidang sosial, riadah dan kreativiti sebagaimana yang terdapat dalam Sukatan Pelajaran Pendidikan Khas Bermasalah Pembelajaran Sekolah Rendah dan turut digabungkan dengan komponen lain. Sebagai pelajar yang telah menjejaki kaki ke alam persekolahan, mereka akan mengalami krisis dan tekanan dalam kehidupan seharian. Di era globalisasi ini, menyukarkan pelajar bekeperluan khas membuat pertimbangan dan penyesuaian tanpa dibantu dan dibimbing iaitu ingin berdikari dalam apa jua bidang. Pada ketika ini, pelajar bekeperluan khas juga boleh berada dalam keadaan yang meragukan jika tidak dikawal. Justeru itu, pihak sekolah haruslah memainkan peranan yang penting dalam membantu remaja ini dimana yang baru melangkah ke sekolah untuk mengetahui perkembangan yang bakal dihadapi dalam membina masa depan yang cemerlang. Pelaksanaan program Pendidikan Khas memerlukan guru yang profesional dan berketerampilan dalam pelbagai aspek bagi menyahut cabaran pendidikan bertaraf dunia. Oleh itu, pengalaman sesebuah organisasi khususnya dalam bidang pendidikan khas amatlah penting untuk memberi pendedahan yang meluas dalam membentuk insan guru yang profesional, berkemahiran dan berpengetahuan luas. Di samping itu, program ini bertujuan untuk mendedahkan pelajar mengecapi pengalaman sebenar kepada guru-guru pelatih mengenai dunia Pendidikan Khas yang sebenar terutamanya dalam bidang terapi.

2.0 Rasional 2.1 Pelajar lebih berminat untuk mengikuti aktiviti luar yang dijalankan. 2.2 Pelajar dapat membina keyakinan diri. 2.3 Pelajar dapat menimba ilmu berkaitan persekitaran di luar bilik darjah. 2.4 Pelajar boleh berdikari semasa melakukan aktiviti. 2.5 Dapat meningkatkan kemahiran bersosialisasi para pelajar.

3.0 Matlamat Program ini diharapkan dapat membantu murid- murid berkeperluan khas meningkatkan nilai- nilai dalam aspek kehidupan serta meneruskan proses perkembangan diri yang lebih baik ke arah kedewasaan yang mantap dan memberikan pengalaman pembelajaran di luar bilik darjah yang menyeronokkan.

4.0 Modular Terapi Mobiliti dan Membeli Belah Bil

Mata Pelajaran/ Komponen

Bahasa Malaysia ( Tahun 1)

3.1

Mengecam persamaan

3.1.2

Mengecam persamaan bentuk

Bahasa Malaysia ( Tahun 3)

3.1

Membaca perkataan

3.1.1

Membaca perkataan

Bahasa Inggeris (Tahun 1)

1.4

Pupils will be able to understand and respond to oral text

1.4.1

Respon with YES or NO based on the stimulus given : picture

Bahasa Inggeris (Tahun 3) Matematik ( Tahun 1)

2.3

Menggunakan nombor dalam kehidupan harian

2.3.2

Membilang objek dalam persekitaran

Matematik ( Tahun 3)

4.4

Menyelesaikan masalah harian melibatkan nilai wang

4.4.1

Menyelesaikan masalah harian melibatkan nilai wang

Pendidikan Agama Islam (Tahun 1)

5.1

Memahami dan mengamalkan adab makan

5.1.4

Mengamalkan adab sebelum, semasa dan selepas makan.

Pendidikan Agama Islam (Tahun 3)

7.1

Adab kepada rakan

7.1.1

Pengurusan Diri (Tahun 1)

1.3

Adab makan dan minum.

1.3.4

Adab bergaul dengan rakan-rakan semasa melakukan aktiviti. Mengamalkan adab makan dan minum.

Pengurusan Diri (Tahun 3)

3.1

Menggunakan kemudahan tandas dan bilik mandi

3.1.2

Menjaga alatan di dalam tandas dan bilik air dengan selamat

Kemahiran Manipulatif (Tahun 1)

3.1

Pengamatan pendengaran

3.1.2

Mengecam bunyi seperti haiwan, kenderaan, alam semulajadi dan persekitaran

Kemahiran Manipulatif (Tahun 3)

1.3

Pergerakan motor halus kasar melalui gerakan

1.3.1

Pergerakan bebas dan terkawall

Standard Kurikulum

Standard Pembelajaran

5.0 Objektif 5.1 Menanam kemahiran berdikari dalam diri murid-murid ketika menghadapi situasi persekitaran luar. 5.2 Memupuk semangat kerjasama secara berpasukan dan bertanggungjawab terhadap ahli kumpulan. 5.3 Menambahkan pengetahuan dan kemahiran berkaitan dengan urusan jual beli. 5.4 Melahirkan murid yang dapat berinteraksi secara mesra dengan masyarakat sekeliling. 5.5 Membina keyakinan diri murid untuk menggunakan pengangkutan awam dan membiasakan diri untuk berada di tempat awam. 5.6 Mendidik jiwa dan tingkah laku yang sopan ketika menggunakan perkhidmatan awam.

5.0 Kumpulan Sasaran Pelajar Program Pendidikan Khas Integrasi, guru-guru dan pembantu pengurusan murid.

Bil

Perkara

Jumlah

Pelajar Kelas Pendidikan Khas 1 A

7 orang

Pelajar Kelas Pendidikan Khas 1 B

6 orang

Pelajar Kelas Pendidikan Khas 3

8 orang

Guru-Guru Pendidikan Khas

5 orang

Pembantu Pengurusan Murid

2 orang Jumlah

28 orang

6.0 Butiran Program Hari

: Khamis

Tarikh

: 1 November 2018

Masa

: 8.00 pg – 2.00 petang

Tempat : Terminal Bas Melaka Sentral dan Mydin Ayer Keroh Melaka

7.0 Pengangkutan Semua murid, guru dan pembantu pengurusan murid akan menaiki bas

8.0 Jawatankuasa Pelaksana Pengerusi

: En. Mohamad Bin Jaapar

(Guru Besar)

N. Pengerusi 1

: Pn. Siti Zariah Binti Zubir (GPK Kokurikulum)

N. Pengerusi 2

: Pn. Zaiton Binti Ahmad

N. Pengerusi 3

: En. Mohd Zahrol Bin Taha (GPK HEM)

(GPK Pentadbiran)

Penyelaras PPKI/ : Pn. Norashikin Binti Muhamad Setiausaha Bendahari

: Pn. Norisah Binti Hj Said

(Kebersihan)

AJK

: En. Izhar Raihan Bin Muhammad Yazid (Kecemasan) : Pn. Norhasikin Binti Tukimin Pn. Siti Mardiha Binti Shahari

(Makan dan Minum) (Senarai Alatan dan Gambar )

: Pn. Shanisah Binti Deraman

(Brosur)

: Cik Siti Naqibah Binti Baharim

(Jurugambar)

: Semua Guru ( Kawalan dan Disiplin Murid)

9.0 Tentatif Program

Masa

Aktiviti

7.30 pg

Murid berkumpul di sekolah dan bersarapan pagi RMT

8.00 pg

Bertolak ke Terminal Bas Melaka Sentral

8.15 pg

Menaiki bas ke Mydin Ayer Keroh Melaka

9.30 pg

Tiba di Mydin Murid-murid membeli belah mengikut senarai yang telah diberikan sambil diawasi oleh guru-guru dan ppm.

10.30 pg

Aktiviti bayaran di kaunter

11.00 pg

Aktiviti bebas di laman rehat Mydin

11.30 pg

Minum pagi di Mydin

12.15 t/h

Menaiki bas untuk pulang ke sekolah

1.30 ptg

Dijangka tiba di sekolah

10.0 Anggaran Perbelanjaan Bil 1

Perkara Pengangkutan (Bas

Kuantiti

Jumlah

1 buah

Percuma

RM 10

RM 10 X 21 orang

Catatan –

Panorama) 2

Makan tengahari

=RM 210 3

Pembelian alat tulis untuk tahun 2019

Pensil

RM 30 X 21

Pembaris

=RM 42 Kutipan

Pemadam Pengasah pensel

RM 630

daripada murid

Bekas pensel Pensel warna Gam

Wang saku

RM 10

RM 10 X 21 org =RM210

JUMLAH

RM 1050.00

* Pembayaran wang murid menggunakan elaun murid khas / sumbangan ibu bapa.

11.0 Penutup Akhir sekali, dengan kerjasama dan komitmen yang tidak berbelah bagi daripada semua pihak yang terlibat, adalah amat diharapkan semoga melalui program ini ianya akan dapat dilaksanakan dengan sempurna dan tercapai objektifnya. Diharapkan juga program ini dapat meransang murid untuk bergerak balas secara positif terhadap sesuatu kemahiran disamping mengukuhkan hubungan di antara pelajar, guru, PPM dan masyarakat luar.

Di sediakan oleh, ……………………………………………….. (NORASHIKIN BINTI MUHAMAD) Penyelaras PPKI, SK Bachang, Melaka

Di sokong oleh, ……………………………………………….. ( Siti Zariah Binti Zubir) GPK Kokurikulum, SK Bachang, Melaka

Diluluskan oleh, ……………………………………………….. (MOHAMAD BIN JAAPAR) Guru Besar, SK Bachang, Melaka

Busine ss Plan TUGAS MATA KULIAH KEWIRAUSAHAAN AL-KHAWARIZMI SOFTWARE TRAINING CENTER

Busine ss Plan TUGAS MATA KULIAH KEWIRAUSAHAAN AL-KHAWARIZMI SOFTWARE TRAINING CENTER
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Laporan Hasil Kegiatan Supervisi Fasilitatif
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Author/Uploader: Amalia Dwi Aryanti

LAPORAN HASIL KEGIATAN SUPERVISI FASILITATIF Tanggal : …. Juni 2021 Tempat : Pustu Curah malang Petugas : – Pengelola KIA –

Pengelola Gizi

–

Petugas Farmasi

–

Bangunan cukup memadai ,tapi pemanfaatan tiap ruang masih kurang Kebersihan ruangan cukup bersih Media konseling ada tapi kurang lengkap, ttg KIA. ABPK sudah ada,lembar balik ada Register kohort ibu ,bayi,dan balita kurang lengkap,mohon dilengkapi Capaian program KIA masih kurang ( KN,KF ) Pendokumentasian masih kurang Jumlah balita BGM 8 Anak balita,bumil KEK 5 sudah mendapatkan PMT,bumil KEK dan BGM harus sesuai dan pemantauan bumil KEK dan Balita gizi kurang di tingkatkan Tablet FE ketersediaan cukup Kantong persalinan sudah ada dan di isi. Peralatan emergensi sidah ada Grafik grafik sudah ada Alur pelayanan – papan informasi ruangan dibuat dan sudah ada Pelatihan – pelatihan banyak yang belum Dokumentasi resep obat,rasio pemberian obat, ditingkatkan Laporan obat ED Arsip pengeluaran/melidi obat sudah ada

Hasil :

–

Bidan koordinator KIA

SITI ERLINA STr.Keb

LAPORAN HASIL KEGIATAN SUPERVISI FASILITATIF Tanggal :

Maret 2020

Tempat : Polindes Talun kidul Petugas : – Pengelola KIA –

Pengelola Gizi Petugas Promosi Kesehatan

–

Bangunan cukup memadai ,tapi jumlah ruangan masih kurang untuk pelayanan Kebersihan ruangan cukup bersih Jadwal kegiatan sudah ada Media konseling ada tapi kurang lengkap,usulan media promkes ttg PHBS,POSBINDU,ISPA dan Diare. ABPK sudah ada,lembar balik ada Register kohort ibu ,bayi,dan balita kurang lengkap,mohon dilengkapi Kebutuhan kohort bayi,ibu,balita 5 pos Target imunisasi sdh UCI Bumil KEK dan BGM harus sesuai dan ditandai di register termasuk pemberian PMT Tablet FE ada yang ED,Fe ketersediaan cukup Kantong persalinan sudah ada dan di isi. Peralatan dan obat emergensi kurang lengkap,usulan bon di puskesmas Grafik grafikdan peta sasaran sudah ada Alur pelayanan – papan informasi ruangan dibuat dan sudah ada Pelatihan – pelatihan banyak yang belum

Hasil :

–

Bidan koordinator KIA

SITI ERLINA STr.Keb

LAPORAN HASIL KEGIATAN SUPERVISI FASILITATIF Tanggal :

Maret 2020

Tempat : Polindes Madiopuro Petugas : – Pengelola KIA –

Pengelola Gizi Petugas Promosi Kesehatan

–

Bangunan cukup memadai ,tapi pemanfaatan tiap ruang masih kurang Kebersihan ruangan cukup bersih Media konseling ada tapi kurang lengkap,usulan media promkes ttg PHBS,POSBINDU,ISPA dan Diare. Jadwal kegiatan sudah ada ABPK sudah ada,lembar balik ada Register kohort ibu ,bayi,dan balita kurang lengkap,mohon dilengkapi ,data harus sesuai dengan buku KIA sasaran Kebutuhan kohort bayi,ibu,balita masing2 butuh 4 . Target imunisasi sudah UCI dan IDL tercapai Bumil KEK dan BGM harus sesuai dan ditandai di register termasuk pemberian PMT harus masuk register. Tablet FE ada yang ED,Fe ketersediaan cukup Kantong persalinan sudah ada dan di isi. Peralatan dan obat emergensi kurang,usulan bon puskesmas Grafik grafik dan Peta sudah ada Alur pelayanan – papan informasi ruangan dibuat dan sudah ada Pelatihan –pelatihan banyak yang belum

Hasil :

–

Bidan koordinator KIA

SITI ERLINA STr.Keb

LAPORAN HASIL KEGIATAN SUPERVISI FASILITATIF Tanggal :

Maret 2020

Tempat : Ponkesdes Kendalsari Petugas : – Pengelola KIA –

Pengelola Gizi Petugas Promosi Kesehatan

–

Bangunan cukup memadai , pemanfaatan tiap ruang sudah sesuai Kebersihan ruangan cukup bersih Jadwal kegiatan sudah ada Media konseling ada tapi kurang lengkap,usulan media promkes ttg PHBS,POSBINDU,ISPA dan Diare. ABPK sudah ada,lembar balik ada Register kohort ibu ,bayi,dan balita kurang lengkap,mohon dilengkapi Kebutuhan kohort bayi,ibu,balita masing2 butuh 7 Target imunisasi sudah UCI Bumil KEK dan BGM harus sesuai dan ditandai di register termasuk pemberian PMT harus sesuai dengan buku KIA dan masuk diregister. Tablet FE ada yang ED,Fe ketersediaan cukup Kantong persalinan sudah ada dan di isi. Peralatan emergensi sidah ada lengkap Grafik grafik dan Peta sudah ada Alur pelayanan – papan informasi ruangan dibuat dan sudah ada

Hasil :

–

Bidan koordinator KIA

SITI ERLINA STr.Keb

LAPORAN HASIL KEGIATAN SUPERVISI FASILITATIF Tanggal : Maret 2020 Tempat : PUSTU Curahmalang Petugas : – Pengelola KIA –

Pengelola Gizi Petugas Promosi Kesehatan

–

Bangunan cukup memadai ,tapi pemanfaatan tiap ruangan masih kurang Kebersihan ruangan cukup bersih,tapi ruang agak lembab Jadwal kegiatan belum terpasang Media konseling ada tapi kurang lengkap,usulan media promkes ttg PHBS,POSBINDU,ISPA dan Diare. ABPK sudah ada,lembar balik ada Register kohort ibu ,bayi,dan balita kurang lengkap,mohon dilengkapi Kebutuhan kohort bayi,ibu,balita masing2 butuh 8. Target imunisasi sudah UCI Bumil KEK dan balita BGM harus sesuai dengan buku KIA dan ditandai di register termasuk pemberian PMT juga harus masuk. Tablet FE ada yang ED,Fe ketersediaan cukup Kantong persalinan sudah ada dan di isi. Peralatan dan obat emergensi masih kurang,saran bon Puskesmas Buku kunjungan akseptor sudah ada. Grafik grafik dan Peta sudah ada Alur pelayanan – papan informasi ruangan dibuat dan sudah ada Pelatihan pelatihan masih banyak yang belum.

Hasil :

–

Bidan koordinator KIA

SITI ERLINA STr.Keb

Test Practic Excel – 10
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Test practic Excel – cls. 10

Cerințe: În foaia de calcul Angajați 1: 1 – Realizează înghețarea rândului de sus și a primelor două coloane. 2 – Afișează salariul angajaților în lei. 3 – Data angajării să fie de tipul zi lună an (exemplu: 3 februarie 2020).

(0,5 p) (0,5 p) (1 p)

În foaia de calcul Angajați 2: 4 – Filtrează tabelul astfel încât să fie vizibili doar angajații care au salarii cuprinse între 10000 și 12000 de lei. (1p) În foaia de calcul Angajați 3: 5 – Identifică duplicatele de la CNP-uri. 6 – Afișează bare de date pe coloana Vechime.

(1 p) (1 p)

În foaia de calcul Angajați 4: 7 – Sortați tabelul după două criterii: descendent, după vechime și ascendent, după nume. (1 p) 8 – Vechimea angajaților să fie afișată cu o singură zecimală (1 p)

În foaia de calcul comp_x: 9 – Anulați bordurile celulelor rândului 2 al foii de calcul. (0,5 p) 10 – Mutați conținutul rândului 2 pe rândul 15 al aceleiași foi de calcul. (0,5 p) 11 – Redimensionați rândurile 4 și 5 la 250 puncte. (0,5 p) 12 – Pentru grupul de celule A4:D5, activați încadrarea textului (Wrap Text) fără modificarea lățimii celulelor sau a dimensiunii fontului. (0,5 p)

Timp de lucru: 30 de minute.

Se acordă 1 punct din oficiu.

Soal Lingkaran Kelas Viii
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UTS KELAS VIII 1 . Perhatikan gambar Daerah yang diarsir disebut … a. juring b. tembereng c. apotema d. diameter 2. Keliling lingkaran yang berjari-jari 14 cm… a. 88 cm c. 154 cm b. 132 cm d. 308 cm

3. Jari-jari lingkaran yang memiliki keliling 132 cm adalah… a. 7 cm b. 10,5 cm c. 14 cm d. 21 cm 4. Suatu lingkaran berjari-jari 7 cm, maka luas lingkaran tersebut adalah…(π=22/7) a. 308 cm2 b. 154 cm2 c. 44 cm2 d. 22 cm2 5. Sebuah roda berjari-jari 25 cm. Untuk menempuh jarak sejauh 157 meter, maka roda harus berputar sebanyak… a. 50 kali b. 100 kali c. 110 kali d. 120 kali 6. Perbandingan luas dua lingkaran yang memiliki keliling masing-masing 12 cm dan 15 cm adalah… a. 4 : 5 b. 8 : 15 c. 9 : 16 d. 16 : 25 7. Luas daerah yang diarsir pada gambar adalah… a. 157 cm2 b. 196,25 cm2 c. 228 cm2 d. 235,5 cm2

10 cm

20 C M

30 C M

Keliling daerah yang diarsir pada gambar di samping (π=3,14) adalah.. a. 122,8 cm b. 114 cm c. 108,5 cm d. 91,4 cm

Gambar di samping adalah bagian dari lingkaran yang berjari-jari 10 cm. Jika π=3,14, maka keliling daerah yang diarsir adalah… a. 82,8 cm b. 67,1 cm c. 61,1 cm

47,1 cm

10.

O 7cm B A

Perhatikan gambar! Jika panjang busur AB=5,5 cm, dan П= 22/7, maka besar sudut AOB adalah… a. b. c. d.

300 450 600 900

11. Perhatikan gambar di samping Jika luas juring COD 80 cm2, maka luas juring BOC adalah a. 60 cm2 b. 50 cm2 c. 45 cm2 A d. 40 cm2

12.

C o 72

13.

C O

100 A

14.

60o

C B

Jika AB adalah diameter dan panjang busur BC 12 cm, maka panjang busur AC = a. 25 cm b. 21 cm c. 18 cm d. 16 CM

Pada gambar di samping, jika besar sudut BOC= 100 0, maka besar sudut OAC adalah… a. 25o b. 50o c. 75o d. 80o .

Jika besar sudut OCB 65 o, maka besar sudut AOC

C O

65 A

adalah… a. 50o b. 65o c. 70o d. 130o

A C

Jika besar sudut AOC = 70o, maka besar ABC adalah… a. 35o b. 70o c. 105o d. 140o

15.

16.

Pada gambar di samping, AC adalah diameter, besar sudut AOB adalah 45o Jika panjang OA =7cm, maka luas juring OBC adalah…

cm2

b. 59 cm2 c.

59 cm2

d. 57 cm2 17.

F 45

102

o 98

o 35

o C

Berdasarkan gambar di samping, terdapat pasangan busur sebagai berikut: i. Busur AB dan busur EF ii. Busur AF dan busur CD iii. Busur BC dan busur ED iv. Busur AB dan busur ED Pasangan busur di atas yang sama panjang adalah… a. i dan iii b. ii dan iv c. i dan iii d. ii dan iv

18. Pada gambar di samping, diketahui sudut AOB = 120o dan sudut COD = 72o, jika luas juring OCD = 12,8 cm2, maka luas juring OAB adalah… a. 15,8 cm2 b. 19,6 cm2 c. 21,3 cm2 d. 25,6 cm2

O A

19.

Dari gambar di samping, besar sudut CAO = 2xo, besar sudut ABC = 3xo, maka besar sudut ADC = …. a. 30o b. 48o c. 54o d. 60o

2xo

3x 0

o B

20.

r O

Dari gambar di atas, jika panjang OQ = 5 cm dan OP = 13 cm, maka panjang PQ adalah… a. 8cm b. 9 cm c. 10 cm d. 12 cm 21. jika panjang AC = 8 cm, dan AB = 17 cm, maka luas layang-layang ACBD adalah… C a. 60 cm2 2 b. 68 cm c. 120 cm2 d. 180 cm2 A B

D 22. Untuk melukis lingkaran dalam sebuah segitiga, maka terlebih dulu kita harus membuat…. a. Garis tinggi segitiga b. garis bagi segitiga c. garis singgung persekutuan luar d. garis singgung persekutuan dalam

23. Dua buah lingkaran berjari-jari masing-masing 13 cm dan 5 cm. Jika jarak kedua pusat lingkaran sama dengan 17 cm, maka panjang garis persekutuan luar kedua lingkaran tersebut adalah… a. 15 cm b. 13 cm c. 12 cm d. 8 cm 24. P

B Q

Pada gambar di samping, jika panjang PQ = 20 cm, maka jarak AB adalah… a. 12 cm b. 21 cm c. 24 cm d. 25 cm

25.

Lingkaran A dan B bersinggungan dan berjari-jari sama. Jika panjang jari-jari kedua lingkaran adalah 5 cm, dan π= 3,14, maka panjang lilitan tali minimum adalah… a. 51,4 cm b. 41,4 cm c. 35,7 cm d. 25,7 cm

Progetto Solaio in Cemento Armato
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LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B prof. Renato Giannini

Progetto delle armature longitudinali del solaio (arch. Lorena Sguerri) Correzioni del diagramma di momento flettente Prescrizioni di normativa specifiche per il solaio Progetto delle armature longitudinali di un travetto Diagramma dei momenti resistenti Lunghezze di ancoraggio Disegno dei ferri longitudinali di un travetto

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Diagrammi di taglio e momento del solaio 1.80

5.00

4.00

Qd2

Qd1 Pd1

6.00

Pd2 Fd A 1.80

B 5.00

1.00

5.00

27.45 kN m

A 25.60 kN

C 4.00

21.20 kN m

13.11 kN m

13.84 kN m

25.69 kN 16.65 kN

A 1.80

B 5.00

C 4.00

A -27.31 kN

B -25.30 kN

Nel caso specifico i diagrammi di taglio e momento costituiscono l’inviluppo dei diagrammi relativi alle quattro combinazioni di carico

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Correzioni sul diagramma di inviluppo dei Momenti La cerniera di estremità della trave continua, a momento nullo, rappresenta nella realtà un vincolo di semi-incastro il cui momento è tutt’altro che nullo. Per questo motivo, si -(P +Q ) x L /24 aggiunge fuori calcolo un momento negativo C che può essere calcolato A B considerando la campata Q d1 /2 come una trave Pd1 /2 incastrata e caricata con la metà del carico B C complessivo LBC (permanente + variabile) d1

-[(Pd1+Qd1)/2] x LBC /12

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Correzioni sul diagramma di inviluppo dei Momenti Per quanto riguarda l’esempio, il valore del momento negativo “aggiunto” in corrispondenza della cerniera C sarà: MC = -(Pd1+Qd1) · L2BC/24 = -(7.00 + 3) · 42/24 = -6.70 kN·m Per tracciare il tratto di diagramma che interessa si può ricorrere alla legge di variazione del momento per la trave incastrata con carico uniformemente distribuito pari a (Pd1+Qd1)/2 27.45 kN m

21.20 kN m 6.70 kN m

13.11 kN m

13.84 kN m

0.85

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Correzioni sul diagramma di inviluppo dei Momenti M(x) = MC + [(Pd1+Qd1) · LBC /4] · x – [(Pd1+Qd1)/2] · x2/2 Inserendo i valori noti e risolvendo l’equazione di 2° grado in x, si ottiene l’ascissa in corrispondenza della quale il momento flettente si annulla: M(x) = -6.70 + [(7+3) · 4 /4] · x – [(7+3)/2] · x2/2 M(x) = -6.70 + 10 · x – 2.5 · x2

3.148 m

⇒

x= 0.852 m 2

-[(Pd1+Qd1)/2] x LBC /12

C 3.148 0.852

0.852

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Prescrizioni di normativa per le armature longitudinali dei solai La normativa (D.M. 09/01/96, par.7) fornisce alcune indicazioni sul pre-dimensionamento minimo delle armature longitudinali di un solaio: Si deve disporre agli appoggi dei solai (quindi in corrispondenza delle travi) un’armatura inferiore, convenientemente ancorata, in grado di assorbire, allo stato limite ultimo, uno sforzo di trazione pari al taglio di calcolo: Afmin = Td / fyd (cm2) L’armatura (inferiore) deve essere sempre superiore a: Afmin ≥ 0.07 H cm2 al metro ove H è l’altezza del solaio espressa in centimetri

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Regole pratiche per il progetto delle armature longitudinali dei solai La non perfetta coincidenza del modello “trave continua” con la realtà, richiede cautela nella progettazione dei ferri longitudinali del solaio: non si è tenuto conto, ad esempio, che la trave non è un appoggio fisso, ma un appoggio elastico. Possono verificarsi, quindi, dei cedimenti differenziali tra un vincolo e l’altro con conseguente variazione del diagramma dei momenti, rispetto a quello di calcolo, lungo l’asse principale del solaio. Per questo motivo è buona norma progettare le armature longitudinali inferiori in campata per un valore del momento non inferiore a (Pd+Qd) · L2/16. L’area di armatura minima quindi sarà calcolata seguendo il seguente criterio: Afmin(in campata) funzione di: max [Md ; (Pd+Qd) · L2/16] con Md = momento di calcolo

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Regole pratiche per il progetto delle armature longitudinali dei solai La prescrizione di normativa Afmin ≥ 0.07 H cm2 al metro obbliga a disporre almeno un ferro corrente inferiore lungo tutto il travetto. In campata, se serve, viene disposto anche un ferro aggiuntivo. Il numero dei ferri inferiori non deve essere superiore a 2. I ferri superiori, in corrispondenza degli appoggi, vengono disposti solo dove servono: in campata, dove il momento è positivo, i ferri superiori possono anche non esserci. I valori di calcolo dei armatura superiore diagrammi di taglio e momento soletta collaborante s H sono stati ricavati per una striscia pignatta h di solaio larga 1 metro, quindi i travetto armatura inferiore valori delle sollecitazioni sono b b b i relativi a due travetti o

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Progetto delle armature longitudinali del travetto I dati del solaio riportato nell’esempio sono: H = 20/16 cm ; d’ = 2 cm ; d = 18/14 cm (app.A) I dati dell’acciaio e le aree dei tondini sono: FeB44k

⇒

fyk = 430 Mpa

⇒

fyd = 37.4 kN/ cm2

Af cm2

1φ8

0.5

1 φ 10

0.79

4 cm 4 cm

1 φ 12

1.13

16 cm

1 φ 14

1.54

1 φ 16

2.01

1 φ 18

2.54

1 φ 20

3.14

pavimento in ceramica

10 cm

40 cm 50 cm 100 cm

massetto

10 cm

intonaco

20 cm

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Progetto delle armature longitudinali del travetto 27.45 kN m

25.60 kN

21.20 kN m

25.69 kN 16.65 kN

6.70 kN m

13.11 kN m

13.84 kN m

0.85

Md PL2 Sez kN cm 16

Td kN

Md 0.9 d fyd

-27.31 kN

Td fyd

-25.30 kN

0.07 H

Afmin x 0.5

Af,eff cm2

ABinf 1311 1563

2.57 cm2

1.4 cm2 1.29 cm2 2φ10

1.58

BCinf 1384 1000

2.28 cm2

1.4 cm2 1.14 cm2 2φ10

1.58

Asup

2745

5.82 cm2

2.91 cm2 3φ12

3.39

Bsup

2120

3.49 cm2

1.75 cm2

Csup

670

1.11 cm2

0.56 cm2 1φ10

d = 14 cm

1φ12 1.92 1φ10 0.79

Ainf

27.31

0.73 cm2 1.4 cm2 0.7 cm2

1φ10

0.79

Binf

25.69

0.69 cm2 1.4 cm2 0.7 cm2

1φ10

0.79

Cinf

16.65

0.45 cm2 1.4 cm2 0.7 cm2

1φ10

0.79

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Momento resistente di una sezione Una volta aver trasformato le aree di ferro minimo in tondini, è necessario stabilire la disposizione dei ferri, dove interromperli, dove aggiungerli ecc… Questa operazione può essere svolta graficamente attraverso il diagramma dei momenti resistenti: Il momento resistente Mr (φ) relativo ad una sezione armata con un certo quantitativo Aeff di armatura, può essere calcolato, in via approssimativa, invertendo la formula semplificata con cui vengono calcolati i quantitativi minimi di armatura: Afmin = Md /(0.9·d ·fyd)

⇓ Mr(φ) = Aeff · 0.9 · d · fyd

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Diagramma dei momenti resistenti di una sezione Mr(1φ10) = 0.79 · 0.9 · 18 · 37.4 = 478.64 kN · cm 1 373 kN cm

1 060 kN cm 3 35 kN cm

0 M r(1 φ 10)

6 56 kN cm

1φ 10

6 92 kN cm

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Diagramma dei momenti resistenti di una sezione Mr(2φ10) = 1.58 · 0.9 · 18 · 37.4 = 957.28 kN · cm 1 373 kN cm

1 060 kN cm 3 35 kN cm

0 M r(1 φ 10) M r(2 φ 10)

1 φ10 1φ 10

1φ10

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Diagramma dei momenti resistenti di una sezione

1 373 kN cm

1 060 kN cm 3 35 kN cm

0 M r(1 φ 10) M r(2 φ 10)

1 φ10 1φ 10

1φ10

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Diagramma dei momenti resistenti di una sezione Mr(1φ10) = 0.79 · 0.9 · 18 · 37.4 = 478.64 kN · cm 1 373 kN cm

1 060 kN cm Mr (1 φ10)

0 M r(1 φ 10) M r(2 φ 10)

1 φ10 1 φ10 1φ 10

1φ 10 1φ10

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Diagramma dei momenti resistenti di una sezione Mr(1φ12+ 1φ10) = 1.92 · 0.9 · 18 · 37.4 = 1163.29 kN · cm 1 373 kN cm

Mr (1 φ12+1 φ 10) Mr (1 φ10)

0 M r(1 φ 10) M r(2 φ 10)

1 φ12 1 φ10 1 φ10 1φ 10

1φ 10 1φ10

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Diagramma dei momenti resistenti di una sezione Mr(1φ12) = 1.13 · 0.9 · 14 · 37.4 = 532.5 kN · cm Mr(2φ12) = 2.26 · 0.9 · 14 · 37.4 = 1065 kN · cm Mr(3φ12) = 3.39 · 0.9 · 14 · 37.4 = 1597.5 kN · cm M r(3 φ 12) d=14 M r(2 φ 12) d=14

Mr (1 φ12+1 φ

M r(1 φ 12) d=14

Mr (1 φ10)

0 M r(1 φ 10) M r(2 φ 10)

1 φ12 1 φ12

1 φ12

1 φ10

1φ12 1 φ10 1φ 10

1φ 10 1φ10

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Diagramma dei momenti resistenti di una sezione

M r(3 φ 12) d=14 M r(2 φ 12) d=14

Mr (1 φ12+1 φ

M r(1 φ 12) d=14

Mr (1 φ10)

0 M r(1 φ 10) M r(2 φ 10)

1 φ12 1 φ12

1 φ12

1 φ10

1φ12 1 φ10 1φ 10

1φ 10 1φ10

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Lunghezze di ancoraggio I ferri devono essere convenientemente ancorati. Senza ricorrere, per il momento, alla normativa che fornisce una formula precisa per calcolare la lunghezza di ancoraggio in funzione del diametro del tondino, si assuma forfettariamente Lb = 40 · φ M r(3 φ 12) d=14

Mr (1 φ12+1 φ

M r(2 φ 12) d=14

Mr (1 φ10)

M r(1 φ 12) d=14 0 M r(1 φ 10) M r(2 φ 10)

A 48 48

48 48

40 40

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Disegno dei ferri: soluzione 1 I ferri devono essere disegnati sotto ad una sezione longitudinale, in scala 1:50, del travetto specificando il diametro dei tondini e le lunghezze dei ferri. I ferri non possono avere lunghezza superiore ai 12 metri

1 φ12 1 φ12

155 cm 280 cm

1 φ12

450 cm 1 φ10

1 φ12

220 cm

1 φ10

355 cm

260 cm 1φ 10

1091 cm

1φ10

1φ 10

150 cm

280 cm 16

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Disegno dei ferri: soluzione 2

Un ferro continuo può essere spezzato in più tratti ricorrendo ad un’adeguata sovrapposizione (80φ = 40φ + 40φ): • I ferri inferiori possono essere spezzati in corrispondenza degli appoggi (momento positivo nullo) • I ferri superiori possono essere spezzati in campata (momento negativo nullo)

1 φ12

155 cm

1 φ12

280 cm

1 φ12

450 cm 1 φ10

1 φ10

260 cm

718 cm

1 φ12

220 cm

1 φ10

595 cm

16 1φ 10 1φ10

320 cm 453 cm

16 16

LABORATORIO DI COSTRUZIONE DELL’ARCHITETTURA 2B

Esecutivo del solaio L’esecutivo comprende: – una sezione longitudinale in scala 1:50, quotata. – Il disegno dei ferri, del loro quantitativo, del diametro e delle lunghezze – alcune sezioni trasversali significative in scala 1:10 con indicate le dimensioni e i relativi ferri.

Catholic Vicar Apostolic of The Mountain Province v. CA

Catholic Vicar Apostolic of The Mountain Province v. CA
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CATHOLIC VICAR APOSTOLIC OF THE MOUNTAIN PROVINCE v. COURT OF APPEALS, HEIRS OF EGMIDIO OCTAVIANO AND JUAN VALDEZ G.R. No. 80294-95 September 21, 1988 Gancayco, J. [Loo, Lissa Marie G.] FACTS: The Catholic Vicar Apostolic of the Mountain Province (VICAR for brevity) filed with the Court of First Instance of Baguio Benguet an application for registration of title over Lots 1, 2, 3, and 4 in Psu-194357, situated at Poblacion Central, La Trinidad, Benguet, said Lots being the sites of the Catholic Church building, convents, high school building, school gymnasium, school dormitories, social hall, stonewalls, etc. The Heirs of Juan Valdez and the Heirs of Egmidio Octaviano filed their Answer/ Opposition on Lots Nos. 2 and 3, respectively, asserting ownership and title thereto. After trial on the merits, the land registration court promulgated its Decision confirming the registrable title of VICAR to Lots 1, 2, 3, and 4. The Court of Appeals rendered its decision reversing the decision of the land registration court and dismissing the VICARʼs application as to Lots 2 and 3, the lots claimed by the two sets of oppositors in the land registration case (and two sets of plaintiffs in the two cases now at bar), the first lot being presently occupied by the convent and the second by the womenʼs dormitory and the sisterʼs convent. The plaintiffs argue that the defendant Vicar is barred from setting up the defense of ownership and/or long and continuous possession of the two lots in question since this is barred by prior judgment of the Court of Appeals under the principle of res judicata. Plaintiffs contend that the question of possession and ownership have already been determined by the Court of Appeals and affirmed by the Supreme Court. Defendant Vicar maintains that the principle of res judicata would not prevent them from litigating the issues of long possession and ownership because the dispositive portion of the prior merely dismissed their application for registration and titling of lots 2 and 3. Defendant Vicar contends that only the dispositive portion of the decision, and not its body, is the controlling pronouncement of the Court of Appeals

ISSUE: May the decision of the Court of Appeals promulgated a long time ago can properly be considered res judicata by respondent Court of Appeals in the present two cases between petitioner and two private respondents? HELD: Yes. Petitioner was in possession as borrower in commodatum up to 1951, when it repudiated the trust by declaring the properties in its name for taxation purposes. When petitioner applied for registration of Lots 2 and 3 in 1962, it had been in possession in the concept of an owner only for eleven years. Ordinary acquisitive prescription requires possession for ten years, but always with just title. Extraordinary acquisitive prescription requires 30 years. Petitioner did not meet the requirement of 30 years possession for acquisitive prescription over Lots 2 and 3. Neither did it satisfy the requirement of 10 years possession for ordinary acquisitive prescription because of the absence of just title. The appellate court did not believe the findings of the trial court that Lot 2 was acquired from Juan Valdez by purchase and Lot 3 was acquired also by purchase from Egmidio Octaviano by petitioner Vicar because there was absolutely no documentary evidence to support the same and the alleged purchases were never mentioned in the application for registration. Respondent appellate court did not commit any reversible error, much less grave abuse of discretion, when it held that the Decision of the Court of Appeals is governing, under the principle of res judicata, hence the rule, in the present cases CA-G.R. No. 05148 and CA-G.R. No. 05149. The facts as supported by evidence established in that decision may no longer be altered.

Law of Taxation (16B162)
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Gujarat National Law University, Gandhinagar, (2019-20)

A Research Paper on OFFENCES LIABLE TO PROSECUTION – a Critique Submitted by Supervisor –

Faculty

Subham Agarwal(16B162) Prabhavati Baskey,

Mrs.

Semester – VII [B.BA. LL.B. (Hons.)] Assistant Professor of Law (Batch: 2016-21)

This Research paper is submitted for the partial fulfilment of the academic requirements for the Subject ‘Law of Taxation – 1’.

1|Page

INDEX S.

Topic

Page

No. 1

Acknowledgement

No. 03

List of Abbreviations

 Introduction

 Concept of Mens Rea

 Various Offences Liable to Prosecution

5 6

2|Page

06-13

 Proceedings before income tax authorities

 Limitation for initiation of proceedings Conclusion

14 15

Bibliography

16-17

ACKNOWLEDGEMENT I express my profound gratitude to our supervisor Mrs. Prabhavati Baskey,

Assistant

Professor

Law,

Gujarat

National

Law

University, for her expert, sincere and valuable guidance and constant encouragement extended to me. I salute her perseverance for perfection and diligence for quality which enabled me to carry out the work with utmost precision. I wish to express my sincere thanks to Dr. S. Shanthakumar, Director,

Gujarat

National

Law

University,

Gandhinagar

for

providing me with all the necessary facilities. I express my indebtedness towards my parents who always have been my source of inspiration. My role models, my parents have been our lifetime trainers. They have continuously fuelled zeal and enthusiasm to achieve new milestones in our life. I dedicate this work to them.

3|Page

LIST OF ABBREVIATIONS

Abbreviation

Full Form

and

03rd

Third

ACIT

Assistant Commissioner of Income Tax Article

Art.

CIT

Bachelor of Business Administration and Bachelor of Law Commissioner of Income Tax

Del

Delhi

Dr.

Doctor

etc.

Et cetra

Income Tax

ITAT

Income Tax Appellate Tribunal

ITD

Income Tax Department

ITO

Income Tax Officer

ITR

Income Tax Reporters

Ltd.

Limited

Mum

Mumbai

No.

Number

Pvt.

Private

Serial

TDS

Tax Deducted at Source

versus

Versus

versus

B.B.A. LL.B.

4|Page

INTRODUCTION The Income Tax Law contains several provisions providing for prosecutions for acts committed by any taxpayer. There are various acts for which a taxpayer can be prosecuted apart levying of penalties for defaults. Under the I.T Act, 1961, there are several provisions which calls for compliance with taxing provisions and tax collections. The I.T Act objects to enforce compliance of taxation in a three fold manner:(a) Imposition of Interests, (b) Imposition of Penalties and, (c) Prosecutions.1 Chapter XXII of the Income Tax Act, 1961, deals with the offences and prosecution proceedings. However, under no circumstances, the Act deals with the procedures which regulates the prosecution. Such procedures are regulated by the provision of CrPC (Criminal Procedure Code), 19732. The provisions of such Code are to be read for all the offences committed under the I.T Act. The Central Government has been given the ultimate power to establish Special Courts after consulting the Chief Justices of the jurisdictional High Courts. Under normal circumstances, the Magistrate Court in whose jurisdiction the offence took place, tries the offence. In cases of direct tax, the jurisdiction of the offence is said to be at the place where submission of false returns took place. In J. K Synthetics Ltd. v. ITO, 3 the Court observed that any offence committed under Section 277, can be tried only at such place where the false statement had been delivered. All India Federation of Tax Practitioners accessed 01 October 2019 2 Criminal procedure Code, 1973 3 J. K Synthetics Ltd. v. ITO (1987) 168 ITR 467 (Delhi) (HC) 1

5|Page

In Babita Lila v. UOI,4 the Court held that any First Class Magistrate or a Metropolitan Magistrate, shall try the prosecution proceedings under the direct taxes. If any notification has been given related to Special Economic offences Court, then the complaint must be filed before that specific court.

CONCEPT OF MENS REA The concept of mens rea has always been an integral part of criminal jurisprudence. An offence cannot be said to be committed without any intention. The golden rule in criminal jurisprudence has evolved over the years and today, the concept of “innocent until proven guilty” stands. However, the Taxation Laws has carved out an exception to the said rule. The Section 278E places the burden upon the accused to prove the absence of mens rea, and that also shall be proved beyond reasonable doubt. In Prakash Nath Khanna v. CIT,

the Court has opined that the

Court has to mandatorily presume that culpable mental state exists, and absence of such mental status can only be pleaded by the accused in terms of his own defense. In J. Tewari v. UOI,6 evidence

the Court has observed that the law of presumptions

culpability

does

not

differentiate between a juristic person and a natural person in any circumstance and that the court itself will presume whether the culpable state of mind exists or not.

VARIOUS OFFENCES LIABLE TO PROSECUTION There are various offences under the Income Tax Act, 1961 , which is liable to prosecution. Such offences have been explained as following:-

4 5 6

Babita Lila v. UOI (2016) 387 ITR 305 (SC) Prakash Nath Khanna v. CIT (2004) 266 ITR 1 (SC) (12) J. Tewari v. UOI, (1997) 225 ITR 858 (Cal.) (HC) (861)

6|Page

Wilful attempt to evade tax, interest or penalty If any person wilfully attempts to evade any kind of tax, interest or penalty or hides his income, then prosecution proceedings shall be intitated against such evader under Section 276-C.7 Actions and/or activities wherein an individual or business entity avoids payment of their tax liability, either partly or fully is/are known as tax evasion. A few examples of tax evasion are: (a) Non-payment of taxes (b) Under-payment of taxes (c) Concealment of assets to reduce/understate tax liability.8 Section 271 AAB9 further specifies the penalties under different scenarios viz., : a. In

case

the

Assessee

confesses/admits

the

undisclosed income, a 10% penalty on the undisclosed income along with the interest shall be levied. b. In case the Assessee does not confess/admit to the undisclosed income but reports of such income in the Income Tax Return furnished in the Previous Year, a 20% penalty on the undisclosed income along with the interest shall be levied. c. If case the Assessee does not disclose the amount and it is

found

out

enquiry/investigation,

the a

Department penalty

upon

ranging

further from

Income Tax Act, 1961, Section 276 Paisa Bazaar, accessed October 2019 9 Income Tax Act, 1961, Section 271

7 8

7|Page

minimum 30% to a maximum 90% on the undisclosed amount shall be levied.10 In K.C Builder v. ACIT,11 the court opined that when any penalty stands cancelled, the prosecution under Section 276C for evasion of tax canoot be initiated thereafter. In ITO v. Nandlal and Co.,12 the court passed a judgment that when any order for penalty is set aside, the prosecution initiated for willful evasion of tax also does not survive.

Dealing with Seized Assets Section 13213 deals with removing, parting or otherwise dealing with seized assets. It gives power to the tax authorities to begin with search proceedings at the taxpayer’s premises. While the search is in process, the authorities also have the power to seize jewellery, bullion, money or any other valuable article found at the premises. In the normal course, any valuable thing found or seized by the tax authorities, must be kept in their custody, i.e. in the Government’s custody. In case it is not possible for the authorities to keep possession of the valuables or store it in a safe place due to its characteristic such as volume, weight, or it being in a dangerous state. The Second Proviso to Section 132(1) also empowers the authorities to take charge of the asset by storing the asset at the taxpayer’s place only. In those cases, the asset will still be called to be ‘seized’ by the authorities. The Authorized officer needs to serve an order on the person with immediate possession or the owner of the seized assets, that under no circumstances, any part of the asset will be Paisa Bazaar, accessed October 2019 11 K.C Builder v. ACIT (2004) 265 ITR 562 (SC) 12 ITO v. Nandlal and Co. (2012) 341 ITR 510 (SC) 13 Income Tax Act, 1961, Section 132 10

8|Page

moved or dealt with. Any movement in the asset would require permission of the officer. Such actions performed by the Officer will be covered under the Income Tax Act. Sometimes, it might not be practicable to seize any documents, books of accounts, money, jewellery, or any other valuable article for other reasons than mentioned in the second proviso to 132(1). Similarly, in these cases, the authorities may serve an order on the person with immediate possession or the owner that he shall not part with, remove or deal with the valuables. Any transaction can be made only with prior permission of thee officer. In cases of non- compliance with this section, the person will be charged under Section 275A,14 which calls for prosecution.

Provision of necessary facility for insoection of books and oter documents In case the person-in-charge fails to provide necessary facility to the authorities conducting search to inspect documents and books of accounts, shall be punishable with rigorous imprisonment and fine under Section 275B.

Dealing with the Property in order to prevent tax recovery If any person, who is eligible to pay tax, defaults in discharging himself from the tax liability, then the tax authority is empowered to recover the dues from him. Recovery can be made by attaching his immovable and movable property. If the taxpayer intends to fraudulently remove, transfer, conceal or delivery any property to any other person, thereby trying to evade the authorities and prevent the property from being attached for recovery, would be 14

Income Tax Act, 1961, Section 275

9|Page

liable an prosecution proceedings have to be initiated against him under Section 27615.

Failure by the Liquidator of a Company Section 178(1)16 mandates that every person, who has been appointed a liquidator of any company or receiver of any assets of the company, shall give notice of his appointment to the tax authority within 30 days of him becoming the liquidator. Section 178(3) provides that no liquidator can part or deal with any assets of the Company unless notified by the Assessing Officer. The liquidator, on being notified, shall ensure to set aside the amount equal to the notified amount, and unless he does so, he shall not deal with any other assets of the Company. Under no circumstances, the liquidator can be debarred from dealing with the assets or purpose of tax payment by the company or for making any kind of payment to the secured creditors. Section 276A calls for prosecution in the case of failure to serve a notice or in setting aside the given sum in compliance with the provisions. Prosecution proceedings can also be initiated in case the liquidator deals with any assets or property of the Company in contrary to the provisions.

Payment of TDS or DDT to the Government’s credit A person is liable to be prosecuted with rigorous imprisonment and fine under 276B, if he/she fails to pay :(a) The tax deducted at source, (b) Dividend Distribution Tax, 15 16

Income Tax Act, 1961, Section 276 Income Tax Act, 1961, Section 178

10 | P a g e

Payment of the tax collected Section 206C17 of the Income Tax Act, governs the provisions related to collection of tax at source. If any person fails to pay the tax to the Government’s credit, then he/she shall be prosecuted and fined as per Section 276BB.

Furnishing of return of income A person wilfully failing to furnish his return of income is also liable to prosecution under the Act. Such person wil be prosecuted under Section 276CC. A person is liable to furnish his return of income or respond to notice under 142(1)(i). Failing to comply will result in attracting Section 276CC18. Nevertheless, the taxpayer cannot be prosecuted for failure to furnish his return of income in duetime:(a) When the return is filed before the expiry of the assessment year, (b) When the tax payable on the income determined on regular assessment does not exceed Rs. 10,000.

Production of documents and accounts or compliance with the direction issued

17 18

Income Tax Act, 1961, Section 206 Income Tax Act, 1961, Section 276

11 | P a g e

Any taxpayer is liable to prosecution under the Income Tax Act, if he/she wilfully fails to produce documents and accounts under Section 142(1)19 or fails to comply with any direction issued under 142(2A). Section 142(1) deals with the provisions relating to the inquries conducted before assessment. Under such section, the Assessing Officer can serve a notice on the taxpayer asking him/her to file the return of income, in case of failure to file or produce such documents or books of accounts. On the other hand Section 142(2A) provides for special audit. Accordingly, if the conditions mentioned in this Section is not satisfied, then the Assessing Officer may serve an order to the taxpayer to get his/her accounts audited from a Chartered Accountant, who shall be nominated by the Chief Commissioner or Principal Chief Commissioner, and to also furnish such report of audit in the prescribed manner. Section 276D of the Income Tax Act says that in cases of taxpayers wilfully failing to produce such accounts and documents or comply with such directions, are liable for prosecution.

Delivery of False Statement Any taxpayer who has made any statement for any verification under the Income Tax Act or has delivered any account or statement which he knows is false or believes to be false, shall be charged with prosecution under Section 27720 of the Act.

Enable any other person to evade any kind of tax, interest or penalty 19 20

Income Tax Act, 1961, Section 142 Income Tax Act, 1961, Section 277

12 | P a g e

If any person wilfully intends to enable or abet any other person to evade any kind of tax, nterest or penalty, or causes to make any false entry or statement and which is also known to be false to that person, then that person shall be liable for prosecution under Section 277A.

Abetment of false account, return, etc. If any person induces or abets any other person to deliver a false statement, declaration or an account related to any income, which is chargeable to tax, and which is also known to be false or believes to be not true, then such person is said to commit an offence under Section 276C(1) and shall be prosecuted under Section 278. Abetment can be committed in mainy three ways; By instigation, by conspiracy or by intentional aid. In order to establish abetment, it must be proved that the abettor has intentionally aided the commission of crime. Intentional aid and complicity are the main ingredients of the offence of abetment. In Shri Ram v. State of Uttar Pradesh,21 it was held that a man can be held guilty for abetting even if the offence has not been committed. To prove abetment, it is not necessary that the offence must have taken place. In Faunga Nath v. State of Uttar Pradesh,22 the court held that a person can be convicted for abetment, even when the alleged person has been acquitted. In Jamuna Singh v. State of Bihar,23 the Court opined that when a Tribunal sets aside the Assessing Officer’s order , the Complaint

21 22 23

Shri Ram v. State of Uttar Pradesh, 1975 SCC (3) 495 Faunga Nath v. State of Uttar Pradesh, AIR 1959 SC 673 Jamuna Singh v. State of Bihar, AIR 1967 SC 553

13 | P a g e

which has been filed for abetment is quashed. Such stance was also taken by the court in Smt. Sheela Gupta v. IAC.24

Disclosure of particulars by Public Servants Under the I.T Act, Section 138(1) talks about the disclosure of information by the authorities to other authority, officers, etc. Whereas Section 138(2) puts a restriction on declaration of information by public servants. In case the public servants fails to comply with Section 138(2), he/she is liable to prosecution under Section 280.

Offences by a Company. I.T Act also provides for offences committed by any Company. According to Section 278B, if any offence has been committed by a Company, then, every person who was incharge and responsible for the conduct of the Company at the time of offence, shall be liable for the offence and proceedings shall be initiated against them accordingly. If the person held for the offence is able to prove that the offence was committed without his prior knowledge or that he took all steps to prevent commission of such offence, then the person shall not be held guilty for that offence. When there is an offence committed by a Company, under the Income Tax Act, and it has been proved that the offence committed with the consent of, or due to neglect of any director, secretary, manager or any other officer of the Company, then, that person shall be held guilty and proceedings shall be initiated against him.

Smt. Sheela Gupta v. IAC (2002) 253 ITR 551 (Delhi) (HC)

14 | P a g e

In Dhrupadi Devi (Smt.) v. State of Rajasthan,25 the Court observed that the criminal liability of any partner cannot be thrusted upon his/her legal heirs. In ITO v. Kamra Trading Co.,26 the Court took a stance that initiating prosecution proceedings against the sleeping partner is bad in law for failure in tax payment.

Offences by a Hindu Unidivided Family Under the Section 278C of I.T Act, any offence committed by a Hindu Undivided Family, then in such circumstances, the Karta shall be held guilty of that particular offence and proceedings shall be initiated against him. Nevertheless, if the Karta is able to prove that the offence has been committed without his knowledge or that he had already exercised all due diligence to prevent the commission of that offence. When there is an offence committed by a Hindu Undivided Family, under the Income Tax Act, and it has been proved that the offence committed with the consent of, or due to neglect of any member of the Hindu undivided Family, then, that person shall be held guilty and proceedings shall be initiated against him. In Roshan Lal v. Special Chief Magistrate, 27 the Court opined that any member of the Hindu Undivided family shall not be held liabe for delayed filing of returns, even though he has participated in the assessment proceedings.

25 26 27

Devi (Smt.) v. State of Rajasthan (2001) 106 Comp. Cas 90 (Raj.) (HC) 93 ITO v. Kamra Trading Co. (2004) 267 ITR 170 (P&H) (HC) Roshan Lal v. Special Chief Magistrate, (2010) 322 ITR 353 (All.) (HC)

15 | P a g e

PROCEEDINGS

BEFORE

INCOME

TAX

AUTHORITIES Section 13628 of the Income Tax Act provides that such proceedings initiated under this Act shall be covered under the meaning of judicial proceedings in Section 193 and for Section 196 of the IPC. 29 Nevertheless all proceedings under this Act cannot be covered under the meaning of judicial proceedings. In KTS Mohammed v. UOI,30 the Court opined that the Officer cannot initiate prosecution for perjury in proceedings under FERA. Also, if any assessee gives any false evidence, then that assessee would be liable for prosecution under 193 of IPC, 1860.

LIMITATION FOR INITIATION OF PROCEEDINGS Chapter XXXVI of the CrPC,31 has laid down the limitation period. No court can take any cognizance of any offence beyond the limitation period. Such offence should be punishable with fine only or imprisonment which does not exceed three years. In Friends Oil Mills & ors. v. ITO,32 the Hon’ble Court observed that the limitation bar prescribed under the Section 468 of CrPC, would not be applicable to prosecution under the I.T Act. In lieu of this, there does not exist any fixed limitation period for initiation of proceedings.

28 29 30 31 32

Income Tax Act, 1961, Section 136 Indian Penal Code, 1860, Section 196 KTS Mohammed v. UOI, (1992) 197 ITR 196 (SC) Code of Criminal Procedure, 1973 Friends Oil Mills & ors. v. ITO, (1977) 106 ITR 571 (Ker.) (HC)

16 | P a g e

In Gajanand v. State (1986),33 the High Court was of the opinion that in cases where the proceedings have proceeded for more than twelve years and still, the department of Income tax has not produced the evidence, then in such cases, the prosecution proceedings shall be quashed. In State of Maharashtra v. Natwarlal Damodardas,34 the High Court held that while mitigating the sentence, any kind of delay and other circumstances must be taken into consideration.

CONCLUSION It is very important for the tax consultants to guide the assesses to comply with the rules and regulations of the Act and also adopt a much needed and better tax management services to stay in the liability free zone. It has never been advisabke to enter into tax avoidance

schemes

order

evade

tax

payment

the

Government. No person shall try to escape the laws of the land. The Tax administration is well equipped with technology and systems, which can easily get hold of the tax invaders. There has been various suggestions by the Comptoller and Auditor General of India for better analysis and administration of proceedings. The CBDT tries to ensure that the public faces no issue in paying the taxes and also setting up a proper mechanism so that no person can evade tax.

33 34

Gajanand v. State (1986) 159 ITR 101 (Pat) (HC) State of Maharashtra v. Natwarlal Damodardas AIR 1980 SC 593

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BIBLIOGRAPHY 

All

India

Federation

Tax

Practitioners

accessed 01 October 2019  Babita Lila v. UOI (2016) 387 ITR 305 (SC)  Code of Criminal Procedure, 1973  Criminal procedure Code, 1973  Devi (Smt.) v. State of Rajasthan (2001) 106 Comp. Cas 90 (Raj.) (HC) 93  Faunga Nath v. State of Uttar Pradesh, AIR 1959 SC 673  Friends Oil Mills & ors. v. ITO, (1977) 106 ITR 571 (Ker.) (HC)  Gajanand v. State (1986) 159 ITR 101 (Pat) (HC)  Income Tax Act, 1961, Section 132  Income Tax Act, 1961, Section 136  Income Tax Act, 1961, Section 142  Income Tax Act, 1961, Section 178  Income Tax Act, 1961, Section 206  Income Tax Act, 1961, Section 271  Income Tax Act, 1961, Section 275  Income Tax Act, 1961, Section 276  Income Tax Act, 1961, Section 276  Income Tax Act, 1961, Section 276  Income Tax Act, 1961, Section 277  Indian Penal Code, 1860, Section 196  ITO v. Kamra Trading Co. (2004) 267 ITR 170 (P&H) (HC)  ITO v. Nandlal and Co. (2012) 341 ITR 510 (SC)  J. K Synthetics Ltd. v. ITO (1987) 168 ITR 467 (Delhi) (HC)  J. Tewari v. UOI, (1997) 225 ITR 858 (Cal.) (HC) (861)  Jamuna Singh v. State of Bihar, AIR 1967 SC 553  K.C Builder v. ACIT (2004) 265 ITR 562 (SC)  KTS Mohammed v. UOI, (1992) 197 ITR 196 (SC) 18 | P a g e

 Paisa

Bazaar, accessed 2 October 2019  Paisa

Bazaar, accessed 2 October 2019  Prakash Nath Khanna v. CIT (2004) 266 ITR 1 (SC) (12)  Roshan Lal v. Special Chief Magistrate, (2010) 322 ITR 353 (All.) (HC)  Shri Ram v. State of Uttar Pradesh, 1975 SCC (3) 495  Smt. Sheela Gupta v. IAC (2002) 253 ITR 551 (Delhi) (HC) 

State of Maharashtra v. Natwarlal Damodardas AIR 1980 SC 593

19 | P a g e

Organsko Vocarstvo PDF
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PROIZVODNJA VOĆA U ORGANSKOJ POLJOPRIVREDI Miodrag Leković

Podgorica 2011

Autor: dipl. ing. agr. Miodrag Leković Stručna konsultantkinja: dr Gordana Šebek

SADRŽAJ

Izdavač: Program razvoja organske poljoprivrede u Crnoj Gori Lektura i korektura: doc. dr Ljiljana Pajović-Dujović Dizajn i priprema za štampu: EXPEDITIO Naslovna fotografija: © Sylvie Bouchard – Fotolia.com Štampa: AP Print, Podgorica Tiraž: 500

Uvod

Izbor položaja

Podgorica 2011.

Klima Zemljište Lokacija

Organizacija mješovitog proizvodnog zasada

Sistemi gajenja u organskom voćarastvu

Podizanje organskog voćnjaka

Obrada zemljišta u organskom voćnjaku

12 14 17 21

Obrada zone ispod krošnji Sendvič sistem Zastiranje (malčovanje)

Dubrenje

Ministarstvo poljoprivrede i ruralnog razvoja

UNIVERZITET CRNE CRNE GORE UNIVERZITET GORE BIOTEHNIČKI FAKULTET BIOTEHNIČKI FAKULTET

Kompost Formiranje kompostne hrpe

Navodnjavanje

Zaštita od korova u organskom voćnjaku

Plitka obrada zemljišta Malčovanje (zastiranje zemljišta) Solarizacija Kultivacija plamenom

Zaštita od bolesti i štetočina

Berba

Uvod u organsku rasadničku proizvodnju

Jabuka

Najčešće bolesti i mjere zaštite Najčešće štetočine i mjere zaštite

Kruška

Najčešće bolesti i mjere zaštite Najčešće štetočine i mjere zaštite

Malina

Najčešće bolesti i mjere zaštite Najčešće štetočine i mjere zaštite

Maslina

Izbor lokacije za organski rasadnik Priprema zemljišta Obrada zemljišta prije sadnje podloga Sadnja podloga Đubrenje u rasadniku Navodnjavanje u rasadniku Redovna kontrola bolesti i štetočina Kontrola korova u rasadniku Kvalitet sadnica

Najčešće bolesti i mjere zaštite Najčešće štetočine i mjere zaštite

Recepti za preparate

Literatura

PRILOG: kalendar radova PROI Z V O D N J A V O Ć A U O R G A N S K O J P O L J O P R I V R E D I

UVOD Koliko god termin „organska poljoprivreda“ zvučao novo, ipak kao koncept, ali i kao ustaljena praksa, postoji još od tridesetih godina prošlog vijeka. Ocem organske poljoprivrede smatra se Sir Albert Howard, britanski botaničar koji je svoj život posvetio proučavanju i promovisanju ideje razvoja poljoprivrede, uz očuvanje prirode i korišćenje prirodnih zakona. Od osamdesetih godina prošlog vijeka ovaj sektor poljoprivrede bilježi konstantan rast, gledano na nivou Evropske unije. Novija istraživanja govore da se svjetsko tržište organskih proizvoda, od 2002. do 2005. godine uvećalo za 43%, a da se, na nivou EU, uvećava za 10 do 15% svake godine. Evropa i Sjeverna Amerika su najveći proizvođači i potrošači organske hrane, a činjenica je da proizvodnja još nije dostigla potrošnju. To utiče i na forimiranje cijena organske hrane, koja je skuplja, u prosjeku, za 10 do 20% od konvencionalno proizvedene.

Time ova grana poljoprivredne proizvodnje postaje sve atraktivnija za proizvođače, pa se evropski farmeri sve češće odlučuju za organsku poljoprivredu kao perspektivu koja će im donijeti profit, ali i druge benefite kao što je čistija okolina, manje otpada, zdravstveno bezbjednija hrana i sigurnije tržište. U prilog ovome govori podatak da udio organske proizvodnje u cjelokupnoj poljoprivredi Danske iznosi 5 %, Švedske 3 %, Njemačke 2,6 %, Holandije 1,8 %, a Francuske 1,3%, kao i da se konstantno uvećava. U Crnoj Gori organska poljoprivreda takođe bilježi rast. Potporu ovom trendu predstavlja Zakon o organskoj poljoprivredi donešen 2004. godine, kao i osnivanje nacionalnog sertifikacionog tijela Monteorganica, čija je uloga sertifikacija i kontrola organskih farmera u skladu sa pomenutim zakonom. Ideja donosilaca ovog pravnog akta je da se pokušaju

Program razvoja organske poljoprivrede u Cr noj Gori

pratiti navedeni svjetski i evropski trendovi, da se na najbolji način iskoriste prirodni i proizvodni resursi, da se slabost, u vidu usitnjenih poljoprivrednih površina i malih proizvodnih kapaciteta, pretvori u prednost, kao i da se zaštite, uobliče i prilagode poljoprivredne prakse, duboko utemeljene u našoj tradiciji. Sve je to u cilju jačanja poljoprivrednog sektora, ali i prilika malim proizvođačima da proizvode kvalitetnu hranu i da kroz njen plasman ostvare značajniju ekonomsku dobit. Kada se ima u vidu da će uvođenje navedenih praksi voditi očuvanju i razvoju prirodnih resursa, jasno je da se organska poljoprivreda postavlja kao osnova ekonomskog razvoja turističke i ekološke Crne Gore.

Želja autora ovog priručnika jeste da približi ideju organske poljoprivrede proizvođačima koji u tom sektoru vide svoju budućnost i čija je vizija proizvodnja ukusnog i zdravstveno bezbjednog proizvoda koji će lakše naći put do potrošača, koji su, evidentno je, sve izbirljiviji. Priručnik je napravljen sa nastojanjem da se proizvođačima predoči činjenica da organska proizvodnja ne znači ne raditi ništa u voćnjaku i pustiti ga da se sam bori protiv bolesti i štetočina. Naprotiv, biti organski proizvođač znači biti stalno u voćnjaku, primijetiti i pratiti sve promjene na stablima, a i oko njih, poznavati osnovne osobine štetočina i izazivača bolesti, znati kako izbjeći štete, ali i kako reagovati ako se problemi pojave. Jedino na taj način organska proizvodnja voća može biti održiva i konkurentna, a proizvođaču može donijeti sigurnu prodaju i veći profit.

PROI Z V O D N J A V O Ć A U O R G A N S K O J P O L J O P R I V R E D I

IZBOR POLOŽAJA Izbor položaja budućeg voćnjaka od izuzetnog je značaja u organskom voćarstvu. Termin „položaj“ objedinjuje faktore proizvodnje koji su veoma usko povezani: klimu, zemljište i lokaciju. Ekonomija organske proizvodnje voća u velikoj mjeri zavisi od izbora položaja. Kako je u organskom voćarstvu veoma ograničena upotreba sredstava za zaštitu, pravilan izbor položaja voćnjaka je od neprocjenjivog značaja za preventivu bolesti i štetočina. Da bi se postigla ekonomski uspješna proizvodnja, faktori proizvodnje moraju odgovarati specifičnim zahtjevima voćnih vrsta i sorti. Dakle, najvažniji preduslov za uspješnu organsku proizvodnju voća jeste pravilan izbor voćne vrste i sorte spram proizvodnih uslova na izabranoj lokaciji. Bilo bi besmisleno pokušati sa zasnivanjem komercijalne organske proizvodnje u području gdje su nepovoljni uslovi. Ako postoje samo manji nedostaci,

treba razmotriti mogućnosti i isplativost njihovog otklanjanja. U svakom slučaju, prije osnivanja organskog voćnjaka ili konverzije postojećeg u organski, potrebno je konsultovati Savjetodavnu službu u biljnoj proizvodnji.

Klima Klima je od fundamentalnog značaja u određivanju koja se voćna vrsta i sorta može uspješno gajiti u određenom području. Najznačajniji klimatski faktori su: o t emperatura (minimalne i maksimalne godišnje temperature, broj dana sa srednjim dnevnim temperaturama iznad +5 °C, suma srednjih dnevnih temperatura tokom vegetacionog perioda, opasnost od mrazeva …); o padavine (suma godišnjih padavina, intenzitet padavina, raspored tokom vegetacione sezone, pojava grada …);

Program razvoja organske poljoprivrede u Cr noj Gori

o svjetlost (broj sunčanih sati tokom vegetacije).

ovome će biti više riječi u poglavlju Obrada zemljišta u organskom voćnjaku.

Zemljište

Lokacija

Plodno, drenirano zemljište odgovarajuće dubine i vodnovazdušnog kapaciteta, bogato korisnim zemljišnim organizmima, preduslov je za razvoj zdravih voćki, posebno u godinama sa izraženim klimatskim pojavama, kakve su suše, veoma visoke temperature ili intenzivne padavine. Ustaljeni sistemi održavanja zemljišta, kao što je stalna obrada, dovode do sabijanja zemljišta, a time do smanjenja kapaciteta za razvoj korijena, smanjenja nivoa kiseonika, prezasićenja vodom tokom dugotrajnih padavina, erozije, ubrzane mineralizacije organske materije i smanjenja sadržaja humusa, odumiranje zemljišne mikrofaune i do niza drugih negativnih pojava. Plodno zemljište sadrži 50 % čvrstih materija (organskih i mineralnih), 50 % pora (od čega je pola ispunjeno vodom, a druga polovina vazduhom), kao i aktivnu mikro floru i faunu. To se u organskom voćarstvu postiže redukovanom obradom, upotrebom organskih đubriva i biološkim metodama zaštite od korova. O

Izbor lokacije, tačnije, podrazumijeva uticaj nadmorske visine, nagiba, orIjentacije, okolnih uzvišenja, šuma, objekata i dr. na osnovne klimatske proizvodne uslove.

i štetočina, povećana opasnost od mrazeva zbog zadržavanja hladnog vazduha.

visokih objekata ili šuma, dok se optimalnim lokacijama smatraju blage padine (5 do 10 % nagiba) okrenute jugu;

Zaklonjena lokacija

Zaklonjena lokacija je najbolji izbor, posebno ako je zaklonjena (objektima, šumom …) sa sjeveroistočne strane, a otvorena prema jugozapadu.

Osnovni tipovi lokacija Otvorena lokacija − prednosti: provjetrenost smanjuje pojavu bolesti i štetočina, brže je sušenje zemljišta i lišća nakon obilnijih padavina; − mane: mehanički uticaj vjetra (lome se grane, isušuje se žig tučka cvijeta, otpadaju cvjetovi i plodovi, vjetar ometa pčele prilikom oprašivanja …), pretjerano isušivanje vazduha i zemljišta tokom sušnog perioda. Zatvorena lokacija − prednosti: spriječen je negativan mehanički uticaj vjetra, spriječeno je pretjerano isušivanje tokom sušnog dijela godine; − mane: učestalost pojave bolesti

PROI Z V O D N J A V O Ć A U O R G A N S K O J P O L J O P R I V R E D I

Kriterijumi za izbor lokacije o Rizik od mrazeva – treba izbjegavati potpuno zatvorene lokacije i doline okružene padinama da bi se izbjegli kasni proljećni ili rani jesenji mrazevi; o Insolacija (osunčanost) – voćnjak se ne smije podizati u sijenci

o Vjetar – već su pomenuti pozitivni i negativni uticaji vjetra, a može se zaključiti da su optimalne lokacije one na kojima se redovno javljaju slabiji vjetrovi; o Nadmorska visina – sa povećanjem nadmorske visine temperatura pada, vegetaciona sezona se skraćuje i odlaže se sazrijevanje (jedan dan za svakih 30 m nadmorske visine), dok su, zbog uticaja UV zraka, plodovi boljeg kvaliteta i obojenosti, a mogu se i duže čuvati; o Blizina tržišta – kriterijum koji se ne smije zanemariti, jer se sa povećanjem udaljenosti povećavaju troškovi proizvodnje i sama prodajna cijena, što daje prednost proizvođačima koji su bliži kupcima.

Program razvoja organske poljoprivrede u Cr noj Gori

ORGANIZACIJA MJE Š OVIT OG PROIZVODNOG ZASADA Organsko voćarstvo ne predstavlja samo upotrebu biopesticida, organskih đubriva i redukovanih sistema obrade zemljišta, već je to, zapravo, stvaranje i održavanje što prirodnijeg sistema čija ravnoteža omogućava dobijanje organskih proizvoda visokog kvaliteta. Ne postoji (bio)pesticid koji može riješiti sve fitosanitarne probleme. Zato je veoma važno preduzeti sve mjere u cilju postizanja prirodne ravnoteže i samoregulacije. Što je veća biološka raznovrsnost, stabilniji je ekosistem voćnjaka. Zato se, prilikom podizanja organskog voćnjaka ili konverzije postojećeg u organski, mora obezbijediti stanište i za korisne biljke, životinje i insekte čime će se postići pomenuta raznovrsnost i fitosanitarna stabilnost. Šema na sljedećoj strani prikazuje jedan od načina organizacije organskog voćnjaka. 12

Na šemi su redovi orijentisani u pravcu sjever-jug i od toga se može samo neznatno odstupati zbog već pomenutih razloga. Predložene voćne vrste ne predstavljaju pravilo, već dolaze u obzir i druge kombinacije zavisno od regiona u kojem se voćnjak nalazi ili podiže (jabuka-kruška, kruška-trešnja, smokva-vinova loza, nar-mandarina i druge kombinacije). Sjeverna ni južna ograda ne smije biti suviše visoka niti gusta, osim ako ne predstavlja izolaciju od konvencionalnih poljoprivrednih zasada. Idealno rješenje je žičana ograda koja dodatno služi kao potpora za puzavice kakav je bršljan (Hedera helix), orlovi nokti (Lonicera caprifolium), klematis (Clematis spp.) i dr.

i ptica. Treba birati biljne vrste kojima odgovara klima i koje zahtijevaju što manje održavanja, a izbjegavati divlje voćne vrste (divlja jabuka, divlja kruška, oskoruša, gloginja) koje mogu biti domaćini izazivača bolesti i štetočina kultivisanih sorti. Pojas stalnog travnjaka unutar voćnjaka, koji čine biljne vrste uobičajene za podneblje, uz dodatak cvjetnica, ima ulogu privlačenja korisnih insekata i oprašivača. Pojas je širine 3 do 5 m i održava se košenjem po potrebi (češće tokom intenzivnih radova u voćnjaku). Pokošene biljke se mogu koristiti za zastiranje (malčovanje) prostora ispod krošnji voćaka, čime se zemljište obogaćuje

organskom materijom i spriječava gubitak vlage iz zemljišta. Ako postoji mogućnosti širenja sjemena agresivnih korovskih biljnih vrsta i mogućnost prenamnožavanja glodara ispod malča, preporučuje se iznošenje pokošene mase i njeno kompostiranje (poglavlje Kompost). Simbolom drveta na šemi je prikazano ukrasno drveće ili voćke sa prirodnom krošnjom koje okružuju ekonomsko dvorište i prave zaštitu od hladnog sjevernog vjetra. Treba izbjegavati sadnju stabala jabučastih voćnih vrsta sa prirodnom krošnjom pored intenzivnih zasada istih vrsta zbog zajedničkih problema sa bolestima i štetočinama.

ekonomsko dvorište

jabuka šljiva

Na istočnoj i zapadnoj ivici voćnjaka treba podići živu ogradu visine oko 2 m kao izolaciju od okolnih proizvodnih imanja i kao stanište korisnih insekata

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Program razvoja organske poljoprivrede u Cr noj Gori

SISTEMI GAJENJA U O RGA NSKO M VOĆARASTVU Kod sistema gajenja koji omogućavaju cirkulaciju vazduha i dobru osvijetljenost, voćke su otpornije na bolesti, a lakša je i kontrola štetočina. Samim tim, takvi sistemi pogodni su za organsko voćarstvo. Treba imati na umu i visoku produktivnost sistema koja se postiže kod savremenih, gustih voćnih zasada sa 1500 do 2000 stabala po hektaru, a koji se sve više koriste prilikom podizanja organskih voćnjaka. Međuredni razmak zavisi od kvaliteta zemljišta i klime, bujnosti vrste i sorte, kao i mehanizacije koja planira da se koristiti. Najčešće se kreće od 3-4 m kod jabuke do 4-4,5 m kod kruške i šljive, zavisno od vrste, sorte i podloge. Voćke svojom visinom moraju zadovoljiti potrebu obavljanja većine pomotehničkih operacija sa zemlje, što posebno pozitivno utiče na fitosanitarne prilike u voćnjaku. Time se, takođe, smanjuju operativni 14

voćna vrsta

podloga

način gajenja

rastojanje u zasadu

M2, M7, MM106

palmeta: – bujne sorte – srednje bujne sorte – slabo bujne sorte vretenasti žbun vitko vreteno

4,0 – 4,5 x 3,0 – 4,0 m 4,0 x 3,0 m 3,5 – 4,0 x 2,5 – 3,5 m 3,5 – 4,0 x 2,0 – 3,0 m 3,0 – 4,0 x 1,0 – 2,0 m

kruška

dunja MA, BA29 i ČA7

palmeta i vretenasti žbun: – bujne sorte – srednje bujne sorte – slabo bujne sorte

4,0 x 3,0 m 3,5 x 2,5 m 3,0 x 2,0 m

šljiva

džanarika

vaza, poboljšana piramida: -bujne sorte – srednje bujne sorte

5,0 x 4,0 – 3,0 m 5,0 x 2,0 – 3,0 m

malina

špalir

2,5 – 3,0 x 0,25 m

kupina

špalir

2,0 – 3,0 x 1,0 – 1,5 m

tupasto-piramidalni: – bujne sorte – srednje bujne sorte – slabo bujne sorte

5,0 – 5,5 x 3,5 – 4,0 m 4,5 x 3,0 m 3,5 – 4,0 x 2,0 – 2,5 m

jabuka M9 i M26

troškovi, što je cilj svake komercijalne poljoprivredne proizvodnje. Prednosti upotrebe sistema sa niskim uzgojnim oblicima i gustom sadnjom iste su i u organskom i u „standardnom“ (konvencionalnom ili integralnom) voćarstvu: − rani početak plodonošenja; − redovni prinosi i izbjegavanje pojave alternativne rodnosti; − povećanje kvaliteta plodova usled optimalne osvijetljenosti; − smanjenje troškova i potrebe za radnom snagom, posebno prilikom rezidbe i berbe; − efikasnija upotreba mehanizacije; − lakša i efikasnija zaštita od bolesti, štetočina, mraza itd; − smanjenje troškova proizvodnje; − mogućnost brzih promjena kao odgovora na zahtjeve tržišta i nova naučna dostignuća (kvalitetnije i otpornije sorte).

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mandarina

Poncirus trifoliata

maslina

6,0 – 7,0 x 5,0 m

nar

žbun sa 3 do 4 stabla

4,0 – 5,0 x 3,0 – 4,0 m

smokva

vaza palmeta

7,0 x 6,0 m 6,0 x 5,0 m

aktinidija

pergola (odrina ili krevet)

4,0 – 6,0 x 3,0 – 5,0 m

Program razvoja organske poljoprivrede u Cr noj Gori

Kao mane takvih sistema proizvodnje može se navesti sljedeće: − uvećana investiciona ulaganja zbog većeg broja sadnica po jedinici površine i potrebe postavljanja naslona za voćke; − obavezna upotreba podloga manje bujnosti (posebno kod jabuke)

koje se razvijaju u plićem sloju zemljišta gdje im, u iskorišćavanju vode i hraniva, konkuriše pokrovna vegetacija; − gušći sklop smanjuje cirkulaciju vazduha što isključuje bilo kakve kompromise u izboru smjera redova ili načina rezidbe.

Mali međuredni razmak povećava rod, ali i osjetljivost voćki na bolesti i štetočine 16

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PODIZANJE ORGANSKOG VOĆ NJ AK A Hemijska analiza zemljišta, meliorativno đubrenje i nabavka kvalitetnog, bezvirusnog sadnog materijala od proizvođača koji posjeduju deklaraciju o kvalitetu, osnovni su preduslovi podizanja komercijalnog voćnog zasada. Vrlo je važno izvršiti hemijsku analizu zemljišta na kojem planiramo podizanje novog zasada i, na osnovu dobijenih parametara, odrediti norme đubriva dozvoljenih u organskom voćarstvu. Centar za ispitivanje zemljišta Biotehničkog fakulteta u Podgorici vrši uzorkovanje, kao i analizu hemijskog i mehaničkog sastava, nakon čega daje preporuke za unošenje đubriva i drugih sredstava za popravljenje kvaliteta zemljišta. U organskoj poljoprivredi to moraju biti organska đubriva i drugi materijali predviđeni Zakonom o organskoj poljoprivredi. Meliorativno đubrenje izvodi se u godini prije podizanja zasada. Veoma je bitno da se ova

operacije vrši pri idealnoj vlažnosti zemljišta, a posebno je važno da zemljište nije suviše vlažno, jer bi se obradom narušila njegova prirodna struktura. Zemljište treba prvo očistiti od krupnijih grana zaostalih od prethodne vegetacije, kamenja i ostalog što bi moglo ometati rad mašina. Ova faza može se iskoristiti i za ravnanje depresija i izbočina na parceli. Nakon toga đubrivo se rastura ravnomjerno po cijeloj površini i zaorava plitkim oranjem. Zemljište se, zatim, priprema za sadnju u slučaju da se izvodi zimska sadnja, ili ostavlja da prezimi ako se planira proljećna sadnja. Rigolovanje, kao uobičajena mjera pripreme zemljišta za sadnju, ne preporučuje se u organskoj poljoprivredi. Ovim načinom dubokog oranja površinski sloj zemljišta, koji je bogat aktivnom mikro florom i faunom, premješta se u niže slojeve u kojima prestaje njihova aktivnost. Tako

Program razvoja organske poljoprivrede u Cr noj Gori

po potrebi 18

april-maj

april planiranje zasada; kontaktiranje rasadnika đubrenje; zaoravanje; podrivanje

sjetva pokrovnog usjeva

oktobar – novembar ili feb. – mart n.g.

analiza zemljišta

Sadnice voćnih sorti koje su otporne na bolesti i, time, pogodne za organsku proizvodnju, nijesu uvijek dostupne na tržištu. Zbog toga je potrebno, barem, godinu dana prije sadnje kontaktirati rasadnike i ugovoriti nabavku sadnica željenih sorti na pogodnim podlogama. To je dovoljno vremena da u rasadniku izvrše nabavku plemki, kalemljenje i pripremu sadnica za podizanje voćnjaka.

septembar ili februar n.g.

obavezno

mart

Pokrovni usjev zasniva se ako se na parceli nalaze agresivne korovske vrste koje bi onemogućavale izvođenje agrotehničkih operacija u organskom voćnjaku. Treba biti pažljiv oko izbora biljnih vrsta za pokrovni usjev jer, recimo, leguminoze (djeteline, lucerka, lupina, grahorica …) mogu vezati veliku količinu atmosferskog azota koji, na taj način postaje dostupan biljkama. Višak azota kod voćaka izaziva veliku bujnost, osipanje cvjetova, osjetljivost

(1) Susjedno imanje koje u trenutku podizanja organskog voćnjaka može biti neobrađeno, ali treba uzeti u obzir mogućnost da će se nekada aktivirati. Iz tog razloga je bolje od početka planirati izolacioni pojas.

na bolesti i štetočine i druge negativne pojave. Zbog toga, više se preporučuje podsticanje prirodne, lokalne travne vegetacije, koja je prilagođena klimatskom uslovima i lako se održava. Agresivne korove treba iscrpljivati češćim košenjem i okopavanjem.

jun-julavgust

pripremljenom zemljištu treba mnogo više vremena da uspostavi prirodnu ravnotežu. Ako u nižim slojevima zemljišta postoji nepropusni horizont, on se razbija podrivanjem koje ne prevrće zemlju.

kopanje rupa za sadnice

pripremanje za sadnju i sadnja

njega pokrovnog usjeva

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(2) Dio Vašeg imanja koji se graniči sa susjednim i predstavlja prostornu barijeru. Održava se češćim košenjem i odnošenjem pokošene mase čime se sprečava prelazak glodara u voćnjak. Širina pojasa je najmanje 2 m. Prirodni travni pokrivač se lako održava, obogaćuje zemljište organskom materijom i predstavlja utočište korisnim insektima

Prilikom planiranja novog voćnjaka važno je predvidjeti prostor koji će izolovati organski voćnjak od susjednih zasada, čak i ako ih u tom trenutku nema. Izolaciju, zapravo, čine prirodne barijere koje imaju višestruku funkciju.

3 1

(3) Živa ograda visine najmanje 2 m, predstavlja barijeru, a istovremeno i utočište za mnoge korisne životinje i insekte. Treba koristiti biljke prilagođene klimatskim uslovima, a izbjegavati divlje voćne vrste koje mogu biti domaćini uzročnika bolesti kultivisanih sorti. (4) Pojas travnog pokrivača i niskih cvjetnica. Ovaj dio voćnjaka koristi se za prolaz mehanizacije, a predstavlja i utočište korisnih insekata među kojima su i polinatori (oprašivači). Održava se povremenim košenjem, u slučaju kad ometa prolaz mehanizacije. Širina je 3 do 5 m, zavisno od širine traktora i zahvata priključaka, kao i od uzgojnog oblika.

Program razvoja organske poljoprivrede u Cr noj Gori

Pripreme za sadnju počinju krajem ljeta, kada treba roto-frezom obraditi redove širine do 1 m, u kojima će se saditi voćke. Tako dobijene obrađene trake treba održavati čistim od korova. Kopanje rupa vrši se ručno ili mašinski.

Prilikom sadnje treba strogo poštovati osnovna pravila: o koristiti samo zdrave i kvalitetne sadnice, po mogućnosti sertifikovane;

Dimenzije rupa zavise od tipa zemljišta i od toga da li je prethodno izvršeno podrivanje. Na težim zemljištima i gdje nije vršeno podrivanje treba kopati dublje rupe (do 80 cm), dok na lakšim zemljištima rupe mogu biti pliće (do 50 cm).

dubinu na kojoj je bila u rasadniku (mjesto se poznaje po razlici u boji kore – dio sadnice koji je bio u zemlji svjetlije je boje), ili 4 do 6 cm dublje;

o r asporediti korjenove žile radijalno o ne vršiti sadnju na temperaturama na dnu rupe, prekriti korijen ispod 0 °C ili kada vlažnost kvalitetnom zemljom sa površine zemljišta nije optimalna – zemljište i dobro nagaziti da ne bi ostali ne smije da se lijepi za alat ili da vazdušni džepovi; bude suviše suvo; ou rupu dodati 5 do 10 kg zgorelog o korijenje treba skvasiti prije sadnje, stajnjaka ili komposta – to će biti a najbolje ga je potopiti u smješu značajna rezerva hranljivih materija jednakih dijelova zemlje, svježe tokom prvih godina rasta i razvoja kravlje balege i vode; voćke; o odrezati oštećene korjenove žile; o obratiti pažnju na dubinu sadnje – sadnica treba da bude posađena na

O BRADA ZEMLJIŠTA U ORGAN SKOM VOĆ NJ AK U Organsko voćarsto samo po sebi podrazumijeva redukovanu obradu zemljišta kojom se postiže bolja poroznost i veći vodno-vazdušni kapacitet zemljišta, veći sadržaj organske materije u zemljištu i veća plodnost, aktivnija mikro flora i fauna zemljišta, veća biološka raznolikost (biodiverzitet) itd. Neprihvatljiv je sistem jalovog ugara (stalna obrada zemljišta) koji je najrašireniji sistem kod nas, posebno u južnim krajevima. Takva obrada izaziva veliki broj negativnih pojava i povećanje troškova proizvodnje. Iskustva organskih proizvođača voća širom svijeta preporučuju nekoliko sistema koji se mogu primjenjivati i u našim proizvodnim uslovima.

Obrada zone ispod krošnji Međuredni prostor pokriven je spontanom travnom vegetacijom ili pokrovnim usjevom. Prostor ispod krošnji neprestano se obrađuje tokom vegetacije.

o z aliti vodom odmah nakon sadnje, posebno ako se sadi u proljeće – time će se i dodatno slegnuti zemlja koju treba nadoknaditi do vrha rupe.

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Program razvoja organske poljoprivrede u Cr noj Gori

Održavanje:

Sendvič sistem

Održavanje:

Zastiranje (malčovanje)

Košenje rastinja u međurednom prostoru – po potrebi, češće tokom intenzivnih radova u voćnjaku da ne bi ometalo rad mehanizacije.

Sličan je prethodnom sistemu samo što se između stabala u redu ostavlja traka pokrivena vegetacijom, dok se sa obije strane formiraju trake širine 50 cm koje se stalno obrađuju. Ovim sistemom postiže se smanjenje potrebe za održavanjem, ali zahtijeva nešto veće količine đubriva.

Košenje rastinja u međurednom prostoru kao u prethodnom slučaju. Plitka obrada traka – koristiti freze i kultivatore radnog zahvata do 50 cm, isključivo pri optimalnoj vlažnosti zemljišta.

Koristi se odmah nakon sadnje, posebno u sušnim krajevima i na zemljištima siromašnim organskom materijom i kalijumom. Zona ispod krošnji održava se zastiranjem različitim materijalima, kao što su folije od biorazgradivih plastičnih masa, papirom, slamom, piljevinom, tresetom, kompostom itd. Nakon 2 do 3 godine, kada se malč razgradi, postupak se može ponoviti ili preći na obradu zemljišta u redu (ispod krošnji). Međuredni prostor održava se košenjem.

Iznošenje pokošene mase preporučuje se samo ako postoji opasnost od prenamnožavanje glodara ili od požara. Nakon iznošenja može se koristiti za ishranu stoke ili pravljenje komposta. Obrada prostora ispod krošnje – u savremenoj, komercijalnoj voćarskoj proizvodnji za ovu operaciju koriste se kultivatori sa senzorom koji se pomjeraju u stranu kada naiđu na stablo. U manjim zasadima se mogu koristiti motokultivatori sa frezom.

Održavanje trake sa travnom vegetacijom ispod krošnji – košenje po potrebi, jednom do dva puta tokom vegetacije. Đubrenje – može se izvesti zastiranjem obrađenih traka nekim organskim đubrivom neposredno prije obrade (detaljnije u poglavlju Đubrenje).

Savjet: Za košenje pokrovnog rastinja u voćnjaku koristite strižne kosačice prije nego malčere. Iako malčeri bolje usitnjavaju travu, takođe uništavaju i veliki broj korisnih insekata koji su prirodni neprijatelji štetočina voćaka. To može u značajnoj mjeri poremetiti biološku ravnotežu voćnjaka.

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Program razvoja organske poljoprivrede u Cr noj Gori

Pravila organske poljoprivrede nalažu da se komercijalna bio-đubriva i organska đubriva proizvedena na imanju koriste na osnovu rezultata analize zemljišta i potreba gajenih biljaka. Jedino je tako moguće izračunati potrebnu količinu hraniva koju treba unijeti u vidu dozvoljenih đubriva. Optimalni osnovni parametri kojima treba težiti su: pH 6-7, sadržaj humusa min 3 %, sadržaj K2O 30 mg/100 g zemljišta, sadržaj P2O5 15 mg/100 g zemljišta. Kod organske proizvodnje, u principu, moraju se preduzimati sve mjere da se poveća plodnost zemljišta. To podrazumijeva pažljivu obradu zemljišta koja neće narušiti njegovu strukturu, povećanje procenta humusa, kao i unošenje organskih đubriva dobijenih na farmi. Optimalna plodnost, postignuta na taj način, garantuje dovoljne količine hraniva za gajene biljke. 24

Sadržaju azota u zemljištu treba posvetiti posebnu pažnju jer je veoma bitan za normalan rast i razvoj voćaka. Simptomi koji ukazuju na nedostatak azota u zemljištu su slab porast izadanaka, nepravilni cvjetovi i njihovo osipanje, promjena boje lišća, posebno starijeg, u svijetlo zelenu ili žutu, otpadanje velikog broja zametnutih plodova itd. Azot u višku, takođe, izaziva razne fiziološke poremećaje koji mogu dovesti u pitanje količinu i kvalitet roda. Zbog toga treba imati na umu blisku povezanost sadržaja azota i količine humusa u zemljištu. Što je veća količina (procenat) humusa veća je i količina azota dostupnog biljkama. Tako 1 % humusa obezbjeđuje oko 30-40 kg/ha godišnje, što je, zapravo, i godišnja potreba voćaka tokom vegetacije. Ako je sadržaj humusa preko 3 % i ako je, prije početka vegetacije, unijeto organsko đubrivo bogato azotom, onda

PROI Z V O D N J A V O Ć A U O R G A N S K O J P O L J O P R I V R E D I

nema potrebe za dodatnim azotnim đubrivima. Tokom jeseni i zime azot iz zemljišta se imobiliše u pokrovnom rastinju. Prvom proljećnom obradom zemljišta u zoni između stabala, dolazi do mineralizacije azota i on postaje dostupan voćkama. Ako se, po simptomima na voćkama, identifikuje nedostatak azota, nije potrebno odmah koristiti azotna đubriva, već je, najčešće, dovoljno preduzeti neku od sljedećih mjera: – obradom zemljišta, odnosno zone koju inače obrađujete, izazvati mineralizaciju azota koji postaje dostupan biljkama; – ako je sušno, navodnjavanjem ćete pospješiti mobilnost azota; – podstaći drenažu zemljišta – ako je zemljište suviše vlažno i hladno, simptomi nedostatka azota će se pojaviti, čak i ako je njegov sadržaj visok. Ako ni jedna od ovih mjera ne donosi očekivani rezultat, treba izvršiti hemijsku analizu sadržaja azota u zemljištu i u lišću voćki i na osnovu rezultata analize izvršiti đubrenje nekim od dozvoljenih đubriva. Savjet: Đubriva bogata azotom (stajnjak, kompost) unose se u zonu

ispod krošnji neposredno prije obrade, dok se ostala organska đubriva rasturaju po cijeloj površini voćnjaka bez naknadne obrade. Mineralna bio-đubriva, posebno fosforna, unose se dublje u zemljište (najčešće prilikom meliorativnog đubrenja). Tabela na sljedećoj strani prikazuje sadržaje hraniva (u kg/m3) u najčešće primjenjivanim organskim đubrivima i optimalne periode za njihovu upotrebu. Ako se zna da, za ostvarivanje prinosa između 25 i 50 t/ha, voćka iskoristi 20-30 kg N, 5-15 kg P2O5, 50-80 kg K2O, 17-20 kg CaO i 6-8 kg MgO, uz informacije iz prethodne tabele mogu se izračunati godišnje norme đubrenja. Pri tome, svakako, treba uzeti u obzir specifične zahtjeve pojedinih voćnih vrsta, stvarne sadržaje hraniva u đubrivu kojim raspolažete, kao i činjenicu da se određena količina hraniva ispira ili fiksira u zemljištu ili pokrovnom rastinju. Zbog ovih razloga, precizne norme đubrenja treba odrediti na osnovu višegodišnjih zapažanja i rezultata proizvodnje, kao i povremenih analiza sadržaja hraniva u zemljištu ili lisnom materijalu.

Program razvoja organske poljoprivrede u Cr noj Gori

N ukupno

N dostupno

P2O5

K2O

Optimalno vrijeme upotrebe

kompost (1m3 ≈ 700 kg)

4,9

0,5

2,8

4,0

2,2

20,0

feb.- april

stajnjak (1m3 ≈ 700 kg)

3,4

0,7

2,2

4,6

0,6

2,6

mart – april

supstrat za pečurke (1m3 ≈ 500 kg)

3,5

1,5

2,5

4,0

1,5

2,7

mart – april

tečni stajnjak

4,3

2,2

1,7

5,2

0,7

1,3

april – maj

Kompost Kompost predstavlja najkompletnije organsko đubrivo koje se koristi u organskoj poljoprivredi. Može se proizvoditi na farmi, pa postaje sve popularnije kod proizvođača. Kompost je sačinjen od razgrađenih ostataka biljnog (svježe pokošena trava, sijeno, slama, lišće, piljevina …) i životinjskog porijekla (stajnjak, koštano i krvno brašno …), kao i kuhinjskih i kancelarijskih otpadaka (ostaci i kore voća i povrća, iskorišćena kafa i kesice čaja, ljuske jaja, usitnjeni kancelarijski papir, kartonska ambalaža …). 26

Osnovno je pravilo da materijali koji se kompostoriju nijesu hemijski tretirani pesticidima i sličnim sintetičkim sredstvima, a da materijali životinjskog porijekla ne potiču sa intenzivnih farmi gdje se koriste hormoni, antibiotici i druge hemikalije koje nijesu dozvoljene u organskoj poljoprivredi. Takođe treba izbjegavati i zaražene, odnosno oboljele biljne djelove. Kompostiranje je aerobni proces (zahtijeva prisustvo vazduha) pri kojem mikroorganizmi razlažu organsku materiju i transformišu je u humus. Osnovni proces razlaganja traje kratko, između 15 i 30 dana

PROI Z V O D N J A V O Ć A U O R G A N S K O J P O L J O P R I V R E D I

u prosjeku. Tokom te prve faze temperatura raste unutar kompostišta, dostižući i 60 °C. Visoka temperatura uništava sjeme korova i najveći dio biljnih patogena (kompostiranje, ipak, preživljavaju virus mozaika duvana, zatim Sclerotinia koja izaziva bijelu trulež i izazivači nekih bolesti kupusnjača). Nakon faze razlaganja kompost treba da prođe i fazu zrenja koja traje i do 10 mjeseci. Za to vrijeme proste organske materije prelaze u stabilnije humusne supstance koje su pristupačnije biljkama.

Formiranje kompostne hrpe Za proizvodna imanja najprikladnije su kompostne hrpe ravnih ili kosih strana (do 45 °), sa bazom širine od 2 do 2,5 m, visine 1,5 do 2 m i dužine prema potrebi, odnosno raspoloživoj količini materijala. Kompostnu hrpu treba formirati u polusjenci, zaklonjenu od jakog vjetra, u pravcu sjever-jug da bi što ravnomjernije bila zagrijana. Osnovno je pravilo da se kompostna hrpa formira tek kada se sakupi dovoljno materijala. Zemlja na kojoj se podiže kompostište treba da je porozna, što se može poboljšati

laganim, površinskim prekopavanjem. Na površini zemlje treba naslagati nešto krupnije grančice koje će odvojiti hrpu od zemlje, u cilju ocjeđivanja suvišne vode i bolje prozračnosti. Pošto se formira baza od grančica, počinje se sa naizmjeničnim slaganjem tankih slojeva različitih materijala. Slaganje treba izvesti tako da se smjenjuju materijali koji su bogati azotom (stajnjak, svježe pokošena trava, kuhinjski ostaci, sijeno mahunarki), sa materijalima koji sadrže manje azota (grančice, suvo lišće, piljevina, usitnjeni papir i karton, slama). Osjemenjene korove i kuhinjske ostatke treba smjestiti u sredinu hrpe gdje je najviša temperatura. Razlaganje će se ubrzati ako tokom slaganja slojeva unesete i nekoliko slojeva već pripremljenog komposta ili plodne zemlje, sa kojim i završite slaganje hrpe. Tokom slaganja slojeva treba ih vlažiti vodom, najbolje izvorskom ili bunarskom, do te mjere da iz materijala stisnutog u šaci ne curi voda, ali da ostaje kompaktan nakon puštanja iz ruke. Tako ćete znati da je vlažnost između 50 i 60 %, što je optimalno za kvalitetno kompostiranje. Na kraju hrpu treba prekriti po vrhu slamom, sijenom, starim platnom ili najlonom, ostavljajući strane slobodne za protok vazduha.

Program razvoja organske poljoprivrede u Cr noj Gori

NAVODNJAVANJE

Kompostna hrpa pokrivena sijenom

Tokom prve faze kompostiranja korisno je rastresti materijal u cilju dodatne aeracije i ravnomjernijeg razlaganja, što se obavlja jednom u 15 do 20 dana. Ovo je naročito preporučljivo ako je materijal prevlažan i ako hrpa, usljed toga, ne postiže očekivanu temperaturu. Završetak ove faze prepoznaje se po spuštanju temperature unutar hrpe na nivo spoljašnje temperature, dok materijal postaje homogen i dobija tamnu, zemljanu boju. Nakon toga kompost prelazi u fazu sazrijevanja, tokom koje nije potrebno miješanje niti bilo koja druga intervencija. Potrebno ga je samo pokriti da se izbjegne ispiranje hranljivih materija kišom. Tokom sazrijevanja u kompostu se može 28

primijetiti veća aktivnost insekata i kišnih glista. Završetak ove faze treba očekivati za najmanje 10 mjeseci što se prepoznaje po izrazito tamnoj boji komposta i odsustvu mikro faune koja je obavila svoju funkciju.

Nedostatak vode tokom vegetacije usporava rast i smanjuje veličinu i kvalitet voća. Najveći je rizik za mlade voćnjake na plitkim i lakim zemljištima. Voda takođe mobiliše hraniva iz zemljišta i čini ih dostupnim biljkama. Voćke kojima se podižu komercijalni, gusti zasadi, kaleme se na slabo bujne podloge koje mogu patiti usljed nedostatka vode u površinskom sloju zemljišta, gdje se najvećim dijelom

i razvijaju. Problem nedostataka vode može se umanjiti nekim od posrednih načina kao što je izbor bujnijih podloga, malčovanje, češće košenje pokrovne vegetacije itd. Ipak navodnjavanje, kao direktna mjera, ostaje kao jedina garancija dobrog stanja voćnjaka i sigurnog prinosa. Tabela na sljedećoj strani navodi prednosti i nedostatke pojedinih načina navodnjavanja.

Savjet: Zrelost komposta se može provjeriti pomoću testa sa sjemenom salate. Kutija manjih dimenzija napuni se kompostom u koji se posije sjeme salate i zalije vodom. Nicanje bi trebalo da uslijedi nakon 2 do 3 dana, a mlade biljke treba da budu zelene i uspravne sa bijelim korijenom. Ako to nije slučaj, kompost se mora vratiti na dozrijevanje još par mjeseci, nakon čega treba ponoviti test.

PROI Z V O D N J A V O Ć A U O R G A N S K O J P O L J O P R I V R E D I

Program razvoja organske poljoprivrede u Cr noj Gori

navodnjavanje brazdama

prednost

nedostatak



 



avodnjava se zona n korijena; nema troškova instalacije sistema;



kap-po-kap

e konomično korišćenje vode;  autonoman rad;  jednostavno određivanje normi zalivanja;  mogućnost dodavanja rastvorljivih organskih đubriva;



o graničena zona zalivanja koja ne obuhvata kompletnu zonu korijena – problem je moguće riješiti ugradnjom mikrorasprskivača koji pokrivaju širu zonu;  cijena instalacije;  mogućnost oštećenja sistema prilikom obrade zemljišta;  mogućnost začepljenja sistema taloženjem kamenca ili đubriva;



vještačka kiša prskalice

ože se korism titi kao prevencija smrzavanja pupoljaka u proljeće;  navodnjava se i pokrovna vegetacija;



velika potrošnja vode; značajan utrošak radnog vremena – otvaranje brazde i premještanje crijeva; otežano određivanje norme zal ivanja;

  

cijena instalacije; neekonomično iskorišćenje vode; povećanje vlažnosti u zoni krošnje podstiče razvoj gljivičnih oboljenja;

PROI Z V O D N J A V O Ć A U O R G A N S K O J P O L J O P R I V R E D I

ZAŠTITA OD KOROVA U O RG ANSKOM VOĆ NJ AKU Formiranjem i održavanjem pokrovne vegetacije u organskom voćarstvu, kontrola korova dobija drugu dimenziju, i više ne znači suzbijanje kompletne vegetacije ispod voćaka. Pojedine biljke u organskom voćarstvu, ipak, zadržavaju pridjev korovske, a to su uglavnom višegodišnji korovi koji se, jedino upornim tretiranjem mogu potpuno suzbiti (čičak – Xanthium spp., štir – Amaranthus retroflexus, slačac – Convolvulus arvensis, divlja kupina – Rubus spp.). Korovi predstavljaju poseban problem kada se zapušteni voćnjak (npr. maslinjak), ponovo privodi kulturi ili u proizvodnji jagoda u organskoj poljoprivredi. Iako postoje neki organski herbicidi, zbog njihove male efikasnosti, može se prvo pokušati sa nekim od sljedećih načina suzbijanja.

Plitka obrada zemljišta Primjenjuje se prilikom pripremanja terena za podizanje voćnjaka ako je veliko prisustvo višegodišnjih korova. Naizmjenično se kombinuje sa navodnjavanjem čime se podstiče klijanje sjemena korova. Otkopavanjem i iznošenjem iz voćnjaka mogu se iskorijeniti pojedinačni višegodišnji korovi i spriječiti njihovo dalje širenje.

Malčovanje (zastiranje zemljišta) Posebno se koristi prilikom uzgoja jagoda ili za održavanje prostora između stabala u voćnjaku. U jagodnjacima se često koriste plastične folije, ali se može koristiti i malč od prirodnih materijala. Da bi bio efikasan, sloj prirodnog malča mora biti debeo oko 10 cm. Najčešće se koristi sijeno, piljevina, treset, usitnjeni papir itd.

Program razvoja organske poljoprivrede u Cr noj Gori

Solarizacija Pokrivanjem manjih parcela providnom plastičnom folijom tokom ljetnjih mjeseci postiže se povećanje temperature u površinskom sloju zemljišta, čime se uništava sjeme korova. Metod je efikasan u suzbijanju jednogodišnjih korova, a srednje efikasan za suzbijanje višegodišnjih. Korisno je izvršiti navodnjavanje prije pokrivanja folijom, jer se vlažno zemljište bolje zagrijava nego suvo.

Kultivacija plamenom Sve češće primjenjivan tretman u organskoj poljoprivredi, koji podrazumijeva upotrebu gasnih plamenika ili baklji čiji plamen isušuje korove. Najefikasniji je do pojave trećeg lista na stabljici korova. Korov se tretira par sekundi, a potpuno sušenje će uslijediti nakon nekoliko dana. Prije kultivacije plamenom treba izvršiti prevenciju požara, oštećenja voćaka, sistema za navodnjavanje i malč folija i preduzeti druge mjere bezbjednosti.

ZAŠTITA OD BOLESTI I ŠTETO ČIN A U organskoj poljoprivredi je najveća pažnja usmjerena na preventivne metode zaštite. Kako je izbor dozvoljenih pesticida veoma slab i kako su bio-pesticidi, generalno, manje efikasni od sintetičkih, moraju se preduzeti sve mjere zaštite da bi se postigli željeni rezultati. Te mjere počinju izborom pozicije voćnjaka, izborom sorte, uzgojnog oblika, zasnivanjem pokrovne kulture, da bi primjena bio-pesticida došla kao krajnja mjera. Kontrola brojnosti i uticaja štetočina u organskoj poljoprivredi koristi prednost mnogobrojnih antagonostičkih relacija koje su prisutne u prirodi, u cilju smanjenja populacije štetnih organizama. To se postiže na dva načina: o kontrolom uslova u voćnjaku, u cilju zaštite i povećanja efikasnosti postojećih, prirodnih antagonista

PROI Z V O D N J A V O Ć A U O R G A N S K O J P O L J O P R I V R E D I

(neprijatelja štetnih organizama); o unošenjem i širenjem prirodnih antagonista.

Utočište za korisne insekte u organskom kupinjaku

Povratak prirodnim relacijama uključuje, ne samo korišćenje odbrambenih kapaciteta biljke (sorte otporne na bolesti), već i primjenu

Program razvoja organske poljoprivrede u Cr noj Gori

praksi koje doprinose prirodnoj raznolikosti (plodored, kombinovani zasadi, pokrovno rastinje, žive ograde), a sve u cilju obnove izgubljenih antagonističkih odnosa i prirodne samoregulacije. Naredne mjere mogu se preduzeti u cilju postizanja raznolikosti flore i faune u voćnjaku: o povećanje broja korisnih ptica – postavljanje kućica za ptice koje se hrane insektima (sjenice), ili postavljanje visokih prečki za ptice grabljivice koje kontrolišu brojnost glodara; o povećanje broja insekata koji su prirodni predatori štetočina – uzgoj i održavanje traka sa različitim cvjetnicama oko voćnjaka ili podizanje jednostavnih konstrukcija od porozne gline koje će poslužiti kao stanište korisnih insekata.

Uholoža se hrani biljnim vašima 34

Savjet: Kućice za ptice treba da su dimenzija 250 x 150 x 150 mm sa otvorom prečnika 25 do 30 mm. Kače se na drvo ili stub, na visinu 150 do 200 cm, okrenute u pravcu juga ili jugoistoka, odnosno u pravcu redova u voćnjaku. Treba da su zaklonjene od uticaja jakog vjetra i direktnih sunčevih zraka. Razmak između kućica mora biti 20 do 25 m jer su sjenice veoma teritorijalne ptice. Kućice treba čistiti svake jeseni od ostataka gniježđenja. Savjet: Napravite konstrukciju od isprepletanih vrbovih grančica, nalik ljesama od pruća. Obložite je mješavinom gline, pijeska i slame, formirajući sloj debljine oko 20 cm sa obije strane i ostavite da se osuši na suncu. Uspravno postavite dobijenu konstrukciju pored ili unutar voćnjaka, okrenite je sjeveru i zaštitite jednostavnim krovom od tankih dasaka. Korisni insekti će, u poroznom zidu konstrukcije, vremenom formirati svoja gnijezda. Takođe se mora vršiti stalni monitoring (praćenje) prisustva štetnih insekata, ponajviše u cilju procjene ekonomskih pragova štetnosti nakon kojih treba preduzimati direktne mjere zaštite. Pošto su štetočine

PROI Z V O D N J A V O Ć A U O R G A N S K O J P O L J O P R I V R E D I

veoma malih dimenzija, posebno kada su u formi jaja ili larve, svaki organski voćar mora imati lupu koja će mu olakšati posmatranje, kao i određivanje pravog trenutka za preduzimanje odgovarajućih zaštitnih mjera. Neki od načina monitoringa su: o pregled uzoraka grančica uzetih sa stabala tokom zime – najčešće se ocjenjuje prisustvo zimskih jaja crvenog pauka – Panonychus ulmi (tretman je obavezan ako nakon prelaska prstom po baznom dijelu grančice ostane vidljiva crvena boja); o stresanje insekata udaranjem po granama vrši se preko dana kada je temperatura iznad 12 °C – vrši se u cilju praćenja pojave i brojnosti cvjetojeda jabuke – Anthonomus pomorum, kao i druge faune u krošnjama; o vizuelna kontrola – proizvoljno se uzima 100 različitih organa voćaka (cvjetni pupoljci, lisne rozete, duge grančice, plodovi …) na kojima se ispituje brojnost štetočina pomoću lupe; o kontrolne table u boji – na njima se lijepe insekti privučeni jarkom bojom čime se procjenjuje datum njihovog pojavljivanja i brojnost; o feromonske zamke – sličan koncept

kao i u prethodnom slučaju samo što insekte privlači seksualni hormon ženki koji se oslobađa iz malih kapsula pričvršćenih na ljepljivu ploču;

Pojas od sintetičke vune „rinchotrap“ spriječava penjanje štetnih insekata u krošnju voćke

Glodari i divljač mogu nanijeti štete, kako mladom voćnjaku, tako i voćnjaku u rodu. Zaštita se postiže na nekoliko načina: – održavanjem prostornih barijera košenjem i iznošenjem pokošene mase koja bi mogla predstavljati zaklon za glodare; – košenjem i iznošenjem pokrovnog rastinja unutar voćnjaka prije nego formira sjeme koje, zaostalo na zemlji, može privući sitne glodare; – postavljanjem žičane mreže malog promjera (5 do 10 mm) u dnu ograde oko voćnjaka. Visina mreža

Program razvoja organske poljoprivrede u Cr noj Gori

treba da bude 0,8 do 1 m, s tim da se pola mreže ukopa u zemlju, a na vrhu treba postaviti pojas od lima ili plastike širine 10 cm; – postavljenjem pojedinačnih zaštita od mreže oko svakog stabla, kao alternativa prethodnoj mjeri; – podsticanjem prisustva ptica grabljivica; – postavljanjem zamki i mišolovki u slučaju napada koji se ne može kontrolisati nekim od prethodnih mjera.

Tokom perioda sazrijevanja voća problem mogu predstavljati ptice koje se hrane tim voćem. Treba imati na umu da to nijesu iste ptičje vrste koje su naselile kućice koje ste postavili u voćnjaku, jer se one hrane pretežno insektima. Za kontrolu šteta od ptica, sa manje ili više uspjeha, mogu se koristiti čegrtaljke, plinski topovi (ne smiju se koristiti u naseljenom području), razne svjetlucave trake, ogledala itd. Najefikasniji metod je zaštita mrežama kojima se prekrivaju pojedinačna stabla ili cijeli voćnjaci.

Preporučljivije je pokrivanje stabala da se ne bi ometao let korisnih ptica kroz voćnjak. Mreže moraju biti samo za tu namjenu i moraju se uklanjati odmah nakon berbe. Bolesti u voćnjaku mogu biti izazvane od strane gljivica, bakterija, virusa, mikoplazmi i protozoa. Dobra odbrana od uzročnika bolesti podrazumijeva održavanje voćnjaka u odličnoj kondiciji uz dovoljnu količinu hraniva i vode. Prije upotrebe krajnjih mjera u vidu dozvoljenih sredstava za zaštitu protiv bolesti, moraju se sprovesti sve preventivne mjere:

osnovni preduslov razvoja gljivičnih bolesti; o uklanjanje orezanih grana, otpalog lišća i voća – ako se procjenjuje da orezani ili otpali dijelovi stabla mogu biti zaraženi, najbolje je da se unište spaljivanjem, dok se u suprotnom mogu kompostirati; o povećanje plodnosti zemljišta i vitalnosti mikro faune u zemljištu – gliste se hrane otpalim lišćem uništavajući tako i gljivice zaostale na njemu, na taj način smanjujući produkciju spora i do 90 %.

o izbor vrste i sorte voća – treba izbjegavati vrste i sorte koje su jako osjetljive na bolesti koje se često javljaju u regionu u kojem se podiže organski voćnjak; o izbor položaja organskog voćnjaka – pozicije otvorene prema jugu, sa konstantnom i umjerenom cirkulacijom vazduha na kojima nema opasnosti od izmrzavanja, osiguraće voćkama vitalnost i smanjiće mogućnost pojave bolesti; o pravilna zimska i zelena rezidba – osigurava prozračnost krošnje i smanjuje vlažnost unutar nje, koja je

PROI Z V O D N J A V O Ć A U O R G A N S K O J P O L J O P R I V R E D I

Program razvoja organske poljoprivrede u Cr noj Gori

napomene

tehnike berbe

jabuka

-organoleptička metoda -oblik, boja, miris, ukus; -lakoća odvajanje peteljke od grane; -broj dana od T stadijuma; -čvrstina mesa ploda (mjereno penetrometrom); -sadržaj šećera (mjereno refraktometrom); -jodno-skrobni test;

-zavisno od predviđene dužina i načina skladištenja, plodovi se beru u različitim fazama zrelosti. Često je potrebno brati i iz dva puta. Dobro je unaprijed tražiti instrukcije distributera.

-koristiti kengur torbe, čiste gajbice ili druge vrste ambalaže; -za berbu plodova na višim granama ne smiju se koristiti metode koje mogu povrijediti pokožicu ploda – koristiti merdevine ili pokretne platforme. -sortirati plodove prije skladištenja; -pažljivo postupati sa plodovima da se ne bi javile povrede i promjene na površini;

kruška

-isto kao kod jabuke izuzev T stadijuma;

-slično kao kod jabuke, s tim što je tačno vrijeme berbe teže odrediti;

-isto kao kod jabuke;

šljiva

kriterijumi za određivanje datuma berbe

-organoleptička metoda – oblik, boja, miris, ukus, pepeljak na pokožici; -lakoća odvajanje peteljke od grane; -čvrstina mesa ploda (mjereno penetrometrom); -nivo šećera i kiselina (za svaku sortu posebno);

-zavisno od procijenjenog vremena koje će proći između berbe i prodaje, plodovi se beru u različitim fazama zrelosti. Često je potrebna i berba u nekoliko navrata.

-slagati plodove direktno u malu ambalažu za prodaju ili u veću za preradu; -prilikom berbe plodova za upotrebu u svježem stanju treba nastojati da se očuva pepeljak na pokožici – treba koristiti rukavice ako je to neophodno.

BERBA Vrijeme i tehnika berbe imaju veliki uticaj na kvalitet voća, čime zaslužuju posebnu pažnju organskih proizvođača. Organsko voće mora zadovoljiti sertifikacione standarde, ali, isto tako, i zahtjeve potrošača. Distributeri ne procjenjuju samo spoljašnji izgled plodova, već se, sve češće, mjeri sadržaj šećera i čvrstoća mesa ploda.

Berba masline 38

Opšta pravila kojih se treba pridržavati su sljedeća: • berači moraju održavati ličnu higijenu, posebno čistoću ruku; • potrebno je obezbijediti sanitarne prostorije, koje mogu biti i montažnog tipa, unutar ili u blizini voćnjaka; • plodovi se slažu pažljivo u ambalaži da ne bi došlo do pojave povreda na površini; • ambalaža mora biti čista i dezinfikovana sredstvima dozvoljenim u organskoj proizvodnji; • ambalaža sa voćem se ne smije držati direktno na zemlji; • potrebno je obezbijediti zasijenjeno mjesto za odlaganje ubranog voća prije transporta u skladište; • transport obavljati pažljivo da ne bi došlo do oštećenja plodova.

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Program razvoja organske poljoprivrede u Cr noj Gori

malina maslina 40

-lakoća odvajanja ploda od cvjetne lože; -čvrstina ploda; -boja i ukus ploda;

-boja ploda – za ulje; -boja, veličina i tekstura ploda – za konzerviranje;

-za upotrebu u svježem stanju ili zamrzavanje, plodovi se beru dan ili dva dana prije pune zrelosti. -plodovi namijenjeni preradi beru se u punoj zrelosti.

-masline za proizvodnju ulja treba brati kada plodovi počnu mijenjati boju (šarak). -masline za stonu upotrebu treba brati neposredno prije promjene boje za zeleno konzerviranje, ili pri punoj zrelosti (potpuno tamna boja) i kada su najkrupnije za crno konzervisanje.

-berba se obavlja ručno i u više navrata. -zbog svoje osjetljivosti, plodovi se, prilikom berbe, odmah klasiraju i slažu u ambalažu u kojoj će se prodavati. -berbu treba obavljati ujutro i predveče.

-masline za konzervisanje beru se ručno uz pomoć kengur torbi i plitke ambalaže. Često je potrebna berba u više navrata. -masline za preradu beru se uz pomoć tresača ili pneumatskih češljeva i mreža, a transportuju se u plitkim ambalažama (gajbicama).

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UVOD U O RGAN SKU RASADNIČKU PROIZVO DNJU Prema Zakonu o organskoj poljoprivredi, samo sadnice dobijene po metodama organske proizvodnje mogu se koristiti za podizanje organskih voćnjaka (osim u slučaju prelaznog perioda kada se može koristiti i standardni sadni materijal). To znači da podloge i sadnice moraju biti proizvedene u organskim rasadnicima.

Izbor lokacije za organski rasadnik Samo relativno ravno zemljište pogodno je za rasadničku proizvodnju. Na nagnutim terenima postoji opasnost od erozije pošto se zemljište u rastilu rasadnika mora održavati čistim od drugog rastinja. Lokacije na kojima postoji rizik od mraza (zimskog ili proljećnog) nisu pogodne za rasadnik, posebno u proizvodnji sadnica koštičavih voćnih vrsta. Najpogodnije je

srednje teško zemljište, tipa pjeskovite ilovače, sa sadržajem humusa između 1,5 i 4 % i pH između 5,5 i 6,5.

Priprema zemljišta Analiza zemljišta je neophodna prije podizanja organskog rasadnika, jer se na osnovu nje određuje norma meliorativnog đubrenja. Nakon meliorativnih zahvata preporučljiva je sjetva biljaka za zelenišno đubrenje. Leguminoze se preporučuju u tu svrhu, u cilju obogaćenja zemljišta azotom koji fiksiraju iz atmosfere. Ni preko zime zemljište ne treba ostaviti golo, već treba posijati leguminoze koje će obezbijediti azot za voćne podloge koje će se saditi u rano proljeće. Prije zaoravanja zelene mase u rano proljeće poželjno je ravnomjerno rasuti đubrivo bogato azotom kao što su: usitnjene uljne pogače, rožno ili krvno brašno, osoka i dr.

Program razvoja organske poljoprivrede u Cr noj Gori

Obrada zemljišta prije sadnje podloga Obrada zemljišta se sastoji od plitkog zaoravanja zelenišnog ili drugog organskog đubriva na dubini do 20 cm. Prije same sadnje potrebno je cijelu površinu obraditi roto-frezom.

Sadnja podloga Mjere koje treba preduzeti prije sadnje podloga su sljedeće: – skratiti korijen podloge 10 do 14 dana prije sadnje na dužinu 15 do 20 cm i potopiti ga, prije sadnje, u 1 % rastvor bakarnog preparata u cilju prevencije od raka korijena i stabla (Bacterium tumefaciens); – skratiti podlogu na 50 cm visine mjereno od korijenovog vrata; – neposredno prije sadnje korijen treba potopiti u smješu jednakih dijelova vode, gline i svježe kravlje balege u cilju boljeg kontakta zemlje i korijena. Sadnja se vrši ručno ili pomoću priključne mašine, koja može biti isplativa ako je broj podloga veći od 15000. Rastojanje između podloga je 80 – 120 cm x 30 – 40 cm što zavisi od bujnosti podloge. Ovih se rastojanja treba pridržavati u cilju dobijanja 42

kvalitetnih sadnica sa prijevremenim izdancima, a moguće ih je i povećati ako to zahtijeva zahvat mehanizacije za obradu i kontrolu korova.

Đubrenje u rasadniku Đubrenje u rastilu rasadnika podrazumijeva redovno dodavanje đubriva bogatih azotom kao što su: usitnjene uljne pogače, koštano, rožno ili krvno brašno, osoka, stajnjak, kompost i dr. Takođe se preporučuje i folijarno đubrenje ako za tim ima potrebe, ali ne prije pojave 3 do 5 razvijenih listova.

Navodnjavanje u rasadniku Adekvatno navodnjavanje je potrebno u prvih nekoliko mjeseci nakon sadnje da se osigura slijeganje zemljišta i dobar rast korijena. Proizvodnja bez navodnjavanja je nezamisliva na pjeskovitim zemljištima.

Redovna kontrola bolesti i štetočina Pažnja se mora obratiti na prve znake bolesti i prisustva štetočina. Tako se kod jabuke opaža pojava krastavosti

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(uljne mrlje na mladom lišću) i pepelnice (na izdancima i lišću javlja se bijela prevlaka nalik prahu), kao i prisustvo biljnih vaši ili crvenog pauka. Takođe se ne smije zanemariti preventiva šteta koju mogu nanijeti glodari mladim sadnicama.

prvoj godini podizanja voćnjaka. Kod sadnica bez prijevremenih izdanaka, u prvoj godini nakon sadnje prvo treba podsticati razvoj izdanaka na stablu, koji tek u narednoj godini mogu dati rod, što odlaže dobijanje roda i produžava investicioni period.

Kontrola korova u rasadniku

Kvalitetna sadnica mora posjedovati sljedeće karakteristike: – razvijen i zdrav korjenov sistem; – pravo deblo sa sazrelom korom, debljine 10 do 13 mm; – najmanje 4 prijevremena izdanka duža od 30 cm na visini od 70 do 100 cm i plitkog ugla grananja; – mjesto kalemljenja je 15 cm od korjenovog vrata; – osovina korijena je, najmanje, 30 cm duga.

Iako se u organskoj proizvodnji voća podstiče prisustvo pokrovnog rastinja, ono u rastilu rasadnika nije poželjno i treba ga redovno uništavati. Kako je upotreba herbicida zabranjena, zaštita od korova se vrši roto frezama ili gasnim kultivatorima (plamenom). Osnovna je obrada u prvim fazama rasta korova, pa se preporučuje obrada odmah nakon sadnje i nekoliko tokom vegetacije (po potrebi).

Kvalitet sadnica Jedan od najvažnijih faktora uspješne organske proizvodnje voća je kvalitet sadnica. Mora se garantovati tip ili klon podloge, uniformnost, porijeklo i kvalitet plemke, odsustvo bolesti, štetočina i mehaničkih oštećenja. Sve su traženije sadnice sa prijevremenim izdancima, jer mogu dati rod i u

Program razvoja organske poljoprivrede u Cr noj Gori

rak grana Nectria galligena

Izbjegavati sorte koje su veoma osjetljive na ovu bolest, kao što su: gala, gloster, ajdared, samerred i mekintoš. Koristiti sertifikovan sadni materijal. Održavati voćke u dobroj kondiciji. Obezbijediti drenažu zemljišta, ako postoji potreba za tim. Vršiti stalno praćenje simptoma ove bolesti, posebno u mladim voćnjacima. Zaražena stabla, posebno mlada, treba odmah ukloniti iz voćnjaka. Vršiti dezinfekciju alata za rezidbu.

Tokom rezidbe treba ukloniti zaražene ljetoraste, a rezove premazati sredstvom na bazi pčelinjeg voska i smole. Ako je primijećena infekcija, treba obaviti više tretiranja sredstvima na bazi bakra.

bakteriozna plamenjača Erwinia amylovora

Koristiti sertifikovan sadni materijal. Redovno suzbijati biljne vaši koje su prenosioci ove bakterije. Prilikom rezdbe treba uklanjati zaražene ljetoraste 20 cm ispod zaraženog mjesta, a nakon toga obavezno izvršiti dezinfekciju makaza za rezidbu.

bakar-sulfat tokom mirovanja

trulež plodova Monilinia fructigena

Uklanjati mumificirane plodove sa drveća, kao i otpale plodove, grane i lišće, posebno ako se primijeti prisustvo bolesti. Preduzeti sve mjere da se u zemljištu obezbijedi što veće prisustvo glista koje se hrane otpalim biljnim dijelovima. Nikako ne brati vlažne plodove za skladištenje. Obezbijediti brz transport do skladišta, kao i optimalne uslove u skladištu (temperatura i vlažnost vazduha).

Koristiti ekstrakte od rastavića ili hajdučke trave za povećanje otpornosti voćki.

Najčešće bolesti i mjere zaštite preventivne mjere

čađava krastavost Venturia inaequalis

pepelnica Podosphaera leucotricha

direktne mjere

Izbjegavati sorte koje su osjetljive na ovu bolest, kao što su: gala, zlatni delišes, mekintoš, gloster, rubinet, samerred ili jonagold. Pažljivo birati poziciju za podizanje organskog voćnjaka (ne smije se zadržavati magla i rosa, tj. mora postojati konstantna cirkulacija vazduha). Održavati voćke u dobroj kondiciji. Sakupljanjem i usitnjavanjem otpalog lišća tokom jeseni, broj spora koje izazivaju infekciju može se smanjiti i za 90%. Preduzeti sve mjere da se obezbijedi što veće prisustvo glista u zemljištu – hraneći se lišćem, mogu uništiti i do 90% spora V. inaequalis.

sredstva na bazi sumpora

Izbjegavati sorte koje su veoma osjetljive na ovu bolest, kao što su: jonagold, ajdared i mekintoš. Tokom kasne ljetnje i zimske rezidbe ukloniti zaražene izdanke i ljetoraste. Izbjegavati ranu rezidbu ako je napad veoma jak, jer će mladi izdanci i lišće takođe oboljeti.

sredstva na bazi sumpora

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Program razvoja organske poljoprivrede u Cr noj Gori

Najčešće štetočine i mjere zaštite preventivne mjere

lisne vaši

krvava vaš Eriosoma lanigerum

jabučna osica Hoplocampa testudinea

Spriječiti pretjerano bujan rast voćki. Podsticati prisustvo korisnih insekata kao što su bubamare, zlatooke, parazitske osice i dr. Postaviti oko debla u proljeće ljepljive trake za insekte, koje će spriječiti ulazak mrava u krošnje voćaka (mravi štite biljne vaši od njihovih prirodnih predatora).

meki sapun; ekstrakt koprive ili bijelog luka; azadirahtin prije cvjetanja; piretrin i rotenon nakon cvjetanja;

Izbjegavati sadnju osjetljivih sorti. Zaštititi voćke od mehaničkih povreda. Spriječiti bujan rast izdanaka.

Sredstva na bazi mekog sapuna, piretrina ili rotenona.

Nijesu poznate preventivne mjere zaštite.

Sredstva na bazi piretrina i rotenona protiv odraslih insekata. Sredstva na bazi kvazije protiv larvi.

cvjetojed jabuke Anthonomus pomorum

Nijesu poznate preventivne mjere zaštite.

smotavac jabuke Cydia pomonella

Sakupljanje otpalih zelenih plodova i njihovo kompostiranje, može značajno smanjiti potencijal napada ove štetočine.

direktne mjere

Najčešće bolesti i mjere zaštite preventivne mjere

direktne mjere

čađava krastavost Venturia pyrina

kao kod jabuke

bakteriozna plamenjača Erwinia amylovora

kao kod jabuke

Najčešće štetočine i mjere zaštite

rotenon/piretrin

granulose virus

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kruškina buva Cacopsylla pyri Cacopsylla pyricola Cacopsylla pyrisuga

preventivne mjere

direktne mjere

Podsticati prisustvo insekata predatora kao što je Anthocoris nemoralis, kojeg privlače cvjetnice tipa margareta ili suncokreta. Spriječiti bujan rast izdanaka, jer kruškina buva napada njihove vrhove.

Tretirati sredstvima na bazi piretrina nakon kiše. Sredstvo na bazi mekog sapuna ispira mednu rosu koju stvara kruškina buva i toksično djeluju na njene larve. Ovo sredstvo koristiti do kraja cvjetanja.

Program razvoja organske poljoprivrede u Cr noj Gori

Najčešće bolesti i mjere zaštite

Najčešće bolesti i mjere zaštite preventivne mjere

direktne mjere

Saditi otporne sorte (sorta Miker pokazuje otpornost). Ograničiti unošenje đubriva bogatih azotom. Prorjeđivati rodne izdanke. Iznijeti i uništiti oboljele izdanke nakon berbe.

sredstva na bazi bakra

smeđa pjegavost lišća Sphaerulina rubi

isto kao kod ljubičaste pjegavosti

siva trulež plodova Botryotinia fuckeliana

Ograničiti unošenje đubriva bogatih azotom. Brati zdrave, čvrste i suve plodove i odmah ih pakovati u ambalažu za prodaju.

Sredstva na bazi ekstrakta preslice čine malinu otporniju na ovu bolest, dok druge direktne mjere nijesu poznate.

uvenuće pupoljaka i rodnih izdanaka – ljubičasta pjegavost Didymella applanata

Najčešće štetočine i mjere zaštite preventivne mjere

direktne mjere

malinina buba Byturus tomentosus

Malinjake podizati dalje od šume.

Suzbija se mehanički, sakupljanjem i uništavanjem.

malinin prstenar Agrilus rubicola

Ukloniti iz malinjaka i uništiti zaražene izdanke.

Suzbija se mehanički, sakupljanjem i uništavanjem.

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preventivne mjere

direktne mjere

paunovo oko Byturus tomentosus

Sakupljati i iznositi iz maslinjaka otpalo lišće sa znacima bolesti.

sredstva na bazi bakra

čađavica Capnodium spp. Alternaria spp.

Vršiti redovnu i pravilnu rezidbu čime će se dobiti optimalna provjetrenost krošnje. Redovno suzbijati biljne vaši.

Medna rosa, na kojoj se čađavica javlja, spira se sredstvima na bazi mekog sapuna. Tokom ljeta se vrši tretiranje sredstvima na bazi bakarsulfata.

truljenje drveta Coriolus spp. Fomes spp. Stereum spp. Polyporus spp.

Održavati stabla masline u dobroj kondiciji, uz dovoljno hraniva. Spriječiti mehaničko oštećenje grana i stabla.

Odstraniti oboljelo tkivo stabla, dezinfikovati ranu sredstvom na bazi bakra i premazati sredstvom na bazi pčelinjeg voska i smole.

Program razvoja organske poljoprivrede u Cr noj Gori

Najčešće štetočine i mjere zaštite preventivne mjere

direktne mjere

maslinina muva Bactrocera oleae

Treba sakupljati otpale plodove i unuštivati ih izvan maslinjaka.

Kombinacija klopki sa mamcem, sredstava na bazi spinosada i kaolinitske gline.

maslinin moljac Prays olea

isto kao kod maslinine muve

azadirahtin i Bacillus thuringiensis

maslinin medić Saissetia oleae

Sakupljati i uništavati otpalo lišće napadnuto medićem. Podsticati prisustvo prirodnih predatora (bubamara).

maslinina buva Euphyllura olivina

Podsticati prisustvo prirodnih predatora.

Tretirati mineralnim uljem, najviše u 2 navrata tokom ljeta, manjim koncentracijama i pri nižim temperaturama (predveče). meki sapun i azadirahtin; mehanački uklanjati i uništavati legla larvi.

RECEPTI ZA PREPARATE Preparat od mekog sapuna Koristi se protiv biljnih vaši i gusjenica. Gubi efikasnost nakon sušenja, tako da ga treba koristiti pri višoj relativnoj vlažnosti vazduha, nižim temperaturama i kada nema vjetra. U suprotnom, koristiti ga u kasnim poslijepodnevnim časovima. Preparat koristiti do precvjetavanja, jer ostaci na plodovima mogu izazvati pojavu pjene prilikom pranja voća (kao kod svakog sapuna), što nije štetno po zdravlje, ali može izazvati nepovjerenje kod potrošača. Priprema se koncentracija od 5 do 8 g kalijumovog sapuna na 1 l vode. Kalijumov sapun se prodaje u prodavnicama boja i lakova. Neke vrste ili sorte voća mogu biti osjetljive na preparat, tako da treba

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napraviti probu na manjem broju grana i sa manjom koncentracijom, a zatim povećati ako se na voćkama ne registruju oštećenja. Sačekati 2 dana nakon prskanja na pojavu simptoma oštećenja na biljkama.

Preparat od sode bikarbone Koristi se preventivno protiv pepelnice kod voćaka, kao i kod drugih biljaka. Pripremiti koncentraciju od 10 do 15 g sode bikarbone na 10 l vode. Napraviti probu na jednom stablu ili manjem dijelu krošnje koristeći manju koncentraciju. Ako nakon 2 dana nema simptoma oštećenja, nastaviti prskanje ponavljajući ga u intervalu od 7 dana. Probu napraviti za svaku vrstu, kao i sortu voća posebno. Preparat je posebno koristan u početku vegetacije, dok su temperature suviše niske za

Program razvoja organske poljoprivrede u Cr noj Gori

upotrebu sumpora. Ako se pepelnica već pojavila ovo sredstvo je, ipak, ne može suzbiti, ali može spriječiti širenje.

Preparat od bijelog luka Koristi se preventivno protiv pepelnice, ali i protiv biljnih vaši i grinja. Potrebno je 75 g sitno isjeckanog ili zdrobljenog bijelog luka preliti sa 10 litara ključale vode, poklopiti i, nakon 1 sat, procijediti. Kao i prethodni, i ovaj preparat se koristi protiv pepelnice u početku vegetacije, dok se ne steknu temperaturni uslovi za upotrebu sumpora.

Preparat od hajdučke trave (Achillea millefolium) Koristi se kao preventivno sredstvo protiv pepelnice, truleži i drugih gljivičnih oboljenja. Potrebno je 2 kg svježih, odnosno 200 g suvih listova hajdučke trave držati tri dana u 10 litara vode uz povremeno miješanje. Ekstrakt dobijen nakon procjeđivanja razrijediti vodom u razmjeri 5:1 i time prskati biljke svakih 7 dana ili prema procjeni potencijala zaraze.

Preparat od rastavića (Equisetum arvense) Koristi se za povećanje otpornosti biljaka na pepelnicu, plamenjaču, rđu i druga gljivična oboljenja. Potrebno je 1 kg svježe biljke bez korijena potopiti u 10 litara vode tokom 24 časa, a nakon toga prokuvati 20 do 30 minuta. Ocijeđenu tečnost razrijediti vodom u razmjeri 5:1 i prskati voćke finim rasprskivačem.

LITER ATURA 1. Lind, K., Lafer, G., Schloffer, K., Innerhofer, G., Meister, H. (2003): Organic fruit growing. CABI Publishing, Oxon, United Kingdom. 2. Schmid, A., Weibel, F., Haseli, A. (2005): Dwarf tree orchard maintenance, Organic fruit growing, part 1 and Organic fruit growing, part 2. FiBL, Frick, Switzerland. 3. Znaor, D. (1996): Ekološka poljoprivreda. Globus, Zagreb, Hrvatska. 4. Radulović, M., Šturanović, M. (2009): Podizanje i održavanje voćnjaka i vinograda. Biotehnički fakultet, Univerzitet Crne Gore. 5. Miranović, K. (2006): Maslina. „Pobjeda“, Podgorica, Crna Gora. 6. Bjeliš, M. (2009): Zaštita masline u ekološkoj proizvodnji. Solin, Hrvatska. 7. Karoglan Todorović, S., Malić, D. (1997): Osnove biovrta i biopoljoprivrede. Znanje za okoliš, Zagreb, Hrvatska. 8. Veličković, N. (2007): Malina. Pegaz, Bijelo Polje, Crna Gora.

Preparat od koprive Koristi se protiv biljnih vaši i za jačanje biljaka. Za dobijanje preparata treba narezati 1 kg svježe koprive (nadzemni dio) i potopiti je u 10 litara vode. Pustiti da odstoji, najviše 24 časa i nakon toga procijediti. Preparat koristiti u kasnim popodnevnim časovima, prskajući finim rasprskivačem po napadnutim biljkama. Ako je došlo do jakog napada preporučuje se prskanje 3 dana zaredom, dok je u redovnim uslovima dovoljno ponavljati tretman u sedmodnevnom intervalu ili po potrebi.

PROI Z V O D N J A V O Ć A U O R G A N S K O J P O L J O P R I V R E D I

Program razvoja organske poljoprivrede u Cr noj Gori

januar

februar

za sve voćne vrste

jabuka

mart

april

maj 4

jun

jul

avgust

septembar 6

oktobar

novembar 7

decembar 1

3 B

šljiva

maslina

Kalendar radova za sve voćne vrste

mrazovca i drugih štetočina u krošnju gdje bi položile jaja; ukloniti iz krošnji sve mumificirane plodove i oštećene i zaražene grane (pepelnica) i zapaliti ih van voćnjaka (ova operacija se može izvršiti i kasnije tokom faze mirovanja); sakupiti lišće otpalo sa voćki, iznijeti ga iz voćnjaka i kompostirati.

postavljenih u krošnjama sa sunčane strane. Prag štetnosti predstavlja 20 do 50 osica uhvaćenih na jednoj tabli. U tom slučaju, preporučuje se tretman sredstvom na bazi piretrina/rotenona. Ako se sa ovim zakasni, treba tretirati larve u trenutku izlijeganja sredstvom na bazi kvazije. Treba potražiti oštećeni pupoljak, pažljivo ga otvoriti pomoću igle i pronaći jaje ose. Pupoljak se obilježava i ostavlja na grani, a jaje se svakodnevno provjerava sve do faze pojave crne tačkice na njemu. To je znak da će se larva izleći u narednih 1-3 dana, kada treba tretirati voćke. Kod sorti koje cvjetaju u različito vrijeme treba izvesti posebno praćenje trenutka izlijeganja larvi, a time i posebno prskanje. (C) Period vegetacije od kraja cvjetanja do berbe : Pepelnica i čađava krastavost jabuke – nastaviti sa prskanjem kvašljivim sumporom imajući na umu da se, sa povećanjem dnevne temperature iznad 28°C, uvećava opasnost od fitotoksičnosti. U tom slučaju smanjiti koncentraciju sredstva na najnižu preporučenu uputstvom za upotrebu i prskati samo u kasnim popodnevnim časovima. Interval između prskanja produžiti na 10 do 14 dana. Smotavac jabuke – kada temperature u predvečerje dostignu 13 do 15°C može se očekivati aktivnost odraslih jedinki prve generacije ove štetočine, čije ženke polažu jaja na starijim listovima blizu plodova, ili na samim plodovima. Jaja su okrugla i pljosnata, prečnika 1 mm, bijela do svijetlo-zelena. Ako se jaja primijete, treba pratiti trenutak izlijeganja larvi i u tom momentu prskati sredstvom na bazi granulose virusa. Prskati u samo predvečerje zbog osjetljivosti sredstva na UV zračenje. Tretman ponoviti nakon 5 do 7 dana ako je vrijeme sunčano i toplo, odnosno nakon 8 do 12 dana ako je hladno i kišovito. Praćenje napada druge generacije započeti tokom druge polovine jula i nastaviti tokom avgusta. Ako se uoče jaja, postupiti kao što je objašnjeno za prvu generaciju. Lisne vaši – u slučaju intenzivnog napada tretirati ekstraktom koprive 3 dana uzastopno ili sredstvima na bazi rotenona/piretrina u intervalu od 10 do 14 dana, dok traje napad vaši. Mlada stabla koja ne donose plod mogu se prskati mekim sapunom. (D) Kada otpadne najveći dio lišća potrebno je isprskati voćke sredstvom na bazi bakra u cilju preventive čađave krastavosti plodova, bakteriozne plamenjače i raka grana. Prskanje obaviti po lijepom vremenu i temperaturi iznad 10°C. Stabla temeljno isprskati.

(1) Rezidba se može obaviti tokom cijele fenofaze mirovanja, a preporučuje se neposredno prije početka vegetacije – u kasnu zimu ili rano proljeće. Obavezno je vršiti dezinfekciju alata za rezidbu, za šta se može koristiti alkohol ili 8% rastvor izbjeljivača u vodi. Nakon rezidbe orezane grane treba ukloniti iz voćnjaka, jako zaražene zapaliti, a ostale se mogu usitniti i kompostirati. Velike rezove premazati smješom voska i smole. U ovo doba godine vrši se uzorkovanje i analiza zemljišta i, na osnovu dobijenih rezultata, pravi plan đubrenja za predstojeću sezonu. (2) Napraviti plan fitosanitarnih mjera i naručiti zaštitna sredstva ako nijesu dostupna na domaćem tržištu; nabaviti stajsko đubrivo i rasuti ga prije početka vegetacije, zavisno od klimatskih uslova i sistema održavanja zemljišta; servisirati mehanizaciju; osmisliti strategiju prodaje i reklamiranja za predstojeću sezonu. (3) Provjeriti stanje postojećih i napraviti nova skloništa za solitane pčele, uholože i parazitske ose. Provjeriti kućice za ptice i popraviti one koje imaju oštećenja. (4) Izvršiti prorjeđivanje cvjetova na voćkama u slučaju prevelikog broja; pokositi travu unutar redova; obnoviti sloj malča ako se na taj način održava zemljište. (5) Tokom juna i jula vršiti zelenu rezidbu u cilju uklanjanja prirasta koji nepravilno rastu ili su oštećeni; navodnjavati po potrebi; vršiti prihranu stabala ako se pojave znaci deficita na lišću; nakon formiranja plodova ukloniti one koji smetaju normalnom razvoju ostalih ili koji su oštećeni; raditi na formiranju uzgojnog oblika mladih stabala; naručiti sadnice za eventualnu zamjenu u jesen. (6) Navodnjavati po potrebi; pripremiti ambalažu i opremu za berbu; pokositi rastinje unutar redova prije berbe i iznijeti ga, ako je potrebno, da ne smeta prilikom berbe i da ne bi pružalo zaklon glodarima nakon berbe. (7) Postaviti ljepljive trake oko stabla voćaka u cilju sprečavanja prelaska ženki malog

(A) Neposredno nakon rezidbe, tretirati stabla crvenim uljem koje djeluje protiv izazivača čađave krastavosti plodova, bakteriozne plamenjače, raka grana kao i prezimljujućih formi crvenog pauka, lisnih vaši, štitastih vaši i drugih štetočina. Stabla temeljno isprskati. (B) Period vegetacije, od aktiviranja pupoljaka do kraja cvjetanja, kritičan je za prevenciju najbitnijih bolesti i najopasnijih štetočina jabuke, kao što su: Pepelnica i čađava krastavost jabuke – nakon kretanja pupoljaka započeti sa tretiranjem sredstvom na bazi sode bikarbone sa ponavljanjima u intervalu od 7 dana. Kada srednja dnevna temperatura dostigne 12°C, preći na kvašljivi sumpor sa istim intervalom ponavljanja. Lisne vaši – reagovati na prvu pojavu lisnih vaši prskanjem vodenim rastvorom mekog (kalijumov) sapuna ili ekstraktom koprive. U slučaju jačeg napada tretirati sredstvom na bazi azadirahtina neposredno prije cvjetanja, zbog odloženog djelovanja. Cvjetojed jabuke – sa prvim toplim danima krajem februara i početkom marta, potrebno je, metodom stresanja grana, utvrditi prisustvo i brojnost odraslih insekata. Ako se testom utvrdi 10 i više insekata na 100 grana, preporučuje se tretiranje stabala sredstvom na bazi rotenona/piretrina. Jabučna osica – praćenje brojnosti odraslih formi vrši se pomoću bijelih ljepljivih tabli

(A) Nakon rezidbe, odnosno pred kretanje vegetacije neophodno je šljive isprskati bakarnim sredstvom i mineralnim uljem, ili crvenim uljem koje predstavlja kombinaciju ova dva pomenuta sredstva. Ovo se radi u cilju prevencije gljivičnih bolesti čiji izazivači, u nekoj formi, prezimljuju na kori ili pupoljcima npr. izazivač rogača šljive. Mineralno ulje je efikasno protiv prezimljujućih formi lisnih vaši, štitastih vaši, crvenog pauka itd. (B) U fazi cvjetnih pupoljaka u balonu započeti sa prskanjem sumporom, ili nekim alternativnim sredstvom ako se još nijesu stekli temperaturni uslovi za upotrebu

PROI Z V O D N J A V O Ć A U O R G A N S K O J P O L J O P R I V R E D I

Program razvoja organske poljoprivrede u Cr noj Gori

PROIZVODNJA VOĆA U ORGANSKOJ POLJOPRIVREDI

Jabuka

Šljiva

sumpora (sredstvo na bazi sode bikarbone, ekstrakt bijelog luka, hajdučke trave ili rastavića). (C) Nakon precvjetavanja nastaviti sa sumporom poštujući interval ponavljanja od 7 do 10 dana. Sa povećanjem dnevnih temperatura iznad 28°C produžiti vrijeme između tretiranja, smanjiti koncetraciju sredstva na najmanju preporučenu uputstvom za upotrebu, a voćke prskati u kasnim popodnevnim časovima. U samom precvjetavanju, kada se završi oplodnja cvjetova i krunični listići počnu otpadati, voćke treba isprskati rotenonom protiv šljivine osice. Tretman ponoviti još jednom nakon 7 dana. Pošto prva generacija šljivinog smotavca ne pričinjava značajne štete, tokom faze junskog otpadanja plodova treba se skoncentrisati na preduzimanje opisanih preventivnih mjera. Ako se tokom druge polovine jula i avgusta primijeti aktivnost odraslih štetočina, a zatim i pljosnata bijela jaja položena pojedinačno na dnu ploda, treba pratiti trenutak njihovog izlijeganja i tada prskati voćke sredstvom na bazi granulose virusa. Prskanje obaviti u kasnim popodnevnim časovima i ponoviti ga nakon 5 do 7 dana. (D) Kada otpadne najveći dio lišća potrebno je isprskati voćke sredstvom na bazi bakra u cilju preventive rogača šljive i drugih gljivičnih bolesti. Prskanje obaviti po lijepom vremenu i temperaturi iznad 10°C. Stabla temeljno isprskati.

Maslina (A) Nakon rezidbe, a prije početka vegetacije stabla treba temeljno isprskati nekim sredstvom na bazi bakra u cilju preventive gljivičnih bolesti paunovo oko i olovna bolest. Ako se, na osnovu zapažanja iz prethodne godine, sumnja na prisustvo prezimljujućih formi štetočina, može se koristiti crveno ulje. (B) U ovom periodu posebnu pažnju treba posvetiti zaštiti od sljedećih štetočina: Lisne vaši i maslinina buva – sa prvom pojavom ovih štetočina prskati vodenim rastvorom mekog sapuna ili ekstraktom koprive. U slučaju jačeg napada koristiti sredstvo na bazi azadirahtina neposredno prije cvjetanja. Maslinin moljac – pomenuti tretman azadirahtinom biće djelotvoran i protiv ove štetočine, a može se koristiti i Bacillus thuringiensis u trenutku otvaranja prvih cvjetova. Maslinina muva – u aprilu postaviti klopke tipa Mc Phail sa buminalom ili torula kvascem kao mamcem. Mamac mijenjati svake dvije nedelje. (C) Po potrebi nastaviti zaštitu od lisnih vaši ekstraktom koprive ili, u slučaju jačeg napada, sredstvom na bazi rotenona/piretrina. Kada se na žutim kontrolnim pločama pojave odrasle jedinke maslinine muve, treba početi sa tretiranjem stabala sredstvom na bazi spinosada sa intervalom ponavljanja od 7 dana. Od kraja avgusta pa sve do berbe, stabla treba prskati sredstvom na bazi kaolinitske gline što treba ponavljati po potrebi (ako kiša spere zaštitni sloj kaolinitske gline sa plodova). Sve ovo je nepotrebno ako monitoring u maslinjaku ili izvještaji stručnih službi ne upozoravaju na štete od maslinine muve.

Program razvoja organske poljoprivrede u Cr noj Gori

PROI Z V O D N J A V O Ć A U O R G A N S K O J P O L J O P R I V R E D I

LP Salik
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Banghay-Aralin sa Edukasyon sa Pagpapakatao 7 (Enero 21-31, 2019) I. Layunin: a. naipaliliwanag ang mga panloob na salik na nakaiimpluwensiya sa paghubog ng mga pagpapahalaga; b. nasusuri ang isang kilos batay sa isang panloob na salik na nakaiimpluwensya sa paghubog ng mga pagpapahalaga; c. nahihinuha na ang paglalapat ng mga panloob na salik sa pang araw-araw na buhay ay gabay sa paggawa ng mapanagutang pagpapasiya; d. naisasagawa ang mga tiyak na hakbang na ilalapat sa mga pang araw-araw na gawain at pagpapasiya na makatutulong sa paghubog ng bawat panloob na salik na nakaiimpluwensiya sa paghubog ng mga pagpapahalaga. II. Paksang-aralin: a. Paksa: Panloob na Salik na Nakaiimpluwensiya sa Paghubog ng mga Pagpapahalaga b. Sanggunian: Edukasyon sa Pagpapahalaga 7 (Learner’s and Teacher’s Guide) c. Kagamitan: telebisyon, manila paper, pentel pen, mga larawan III. Pamamaraan:

a. Pang araw-araw na Gawain

b. Pagganyak

c. Panlinang na Gawain

Panalangin W.o.W. (Words of Wisdom) Pagtala ng liban sa klase Pagbabalik-aral (Sa nakaraang aralin, naunawaan natin ang mahahalagang konsepto ukol sa Hirarkiya ng Pagpapahalaga. Naipaunawa na masisigurong gumagawa ka ng mabuti kung ang pagpapahalaga ay nasa mataas na antas.) Pagpapalabas ng short video clip ukol sa dalagang nagkaroon ng malaking transpormasyon: https://www.youtube.com/watch?v=TZSBvEn7M5Y Matapos ipalabas ang video, gawin ang pagpoproseso: 1. Tungkol saan ang video na pinanood? 2. Ano ang nais na maabot ng pangunahing tauhan sa video? Naabot niya ba ito? 3. Paano niya ito natupad? 4. Ano ang napulot na aral sa pinanood? Ipabasa sa klase ang mga sumusunod na case studies:

Proseso: 1. Anu-ano ang mga nag-udyok sa mga tauhan na gawin ang kanilang ginawa? 2. Magbigay ng 3 mahahalagang aral na natutuhan mula sa mabuting ginawa. 3. Nakikita mo ba nag sarili mo sa kanila? Ipaliwanag ang kasabihan na, “DO NOT JUST EXIST, LIVE.” Tumawag ng mag-aaral na maaaring magbigay paliwanag sa pahayag. Tanungin ang mga magaaral na iugnay ang video na kanilang pinanood at kasabihan na kanilang nabasa sa paksang-aralin.

d. Presentasyon

e. Pagpapalalim

Gawain: Panuto: Iayos ang jumbled letters upang malaman ang mga panloob na salik. 1. IYAOKNENSS 2. ANAKYALAA 3. NESIBOTSI 4. RITBUD 5. NAPASGILINR IDPISLIAN 6. ARLOM AN TINEGRDIDA Hatiin ang klase sa anim at bigyan ang bawat pangkat ng cue card na kung saan nakasulat ang kahulugan ng mga PANLOOB NA SALIK. Hayaan ang mag-aaral na tumuklas ng kahulugan ng bawat salik. Pagtalakay sa teksto sa pahina 230-232.

f. Pagsasabuhay

IV. Pagtataya: Tukuyin kung anong Panloob na Salik ang inilalarawan ng pahayag. _____________1. Ito ay ang pagsasaloob ng mga katotohanang pagpapahalagang moral.

unibersal

_____________2. Masasabi lamang na naging matagumpay ang pagtuturo ng Edukasyon sa Pagpapahalaga ng iyong guro o ng iyong mga magulang kung tunay mong isinasabuhay nang paulit-ulit ang iba’t ibang mga birtud _____________3. Ang pagtukoy sa pangkalahatang kabutihan o kasamaan ng kilos ng tao ay masusukat sa pamamagitan ng mga sumusunod: a. layon (end) – tumutukoy sa layunin, dahilan o intensiyon ng kilos at ng gumagawa ng kilos b. pamamaraan (means) – ay ang mismong kilos o gawa c. mga pangyayari (circumstances) – konsiderasiyon sa oras, lugar, paraan o ang tumutugon sa tanong na kailan, saan, paano o gaano. _____________4. Ito ay laging may kakambal na pananagutan. _____________5. Ito ang batas moral na itinanim ng Diyos sa isip at puso ng tao. V. Takdang-aralin: Basahin ang susunod na aralin: “Panlabas na Salik”.

2016 Tanah Pinem Dalam Angka
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Kecamatan

TANAH PINEM Subdistrict

Dalam Angka

In Figures

2016

No. Publikasi/Publication Number Katalog BPS/BPS Catalogue

: :

1210.16.016 1102001.1210.120

Ukuran Buku/Book Size Jumlah Halaman/Page

: :

15 cm x 21 cm xix + 119

Pengumpul Data/Collector Data: Koordinator Statistik Kecamatan Tanah Pinem Statistic Coordinator of Tanah Pinem Sub Regency Badan Pusat Statistik Kabupaten Dairi BPS-Statistics of Dairi Regency Penyunting/Editor/Editor: Seksi Integrasi Pengolahan dan Diseminasi Statistik (IPDS) Data Processing and Dissemination of Statistics Badan Pusat Statistik Kabupaten Dairi BPS-Statistics of Dairi Regency Gambar Kulit/Art Designer: Seksi Integrasi Pengolahan dan Diseminasi Statistik (IPDS) Data Processing and Dissemination of Statistics Badan Pusat Statistik Kabupaten Dairi BPS-Statistics of Dairi Regency Diterbitkan Oleh/Published by: CV. Bima masa Medan

Dilarang mengumumkan, mendistribusikan, mengomunikasikan, dan/atau menggandakan sebagian atau seluruh isi buku ini untuk tujuan komersil tanpa izin tertulis dari Badan Pusat Statistik Kabupaten Dairi Prohibited to announce, distribute, communicate,and/or copy part or all of this book for commercial purpose without permission from BPS-Statistics Dairi Regency”

PETA KECAMATAN TANAH PINEM

KATA PENGANTAR

Dengan memanjatkan puji syukur kehadirat Tuhan Yang Maha Kuasa, Koordinator Statistik Kecamatan Tanah Pinem dapat menyelesaikan buku “KECAMATAN TANAH PINEM DALAM ANGKA 2016“. Publikasi ini merupakan lanjutan dari publikasi tahun-tahun sebelumnya yang secara rutin dalam upaya menyediakan data statistik yang lengkap, akurat dan tepat waktu.

Berhasilnya usaha ini tidak lain adalah berkat kerjasama yang baik dan bantuan yang telah diberikan oleh Pemerintah Kabupaten serta instansi-instansi maupun Kelurahan/Desa yang ada di Kecamatan tersebut.

Semoga data ini dapat dipergunakan sebaik-baiknya, dan kami menyadari bahwa buku ini belum sempurna. Untuk itu kami mengharapkan saran dan kritik yang sehat demi perbaikan buku ini pada penerbitan tahun-tahun mendatang, terima kasih.

Sidikalang, Juni 2016 Badan Pusat Statistik Kabupaten Dairi Kepala

Anggiat Tulus Sibagariang

PREFACE

By blessing to God prayer, Statistic Coordinator of Tanah Pinem Sub Regency has been finished the publication “TANAH PINEM SUBDISTRICT IN FIGURES 2016”. This publication is following from the publication years before as continually published in the effort to prepare, accurate, timely, and complete statistic data.

Having finished this publication is because of good cooperation and attention from The Regional Government and also other institutions and Suburban/Village Government in this sub regency.

We hope this data can be used well, and we realize the unperfect of this publication. Therefore, we hope suggestion and critic from the user of this publication to perfect this publication in the future, thank you.

Sidikalang, Juni 2016 BPS–Statistics of Dairi Regency Chief,

Anggiat Tulus Sibagariang

Tanah Pinem Dalam Angka 2016

DAFTAR ISI/ CONTENTS Halaman Page Peta Kecamatan Tanah Pinem/ Map of Tanah Pinem Sub Regency …………..

iii

Kata Pengantar Kepala BPS Kabupaten Dairi/ Preface of Chief of BPSStatistics of Dairi Regency…………………………………………………………………….

Daftar Isi/ Contents ……………………………………………………………………………..

vii

Daftar Gambar/List of Picture……………………………………………………..

Daftar Tabel/ List of Tables…………………………………………………………………..

Daftar Lampiran/ List of Appendix…………………………………………………………..

xviii

BAB I

Letak dan Geografis/ Location and Geography ……………………………………….

BAB II

Pemerintahan/ Government………………………………………………………………….

BAB III

Penduduk/ Population………………………………………………………………………….

BAB IV

Sosial/ Social ……………………………………………………………………………………..

BAB V

Pertanian/ Agriculture ………………………………………………………………………….

BAB VI

Perindustrian/ Manufacturing ………………………………………………………………..

BAB VII

Perdagangan/ Trade……………………………………………………………………………

BAB VIII

Perhubungan dan Komunikasi/ Transportation and Communication…………………………………………………………………………………..

BAB IX

Keuangan/ Finance…………………………………………………………………..

Lampiran/Appendices …………………………………………………………………………..

Badan Pusat Statistik Kabupaten Dairi

| vii

Tanah Pinem Dalam Angka 2016

DAFTAR GAMBAR/ List of Pictures Halaman Page

Gambar : 2.1 Picture

Banyaknya Tenaga Kerja Menurut Lapangan Pekerjaan dan Desa/ Number of Labor by Education Level and Sex (orang/person)..

Gambar : 3.1 Picture

Penduduk Menurut Jenis Kelamin menurut Desa Population by Sex by Village (jiwa/person)……………………….

Gambar : 9.1 Picture

Besarnya Pokok Penetapan dan Realisasi Penerimaan Pajak Bumi dan Bangunan (PBB) Menurut Desa Number of Fixed Target and Realization of Land and Building Tax Revenue by Village (rupiah/rupiahs)…………………………

Badan Pusat Statistik Kabupaten Dairi

| ix

Kecamatan Tanah Pinem Dalam Angka 2016 DAFTAR TABEL/ LIST OF TABLES

Halaman Page Tabel : 1.1 Table

Letak dan Geografis Kecamatan Location and Geography of Tanah Pinem Sub Regency 2015 ………………………………………………………………………………………

Tabel : 1.2 Table

Jarak Kantor Kepala Desa ke Ibukota Kecamatan dan Alat Angkutan Menurut Desa The Distance from Village Chief Office to Sub Regency City and Transportation Mode by Village (km) …………………………………………..

Tabel : 1.3 Table

Luas Wilayah Menurut Desa Area and Ratio by Village ………………………………………………………….

Tabel : 1.4 Table

Rasio Terhadap Luas Kecamatan Menurut Desa/ Ratio on Subdistrict Area by Village 2015 ………………………………………………….

Tabel : 1.5 Table

Indeks Pembangunan Desa (IPD) di Kecamatan Tanah Pinem Village Development Index in Tanah Pinem Subregency 2015 ……….

Tabel : 1.6 Table

Desa Menurut Klasifkasi Village by Classification 2015 ……………………..

Tabel : 2.1 Table

Banyaknya Dusun Menurut Desa Number of Sub Village by Village 2015 ……………………………………….

Tabel : 2.2 Table

Desa Menurut Klasifikasi Village by Classification 2015 ……………………………………………………

Tabel : 2.3 Table

Banyaknya Tenaga Kerja Menurut Lapangan Pekerjaan dan Desa Number of Labor by Education Level and Sex (orang/person) 2015

Tabel : 2.4 Table

Banyaknya Pegawai Negeri Sipil (PNS) dan Honorer Menurut Dinas Number of Civil Servant and Honorarium by Agency (orang/person) 2015 ……………………………………………………………………………………..

Badan Pusat Statistik Kabupaten Dairi

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Tanah Pinem Subdistrict In Figures 2016 Tabel : 2.5 Table

Banyaknya Pegawai Negeri Sipil (PNS) Pada Kantor Camat Menurut Golongan Pangkat dan Jenis Kelamin Number of Civil Servant in Sub Regency Offce by Type of Rank and Sex (orang/person) 2015…………………………………………………

Tabel : 3.1 Table

Luas Wilayah, Banyaknya Penduduk, dan Kepadatan Penduduk Menurut Desa Area, Population and Population Density by Village 2015 ………………

Tabel : 3.2 Table

Penduduk Menurut Jenis Kelamin, Rasio Jenis Kelamin dan Desa Population by Sex, Sex Ratio and Village (jiwa/person) 2015 …………

Tabel : 3.3 Table

Banyaknya Penduduk, Rumah Tangga, dan Rata-rata Anggota Rumah Tangga (ART) Menurut Desa Population, Household and Average of Household Size by Village 2015 ……………………………………………………………………………………..

Tabel : 4.1 Table

Banyaknya Sekolah Dasar (SD) Negeri dan Swasta Menurut Desa Number of State and Private Primary Schools by Village (buah/unit) 2015 ……………………………………………………………………..

Tabel : 4.2 Table

Banyaknya Guru dan Murid Pada Sekolah Dasar (SD) Negeri dan Swasta Menurut Desa Number of Teachers and Pupils in State and Private Primary School by Village (orang/person) 2015 ………………………………………………….

Tabel : 4.3 Table

Banyaknya Guru Sekolah Dasar (SD) Menurut Tingkat Pendidikan dan Unit Sekolah Number of Teachers in Primary School by Education Level, and School Unit (orang/person) 2015 ……………………………………………….

Tabel : 4.4 Table

Banyaknya Guru Sekolah Dasar (SD) Menurut Status dan Unit Sekolah Number of Teachers in Primary School by Status, and School Unit (orang/person) 2015 ………………………………………………………………..

Tabel : 4.5 Table

Banyaknya Murid Sekolah Dasar (SD) Menurut Kelas dan Desa Number of Pupils in Primary School by Class and Village (orang/person) 2015 ………………………………………………………………..

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BPS-Statistic of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016 Tabel : 4.6 Table

Banyaknya Murid Sekolah Dasar (SD) Menurut Kelas, Jenis Kelamin, dan Unit Sekolah Number of Pupils in Primary School by sex, and School Units (orang/person) 2015 ………………………………………………………………..

Tabel : 4.7 Table

Banyaknya Sekolah Lanjutan Tingkat Pertama (SLTP) Negeri dan Swasta Menurut Desa Number of State and Private Junior High School by Village (buah/unit) 2015 ……………………………………………………………………..

Tabel : 4.8 Table

Banyaknya Guru dan Murid Pada Sekolah Lanjutan Tingkat Pertama (SLTP) Negeri dan Swasta Menurut Desa Number of Teachers and Pupils in State and Private Junior High School by Village (orang/person) 2015 ………………………………………

Tabel : 4.9 Table

Banyaknya Guru Sekolah Lanjutan Tingkat Pertama (SLTP) Menurut Tingkat Pendidikan dan Unit Sekolah Number of Teachers in Junior High School by Education Level and School Unit (orang/person) 2015 ……………………………………………….

Tabel : 4.10 Table

Banyaknya Guru Sekolah Lanjutan Tingkat Pertama (SLTP) Menurut Status Guru dan Unit Sekolah Number of Teachers in Junior High School by Status and School Unit (orang/person) 2015 ………………………………………………………….

Tabel : 4.11 Table

Banyaknya Murid Sekolah Lanjutan Tingkat Pertama (SLTP) Menurut Kelas, Jenis Kelamin, dan Unit Sekolah Number of Pupils in Junior High School by Class, Sex, and School Unit (orang/person) 2015 ……………………………………………….

Tabel : 4.12 Table

Banyaknya Murid Sekolah Lanjutan Tingkat Pertama (SLTP) Menurut Kelas dan Desa Number of Pupils in Junior High School by Class and Village (orang/person) 2015 ………………………………………………………………..

Tabel : 4.13 Table

Banyaknya Sekolah Menengah Umum (SMU) Negeri dan Swasta Menurut Desa Number of State and Private General Senior High School by Village 2015……………………………………………………………………………

Tabel : 4.14 Table

Banyaknya Guru dan Murid Pada Sekolah Menengah Umum (SMU) Negeri dan Swasta Menurut Desa Number of Teachers and Pupils in State and Private General Senior High School by Village (orang/person) 2015 ………………………………..

Badan Pusat Statistik Kabupaten Dairi

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Tanah Pinem Subdistrict In Figures 2016 Tabel : 4.15 Table

Banyaknya Guru Sekolah Menengah Umum (SMU) Menurut Tingkat Pendidikan dan Unit Sekolah Number of Teachers in General Senior High School by Education Level and School Unit (orang/person) 2015 …………………………………

Tabel : 4.16 Table

Banyaknya Guru Sekolah Menengah Umum (SMU) Menurut Status dan Unit Sekolah Number of Teachers in General Senior High School by Status and School Unit (orang/person) 2015 ……………………………………………….

Tabel : 4.17 Table

Banyaknya Murid Sekolah Menengah Umum (SMU) Menurut Kelas, Jenis Kelamin dan Unit Sekolah Number of Pupils in General Senior High School by Class, Sex, and School Unit (orang/person) 2015 ……………………………………………….

Tabel : 4.18 Table

Banyaknya Murid Sekolah Menengah Umum (SMU) Menurut Kelas dan Desa Number of Pupils in General Senior High School by Class and Village (orang/person) 2015………………………………………………………

Tabel : 4.19 Table

Banyaknya Sarana Kesehatan Umum Menurut Jenis dan Desa Number of Public Health Facility by Types and Village (buah/unit) 2015 ……………………………………………………………………………………..

Tabel : 4.20 Table

Banyaknya Tenaga Medis Menurut Klasifikasi dan Desa Number of Medical Servant by Classification and Village (orang/person) 2015 ………………………………………………………………..

Tabel : 4.21 Table

Banyaknya Wanita Usia Subur 15-49 Tahun (WUS) dan Pasangan Usia Subur (PUS) Menurut Desa Number of Fertile Age Couple by Type of Contraceptive Used and Village (pasangan/couple) 2015…………………………………………………

Tabel : 4.22 Table

Banyaknya Pasangan Usia Subur 15-49 Tahun ( PUS) yang Menggunakan Kontrasepsi Menurut Desa Number of Ever Merrit Women and Fertile Couples by Village (pasangan/couple) 2015 ………………………………………………………….

Tabel : 4.23 Table

Banyaknya Pasangan Usia Subur (PUS) Menurut Jenis Alat Kontrasepsi yang digunakan dan Desa Number of Fertile Age Couple by Type of Contraceptive Used and Village (pasangan/couple) 2015…………………………………………………

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BPS-Statistic of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016 Tabel : 4.24 Table

Banyaknya Keluarga Pra KS, KS-1, KS-2, KS-3 dan KS-3 Plus Menurut Desa Number of Pra Prosperous, 1 st Prosperous, 2 st Prosperous, 3 st Prosperous, and 3 st Plus Prosperous Household by Village (pasangan/couple) 2015 ………………………………………………………….

Tabel : 4.25 Table

Banyaknya Rumah Menurut Jenis Bangunan dan Desa Number of House by Type of Building and Village (buah/unit) 2015…

Tabel : 5.1 Table

Luas Panen, Produksi, dan Produktivitas Padi Sawah Menurut Desa Harvest Area, Production and Productivity of Wet Land Paddy by Village 2015……………………………………………………………………………

Tabel : 5.2 Table

Luas Panen, Produksi, dan Produktivitas Padi Ladang Menurut Desa Harvest Area, Production and Productivity of Dry Land Paddy by Village 2015……………………………………………………………………………

Tabel : 5.3 Table

Luas Lahan Sawah Menurut Jenis Irigasi dan Desa Area of Wet Land Paddy by Type of Irrigation and Village (ha) 2015 .

Tabel : 5.4 Table

Luas Tanaman Palawija Menurut Jenis Tanaman dan Desa/Kelurahan Planting Area of Crop by Types of Plant and Village/Suburban (ha) 2015 ……………………………………………………………………………… Produksi Tanaman Palawija Menurut Jenis Tanaman dan Desa Production of Crop by Types of Plant and Pest and Village (ha) 2015 ……………………………………………………………………………….

Tabel : 5.5 Table

Tabel : 5.6 Table

Produksi Buah-buahan Menurut Jenisnya Production of Fruits by Types (ton) 2015 …………………………………….

Tabel : 5.7 Table

Luas Tanaman Perkebunan Rakyat Menurut Jenis Tanaman dan Desa Planting Area of Smallholder Estate by Types of Plant and Village (ha) 2015 ……………………………………………………………………………….

Tabel : 5.8 Table

Produksi Tanaman Perkebunan Rakyat Menurut Jenis Tanaman dan Desa Production of Smallholder Estate by Types of Plant and Village (ton) 2015 ……………………………………………………………………………………..

Badan Pusat Statistik Kabupaten Dairi

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Tanah Pinem Subdistrict In Figures 2016 Tabel : 5.9 Table

Luas Panen, Produksi, dan Produktivitas Sayur-sayuran Menurut Jenisnya Harvest Area, Production, and Productivity of Vegetables by Types (ton) 2015 ……………………………………………………………………………..

Tabel : 5.10 Table

Banyaknya Kelompok Tani (Poktan) dan Golongan Kelompok Tani (Gapoktan) Menurut Desa Number of Farmer Group and Combinatin of Farmer Group by Village (ha) 2015 ………………………………………………………………………………

Tabel : 5.11 Table

Banyaknya Ternak Menurut Jenisnya dan Desa Number of Livestock by Types and Village (ekor/tail) 2015 …………….

Tabel : 5.12 Table

Banyaknya Ternak Unggas Menurut Jenisnya dan Desa Number of Poultry by Types and Village (ekor/tail) 2015………………..

Tabel : 5.13 Table

Produksi Ikan Tawar Menurut Desa Production of Water Fish by Village (ton/ton) 2015 ……………………….

Tabel : 6.1 Table

Banyaknya Industri dan Pertambangan/ Galian C Menurut Jenis dan Desa Number of Worker Service by Types and Village (perusahaan/establishment) 2015………………………………………………

Tabel : 6.2 Table

Banyaknya Kilang Padi dan Pedagang Eceran Menurut Desa Number of Paddy Factory and Retailer by Village (perusahaan/establishment) 2015………………………………………………

Tabel : 6.3 Table

Banyaknya Jasa Pertukangan Menurut Jenis dan Desa Number of Worker Service by Types and Village 2015 ………………….

Tabel : 6.4 Table

Banyaknya Bengkel Menurut Jenis Bengkel dan Desa Number of Workshop by Types and Village (usaha/establishment) 2015 ……………………………………………………………………………………..

Tabel : 6.5 Table

Banyaknya Rumah Tangga Pelanggan Listrik Menurut Desa Number of Electricity Customers Household by Village (rumahtangga/household) 2015 …………………………………………………

Tabel : 6.6 Table

Banyaknya Rumah Tangga Pelanggan PAM Menurut Desa Number of Drinking Water Customers by Village (rumahtangga/household) 2015 …………………………………………………

Tabel : 7.1 Table

Banyaknya Warung Nasi Menurut Desa Number of Traven Rice by Village (buah/unit) 2015 ………………………

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BPS-Statistic of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016 Tabel : 7.2 Table

Banyaknya Jasa Perseorangan Menurut Jenisnya dan Desa Number of Individual Service by Type and Village (buah/unit) 2015…

Tabel : 8.1 Table

Banyaknya Sarana Angkutan Menurut Jenis dan Desa Number of Transportation Facility by Types and Village (buah/unit) 2015 ……………………………………………………………………………………..

Tabel : 8.2 Table

Banyaknya Rumah Tangga Pemilik Televisi dan Antena Parabola Menurut Desa Number of Household Who own The Television and Parabola Antena by Village (rumahtangga/household) 2015………………………..

Tabel : 9.1 Table

Badan Pusat Statistik Kabupaten Dairi

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Kecamatan Tanah Pinem Dalam Angka 2016

DAFTAR LAMPIRAN/ LIST OF APPENDIX Halaman Page Lampiran : 1 Appendix

Nama-Nama Camat Tanah Pinem Menurut Tahun Masa Jabatan Names of Chief of Tanah Pinem Sub Regency by Years of Duty Period …………………………………………………………………..

Lampiran : 2 Appendix

Nama-Nama Kepala Kepolisian Sektor (Kapolsek) Kecamatan Tanah Pinem Menurut Tahun Masa Jabatan Name of Chief of Police Station Sector of Tanah Pinem Sub Regency by Years of Duty Period 2015 ……………………………..

Lampiran : 3 Appendix

Nama Kepala Desa Menurut Jenis Kelamin, Status, dan Desa Names of Village Chief by Sex, Status and Village 2015………

Lampiran : 4 Appendix

Nama Kepala Muspika Menurut Jabatan dan Pangkat Names of Muspika by Position and Rank 2015 …………………..

Lampiran : 4 Appendix

Daftar Nama Dusun dan Nama Kepala Dusun Menurut Desa Names of Hillbily and Their Name by Village 2015 ………………

Badan Pusat Statistik Kabupaten Dairi

xix

Kecamatan Tanah Pinem Dalam Angka 2016

Badan Pusat Statistik Kabupaten Dairi

Tanah Pinem Subdistrict in Figures 2016

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

BAB I LETAK GEOGRAFIS

Kecamatan Tanah Pinem memiliki batas-batas sebagai berikut :

– Sebelah Utara berbatasan dengan Kabupaten Karo – Sebelah Timur berbatasan dengan Provinsi Nanggroe Aceh Darusallam – Sebelah Selatan berbatasan dengan Kecamatan Tigalingga, Kecatan Gunung Sitember, dan Kecamatan Siempat Nempu Hillir – Sebelah Barat berbatasan dengan Kabupaten Karo

Kecamatan Tanah Pinem merupakan Kecamatan di Dairi yang paling besar ke 1 berdasarkan luas wilayahnya, yang mencapai 439.40 km2 . Wilayah administrasi desa yang terbesar adalah Desa Suka Dame yang mencapai luas 75,00 km2 atau sebesar 17.06 persen dari luas total Kecamatan 439.40 km2 Secara topografis, wilayah Kecamatan Tanah Pinem berada di daratan. Apabila ditarik garis lurus dari ibukota kecamatan, maka Desa Suka Dame dan Desa Alur Subur adalah desa yang terjauh, yaitu mencapai 55 km dan 46 km.

Badan Pusat Statistik Kabupaten Dairi

Tanah Pinem Subdistrict in Figures 2016

CHAPTER I LOCATION AND GEOGRAPHIC

Tanah Pinem have boundaries as follows :

– North side adjacent to Karo – To the East with the Province of Nanggroe Aceh Darussalam – South side is bordered by the District Tigalingga , Kecatan Mount Sitember , and District Siempat Nempu Hillir – West borders with Karo

Tanah Pinem the Dairi District in the greatest to one based on the vast territory, which reached 439.40 km2 . The administrative area of the village is the village of Suka Dame is wide reaching 75.00 km2 or at 17:06 per cent of the total area of 439.40 km2 Topographically the District , the District of Land Pinem on the mainland . If a straight line drawn from the capital district , the village of Suka Dame and the village of Alur Subur is the furthest village , which reached 55 km and 46 km .

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : Table

1.1

Letak dan Geografis Kecamatan Location and Geography of Tanah PinemSub Regency 2015

1. Geografis Kecamatan Tanah Pinem Geography of Tanah Pinem Sub Regency

Lintang Utara/ North Latitude

20 53’ – 3007’

980 30’ – 98045’

Bujur Timur/ East Longitude

43 940

km²

2. Luas Wilayah/ Area

3. Letak di atas Permukaan Laut/ Heights Above Sea Level

650 – 950

meter

4. Batas-Batasnya/Boundaries a. Sebelah Utara/Northern

Kabupaten Karo/ Karo Sub Regency Kecamatan Tigalingga, Kecatan Gunung Sitember, dan Kecamatan Siempat Nempu Hillir/ Tigalingga Sub Regency, Gunung Sitember Sub Regency dan Siempat Nempu Hilir Sub Regency

b. Sebelah Selatan/Southern

c. Sebelah Barat/Western

Kabupaten Karo/ Karo Regency

d. Sebelah Timur/Eastern

Provinsi Nanggroe Aceh Darusallam/ Nanggroe Aceh Darusallam Province

55 km

5. Jarak Kantor Camat ke Kantor Bupati Dairi/ The Distance from Sub Regency Office to Regency Office

Sumber Source

: :

Badan Pusat Statistik (BPS) Kabupaten Dairi BPS – Statistics of Dairi Regency

Badan Pusat Statistik Kabupaten Dairi

Tanah Pinem Subdistrict in Figures 2016

Tabel : 1.2 Table

Jarak Kantor Kepala Desa ke Ibukota Kecamatan dan Alat Angkutan Menurut Desa The Distance from Village Chief Office to Sub Regency City and Transportation Mode by Village (km)

Desa/Village

Jarak (km)

Akses/Sarana Transportasi Transportation Mode

(1)

(2)

(3)

1. Renun

22,00

Jeep

2. Pasir Tengah

15,00

Beca/Ojek

6,00

Beca/Ojek

3. Pamah 4. Kuta Buluh

–

5. Tanah Pinem

15,00

Beca/Ojek

6. Kempawa

27,00

Beca/Ojek

7. Kuta Gamber

29,00

Beca/Ojek

8. Lau Primbon

26,00

Beca/Ojek

9. Harapan

25,00

BEca/Ojek

10. Gunung Tua

32,00

Beca/Ojek

11. Sukadame

55,00

Beca/Ojek

12. Lau Tawar

17,00

Beca/Ojek

13. Mangan Molih

20,00

Jeep

14. Lau Njuhar I

30,00

Jeep

15. Liang Jering

38,00

Jeep

16. Alur Subur

46,00

Jeep

17. Balandua

5,00

Beca

18. Pasir Mbelang

11,00

Ojek

19. Sinar Pagi

36,00

Jeep

Sumber : Kepala Desa Se-Kecamatan Tanah Pinem Source : Whole Village Chief of Tanah Pinem Sub Regency

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 1.3 Table

Luas Wilayah Menurut Desa Area by Village 2015

Luas Area (km2)

Desa/Village

(1) 1. Renun

(2) 8,00

2. Pasir Tengah

52,00

3. Pamah

36,42

4. Kuta Buluh

29,00

5. Tanah Pinem

10,00

6. Kempawa

16,00

7. Kuta Gamber

16,28

8. Lau Primbon

29,00

9. Harapan

32,70

10. Gunung Tua

39,00

11. Sukadame

75,00

12. Lau Tawar

10,00

13. Mangan Molih

8,00

14. Lau Njuhar I

14,00

15. Liang Jering

11,00

16. Alur Subur

12,00

17. Balandua

16,00

18. Pasir Mbelang

17,00

19. Sinar Pagi

8,00 Jumlah / Total

439,40

Sumber : Kantor Kecamatan Tanah Pinem Source : Village Chief of Tanah Pinem Sub Regency

Badan Pusat Statistik Kabupaten Dairi

Tanah Pinem Subdistrict in Figures 2016

Tabel : 1.4 Table

Rasio Terhadap Luas Kecamatan Menurut Desa Ratio on Sub Regency Area by Village 2015

Desa/Village

Rasio Terhadap Total Kecamatan Ratio on Total of Sub Regency Area (%)

(1)

(3)

1. Renun 2. Pasir Tengah

1,82 11,83

3. Pamah

8,29

4. Kuta Buluh

6,60

5. Tanah Pinem

2,28

6. Kempawa

3,64

7. Kuta Gamber

3,71

8. Lau Primbon

6,60

9. Harapan

7,44

10. Gunung Tua

8,88

11. Sukadame

17,07

12. Lau Tawar

2,28

13. Mangan Molih

1,82

14. Lau Njuhar I

3,19

15. Liang Jering

2,50

16. Alur Subur

2,73

17. Balandua

3,64

18. Pasir Mbelang

3,87

19. Sinar Pagi

1,82

Jumlah / Total

100,00

Sumber : Kantor Kecamatan Tanah Pinem Source : Village Chief of Tanah Pinem Sub Regency

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016 Tabel : 1.5 Table

Indeks Kesulitan Geografis (IKG) Kecamatan Tanah Pinem Geographic Difficulty Index District of Tanah Pinem 2014 Indeks Perdimensi

Desa/Village

IKG

Jumlah Penduduk 2014

(1)

(2)

(3)

Jumlah Penduduk Miskin 2014 (4)

Renun

52.67

818

9.48

Pasir Tengah

45.75

1484

40.77

Pamah

39.18

2116

41.99

Kuta Buluh

28.69

1883

32.00

Tanah Pinem

28.80

1283

11.85

Kempawa

62.80

806

18.96

Kuta Gamber

47.50

740

16.95

Lau Primbon

49.59

1061

29.63

Harapan

27.19

1957

38.75

Gunung Tua

47.54

453

16.59

Sukadame

54.06

1119

134

53.33

Lau Tawar

28.90

1261

11.85

Mangan Molih

58.59

784

9.48

Lau Njuhar I

52.18

1391

144

16.59

Liang Jering

74.13

793

13.04

Alur Subur

74.33

615

10.80

Balandua

46.02

776

17.04

Pasir Mbelang

64.07

922

20.15

Sinar Pagi

70.75

544

9.48

Luas Desa Km2 (5)

Sumber : Badan Pusat Statistik Kabupaten Dairi Source : Statistict of Dairi Regency

Badan Pusat Statistik Kabupaten Dairi

Tanah Pinem Subdistrict in Figures 2016 Desa Menurut Klasifikasi Village by Classification 2014

Tabel : 1.6 Table

Desa/Village

Desa Tertinggal

Desa Berkembang

Desa Mandiri

(1)

(2)

(3)

(4)

1. Renun



2. Pasir Tengah



3. Pamah



4. Kuta Buluh



5. Tanah Pinem



6. Kempawa



7. Kuta Gamber



8. Lau Primbon



9. Harapan



10. Gunung Tua



11. Sukadame



12. Lau Tawar



13. Mangan Molih



14. Lau Njuhar I



15. Liang Jering



16. Alur Subur



17. Balandua



18. Pasir Mbelang



19. Sinar Pagi



Jumlah / Total

Sumber : Badan Pusat Statistik Kabupaten Dairi Source : Statistict of Dairi Regency

10 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Badan Pusat Statistik Kabupaten Dairi

| 11

Tanah Pinem Subdistrict in Figures 2016

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BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

BAB II PEMERINTAHAN

Kecamatan Tanah Pinem terdiri dari 19 desa yang status hukumnya sudah menjadi desa definitif , dimana setiap desa dipimpin oleh kepala desa. Dilihat dari status pemerintahannya, kecamatan Tanah Pinem terdiri dari 66 Dusun.

Tingkat partisipasi perempuan dalam menjalankan pemerintahan di Kantor Kecamatan Tanah Pinem sangat membanggakan Sebanyak 8 orang adalah perempuan dari total 15 Pegawai di Kantor Kecamatan Tanah Pinem atau sebesar 53.33 persen.

Badan Pusat Statistik Kabupaten Dairi

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Tanah Pinem Subdistrict in Figures 2016

CHAPTER II GOVERMENT

Tanah Pinem consists of 19 villages that legal status has become definitive village , where every village is led by the village head . Judging from the status of his administration , district Pinem Land consists of 66 Hamlet .

The level of women’s participation in running the government at the District Office Land Pinem very proud total of 8 people were women of a total of 15 clerks at the District Office Land Pinem or by 53.33 percent .

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BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 2.1 Table

Banyaknya Dusun Menurut Desa Number of Sub Village by Village 2015

Desa/Village

Banyaknya Dusun/ Number of Sub Village

(1)

(2)

1. Renun

2. Pasir Tengah

3. Pamah

4. Kuta Buluh

5. Tanah Pinem

6. Kempawa

7. Kuta Gamber

8. Lau Primbon

9. Harapan

10. Gunung Tua

11. Sukadame

12. Lau Tawar

13. Mangan Molih

14. Lau Njuhar I

15. Liang Jering

16. Alur Subur

17. Balandua

18. Pasir Mbelang

19. Sinar Pagi

Jumlah/Total

Sumber : Kantor Kecamatan Tanah Pinem Source : Tanah Pinem Sub Regency Office

Badan Pusat Statistik Kabupaten Dairi

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Tanah Pinem Subdistrict in Figures 2016 Tabel : 2.2 Table

Desa Menurut Klasifikasi Village by Classification 2015

Desa/ Villages Desa/Village

Swadaya/ Initiate Strength

Swakarya/ Self Developing

(2)

(3)

(4)

1. Renun

–

2. Pasir Tengah

–

3. Pamah

–

4. Kuta Buluh

–

5. Tanah Pinem

–

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

(1)

Jumlah/Total

Swasembada/ Self Sufficient

Sumber : Kaur Bang Kecamatan Tanah Pinem Source : Chief Section of Development at Tanah Pinem

16 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Gambar : 2.1 Pictue

Banyaknya Tenaga Kerja Menurut Lapangan Pekerjaan dan Desa/ Number of Labor by Education Level and Sex (orang/person) 2015

Badan Pusat Statistik Kabupaten Dairi

| 17

Tanah Pinem Subdistrict in Figures 2016

Tabel : 2.3 Table

Banyaknya Tenaga Kerja Menurut Lapangan Pekerjaan dan Desa/ Number of Labor by Education Level and Sex (orang/person) 2015

Tingkat Pendidikan/ Education Level (1)

Jenis Pekerjaan Pertanian/ Industri/ PNS/Honor /ABRI Agriculture Indutry (2) (3) (4)

Lainnya/ Another (5)

Jumlah/ Total (6)

1. Renun

448

–

2. Pasir Tengah

924

–

967

3. Pamah

1 521

–

1597

4. Kuta Buluh

437

1 168

135

1341

5. Tanah Pinem

684

–

751

6. Kempawa

438

–

459

7. Kuta Gamber

461

–

482

668

–

692

1 140

–

1197

10. Gunung Tua

221

–

239

11. Sukadame

779

–

794

12. Lau Tawar

948

1004

13. Mangan Molih

528

–

545

14. Lau Njuhar I

933

–

954

15. Liang Jering

421

–

435

16. Alur Subur

352

–

362

17. Balandua

452

487

18. Pasir Mbelang

647

–

686

19. Sinar Pagi

230

–

242

12 963

438

461

273

8. Lau Primbon 9. Harapan

Jumlah/Total

Sumber : Kantor Camat Tanah Pinem Source : Tanah Pinem Sub Regency Office

18 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016 Tabel : 2.4 Table

Banyaknya Pegawai Negeri Sipil (PNS) dan Honorer Menurut Dinas Number of Civil Servant and Honorarium by Agency (orang/person) 2015

Tingkat Pendidikan/ Education Level

PNS

Honorer

(1)

(2)

(3)

–

4. KUA

–

5. PPLKB

–

6. PPL Pertanian/Peternakan

7. Kantor Pos

–

155

104

10. Guru SMA/Tenaga ADM

11. Guru SMK/Tenaga ADM

Jumlah/Total

280

172

1. Kantor Camat 2. UPT Dinas Pendidikan Dasar 3. Puskesmas dan Tenaga Kesehatan

8. Guru SD/Tenaga ADM 9. Guru SLTP/Tenaga ADM

Sumber : Kantor Camat Tanah Pinem Source : Tanah Pinem Sub Regency Office

Badan Pusat Statistik Kabupaten Dairi

| 19

Tanah Pinem Subdistrict in Figures 2016

Tabel : 2.5 Table

Banyaknya Pegawai Negeri Sipil (PNS) Pada Kantor Camat Menurut Golongan Pangkat dan Jenis Kelamin Number of Civil Servant in Sub Regency Offce by Type of Rank and Sex (orang/person) 2015

Golongan Pangkat/ Groups (1)

Jenis Kelamin/Sex Laki-laki/ Male

Perempuan/ Female

Jumlah/ Total

(2)

(3)

(4)

–

IIa

–

IIb

–

IIc

–

IId

–

IIIa

–

IIIb

III IIIc IIId

IVa

–

IVb

IVc

–

IVd

–

Jumlah/Total

Sumber : Kantor Camat Tanah Pinem Source : Tanah Pinem Sub Regency Office

20 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Badan Pusat Statistik Kabupaten Dairi

| 21

Tanah Pinem Subdistrict in Figures 2016

22 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

BAB III KEPENDUDUKAN

Jumlah Penduduk Kecamatan Tanah Pinem pada tahun 2015 adalah 20993 jiwa, yang terdiri dari 10481 jiwa laki-laki dan 10512 jiwa perempuan. Dari komposisi jumlah laki-laki dan perempuan tersebut, Kecamatan Tanah Pinem memiliki nilai sex rasio sebesar 99.67, hal ini menunjukkan bahwa dalam 100 jiwa perempuan terdapat 99 jiwa laki-laki.

Dengan luas wilayah 439,40 km2 dan jumlah penduduk 20993 jiwa, ternyata menghasilkan kepadatan penduduk sebesar 47 49, yang artinya dalam setiap 1 km² dihuni oleh sekitar 48 orang.

Kecamatan Tanah Pinem mempunyai 5 733 jumlah keluarga dengan rata-rata jumlah warga dalam keluarga adalah 4 orang. Jumlah tersebut hampir merata di semua desa.

Badan Pusat Statistik Kabupaten Dairi

| 23

Tanah Pinem Subdistrict in Figures 2016

CHAPTER III POPULATION

Population Tanah Pinem in 2015 was 20 993 people, consisting of 10481 souls 10512 male and female psyche . From the composition of the number of men and women , the District Land Pinem sex ratio has a value of 99.67 , this suggests that in women’s 100 inhabitants are 99 male psyche .

With an area of 439.40 km2 and a population of 20 993 inhabitants , it produces a population density of 47 49 , which means that each 1 km² inhabited by about 48 people .

Tanah Pinem has 5733 number of families with an average number of people in the family is four people . The amount is almost uniformly in all villages .

24 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016 Tabel : 3.1 Table

Luas Wilayah, Banyaknya Penduduk, dan Kepadatan Penduduk Menurut Desa Area, Population and Population Density by Village 2015

Desa/Village

(1) 1. Renun

Luas/ Area (km2)

Penduduk/ Population (jiwa)

(2)

(3)

Kepadatan Penduduk/ Population Density (jiwa/km2) (4)

8,00

757

99,00

2. Pasir Tengah

52,00

1,379

26,35

3. Pamah

36,42

2,258

61,56

4. Kuta Buluh

29,00

1,861

63,90

5. Tanah Pinem

10,00

1.249

124,60

6. Kempawa

16,00

796

49,63

7. Kuta Gamber

16,28

776

47,54

8. Lau Primbon

29,00

1 126

38,76

9. Harapan

32,70

1 863

56,48

10. Gunung Tua

39,00

452

11,54

11. Sukadame

75,00

1 229

16,36

12. Lau Tawar

10,00

1 282

127,40

8,00

754

94,13

14. Lau Njuhar I

14,00

1 491

106,29

15. Liang Jering

11,00

855

76,82

16. Alur Subur

12,00

628

51,58

17. Balandua

16,00

799

49,56

18. Pasir Mbelang

17,00

952

55,63

8,00

446

47,49

439,40

20 993

13. Mangan Molih

19. Sinar Pagi Jumlah/Total

47 49

Sumber : Badan Pusat Statistik (BPS) Kabupaten Dairi – Hasil Proyeksi Penduduk 2015 Source : BPS-Statistics of Dairi Regency – Projection Figure of Population 2015

Badan Pusat Statistik Kabupaten Dairi

| 25

Tanah Pinem Subdistrict in Figures 2016

Tabel : 3.2 Table

Penduduk Menurut Jenis Kelamin, Rasio Jenis Kelamin dan Desa Population by Sex, Sex Ratio and Village (jiwa/person) 2015

Jenis Kelamin/Sex Desa/Village

(1)

Laki-laki/ Male

Rasio Jenis Kelamin/ Sex Ratio

(4)

(5)

1. Renun

383

414

797

92.23

2. Pasir Tengah

690

689

1 379

100.00

1 118

1 140

2 285

98.06

4. Kuta Buluh

928

933

1 861

99.25

5. Tanah Pinem

605

644

1 249

93.78

6. Kempawa

399

397

796

100.51

7. Kuta Gamber

389

387

776

101.04

8. Lau Primbon

545

581

1 126

94.13

9. Harapan

930

933

1 863

99.68

10. Gunung Tua

224

228

452

98.24

11. Sukadame

641

588

1 229

109.03

12. Lau Tawar

624

658

1 282

94.80

13. Mangan Molih

373

381

754

98.16

14. Lau Njuhar I

766

725

1 491

105.87

15. Liang Jering

436

419

855

103.61

16. Alur Subur

328

300

628

109.12

17. Balandua

395

404

799

97.76

18. Pasir Mbelang

460

492

952

93.24

19. Sinar Pagi

247

199

446

123.62

3. Pamah

Jumlah/Total

(2)

Perempuan/ Female (3)

Jumlah/ Total

10481

10512

20993

99.67

Sumber : Badan Pusat Statistik (BPS) Kabupaten Dairi – Hasil Proyeksi Penduduk 2015 Source : BPS-Statistics of Dairi Regency – Projection Figure of Population 2015

26 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Gambar : 3.1 Picture

Penduduk Menurut Jenis Kelamin menurut Desa Population by Sex by Village (jiwa/person) 2015

Badan Pusat Statistik Kabupaten Dairi

| 27

Tanah Pinem Subdistrict in Figures 2016

Tabel : 3.3 Table

Banyaknya Penduduk, Rumah Tangga, dan Rata-rata Anggota Rumah Tangga (ART) Menurut Desa Population, Household and Average of Household Size by Village 2015

Desa/Village

Penduduk/ Population (jiwa)

Rumah Tangga/ Number of Household

Rata-rata ART Per Rumah Tangga/ Average of Household Size

(1)

(2)

(3)

(4)

1. Renun

797

213

3.74

2. Pasir Tengah

1 379

392

3.52

3. Pamah

2 258

624

3.60

4. Kuta Buluh

1 861

509

3.64

5. Tanah Pinem

1 249

351

3.55

6. Kempawa

796

234

3.41

7. Kuta Gamber

776

214

3.60

8. Lau Primbon

1 126

325

3.47

9. Harapan

1 863

516

3.60

10. Gunung Tua

452

127

3.54

11. Sukadame

1 229

324

3.79

12. Lau Tawar

1 282

345

3.70

13. Mangan Molih

754

213

3.54

14. Lau Njuhar I

1 491

387

3.84

15. Liang Jering

855

237

3.60

16. Alur Subur

628

152

4.10

17. Balandua

799

227

3.51

18. Pasir Mbelang

952

257

3.70

19. Sinar Pagi

446

106

4.20

20 865

5 733

3.64

Jumlah/Total

Sumber : Badan Pusat Statistik (BPS) Kabupaten Dairi – Hasil Proyeksi Penduduk 2015 Source : BPS-Statistics of Dairi Regency – Projection Figure of Population 2015

28 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Badan Pusat Statistik Kabupaten Dairi

| 29

Tanah Pinem Subdistrict in Figures 2016

30 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

BAB IV SOSIAL

Jumlah sarana pendidikan di Kecamatan Tanah Pinem relative banyak dan cukup merata di seluruh desa. Sarana pendidikan berjumlah 30 unit, dengan perincian 24 unit Sekolah Dasar, 4 unit Sekolah Menengah Pertama, 2 unit Sekolah Menengah Atas. Hampir seluruh desa memiliki Sekolah Dasar sebagai sarana pendidikan dasar untuk masyarakat.

Tingkat rasio murid-guru cenderung bervariasi pada tiap jenjang pendidikan. Secara rata-rata, rasio murid-guru di Kecamatan Tanah Pinem sebesar 8 murid per guru. Rasio murid guru tertinggi berada pada jenjang Sekolah Lanjutan Tingkat Pertama yang mencapai 9 murid untuk tiap guru. sedangkan rasio murid-guru pada jenjang pendidikan SD dan SMU masingmasing sebesar 7-8 murid per gurunya.

Badan Pusat Statistik Kabupaten Dairi

| 31

Tanah Pinem Subdistrict in Figures 2016

CHAPTER IV SOCIAL

The number of educational facilities in the district of Tanah Pinem relatively large and fairly evenly distributed throughout the village . Education facilities amounted to 30 units , with 24 units details Elementary School , Junior High School 4 units , 2 units of high school. Almost the entire village has a primary school as a means of basic education for the community .

The level of student-teacher ratios tend to vary at each level of education . On average , student-teacher ratio in the district of Tanah Pinem of 8 students per teacher . Teacher pupil ratio is the highest in the Junior High School level at 9 pupils for each teacher . while the pupil-teacher ratio in the elementary and high school education , each for 7-8 students per teacher.

32 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 4.1 Table

Banyaknya Sekolah Dasar (SD) Negeri dan Swasta Menurut Desa Number of State and Private Primary Schools by Village (buah/unit) 2015 SD/Primary School Desa/Village

Jumlah/ Total

Negeri/ State

Swasta/ Private

(2)

(3)

(4)

1. Renun

–

2. Pasir Tengah

–

3. Pamah

–

4. Kuta Buluh

–

5. Tanah Pinem

–

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

(1)

Jumlah/Total

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pinem

Badan Pusat Statistik Kabupaten Dairi

| 33

Tanah Pinem Subdistrict in Figures 2016

Tabel : 4.2 Table

Banyaknya Guru dan Murid Pada Sekolah Dasar (SD) Negeri dan Swasta Menurut Desa Number of Teachers and Pupils in State and Private Primary School by Village (orang/person) 2015 Guru/Teachers

Desa/Village

(1)

Murid/Pupils

Negeri/ Swasta/ Jumlah/ Negeri/ Swasta/ State Private Total State Private (5)

–

210

–

210

2. Pasir Tengah

–

237

–

237

3. Pamah

–

329

–

329

4. Kuta Buluh

–

239

–

239

5. Tanah Pinem

–

206

–

206

6. Kempawa

–

117

–

117

7. Kuta Gamber

–

115

–

115

8. Lau Primbon

–

167

–

167

9. Harapan

–

270

–

270

–

11. Sukadame

–

209

–

209

12. Lau Tawar

–

189

–

189

13. Mangan Molih

(3)

(6)

(7)

(4)

1. Renun

10. Gunung Tua

(2)

Jumlah/ Total

–

110

–

110

14. Lau Njuhar I

–

137

–

237

15. Liang Jering

–

147

–

147

16. Alur Subur

–

149

–

149

18. Pasir Mbelang

–

116

–

116

19. Sinar Pagi

–

250

256

3 144

3 189

17. Balandua

Jumlah/Total

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pinem

34 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 4.3 Table

Banyaknya Guru Sekolah Dasar (SD) Menurut Tingkat Pendidikan dan Unit Sekolah Number of Teachers in Primary School by Education Level, and School Unit (orang/person) 2015

No.

Tingkat Pendidikan/ Education Level

Nama Sekolah/ School Name

Jumlah/ Total

< D-3

D-3

S-1

S-2/ S-3

(3)

(4)

(5)

(6)

(7)

(8)

1. SDN 030437 Kuta Buluh

–

2. SDN 030438 Tanah Pinem

–

3. SDN 030439 Lau Meciho

–

4. SDN 030440 Lau Primbon

–

5. SDN 030441 Pamah

–

6. SDN 030442 Pamah

–

7. SDN 033921 Simbetek

–

8. SDN 034818 Butar

–

9. SDN 034819 Liren

–

10. SDN 034820 Lau Petundal

–

11. SDN 034821 Pasir Tengah

–

12. SDN 034822 Tambang Timah

–

13. SDN 034823 Kutabuluh

–

14. SDN 035948 Renun

–

15. SDN 035939 Kempawa

–

16. SDN 035940 Mangan Molih

–

17. SDN 036463 Lau Lubuk

–

(1)

(2)

Badan Pusat Statistik Kabupaten Dairi

| 35

Tanah Pinem Subdistrict in Figures 2016

Tabel : 4.3 Table

No.

(1)

Lanjutan/Continued

Tingkat Pendidikan/ Education Level

Nama Sekolah/ School Name (2)

Jumlah/ Total

< D-3

D-3

S-1

S-2/ S-3

(3)

(4)

(5)

(6)

(7)

(8)

18. SDN 037158 Lau Njuhar

–

19. SDN 037729 Sinar Pagi

–

20. SDN 037999 Juma Batu

–

21. SDN 038096 Pasir Mbelang

–

22. SD Inpres Liang Jering

–

23. SD Inpres Kuta Mbaru

–

24. SD SWT Madrasah Ibtidaiyah

–

169

–

254

Jumlah/Total

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pinem

36 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 4.4 Table

Banyaknya Guru Sekolah Dasar (SD) Menurut Status dan Unit Sekolah Number of Teachers in Primary School by Status, and School Unit (orang/person) 2015

No.

Nama Sekolah/ School Name

(1)

(2)

Status Guru/ Teacher’s Status PNS

Tetap Lain

Non PNS

(3)

(4)

(5)

Jumlah/ Total (6)

1. SDN 030437 Kuta Buluh

–

2. SDN 030438 Tanah Pinem

–

3. SDN 030439 Lau Meciho

–

4. SDN 030440 Lau Primbon

–

5. SDN 030441 Pamah

–

6. SDN 030442 Pamah

–

7. SDN 033921 Simbetek

–

8. SDN 034818 Butar

–

9. SDN 034819 Liren

–

10. SDN 034820 Lau Petundal

–

11. SDN 034821 Pasir Tengah

–

12. SDN 034822 Tambang Timah

–

13. SDN 034823 Kutabuluh

–

14. SDN 035948 Renun

–

15. SDN 035939 Kempawa

–

16. SDN 035940 Mangan Molih

–

17. SDN 036463 Lau Lubuk

–

Badan Pusat Statistik Kabupaten Dairi

| 37

Tanah Pinem Subdistrict in Figures 2016

Tabel : 4.4 Table

No.

(1)

Lanjutan/Continued

Nama Sekolah/ School Name (2)

Status Guru/ Teacher’s Status PNS

Tetap Lain

(3)

(4)

Non PNS

Jumlah/ Total

(5)

(6)

18. SDN 037158 Lau Njuhar

–

19. SDN 037729 Sinar Pagi

–

20. SDN 037999 Juma Batu

–

21. SDN 038096 Pasir Mbelang

–

22. SD Inpres Liang Jering

–

23. SD Inpres Kuta Mbaru

–

24. SD SWT Madrasah Ibdaiyah

–

147

101

254

Jumlah/Total

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pinem

38 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 4.5 Table

Banyaknya Murid Sekolah Dasar (SD) Menurut Kelas dan Desa Number of Pupils in Primary School by Class and Village (orang/person) 2015

Kelas/Class

Jumlah/ Total

Desa/Village (1)

(4)

(5)

(6)

(7)

(2)

(3)

1. Renun

204

2. Pasir Tengah

236

3. Pamah

323

4. Kuta Buluh

239

5. Tanah Pinem

206

6. Kempawa

116

7. Kuta Gamber

115

8. Lau Primbon

167

9. Harapan

270

11. Sukadame

209

12. Lau Tawar

189

13. Mangan Molih

110

14. Lau Njuhar I

233

15. Liang Jering

154

16. Alur Subur

17. Balandua

146

18. Pasir Mbelang

118

19. Sinar Pagi

566

570

519

526

529

479

3 189

10. Gunung Tua

Jumlah/Total

(8)

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pinem

Badan Pusat Statistik Kabupaten Dairi

| 39

Tanah Pinem Subdistrict in Figures 2016

Tabel : 4.6 Table

Banyaknya Murid Sekolah Dasar (SD) Menurut Kelas, Jenis Kelamin, dan Unit Sekolah Number of Pupils in Primary School by sex, and School Units (orang/person) 2015 Kelas/Class

Unit Sekolah/ School Unit

(1)

Jumlah/ Total

Jumlah /Total

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

SDN 030437 Kuta Buluh

SDN 030438 Tanah Pinem

SDN 030439 Lau Meciho

SDN 030440 Lau Primbon

5. SDN 030441 Pamah

6. SDN 030441 Pamah

7. SDN 033921 Simbetek

8. SDN 034818 Butar

9. SDN 034819 Liren

10.

SDN 034820 Lau Petundal

11.

SDN 034821 Pasir Tengah

12.

SDN 034822 Tambang Timah

40 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016 Tabel : 4.6 Table

Lanjutan/Continued

Kelas/Class Unit Sekolah/ School Unit

(1)

Jumlah/ Total

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

13. SDN 034823 Kutabuluh

14. SDN 035948 Renun

15. SDN 035939 Kempawa

17. SDN 036463 Lau Lubuk

18. SDN 037158 Lau Njuhar

19. SDN 037729 Sinar Pagi

20. SDN 037999 Juma Batu

SDN 038096 Pasir Mbelang

22. SD Inpres Liang Jering

23. SD Inpres Kuta Mbaru

306

260

302

268

570

260

259

219

16.

21.

24.

SDN 035940 Mangan Molih

SD SWT Madrasah Ibdaiyah Jumlah/Total

566

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pinem

Badan Pusat Statistik Kabupaten Dairi

| 41

Tanah Pinem Subdistrict in Figures 2016 Tabel : 4.6 Table

Lanjutan/Continued

Kelas/Class Unit Sekolah/ School Unit

(1)

Jumlah/ Total

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

SDN 030437 Kuta Buluh

SDN 030438 Tanah Pinem

SDN 030439 Lau Meciho

SDN 030440 Lau Primbon

5. SDN 030441 Pamah

6. SDN 030441 Pamah

7. SDN 033921 Simbetek

8. SDN 034818 Butar

9. SDN 034819 Liren

10.

SDN 034820 Lau Petundal

11.

SDN 034821 Pasir Tengah

12.

SDN 034822 Tambang Timah

42 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016 Tabel : 4.6 Table

Lanjutan/Continued

Kelas/Class Unit Sekolah/ School Unit

(1) 13.

(2) SDN 034823 Kutabuluh

14. SDN 035948 Renun

Jumlah/ Total

Jumlah/T otal

(12)

(13)

(14)

(15)

(16)

(17)

(18)

(19)

(20)

15.

SDN 035939 Kempawa

16.

SDN 035940 Mangan Molih

17.

SDN 036463 Lau Lubuk

18.

SDN 037158 Lau Njuhar

19.

SDN 037729 Sinar Pagi

20.

SDN 037999 Juma Batu

21.

SDN 038096 Pasir Mbelang

22. SD Inpres Liang Jering

23. SD Inpres Kuta Mbaru

285

241

526

289

240

524

238

241

479

24.

SD SWT Madrasah Ibdaiyah Jumlah/Total

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pinem

Badan Pusat Statistik Kabupaten Dairi

| 43

Tanah Pinem Subdistrict in Figures 2016

Tabel : 4.7 Table

Banyaknya Sekolah Lanjutan Tingkat Pertama (SLTP) Negeri dan Swasta Menurut Desa Number of State and Private Junior High School by Village (buah/unit) 2015 SLTP/ Junior High School Desa/Village

(1)

Negeri/ State

Swasta/ Private

Jumlah/ Total

(2)

(3)

(4)

1. Renun

—

–

2. Pasir Tengah

–

3. Pamah

–

4. Kuta Buluh

–

5. Tanah Pinem

–

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

Jumlah/Total

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pinem

44 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 4.8 Table

Desa/Village (1) 1. Renun 2. Pasir Tengah 3. Pamah

Murid/Pupils

Negeri/ Swasta/ Jumlah/ Negeri/ Swasta/ Jumlah/ State Private Total State Private Total (2)

(3)

(4)

(5)

(6)

(7)

–

4. Kuta Buluh

–

386

–

386

5. Tanah Pinem

–

285

–

285

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

809

–

809

Jumlah/Total

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pinem

Badan Pusat Statistik Kabupaten Dairi

| 45

Tanah Pinem Subdistrict in Figures 2016

Tabel : 4.9 Table

Banyaknya Guru Sekolah Lanjutan Tingkat Pertama (SLTP) Menurut Tingkat Pendidikan dan Unit Sekolah Number of Teachers in Junior High School by Education Level and School Unit (orang/person) 2015

Tingkat Pendidikan/ Education Level Nama Sekolah/ School Name

Jumlah/ Total < D-3

D-3

D-4

S-1

S-2/ S-3

(2)

(3)

(4)

(5)

(6)

(7)

SMP Negeri 1 Kutabuluh

SMP Negeri 2 Tanah Pinem

SMP Negeri 3 Pasir Tengah

SMP Negeri 4 Lau Njuhar

(1)

Jumlah/Total

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pinem

46 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 4.10 Table

Banyaknya Guru Sekolah Lanjutan Tingkat Pertama (SLTP) Menurut Status Guru dan Unit Sekolah Number of Teachers in Junior High School by Status and School Unit (orang/person) 2015

Status Guru/ Teacher’s Status Nama Sekolah/ School Name

Jumlah/ Total PNS

Tetap Lain

Non PNS

(2)

(3)

(4)

(5)

SMP Negeri 1 Kutabuluh

–

SMP Negeri 2 Tanah Pinem

–

SMP Negeri 3 Pasir Tengah

–

SMP Negeri 4 Lau Njuhar

–

(1)

Jumlah/Total

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pinem

Badan Pusat Statistik Kabupaten Dairi

| 47

Tanah Pinem Subdistrict in Figures 2016

Tabel : 4.11 Table

Banyaknya Murid Sekolah Lanjutan Tingkat Pertama (SLTP) Menurut Kelas, Jenis Kelamin, dan Unit Sekolah Number of Pupils in Junior High School by Class, Sex, and School Unit (orang/person) 2015

Kelas VII/ Class VII Nama Sekolah/ School Name

(1)

(2)

Kelas VIII/ Class VIII

Kelas IX/ Class IX

Jumla/ Total

Jumlah/ Total

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

SMP Negeri 1 Kutabuluh

138

121

131

SMP Negeri 2 Tanah Pinem

107

SMP Negeri 3 Pasir Tengah

SMP Negeri 4 Lau Njuhar

Jumlah/Total

138

156

294

117

134

251

132

137

269

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pinem Keterangan / Note : Lk = Laki-Laki/Male Pr = Perempuan/Female

48 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 4.12 Table

Banyaknya Murid Sekolah Lanjutan Tingkat Pertama (SLTP) Menurut Kelas dan Desa Number of Pupils in Junior High School by Class and Village (orang/person) 2015

Tingkat Kelas/ Class level Desa/Village

Jumlah/ Total

VII

VIII

(1)

(2)

(3)

(4)

–

2. Pasir Tengah

–

4. Kuta Buluh

135

121

131

390

5. Tanah Pinem

111

192

279

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

294

251

269

814

1. Renun

3. Pamah

Jumlah/Total

(5)

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pine

Badan Pusat Statistik Kabupaten Dairi

| 49

Tanah Pinem Subdistrict in Figures 2016

Tabel : 4.13 Table

Banyaknya Sekolah Menengah Umum (SMU) Negeri dan Swasta Menurut Desa Number of State and Private General Senior High School by Village (unit/ unit) 2015

Desa/Village

SMU/General Senior High School

Jumlah/ Total

Negeri/ State

Swasta/ Private

(2)

(3)

(4)

1. Renun

–

2. Pasir Tengah

–

3. Pamah

–

4. Kuta Buluh

–

5. Tanah Pinem

–

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

(1)

Jumlah/Total

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pinem

50 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 4.14 Table

Murid/Pupils

Desa/Village Negeri/ Swasta/ Jumlah/ Negeri/ Swasta/ Jumlah/ State Private Total State Private Total (2)

(3)

(4)

(5)

(6)

(7)

1. Renun

–

2. Pasir Tengah

–

3. Pamah

–

(1)

4. Kuta Buluh

–

386

–

386

5. Tanah Pinem

–

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

10. Gunung Tua

9. Harapan

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

478

–

478

Jumlah/Total

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pinem

Badan Pusat Statistik Kabupaten Dairi

| 51

Tanah Pinem Subdistrict in Figures 2016

Tabel : 4.15 Table

Nama Sekolah/ School Name

Jumlah/ Total

< D-3

D-3

S-1

S-2/ S-3

(2)

(3)

(4)

(5)

(6)

(7)

SMANegeri 1 Kutabuluh

–

SMKNegeri 1 Kuta Mbaru

–

Jumlah/Total

–

(1)

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pinem

52 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016 Tabel : 4.16 Table

Banyaknya Guru Sekolah Menengah Umum (SMU) Menurut Status dan Unit Sekolah Number of Teachers in General Senior High School by Status and School Unit (orang/person) 2015

Status Guru/ Teacher’s Status Nama Sekolah/ School Name

Jumlah/ Total

PNS

Tetap Lain

(2)

(3)

(4)

(5)

SMANegeri 1 Kutabuluh

–

SMKNegeri 1 Kuta Mbaru

–

(1)

Jumlah/Total

Non PNS

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pinem

Badan Pusat Statistik Kabupaten Dairi

| 53

Tanah Pinem Subdistrict in Figures 2016

Tabel : 4.17 Table

Nama Sekolah/ School Name (1)

(2)

Kelas XI/Class XI

Kelas XII/Class XII

Jumlah/ Total

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

103

SMANegeri 1 Kutabuluh

102

105

SMKNegeri 1 Kuta Mbaru

–

Jumlah/Total

102

194

100

197

–

103

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pinem

Keterangan / Note : Lk = Laki-Laki/Male Pr = Perempuan/Female

54 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 4.18 Table

Banyaknya Murid Sekolah Menengah Umum (SMU) Menurut Kelas dan Desa Number of Pupils in General Senior High School by Class and Village (orang/person) 2015

Tingkat Kelas/ Class level Desa/Village

Jumlah/ Total

XII

(2)

(3)

(4)

(5)

1. Renun

–

2. Pasir Tengah

–

3. Pamah

–

102

105

103

310

5. Tanah Pinem

–

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

92-

–

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

102

197

103

402

(1)

4. Kuta Buluh

Jumlah/Total

Sumber : UPTD Pendidikan Kecamatan Tanah Pinem Source : Branch Office of Education at Tanah Pinem

Badan Pusat Statistik Kabupaten Dairi

| 55

Tanah Pinem Subdistrict in Figures 2016

Tabel : 4.19

Banyaknya Sarana Kesehatan Umum Menurut Jenis dan Desa Number of Public Health Facility by Types and Village (buah/unit) 2015 Jenis Sarana Kesehatan Umum/ Types of Public Health Facilitiy

Desa/Village

(1)

Puskesmas/ Public Health Sub Center (2)

Pustu/ Small Public Health Sub Center (3)

Posyandu /Integrated Health Service (4)

1. Renun

–

2. Pasir Tengah

–

3. Pamah

–

4. Kuta Buluh

–

5. Tanah Pinem

–

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

Jumlah/Total

Sumber : UPTD Kesehatan dan Sosial Kabupaten Dairi Source : Branch Office of Education at Dairi Sub Regency

56 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 4.19

Lanjutan/Continued

Jenis Sarana Kesehatan Umum/ Types of Public Health Facilitiy Desa/Village

(1)

Polindes/ Village Clinic

Poskesdes

Jumlah/ Total

(2)

(3)

(4)

Renun

–

Pasir Tengah

–

Pamah

–

Kuta Buluh

–

Tanah Pinem

–

Kempawa

–

Kuta Gamber

–

Lau Primbon

–

Harapan

–

Gunung Tua

–

Sukadame

–

Lau Tawar

–

Mangan Molih

–

Lau Njuhar I

–

Liang Jering

–

Alur Subur

–

Balandua

–

Pasir Mbelang

–

Sinar Pagi

–

Jumlah/Total

Sumber : UPTD Kesehatan dan Sosial Kabupaten Dairi Source : Branch Office of Education at Dairi Sub Regency

Badan Pusat Statistik Kabupaten Dairi

| 57

Tanah Pinem Subdistrict in Figures 2016 Tabel : 4.20 Table

Banyaknya Tenaga Medis Menurut Klasifikasi dan Desa Number of Medical Servant by Classification and Village (orang/person) 2015

Desa/Village

(1)

Klasifikasi Tenaga Medis/ Medical Servant Classification Dukun Jumlah/ Bayi/ Total Dokter/ Bidan/ Perawat/ Lainnya/ Baby Doctor Midwife Nurse Others Sooth sayer (2) (3) (4) (5) (6) (7)

1. Renun

–

2. Pasir Tengah

–

3. Pamah

–

4. Kuta Buluh

–

5. Tanah Pinem

–

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

Jumlah/Total

Sumber : UPTD Kesehatan dan Sosial Kabupaten Dairi Source : Branch Office of Education at Dairi Sub Regen

58 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016 Tabel : 4.21

Banyaknya Wanita Usia Subur 15-49 Tahun (WUS) dan Pasangan Usia Subur (PUS) Menurut Desa Number of Ever Merrit Women and Fertile Couples by Village (orang/person) 2015

Desa/ Village

WUS/ Ever Merrit Women

PUS/ Fertile Couples

(1)

(2)

(3)

1. Renun

192

155

2. Pasir Tengah

328

271

3. Pamah

593

447

4. Kuta Buluh

492

352

5. Tanah Pinem

545

225

6. Kempawa

220

166

7. Kuta Gamber

186

158

8. Lau Primbon

343

202

9. Harapan

409

237

10. Gunung Tua

132

105

11. Sukadame

305

256

12. Lau Tawar

338

198

13. Mangan Molih

188

131

14. Lau Njuhar I

311

274

15. Liang Jering

197

130

16. Alur Subur

153

119

17. Balandua

196

115

18. Pasir Mbelang

192

139

19. Sinar Pagi

181

5501

3772

Jumlah/ Total

Sumber : UPTD Kesehatan dan Sosial Kabupaten Dairi Source : Branch Office of Education at Dairi Sub Regenc

Badan Pusat Statistik Kabupaten Dairi

| 59

Tanah Pinem Subdistrict in Figures 2016 Tabel : 4.22

Banyaknya Pasangan Usia Subur (PUS) yang Menggunakan Alat Kontrasepsi Menurut Desa Number of Fertile Couples Used Contraceptive by Village (pasangan/couple) 2015

Desa/ Village (1)

Menggunakan Alat Kontrasepsi/ Used Contraceptive (2)

Tidak Menggunakan Alat Kontrasepsti/ non Contraceptive (3)

Jumlah/ Total (4)

1. Renun

129

155

2. Pasir Tengah

154

117

271

3. Pamah

295

152

447

4. Kuta Buluh

219

133

352

5. Tanah Pinem

134

225

166

7. Kuta Gamber

107

158

8. Lau Primbon

137

202

9. Harapan

149

237

105

11. Sukadame

108

148

256

12. Lau Tawar

129

198

6. Kempawa

10. Gunung Tua

131

14. Lau Njuhar I

143

131

274

15. Liang Jering

130

16. Alur Subur

119

17. Balandua

115

18. Pasir Mbelang

139

19. Sinar Pagi

13. Mangan Molih

Jumlah/ Total

2371

1401

3772

Sumber : UPTD Kesehatan dan Sosial Kabupaten Dairi Source : Branch Office of Education at Dairi Sub Regen

60 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 4.23 Table

Banyaknya Pasangan Usia Subur (PUS) Menurut Jenis Alat Kontrasepsi yang Digunakan dan Desa Number of Fertile Age Couple by Type of Contraceptive Used and Village (pasangan/couple) 2015 Jenis Alat Kontrasepsi/ Type of Contraceptive Used

Desa/Village Spiral/ IUD

Operasi Medis/ Medical Operation

Implan/ Implant

MOP

MOW

(2)

(3)

(4)

1. Renun

2. Pasir Tengah

3. Pamah

4. Kuta Buluh

5. Tanah Pinem

6. Kempawa

7. Kuta Gamber

8. Lau Primbon

9. Harapan

(1)

(5)

10. Gunung Tua

11. Sukadame

12. Lau Tawar

13. Mangan Molih

14. Lau Njuhar I

15. Liang Jering

16. Alur Subur

17. Balandua

7 11

18. Pasir Mbelang

124

263

19. Sinar Pagi Jumlah/Total

Sumber : PPLKB Kecamatan Tanah Pinem Source : Family Planning Clerck at Tanah Pinem

Badan Pusat Statistik Kabupaten Dairi

| 61

Tanah Pinem Subdistrict in Figures 2016

Tabel : 4.23

Lanjutan/Continued

Jenis Alat Kontrasepsi/ Type of Contraceptive Used Desa/Village

(1)

Suntik/ Injection

Pil/ Pill

Kondom/ Condom

Jumlah/ Total

(6)

(7)

(8)

(9)

1. Renun

120

2. Pasir Tengah

146

3. Pamah

292

4. Kuta Buluh

223

5. Tanah Pinem

136

6. Kempawa

7. Kuta Gamber

8. Lau Primbon

115

9. Harapan

158

10. Gunung Tua

11. Sukadame

12. Lau Tawar

144

13. Mangan Molih

14. Lau Njuhar I

130

15. Liang Jering

16. Alur Subur

17. Balandua

18. Pasir Mbelang

19. Sinar Pagi

658

457

140

2235

Jumlah/Total

Sumber : PPLKB Kecamatan Tanah Pinem Source : Family Planning Clerck at Tanah Pinem

62 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016 Tabel : 4.24 Table

Banyaknya Keluarga Pra KS, KS-1, KS-2, KS-3 dan KS-3 Plus Menurut Desa Number of Pra Prosperous, 1 st Prosperous, 2 st Prosperous, 3 st Prosperous, and 3 st Plus Prosperous Household by Village (pasangan/couple) 2015 Tingkat Kesejahteraan Rumah Tangga/ Level of Household Prosperity

Desa/Village

(1)

KS-III Jumlah/ Pra KS/ KS-I/ 1 KS-III/ Plus/ 3 st Total KS-II/ 2 st st Pra 3 st Prosperou Plus Prospe- ProspeProspero s Prospero rous rous us us (2)

(3)

(4)

(5)

(6)

(7)

106

217

103

139

108

367

3. Pamah

370

218

708

4. Kuta Buluh

321

162

561

5. Tanah Pinem

161

116

362

6. Kempawa

240

7. Kuta Gamber

222

163

109

348

105

217

146

432

1. Renun 2. Pasir Tengah

8. Lau Primbon 9. Harapan 10. Gunung Tua

138

11. Sukadame

147

102

342

12. Lau Tawar

155

133

371

13. Mangan Molih

203

14. Lau Njuhar I

119

155

346

15. Liang Jering

230

16. Alur Subur

145

17. Balandua

102

218

18. Pasir Mbelang

255

19. Sinar Pagi

166

2677

1773

187

5871

Jumlah/Total

1189

Sumber : Kepala Desa Se-Kecamatan Tanah Pinem Source : Whole Village Chief of Tanah PinemSub Regency

Badan Pusat Statistik Kabupaten Dairi

| 63

Tanah Pinem Subdistrict in Figures 2016

Tabel : 4.25 Table

Banyaknya Rumah Ibadah Menurut Jenis dan Desa Number of Place of Worship by Type and Village (buah/unit) 2015 Jenis Sarana Ibadah/ Types of Worship Facility

Desa/Village

(1)

Mesjid/ Musolah/ Mosque Mushola (2)

(3)

1. Renun

–

2. Pasir Tengah

3. Pamah 4. Kuta Buluh

Gereja/ Kuil/ Wihara/ Church Temple Vihara (5)

(6)

–

5. Tanah Pinem

–

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

113

Jumlah/Total

(4)

Jumlah/ Total

(7)

Sumber : Kepala Desa Se-Kecamatan Tanah Pinem Source : Whole Village Chief of Tanah PinemSub Regency

64 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Badan Pusat Statistik Kabupaten Dairi

| 65

Tanah Pinem Subdistrict in Figures 2016

66 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

BAB V PERTANIAN

Bidang pertanian di Kecamatan Tanah Pinem yang termasuk maju adalah bidang Pertanian. Tercatat pada Tahun 2015, produktivitas Jagung dan Ubi Kayu mencapai masing-masing 29669 ton dan 430 ton.

Untuk Padi Ladang di Kecamatan Tanah Pinem Luas Panen di tahun 2015 mecapai 470.00 Hektare dengan Produksi 1071.75 Ton, dengan tingkat produktivitas mencapai 2.27 Ton/ Hektare

Badan Pusat Statistik Kabupaten Dairi

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Tanah Pinem Subdistrict in Figures 2016

CHAPTER V AGRICULTURE

Agriculture in the District Land Pinem which includes advanced is the field of Agriculture . Recorded in 2015 , the productivity of corn and cassava reached respectively 29 669 tonnes and 430 tonnes .

To Rice Field in the District Land Pinem Harvested in 2015 mecapai 470.00 hectares with a production of 1071.75 tons , with a productivity level reaches 2:27 Tons / Hectare

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BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 5.1 Table

Luas Panen, Produksi, dan Produktivitas Padi Sawah Menurut Desa Harvest Area, Production and Productivity of Wet Land Paddy by Village 2015

Desa/ Village (1)

Luas panen/ Harvest Area (ha)

Produksi/ Production (ton)

Produktivitas/ Productivity (ton/ha) (4)

(2)

(3)

1. Renun

–

2. Pasir Tengah

–

3. Pamah

–

4. Kuta Buluh

–

5. Tanah Pinem

22.50

4.50

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

36.80

4.60

9. Harapan

–

10. Gunung Tua 11. Sukadame

238.00

4.25

12. Lau Tawar

27.00

4.50

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

23.00

4.60

347.30

4.74

Jumlah/Total

Sumber : UPTD DP3 Kecamatan Tanah Pinem6.00 Source : Branch Office of Agriculture and Food R16.10esilience at Tanah Pinem

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Tanah Pinem Subdistrict in Figures 2016

Tabel : 5.2 Table

Luas Panen, Produksi, dan Produktivitas Padi Ladang Menurut Desa Harvest Area, Production and Productivity of Dry Land Paddy by Village 2015

Desa/ Village (1)

Luas panen/ Harvest Area (ha)

Produksi/ Production (ton)

Produktivitas/ Productivity (ton/ha)

(2)

(3)

(4)

1. Renun

8.00

19.20

2.40

2. Pasir Tengah

6.00

13.80

2.30

3. Pamah

16.10

37.25

2.25

4. Kuta Buluh

18.40

43.06

2.34

5. Tanah Pinem

15.00

15.54

2.22

6. Kempawa

42.00

88.20

2.10

7. Kuta Gamber

40.00

84.00

2.10

8. Lau Primbon

60.30

123.62

2.05

9. Harapan

25.00

60.00

2.40

10. Gunung Tua

45.00

108.00

2.40

11. Sukadame

73.80

172.69

2.34

12. Lau Tawar

12.00

27.60

2.30

13. Mangan Molih

10.00

22.40

2.24

14. Lau Njuhar I

8.00

18.40

2.30

15. Liang Jering

10.00

22.00

2.20

16. Alur Subur

15.00

33.00

2.20

17. Balandua

15.00

36.00

2.40

18. Pasir Mbelang

10.00

23.00

2.30

19. Sinar Pagi

50.00

125.00

2.50

470.00

1071.75

2.27

Jumlah/Total

Sumber : UPTD DP3 Kecamatan Tanah Pinem Source : Branch Office of Agriculture and Food Resilience at Tanah Pinem

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BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 5.3 Table

Luas Lahan Sawah Menurut Jenis Irigasi dan Desa Area of Wet Land Paddy by Type of Irrigation and Village (ha) 2015

Jenis Irigasi/Types of Irigation Desa/Village

(1)

Teknis/ Technical

Setengah/ Half Technical

Sederhana/ Modestly

(2)

(3)

(4)

1. Renun

–

2. Pasir Tengah

–

3. Pamah

–

4. Kuta Buluh

–

5. Tanah Pinem

–

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

Jumlah/Total

Sumber : UPTD DP3 Kecamatan Tanah Pinem Source : Branch Office of Agriculture and Food Resilience at Tanah Pinem

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Tanah Pinem Subdistrict in Figures 2016

Tabel : 5.3

Lanjutan/Continued

Jenis Irigasi/ Types of Irigation Desa/Village

Jumlah/ Total

Non P.U/ Non Public Service

Tadah Hujan/ Depend on Rain Water

(5)

(6)

(7)

1. Renun

–

2. Pasir Tengah

–

3. Pamah

–

4. Kuta Buluh

–

5. Tanah Pinem

–

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

(1)

Jumlah/Total

Sumber : UPTD DP3 Kecamatan Tanah Pinem Source : Branch Office of Agriculture and Food Resilience at Tanah Pinem

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BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016 Tabel : 5.4 Table

Luas Tanaman Palawija Menurut Jenis Tanaman dan Desa/Kelurahan Planting Area of Crop by Types of Plant and Village/Suburban (ha) 2015 Jenis Tanaman/Types of Plant

Desa/Village

Jagung/ Corn

Ubi Kayu/ Cassava

Kacang Tanah/ Peanut

(2)

(3)

(4)

(1) 1. Renun

600

–

Kacang Hijau/ Kedelai/ Green Soybean Bean (5) (6)

–

2. Pasir Tengah

1525

–

3. Pamah

1330

1.00

0.50

0.20

–

0.60

–

1050

3.00

0.50

–

6. Kempawa

552

–

0.50

–

7. Kuta Gamber

400

–

1.00

0.10

–

8. Lau Primbon

530

–

1.20

0.20

–

9. Harapan

550

2.00

0.50

–

10. Gunung Tua

180

–

1.40

1.80

–

11. Sukadame

180

–

1.40

1.80

–

12. Lau Tawar

900

4.00

1.00

–

13. Mangan Molih

650

–

14. Lau Njuhar I

600

–

15. Liang Jering

400

–

16. Alur Subur

–

17. Balandua

165

–

18. Pasir Mbelang

690

–

1.40

0.40

–

10.2

4. Kuta Buluh 5. Tanah Pinem

19. Sinar Pagi Jumlah/Total

10422

2.7

2.4

Sumber : UPTD DP3 Kecamatan Tanah Pinem Source : Branch Office of Agriculture and Food Resilience at Tanah Pinem

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Tanah Pinem Subdistrict in Figures 2016 Tabel : 5.5 Table

Produksi Tanaman Palawija Menurut Jenis Tanaman dan Desa Production of Crop by Types of Plant and Village (ton) 2015

Jenis Tanaman/Types of Plant Desa/Village

(1)

Ubi Kacang Jagung/ Kacang Kayu/ Hijau/ Kedelai/ Tanah/ Corn CassaGreen Soybean Peanut va Bean (2)

(3)

(4)

(5)

(6)

Jumlah/ Total (8)

3720

–

372.00

10675

–

10675.00

8610

0.80

–

951.80

455

–

0.80

–

455.80

5. Tanah Pinem

7350

135

0.80

–

1005.80

6. Kempawa

3588

–

0.80

–

3588.80

7. Kuta Gamber

2520

–

1.50

0.54

–

254.04

8. Lau Primbon

3445

–

1.60

0.90

–

3447.50

9. Harapan

3740

0.60

–

555.20

1224

–

1.90

2.82

–

1228.72

11. Sukadame

630

–

4.80

0.43

3.96

639.19

12. Lau Tawar

6300

160

1.6

–

384.60

13. Mangan Molih

4355

–

4355.00

14. Lau Njuhar I

3900

–

0.60

–

39.60

15. Liang Jering

2480

–

248.00

16. Alur Subur

480

–

480.00

17. Balandua

1072

–

0.60

–

1072.60

18. Pasir Mbelang

4830

–

483.00 320.62

1. Renun 2. Pasir Tengah 3. Pamah 4. Kuta Buluh

10. Gunung Tua

19. Sinar Pagi Jumlah/Total

318

–

2.20

0.42

–

29669

430

18.6

5.71

3.96

30557.27

Sumber : UPTD DP3 Kecamatan Tanah Pinem Source : Branch Office of Agriculture and Food Resilience at Tanah Pinem

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BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 5.6 Table

Banyaknya Tanaman Buah-buahan Menurut Jenisnya Tree of of Fruits by Types (pohon/ tree) 2015

Jenis Buah-buahan/ Types of Fruits

Pohon/Batang Tree

(1)

(2)

1. Durian/Durian

8450

2. Rambutan/Rambutan

1340

3. Sawo/Chicoo

540

4. Manggis/Mangosteen

800

5. Alpukat/ Avocado

4550

6. Duku/Langsat/ lansium domesticum

2520

7. Pepaya/Papaya

3300

8. Pisang/Banana

35400

Sumber : UPTD DP3 Kecamatan Tanah Pinem Source : Branch Office of Agriculture and Food Resilience at Tanah Pinem

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Tanah Pinem Subdistrict in Figures 2016

Tabel : 5.7 Table

Luas Tanaman Perkebunan Rakyat Menurut Jenis Tanaman dan Desa Planting Area of Smallholder Estate by Types of Plant and Village (ha) 2015 Jenis Tanaman/Types of Plant

Desa/Village

(1)

Kelapa/ Kopi/ Coconut Coffee (2)

(3)

Coklat/ Cacao (4)

Kemiri/ Tembakau/ Jahe/ Hazelnut Tobacco Ginger (5)

(7)

(6)

1. Renun

8.0

–

15.0

96,00

–

2. Pasir Tengah

5.0

–

12.0

310,80

–

3. Pamah

5.5

–

25.4

210,60

–

4. Kuta Buluh

4.0

–

20.0

452,10

0,80

–

5. Tanah Pinem

4.0

–

15.0

202,54

–

6. Kempawa

–

2.40

5.8

173,04

1,20

—

7. Kuta Gamber

2.2

–

8.5

113,28

0,10

–

8. Lau Primbon

2.0

2.80

11.6

121,11

0,80

–

9. Harapan

4.2

2.80

20.0

105,84

–

10. Gunung Tua

4.3

6.10

12.0

57,20

–

11. Sukadame

3.0

6.80

4.2

32,19

3,10

22,7

12. Lau Tawar

4.5

–

12.0

–

13. Mangan Molih

5.2

–

6.6

136,96

–

14. Lau Njuhar I

5.8

–

8.5

226,94

–

15. Liang Jering

4.6

–

184,81

–

16. Alur Subur

4.4

2.40

11.3

232,32

–

17. Balandua

2.4

–

5.5

275,97

–

18. Pasir Mbelang

5.3

–

12.0

235,56

–

19. Sinar Pagi

2.0

30.2

4.2

76,40

–

76.4

53.50

218.6

6,00

22,7

Jumlah/ Total

9.0

143,26

Sumber : UPTD DP3 Kecamatan Tanah Pinem Source : Branch Office of Agriculture and Food Resilience at Tanah Pinem

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BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016 Tabel : 5.8 Table

Produksi Tanaman Perkebunan Rakyat Menurut Jenis Tanaman dan Desa Production of Smallholder Estate by Types of Plant and Village (ton) 2015

Jenis Tanaman/Types of Plant Desa/Village

(1)

Kelapa/ Kopi/ Coconut Coffee (2)

(3)

Coklat/ Cacao (4)

Kemiri/ Tembakau/ Jahe/ Hazelnut Tobacco Ginger (5)

(6)

(7)

1. Renun

5,60

–

13,50

96,00

–

2. Pasir Tengah

3,80

–

10,80

310,80

–

3. Pamah

3,85

–

25,40

210,60

–

4. Kuta Buluh

2,80

–

28,80

452,10

0,64

–

5. Tanah Pinem

3,20

–

19,50

202,54

–

—

–

3,84

4,64

173,04

2,04

–

6. Kempawa 7. Kuta Gamber

1,54

–

9,35

113,28

0,12

–

8. Lau Primbon

1,40

1,68

10,40

121.,11

1,34

–

9. Harapan

2,73

2,52

23,94

105,84

–

10. Gunung Tua

3,31

9,39

10,80

57,20

–

11. Sukadame

1,98

12,24

5,04

32,19

6,20

145,28

12. Lau Tawar

3,15

–

14,4

143,26

–

13. Mangan Molih

3,95

–

6,60

136,96

–

14. Lau Njuhar I

4,12

–

9,35

226,94

–

15. Liang Jering

2,90

–

8,82

184,81

–

16. Alur Subur

2,64

0,96

15,82

232,32

–

17. Balandua

1,49

–

4,95

275,97

–

—

18. Pasir Mbelang

4,24

–

12,00

235,56

–

19. Sinar Pagi

0,90

4,24

3,70

76,40

—

–

10,34

145,28

Jumlah/ Total

53,60

88,01

237,81

3.386.92

Sumber : UPTD DP3 Kecamatan Tanah Pinem Source : Branch Office of Agriculture and Food Resilience at Tanah Pinem

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Tanah Pinem Subdistrict in Figures 2016

Tabel : 5.9 Table

Luas Panen, Produksi, dan Produktivitas Sayur-sayuran Menurut Jenisnya Harvest Area, Production, and Productivity of Vegetables by Types 2015

Jenis Sayur/ Types of Vegetables

Luas panen/ Harvest Area (ha)

Produksi/ Production (kw)

Produktivitas/ Productivity (kw/ha)

(1)

(2)

(3)

(4)

2. Bawang Merah/Shallots

3. Tomat/Tomato

1. Cabe Merah/Red Chili Pepper

4. Cabe Rawit/Cayenne Pepper

Sumber : UPTD DP3 Kecamatan Tanah Pinem Source : Branch Office of Agriculture and Food Resilience at Tanah Pinem

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BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016 Tabel : 5.10 Table

Banyaknya Kelompok Tani (Poktan) dan Golongan Kelompok Tani (Gapoktan) Menurut Desa Number of Farmer Group and Combinatin of Farmer Group by Village 2015

Desa/ Village (1)

Kelompok Tani/ Farmer Group

Golongan Kelompok Tani/ Combinatin of Farmer Group

(2)

(3)

1. Renun

2. Pasir Tengah

3. Pamah

6. Kempawa

7. Kuta Gamber

8. Lau Primbon

9. Harapan

10. Gunung Tua

11. Sukadame

12. Lau Tawar

13. Mangan Molih

14. Lau Njuhar I

15. Liang Jering

16. Alur Subur

17. Balandua

18. Pasir Mbelang

19. Sinar Pagi

4. Kuta Buluh 5. Tanah Pinem

Jumlah/Total

147

Sumber : UPTD DP3 Kecamatan Tanah Pinem Source : Branch Office of Agriculture and Food Resilience at Tanah Pinem

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Tanah Pinem Subdistrict in Figures 2016

Tabel : 5.11 Table

Banyaknya Ternak Menurut J8enisnya dan Desa Number of Livestock by Ty1pes and Village (ekor/tail) 2015 Jenis Ternak/Types of Livestock

Desa/Village

(1)

Sapi/ Kerbau Kuda/ Kambing/ Domba/ Cow /Buffalo Horse Goat Sheep (2)

(3)

1. Renun 2. Pasir Tengah

3. Pamah

–

(4)

(5)

(6)

–

Babi/ Pig (7) 34

–

112

–

119

5. Tanah Pinem

–

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

4. Kuta Buluh

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

—

18. Pasir Mbelang

–

19. Sinar Pagi

–

230

1152

–

Jumlah/Total

999

Sumber : UPTD DP3 Kecamatan Tanah Pinem Source : Branch Office of Agriculture and Food Resilience at Tanah Pinem

80 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 5.12 Table

Banyaknya T218ernak- Unggas Menurut Jenisnya dan Desa Number of Poultry by Types and Village (ekor/tail) 2015

Jenis Ternak Unggas/ Types of Poultry Desa/Village Ayam Buras/ Local Chicken (1)

(2)

Itik/ Itik manila/ Duck (3)

Jumlah/ Total

(4)

1. Renun

428

499

2. Pasir Tengah

419

442

3. Pamah

1618

1662

4. Kuta Buluh

1243

1277

5. Tanah Pinem

912

939

6. Kempawa

324

340

7. Kuta Gamber

524

556

8. Lau Primbon

541

584

1015

1030

378

396

9. Harapan 10. Gunung Tua 11. Sukadame

1613

1674

12. Lau Tawar

985

1016

13. Mangan Molih

798

835

14. Lau Njuhar I

1577

1619

15. Liang Jering

912

937

16. Alur Subur

718

740

17. Balandua

453

461

18. Pasir Mbelang

672

703

19. Sinar Pagi

628

645

15758

597

16355

Jumlah/Total

Sumber : UPTD DP3 Kecamatan Tanah Pinem Source : Branch Office of Agriculture and Food Resilience at Tanah Pinem

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Tanah Pinem Subdistrict in Figures 2016

Tabel : 5.13 Table

Produksi Ikan Tawar Menurut Desa Production of Water Fish by Village (ton/ton) 2015

Desa/Village (1)

Ikan Tawar/Water Fish (2)

1. Renun

–

2. Pasir Tengah

–

3. Pamah

0,40

4. Kuta Buluh

0,20

5. Tanah Pinem

0,30

6. Kempawa

0,30

7. Kuta Gamber

–

8. Lau Primbon

0,10

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

0,45

12. Lau Tawar

0,50

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi Jumlah/Total

0,22 2,47

Sumber : UPTD DP3 Kecamatan Tanah Pinem Source : Branch Office of Agriculture and Food Resilience at Tanah Pinem

82 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Badan Pusat Statistik Kabupaten Dairi

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Tanah Pinem Subdistrict in Figures 2016

84 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

BAB VI PERINDUSTRIAN

Berdasarkan data Kecamatan Tanah Pinem pada tahun 2015 jumlah Kilang Padi sebanyak 5. Sedangkan jumlah Usaha Bengkel

sebanyak 18

Usaha. Untuk Jumlah Industri Pertambangan Galian C di Kecamatan Tanah Pinem Ada sebanyak 18 Usaha.

Menurut jenis usaha, industry pengolahan yang paling banyak di Kecamatan Tanah Pinem adalah usaha bengkel sepeda motor, diikuti oleh Pertambanagan Galian C.

Badan Pusat Statistik Kabupaten Dairi

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Tanah Pinem Subdistrict in Figures 2016

CHAPTER VI MANUFACTURING

Based on data from the District Land Pinem 2015 Kilang Padi number as many as 5. While the number as many as 18 Enterprises Repair Enterprises . For the amount of the Mining Industry in Sub Soil Excavation C Pinem There are a total of 18 businesses .

According to the type of business , processing industry the most in Tanah Pinem is a motorcycle repair business , followed by Pertambanagan Excavation C.

86 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 6.1 Table

Banyaknya Industri dan Pertambangan/Galian C Menurut Jenis dan Desa Number of Worker Service by Types and Village 2015 Jenis Industri/ Type of Industry

Desa/Village

(1)

Besar dan Sedang/ Middle Industry

Kecil*/ Small Industry

(2)

(3)

Rumah PertambanTangga/ gan Galian C Houshold Industry (4) (5)

1. Renun

–

2. Pasir Tengah

–

3. Pamah

–

4. Kuta Buluh

–

5. Tanah Pinem

–

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

Jumlah/Total

Sumber : Kepala Desa Se-Kecamatan Tanah Pinem Source : Whole Village Chief of Tanah Pinem Sub Regency

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Tanah Pinem Subdistrict in Figures 2016

Tabel : 6.2 Table

Banyaknya Kilang Padi dan Pedagang Eceran Menurut Desa Number of Paddy Factory and Retailer by Village (perusahaan/establishment) 2015

Kilang Padi/ Paddy Factory

Desa/Village (1)

(2)

1. Renun

–

2. Pasir Tengah

–

3. Pamah

–

4. Kuta Buluh

5. Tanah Pinem

–

6. Kempawa

7. Kuta Gamber

–

8. Lau Primbon

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

Jumlah/Total

Sumber : Kepala Desa Se-Kecamatan Tanah Pinem Source : Whole Village Chief of Tanah Pinem Sub Regency

88 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 6.3 Table

Banyaknya Jasa Pertukangan Menurut Jenis dan Desa Number of Worker Service by Types and Village 2015

Jenis Pertukangan Desa/Village

(1)

Kayu/ Carpenter

Las Karbit

Tambal Ban/ Patch Tire

Jumlah/ Total

(2)

(3)

(4)

(5)

1. Renun

–

2. Pasir Tengah

–

3. Pamah

–

4. Kuta Buluh

–

5. Tanah Pinem

–

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

Jumlah/Total

–

Sumber : Kepala Desa Se-Kecamatan Tanah Pinem Source : Whole Village Chief of Tanah Pinem Sub Regency

Badan Pusat Statistik Kabupaten Dairi

| 89

Tanah Pinem Subdistrict in Figures 2016

Tabel : 6.4 Table

Banyaknya Bengkel Menurut Jenis Bengkel dan Desa Number of Workshop by Types and Village (usaha/establishment) 2015

Jenis Bengkel/Types of Workshop Desa/Village

(1)

Mobil/ Car

Sepeda Sepeda/ Lainnya/ Motor/ Bicycle Others Motorcycle

Jumlah/T otal

(2)

(3)

(4)

(5)

(6)

1. Renun

–

2. Pasir Tengah

–

3. Pamah

–

4. Kuta Buluh

–

5. Tanah Pinem

–

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

Jumlah/Total

–

Sumber : Kepala Desa Se-Kecamatan Tanah Pinem Source : Whole Village Chief of Tanah Pinem Sub Regency

90 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 6.5 Table

Banyaknya Keluarga Pelanggan Listrik Menurut Desa Number of Electricity Customers Family by Village (keluarga/family) 2015

Keluarga Pelanggan/ Family Household Desa/Village

(1)

PLN/ PLN

Non PLN/ Non PLN

(2)

(3)

1. Renun

206

2. Pasir Tengah

378

3. Pamah

609

4. Kuta Buluh

498

5. Tanah Pinem

354

6. Kempawa

235

7. Kuta Gamber

214

8. Lau Primbon

233

9. Harapan

498

10. Gunung Tua

107

11. Sukadame

248

12. Lau Tawar

338

13. Mangan Molih

211

14. Lau Njuhar I

299

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

230

18. Pasir Mbelang

255

–

19. Sinar Pagi Jumlah/Total

5003

357

Sumber : Kepala Desa Se-Kecamatan Tanah Pinem Source : Whole Village Chief of Tanah Pinem Sub Regency

Badan Pusat Statistik Kabupaten Dairi

| 91

Tanah Pinem Subdistrict in Figures 2016

Tabel : 6.6 Table

Banyaknya Rumah Tangga Pelanggan PAM Menurut Desa Number of Drinking Water Customers by Village (rumahtangga/household) 2015

Rumahtangga Pelanggan/ Customers Household Desa/Village Aktif/ Active

Tidak Aktif/ Non Active

(2)

(3)

1. Renun

–

2. Pasir Tengah

–

(1)

3. Pamah

–

4. Kuta Buluh

131

5. Tanah Pinem

–

108

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

239

Jumlah/Total Sumber : Kepala Desa Se-Kecamatan Tanah Pinem Source : Whole Village Chief of Tanah Pinem Sub Regency

92 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Badan Pusat Statistik Kabupaten Dairi

| 93

Tanah Pinem Subdistrict in Figures 2016

94 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

BAB VII PERDAGANGAN

Berdasarkan data dari Kecamatan Tanah Pinem Jumlah Usaha Eceran sebanyak 32Usaha yang tersebar di seluruh desa di Kecamatan Tanah Pinem didominasi oleh Warung Nasi

32 Usaha. Sedangkan Jasa Perseorangan

sebanyak 7 yang terdiri dari tukang pangkas rambut dan tukang jahit.

Badan Pusat Statistik Kabupaten Dairi

| 95

Tanah Pinem Subdistrict in Figures 2016

CHAPTER VII TRADE

Based on data from the District Land Pinem Total Retail Business as 32Usaha scattered around the village in the district of Tanah Pinem dominated by Warung Nasi 32 Enterprises . Meanwhile, as many as 7 Individual Services consisting of barbers and tailors .

96 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 7.1 Table

Banyaknya Warung Nasi Menurut Desa Number of Tavern Rice by Village (buah/unit) 2015

Desa/ Village (1)

Warung Nasi (3)

1. Renun

2. Pasir Tengah

3. Pamah

4. Kuta Buluh

5. Tanah Pinem

–

6. Kempawa

7. Kuta Gamber

8. Lau Primbon

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

19. Sinar Pagi

Jumlah/Total

Sumber : Kepala Desa Se-Kecamatan Tanah Pinem Source : Whole Village Chief of Tanah Pinem Sub Regency

Badan Pusat Statistik Kabupaten Dairi

| 97

Tanah Pinem Subdistrict in Figures 2016

Tabel : 7.2 Table

Banyaknya Jasa Perseorangan Menurut Jenisnya dan Desa Number of Individual Service by Type and Village (buah/unit) 2015 Jasa Perseorangan/ Individual Service Desa/ Village

(1)

Pangkas Rambut/ The Poune Hair (2)

Tukang Jahit/ Tailor (3)

Kolam Panas/Hot Pool (4)

1. Renun

–

2. Pasir Tengah

3. Pamah

–

4. Kuta Buluh

–

5. Tanah Pinem

–

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

Jumlah/Total

Sumber : Kepala Desa Se-Kecamatan Tanah Pinem Source : Whole Village Chief of Tanah Pinem Sub Regency

98 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Badan Pusat Statistik Kabupaten Dairi

| 99

Tanah Pinem Subdistrict in Figures 2016

100 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

BAB VIII PERHUBUNGAN DAN KOMUNIKASI

Kecamatan Tanah Pinem yang berlokasi di daratan

memiliki

infrastruktur jalan yang cukup memadai. Jumlah Sarana Angkutan Umum adalah sebanyak 71, dengan rincian Pick Up 38, Becak moto 10, Truck 23.

Badan Pusat Statistik Kabupaten Dairi

| 101

Tanah Pinem Subdistrict in Figures 2016

CHAPTER VIII TRANSPORTATION AND COMUNICATION

Tanah Pinem located on the mainland have adequate road infrastructure . Number of Public Transport Means are as many as 71 , with details Pick Up 38 , Pedicab moto 10 , Truck 23 .

102 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 8.1 Table

Banyaknya Sarana Angkutan Menurut Jenis dan Desa Number of Transportation Facility by Types and Village (buah/unit) 2015

Jenis Sarana Angkutan/ Types of Transportation Facility Desa/Village

(1)

Kapal Becak Jumlah/ Oplet/ Total Motor/ Bus/ Pickup/ Truk/ Mesin/ Mini Motor Bus Pickup Truck Motor bus Boat Pedicab (2)

(3)

(4)

(5)

(6)

(7)

(8)

1. Renun

–

2. Pasir Tengah

–

3. Pamah

–

4. Kuta Buluh

–

5. Tanah Pinem

–

6. Kempawa

–

7. Kuta Gamber

–

8. Lau Primbon

–

9. Harapan

–

10. Gunung Tua

–

11. Sukadame

–

12. Lau Tawar

–

13. Mangan Molih

–

14. Lau Njuhar I

–

15. Liang Jering

–

16. Alur Subur

–

17. Balandua

–

18. Pasir Mbelang

–

19. Sinar Pagi

–

Jumlah

Sumber : Kepala Desa Se-Kecamatan Tanah Pinem Source : Whole Village Chief of Tanah Pinem Sub Regency

Badan Pusat Statistik Kabupaten Dairi

| 103

Tanah Pinem Subdistrict in Figures 2016

Tabel : 8.2 Table

Banyaknya Rumah Tangga Pemilik Televisi dan Antena Parabola Menurut Desa Number of Household Who own The Television and Parabola Antena by Village (rumahtangga/household) 2015

Desa/Village

Televisi / Television

Televisi dan Antena Parabola/ Television and Parabola Antena

Jumlah/ Total

(1)

(2)

(3)

(4)

1. Renun

–

185

2. Pasir Tengah

–

233

3. Pamah

–

525

4. Kuta Buluh

–

486

5. Tanah Pinem

–

352

6. Kempawa

–

189

7. Kuta Gamber

–

197

8. Lau Primbon

–

305

9. Harapan

–

497

10. Gunung Tua

–

11. Sukadame

–

258

12. Lau Tawar

311

13. Mangan Molih

185

14. Lau Njuhar I

327

15. Liang Jering

16. Alur Subur

17. Balandua

216

18. Pasir Mbelang 19. Sinar Pagi Jumlah

225

–

4677

Sumber : Kepala Desa Se-Kecamatan Tanah Pinem Source : Whole Village Chief of Tanah Pinem Sub Regency

104 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Badan Pusat Statistik Kabupaten Dairi

| 105

Tanah Pinem Subdistrict in Figures 2016

106 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

BAB IX KEUANGAN

Berdasarkan data Kantor Kecamatan Tanah Pinem besaran pokok penetapan Target PBB di Kecamatan Tanah Pinem adalah sebesar Rp. 128.781.285 dan realisasi penerimaan pajak sebesar Rp. 119.505.987

Untuk Realisasi Penerimaan Pajak

terbesar ada pada Pamah

sebesar Rp. 14.825.822 dan terendah ada pada desa Lau Primbon sebesar Rp. 2.006.602

Badan Pusat Statistik Kabupaten Dairi

| 107

Tanah Pinem Subdistrict in Figures 2016

CHAPTER IX FINANCE

Based on data from the Office of the District Land Pinem principal amount determination UN target in Tanah Pinem is Rp . 128.781.285 and tax revenues of Rp . 119.505.987

Revenues for the largest tax there on Pamah Rp . 14.825.822 and the lowest is in the village of Lau Primbon Rp . 2.006.602

108 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Tabel : 9.1 Table

Besarnya Pokok Penetapan dan Realisasi Penerimaan Pajak Bumi dan Bangunan (PBB) Menurut Desa Number of Fixed Target and Realization of Land and Building Tax Revenue by Village (rupiah/rupiahs) 2015

Badan Pusat Statistik Kabupaten Dairi

| 109

Tanah Pinem Subdistrict in Figures 2016 Tabel : 9.1 Table

Besarnya Pokok Penetapan dan Realisasi Penerimaan Pajak Bumi dan Bangunan (PBB) Menurut Desa Number of Fixed Target and Realization of Land and Building Tax Revenue by Village (rupiah/rupiahs) 2015

Desa/Village (1) 1. Renun

Pokok Penetapan/ Fixed Target (2)

Realisasi/ Realization

Persentase/ Percentage (%)

(3)

(4)

12270398

10235550

7320545

100

14826822

14825822

100

4. Kuta Buluh

5240995

100

5. Tanah Pinem

7207623

100

6. Kempawa

4160458

100

7. Kuta Gamber

2734651

100

8. Lau Primbon

2006602

100

9. Harapan

3282948

100

10. Gunung Tua

5844200

5884200

100

11. Sukadame

6209158

100

12. Lau Tawar

3795278

100

13. Mangan Molih

8638250

100

14. Lau Njuhar I

9459212

9459121

100

15. Liang Jering

5773025

100

16. Alur Subur

5951250

100

17. Balandua

12884750

5418300

18. Pasir Mbelang

3738220

100

19. Sinar Pagi

7436900

7064000

128781285

119505987

9280

2. Pasir Tengah 3. Pamah

Jumlah/Total

Sumber : Kantor Camat Tanah Pinem Source : Tanah PinemSub Regency Office

110 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Badan Pusat Statistik Kabupaten Dairi

| 111

Tanah Pinem Subdistrict in Figures 2016

112 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016

Lampiran : 1 Appendix

Nama-Nama Camat Tanah Pinem Menurut Tahun Masa Jabatan Names of Chief of Tanah PinemSub Regency by Years of Duty Period

Nama/Names

Tahun Masa Jabatan/ Year of Duty Period

Drs. W. Nababan

1990 – 1993

Jainal Sinamo, BA

1993 – 1994

G.P Limbong, BA

1994 – 1996

Drs. Tigor Solin

1996 – 1998

Drs. Ramses Simamora

1998 – 1999

Drs. Adil Tarigan

1999 – 2007

Suasta Ginting, S.Sos., M.AP

2007 – 2009

Drs. Tambar Barus

2009 – 2012

Robert Ginting, AP, M.Si

2012 – 2015

10 Pusuh Karo-karo

2015 – sekarang

Sumber : Kantor Camat Tanah Pinem Source : Tanah PinemSub Regency Office

Badan Pusat Statistik Kabupaten Dairi

| 113

Tanah Pinem Subdistrict in Figures 2016

Lampiran : 2 Appendix

Nama-Nama Kepala Kepolisian Sektor (Kapolsek) Kecamatan Tanah PinemMenurut Tahun Masa Jabatan Name of Chief of Police Station Sector of Tanah Pinem Sub Regency by Years of Duty Period

Nama/Names

Tahun Masa Jabatan/ Year of Duty Period

AKP. JF. MANURUNG

2008 – 2010

AKP. ISDIPIRO

2010 – 2012

AKP. L. SIREGAR

2012 – 2013

AKP. K. SARAGIH

2013 – 2014

AKP. ILHAM HARAHAP, S.H

2015 – sekarang/Now

Sumber : POLSEK Kecamatan Tanah Pinem Source : Police Station Sector of Tanah Pinem Sub Regency

114 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016 Lampiran : 3 Appendix

Desa/Village

Nama Kepala Desa Menurut Jenis Kelamin, Status, dan Desa Names of Village Chief by Sex, Status, and Village 2015 Nama Kepala Desa Names of Village Chief

(1)

(2)

Jenis Kelamin/ Sex

(3)

Status/

(4)

Renun

Losta Sembiring

Lk/Male

Pasir Tengah

Mia Maha

Pr/Female

Depenitif

Pamah

Resepsi Ginting

Lk/Male

Depenitif

Kuta Buluh

Sastra Pinem

Lk/Male

Depenitif

Tanah Pinem

Arjuna Kaban

Lk/Male

Pejabat

Kempawa

Alexander

Lk/Male

Pejabat

Kuta Gamber

Praten Ginting

Lk/Male

Pejabat

Lau Primbon

Minpin Karo-karo

Lk/Male

Pejabat

Harapan

Asnawati Tarigan

Pr/Female

Pejabat

10.

Gunung Tua

Syunario

Lk/Male

Pelaksana Tugas

11.

Sukadame

Jon Action Ginting

Lk/Male

Pelaksana Tugas

12.

Lau Tawar

Beres Tarigan

Lk/Male

Depenitif

13.

Mangan Molih

Rimbun Maha

Lk/Male

Penjabat

14.

Lau Njuhar I

Drs. Arjuna Maha

Lk/Male

Depenitif

15.

Liang Jering

Abdullah Solin

Lk/Male

Pejabat

16.

Alur Subur

Jonnis Berutu

Lk/Male

Pelaksana Tugas

17.

Balandua

Antonius Pinem

Lk/Male

Pejabat

18.

Pasir Mbelang

Aster Anakampun

Pr/Female

19.

Sinar Pagi

Bernadus Sinaga

Lk/Male

Pejabat

Pelaksana Tugas Pejabat

Sumber : Kantor Camat Tanah Pinem Source : Tanah PinemSub Regency Office

Badan Pusat Statistik Kabupaten Dairi

| 115

Tanah Pinem Subdistrict in Figures 2016 Lampiran : 4 Appendix

Nama Muspika Menurut Jabatan dan Pangkat Names of Muspika by Position and Rank 2015

Nama/ Name

Jabatan/ Position

(1)

1. Pusuh Karo-karo

(2)

Pangkat/ Rank (3)

Camat

IVA

2. Ilham Harahap, S.H

Kapolsek

AKP

3. Joni Sihombing

Danramil

Kapten

Sumber : Kantor Camat Tanah Pinem Source : Tanah PinemSub Regency Office

116 |

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016 Lampiran : 5 Daftar Nama Dusun dan Nama Kepala Dusun Menurut Desa Appendix List Name of Hillbily dan Name by Village 2015 Desa/Village (1) 1. Renun

2. Pasir Tengah

3. Pamah

4. Kuta Buluh

5. Tanah Pinem

6. Kempawa

7. Kuta Gamber

Badan Pusat Statistik Kabupaten Dairi

Nama Dusun (2) Renun Inpres Lau Timah Cinta Damai Bukit Harapan I Bukit Harapan II Kampung Dalam Simpang Tiga Fajar Harapan Lau Gunung I Bunga Ncole Kampung Dalam Pamah I Pamah II Gunung Mulia Simpang Pamah Lau petundal I Lau Petundal II Simpang Lau Petundal Kuta Buluh Bawah Lau Belin Pekan Tiga Tuah Kuta BuluhAtas Tanah Pinem I Tanah Pinem II Tanah Pinem II Kampung Jawa Kempawa Durian Kuta Nangka Kuta Gamber Liren Simpang Tiga

Nama Kepala Dusun (3) Sempa Kita Sembiring Nasmara Tarigan Donna Karo-karo Piser Ginting Mateus Berutu Natal Padang D. Sudi Darma Putra Pinem Andhy Soesanto P Apollo Sagala

Undang Ginting Nasaretta Pinem Sempurna Pinem Rafael Ginting Sentral Sebayang Jumpa Jon Purba Bero Sembiring Datar Tarigan Dekrit Sabar Tarigan Candera Pinem Peraten Ginting –

| 117

Tanah Pinem Subdistrict in Figures 2016 Lampiran : 5 Appendix

Lanjutan/Continued

Desa/Village (1)

8. Lau Primbon

(2) Lau Primbon Lau Primbon Kepar

9. Harapan

Nama Kepala Dusun (3)

Nama Dusun

Karsa Sembiring

Lau Sungsang

Ngantar Pinem

Tanjung Jati

Adil Padang

Buluh Lagah

Perdamen Sembiring

Kuta Mbaru Inpres Kuta Mbaru Atas

Jandia Karo-karo

Kuta Mbaru Bawah

10. Gunung Tua

11. Sukadame

12. Lau Tawar

13. Mangan Molih

118 |

Lau Meciho I

Antoni Ginting

Lau Meciho II

Sabar Pinem

Kuta Pinang

Sisma Manik

Kampung Jawa

Tukino

Buluh Sema

Joes Tarigan

Inpres Lau Lubuk

Bahagia Sembiring

Simpang Payong

–

Juma Batu

Musim Barus

Pamah Silep-lep

Saman Pinem

Pinem

Tomi Jefisa Ginting

Ramah Telko

Lala Ziduhu

Sigedeng

Basmi Karo-karo

Barisan Gereja

–

Lau Tawar

Laksana Pinem

Tanjung Pamah

Eddy Suranta Tarigan

Lau Rambong

Daniel Sembiring

Mangan Molih

Raskami Ginting

Namo Sangar

Rimbun Maha

Lau Njuhar

Thomas Maha

BPS- Statistics of Dairi Regency

Kecamatan Tanah Pinem Dalam Angka 2016 Lampiran : 5 Appendix

Lanjutan/Continued

Desa/Village (1)

14. Lau Njuhar I

Nama Kepala Dusun (3)

Nama Dusun (2) Lau Njuhar Lau Njuhar I

Mahdi Berutu

Lau Njuhar II Muara Lau Sige

Riskon Maha

Lau Melas

15. Liang Jering

Inpres

Juanda Maha

Mbal-mbal

Bangsawan Berutu

Liang Jering I

Abdullah Solin

Gereja/Liang Jering Bawah Jahiller Bancin

16. Alur Subur

Siudang-udang

Julani Banurea

Sada Arih

Pusman Solin

Deleng Datok

Rasutin Berutu

Simpang Lima

–

Alur Subur

Rensitol Berutu

Kilang

Waspada Sembiring

Simpang Aman

Arus Manik

Bom

Julaidar Berutu

Km 27 Mesjid

17. Balandua

18. Pasir Mbelang

19. Sinar Pagi

Butar

Kalpinus Bangun

Pondok

Andel Kaban

Lau Riman

Koprasi Ginting

Pasir Mbelang

Aster Anak Ampun

Rambingen

Obet Sembiring

Kampung Baru

Erni Suryani Manik

Lau Peske

Reksa Sembiring

Dusun I Blok Darat

Hotma Solin

Dusun II Blok Karo/Mesi

Mangasi Situmorang

Blok III Parhutaan

Radot P Sdabutar

Blok iv Liang Galuh

Malintong Manik

Sumber : Kantor Camat Tanah Pinem Source : Tanah PinemSub Regency Office

Badan Pusat Statistik Kabupaten Dairi

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ORSON WELLES’ MEMO ON By Lawrence French In 1998, after 40 years, the world finally got to see Orson Welles TOUCH OF EVIL as the director intended it. And unlike some other Welles films that have been restored, rediscovered or re-edited, (i.e. DON QUIXOTE, OTHELLO and IT’S ALL TRUE), the changes in TOUCH OF EVIL were carried out with a scrupulous attention to detail, that is truly in the spirit of Orson Welles. Of course, no one can say for certain, just how Welles would have edited his movie, but as can be seen in reading Welles’ long memo of detailed editing instructions, producer Rick Schmidlin and editor Walter Murch have come up with the closest approximation that we’re ever likely to get. Why TOUCH OF EVIL needed to be re-edited in the first place is a rather complex tale, that requires some background. In 1957, Universal took the film out of Welles hands, after he had spent about three months in the cutting room. As Welles was the first to admit, he worked very slowly while editing. “I could work forever on the editing of a film,” Welles told Cahiers du Cinema in 1958. “I don’t know why it takes me so much time, but that has the effect of arousing the ire of the producers, who then take the film out of my hands.” After completing a rough cut, in July of 1957, Welles left the editing of the film to Universal staff editor Aaron Stell. That fall, when Welles returned and was shown the results of the studio’s re-cut, he wrote a heart-felt 58 page letter to Universal’s head of production, Edward Muhl. Unfortunately, many of Welles suggested changes went unheeded, and TOUCH OF EVIL was eventually released in February, 1958 in an aborted version that ran only 93 minutes. The 93 minute version was all that was available for 18 years-until 1976, when Universal put a longer 108 minute version they accidentally uncovered in their archives into circulation. Of course, back in 1976, Welles was still alive, and in retrospect, it seems rather unfortunate that Universal never bothered to consult him about making changes to TOUCH OF EVIL. However, at the time, the video and laserdisc market had yet to emerge, and the idea of a director’s cut was virtually unheard of. Although, when Universal released the longer version of TOUCH OF EVIL on video, they mistakenly called it a “complete uncut and restored version.” This, however was certainly not the case, because while the long version had 15 minutes of additional footage, including three important scenes directed by Welles, it also contained more footage directed by Harry Keller. Universal hired Keller to shoot clarification scenes, after Welles had been removed from the picture. Why Universal executives would go to the expense of shooting these additional scenes and not include them in the released picture (the 93 minute version), has never been adequately explained. In any case, neither of the two versions of TOUCH OF EVIL that have been in circulation for the past 40 years are what Orson Welles intended. To correct that, the re-editing was undertaken.

Part of the impetus behind the re-edit seems to be a vast interest and re-discovery of Orson Welles work, which is somewhat ironic, since Welles had so much difficulty financing projects while he was alive. For instance, it seems rather strange that Welles’ unfinished films and screenplays are still coming to light, (along with films that feature Welles as a character, like RKO 291 and THE CRADLE WILL ROCK) – while during his lifetime, he couldn’t find any financing for making movies. The possibility of re-editing TOUCH OF EVIL began in 1992, when Welles scholar Jonathan Rosenbaum published excerpts from Welles’ memo in FILM QUARTERLY. Subsequently, the memo came to the attention of producer Rick Schmidlin, who had long been a fan of TOUCH OF EVIL. Schmidlin was initially interested in doing a laserdisc version of TOUCH OF EVIL that would include commentary by Charlton Heston and Janet Leigh, as well as documenting the different versions of the film. However, Universal executives were so sold on the merits of re-cutting the film, they deemed a theatrical re-release would be in order. What should be specifically emphasized about the re-editing of TOUCH OF EVIL, is that when Welles wrote his memo in December of 1957, he had been completely barred from the editing of the film. Therefore, the intention of his memo was to get Universal executives to make the changes he wanted-even though Welles knew he would not be allowed to supervise those changes. That’s why Welles’ memo contained such detailed instructions-so Universal’s staff editors could implement the editing changes without Welles actually being there. That is also why, even though Welles is no longer alive, the cutting could be carried out 40 years later, and still follow Welles wishes fairly closely. Welles wrote his memo so any experienced film editor could implement the changes, although he was fully aware that Universal might not make them as perfectly as if he where there guiding the cutting in person. He wrote to Charlton Heston, hoping to enlist his aid in getting the changes made, telling him, “that memo represented my notion of the minimum number of improvements necessary. It’s my fear that (Universal’s) execution of these changes will leave something to be desired, since they may be acting without much enthusiasm, but most importantly, because they will be working in great haste.” In 1958 Universal elected to ignore most of Welles requests. But in 1998, Walter Murch-one of the finest editors in the business-was able to implement them with the kind of enthusiasm that Welles felt might be lacking from those in charge at Universal. The end results, are well worth the 40 year wait, although they are surprising subtle. There is no new footage on view, nor any attempt to convert the original mono soundtrack to stereo-so none of the changes jump out at a viewer familiar with the previous versions. However, there is little doubt that the film plays better than ever before. Besides re-editing the film, the entire negative was beautifully restored, by Universal’s in house preservation expert, Bob O’Neil. Welles originally shot most of the movie at night, on locations in Venice, California and (along with his cinematographer, Russell Metty), got the kind of rich black and white, high contrast look that has become such a Welles trademark. So even if the film hadn’t been re-edited to Welles specifications, it would

now be well worth seeing, solely for the pleasure of experiencing it’s images so gorgeously restored. It’s often been said that Welles was far ahead of his time, so it may be that only now-40 some years after it was made, that TOUCH OF EVIL can truly be appreciated. The complete text of Welles memo follows, along with notations (in bold) on the changes were made to the three different versions of the film. The following notes were received from Orson after he viewed the re-cut version of the entire picture which included the new close-up shots directed by Harry Keller.

Memo From Orson Welles ———————————————————————–DATE: December 5, 1957 TO: Edward I. Muhl, Vice-President in charge of production Universal-International Pictures FROM: Orson Welles, writer and director of TOUCH OF EVIL. I much regret that a business meeting Friday and illness Monday prevented me from seeing the picture until Tuesday. Work on the following notes was commenced as soon afterwards as I could obtain help in the typing. Unhappily, my illness has slowed me up somewhat, and an unexpected shortage in secretarial help finds me, at the end of a long day, without a fair copy of the remainder of these notes to put into your hands. I shall go on working through the night, however, and with typists getting an early start tomorrow, it’s safe to promise you the complete memo sometime before the end of the morning. I assume that the music now backing the opening sequence of the picture is temporary… As the camera roves through the streets of the Mexican bordertown, the plan was to feature a succession of different and contrasting Latin American musical numbers the effect, that is, of our passing one cabaret orchestra after another. In honky-tonk districts on the border, loudspeakers are over the entrance of every joint, large or small, each blasting out it’s own tune by way of a “comeon” or “pitch” for the tourists. The fact that the streets are invariably loud with this music was planned as a basic

device throughout the entire picture. The special use of contrasting “mambo-type” rhythm numbers with rock ‘n’ roll will be developed in some detail at the end of this memo, when I’ll take up details of the “beat” and also specifics of musical color and instrumentation on a scene-by-scene and transition-by-transition basis. In the version I was shown yesterday, it’s not clear where you have decided to place the credits. A brief report on this will determine whether or not my old ideas for sound and music patterns in this opening reel are still of some potential value. Since a clear description of this original plan will occupy some space and take a little more time to put together, I’ll postpone this pending your reply. The moment when Vargas says to Susan, “Don’t be morbid…” is an unpleasant one and creates a harmful impression. (In an earlier memo, I made a strong point of this.) ———————————————————————–This is the scene as it appeared in Welles’ script: REVERSE ANGLE – NEAR THE FLAMING WRECK OF THE CAR The following sequence is photographed with a hand camera the operator following Mike and Susan through the crowd on foot. Mike, followed by Susan, is running forward when an OLD MAN (a field-hand type) dashes by, going in the other direction. Mike stops him and there is a swift exchange in Spanish. SUSAN Mike! – What’s happened? The old man dashes OFF SCENE. Mike continues hurrying toward the scene of the accident, Susan tagging along at his side. MIKE It exploded –

SUSAN (breathlessly, by now they are almost running) Just the car? – How could it do that? MIKE I’d better find out, Susie. Don’t you come any closer… it’s bound to be messy… We’ll have to postpone the soda, I’m afraid SUSAN (catching up with him) Why? – Can’t I come and see, too? MIKE (turning back with a nervous laugh) Darling, don’t be morbid. SUSAN (Flaring up a trifle) Well, what are you being, for golly’s sake? Anyway, it happened over here on the American side – so MIKE (his voice hardens) So it’s none of my business? SUSAN (after a moment) That’s sort of what I mean, I guess. MIKE (very serious) You’re wrong, love. This could be very unpleasant for us… SUSAN For us – ? MIKE I mean for Mexico. (Sighs) There’s probably nothing I can do –

So –

SUSAN

MIKE So I’ll try not to be too long about it. He kisses her in haste but very tenderly – then turns and breaks into a run. HAND CAMERA FOLLOWING HIM TO THE wrecked car. Policemen are holding off the gathering crowd. ———————————————————————–The present editing not only retains this line, but the cut between Vargas’s leading Susan off-scene and their next two-shot is very rough. The original editing of this particular little section was really quite effective and I honestly can’t see what, from any point of view, has been accomplished by tearing it up and re-building it in this form. In terms of clarity, nothing is gained; considerable excitement has been lost and an unpleasant line (which I regret having written) has been put back in. [This was changed by Universal]. Schwartz’ line: “He must be driving up from that turkey ranch of his”, is unclear and must obviously be dubbed. [The line was changed to: “I got him out of bed at his ranch, he’s on his way.”] “An hour ago, Rudy Linneker had this town in his pocket… etc., etc.” – must also be re-dubbed with considerable more force and attack by Mr. Collins, if the present editing is to be retained. The jump to this from Chief Gould’s line just previous to this is most upsetting to the ear, and I must emphasize that this is not merely a case of “balancing” in the final process of sound-mixing. The Police Chief is literally screaming (to cover sounds of the arriving fire engines, ambulances and other background effects) while Adair in the cut right after it, is speaking in a very subdued mood. It may be that Adair and Gould should both be dubbed again, but it will probably be sufficient to re-do only the Adair line giving it more force. This may seem an un-important detail, but the abrupt, very extreme contrast in attack between these two brief cuts needlessly underlines the arbitrary character of

the editing at this point and, without re-dubbing, is bound to create a most upsetting effect. The pace would be helped if a part of the line “that I don’t think Mr. Vargas claims… etc., etc.” be laid over the close-up of Vargas. Resigned as I am to the fact that a great majority of my previous notes and suggestions have been disregarded, the case of the scene between Grandi and Susan is one of the few issues I feel justified in reopening. This scene is just exactly a thousand percent more effective played, as it was first arranged, in two parts, with a cutaway to the scene of the explosion between those two parts. No matter how the scene is edited, this scene has – and was intended to have – a curious, rather inconclusive quality. It was written that way and directed and played that way. The audience is presented with a menacing villain who does not, in fact, succeed in being very menacing after all. He takes a threatening tone with Susan, but as it turns out, his threats are vague and the audience must begin to realize (if the scene works at all) that he’s actually more frightened than frightening. Dividing this scene in two parts, as we intended, and keeping the situation with Vargas at the scene of the explosion “alive” in the audience’s mind, is not to confuse but to clarify. Making a short contrapuntal reference to what is going on across the border underlines and precisely illustrates the correct values. Absolutely nothing is gained by gluing these two parts together, except to make the total scene seem rather long and rather shapeless. The shooting was done, for the most part, on location, certain reverses and close-ups having been picked up in the studio. Now I did not allow in shooting these for a version in two parts, and hence, there is no available footage for continuous action. As the editing now stands, the welding of these two parts has been managed with as much skill as the resources in actual film made possible, and I congratulate whoever made the attempt. It remains, however, just that: an attempt. The off stage dialogue “…who sent to make trouble…” (there is more to the line than this but I have no covering note) which is now laid over the rather lengthy shot of “Pancho” is an ingenious effort, but as a real solution in the editing it simply does not – and cannot – come off.

When photography falls sharply below a particular standard, cameramen say that the scene shot is not “commercial.” They do not, of course, mean that it is too “artistic” for the commercial market, but that the physical quality of the film is not up to the ordinary minimum standards generally required for exhibition. The sort of editing it was necessary to resort to in the attempt to force these two parts of a sequence into the form of a single scene can only be described in the same way: it is simply not commercial. By all means retain, in its main lines the edited form of this reel as you now have it put together. Little of the admirable labors of Ernie Nims and his assistants in behalf of clarity need be lost, but let me urge very earnestly that the cutaway from Grandi – in which he was just starting to menace Susan (the scene’s deliberately anticlimatic quality, not at this point, having been established) be retained. The cut by which we returned to Grandi (after a brief visit to the scene of the explosion) with his violent movement towards the mirror and the line: “We used to have a nice quiet town around here!” – was also a very good cut indeed. Both were exceptionally effective and cry out to be restored. In the desire to completely re-edit and rearrange these opening reels, I do sincerely believe that the decision to unite the two Grandi scenes into a single sequence was born of an overall desire for simplification and clarity – and, granting the worth of the other cuts, this was the one change too many. This was the one alteration which cannot be defended from any point of view in terms of its result. What matters is the really rough jump in editing, – unavoidable in the present version. If I’d been one of your number during the editorial discussions, I should know whom to address on this question which I consider to be so important. As it is, I can only plead with whoever it was who championed the notion that these two scenes be joined together as one – plead that since all other rearrangements in all these opening sequences are now fixed in an acceptable form, the GrandiSusan scene be re-examined with an open mind. No great effort will be needed to find the proper footage for intercutting from the wealth of material available from the various scenes which play by the flaming car. It’s my opinion that the entrance of Quinlan should be saved for

this. I think that moving the conflict between Quinlan and Vargas closer to the street scene in front of the hotel will aid clarity and much improve the narrative line. But this is only one of several solutions. Quinlan’s arrival through his line, “Whoever did it, y’ jackass,” and the cut of the blazing car would also make a most effective transition. You would then return to Grandi (by a quick dissolve, if you prefer) for his line, “We used to have a nice quiet town around here!” This would play beautifully. The subject of Grandi’s anxiety would have been dramatically illustrated, we would not have left the scene of the explosion until after all our principals had been established, and the device of cutting away from Quinlan (clearly the most significant figure to appear since the entrance, at the start of the film, of the leading man and leading woman) would pique the audience interest without the remotest danger of confusion. This is in the best, classic tradition of movie continuity, the clinching virtue of which is the fact that in this arrangement we would never stay away from either story Susan’s or Vargas’s long enough to lose their separate but relating threads of interest. But as I’ve said, a number of attractive solutions present themselves. What’s vital is that both stories – the leading man’s and the leading woman’s – be kept equally and continuously alive; each scene, as we move back and forth across the border, should play at roughly equal lengths leading up to the moment at the hotel when the lovers meet again. This simple but drastic improvement, added to the body of Ernie Nims clear and concise version of this opening section of the picture, will put the identification with the characters in a just proportion and in a form which I’m sure you’ll admit, if you’re willing to try it, is irresistibly interesting. No point concerning anything in the picture is made with such urgency and such confidence as this. Do please – please give it a fair try. [These cross-cutting changes were not made by Universal, but were carried out in the ’98 re-edit]. On the cue “Mexico City”, Grandi is interrupted by Pancho who shushes him. This extended “ssh…!” must be dubbed in. This minor detail is mentioned because if forgotten, it might seem that Pancho was speaking a line which had somehow been dropped out of the soundtrack. At the end of the Grandi scene, there is a new trim which is by no means

an improvement. In almost every instance of this kind that is to say, where there’s simply a difference of taste between your editing and mine I have resigned myself to the futility of discussion, and will spare you my comments. In most cases, I can see, or guess, the point of view which has motivated the change, even when I don’t happen, personally, to agree with it. But in some few instances, the point of view remains completely mysterious to me, and in those cases where the improvement is not apparent, and where I cannot fathom the reasons for alteration, I’m registering, as I do here, my objections. This matter of the “trim” isn’t a vital issue one way or the other, but since it took me some considerable work on the moviola to decide on the precise frame to cut away from the Grandi street scene, and again, to pick up Vargas and the others near the hotel, I find it hard to resist pointing out that the new version – though the idea behind it may well be superior – displays a much hastier craftsmanship. [This change was made by Universal]. My earlier memo noted that several “wild” lines were to have been dubbed between Menzies and myself to cover the long move by Vargas across the street and up the alley to the stage door of the cabaret, where he, at last, catches up with the group. True enough, this conversation between the detectives is not absolutely vital to the plot, but the present considerable lengthening of the scene between Vargas and Susan in the hotel lobby, would seem to lend increased importance to the need for keeping the other group “alive” as they proceed across the street toward the night club. On the other hand, I see that it may be also argued that having left this group for a longer period of time, hearing their voices during Vargas’s move across the street may, in fact, tend to be confusing rather that helpful. I raise the point in the form of a question and without any definite recommendation on my own. Since the question of dubbing has been raised here, I should also note that there are several lines of mine in the new and extended version of the scene of the explosion which will have to be dubbed. Quite possibly, Adair, Gould, Menzies and Schwartz must also be dubbed. A single running of the picture did not give me an opportunity to note this in accurate detail. Most of the talking in the new lengthened version of the scene is done by me and what

turns up in my notes as I transcribe them now refers to this dialogue – which is indeed far from distinct. Further on the question of dubbing: A note reminds me that there is a line of Quinlan’s at the end of the quarrel scene, (the scene which plays in front of Tania’s) – a line by Quinlan as he turns away with Menzies and which was not recorded at the time of shooting on location. I stand ready to do this post-synching at what I hope will be your earliest convenience. [Presumably, the line was: “Come on Pete, lets get back to civilization.”] We now come to the first additional dialogue: the new scene between Susan and Vargas. In the light of the decision to deny me permission to direct these scenes, to write the dialogue for them or to collaborate in that writing, or indeed even to be present during your discussions of the matter, I must, of course, face the strong probability that I am the very last person whose opinion will be likely to carry any weight with you. I am, therefore, limiting myself to points which might genuinely interest you – points which seem to me to interfere quite actively with the story itself, and tend to confuse the narrative line. Without going into any question of quality in the actual writing of the dialogue for this added scene in the hotel lobby, I think two points are truly confusing to the simple mechanics of the plot, and this, I suggest, could very probably be fixed by the simple process of dubbing slightly different lines over the scene. To begin with the less important point: Vargas tells his wife to be sure and lock the door to her room. Yet, we will see him later opening this door by a simple turn of the knob. Since she has been genuinely frightened and disturbed, it is a little hard to understand why she has chosen to disregard her husband’s good advice. As the film now stands, his injunction about the door locking is the last thing she hears from him before going to the nearby room, and it isn’t easy to see how she could possibly have forgotten it during the course of that short walk. In the original version, the question of the door being locked is simply not raised. Bringing Susan to the door to unlock it would have changed the basic action in the scene in the hotel room and made Vargas’s semi-comic confusion in the darkness unworkable. Thus, he was through the door and into the room before the audience could have time to think about the question of Susan’s

locking it at all. Anyone who wished to be sharply analytical could have assumed that she had simply neglected to do this – a foolish but not really an idiotic mistake. However, if her husband has told her to lock the door, her failure to do so is underlined, and the audience, forced to think about the whole door-locking business, is given a choice between blaming the director for carelessness, or considering that the character played by the leading lady is flighty to the point of feeble-mindedness. The second point about this new scene in the hotel lobby is, I think, a more important one and has to do with reference to “those boys.” Unfortunately, since this new dialogue was never sent to me, I do not have the exact text and was unable, during a single running of the picture, to write it down in the projection room. The substance, however, of what is said at this point would seem to be that Susan has been impressed by the existence of what she describes as “those boys.” or “those kids.” I believe Vargas also directly refers to them in some such terms. The purpose here, one presumes, was to establish the gang of delinquents, on the face a good idea. But a real difficulty presents itself in terms of logic: Susan has not seen this gang at all and neither has the audience. True, one boy directed her attention towards the photograph, but he could only impress her (and the audience) as being one of several people in the street. As yet, there has been no impression given at all of a group of “kids.” Susan and the audience would remember “Pancho,” some old men, a woman with a baby, and Grandi. Of these, of course, Pancho and Grandi will impress themselves as the significant figures. In other words, we have established a middle-aged gangster and his young henchman, and beyond that, a general, rather vague impression of Mexicans of all different ages and types obviously bearing no special meaning in the story. “Sal” will appear later and so will “Risto.” Only in the scene in the street between Grandi and these three boys will the actual existence of a gang of youths begin to impress itself. This talk of “boys” and “kids” is almost certainly going to have the effect of confusing the audience. If Susan and Vargas had emphasized Grandi, the conversation would be clear. As it is, the natural reaction will be to wonder, “What kids are they talking about?” The whole problem of the opening reels is one of clarity. There are several different sets of characters and innumerable relationships which must be very clearly

established and set off one from the other. I believe that the criticism of my own, unfinished version of these opening reels was entirely justified and, as I told him, Ernie Nims made dramatic progress in reducing this confusion. The added dialogue on the subject of the “kids”, however, is the very contrary to clarification. It poses a question in the audiences mind which cannot logically be answered at this point in the story when we must agree that the slightest sense of bewilderment may spark an irritation and produce that chain reaction of bewilderment which leads so often to a lack of interest. Thus, in the strongest terms possible, I want to urge that you consider this point on its merits. Just as in July you were able to look at the pictures with fresh eyes and with reactions uncompromised by an intimate knowledge of the material, so I am now able to see this added scene as something quite new, and can therefore make a fairer judgment perhaps than those responsible for the scene. A few slight word changes can be made and dubbed onto this footage without difficulty by means of which this bewildering emphasis on the “kids” can be sufficiently reduced, and if I could have the text of this new scene, I would be happy to work on it, and present you immediately with suggested alterations in the dialogue. You will prefer, I suppose, to accomplish this on your own and without any direct collaboration on my part. But do please give the question some thought. [Both scenes with the offending dialogue, referring to the “locked door” and “those kids,” was changed by Universal]. Some specific problems are posed by the introduction of the new scene in the hotel lobby concerning which I simply cannot bring myself to keep silent. The excuse for this added scene, I take it, is clarification of the plot, and perhaps, too, the value of added footage for Miss Leigh and Mr. Heston. But, in terms of the characters they play, and their relationship to each other, I must insist that, as far as the author is concerned – (and for whatever remnant of interest may be attached to his opinion) – this particular new scene goes directly against the intentions of the script, and the original line of the story. This added dialogue makes the later scene (one of my own), in which Susan packs and stamps out of her hotel room, completely arbitrary. Coming, as this does now, quite without emotional preparation of any kind, we wonder what

makes Susan so coldly furious with her husband, and why, when he opens the door, she doesn’t simply throw her arms around him and beg him to take her away from this awful place. The new lobby scene leaves our couple in a fairly warm relationship, and with a perfectly rational understanding of each other. True, the young wife states her opposition to hubby’s police activities in the course of their honeymoon, but her indignation is expressed in a poutingly “cute” sort of tone (a standard cliché reaction of newlyweds in B pictures). She is, in fact, more hurt than angry; this new scene with her husband actually leaves her fairly well resigned to what, as her husband explains it, is to be a short but necessary operation. Thus, the essential tension between them is totally relaxed: we have nothing “cooking” between these two except a hint of their physical interest in each other and their momentary but inconsequential pang at being parted. The original story line went, briefly, as follows: A honeymoon couple, desperately in love, is abruptly separated by a violent incident (the bombing of the car) – an incident which, although it has no personal bearing on either of them, the man considers as a matter of his urgent professional concern. This feeling of responsibility by Vargas is, of course, an expression of the basic theme of the whole picture; further, his wife’s resistance to such masculine idealism, her failure, and even her refusal, to understand is a human and very feminine reaction which any audience can grasp easily and sympathize with. She is, after all, in a foreign country and has been subjected to a series of indignities which irritate and bewilder her and which her husband fails to completely appreciate. Vargas’s behavior and her reaction make it necessary to dramatize and underline this temporary misunderstanding between them. By minimizing it, by sweetening their relationship at the wrong moment, and warming it up at precisely that point where the distance separating the man and woman should be at its greatest, there is a sharp loss in dimension, and both Vargas and Susan emerge as stock characters – the sort of routine “romantic leads” to be found in any programme picture. [The added Hotel scene, directed by Harry Keller, remained in both the release and preview versions. It was eliminated from the ’98 re-edit]. ———————————————————————–Here is the scene as Welles originally intended it:

EXT. AND INT. HOTEL Through the glass window we can see Mike in the lobby, pressing questions on a bellhop. The man shrugs; Mike looking worried – opens the door and comes out into the street just as Susan runs INTO Scene straight into his arms. CAMERA TIGHTENS TO A TWO SHOT MIKE Susie! – Where in the world were you? Where did you go? SUSAN (weakly) Oh, Mike…darling… Just wait till I tell you. This crazy thing that happened to me And she starts to explain. MIKE Tell me later. MED SHOT – QUINLAN’S GROUP – MEXICAN STREET They exchange looks as they come to a halt. QUINLAN Who’s the jane? ADAIR (under his breath) His wife. QUINLAN Well, whatya know – ! (slight pause) She don’t look Mexican either. Quinlan turns and leads the way into Grandi’s Rancho. REVERSE – TIGHT TWO SHOT – MIKE AND SUSAN – HOTEL ENTRANCE

MIKE Darling, let me take you to the hotel. SUSAN (as Mike turns to go) You mean you’re leaving me? MIKE (breaking in gently) I’ll be just across the street I hate leaving you like this, but, after all, I’m working on a case She glares at him; then turns to the honky-tonk. HER VIEWPOINT – FULL SHOT – “GRANDI’S RANCHO” With big cheesecake blow-ups. BACK TO SCENE SUSAN (reading the sign) “Twenty Sizzling Strippers” Some case! Who pinned the tin badge on you. Fearless Fosdick? MIKE Well, Susie SUSAN Oh, for heaven’s sake! MIKE (breaking off, doing a mild double-take) Fosdick? Who’s he? SUSAN (with a sigh) A corny detective in a comic strip. She marches indignantly INTO the hotel –

MIKE Susie But she has gone. He sighs and moves across the street. ———————————————————————–The added scene in the hotel cannot have been made in the expectation of reaching a real level of sexiness; its tone is simply intimate – the tone of that standard “maritalfriendly” relationship with which moviegoers are by now so very familiar. If it was felt that an extended scene between the two was really necessary at this point, then that scene should have been developed along the lines of the gulf widening between a couple passionately in love. This, believe me, is not at all a matter of mere preference on the part of the author of the script and the director of the picture. Here I invoke more than personal opinion; it’s a simple fact that what I’m pressing on your acceptance has a very direct bearing on the story line. The separation of the newlyweds is a vital point in that story line, it is a separation which doesn’t come about through the arbitrary mechanics of the detective story, but develops as an organic progression of events implicit in the characters of the people rather than the plot. Woman’s classic failure to fully appreciate and sympathize with that sense of abstract duty so peculiar to the male – a sense bearing no relationship to the personal reality of a marriage – is here intensified by the fact that these are honeymooners, that she’s American and he a Mexican. Their separation, too, is directly the result of a sort of “border incident” in which the interests of their two native countries are in some conflict. This is a pretty good story. The underlying sex relationship was, in my opinion, stated with some degree of dramatic truth by developing it, just at this point, in terms of Susan’s irritation and Vargas’s exasperation: that form of quarreling which is sparked in the very midst of passion. The later reconciliation in the car was intended as a climax to this particular phase of the story. Without the right preparation this makes no impact as a reconciliation but is merely another scene. The leading man and the leading woman cuddle up to each other and kiss; there is neither resolution nor development – just an empty display of snuggling. Now there’s no intrinsic merit in a perfectly straightforward honeymoon relationship being interrupted by

the machinery of a detective plot. In those terms, the girl would be present in our picture simply to provide “feminine interest” in its most shapeless and ordinary form. But if you’re sure you prefer the boy-girl relationship to develop along the routine lines of uncomplicated wifely warmth and husbandry intimacy, then Susan’s later actions in the bedroom and the manner in which she flings out of the hotel is totally unmotivated. My promise to withhold direct attack from any of the other added scenes will, I hope, give me the right to hope that you, on your side, will be willing to re-examine this sequence in the light of the objections I’ve laid before you. Reducing the peculiar angles and sharp edges in this early relationship between Susan and Vargas eliminates whatever might be interesting about the couple. In these opening stages, regardless of any question of individual taste, I’m convinced that one story (mine) or the other (yours) should be told. The attempt to combine them annuls the logic of both. I can well appreciate your proprietary feelings, for this new scene of yours. For my part, I’ve looked on the rest of the picture (and on the edited version I was so near to finishing last July) with just the same jealous sentiments of ownership. Pride in your own work is also bound to be stiffened by the special circumstances in which that work was carried out. That I was denied even the right of consultation with you is a hard fact strongly hinting that, of all people, I must be the least welcome as a critic. In spite of this – and in fairness to a picture which you now describe as “exceptionally entertaining” – I must ask that you open your mind for a moment to this opinion from the man who, after all, made the picture. My effort has been to keep scrupulous care that this memo should avoid those wide and sweeping denunciations of your new material to which my own position naturally and sorely tempts me. In this one instance I’m passing on to you a reaction based – not on my convictions as to what my picture ought to be – but only what here strikes me as significantly mistaken in your picture. It’s sufficiently your own by now, for me to be able to judge it on what I take to be your terms alone, and to bring to that judgment – (after so much time away from the film in any form) – a certain freshness of eye.

Where the story follows a new line, you must make quite sure that the vestigial remnants of the old line are not permitted to remain in too obvious conflict with your added material. I ask you please to believe that what minimum criticism of that new material I am passing on to you, is made in recognition and full acceptance of the fact that the final shape and emphasis of the film is to be wholly yours. I want the picture to be as effective as possible – and now, of course, that means effective in your terms. Just on those terms, however, there are some contradictory elements which I venture to ask you to deal with; also an occasional lapse in continuity and one or two mistaken excisions. These I’ve chosen for this memo most economically – they are the changes I take to be indicated by your own new version rather than my old one – changes which are simple enough, and above all, easy enough to give me the hope they won’t be disregarded. I was pleased to see that the brief scene between Susan and Vargas on the hotel stairway has been restored. The cut away from Grandi, however, now seems like a mistake: the cut takes place in the middle of some word in the sentence “…half of you are too wet behind the ears.” I’m sure this can be smoothed easily. Checking the first draft of these notes I find that the question I wanted to put to you regarding the new scene in the car between Vargas and Susan, might just possibly, in it’s simple form, give an impression of sarcasm. The question is this: do you mean us to gather that Quinlan’s car encounters Vargas’s out of sheer coincidence? I assure you no sarcasm in intended! I really want to know if this meeting is meant to be accidental. As it goes now, Vargas stops his car apparently because Susan suddenly wants to make love, or at least out of deference to an amorous mood, or perhaps as an indication of his own eager reaction to that mood… Now this raises an incidental point: if the purpose here is to warm up the sex interest, why not finish the scene on the kiss, with the police car interrupting the embrace (as in the original version)? If we carry on with the snuggling business, up to and including Susan’s line to the effect that she figures she could sleep forever on her husband’s shoulder, – surely the sexiness is banished in favor of the snooze. This in turn brings us back to the really important question of why Vargas stopped in the

first place. Nothing in his attitude showed the slightest indication that this was a section of the road agreed upon for his rendezvous with Quinlan. To the contrary, the whole car stopping business now suggest a spur of the moment decision. I honestly don’t know if that’s what was intended; there’s certainly nothing to be said against it. It may, indeed, be more sympathetic than the former version, but what we’re then faced with is the problem of the police car driving up, so to speak, out of the blue. If no rendezvous was arranged, this seems to be a pretty out of the way corner of the wilderness for the two cars to just happen to meet. Maybe we can assume that they’d agreed, in a general way, to meet somewhere on this particular road. If this is so, why not put in some wild line from Vargas (over his back as he looks up at the arriving police car) which would make this clear? [In Welles script, Vargas arranges to meet Quinlan at the American Police station, and when he stops the car to kiss Susan, they have already arrived back in town and park in front of the bus station]. A couple of other notes on this sequence are worth recommending if only because they’re simple and easy to deal with quickly. Of these, the most important has to do with a new shot involving the police car and, (I think) Grandi’s roadster. Either the shot itself, or it’s placing, has a bewildering effect: one just doesn’t know what’s happening. Maybe eliminating the former shots which established Grandi as having followed Vargas’s car is to blame for this; I don’t know, and with only one viewing, I’m not ready with any valuable or constructive comments. The impression, however, was definitely muddled. You must have had some good reason for cutting the footage in which Grandi’s tailing operation was made clear to the audience, but after considerable thought, I’m still unable to make any sort of guess as to what those reasons could be. For the close angle of the chase, the plan was for a quite interesting pattern of newscasts to be heard on the radios of the two cars and in the two languages. When Vargas switched stations, there was to be a dreamy, oldfashioned Mexican waltz to take the place of the announcer’s excited chatter, and thus underscore our short love scene with a sentimental note, nicely combining “local color” and, in realistic terms, perfectly justified. This pattern was to be rudely broken by the aggressive siren of

Quinlan’s car, and then-after Vargas’s departure in that car-the gently picturesque lullaby would soothe Susan toward sleep as Menzies drove off with her. This music would also have been useful in relation to the waking up business at the motel, and would all be part of a most intricately worked out sequence in which sirens, dynamite explosions, and various radio voices (including the news flashes in the police car) would play their different roles. As it stands at present, the editing annihilates the possibility of this sound pattern around which, as a matter of fact, this whole series of closely related scenes was originally designed and photographed. What was meant to be a tour de force in the rather sadly neglected dimension of the sound track now cannot be anything more interesting than a succession of straight plot-scenes, all quite necessary to our story, but of no special value in themselves. The excision of those quite colorful crane shots which feature Grandi’s and Vargas’s cars is less to be lamented, but I can’t leave the sequence without registering doubts that this cut accomplishes much of anything in terms of pace. Establishing the oil derricks (rather surprising country, in which our closing scenes are played) was of some importance too. The audience, I believe, should be prepared for those derricks. This also was an element in a carefully built-up pattern – in this instance, a visual pattern. (You may be sure that I have strong opinions on the quality of all the new dialogue, the texture of the photography and the direction and the playing of the new scenes, but, as I’ve said, the purpose of this memo is not to discuss every change I think should be made in the final version, – but solely to bring up those very few matters which I take to come within the framework of the picture as it now exists, and to which I hope you’re ready to give a few moments of your open-minded attention.) I have a note which reads – (rather cryptically, since it was written in the dark projection room) – “the new cut from Menzies line – ‘brave, say -‘” is confusing.

Unfortunately, I can’t remember what that cut was. The line, of course, is spoken by Menzies to Susan in the car. (The scene was retaken, for some reason I don’t know about, in front of a process screen). This sharp clipping off of dialogue gives a jerky, unpleasant impression, and it would seem better to cut this scene in the moving car entirely, rather than chop into it in this abrupt fashion. Perhaps, there was the feeling that Susan should be shown settling herself for sleep. But her state of drowsiness has been made perfectly obvious before this, and there would be nothing bewildering about finding her, after a dissolve, already asleep. I’m at a loss to see what other point her scene with Menzies can be expected to make – at least in its present truncated form. Personally, I liked Menzies’ speaking of his boss as though Quinlan were a sort of superman, and I was also fond of the business of the newspaper clippings; but if you didn’t like it, you’ll certainly get no argument from me. This is one of those clear cases where somebody’s taste and personal judgment must be responsible for the decision and, of course, that final judgment is yours. [Ironically, Welles’ memo noted so many lapses of logic in the new re-takes (of Menzies driving Susan to the Motel) that Universal decided to simply drop all of them – even though they had gone through the considerable time and expense of re-shooting them! The studio re-takes were retained in the preview version and the ’98 re-edit]. There’s no need to repeat my arguments, – (given at some length in my first memo last summer) – against the reshuffling of scenes in the sequence following Susan’s departure with Menzies. More than ever, I’m convinced that the best order is the original order. The switching about in continuity is particularly mistaken from the point of view of simple plot clarity. The name “Farnum” is used too sparingly, and, the scene with the construction crew is so brief, that unless it’s followed immediately by the scene in the Sanchez apartment, there’s every likelihood that the whole reference to Farnum and his dynamite will just bewilder the audience. This reference, which is so vital to the plot-line, is embedded in the very middle of an extremely “busy” and elaborate scene, one in which the audience’s ability to follow everything that’s being talked about is strained to the utmost point of safety. Only direct juxtaposition of these

two scenes gives us any hope of not “losing them” just here. [This change was made in the release version, but not in the preview version. It was also made in the ’98 re-edit]. Susan’s arrival at the motel is less confusing, and plays far more effectively, if it comes right after her separation from Vargas. I note that somebody managed to locate at least one of the shots covering Menzies encounter with Grandi. This certainly clarifies the situation of Grandi’s tailing Menzies’ car. The use of odd bits of dialogue from the subsequent scene works quite well. It’s my impression, however, that this trick has been somewhat over-exploited. Less of this dialogue is needed, I think, and it’s surely important not to repeat exactly the same lines from the same take, and on the same sound “level” immediately afterwards. The slow lengthy progress of Vargas’s car (driven by Menzies) from where it was first parked to the motel really must be eliminated. This seems to go on forever and there’s no conceivable interest in watching it. I have the impression that a dissolve or cut to the very close shot of Susan sleeping with Menzies’ voice over scene “wake up, Mrs. Vargas, wake up…” should lead us directly into the first motel scene (between Susan, Menzies and Grandi.) True, the cars are parked over on the road, but at this point the geography is unknown to the audience, and there’s nothing whatever to indicate (in the very full shot which you now use for Grandi’s arrest), that the motel building are just out of scene. By using the close shot of Susan waking, perhaps we can eliminate the starting up of the car and that long, dreary move up the driveway. This is a suggestion and nothing more, since there’s obviously no way of making sure of it’s practicability without trying it. You’ll agree that this section, in it’s present form, is not merely dull and lengthy, but so boring that the whole story interest is gravely jeopardized. In the fear that the business of Grandi’s arrest might not be understandable, I think we’ve gone too far overboard in showing it, and in repeating explanations. Indeed, this whole business is now so noisily explicit that it has the unfortunate effect of wrecking the comedy in the next scene: we are no longer amused by these two, but just fed up at their shouting at each other.

[This change was made by Universal in both the release and preview versions]. The case of Grandi’s following Menzies prompts me to inquire why you’ve cut all shots of Grandi’s pursuit; his hiding when Vargas and Susan stop on the road; his ducking from the police car; and his continued chasing of Vargas’s car. If my version was felt to be wrong, there is surely enough material for another editing in which the clarity of this plot point could be further underwritten-in visual terms. This would make possible an elimination of some of that nagging and repetitive sound track on the road by the motel. [These scenes were cut by Universal for the release version, and partially restored in the preview version. The ’98 re-edit made additional changes to help clarify the scenes]. In Susan’s scene with Weaver, there is a very curious cut by which his move from above the window to the door is eliminated. This is accomplished by an extreme lengthening of Susan’s close-up, while Weaver is heard in a continuous, bewildering chatter off-scene. The close-up is by no means one of Miss Leigh’s best, but even if the camera flattered her more than it does in this shot, her reaction, which is one of drowsy reaction, could not, by its very nature, be interesting enough to support such a very extended closeup. More important than this is the fact that what has been chopped out of Weaver’s performance is strikingly good material in itself. Further, it prepares for and builds up to the extreme eccentricity of his behavior at the door. Unless we see him stuttering (as he does so magnificently) about his position as night-man unless we follow his startled, neurotic, scrabbling progress from the position where he’s first cornered to the door through which he wants to escape, his sudden wild behavior must strike us with a sort of shock, as being wholly arbitrary. This scene is balanced on a perilously delicate point: the audience simply must have time enough to – so to speak – digest Weaver’s character. If they are even slightly rushed in the process, he will seem to be merely phony. Instead of developing as a queerly likeable and diverting sort of zany, he will emerge as an exasperating ham. The simple fact is that “snapping up” or “tightening” any of Weaver’s scenes does not help the pace, it only results in a rackety, disjointed effect which is not pace at all, but

raw confusion. Here the question of rhythm is absolutely central. Each one of Weaver’s scenes was so fully rehearsed, so painstakingly built up in terms of what I can only describe as “sound-pattern” that a single snip of the scissors must bring the whole structure down in noisy ruins. [Universal cut almost half of the ‘Night Man’ sequence in the release version, which was retained in the preview version and the ’98 re-edit]. In the scene in the blind woman’s shop, I note with distress that the shot of Vargas at the telephone has been blown up in such a way as to eliminate the blind woman in the foreground. She was not there by accident. Her presence embarrasses Vargas and inhibits his phone conversation with Susan. This provides a curious note of minor tension which will be missed. Susan in the strange motel speaking with drowsy sexiness to her husband in the even more strange shop of the blind; his discomfort at the quiet, oddly attentive figure of the blind woman – these were elements in a rather carefully balanced little plan. It seems a shame to disrupt this simply because it struck someone that the woman sitting there in the foreground was rather peculiar. It was meant to be peculiar. If the dialogue between Susan and Mike was more significant, if vital plot points were being established, then, of course, the blind woman would be quite the wrong sort of distraction. As it is, she lends a special dimension to a scene which, on the face of it, advances our story not at all and must be perfectly routine. [This change was made by Universal]. The new close-up of Vargas in the Sanchez apartment is probably not something I can hope to persuade you to eliminate, but, all the same, I break my vow to avoid hopeless causes in this memo just long enough to ask a question: if Vargas fully “registers” on Grandi – if he goes so far as to state menacingly that he was anxious to meet him and to start (in a broken speech) a question about Grandi’s treatment of his wife – why doesn’t he continue? In writing this scene, I was most careful to avoid a dramatic confrontation of Grandi by Vargas, and to arrange things so that Vargas never really focuses on him. It seemed important to me that his concentration should remain

on Sanchez because once he really stopped to think about Grandi, and tied him up with Susan, there could be no moral excuse for him to avoid following up the issue and taking Grandi fiercely to task. [Universal apparently inserted a jarring close-up of Vargas into the long take in Sanchez’s apartment. Thankfully, this shot never made it into any version of the film]. For the scene between Vargas and Schwartz in the racing car, I was at some pains to make inserts of the car radio. Ordinarily, of course, inserts are not the responsibility of the director, but I regarded these as so important that I made them myself. They should come at the beginning and at the end of this scene. The effect I had in mind has never been seen or heard and, therefore, could not be judged. The scene was to open on the car radio with the announcer recapping the plot in the form of a fragment from an excited news bulletin. Vargas’s hand switches from this voice to music – the music being a very gay and extremely fast Mexican march. We then cut to the two-shot of Schwartz and Vargas, who play their scene to the accompaniment of this lively “chase music.” This is particularly important because even the second dubbing of the scene failed to eliminate a boxy mechanical quality in the sound track. The background of “chase music” from the radio would do much to fix this and would also offer an amusing, faintly ironic comment on its own. The closing shot of the scene begins with a down angle on the two in the car in which Vargas’s hand goes again to the radio. The idea here was for the music to be suddenly raised in volume. Then, when the camera cranes up, and the car pulls violently ahead, there would be an interesting reverse pattern in the sound, with the “chase music” abruptly fading as the car speeds off into the distance. [This change was made by Universal]. The mirror shot of Miss McCambridge and the blonde Grandi girl (ending with the line “…the fun is just beginning”) is so placed in the continuity as to make no sense at all. The effect is as if these two types have suddenly found their way into Susan’s room. Unless fixed, this very brief scene should certainly be cut. I take pleasure in reporting my enthusiastic approval of the new scene between Schwartz and Vargas. It’s a good

photographic match, the cut itself follows smoothly and the new words make a definite contribution to the clarity of the story. A minor point: why is the camera move off Mr. Collins and on to Vargas’s swiftly moving car now trimmed away? Was it confusing? It was a good shot and I’d thought the fact of Vargas and Schwartz’s departure was helped by it. Anyway, without the camera’s swinging to the car the angle of Adair is a bad butting match with the two shot of Quinlan and Gould. If the car can’t be restored, how about leaving out this close-up? [The moving car shot was restored by Universal]. The present arrangement of scenes in the motel – the scenes building up to the attack on Susan – adds up to a sequence having its own simple melodramatic progression, but which, in fact, is quite a meager substitute for the original plan. By jamming together all the footage in which various members of the gang enter Susan’s room, the cumulative effect is not really so very frightening; it even runs into some danger of being ridiculous. The sheer number of goons following each other through that door and around the bed is just the sort of thing which may very easily get a bad laugh. [This change was not made by Universal, but was made for the ’98 re-edit]. Doing away with the inter-cut to the motel office is particularly regrettable. This is a case where a whole sequence of effects depended on the use of music. The film for this was shot strictly within a most precise pattern involving rather special arrangements of sound and silence. The crescendo of suspense was to depend more on the sound track than the images. The decision to shuffle those images in a new, and much more obvious order could never have been made, except in ignorance of the basic scheme. In the simplest terms of the familiar mechanics of suspense, intercutting to Weaver (who, after all, was Susan’s only hope) was a device of obvious merit. His sudden snapping off of the music and the reaction to this in Susan’s room was important in a sequence which included

many queer starts and stops; sudden gasps; silences; – all this alternating with the roar of rock ‘n’ roll. This was (or would have been) twice as exciting as the present version – to put it very conservatively. The scene was conceived musically and it depended more than anything on syncopation. Syncopation has been utterly removed and we are left with a straightforward quick step. [The cut-away to Dennis Weaver was restored by Universal, with further refinements to the soundtrack made for the ’98 re-edit]. In fairness to the picture, I urge that the real scene be given a fair chance to prove itself in the form in which it was photographed and planned. The endless parade of delinquents around the bed is a real invitation to giggles from the audience, and at best, the present telescoping presents only the bare bones of an event. In the Hall of Records a close shot of Menzies looking up from the table has been put back into the scene. I had cut this because of a mistaken use of the wide-angle lens which distorts Menzies’s face so grotesquely as to bring the scene itself to dead stop. There’s really no use upsetting the audience this way. The scene played all right without this weird close-up. [This change was not made by Universal, but was made in the ’98 re-edit]. The second Hall of Records scene must not be followed by Menzies calling Marlene. This violent distortion of the continuity is a disaster. The end of this scene was carefully photographed to make the most effective use of the dissolve into the motel office where Weaver sits singing moodily to himself, and we hear off-screen, the arrival of Vargas’s car. An establishing shot of the motel would be necessary unless the action follows the clear and simple line of Vargas leaving the Hall of Records and going directly to join his wife. In effect, we must stay with Vargas because his departure from the Hall of Records accompanies the subject of Quinlan’s guilt. If we leave Vargas for another scene it’s logical to expect that when we pick him up again he’s pursuing the Quinlan affair. His turning up in the dark office won’t at first suggest Susan at all, and by the time we make out what he’s saying to the

shadowy figure of Weaver the damage from momentary bewilderment will have been done. This is all the more true if the cut away from Vargas shows us Menzies phoning Marlene. What I’m talking about here is not a really drastic befuddlement, just a mild series of short circuits in the logic of the visual progression. In themselves these short circuits are virtually unnoticeable, their total effect is vaguely numbing, there’s no real dislocation but rather an insensible loosening of tension. Menzies left in the Hall of Records, is left fixed…a tragic, almost immobile figure. To dissolve from such a tableau to Marlene, and to discover that Menzies is busy telephoning her is disturbing. Not dead wrong, but definitely off pitch. The dissolve doesn’t leave Menzies looking as though he were about to do anything. The movement is by Vargas, and Vargas is the man we feel like following. I cannot put this too strongly: either leave the brief scene with Marlene where it was meant to be, or cut it out. Another alternative is to find another place for it. In all events it must not follow the Hall of Records. [This change was made by Universal, who inserted Menzies phoning Tanya as a cutaway shot in the middle of the attack on Susan. However, it seems quite likely this was not where Welles intended the scene to go, since just two scenes earlier, Menzies has found Quinlan in a bar and directed him to Vargas’s meeting with Adair. A more likely placement for the scene, would be between the scene of Vargas leaving the Mirador Motel, (after seeing his wife’s ravaged room), and Quinlan’s clandestine meeting with Grandi at the Hotel Ritz]. The dialogue cuts in the motel office scene may shorten playing time but nothing is accomplished in terms of pace. There is, in fact, a serious loss of suspense. Weaver’s performance building up to the business with the hotel register is one of the most perfectly brilliant things of its kind I’ve ever been privileged to have in a picture. There would have to be some very big advantage to the playing of the whole sequence to justify throwing out the major part of such a scene as that. There is no such advantage. The building up about the party now makes little or no sense and Vargas’s growing apprehension (and ours) is unexploited. Here was a lovely developed atmosphere of

suspense; and the suspense really worked, too. God knows it’s called for at this point. To chop into it in the interests of plain speed is to let the pressure out of the situation, to hurt the story just where it hurts most: at the point of build-up. Here was the original plan: Menzies stands almost paralyzed with shock as Vargas moves out of the Hall of Records and we dissolve (from Menzies’ stricken face) to the forlorn figure of the “night-man” in the motel. Vargas’s car stops and he appears. Where is his wife?… Where, indeed?… Our fears fly ahead of him as he struggles to communicate with Weaver. The exchange is painful: in a spooky sort of way, even a little crazy. Slowly Vargas himself begins to realize that this man he’s talking to is crazy, or something very close to it… Out of hesitation – out of odd, anxious blank moments – a hint of some nameless enormity grows like smoke in the dark room… As the kids would put it, this is a real “gone” scene… The “nightman” is “way, way out there.” …Conscious as ever of the need for careful politeness in this foreign country, Vargas presses on with his questions… Suddenly, out of the murk, the reference to some sort of “party” drops like a heavy stone. That’s the way the scene was shot. As it is now, Vargas appears, asks for his wife, gets one fumbling reply and then, abruptly, without any feeling of chill, we’re faced with that word “Party.” The cut outside comes very quickly – there’s no time given us to let our questions about what’s happened to Susan grow or take on strange, distorted shapes. Now, before we know it, Weaver and Vargas are bustling off to the bedroom. [This change was not made in the release version, but was restored for the preview version and the ’98 re-edit]. I must assume that the missing lines by Weaver in Susan’s bedroom are due to the temporary condition of the soundtrack. It would be the greatest mistake to cut out the references to the smell of reefers. There’s no issue of censorship here, since marijuana has not actually been used. Weaver is batting about in the dark room like some sort of night bird, flinging open windows, and there is simply no sense to his behavior unless he’s trying to get fresh air. His dialogue must be retained. This,

incidentally works in counterpoint with Vargas’s search for his revolver, some of which also seems to be missing. This used to be a most effective moment and is now quite flat. There’s no need for it to remain that way. [Weaver has no dialogue referring to the smell of reefers in any version, but he does pick up and smell a stub which quite obviously is marijuana]. There seems to be a different choice of angles now used in the last scene between Vargas and Weaver. I wonder is this to give Mr. Heston the best of it? (I suggest you ask Mr. Heston about that!) Perhaps, there is a cut in dialogue which caused this. Anyway, this brief scene has lost a great deal of vitality. I’d like to congratulate whoever edited the street scene in which Vargas drives into the traffic jam, fails to hear Susan, and continues across the international boundary. The cutting here is not only superior to what it was at the stage when I left it, but actually better than the effect I’d been hoping for. In the fight scene, the footage of the crowd running past Vargas and out the door is now too extended. I’m not sure that the inter-cut of the reverse angle in the next room is indicated. There are several ways of getting at this, but it’s quite important that Schwartz get into the scene a little quicker than he does. Otherwise, there is a bad moment where Vargas is left too obviously with nothing but egg on his face. The extremely tight shot of Vargas speaking the line “…murder…” has now been trimmed to the point of being merely jerky and abrupt. I particularly regret the decision to cut away from this scene before the effect of going out of focus. I ask that this trim be reconsidered, bearing in mind that the out-of-focus device assists the violent transition to the interior of the jail, and at the same time, expresses the frenzy of Vargas’s feelings at this moment, and his virtual disintegration. The frames have to be carefully picked for this, because the lens itself had to be removed at the end of the out-of-focus effect, and at that moment, of course, the screen goes white. My idea was to dissolve very quickly during the out-of-focus action into the darkness of the jail door, finishing the dissolve as the door opens.

[This was restored in all three versions]. I appreciate the thinking that went into the extended use of close-ups of Menzies during the cell scene between Vargas and Susan, but there are definitely too many of these close-ups. Not only should one of these be cut, but the intercutting between Menzies’s face and Susan’s bed can be much more smoothly worked out. Mr. Heston reports that the cutting of the second half of his scene with Menzies (on the porch opposite Tanya’s), resulted only from the fact that the sudden silence where the recording device is intended to “playback” was not understood. I hope that this is so. The exact sentence which was to have been played back escapes me, but a few moments’ study of the preceding action will make this perfectly clear. The trick of the machine echoing their words at this point is a good one in itself; but what’s genuinely valuable in this scene is just that part of it which is now trimmed. The whole sequence is really a buildup to Menzies’ line “…everything I know I learned from him…” (or something very near that) and then his look off-scene to the house where Quinlan is. Menzies’ feeling for his boss and love for his friend is never shown so well elsewhere in the picture. This is Calleia’s decisive moment in the performance of the character… and communicates much more than Menzies ever says in words. [This change was not made in the release version, but was restored in the preview version and ’98 re-edit]. Two small notes about my scenes with Marlene: The insert of the cards being smeared across the table is not cut into the other material as effectively, or at least, as smoothly as it might be. I suggest that the insert should come just as I lean forward (with part, or all of my line overscene). Surely there are other alternatives, and maybe better solutions. Secondly, there’s a close-up of Marlene glancing up which is needed for the moment when I stumble out of the room. In the “chase”, the effect of static on the “bug” Vargas is carrying is much too loud. I take it that this is only a temporary track, however.

Again, the echo is much too extreme an effect as used now. In the final version it should be the barest whisper – just enough to catch (for a moment only) Quinlan’s attention. I urge that the shots of Marlene’s approach to the bridge be retained. There’s one flash of her passing Vargas’s car which could be used easily, and without sacrificing the retake of the car’s departure. Her arrival as a tiny figure on the bridge with Quinlan immobile in the extreme foreground is one of the best shots in the picture, and surely helps to keep clear some orientation and geography which might otherwise be somewhat bewildering. The whole “snapping up” process in this area is scarcely an improvement. We must assume that this part of the story is genuinely interesting. If it is not, then it should be much more drastically cut, and the end of the picture resolved in quite different terms. But if we are correct in believing that this aspect of the narrative is capable of sustaining interest, then, surely, it deserves to be treated with confidence, – to be developed fully and given its full range of potential effectiveness. I come now to the very end of the picture and in bringing up the following issue, I hope it will be noted that until this point, I have offered no suggestion in this entire memo which you might suppose to be calculated to improve, feature, or in any way build up my own character of Quinlan. Even here, what I’m going to urge is of problematical benefit to me as an actor. However, it does bear very directly on the effectiveness of the closing scene. As I planned it, after Quinlan was shot and Schwartz had turned on the recording device, there were to be two or three very significant lines coming through the little speaker: the accusing echo of the dead Menzies, and finally, Quinlan’s hoarsely repeated cry “…guilty, guilty, guilty…” I believe, it was in the course of putting together an earlier version of this final scene, (now abandoned) in which the picture ended with the departure of Susan and Vargas, that these important cuts between the recording device and Quinlan’s face were eliminated. However this may happened, the brief flashes were dropped, and I would like to urge that they be returned now to their intended place

in the climax of our story. It would be a sad mistake to use a very extended build-up with a “gimmick” without exploiting the very moment toward which we were moving with that “gimmick” all that time. The funny little voice of condemnation was meant to be a general comment on the story itself. Let’s not lose it, please. Incidentally, in its present form, the first quick flash of Quinlan’s face at this moment has him looking in one direction and then almost immediately in the other. The second direction is the correct one and prepares for his rise from the chair. As I remember, this was a “flop-over”. Anyway, it should certainly be fixed. There was also a intercut to Quinlan during the encounter on the bridge between Vargas and Schwartz. Not at all because I want another close-up, but because I think that the intercut really helps the pace and movement. I urge you to return it. At the very end, I had a particular arrangement of short cuts building up to Quinlan’s collapse into the water of the canal. This involved the closing of the recording device, the backing up of Quinlan, his dead body dropping into the water, and other moving shots arranged in a very fast crescendo. As I left it, this brief montage, although not exactly as I wanted it, was quite close to being right. I honestly believe it was – or would have been – one of the most striking things I’ve ever had anything to do with. I close this memo with a very earnest plea that you consent to this brief visual pattern to which I gave so many long days of work. SCENES CUT, CHANGED OR TRA NSPOSED IN By Lawrence French ———————————————————————–Following is a listing of the major changes made in the three different versions of TOUCH OF EVIL. The page and shot numbers refer to the TOUCH OF EVIL continuity script, published in 1985 by the Rutgers University Press. For the sake of clarity, the three different versions of TOUCH OF EVIL referred to, are as follows: Original release version: The 93 minute cut of the film that was released by Universal in 1958. This was the only version of the film available until 1976.

Preview Version: A longer, 108 minute version that was used by Universal for early test screenings. Unfavorable audience reaction led Universal to cut approximately 15 minutes from this version. It was this preview version that was accidentally found in the vaults at Universal in 1975. It was subsequently copied and made available in both 35 & 16mm. This is also the version Universal has most often released on home video. Re-edit version: The 1998 restoration, that re-edits, eliminates and combines shots from the two earlier versions-all in accordance to the instructions Welles gave to Universal, in a detailed, 58 page memo to the head of the studio, Edward I. Muhl. 1. SHOT 79: Susan tells Mike about her meeting with Grandi in the Hotel lobby. This scene was shot by Harry Keller and included in both the release and preview versions. It was eliminated in the re-edited version. (Page 65). 2. SHOT 93: After acid is thrown at Vargas, he returns to the strip club, and Menzies asks him if anything is wrong. This scene was included in the release version, but not in the preview version. It was restored in the re-edit. (Page 66). 3. SHOT 98: Schwartz and Adair standing outside of Tanya’s place, wondering why Quinlan is going inside. This scene was cut from the release version, but included in both the preview version and the ’98 re-edit. (Page 68). 4. SHOTS 121-153: A long sequence in front of Tanya’s, where Menzies tells Quinlan about the acid that was thrown at Vargas. Quinlan then question Vargas about Susan’s being picked-up and led to a dive on the American side of the border. This scene further establishes the hostility between Quinlan and Vargas, and indicates their very different approach to “police procedures.” This long and important sequence (shot entirely by Welles), was cut from the release version. It was restored in both the preview version and the ’98 re-edit. (Page 70-74). 5. SHOT 182-183: A brief trim of the shot where Susan and Vargas descend the stairs of their hotel.

This trim was made in the release version, but was restored in the preview version and the ’98 re-edit. (Page 78). 6. SHOT 193: After arguing in the Hotel lobby, Vargas and Susan are talking in front of the Hotel. Vargas asks her where she wants to go and Susan, changing her mind, says she wants to stay near her husband. This brief scene was neither written or directed by Welles, but one of several re-takes shot by Harry Keller. It remained in all three versions of the picture. (Page 80). 7. SHOTS 206-219: A long sequence where Vargas drives Susan to the motel on the American side of the border. On the way, they stop on the deserted roadside to kiss, but are interrupted by the arrival of Quinlan’s police car. Vargas leaves with Quinlan and Schwartz, while Menzies drives Susan (in Vargas’s car) to the American motel. Meanwhile, Grandi has been following Vargas’s car at a distance, and continues to do so. This long sequence includes footage shot entirely by Harry Keller, and accurately follows Welles scripted dialogue, with the exception of one line. However, Universal cut the entire sequence from the release version. It was retained in the preview version, but with editing that Welles objected to, since, as he noted, the shot of the different cars leaving the rendezvous point was highly confusing. The ’98 re-edit followed Welles intentions, by making some brief modifications to the editing of the departing cars, and cut the one line of Susan’s dialogue not written by Welles: “You don’t mind darling, do you, if we just sit here by this terribly historic border of yours, maybe for about a month?” (Page 82-84). 8. SHOTS 227-238: After switching cars, Menzies drives Susan to the Mirador motel, and tells her about Quinlan’s reputation, and how in a gunfight, Quinlan stopped a bullet that was meant for him. This explains both Quinlan’s “game leg” and his line at the end of the picture, where he says, “Pete, that’s the second bullet I’ve stopped for you.” The sequence continues, with Susan falling asleep, and Menzies discovering that Grandi has been tailing them. Menzies stops Grandi and questions him, before proceeding to the motel, where Susan awakes, and sees Grandi before she checks into her room. This sequence includes footage shot by both Welles and Harry Keller. The process shots in the car were directed by Keller, while most of the location shots at the motel where directed by Welles. This sequence was cut from the release

version, but retained in the preview version – where it was placed incorrectly. In the ’98 re-edit, the order of the scenes was changed to what Welles intended – so now, after the roadside rendezvous, we stay with Menzies driving Susan to the Mirador Motel, rather than cutting away to Quinlan and Vargas arriving at the construction site. (Page 86-88). 9. SHOTS 246-251: During Susan’s first encounter with the motel Night Man, Susan tells Dennis Weaver that Grandi has been arrested. The ending part of Susan’s scene with Dennis Weaver was truncated for the release version. It was restored in both the preview version and the ’98 re-edit. In the release version, the beginning of this scene (Susan arriving at the motel), follows immediately after the scene of Grandi getting in his car to tail Vargas and Susan (eliminating two complete sequences – Number 7 & 8, above). (Page 90). 10. SHOT 256: In the long interrogation scene, when Quinlan punches Sanchez off-screen, the release version deletes Quinlan’s line, “We gave it to them like this!,” as well as the sound of Quinlan punching Sanchez. This was restored in both the preview and the re-edit versions. (Page 95). 11. SHOT 274: A brief shot of a policeman throwing Vargas his car keys as he prepares to re-enter Sanchez’s apartment. This scene was cut from the release version, and restored in both the preview version and the ’98 re-edit. (Page 100). 12. SHOT 319: Susan in her motel bedroom, listening through the wall to a girl in the next room. In the release version of this scene, after Susan hears the girl in the next room say, “You know what a mainliner is?, the girl continues by saying, “It will make you feel good.” In the preview version and the ’98 re-edit, the line is changed to: “you take it in the vein.” (Page 117). 13. SHOTS 321-323: Menzies finds Quinlan drinking in a bar and orders coffee to sober him up. He then tells Quinlan about a meeting that Vargas has called with District Attorney Adair. The beginning of this scene was cut from the release version, and restored in both the preview version and the ’98 re-edit. (Page 117).

14. SHOT 335: After Vargas is told to apologize to Quinlan by Adair, Vargas asks Schwartz where he can find the details on Quinlan’s old cases. This brief scene was shot by Harry Keller, and is one of the few added scenes that Welles approved of. It appears in all three versions of the film. (Page 124). 15. SHOT 340: The first scene in the Hall of Records, where Vargas tells Schwartz he can manage to do the research into Quinlan’s old cases by himself – thus saving Schwartz from a potential conflict with his boss. This scene was cut from the release version, and restored in both the preview version and the ’98 re-edit. (Page 125). 16. SHOTS 348-362: Susan is terrorized in her motel room, with shots showing several gang members entering her room. Welles objected to the jamming together of all the footage of the gang members entering Susan’s room. This was not changed by Universal, but was altered in the ’98 re-edit, so we see Susan’s reaction not to the actual gang members, but the door to her room opening. 17. SHOT 395: The Night Man at the motel is singing to himself, when Vargas arrives and asks to be shown to Susan’s room. The Night Man tells Vargas that no one is staying at the motel. Vargas then asks to see the register. This scene was cut from the release version, and restored in both the preview version and the ’98 re-edit. (Page 130). 18. SHOT 533-539: A sequence showing Vargas outside of Tanya’s place, trying to find out what Quinlan is doing. Inside, Quinlan, who has been drinking heavily, gets up, after catching a glimpse of Vargas through the window. This scene was cut from the release version, and restored in both the preview version and the ’98 re-edit. (Page 147). 19. SHOTS 540-541: Vargas and Menzies discuss how to get Quinlan to come out of Tanya’s place, and Menzies reveals his deep conflict over having to entrap his friend by clandestinely taping him. Only a brief section of this important scene was left in the release version. It was restored in both the preview version and the ’98 re-edit. (Page 148).

20. SHOT 561: A brief shot of Tanya sitting at her poker table, doing the books, after Quinlan sees Menzies at the door. In the release and preview versions, an incorrect cutaway shot of Tanya was used. She does not look up as Quinlan leaves the room. The ’98 re-edit corrected this, by adding a second cutaway shot to Tanya, so she now looks up after Quinlan leaves the room. (Page 152). 21. SHOTS 722-725: A quick series of shots: Schwartz snapping the tape recorder shut, then climbing from under the bridge, to join Tanya above him, who is standing at the edge of the bridge. These shots were cut from the release version, and restored in the preview version. In the ’98 re-edit, these shots, as well as two shots of Tanya, were edited in a slightly different fashion. The shots of Tanya were trimmed to eliminate a man who passes by her as she approaches the edge of the bridge. (Page 168). ORSON WELLES LETTER TO THE NEW STATESMAN – LONDON REGARDING TOUCH OF EVIL May 24, 1958 Sir: Without being quite so foolish as to set my name to that odious thing, a ‘reply to the critic’, perhaps I may add a few oddments of information to Mr. Whitebait’s brief reference to my picture TOUCH OF EVIL (what a silly title, by the way; it’s the first time I’ve heard it). Most serious film reviewers appear to be quite without knowledge of the hard facts involved in manufacturing and, especially, merchandising a motion picture. Such innocence, I’m sure, is very proper to their position; it is, therefore, not your critic I venture to set straight, but my own record. As author-director I was not and normally would not be-consulted on the matter of the ‘release’ of my film without a press showing. That this is an ‘odd subterfuge’, I agree; but there can be no speculation as to the responsibility for such a decision. As to the reason, one can only assume that the distributor was so terrified of what the critics might write about it that a rash attempt was made to evade them altogether and smuggle TOUCH OF EVIL directly to the public. This is understandable in the light of the wholesale re-editing of

the film by the executive producer, a process of re-hashing in which I was forbidden to participate. Confusion was further confounded by several added scenes which I did not write and was not invited to direct. No wonder Mr. Whitebait speaks of muddle. He is kind enough to say that ‘Like Graham Greene’ I have ‘two levels’. To his charge that I have ‘let the higher slip’ I plead not guilty. When Mr. Greene finishes one of his ‘entertainment’s’ he is immediately free to set his hand to more challenging enterprises. His typewriter is always available; my camera is not. A typewriter needs only paper; a camera uses film, requires subsidiary equipment by the truck-load and several hundreds of technicians. That is always the central fact about the film-maker as opposed to any other artist: he can never afford to own his own tools. The minimum kit is incredibly expensive; and one’s opportunities to work with it are rarer less numerous than might be supposed. In my case, I’ve. been given the use of my tools exactly eight times in 20 years. Just once my own editing of the film has been the version put into release; and (excepting the Shakespearean experiments) I have only twice been given any voice at all as to the ‘level’ of my, subject matter. In my trunks stuffed with unproduced films scripts, there are no thrillers. When I make this sort of picture — for which I can pretend to no special interest or aptitude — it is not ‘for the money’ (I support myself as an actor), but because of a greedy need to exercise, in some way, the function of my choice: the function of director. Quite baldly, this is my only choice. I have to take whatever comes along from time to time, or accept, the alternative, which is not working. Mr. Whitebait revives my own distress at the shapeless poverty of Macbeth’s castle. The paper mache’ stagy effect in my film was dictated by a ‘B-Minus’ budget with a ‘quickie’ shooting schedule of 20 days.. Returning to the current picture, since he comments on the richness of the urban scenery of the Mexican border’ perhaps Mr. Whitebait will be amused to learn that all shooting was in Hollywood. There was no attempt to approximate reality; the film’s entire ‘world’ being the director’s invention. Finally, while the style of TOUCH OF EVIL may be somewhat overly baroque, there are positively no camera tricks. Nowadays the eye is tamed, I think, by the new wide screens. These ‘systems’ with their rigid technical limitations are in such monopoly that any vigorous use of the old black -andwhite, normal aperture camera runs the risk of seeming tricky by comparison. The old camera permits use of a range

of visual conventions as removed from ‘realism’ as grand opera. This is a language not a bag of tricks. If it is now a dead language, as a candid partisan of the old eloquence, I must face the likelihood that I shall not again be able to put it to the service of any theme of my own choosing. ORSON WELLES ROME

4 Pendekatan DACUM Dan Analisis Tugas
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4 Pendekatan DACUM dan Analisis Tugas Mari kita kaji pendekatan DACUM dan analisis tugas yang dikemukakan oleh Finch & Crunkilton (1999) dalam mengukuhkan kandungan kurikulum. Seterusnya, bincangkan potensi pendekatan dacum dan analisis tugas dalam mengukuhkan kandungan kurikulum Kemahiran Hidup Sekolah Rendah di tempat anda bertugas. Pendekatan DACUM DACUM (Developing A Curriculum) merupakan helaian profil kemahiran yang menyediakan rancangan kurikulum dan instrumen penilaian bagi program latihan kemahiran. Pendekatan ini pada awalnya dikembangkan oleh RBT 3103 KAJIAN KURIKULUM KEMAHIRAN HIDUP SEKOLAH RENDAH para ahli kurikulum di Kanada. Aplikasi pendekatan DACUM boleh menentukan kandungan kurikulum dan menjadi panduan bagi proses menentukan kandungan kurikulum secara sistematik. Hasil dari pendekatan DACUM adalah suatu Jadual yang menghuraikan secara ringkas tugas- tugas pekerjaan (outline job duties), kemampuan yang diperlukan, cara melakukan kerja, alat yang diperlukan, peralatan, persediaan, bahan dan trenda masa depan berkaitan pekerjaan tertentu yand terdapat di industri. Jadual analisis dikembangkan melalui suatu proses bersama- sama pakar khusus di dalam sesuatu pekerjaan, instruktur dan fasilitator yang akan memandu menyusun jadual tersebut. JadJadual ini akan menjelaskan suatu kurikulum bagi suatu bidang latihan.

RBT 3103

KAJIAN KURIKULUM KEMAHIRAN HIDUP SEKOLAH RENDAH Rajah 2: Carta Perkembangan Proses DACUM Rajah2: Carta Perkembangan Proses DACUM Dalam DACUM perlu ada elemen yang berikut:

bidang pekerjaan mereka daripada orang lain.

dilaksanakan oleh pekerja dengan jayanya.

yang mesti ada pada pekerja untuk melaksanakan tugasan tersebut dengan betul. Untuk keterangan lanjut, sila rujuk Finch & Crunkilton (1999) muka surat 140 hingga 146. Pendekatan Analisis Tugas Analisis tugas merupakan proses di mana tugas-tugas yang dilakukan oleh pekerja bagi sesuatu pekerjaan tertentu dikenalpasti dan disahkan. RBT 3103 KAJIAN KURIKULUM KEMAHIRAN HIDUP SEKOLAH RENDAH Dalam pendekatan ini, isi kandungan kurikulum diambil dari tugas-tugas dalam pekerjaan tertentu yang diambil secara langsung dari deskripsi pekerjaan atau deskripsi tugas yang sudah mantap. Aktiviti bagi suatu pekerjaan itu terdiri dari daripada beberapa duti (duty) dan tugas (task) yang perlu dilakukan oleh pekerja. Duti merupakan segmen yang luas bagi kerjakerja yang perlu dilakukan oleh individu bagi suatu jenis pekerjaan. Manakala tugas (task) pula merupakan unit-unit aktiviti bagi setiap duti. Dalam melakukan analisis tugas, langkah-langkah yang perlu dipertimbangkan adalah seperti berikut:

ri pekerjaan atau jabatan;

laksanakan tinjauan atau penelitian di lapangan;

Hasil tinjauan bagi analisis tugas, kemudiannya disusun dan diolah sehingga menjadi bahan acuan dalam penentuan isi kurikulum. Untuk keterangan lanjut, sila rujuk Finch & Crunkilton (1999) muka surat 146 hingga 153. Aktiviti 3 Bentuk kumpulan kecil dan bincangkan soalan-soalan di b

DEFINITION DACUM (day-kum)   

An abbreviation for Developing A Curriculum A job occupational analysis performed by expert workers in the occupation An occupational skill profile which can be used for instructional program planning, curriculum development, training materials development, organizational restructuring, employee recruitment, training needs assessment, meeting ISO 9000 standards, career counseling, job descriptions, competency test development, and other purposes.

PHILOSOPHY

The DACUM philosophy states that:   

Expert workers can describe and define their jobs more accurately than anyone else. An effective way to define a job is to precisely describe the tasks that expert workers perform. All tasks, in order to be performed correctly, require certain knowledge, skills, tools, and worker behaviors.

The DACUM Process The DACUM process for occupational analysis involves local men and women with reputations for being the “top performers” at their jobs, working on a short-term committee assignment with a qualified DACUM facilitator. Workers are recruited directly from business and industry. These workers become the Panel of Experts who collectively and cooperatively describe the occupation in the language of the occupation. Its use with many companies, community colleges, and government agencies has also shown the process to be very effective, quickly accomplished, and low cost. The Panel works under the guidance of a trained facilitator for two days to develop the DACUM Research Chart. The chart contains a list of general areas of competence called DUTIES and the TASKS that define that duty. Brainstorming techniques are used to obtain the collective expertise and consensus of the Panel. As the Panel determines each task, it is written on a card. The cards are attached to the wall in front of the Panel. The completed chart is a graphic profile of the duties and tasks performed by successful workers in the occupation. The Panel also identifies the general knowledge and skills required of successful workers, the tools, equipment, supplies, and materials used, the important worker behaviors essential for success, and the future trends and concerns likely to cause job changes. The process produces superior results for all levels – skilled, technical, supervisory, managerial, companies, community colleges, and professional organizations. DACUM has multiple usesand subordinate uses such as Management Decision-Making, Human Resources/Organizational Development, Career Planning/Advision, Learner Assessment, certification and licensure. The process can be used for job analysis, occupational analysis, process analysis, functional analysis, and conceptual analysis.

Soal Matematika Balok
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JAWABLAH PERTANYAAN-PERTANYAAN BERIKUT INI DENGAN BENAR! 1.

Hitunglah volume bangun di atas! 2. Pak Bagas mempunyai aquarium berbentuk kubus dengan panjang sisinya 120 cm. Jika Pak Bagas hanya ingin mengisi air separuhnya saja. Berapakah volume air yang harus dimasukkannya? 3. Doni dan Rina memiliki kotak pensil berbentuk kubus. Dodi memiliki kotak pensil engan panjang sisi 16 cm, sedangkan punya Rina panjang sisinya adalah 17 cm. Hitunglah selisih volume kotak pensil antara Doni dan Rina. 4. Dina mempunyai kotak mainan yang berukuran 50 cm x 30 cm x 24 cm. Kotak itu akan diisi kubus-kubus kecil yang berukuran 2 cm x 2 cm x 2 cm sampai penuh. Berapa banyaknya kubus kecil yang dapat dimuat kotak mainan tersebut? 5. Di sebuah wahana wisata terdapat 4 buah kolam renang dengan ukuran yang sama dengan bentuk berupa balok. Panjang kolam tersebut adalah 8 m, lebar 6 m dan tinggi 1,5 m. Dua kolam diisi air hingga penuh dan dua kolam yang lainnya diisi setengahnya saja. Berapakah volume air yang dibutuhkan untuk mengisinya?

JAWABLAH PERTANYAAN-PERTANYAAN BERIKUT INI DENGAN BENAR! 1.

1. Volume bangun gabungan : Diketahui : s kubus = 10 cm p balok = 14 cm l balok = 10 cm t balok = 10 cm + 7 cm = 17 cm – Volume kubus V=sxsxs V = 10 cm x 10 cm x 10 cm V = 1.000 cm³ – Volume balok V=pxlxt V = 14 cm x 10 cm x 17 cm V = 2.380 cm³ Volume semuanya = luas kubus + luas balok Volume semuanya = 1.000 cm³ + 2.380 cm³ = 3.380 cm³ 2. Diketahui : Bentuk aquarium = kubus Panjang sisi = 120 cm Isi aquarium = 1/2 Ditanya = volume air ? Volume air =1/2 x ( s x s x s ) V = 1/2 x ( 120 cm x 120 cm x 120 cm ) V = 1/2 x 1.728.000 cm³ V = 864.000 cm³ atau V = 864 dm³ = 864 liter 3. Diketahui : Dua kotak pensil berbentuk kubus Panjang sisi kotak pensil milik Doni = 16 cm Panjang sisi kotak pensil milik Rina = 17 cm Ditanya = Selisih volume kotak pensil Doni dan Rina ? Jawab : Volume kotak pensil Doni = s x s x s V = 16 cm x 16 cm x 16 cm V = 4.096 cm³ Volume kotak pensil Rina = s x s x s V = 17 cm x 17 cm x 17 cm V = 4.913 cm³ Jadi selisih volume kotak pensil mereka adalah = 4.913 cm³ – 4.096 cm³ = 817 cm³ 4. Volume kotak mainan = p x l x t V = 50 cm x 30 cm x 24 cm V = 36.000 cm³ Volume kubus-kubus kecil = s x s x s V = 2 cm x 2 cm x 2 cm V = 8 cm³ Jumlah kubus yang bisa dimasukkan = Volume kotak mainan : volume kubus = 36.000 cm³ : 8 cm³ = 4.500 kubus kecil

5. Diketahui : Panjang kolam = 8 m Lebar kolam = 6 m Tinggi kolam = 1,5 m Jumlah kolam = 4 ( dua kolam terisi penuh dan dua kolam terisi setengahnya ) – Volume dua kolam yang terisi penuh V=2x(pxlxt) V = 2 x ( 8 m x 6 m x 1,5 m ) V = 2 x 72 m³ V = 144 m³ – Volume dua kolam yang terisi setengahnya V = 2 x 1/2 x ( p x l x t ) V = 2 x 1/2 x ( 8 m x 6 m x 1,5 m ) V = 2 x 1/2 x 72 m³ V = 1 x 72 m³ V = 72 m³ Jadi volume air yang dibutuhkan adalah = 144 m³ + 72 m³ = 216 m³

Polangui Community College: Ii - Learning Objectives

Polangui Community College: Ii – Learning Objectives
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Republic of the Philippines

POLANGUI COMMUNITY COLLEGE Alnay, Albay

AGRI-FISHERY ARTS (MC TEC O4)

I. Introduction This module intended for Bachelor of Science in Education Major in TLE taking the subject of Agri-Fishery Arts 1. It includes the definition of the fishery, areas of fishery technology, and the role of the fishery to agriculture. This module will be focused on the concept, role, and other sciences related to fisheries. It also introduces you to the exploratory aspects of Fishery Arts. It explains the different areas covered by Fishery I; namely, Fish Morphology, Fish Culture, Fish Capture and Fish Preservation. Fish, as the major product will be discussed first in this module. You will be given information on the morphology of fishes; fishery as a business; and the three branches of fishery including technical terms encountered in the study of fishery for further understanding of the topic. You will also be given insights into what you could learn in this module. In this process, you would be able to decide on which area of fishery arts you would specialize in so you can participate in any fishery programs of the government and promote economic progress of the community and the country II.LEARNING OBJECTIVES: After reading this module, students must be able to: 1. Define what fishery and it’s important to agriculture and economic growth. 2. Identify the areas of specialization in fishery technology. 3. Recognize the role of the fishery sector in the increasing population in the Philippines. 4. Differentiate the three (3) branches of fishery. III. CONTENTS Fish is a cold-blooded vertebrate living in water, breathing by means of gills; whose body may or may not be covered with scales. In general, it includes all the fin fishes and other aquatic animals such as crustaceans, ( crabs, prawns, shrimps, lobsters) and mollusk ( clams, mussels, oysters, snails and shellfishes ). At the same time, the fishery is defined as the science of producing fish and other aquatic resources to provide human food. However, other aims are possible ( such as sports and recreational fishing), or obtaining ornamental fish or fish products such as fish oil. It also defined as the science of producing fish and other aquatic resources

to provide human food. However, other aims are possible ( such as sports and recreational fishing), or obtaining ornamental fish or fish products such as fish oil. The fishery is the business of catching, handling, taking, marketing, and preserving of fish and other fishery products. Fish is a business, for it is a source of income, food, and livelihood if it can be cultured for commercial purposes and marketed properly. Based on the fossils recovered five million years ago, there was no distinguishing feature of a fish. The primitive fish belongs to ostracoderm, which has a mouth just a small opening, and the placoderms to which our present-day bony fish belong.

MC TEC 04 – AGRI_FISHERY ARTS1 BTLED email add : [email protected] ; messenger: jho otaber Page 1 of 7

1.0 TYPES OF FISHERY Fishery technology is divided into three areas of specialization, namely marine fisheries technology, inland fisheries technology, and fish processing technology. Marine fisheries technology may be defined as the method of exploring the ocean to catch fish scientifically using modern fishing gears. It includes gear construction and operation, navigation, and seamanship. Marine fish, crustaceans, and mollusks can be caught in the ocean. Examples of marine fish are nemipterid, mackerel, sardine, tuna, shark, snapper, grouper, anchovy, whiting, mojarra, ray, slipmouth, crevalle, cavalla, hairtail, moonfish, barracuda, mullet, and many others. Crab, s Shrimps, prawns, and lobsters are examples of crustaceans. Examples of mollusks are seashells, squid, and octopus. Volute, olive, cowrie, helmet, oyster, mussels, cone, clam, and other shellfishes are examples of seashells. Inland fisheries technology may be defined as the approach or technique to maintain and increase the productivity of inland bodies of water for sustainability yield. The increase may be done by cultivating aquatic fauna and flora in controlled or semicontrolled environments. Examples of the former are the cultivation of fish, crab, shrimp, prawn, and many others in the fish pond, pen, cage, aquarium, and tank. Fish cultivation in a semi-controlled environment in open marine or brackish water (e.g., mussels culture, oyster culture, mother-of-pearl cultivation, window-pane shell (kapis) cultivation and seaweed farming.) Fish processing technology may be defined as a method of lengthening the shelflife of fish and fishery products by applying the principles of chemistry, engineering, and other branches of science to retard the growth of microorganisms, improve the quality attributes of the products, and retain their nutritive values for some time. Processing can be using curing, icing, refrigerating, freezing, canning, and others. Examples of cured products are kench salted fish, dried fish, smoked fish, and pickled fish. In Filipino, these are respectively termed binuro, daing, tilapia, and kilawin. 2.0 IMPORTANCE OF FISHERIES 1. Provide food- fishing is an important Philippine industry. It ranks next to farming and livestock raising in providing the food requirements of the population. Fish comes next to rice as the staple food of the Filipinos. 2. Source of income/employment for fisherman- many job both full time and part time depend upon fishing, apart from fishing itself there is also work in related processing industries, such as canning, freezing for human use. Many of the smaller fish and other organisms, are processed in factories to make pet food, animal feed and fertilizers. There are still industries related like boat building, making nets and fishing tackle and ice production. 3. Contributes to GDP/GNP, therefore to national income 4. Export e.g., shrimps to Japan so as source of earning foreign exchange, improves balance of trade 5. Extra income for agricultural farmers who own fish farms. 6. Reduces rural to urban migration as most of the inland fishing farms are in villages. 7. Development of remote areas e.g. coastal areas by providing roads and electricity.

3.0 Other science related to fisheries MC TEC 04 – AGRI_FISHERY ARTS1 BTLED email add : [email protected] ; messenger: jho otaber Page 2 of 7

1. 2. 3. 4. 5. 6. 7. 8.

Biology –the science which deals with the study of living organisms Ichthyology –the science which deals with the study of fish Planktonology – study of plankton Concholgy – study of shell Oceanography – study of ocean Phycology – study of algae Malacology –study of mollusks Chemistry – the science that treats of the structure, chemical composition and elements of substances and reactions 9. Physics –the science that treats of motion, matter, and energy and their characteristics 4.0 Careers prospects and job opportunity in fishery 1. Fisheries biologist 2. Wildlife biologist 3. Marine biologist 4. Habitat restoration biologist 5. Endangered species biologist 6. Wildlife fish manager 7. Hatchery technician 8. Fishery area manager 9. International/exotic fishery specialis 10. Fishery law enforcement officer 11. Zoo/aquarium animal caretaker 12. Watershed council coordinator 13. Environmental educator 14. Interpreter 15. Extension agent 16. Park range 5.0Branches of Fishery: 1. Fish Culture – the human effort of raising the maximum productivity of fish and other fishery aquatic products and maintaining the supply of these products to satisfy human needs. o the rearing of fish under controlled or semi-controlled condition. Method of Fish Propagation 

Natural Method- the fish breeds and spawns in its natural cycle. o Artificial Method- The fish reproduction is made ahead of organism’s natural reproductive cycle or during nonspawning season.

2. Fish Capture – branch of fishery science that deals with the scientific method of catching fish as well and the type of fishing gear used. 3. Fish Preservation – branch of fishery science that deals with the scientific MC TEC 04 – AGRI_FISHERY ARTS1 BTLED email add : [email protected] ; messenger: jho otaber Page 3 of 7

method of preserving fish and other fishery aquatic products to prevent spoilage. Learning Activity 1.1 Research on the evolution of fish

1. Why is there a need to familiarize yourselves with the morphology of 2. 3. 4. 5.

fishes? How can you differentiate the various phases of fish culture? Explain why there is a need for you to be acquainted with the different terminologies to be used in fish culture. How are the types of fish culture classified and why? How are the different compartments divided based on specifications?

Understanding Let us reflect and understand: Write your opinion and reflection after discussing the first part of the module. Would it be enough for you to decide whether or not you will be a part of the fish industry to augment family income? Ex. As a student of BTLED and given some knowledge and skills in the culture, harvest and preservation of fish and other fish products I have decided to apply this knowledge to improve myself in the fish industry.

After you completed the task, write your output in a bond paper (A4, Font style Arial, Font size 12) and submit via [email protected] or messenger jho otaber. You have one (1) week to work on this module. Please submit your exercise on August 17 , 2020. Upload them to the google classroom. For those who will not have access to internet on the designated date of submission, please drop them at the place designated by place.

TERMINOLOGIES COMMONMLY USED IN FISHERY Anadromous. fish born in freshwater, got to marines’ water to grow and develop, then return to freshwater to spawn or lay eggs. Autolysis . Softening of muscle tissue of fish due to continuous digestion of enzymes. Brackishwater . midway between freshwater and marine water. Crustaceans. one of the classes of arthropod having crust like shells and generally aquatic; include lobsters, crabs, shrimps and prawns. Estuarine. a wide mouth of a river where current meets the sea and is influenced by the tides; an inlet or arm of the sea. MC TEC 04 – AGRI_FISHERY ARTS1 BTLED email add : [email protected] ; messenger: jho otaber Page 4 of 7

Fish .a cold-blooded animal, typically with backbone, gills, and fins and primarily dependent on water as a medium to live. Fishery. can be defined as human harvest of wild marine resources for food and industry. It is not just fish, also crustaceans, mollusks, marine mammals, turtles and algae. Fish Propagation. the increasing of fish size through natural or artificial methods of reproduction. Fishery conservation. the proper and scientific control and utilization of fishery resources to ensure optimum yields and continuous supply of fish and fishery products. Fishery Technology. A course which is divided into three areas of specialization, namely marine fisheries, inland fisheries and fish processing technology. Ichthyology – the science that deals with the study of fishes Ichthyologists – scientists or persons who study fishes Assignment : Collect samples of fish and identify the external and internal parts. Provide the documentation of the activity you can use cam Note: After you completed the task, write your output in a bond paper (A4, Font style Arial, Font size 12) and submit via [email protected] or messenger jho otaber. You have one (1) week to work on this module. Please submit your exercise on August 17 , 2020. Upload them to the google classroom. For those who will not have access to internet on the designated date of submission, please drop them at the place designated by place.

References: Books 1. Calmorin et al, Introduction to Fishery Technology

2. Villanueva et al,.Fishery Arts Handbook

1. BFAR Handbook 2. Classification of Fishing Gears Handbook BFAR 3. Fish Processing Handbook for FilipinosOthers 1. http://www.google.com.ph/imgres? 2. https://www.google.com.ph/search?q=carpa 3. http://www.google.com.ph/imgres? MC TEC 04 – AGRI_FISHERY ARTS1 BTLED email add : [email protected] ; messenger: jho otaber Page 5 of 7

Prepared by : JOSEPHINE R. REBATO Cp No. 09484137544

MC TEC 04 – AGRI_FISHERY ARTS1 BTLED email add : [email protected] ; messenger: jho otaber Page 6 of 7

Polangui Community College

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