latex: more than just academic papers and theses
DESCRIPTION
LaTeX is a document preparation system capable of producing professional quality typesetting output. It is especially suited for documents with complex structures and mathematical material, and is the preferred format of many academic publishers. But modern LaTeX packages allow for the creation of material beyond academic papers and theses, and for various disciplines: presentation slides, leaflets, oversized posters, graph plots, fillable PDF forms, electronic circuit diagrams, chemical structures and reactions, DNA sequences, linguistic syntax trees, even a Gantt chart or two for the project managers! Lian Tze is the author of the usmthesis, mmuthesis and umalayathesis LaTeX packages (http://liantze.penguinattack.org/latextypesetting.html). She is a frequent contributor to the Malaysian LaTeX User Group (http://latex-my.blogspot.com).TRANSCRIPT
Introduction Document Types Special Material Wrapping Up
LATEX: More Than Just Academic Papers and Theses
Lim Lian Tze
http://liantze.penguinattack.org/
cbna
Malaysian Open Source Conference 2011
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Introduction Document Types Special Material Wrapping Up
Contents
1 What are TEX, LATEX and Friends?
2 Document Types
3 Special Material
4 Wrapping Up
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Introduction Document Types Special Material Wrapping Up
Contents
1 What are TEX, LATEX and Friends?
2 Document Types
3 Special Material
4 Wrapping Up
Lim Lian Tze | mosc 2011 3 / 48
Introduction Document Types Special Material Wrapping Up
What are TEX and LATEX, and Friends?
TEX ASCII TeX, /tEx/, /tEk/
A computer typesetting system created by Donald Knuthfor ‘the creation of beautiful books’
LATEX ASCII LaTeX, /"leItEx/, /"leItEk/, /"lA:tEx/, /"lA:tEk/
A document preparation system by Leslie Lamport
Binaries 𝜀-TEX: additional primitives to TEXpdfTEX: additional PDF-related primitivesX ETEX: native UTF-8 input; can access system fontsLuaTEX: includes the Lua scripting engine
Friends BIBTEX, MakeIndex, METAFONT,METAPOST, . . .http://www.ctan.org/what_is_tex.html
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Introduction Document Types Special Material Wrapping Up
Why?From http://www.ctan.org/what_is_tex.html
Output QualityIt has the best output.
It knows typesetting.
Superior EngineeringIt’s fast.
It’s stable.
It’s not rigid (extensible).
Plain text input.
Many output types.
FreedomIt’s free.
It runs anywhere.
PopularityIt’s the standard (inacademia and science).
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Introduction Document Types Special Material Wrapping Up
Where Would I Want to Use LATEX?
Documents with complex structures
Lots of mathematics (or other speciVc needs)
When publishers require them
Batch processing
Back-end of other applications
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Introduction Document Types Special Material Wrapping Up
How Do I Use It?
1 Write a plain text LATEX Vle (.tex)
2 Run it through pdflatex or xelatex → PDF output(or latex + dvips + ps2pdf for DVI + PS + PDF)
3 Run bibtex and/or makeindex to process bibliographies, indices
4 Re-run pdflatex to resolve references and pointers
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Introduction Document Types Special Material Wrapping Up
Example .tex File
\documentclass[a4paper,11pt]{article}\author{Lim Lian Tze}\title{An Introductory Paper}\date{\today}\usepackage[english]{babel}
\usepackage[ngerman]{babel}\usepackage[bahasam]{babel}
\begin{document}\maketitle\tableofcontents
\begin{abstract}This paper introduces\ldots\end{abstract}
\section{Introduction}We consider\ldots
\section{State of the Art}We look at\ldots
\subsection{Document Formats}There are many\ldots\end{document}
An Introductory Paper
Lim Lian Tze
June 7, 2011
Contents
1 Introduction 1
2 State of the Art 12.1 Document Formats . . . . . . . . . . . . . . . . . . . . . . . . 1
Abstract
This paper introduces. . .
1 Introduction
We consider. . .
2 State of the Art
We look at. . .
2.1 Document Formats
There are many. . .
1
An Introductory Paper
Lim Lian Tze
7. Juni 2011
Inhaltsverzeichnis
1 Introduction 1
2 State of the Art 12.1 Document Formats . . . . . . . . . . . . . . . . . . . . . . . . 1
Zusammenfassung
This paper introduces. . .
1 Introduction
We consider. . .
2 State of the Art
We look at. . .
2.1 Document Formats
There are many. . .
1
An Introductory Paper
Lim Lian Tze
7 Jun 2011
Kandungan
1 Introduction 1
2 State of the Art 12.1 Document Formats . . . . . . . . . . . . . . . . . . . . . . . . 1
Abstrak
This paper introduces. . .
1 Introduction
We consider. . .
2 State of the Art
We look at. . .
2.1 Document Formats
There are many. . .
1
pdflatex
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Introduction Document Types Special Material Wrapping Up
Where Do I Get It?
Windows MiKTEX, TEXLive
Un*x, GNU/Linux TEXLive
Mac OS X MacTEX (based on TEXLive)
Installation Use your OS’ package manager(or download manually)
Editors vi, emacs, Texmaker, TeXworks, . . .
LATEX Packages Use MiKTEX or TEXLive’s package manager
Documentation (TEXLive) $ texdoc <package name>
(MiKTEX) $ mthelp <package name>
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Introduction Document Types Special Material Wrapping Up
Easy to Learn, Hard to Master
Customising may not be straightforward (vs word processors)Intentionally so: Style guidelines should be followed strictly
Publisher/organisation provides document class or style VlesUse these to take care of formatting and styling, focus on the content
Fair enough.But where do I learn all the stuU the TEXnicians and TEXperts do?
(There is a learning curve)
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Getting Help
Many free tutorials and e-books on the Web (beware of obsolete ones!)Getting to Grips with LATEX. Andy Roberts.http://www.andy-roberts.net/misc/latex/
LATEX: Beautiful Typesetting. Lim Lian Tze.http://liantze.penguinattack.org/latextypesetting.html
LATEX and Friends. M.R.C. van Dongen.http://csweb.ucc.ie/~dongen/LaTeX-and-Friends.pdf
The LATEX WikiBook. http://en.wikibooks.org/wiki/LaTeX
Questions?TEX FAQ. http://www.tex.ac.uk/cgi-bin/texfaq2html
TEX.SX. http://tex.stackexchange.com/
comp.text.tex usenet groupMalaysian LATEX User Group. http://latex-my.blogspot.com/
Arrange for training
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Introduction Document Types Special Material Wrapping Up
So, What Can LATEX Do?
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Introduction Document Types Special Material Wrapping Up
Contents
1 What are TEX, LATEX and Friends?
2 Document Types
3 Special Material
4 Wrapping Up
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Introduction Document Types Special Material Wrapping Up
Basic Types
Books
\documentclass{book}
\author{...}
\title{...}
\begin{document}
\maketitle
\chapter{...}
\section{...}
...
\subsection{...}
\end{document}
A Wonderful Read
A. Dummy
3rd June 2011
Chapter 1
Heading on level 0 (chapter)
Hello, here is some text without a meaning. This text should show, how aprinted text will look like at this place. If you read this text, you will get noinformation. Really? Is there no information? Is there a difference betweenthis text and some nonsense like »Huardest gefburn«. Kjift – Never mind!A blind text like this gives you information about the selected font, how theletters are written and the impression of the look. This text should containall letters of the alphabet and it should be written in of the original language.There is no need for a special contents, but the length of words should matchto the language.
1.1 Heading on level 1 (section)
Hello, here is some text without a meaning. This text should show, how aprinted text will look like at this place. If you read this text, you will get noinformation. Really? Is there no information? Is there a difference betweenthis text and some nonsense like »Huardest gefburn«. Kjift – Never mind!A blind text like this gives you information about the selected font, how theletters are written and the impression of the look. This text should containall letters of the alphabet and it should be written in of the original language.There is no need for a special contents, but the length of words should matchto the language.
1.1.1 Heading on level 2 (subsection)
Hello, here is some text without a meaning. This text should show, how aprinted text will look like at this place. If you read this text, you will get noinformation. Really? Is there no information? Is there a difference between
3
4 CHAPTER 1. HEADING ON LEVEL 0 (CHAPTER)
this text and some nonsense like »Huardest gefburn«. Kjift – Never mind!A blind text like this gives you information about the selected font, how theletters are written and the impression of the look. This text should containall letters of the alphabet and it should be written in of the original language.There is no need for a special contents, but the length of words should matchto the language.
Heading on level 3 (subsubsection)
Hello, here is some text without a meaning. This text should show, how aprinted text will look like at this place. If you read this text, you will get noinformation. Really? Is there no information? Is there a difference betweenthis text and some nonsense like »Huardest gefburn«. Kjift – Never mind!A blind text like this gives you information about the selected font, how theletters are written and the impression of the look. This text should containall letters of the alphabet and it should be written in of the original language.There is no need for a special contents, but the length of words should matchto the language.
Heading on level 4 (paragraph) Hello, here is some text without ameaning. This text should show, how a printed text will look like at thisplace. If you read this text, you will get no information. Really? Is thereno information? Is there a difference between this text and some nonsenselike »Huardest gefburn«. Kjift – Never mind! A blind text like this givesyou information about the selected font, how the letters are written and theimpression of the look. This text should contain all letters of the alphabetand it should be written in of the original language. There is no need for aspecial contents, but the length of words should match to the language.
1.2 Lists
1.2.1 Example for list (itemize)
• First item in a list
• Second item in a list
• Third item in a list
• Fourth item in a list
• Fifth item in a list
1.2. LISTS 5
Example for list (4*itemize)
• First item in a list
– First item in a list
∗ First item in a list· First item in a list· Second item in a list
∗ Second item in a list
– Second item in a list
• Second item in a list
1.2.2 Example for list (enumerate)
1. First item in a list
2. Second item in a list
3. Third item in a list
4. Fourth item in a list
5. Fifth item in a list
Example for list (4*enumerate)
1. First item in a list
(a) First item in a list
i. First item in a listA. First item in a listB. Second item in a list
ii. Second item in a list
(b) Second item in a list
2. Second item in a list
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Introduction Document Types Special Material Wrapping Up
Basic Types (cont’d)
Articles
\documentclass{article}
\author{...}
\title{...}
\begin{document}
\maketitle
\section{...}
...
\subsection{...}
\end{document}
A Wonderful Read
A. Dummy
3rd June 2011
1 Heading on level 1 (section)Hello, here is some text without a meaning. This text should show, how aprinted text will look like at this place. If you read this text, you will get noinformation. Really? Is there no information? Is there a difference betweenthis text and some nonsense like »Huardest gefburn«. Kjift – Never mind!A blind text like this gives you information about the selected font, how theletters are written and the impression of the look. This text should containall letters of the alphabet and it should be written in of the original language.There is no need for a special contents, but the length of words should matchto the language.
1.1 Heading on level 2 (subsection)
Hello, here is some text without a meaning. This text should show, how aprinted text will look like at this place. If you read this text, you will get noinformation. Really? Is there no information? Is there a difference betweenthis text and some nonsense like »Huardest gefburn«. Kjift – Never mind!A blind text like this gives you information about the selected font, how theletters are written and the impression of the look. This text should containall letters of the alphabet and it should be written in of the original language.There is no need for a special contents, but the length of words should matchto the language.
1.1.1 Heading on level 3 (subsubsection)
Hello, here is some text without a meaning. This text should show, how aprinted text will look like at this place. If you read this text, you will get noinformation. Really? Is there no information? Is there a difference betweenthis text and some nonsense like »Huardest gefburn«. Kjift – Never mind!
1
A blind text like this gives you information about the selected font, how theletters are written and the impression of the look. This text should containall letters of the alphabet and it should be written in of the original language.There is no need for a special contents, but the length of words should matchto the language.
Heading on level 4 (paragraph) Hello, here is some text without ameaning. This text should show, how a printed text will look like at thisplace. If you read this text, you will get no information. Really? Is thereno information? Is there a difference between this text and some nonsenselike »Huardest gefburn«. Kjift – Never mind! A blind text like this givesyou information about the selected font, how the letters are written and theimpression of the look. This text should contain all letters of the alphabetand it should be written in of the original language. There is no need for aspecial contents, but the length of words should match to the language.
2 Lists
2.1 Example for list (itemize)
• First item in a list
• Second item in a list
• Third item in a list
• Fourth item in a list
• Fifth item in a list
2.1.1 Example for list (4*itemize)
• First item in a list
– First item in a list∗ First item in a list
· First item in a list· Second item in a list
∗ Second item in a list– Second item in a list
• Second item in a list
2
2.2 Example for list (enumerate)
1. First item in a list
2. Second item in a list
3. Third item in a list
4. Fourth item in a list
5. Fifth item in a list
2.2.1 Example for list (4*enumerate)
1. First item in a list
(a) First item in a list
i. First item in a listA. First item in a listB. Second item in a list
ii. Second item in a list
(b) Second item in a list
2. Second item in a list
2.3 Example for list (description)
First item in a list
Second item in a list
Third item in a list
Fourth item in a list
Fifth item in a list
2.3.1 Example for list (4*description)
First item in a list
First item in a list
First item in a listFirst item in a list
3
Second item in a listSecond item in a list
Second item in a list
Second item in a list
4
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Introduction Document Types Special Material Wrapping Up
Journal and Conference Proceedings Articles
IEEE
\documentclass{IEEEtran}
1
A Wonderful ReadA. Dummy
Abstract—Hello, here is some text without a meaning.This text should show, how a printed text will look likeat this place. If you read this text, you will get noinformation. Really? Is there no information? Is therea difference between this text and some nonsense like»Huardest gefburn«. Kjift – Never mind! A blind text likethis gives you information about the selected font, how theletters are written and the impression of the look. This textshould contain all letters of the alphabet and it should bewritten in of the original language. There is no need fora special contents, but the length of words should matchto the language.
I. HEADING ON LEVEL 1 (SECTION)
Hello, here is some text without a meaning. Thistext should show, how a printed text will look likeat this place. If you read this text, you will getno information. Really? Is there no information?Is there a difference between this text and somenonsense like »Huardest gefburn«. Kjift – Nevermind! A blind text like this gives you informationabout the selected font, how the letters are writtenand the impression of the look. This text shouldcontain all letters of the alphabet and it should bewritten in of the original language. There is no needfor a special contents, but the length of words shouldmatch to the language.
A. Heading on level 2 (subsection)
Hello, here is some text without a meaning. Thistext should show, how a printed text will look likeat this place. If you read this text, you will getno information. Really? Is there no information?Is there a difference between this text and somenonsense like »Huardest gefburn«. Kjift – Nevermind! A blind text like this gives you informationabout the selected font, how the letters are writtenand the impression of the look. This text shouldcontain all letters of the alphabet and it should bewritten in of the original language. There is no needfor a special contents, but the length of words shouldmatch to the language.
1) Heading on level 3 (subsubsection): Hello,here is some text without a meaning. This textshould show, how a printed text will look likeat this place. If you read this text, you will getno information. Really? Is there no information?Is there a difference between this text and somenonsense like »Huardest gefburn«. Kjift – Nevermind! A blind text like this gives you informationabout the selected font, how the letters are writtenand the impression of the look. This text shouldcontain all letters of the alphabet and it should bewritten in of the original language. There is no needfor a special contents, but the length of words shouldmatch to the language.
a) Heading on level 4 (paragraph): Hello,here is some text without a meaning. This textshould show, how a printed text will look likeat this place. If you read this text, you will getno information. Really? Is there no information?Is there a difference between this text and somenonsense like »Huardest gefburn«. Kjift – Nevermind! A blind text like this gives you informationabout the selected font, how the letters are writtenand the impression of the look. This text shouldcontain all letters of the alphabet and it should bewritten in of the original language. There is no needfor a special contents, but the length of words shouldmatch to the language.
II. LISTS
A. Example for list (itemize)
• First item in a list• Second item in a list• Third item in a list• Fourth item in a list• Fifth item in a list1) Example for list (4*itemize):• First item in a list
– First item in a list∗ First item in a list
· First item in a list
ACM
\documentclass{sig-alternate}
A Wonderful Read
A. Dummy
ABSTRACTHello, here is some text without a meaning. This text should show,how a printed text will look like at this place. If you read thistext, you will get no information. Really? Is there no informa-tion? Is there a difference between this text and some nonsenselike »Huardest gefburn«. Kjift – Never mind! A blind text like thisgives you information about the selected font, how the letters arewritten and the impression of the look. This text should containall letters of the alphabet and it should be written in of the originallanguage. There is no need for a special contents, but the length ofwords should match to the language.
1. Heading on level 1 (SECTION)Hello, here is some text without a meaning. This text should
show, how a printed text will look like at this place. If you readthis text, you will get no information. Really? Is there no infor-mation? Is there a difference between this text and some nonsenselike »Huardest gefburn«. Kjift – Never mind! A blind text like thisgives you information about the selected font, how the letters arewritten and the impression of the look. This text should containall letters of the alphabet and it should be written in of the originallanguage. There is no need for a special contents, but the length ofwords should match to the language.
1.1 Heading on level 2 (subsection)Hello, here is some text without a meaning. This text should
show, how a printed text will look like at this place. If you readthis text, you will get no information. Really? Is there no infor-mation? Is there a difference between this text and some nonsenselike »Huardest gefburn«. Kjift – Never mind! A blind text like thisgives you information about the selected font, how the letters arewritten and the impression of the look. This text should containall letters of the alphabet and it should be written in of the originallanguage. There is no need for a special contents, but the length ofwords should match to the language.
1.1.1 Heading on level 3 (subsubsection)Hello, here is some text without a meaning. This text should
Permission to make digital or hard copies of all or part of this work forpersonal or classroom use is granted without fee provided that copies arenot made or distributed for profit or commercial advantage and that copiesbear this notice and the full citation on the first page. To copy otherwise, torepublish, to post on servers or to redistribute to lists, requires prior specificpermission and/or a fee.MOSC 2011, July 3–5, 2011, Penang, Malaysia.Copyright 2011 ACM 123-4-56789-012-3/11/0007 ...$10.00.
show, how a printed text will look like at this place. If you readthis text, you will get no information. Really? Is there no infor-mation? Is there a difference between this text and some nonsenselike »Huardest gefburn«. Kjift – Never mind! A blind text like thisgives you information about the selected font, how the letters arewritten and the impression of the look. This text should containall letters of the alphabet and it should be written in of the originallanguage. There is no need for a special contents, but the length ofwords should match to the language.
Heading on level 4 (paragraph).Hello, here is some text without a meaning. This text should
show, how a printed text will look like at this place. If you readthis text, you will get no information. Really? Is there no infor-mation? Is there a difference between this text and some nonsenselike »Huardest gefburn«. Kjift – Never mind! A blind text like thisgives you information about the selected font, how the letters arewritten and the impression of the look. This text should containall letters of the alphabet and it should be written in of the originallanguage. There is no need for a special contents, but the length ofwords should match to the language.
2. Lists
2.1 Example for list (itemize)
• First item in a list
• Second item in a list
• Third item in a list
• Fourth item in a list
• Fifth item in a list
2.1.1 Example for list (4*itemize)
• First item in a list
– First item in a list
∗ First item in a list· First item in a list· Second item in a list
∗ Second item in a list
– Second item in a list
• Second item in a list
LLNCS
\documentclass{llncs}
A Wonderful Read
A. Dummy
No Institute Given
Abstract Hello, here is some text without a meaning. This text shouldshow, how a printed text will look like at this place. If you read this text,you will get no information. Really? Is there no information? Is there adifference between this text and some nonsense like »Huardest gefburn«.Kjift – Never mind! A blind text like this gives you information aboutthe selected font, how the letters are written and the impression of thelook. This text should contain all letters of the alphabet and it shouldbe written in of the original language. There is no need for a specialcontents, but the length of words should match to the language.
1 Heading on level 1 (section)
Hello, here is some text without a meaning. This text should show,how a printed text will look like at this place. If you read this text,you will get no information. Really? Is there no information? Is therea difference between this text and some nonsense like »Huardestgefburn«. Kjift – Never mind! A blind text like this gives you infor-mation about the selected font, how the letters are written and theimpression of the look. This text should contain all letters of the al-phabet and it should be written in of the original language. There isno need for a special contents, but the length of words should matchto the language.
1.1 Heading on level 2 (subsection)
Hello, here is some text without a meaning. This text should show,how a printed text will look like at this place. If you read this text,you will get no information. Really? Is there no information? Is therea difference between this text and some nonsense like »Huardestgefburn«. Kjift – Never mind! A blind text like this gives you infor-mation about the selected font, how the letters are written and the
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Introduction Document Types Special Material Wrapping Up
Some Goodies
Quick language-switching with babel
Automatic generation of cross-referencing labels:\section{Introduction}\label{sec:intro}
... We saw in section \ref{sec:intro}...
Automatic generation of lists:\tableofcontents, \listoffigures, \listoftables
Automatic generation of bibliographies and indices:\cite{Knuth:1976}...\bibliography{references.bib}
...the Linux kernel\index{Linux!kernel}... \printindex
Fully hyperlinked PDF with bookmarks: \usepackage{hyperref}
Inclusion of selected pages from other PDFs(while inserting new page headers/footers!)\usepackage{pdfpages}
\includepdf[pages={1,3-5,8},pagecommand=\thispagestyle{plain}]{file.pdf}
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Introduction Document Types Special Material Wrapping Up
University Theses
Universiti Sains Malaysia \documentclass{usmthesis}
WRITING YOUR THESIS WITH LATEX
by
LIM LIAN TZE
Thesis submitted in fulfilment of the requirementsfor the degree of
Master of Science
December 2007
TABLE OF CONTENTS
Acknowledgements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
Table of Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi
List of Plates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
List of Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii
List of Symbols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
Abstrak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi
CHAPTER 1 – INTRODUCTION: SAMPLES OF BASIC LATEXCOMMANDS
1.1 Some Simple Command Usages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Special Characters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Useful Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
CHAPTER 2 – CITATIONS AND BIBLIOGRAPHY
2.1 The *.bib File . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.2 Citations using the natbib package. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.2.1 Author-Year System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.2.2 Numeric System. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
CHAPTER 3 – FIGURES, TABLES, EQUATIONS, ALGORITHMS, ETC
3.1 Inserting Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.2 Inserting Plates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
3.3 Inserting Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
iii
CHAPTER 1
INTRODUCTION: SAMPLES OF BASIC LATEXCOMMANDS
Hello and welcome, fellow Universiti Sains Malaysia (USM) research postgrad! The
usmthesis package and template files were written in the hope that they may help
you prepare your research thesis using LATEX, based on the Institut Pengajian Siswazah
(IPS) requirements (IPS, 2007). Please note that this version is based on the new
guidelines, in force 17 Dec 2007 onwards. (Song, Cai, Lyu and Cai, 2002)
LATEX is powerful and produces beautiful documents. However, there is definitely
a learning curve to it – one that is worth the effort. If you find any errors in these
templates or documents, or have any suggestions or feedback, do e-mail me about it
([email protected]). The author cannot always guarantee prompt response, how-
ever. ©
MiKTEX, my recommended LATEX distribution for Windows, is available on the
CSPC’07 CD. A step-by-step installation walkthrough is available at (Lim, 2009).
1.1 Some Simple Command Usages
There are plenty of free LATEX tutorials online, some of which are listed in the bibli-
ographies or available at http://e-office.cs.usm.my. This sample thesis includes some
examples to do some common tasks. We start with some examples for lists (both bul-
1
REFERENCES
Changsheng, X., Wang, J., Lu, L. and Zhang, Y. (2008). A novel framework forsemantic annotation and personalized retrieval of sports video, Multimedia, IEEETransactions on 10(3): 421–436.
D’Orazio, T., Leo, M., Spagnolo, P., Mazzeo, P. L., Mosca, N., Nitti, M. and Distante,A. (2009). An investigation into the feasibility of real-time soccer offside detec-tion from a multiple camera system, IEEE TRANSACTIONS ON CIRCUITS ANDSYSTEMS FOR VIDEO TECHNOLOGY 19(12): 1804–1818.
D’Orazio, T., Leo, M., Spagnolo, P., Nitti, M., Mosca, N. and Distante, A. (2009).A visual system for real time detection of goal events during soccer matches,Computer Vision and Image Understanding 113(5): 622–632. Computer VisionBased Analysis in Sport Environments.URL: http://www.sciencedirect.com/science/article/B6WCX-4S50K9H-1/2/fe82b213b3ec28e07aef15882eb37538
IPS (2007). A Guide to the Preparation, Submission and Examination of Theses, In-stitute of Graduate Studies, Universiti Sains Malaysia, Penang, Malaysia.
Lim, L. T. (2009). LATEX: Beautiful typesetting, [Online]. [Accessed January 22, 2011].Available from World Wide Web: http://liantze.googlepages.com/latextypesetting.
Mittelbach, F., Goossens, M., Braams, J., Carlisle, D. and Rowley, C. (2004). TheLATEX Companion, Addison-Wesley Series on Tools and Techniques for ComputerTypesetting, 2nd edn, Addison-Wesley, Boston, MA, USA.
Oetiker, T., Partl, H., Hyna, I. and Schlegl, E. (2006). The Not So Short Introductionto LATEX 2ε , 4.2 edn.
Roberts, A. (2005). Getting to grips with LATEX, [Online]. [Accessed January 22,2011]. Available from World Wide Web: http://www.andy-roberts.net/misc/latex/index.html.
Song, J. Q., Cai, M., Lyu, M. R. and Cai, S. J. (2002). A new approach for linerecognition in large-size images using hough transform, Proceedings of the 16thInternational Conference on Pattern Recognition., Vol. 1, pp. 33–36.
24
Lim Lian Tze | mosc 2011 18 / 48
Introduction Document Types Special Material Wrapping Up
University Theses (cont’d)
Multimedia University \documentclass{mmuthesis}
THE MMUTHESIS LATEX DOCUMENTCLASS
BY
LIM LIAN TZEB.Sc. (Hons), University of Warwick, United Kingdom
M.Sc., Universiti Sains Malaysia, Malaysia
THESIS SUBMITTED IN FULFILMENT OF THE
REQUIREMENT FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
(by Research)
in the
Faculty of Information Technology
MULTIMEDIA UNIVERSITYMALAYSIA
April 2010
TABLE OF CONTENTS
COPYRIGHT PAGE ii
DECLARATION iii
ACKNOWLEDGEMENTS iv
DEDICATION v
ABSTRACT vi
TABLE OF CONTENTS vii
LIST OF TABLES viii
LIST OF FIGURES ix
PREFACE x
CHAPTER 1: INTRODUCTION, BACKGROUND STORY,MOTIVATIONS 1
1.1 First Test and I need a really long title, please do oblige me won’t you?Just a few more words and yes we’re there 11.1.1 Second Test 1
1.2 Yeah 2
CHAPTER 2: DUMMY CHAPTER 3
APPENDIX A: MANUALS, TECHNICAL SPECIFICATIONS,DOCUMENTATIONS, EXAMPLE SCENARIOS 4
APPENDIX B: TRY 5
REFERENCES 6
GLOSSARY 7
INDEX 8
PUBLICATION LIST 9
vii
CHAPTER 1
INTRODUCTION, BACKGROUND STORY, MOTIVATIONS
1.1 First Test and I need a really long title, please do oblige me won’t you? Justa few more words and yes we’re there
Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Ut purus elit, vestibu-lum ut, placerat ac, adipiscing vitae, felis. Curabitur dictum gravida mauris. Nam arculibero, nonummy eget, consectetuer id, vulputate a, magna. Donec vehicula augueeu neque. Pellentesque habitant morbi tristique senectus et netus et malesuada famesac turpis egestas. Mauris ut leo. Cras viverra metus rhoncus sem. Nulla et lectusvestibulum urna fringilla ultrices. Phasellus eu tellus sit amet tortor gravida placerat.Integer sapien est, iaculis in, pretium quis, viverra ac, nunc. Praesent eget sem vel leoultrices bibendum. Aenean faucibus. Morbi dolor nulla, malesuada eu, pulvinar at,mollis ac, nulla. Curabitur auctor semper nulla. Donec varius orci eget risus. Duisnibh mi, congue eu, accumsan eleifend, sagittis quis, diam. Duis eget orci sit amet orcidignissim rutrum.
Nam dui ligula, fringilla a, euismod sodales, sollicitudin vel, wisi. Morbi auctorlorem non justo. Nam lacus libero, pretium at, lobortis vitae, ultricies et, tellus. Donecaliquet, tortor sed accumsan bibendum, erat ligula aliquet magna, vitae ornare odiometus a mi. Morbi ac orci et nisl hendrerit mollis. Suspendisse ut massa. Cras nec ante.Pellentesque a nulla. Cum sociis natoque penatibus et magnis dis parturient montes,nascetur ridiculus mus. Aliquam tincidunt urna. Nulla ullamcorper vestibulum turpis.Pellentesque cursus luctus mauris.
Test 1
Figure 1.1: First figure. OK?
1.1.1 Second Test
Their (Audibert, 2004) requirements1 are really amazing2 (Budanitsky & Hirst,2006).
1See here, how weird, how to fill out an entire line. See here, how weird, how to fill out an entire line. See here, how weird,how to fill out an entire line. See here, how weird, how to fill out an entire line. See here, how weird, how to fill out an entire line.
2don’t you agree?
1
REFERENCES
[1] Audibert, L. (2004). Word sense disambiguation criteria: a systematic study. In 20th in-ternational conference on computational linguistics (coling 2004) (pp. 910–916). Geneva,Switzerland: COLING.
[2] Budanitsky, A., & Hirst, G. (2006). Evaluating WordNet-based measures of lexical semanticrelatedness. Computational Linguistics, 32(1), 13–47.
6
Lim Lian Tze | mosc 2011 19 / 48
Introduction Document Types Special Material Wrapping Up
University Theses (cont’d)
Universiti Malaya \documentclass{umalayathesis}
THE UMALAYATHESIS LATEX DOCUMENT CLASS
LIM LIAN TZE
THESIS SUBMITTED IN FULFILMENTOF THE REQUIREMENTS
FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
INSTITUTE OF POSTGRADUATE STUDIESUNIVERSITY OF MALAYA
KUALA LUMPUR
2010
TABLE OF CONTENTS
ABSTRACT ii
DECLARATION iii
ACKNOWLEDGEMENTS iv
TABLE OF CONTENTS v
LIST OF FIGURES vi
LIST OF TABLES vii
LIST OF SYMBOLS AND ACRONYMS viii
LIST OF APPENDICES ix
PREFACE x
CHAPTER 1: INTRODUCTION, BACKGROUND STORY, MOTIVATIONS 11.1 First Test and I need a really long title, please do oblige me won’t you?
Just a few more words and yes we’re there 11.1.1 Second Test 2
1.2 Yeah 2
CHAPTER 2: DUMMY CHAPTER 5
APPENDICES 6
REFERENCES 9
v
CHAPTER 1
INTRODUCTION, BACKGROUND STORY, MOTIVATIONS
1.1 First Test and I need a really long title, please do oblige me won’t you? Just afew more words and yes we’re there
Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Ut purus elit, vestibulum
ut, placerat ac, adipiscing vitae, felis. Curabitur dictum gravida mauris. Nam arcu libero,
nonummy eget, consectetuer id, vulputate a, magna. Donec vehicula augue eu neque. Pel-
lentesque habitant morbi tristique senectus et netus et malesuada fames ac turpis egestas.
Mauris ut leo. Cras viverra metus rhoncus sem. Nulla et lectus vestibulum urna fringilla
ultrices. Phasellus eu tellus sit amet tortor gravida placerat. Integer sapien est, iaculis
in, pretium quis, viverra ac, nunc. Praesent eget sem vel leo ultrices bibendum. Aenean
faucibus. Morbi dolor nulla, malesuada eu, pulvinar at, mollis ac, nulla. Curabitur auctor
semper nulla. Donec varius orci eget risus. Duis nibh mi, congue eu, accumsan eleifend,
sagittis quis, diam. Duis eget orci sit amet orci dignissim rutrum.
Nam dui ligula, fringilla a, euismod sodales, sollicitudin vel, wisi. Morbi auctor
lorem non justo. Nam lacus libero, pretium at, lobortis vitae, ultricies et, tellus. Donec
aliquet, tortor sed accumsan bibendum, erat ligula aliquet magna, vitae ornare odio metus
a mi. Morbi ac orci et nisl hendrerit mollis. Suspendisse ut massa. Cras nec ante. Pellen-
tesque a nulla. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur
ridiculus mus. Aliquam tincidunt urna. Nulla ullamcorper vestibulum turpis. Pellen-
tesque cursus luctus mauris.
Figure 1.1: First figure. OK?
1
REFERENCES
Audibert, L. (2004). Word sense disambiguation criteria: a systematic study. In 20th International Confer-ence on Computational Linguistics (COLING 2004) (pp. 910–916). Geneva, Switzerland: COLING.
Budanitsky, A., & Hirst, G. (2006). Evaluating WordNet-based measures of lexical semantic relatedness.Computational Linguistics, 32(1), 13–47.
9
Lim Lian Tze | mosc 2011 20 / 48
Introduction Document Types Special Material Wrapping Up
Highly ConVgurable Documentsmemoir and KOMA-Script Classes
Sectional headings
Running headers and footers
Good font, colour and illustration choices
http://latex-my.blogspot.com/search/label/bookdesign
Grid Computing ClusterThe Development and Integration of
Grid Services and Applications
Grid@USM2008/09 Report
Edited by Bahari Belaton and Lim Lian TzePlatform for Information & Communication Technology Research
Universiti Sains Malaysia
CONTENTSProject OverviewIntroduction 2Grid@USM: Developing & Integrating Grid Applications & Services 4
Project Milestones 7
Project Expenditures 8
Sub-ProjectsSetting up USM Campus Grid 10
AP Chan Huah Yong, Ang Sin Keat, Tan Chin Min, Kheoh Hooi Leng, Cheng Wai Khuen, M. Muzzammil bin Mohd Salahudin
Dynamic Replica Management in Data Grid Environment 14AP Chan Huah Yong, Aloysius Indrayanto and Muhammad Muzzammil bin Mohd Salahudin
Using Grid Technology to Create a Render-Farm for Blender 3D Animation 18AP Phua Kia Ken and Zafri Muhammad
Grid-enabled Blexisma2 23AP Tang Enya Kong, Lim Lian Tze, Ye Hong Hoe and Dr Didier Schwab
B2B Standards Component Modeling 27Dr Vincent Khoo Kay Teong, Ting Tin Tin, Rinki Yadav, Johnson Foong and Kor Chan Hock
An Automated Java Testing Tool on the Grid 31Dr Kamal Zuhairi Zamli, Dr Nor Ashidi Mat Isa, Mohammed Issam Younis and Saidatul Khatimah binti Said
iNet-Grid 35Prof. Sureswaran Ramadass, AP Rahmat Budiarto, AP Chan Huah Yong and Dr Ahmed M. Manasrah
Grid Application to Wave Front Propagation and Containment of Vector Borne Diseases 40Prof. Koh Hock Lye, Dr Teh Su Yean and Tan Kah Bee
Project ActivitiesOrganised Events 46
Other Events 48Publications 50
Note: The abbreviations Prof. and AP are used for Professor and Associate Professor respectively throughout this book.
Grid@USM:DEVELOPING & INTEGRATINGGRID APPLICATIONS & SERVICES
Image: A simple network. Illustration by ©Svilen Mushkatov (http://www.sxc.hu/profile/svilen001).
USM’S R&D SUSTAINABILITYTo attain the level of excellence as aresearch university (RU), USM in re-cent years has seriously engaged her-self in various efforts to formulateand chart her future research anddevelopment (R&D) directions. Thepinnacle of these efforts was trans-lated into a 2 year strategic plan “USMResearch-Intensive University 2007–2009”.
One of the crucial input elements
for attaining and subsequently sus-taining RU status is the creationof highly conducive research envi-ronment and infrastructure. Gridcomputing is an example of suchinfrastructure, aiming at providingexcellent research facilities by en-suring good computational horse-power to support high impact do-mains in the bio-sciences, physicalsciences, information and communi-cation technology (ICT), Environmentsciences, Education, Arts and others.
Grid computing is by its na-ture highly distributed geographically,consists of highly specialised equip-ment (storage, grid engines and man-agement tools), as well as expensive.It is as such an ideal example of com-mon, core computational resourcesto be created and pooled among as-piring researchers who require highperformance resources.
Equally important, USM needs a fo-cused, holistic and dedicated effort
4
Grid@USM
SLB on utmkblex
LexiconDispenser
PWNAnalyser
PWNAnalyser
LexiconDispenser
PWNAnalyser
Remote Host
LexiconDispenser
PWNAnalyser
Remote Host
LexiconDispenser
PWNAnalyser
Remote Host
LexiconDispenser
Sense-Tagger
SyntacticParser
Remote Host
Figure 3: Blexisma2 agents are deployed on USM Campus Grid nodes using the Globus job submission toolkit.
(a) Diferent meanings of star in context (b) Diferent meanings of school in context
Figure 4: SLB data generated by Blexisma2 agents used to determine most probable meanings of ambiguous lexicalitem. A Web interface to the Sense-Tagger is available at http://utmkblex.usmgrid.myren.net.my:8080/Blexisma2Servlets/CVSenseTagger.
interested to improve its design toa multilingual setting, where morecomplicated cross-lingual phenomenawill have to be considered. We alsohope to improve the agent commu-nication mechanisms to reduce la-tency. Apart from creating moreagents that implement different learn-ing algorithms and heuristics, we arealso planning agents responsible forother NLP tasks such as deep parsing,detecting named entities, etc. In otherwords, we hope to have agents of var-ious responsibilities so that they canbe ‘mixed-and-matched’ to constructnew NLP applications, such as thosementioned in the introduction.
On the performance issues, wemay attempt several solutions for theSLB bottleneck problem mentionedearlier:
Ț hardware (RAM) upgrades,Ț further optimisation of PostgreSQL
server settings,Ț database connection pooling,Ț load balancing,Ț parallelising queries.
PROJECT PUBLICATIONSLim, L. T. & Schwab, D. (2008). Lim-
its of Lexical Semantic Relatedness
with Ontology-based ConceptualVectors. In Proceedings of the 5th In-ternational Workshop on Natural Lan-guage Processing and Cognitive Sci-ence (NLPCS’08). Barcelona, Spain;pp. 153–158.
Schwab, D. & Lim, L. T. (2008). Blex-isma2: a Distributed Agent Frame-work for Constructing a SemanticLexical Database based on Con-ceptual Vectors. In Proceedingsof the International Conference onDistributed Frameworks & Applica-tions 2008 (DFmA 2008). Penang,Malaysia; pp. 102–110.
@G
rid
U
S M
26 GRID-ENABLED BLEXISMA2
Table of Contents
n Conceptual Business Plan 41. Executive Summary 5
2. Company Summary 62.1. Company Background 6
2.2. Business Intent 7
2.3. Start-up Summary 7
3. Service and Product Development 93.1. Technology Overview 9
3.2. Services and Products 10
3.3. Research & Development 13
4. Market Analysis 134.1. Target Market 13
4.2. Market Segmentation 14
4.3. Competitors 17
4.4. SWOT Analysis 19
5. Marketing Plan 205.1. Product Pricing 21
5.2. Sales Strategy 22
5.3. Advertising and Promotional Plan 22
5.4. Sales Forecast 24
6. Management Plan 256.1. Management Team 26
6.2. Human Resources Plan 28
6.3. Job Responsibilities 28
7. Operational Plan 297.1. Location 30
7.2. Production Plan 30
7.3. Service Plan 31
7.4. Distribution Methods 34
7.5. ICT Plan 34
7.6. Suppliers and Vendors 34
7.7. Operational Costs 34
2
B 21 Tingkat Meranti 6, Taman Meranti, 13000 Butterworth, Penang, Malaysia.T +60 (0) 4 123 4567. k [email protected]. m http://texart.penguinattack.org.
TEXAr tTraining
Service and Product Development
3. Service and Product Development
TEXArt Training offers LATEX-related training services and document pre-
paration solutions, catering especially to researchers in Malaysian IHLs in
the company's start-up stage.
3.1. Technology Overview
LATEX is a professional-quality document preparation system. It is open
source, and is both free for use and free of charge.
LATEX is especially suitable for typesetting complex documents with
heavy mathematical material, and is the standard publishing tool in tech-
nical disciplines and many related �elds (Talbert, 2010). Documents pro-
duced with LATEX are of professional publishing quality: the TEX typesetting
engine places lines of text on the page based on complex calculations
and typography rules for that polished professional look (Mittelbach, Goos-
sens, Braams, Carlisle & Rowley, 2004). See Appendix A for sample LATEX
output.
LATEX encourages the writing of well-structured documents. An author
using LATEX therefore focuses on the logical organisation of the contents,rather than being distracted by visual formatting concerns � a common an-noyance with word processors. In other words, LATEX has a clear advantage
over What You See Is What You Get (WYSIWYG) word processors when a
documents grows in complexity and length (Brunton, 2007, Figure 1).
impossible to do
WordÆ
LATEX
document complexity and size
effortandtimeconsumption
Figure 1: Scalability of LATEX and Microsoft WordÆ against document sizeand complexity (Source: Brunton, 2007)
9
B 21 Tingkat Meranti 6, Taman Meranti, 13000 Butterworth, Penang, Malaysia.T +60 (0) 4 123 4567. k [email protected]. m http://texart.penguinattack.org.
TEXAr tTraining
Management Plan
M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M120
2
4
6
8
10
12
Month
Sales(RM1,000)
Beginner Intermediate
Advanced Consultation
Figure 3: Sales forecast for Year 1
Table 11: Sales forecast for �rst 3 years
Category Y1 Y2 Y3
Sales
Training SalesNo. of training seats soldBeg. 450 400 450
Interm. 400 600 700
Adv. 30 60 150
Sales volume (RM)Beg. 22,500 20,000 22,500
Interm. 60,000 90,000 105,000
Adv. 7,500 15,000 37,500
Consultation SalesServices 600 660 720
Total sales 90,600 125,660 165,720
Direct Cost of Sales
Production 396 477 585
Travel 7,200 8,800 11,200
Total cost 7,596 9,277 11,785
6. Management Plan
TEXArt Training is a general partnership owned by Lim Lian Tze andRonald Wong Mun Choong. They own equal parts of the company, and
also share all pro�ts and losses equally.
25
B 21 Tingkat Meranti 6, Taman Meranti, 13000 Butterworth, Penang, Malaysia.T +60 (0) 4 123 4567. k [email protected]. m http://texart.penguinattack.org.
TEXAr tTraining
Projected Monthly Balance Sheet for Year 1
E. Projected Monthly Profit and Loss for Year 1
M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12
Sales 0.00 2500.00 2500.00 7500.00 10000.00 5300.00 10000.00 12500.00 12500.00 10000.00 8750.00 9050.00
Cost of sales 0.00 422.50 422.50 845.00 845.00 422.50 840.50 845.00 845.00 840.50 633.75 633.75
Gross Margin 0.00 2077.50 2077.50 6655.00 9155.00 4877.50 9159.50 11655.00 11655.00 9159.50 8116.25 8416.25
Gross Margin % 0.00 83.10% 83.10% 88.73% 91.55% 92.03% 91.60% 93.24% 93.24% 91.60% 92.76% 93.00%
Operational Costs
Salaries 3865.70 3865.70 3865.70 3865.70 3865.70 3865.70 3865.70 3865.70 3865.70 3865.70 3865.70 3865.70
Rental 150.00 150.00 150.00 150.00 150.00 150.00 150.00 150.00 150.00 150.00 150.00 150.00
Utilities, bills, etc 558.50 558.50 558.50 558.50 558.50 558.50 558.50 558.50 558.50 558.50 558.50 558.50
Total operational costs 4574.20 4574.20 4574.20 4574.20 4574.20 4574.20 4574.20 4574.20 4574.20 4574.20 4574.20 4574.20
Earnings before interest -4574.20 -2496.70 -2496.70 2080.80 4580.80 303.30 4585.30 7080.80 7080.80 4585.30 3542.05 3842.05
Interest 240.00 240.00 240.00 240.00 240.00 240.00 240.00 240.00 240.00 240.00 240.00 240.00
Net Income -4814.20 -2736.70 -2736.70 1840.80 4340.80 63.30 4345.30 6840.80 6840.80 4345.30 3302.05 3602.05
% 0.00 -109.47% -109.47% 24.54% 43.41% 1.19% 43.45% 54.73% 54.73% 43.45% 37.74% 39.80%
F. Projected Monthly Cash Flow for Year 1
M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12
Cash Revenue
Cash from receivables 0.00 2500.00 2500.00 7500.00 10000.00 5000.00 10000.00 12800.00 12500.00 10000.00 8750.00 8750.00
Total Revenue 0.00 2500.00 2500.00 7500.00 10000.00 5000.00 10000.00 12800.00 12500.00 10000.00 8750.00 8750.00
Cash Disbursements
Salary 3865.70 3865.70 3865.70 3865.70 3865.70 3865.70 3865.70 3865.70 3865.70 3865.70 3865.70 3865.70
Rental 150.00 150.00 150.00 150.00 150.00 150.00 150.00 150.00 150.00 150.00 150.00 150.00
Utilities, bills, etc. 0.00 558.50 558.50 558.50 558.50 558.50 558.50 558.50 558.50 558.50 558.50 558.50
Loan repayment 440.00 440.00 440.00 440.00 440.00 440.00 440.00 440.00 440.00 440.00 440.00 440.00
Sales costs 0.00 422.50 422.50 845.00 845.00 422.50 840.50 845.00 845.00 840.50 633.75 633.75
Total Disbursements 4455.70 5436.70 5436.70 5859.20 5859.20 5436.70 5854.70 5859.20 5859.20 5854.70 5647.95 5647.95
Opening Cash Bal. 21670.00 17214.30 14277.60 11340.90 12981.70 17122.50 16685.80 20831.10 27771.90 34412.70 38558.00 41660.05
Net Cash Flow -4455.70 -2936.70 -2936.70 1640.80 4140.80 -436.70 4145.30 6940.80 6640.80 4145.30 3102.05 3102.05
Closing Cash Bal. 17214.30 14277.60 11340.90 12981.70 17122.50 16685.80 20831.10 27771.90 34412.70 38558.00 41660.05 44762.10
G. Projected Monthly Balance Sheet for Year 1
Starting Balance M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12
Assets
Current assetsCash 21670.00 17214.30 14277.60 11340.90 12981.70 17122.50 16685.80 20831.10 27771.90 34412.70 38558.00 41660.05 44762.10
Accounts receivable 0.00 0.00 0.00 0.00 0.00 0.00 300.00 300.00 0.00 0.00 0.00 0.00 300.00
Total current assets 21670.00 17214.30 14277.60 11340.90 12981.70 17122.50 16985.80 21131.10 27771.90 34412.70 38558.00 41660.05 45062.10
Long term assets 8780.00 8780.00 8780.00 8780.00 8780.00 8780.00 8780.00 8780.00 8780.00 8780.00 8780.00 8780.00 8780.00
Total assets 30450.00 25994.30 23057.60 20120.90 21761.70 25902.50 25765.80 29911.10 36551.90 43192.70 47338.00 50440.05 53842.10
Liabilities
Accounts payable 0.00 558.50 558.50 558.50 558.50 558.50 558.50 558.50 558.50 558.50 558.50 558.50 558.50
Current borrowing 12000.00 11800.00 11600.00 11400.00 11200.00 11000.00 10800.00 10600.00 10400.00 10200.00 10000.00 9800.00 9600.00
Total liabilities 12000.00 12358.50 12158.50 11958.50 11758.50 11558.50 11358.50 11158.50 10958.50 10758.50 10558.50 10358.50 10158.50
Owner's Equity
Paid-in capital 20000.00 20000.00 20000.00 20000.00 20000.00 20000.00 20000.00 20000.00 20000.00 20000.00 20000.00 20000.00 20000.00
Retained Earnings -1550.00 -6364.20 -9100.90 -11837.60 -9996.80 -5656.00 -5592.70 -1247.40 5593.40 12434.20 16779.50 20081.55 23683.60
Net Equity 18450.00 13635.80 10899.10 8162.40 10003.20 14344.00 14407.30 18752.60 25593.40 32434.20 36779.50 40081.55 43683.60
Total Liab. & Eq. 30450.00 25994.30 23057.60 20120.90 21761.70 25902.50 25765.80 29911.10 36551.90 43192.70 47338.00 50440.05 53842.10
50
B 21 Tingkat Meranti 6, Taman Meranti, 13000 Butterworth, Penang, Malaysia.T +60 (0) 4 123 4567. k [email protected]. m http://texart.penguinattack.org.
TEXAr tTraining
Lim Lian Tze | mosc 2011 21 / 48
Introduction Document Types Special Material Wrapping Up
Presentation Slides
This presentation was made with LATEX!
Many possible classes: powerdot, beamer
\documentclass{beamer}\usetheme{Warsaw
SzegedBergenoxygen
}
\author ...
\begin{document}\titleframe
\section{Intro}
\begin{frame}\frametitle{Some Background}...\end{frame}\end{document}
Intro
A First Presentation
Lim Lian Tze
June 3, 2011
Lim Lian Tze A First Presentation
Intro
A First Presentation
Lim Lian Tze
June 3, 2011
A First Presentation
A First Presentation
Who? Lim Lian Tze
When? June 3, 2011
Intro
A First Presentation
Lim Lian Tze
June 3, 2011
Lim Lian Tze — A First Presentation 1/2
Intro
Some Background
Once upon a time
There were programmers
Lim Lian Tze A First Presentation
Intro
Some Background
◮ Once upon a time
◮ There were programmers
A First Presentation
Some Background
Once upon a time
There were programmers
Intro
Some Background
Once upon a time
There were programmers
Lim Lian Tze — A First Presentation 2/2
Lim Lian Tze | mosc 2011 22 / 48
Introduction Document Types Special Material Wrapping Up
Oversized Posters
Many possible solutions: sciposter, flowfram, beamerposter
\documentclass{beamer}\usepackage[orientation=portrait,→˓ size=a0]{beamerposter}\usetheme{...}\author ... % Meta−information
\begin{document}\begin{frame}... % Poster contents goes here\end{frame}\end{document}
Low-Cost Construction of aMultilingual Lexicon from Bilingual Lists
Introduction
◮ Bilingual MRDs are good resources for buildingmultilingual lexicons, but heterogeneous structures
◮ Lowest common denominator: list ofsource language item→ target language item(s)
◮ Proposal: Multilingual lexicon construction using onlysimple bilingual lists
One-time Inverse Consultation [1]◮ Generates a bilingual lexicon for new language pair
from existing bilingual lists◮ JP–EN, EN–MS, MS–EN lexicons ⇒ JP–MS
Japanese English Malaymark tanda
p seal anjing lautstamp teraimprintgauge
score(‘tera’) = 2 × |E1 ∩ E2||E1| + |E2|
= 2 × 2
3 + 4= 0.57
∴�p�↔ ‘tera’ is most likely valid
Merging Translation Triples into Sets
◮ (Example: Malay–English–Chinese)◮ Retain OTIC ‘middle’ language links◮ For each ‘head’ language LI, discard triples with score
< αX or score2 < βX, where X = max score of alltriples containing that LI
(garang, ferocious, ö�)(garang, �erce, ö�)
(garang, ööö���) 0.143
(garang, jazzy, ÀÈ)
(garang, ÀÀÀÈÈÈ) 0.125
(garang, bold, 'Æ)
(garang, '''ÆÆÆ) 0.111
(garang, bold, ÑS)
(garang, ÑÑÑSSS) 0.048
(garang, bold, �S)
(garang, ���SSS) 0.048
⋮
◮ Merge all triples with common bilingual pairs
garang
bengkeng�erce
ferocious ö�
Ð→(garang, ferocious,ö�)(garang, �erce,ö�)(bengkeng, �erce,ö�)
References[1]F. Bond and K. Ogura. “Combining linguistic resources to create a
machine-tractable Japanese–Malay dictionary”. In: LanguageResources and Evaluation 42 (2008), pp. 127–136.
Adding a New Language
◮ (Example: Malay–English–Chinese + French)◮ Construct also French–English–Malay triples◮ Add French members to existing M-E-C clusters with
common English & Malay members
garang
bengkeng�erce
ferocious ö�
+ (cruel, ferocious, garang)(féroce, �erce, garang)Ð→
garang
cruelféroce
bengkeng
�erce
ferocious ö�
Precision of 100 Random Translation Sets
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.7
0.75
0.8
0.85
β
Precision
α = 0.0α = 0.2α = 0.8
◮ Precision generally around 0.70–0.82; max 0.86
F1 and Rand Index of Selected Translation Sets
◮ Evaluating accuracy of sets with polysemous ‘middle’language members, e.g. ‘plant’, ‘target’Test Rand Index F1 Best accuracy whenword min max min max α β
‘bank’ 0.417 0.611 0.588 0.632 0.6 0.4‘plant’ 0.818 0.927 0.809 0.913 0.6 0.2‘target’ 0.821 1.000 0.902 1.000 0.4 0.2‘letter’ 0.709 0.818 0.724 0.792 0.8 0.2
Discussion and Conclusion
◮ Low thresholds (α, β): more coverage; low precision◮ High thresholds: good precision; low coverage◮ α = 0.6, β = 0.2 gives good trade-oU between
coverage, precision and recall◮ Results are encouraging for such simple input data!◮ Future plan: Integrate lexicon
into an MT systemwith WSD
Lian Tze Lim Bali Ranaivo-Malançon Enya Kong [email protected] {ranaivo,enyakong}@mmu.edu.myNLP-SIG, Faculty of Information Technology, Multimedia University, Malaysia
Limits of Lexical Semantic Relatedness withOntology-based Conceptual Vectors
Lian-Tze Lim (Universiti Sains Malaysia)Didier Schwab (Université Pierre Mendès France)
Introduction
Miller-Charles dataset (1991)◮ Human judgements of similarity between pairs of English words◮ Machine-computed scores can be compared against dataset
We aim to◮ Represent thematic aspects of text (incl. word senses) with Conceptual
Vectors◮ Define semantic relatedness based on conceptual vectors◮ Study behavior of CVs constructed based on ontology◮ . . . by comparing against Miller-Charles dataset
Complementing WordNet with Non-discrete Navigation
���������A B�CCDE�����A
FDE�D�A
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��C����� ��C�����
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A
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�������������� ������A������◮ WordNet: explicit semantic
relations between senses◮ Introduce non-discrete
navigation with idea ofneightbourhood
◮ To solve (in part) TennisProblem of WordNet
◮ CVs for WordNet sensesprojects them ontohyperspace
Conceptual Vectors (CV)
Principle and Thematic Distance◮ Inspired by componential semantics
◮ Formalism projecting semantic components into vectorial space◮ CV elements correspond to concepts indirectly◮ Overlap of shared ideas between word senses X & Y :
Thematic proximity: Sim(X ,Y ) = cos(X̂ ,Y ) = X ·Y‖X‖×‖Y‖
Angular distance: DA = arccos(Sim(A,B))
Operations on Vectors◮ Normalised Vectorial Sum (⊕): averages operand vectors◮ Vectorial Term-to-Term Product (⊙): highlights common ideas◮ Weak Contextualisation: emphasizes features shared by two terms,
accentuated by each other
γ(X ,Y ) = X ⊕ (X ⊙ Y )
◮ Synonymy: tests thematic closeness of two meanings X and Y , eachenhanced with what it has in common with a third (C)
SynR(X ,Y ,C) = DA (γ(X ,C), γ(Y ,C))
◮ Partial Synonymy: SynR where the context is the sum of contextualisation ofX and Y of their means
SynP(X ,Y ) = SynR(X ,Y , γ(X ,X ⊕ Y )⊕ γ(Y ,X ⊕ Y ))
Construction◮ Can be computed from definitions from different sources (dictionaries,
synonym lists, hand-crafted indices, . . . )◮ Fabricates new CVs from existing CVs→ requires bootstrap kernel of pre-computed CVs
◮ Emergence from randomised vectors (Lafourcade 2006)◮ dimension of the vector space can be chosen freely◮ more constant lexical density in vector space◮ no prior sense-to-concept mapping required◮ requires much more iterations, time and computing resources
◮ We try with ontology-based CVs first
Constructing Ontology-based CV for WordNet Senses
Vector Construction for Ontology Classes◮ 1992 elements (each correspond to class in SUMO/MILO (not all were used)) in CV◮ For each ontology class C, compute V (C) = (v1(C), v2(C), v3(C), . . .)
◮ Initialise V 0(C) with v0i (C) = 1 if vi corresponds to C, 0 otherwise
◮ Then V (C) with vi(C) = v0i (C) +
∑dim(V )j=1
v0j (C)
2dist(C,Cj)
Constructing Ontology-based CV for WordNet Senses (cont.)
Kernel Vectors for WordNet Synsets◮ For each WN sense s, initialise V 0(s) = V (C); C is the SUMO/MILO class
assigned to s (Niles & Pease, 2003)
Learning CVs for WN Senses◮ Iteratively compute V (s) as in (Schwab et al, 2007) but using V 0(s) based
on eXtended WordNet
Comparison with Miller–Charles (M&C) Set
◮ We define two proximity measures based on CV:proxcv(A,B) = 1 −
(DA(A,B)÷ π
2
)
proxsyn(A,B) = 1 −(SynP(A,B)÷ π
2
)
◮ Take highest proxcv and proxsyn values of WN noun senses
Word Pair M&C proxcv proxsynCorr. with M&Cproxcv proxsyn
automobile car 0.98 1.00 1.00 1.000 1.000cord smile 0.03 0.48 0.57 1.000 1.000glass magician 0.03 0.47 0.57 1.000 1.000gem jewel 0.96 1.00 1.00 1.000 1.000rooster voyage 0.02 0.44 0.53 0.999 0.998magician wizard 0.88 0.90 0.92 0.997 0.997bird crane 0.74 0.82 0.86 0.996 0.996crane implement 0.42 0.60 0.68 0.989 0.991noon string 0.02 0.38 0.47 0.988 0.988bird cock 0.76 0.78 0.83 0.983 0.985coast shore 0.93 0.86 0.89 0.980 0.982journey voyage 0.96 0.85 0.88 0.974 0.976midday noon 0.86 1.00 1.00 0.965 0.968furnace stove 0.78 0.70 0.77 0.950 0.956implement tool 0.74 0.67 0.74 0.936 0.944brother lad 0.42 0.47 0.55 0.925 0.930food rooster 0.22 0.34 0.43 0.920 0.921lad wizard 0.11 0.20 0.30 0.915 0.911asylum madhouse 0.90 0.70 0.76 0.901 0.897food fruit 0.77 0.60 0.69 0.885 0.885boy lad 0.94 0.62 0.70 0.856 0.860monk slave 0.14 0.62 0.69 0.837 0.839car journey 0.29 0.71 0.77 0.818 0.818monk oracle 0.28 0.71 0.77 0.800 0.798coast hill 0.22 0.71 0.77 0.777 0.774forest graveyard 0.21 0.81 0.85 0.735 0.731coast forest 0.11 0.70 0.77 0.711 0.704brother monk 0.71 0.34 0.43 0.644 0.634
Corr. with M&C 0.644 0.634
Discussion
Results are not too impressive. . .
Suitability of WN–SUMO/MILO mappings◮ ֒brother֓–֒monk֓ scored too low because mapped to very different classes
(HUMAN and RELIGIOUSORGANISATION)◮ ֒coast֓–֒hill֓, ֒forest֓–֒graveyard֓ and ֒coast֓–֒forest֓ considered dissimilar
by humans, but all LANDAREA in mapping◮ (Take these away and correlations with M&C rise to 0.800 and 0.798)
Suitability of the M&C Set◮ ֒cars֓ and ֒gasoline֓ are semantically related;֒cars֓ and ֒bicycles֓ are semantically similar (Resnik, 1995)
◮ ֒car֓–֒journey֓: low M&C score; high proxcv and proxsyn scores◮ M&C assesses semantic similarity◮ CVs (via proxcv and proxsyn) assesses semantic relatedness
Conclusion
◮ CVs can model the ideas conveyed by lexical meanings◮ Can be constructed based on ontological sources◮ Can be used to measure lexical semantic relatedness◮ Disadvantage of ontology-based CVs:
◮ non-standard density of the hierarchy◮ different philosophies in mapping lexical senses to ontology classes
Future Work◮ Effects of hierarchy-free CVs i.e. construction by emergence◮ Collect human ratings on lexical semantic relatedness as benchmark
[email protected] Computer-aided Translation Unit, School of Computer Sciences, University Sains Malaysia http://[email protected] GETALP-LIG, Laboratoire d’Informatique de Grenoble, Université Pierre Mendès France http://getalp.imag.fr
Lim Lian Tze | mosc 2011 23 / 48
Introduction Document Types Special Material Wrapping Up
LeaWets
leaflet: arrange contents into 6 pages on a foldable double-sided sheet
\documentclass[foldmark,a4paper]{leaflet}\author ... % Meta−information
\begin{document}\maketitle\section ...... % LeaWet contents\end{document}
Discussion
▸ Low thresholds (α, β): more coverage; low precision▸ High thresholds: good precision; low coverage▸ α ≈ 0.6, β ≈ 0.2 gives good trade-o� between coverage,precision and recall▸ Results are encouraging for such simple input data!Especially suitable for under-resourced language pairs▸ Future plan: Integrate multilingual lexicon into anMT
system withWSD and user interaction features
Related Work
▸ Many multilingual lexicon projects [2, 3]) aligned withPrinceton WordNet [4]⊳ Overly �ne sense distinctions in Princeton WordNet▸ Pan Lexicon [5]: compute context vectors of words frommonolingual corpora of di�erent languages, thengrouping into translation sets by matching contextvectors via bilingual lexicons⊳ Sense distinctions derived from corpus evidence⊳ Produces many translation sets that contain
semantically related but not synonymous words,e.g. ‘shoot’ and ‘bullet’ (lower precision)⊳ 44% precision based on evaluators’ opinions (75% ifinter-evaluator agreement is not required)⊳ Does not handle multi-word expressions▸ Markó, Schulz and Hahn [6] use cognate mappings to
derive new translation pairs, validate by processingparallel corpora (medical domain)⊳ Complex terms indexed on the level of sub-words
e.g. ‘pseudo⊕hypo⊕para⊕thyroid⊕ism’⊳ 46% accuracy for each language pair⊳ Requires large aligned thesaurus corpora (easier toacquire for specialised domains?)⊳ Cognate-based approach not applicable for languagepairs that are not closely related▸ Lafourcade [7]: compute contextual vectors for
translation pairs based on gloss text and associated classlabels from semantic hierarchy; compare vectors fromdi�erent bilingual lexicons to detect synonymy⊳ Resource requirements not available for all language
pairs, costly task of assigning class labels
References[1] F. Bond and K. Ogura. “Combining linguistic resources to
create a machine-tractable Japanese–Malay dictionary”. In:Language Resources and Evaluation 42 (2008), pp. 127–136.
[2] P. Vossen. “EuroWordNet: A Multilingual Database ofAutonomous and Language-speci�c Wordnets Connected viaan Inter-Lingual-Index”. In: Special Issue on Multilingual
Databases, International Journal of Linguistics 17.2 (2004).
[3] D. Tu�ş, D. Cristeau, and S. Stamou. “BalkaNet: Aims,Methods, Results and Perspectives – A General Overview”.In: Romanian Journal of Information Science and Technology
Special Issue 7.1 (2004), pp. 9–43.
[4] C. Fellbaum, ed.WordNet: An Electronic Lexical Database.Language, Speech, and Communication. Cambridge,Massachusetts: MIT Press, 1998.
[5] M. Sammer and S. Soderland. “Building asense-distinguished multilingual lexicon from monolingualcorpora and bilingual lexicons”. In: Proceedings of Machine
Translation Summit XI. Copenhagen, Denmark, 2007,pp. 399–406.
[6] K. Markó, S. Schulz, and U. Hahn. “Multilingual LexicalAcquisition by Bootstrapping Cognate Seed Lexicons”. In:Proceedings of the International Conference on Recent
Advances in Natural Language Processing (RANLP) 2005.Borovets, Bulgaria, 2005.
[7] M. Lafourcade. “Automatically Populating Acception LexicalDatabase through Bilingual Dictionaries and ConceptualVectors”. In: Proceedings of PAPILLON-2002. Tokyo, Japan,Aug. 2002.
[8] C. Boitet, M. Mangeot, and G. Sérasset. “�e PAPILLONproject: Cooperatively Building a Multilingual LexicalDatabase to Derive Open Source Dictionaries & Lexicons”.In: Proceedings of the 2nd Workshop on NLP and XML
(NLPXML’02). Taipei, Taiwan, 2002, pp. 1–3.
Contact
Lian Tze Lim [email protected] Ranaivo-Malançon [email protected] Kong Tang [email protected]
NLP-SIG, Faculty of Information TechnologyMultimedia University, Cyberjaya, Malaysia.http://fit.mmu.edu.my/sig/nlp/
Low-Cost Construction of aMultilingual Lexicon from
Bilingual Lists
Lian Tze LimBali Ranaivo-Malançon
Enya Kong Tang
NLP-SIG, Faculty of Information TechnologyMultimedia University, Malaysia
Introduction
▸ BilingualMRDs are good resources for buildingmultilingual lexicons▸ ButMRDs have heterogeneous contents and structures⊳ Not all contain rich information (gloss, domain)
(Especially so for under-resourced languages)⊳ Di�erent structures (sense granularity, distinctions)▸ Lowest common denominator: list of source languageitem→ target language item(s)▸ Construct multilingual lexicon using only bilingual lists
One-time Inverse Consultation [1]
▸ Generates a bilingual lexicon for a new language pairfrom existing bilingual lists▸ Given bilingual lexicons L1–L2, L2–L3, L3–L2, generatebilingual lexicon L1–L3▸ Example: JP–EN, EN–MS, MS–EN lexicons⇒ JP–MS
Japanese English Malay
mark tandap seal anjing laut
stamp teraimprintgauge
score(‘tera’) = 2 × ∣E1 ∩E2∣∣E1∣ + ∣E2∣ = 2 × 2
3 + 4 = 0.57∴�p�↔ ‘tera’ is more likely to be valid
Merging Translation Triples into Sets
▸ Retain OTIC ‘middle’ language links▸ For each ‘head’ language LI, �lter only triples whosescore exceed thresholds (See Algorithm 1)▸ Merge all triples with common bilingual pairs▸ Malay–English–Chinese example:ms–en Kamus Inggeris–Melayu untuk Penterjemahen–zh XDict zh–en CC-CEDICT
(garang, ferocious, ö�)(garang, �erce, ö�)
(garang, ööö���) 0.143
(garang, jazzy, ÀÈ)
(garang, ÀÀÀÈÈÈ) 0.125
(garang, bold, 'Æ)
(garang, '''ÆÆÆ) 0.111
(garang, bold, ÑS)
(garang, ÑÑÑSSS) 0.048
(garang, bold, �S)
(garang, ���SSS) 0.048
⋮
garang
bengkeng
�erce
ferocious ö�
Ð→(garang, ferocious,ö�)(garang, �erce,ö�)(bengkeng, �erce,ö�)
Adding More Languages
▸ Construct L1–L2–L4 triples▸ Add L4 members to existing L1–L2–L3 clusters withcommon L1 & L2 members▸ Example: Malay–English–Chinese + French, using‘ready-made’ triples from FeM
garang
bengkeng
�erce
ferocious ö�
+(cruel, ferocious, garang)(féroce, �erce, garang)Ð→
garang
cruelféroce
bengkeng
�erce
ferocious ö�
Algorithm 1: Generating trilingual translation chains
forall the lexical items wh ∈ L1 do
Wm ← translations of wh in L2
forall the wm ∈Wm do
Wt ← translations of wm in L3
forall the wt ∈Wt do
Output a translation triple (wh ,wm ,wt)Wmr
← translations of wt in L2
score(wh ,wm ,wt) ←∑
w∈Wm
∣common words in wmr∈Wmr
and w|∣words in wmr∈Wmr
∣end
score(wh ,wt) ← 2 × ∑w∈Wmscore(wh ,w ,wt)∣Wm ∣ + ∣Wmr
∣end
X ←maxw t∈Wtscore(wh ,wt)
forall the distinct translation pairs (wh ,wt) doif score(wh ,wt) ≥ αX or (score(wh ,wt))2 ≥ βXthen
Place wh ∈ L1, wm ∈ L2, wt ∈ L3 from all triples(wh ,w . . . ,wt) into same translation setRecord score(wh ,wt) and score(wh ,wm ,wt)
else
Discard all triples (wh ,w . . . ,wt)// The sets are now grouped by(wh ,wt)
end
end
end
Merge all sets containing triples with same (wh ,wm)Merge all sets containing triples with same (wm ,wt)
Algorithm 2: Adding Lk+1 to multilingual lexicon L of{L1 , L2 , . . . , Lk}T ← translation triples of Lk+1 , Lm , Ln generated byAlgorithm 1 where Lm , Ln ∈ {L1 , L2 , . . . , Lk}forall the (wLm
,wLn,wLk+1) ∈ T do
Add wLk+1 to all entries in L that contains both wLmand
wLn
end
Precision of 100 Random Translation Sets
0 0.2 0.4 0.6 0.8
0.7
0.75
0.8
0.85
β
Precision
α = 0.0α = 0.2α = 0.8
▸ Precision increases with threshold parameters α and β▸ Precision generally around 0.70–0.82; max 0.86▸ Most false positives are not ranked at top of the list▸ Many errors caused by incorrect POS assignments
F1 and Rand Index of Selected Translation Sets
▸ False positives will frequently arise when ‘middle’language members are polysemous, e.g. ‘plant’, ‘target’▸ Evaluate accuracy of selected sets with polysemous‘middle’ language members
Precision = TP
TP + FPRecall = TP
TP + FNF1 = 2 × Precision × Recall
Precision + RecallRI = TP + TN
TP + FP + FN + TNTest Rand Index F1 Best accuracy whenword min max min max α β
‘bank’ 0.417 0.611 0.588 0.632 0.6 0.4‘plant’ 0.818 0.927 0.809 0.913 0.6 0.2‘target’ 0.821 1.000 0.902 1.000 0.4 0.2‘letter’ 0.709 0.818 0.724 0.792 0.8 0.2
▸ F1 and RI increases with α and β▸ But may decrease when they are too high and rejectvalid members (false negatives)
Lim Lian Tze | mosc 2011 24 / 48
Introduction Document Types Special Material Wrapping Up
Fillable PDF Forms
\usepackage{hyperref}
... % various settings skipped
\TextField{Name:}\\
\TextField{Affiliation:}\\
\ChoiceMenu[radio=true]
{Are you a:}{Student, Academic}\\
Interest:
\CheckBox{Security}
\CheckBox{Systems}
\CheckBox{User space}\\
\TextField[multiline=true]
{Comments:}\\
Lim Lian Tze | mosc 2011 25 / 48
Introduction Document Types Special Material Wrapping Up
Fillable PDF Forms (cont’d)
Use with caution!poppler-based viewers (evince, xpdf, okular)
Problem displaying and saving radio/check boxes correctlySaved forms can’t be opened by other viewers
Adobe ReaderCannot save Vlled form as PDF unless Acrobat is installedOnly as Veld-and-value text VleCan provide “Submit” button for submission to a URL
Or print hard copy of Vlled form!
PDF XChange ViewerBest freeware for Vlling and saving LATEX-created formsWindows onlyNot OSS
Lim Lian Tze | mosc 2011 26 / 48
Introduction Document Types Special Material Wrapping Up
Flash Cards
\documentclass[avery5388,frame]
{flashcards}
\cardfrontstyle{headings}
\cardfrontfoot{Linux}
\begin{document}
\begin{flashcard}[Security]
{Certificate}
...
\end{flashcard}
\begin{flashcard}[Security]
{MAC ...}
...
\end{flashcard}
\end{document}
Security
CertiVcate
Linux
Security
MAC (Mandatory AccessControl)
Linux
A digital representation of information thatidentiVes you and is issued by Cas, which are
often a trusted third party (TTP).
Access to an object is restricted based on thesensitivity of the object (deVned by the label
that is assigned), and granted throughauthorization (Clearance) to access that level of
data.
Lim Lian Tze | mosc 2011 27 / 48
Introduction Document Types Special Material Wrapping Up
Examination Questions
\documentclass{exam}...\begin{questions}\printanswers\question[5]What is Paul McCartney's middle name?\begin{oneparchoices}\choice John \CorrectChoice Paul\choice Ringo \choice James\end{oneparchoices}
\question[10] What was the Beatles' first˓→single in 1962?\begin{solution}Love Me Do\end{solution}
\question\begin{parts}\part[5] What was George's inspiration for˓→`While My Guitar Gently Weeps'?\begin{solution}He opened a random book and saw the words˓→``gently weep''.\end{solution}...\end{questions}
1. (5)What is Paul McCartney’s middle name?
A. John B. Paul C. Ringo D. James
2. (10)What was the Beatles’ Vrst single in 1962?
3. (a) (5)What was George’s inspiration for ‘WhileMy Guitar Gently Weeps’?
(b) (5)Who guest-performed for the song and why?
1. (5)What is Paul McCartney’s middle name?
A. John B. Paul C. Ringo D. James
2. (10)What was the Beatles’ Vrst single in 1962?
Solution: Love Me Do
3. (a) (5)What was George’s inspiration for ‘WhileMy Guitar Gently Weeps’?
Solution: He opened a random bookand saw the words “gently weep”.
(b) (5)Who guest-performed for the song and why?
Solution: Eric Clapton; he wanted aspiUy guitar solo.
Lim Lian Tze | mosc 2011 28 / 48
Introduction Document Types Special Material Wrapping Up
Contents
1 What are TEX, LATEX and Friends?
2 Document Types
3 Special Material
4 Wrapping Up
Lim Lian Tze | mosc 2011 29 / 48
Introduction Document Types Special Material Wrapping Up
Mathematics
(1) relates the golden ratio and the Fibonacci series.Recall that the golden ratio, 𝜑 = 1
2(1+√5).
𝜑 = 1+∞∑︁
n=1
(−1)n+1
FnFn+1(1)
\eqref{eq:gratio} relates the golden ratio and the Fibonacci series.
Recall that the golden ratio, $\phi = \frac{1}{2} (1 + \sqrt{5})$.
\begin{equation}\label{eq:gratio}
\phi = 1 + \sum^{\infty} _{n=1}
\frac{ (-1)^{n+1} }{ F_n F_{n+1} }
\end{equation}
Lim Lian Tze | mosc 2011 30 / 48
Introduction Document Types Special Material Wrapping Up
Chemical Equations and Molecules
Zn2++2OH–
−−−−⇀↽−−−−+2H+
Zn(OH)2 ↓amphoteres Hydroxid
+2OH–
−−−−⇀↽−−−−+2H+
[Zn(OH)4]2–
Hydroxozikat
H C
H
H
C
H
O
\usepackage[version=3]{mhchem} % suXcient for chemical equations
\usepackage{chemfig} % for 2−D molecule drawings
...
\ce{Zn^2+ <=>[\ce{+ 2OH-}][\ce{+ 2H+}]
$\underset{\text{amphoteres Hydroxid}}{\ce{Zn(OH)2 v}}$
<=> C[+2OH-][{+ 2H+}]
$\underset{\text{Hydroxozikat}}{\cf{[Zn(OH)4]^2-}}$ }
\chemfig{H-C(-[2]H)(-[6]H)-C(-[7]H)=[1]O}
Lim Lian Tze | mosc 2011 31 / 48
Introduction Document Types Special Material Wrapping Up
Linguistics
(1) %*WenWhom
liebtloves
seinehis
Mutter?mother
‘Who does his mother love?’
(2) [[NP He ] [VP kicked [NP the ball ]]]S
S
NP
Pron
He
VP
V
kicked
NP
Det
the
N
ball
\usepackage{linguex,qtree}...\exg. \%*Wen liebt seine Mutter?\\Whom loves his mother\\`Who does his mother love?'
\exi. [[NP He ] [VP kicked [NP the ball ]]]S
\Tree [ .S [.NP [.Pron He ] ] [.VP [.V kicked ] [.NP [.Det the ] [.N ball ]˓→ ] ] ]
Lim Lian Tze | mosc 2011 32 / 48
Introduction Document Types Special Material Wrapping Up
Program Listings
\usepackage{listings,xcolor}
...
\begin{lstlisting}
[language=C,columns=fullflexible,
basicstyle=\ttfamily,
keywordstyle=\bfseries\color{red},
commentstyle=\sffamily\color{green},
stringstyle=\rmfamily\color{orange}]
#include <stdio.h>
/*| Prints "hello world"
*/
int main(void)
{
printf("hello, world\n");
return 0;
}
\end{lstlisting}
#include <stdio.h>
/∗| Prints "hello world"∗/int main(void){
printf("hello, world\n");return 0;
}
Lim Lian Tze | mosc 2011 33 / 48
Introduction Document Types Special Material Wrapping Up
Network Protocols
\usepackage{bytefield}
...
\begin{bytefield}{16}
\bitheader{0,7,8,15} \\
\wordgroupr{Header}
\bitbox{4}{Tag} & \bitbox{12}{Mask} \\
\bitbox{8}{Source} &
\bitbox{8}{Destination}
\endwordgroupr \\
\wordbox{3}{Data}
\end{bytefield}
0 7 8 15
Tag Mask
Source Destination
}︃Header
Data
Lim Lian Tze | mosc 2011 34 / 48
Introduction Document Types Special Material Wrapping Up
Life Sciences
Vrst case (see text)↓
AQP1.PRO TLGLLLSCQISILRAVMYIIAQCVGAIVASAIL 112AQP2.PRO TVACLVGCHVSFLRAAFYVAAQLLGAVAGAAIL 104AQP3.PRO TFAMCFLAREPWIKLPIYTLAQTLGAFLGAGIV 112AQP4.PRO TVAMVCTRKISIAKSVFYITAQCLGAIIGAGIL 133AQP5.PRO TLALLIGNQISLLRAVFYVAAQLVGAIAGAGIL 105
↑second case (see text)
\usepackage{texshade} % for nucleotide and peptide alignments...\begin{texshade}{AQPpro.MSF}\shadingmode{similar}\threshold[80]{50}\setends{1}{80..112}\hideconsensus\feature{top}{1}{93..93}{fill:$\downarrow$}{first case (see text)}\feature{bottom}{1}{98..98}{fill:$\uparrow$}{second case (see text)}\end{texshade}
Lim Lian Tze | mosc 2011 35 / 48
Introduction Document Types Special Material Wrapping Up
Circuits and SI Units
B
20Ω
10Ω
vxS5vx5Ω
A
3.45× 104 V2 lm3 F−1
40 km/h, 85 km/h and 103 km/h
\usepackage{siunitx}\usepackage[siunitx]{circuitikz}...\begin{circuitikz}\draw (0,0) node[anchor=east] {B}to[short, o-*] (1,0) to[R=20<\ohm>, *-*] (1,2)to[R=10<\ohm>, v=$v_x$] (3,2) -- (4,2)to[ cI=$\frac{\si{\siemens}}{5} v_x$, *-*] (4,0) -- (3,0)to[R=5<\ohm>, *-*] (3,2)(3,0) -- (1,0) (1,2) to[short, -o] (0,2) node[anchor=east]{A}
;\end{circuitikz}
\SI{3.45d4}{\square\volt\cubic\lumen\per\farad}\SIlist[per-mode=symbol]{40;85;103}{\kilo\metre\per\hour}
Lim Lian Tze | mosc 2011 36 / 48
Introduction Document Types Special Material Wrapping Up
Meh, What Good is That? Can’t Use it Anywhere Else.
Actually, you can.
\usepackage[active,tightpage]{preview}
\PreviewEnvironment{texshade}
...
\begin{texshade}
...
\end{texshade}
Run pdflatex → cropped PDF containing only contents of texshade
gs -otexshade.png -sDEVICE=png16m -r200 -dTextAlphaBits=4
-dGraphicAlphaBits=4 texshade.pdf
Multiple environments → multi-page PDF
Use -otexshade%02d.png to get texshade01.png, texshade02.png, . . .
Lim Lian Tze | mosc 2011 37 / 48
Introduction Document Types Special Material Wrapping Up
Bar Codes
9 781860 742712 9 783865 411143
ISBN 978-3-86541-114-3
L E 2 8 H S 9 Z
\usepackage{auto-pst-pdf} % Needed if running pdWatex; must use option−shell−escape
\usepackage{pstricks,pst-barcode}
...
\begin{pspicture}
\psbarcode{MECARD:N:Malaysia Open Source Conference...}{eclevel=L}{qrcode}
\psbarcode{9781860742712}{includetext guardwhitespace}{ean13}
\psbarcode{978-3-86541-114}{includetext guardwhitespace}{isbn}
\psbarcode{LE28HS9Z}{includetext}{royalmail}
\psbarcode{^453^178^121^239}{columns=2 rows=10}{pdf417}
\end{pspicture}
Lim Lian Tze | mosc 2011 38 / 48
Introduction Document Types Special Material Wrapping Up
Graph Plots
101 102 103 104
10−5
10−4
10−3
10−2
10−1
Dof
L2Lmax
\usepackage{pgfplots}...\begin{tikzpicture}\begin{loglogaxis}[xlabel=Dof]\addplot table[x=dof,y=L2]{datafile.dat}; \addlegendentry{$L_2$};\addplot table[x=dof,y=Lmax]{datafile.dat}; \addlegendentry{$L_\text{max}$};\end{loglogaxis}\end{tikzpicture}
Lim Lian Tze | mosc 2011 39 / 48
Introduction Document Types Special Material Wrapping Up
Spreadsheets(Seriously, use a proper spreadsheet application for complex stuU.)
Year ending Mar 31 2009 2008 2007
Revenue 14580.20 11900.40 8290.30Cost of sales 6740.20 5650.10 4524.20
Gross proVt 7840.00 6250.30 3766.10
\STautoround*{2}
\begin{spreadtab}{{tabular}{l rrr}}
@Year ending Mar 31 & @2009 & @2008 & @2007\\ \hline
@Revenue & 14580.2 & 11900.4 & 8290.3\\
@Cost of sales & 6740.2 & 5650.1 & 4524.2\\ \cline{2-4}
@\emph{Gross profit} & \STcopy{>}{b2-b3} & &\\ \cline{2-4}
\end{spreadtab}
Lim Lian Tze | mosc 2011 40 / 48
Introduction Document Types Special Material Wrapping Up
Gantt Charts2010 2011
Preliminary Project 100% complete
Objective 1Task ATask B
Objective 2Task ATask B
\usepackage{pgfgantt}...\begin{tikzpicture}\begin{ganttchart}[...settings...]{16}\gantttitle{2010}{4} \gantttitle{2011}{12} \\\ganttbar[progress=100]{Preliminary Project}{1}{4} \\\ganttlink[link mid=.4]{4}{2}{5}{4} \ganttlink[link mid=.159]{4}{2}{5}{7}\ganttgroup{Objective 1}{5}{16} \\\ganttbar[progress=4]{Task A}{5}{10} \\\ganttlinkedbar[progress=0]{Task B}{11}{16} \\...\end{ganttchart}\end{tikzpicture}
Lim Lian Tze | mosc 2011 41 / 48
Introduction Document Types Special Material Wrapping Up
Chess games
\usepackage[skaknew]%
{skak,chessboard}
...
\newgame
\mainline{1. e4 e5 2. Nf3 Nc6 3.
→˓Bb5 a6}
\chessboard[smallboard]
1 e4 e5 2 Nf3 Nc6 3 Bb5 a6
8 rZblkans7 ZpopZpop6 pZnZ0Z0Z5 ZBZ0o0Z04 0Z0ZPZ0Z3 Z0Z0ZNZ02 POPO0OPO1 SNAQJ0ZR
a b c d e f g h�
Lim Lian Tze | mosc 2011 42 / 48
Introduction Document Types Special Material Wrapping Up
Crossword Puzzles
1
2 3 4
5
Across: 1 unit of measure2 * 5 sectioning unit
Down: 1 𝜂 3 unit ofmeasure 4 nonproportionalfont
\usepackage{cwpuzzle}
...
\begin{Puzzle}{5}{3}
|* |* |[1]E|X |* |.
|[2]A|[3]S|T |* |[4]T|.
|* |[5]P|A |R |T |.
\end{Puzzle}
\begin{PuzzleClues}{
\textbf{Across:} }
\Clue{1}{EX}{unit of measure}
\Clue{2}{AST}{\(\ast\)}
\Clue{5}{PART}{sectioning unit}
\end{PuzzleClues}
\begin{PuzzleClues}{
\textbf{Down:} }
\Clue{1}{ETA}{\(\eta\)}
\Clue{3}{SP}{unit of measure}
\Clue{4}{TT}{nonproportional font}
\end{PuzzleClues}
Lim Lian Tze | mosc 2011 43 / 48
Introduction Document Types Special Material Wrapping Up
Song Books with Guitar Tabs
CountryC
road, take meG
home, to theAmplace I be
Flong.
West VirC
ginia, mountainG
momma, take meF
home, countryC
road.
\usepackage{gchords,guitar}
...
\begin{guitar}
\newcommand{\CMaj}{\chord{t}{n,p3,p2,n,p1,n}{C}}
\newcommand{\Amin}...
Country [\CMaj]road, take me [\GMaj]home, ...
\end{guitar}
Lim Lian Tze | mosc 2011 44 / 48
Introduction Document Types Special Material Wrapping Up
Contents
1 What are TEX, LATEX and Friends?
2 Document Types
3 Special Material
4 Wrapping Up
Lim Lian Tze | mosc 2011 45 / 48
Introduction Document Types Special Material Wrapping Up
Summary
LATEXa document preparation systemprofessional quality typesetting output
Output artefactsAcademic: papers, theses, booksDedicated document typesDomain-speciVc material
Usage scenarioDirect authoringAutomatic generation (via scripts etc)As back-end of other applications
Lim Lian Tze | mosc 2011 46 / 48
Introduction Document Types Special Material Wrapping Up
Getting Help
Many free tutorials and e-books on the Web (beware of obsolete ones!)Getting to Grips with LATEX. Andy Roberts.http://www.andy-roberts.net/misc/latex/
LATEX: Beautiful Typesetting. Lim Lian Tze.http://liantze.penguinattack.org/latextypesetting.html
LATEX and Friends. M.R.C. van Dongen.http://csweb.ucc.ie/~dongen/LaTeX-and-Friends.pdf
The LATEX WikiBook. http://en.wikibooks.org/wiki/LaTeX
Questions?TEX FAQ. http://www.tex.ac.uk/cgi-bin/texfaq2html
TEX.SX. http://tex.stackexchange.com/
comp.text.tex usenet groupMalaysian LATEX User Group. http://latex-my.blogspot.com/
Arrange for training
Lim Lian Tze | mosc 2011 47 / 48
Introduction Document Types Special Material Wrapping Up
Thank You
http://latex-my.blogspot.com
Lim Lian Tze | mosc 2011 48 / 48