├── .gitignore ├── .gitmodules ├── README.md ├── Sem1 ├── ArtificialIntelligence │ ├── Heuristic Search Overview │ │ ├── heuristicsearch.tex │ │ └── readme.md │ └── Samenvatting Midas │ │ ├── README.md │ │ └── Samenvatting.tex ├── BesturingsSystemen │ ├── Database Begrippen │ │ ├── bs_db.csv │ │ └── bs_py.py │ ├── README.md │ ├── Samenvatting Hanne │ │ ├── samenvattingBS.tex │ │ └── samenvattingBS_ra.tex │ ├── Samenvatting Jérôme │ │ ├── Chapter-10-File-System.docx │ │ └── Chapter-14-System-protection.docx │ ├── Samenvatting Kiefer │ │ ├── OSdeel01.jpg │ │ ├── OSdeel02.jpg │ │ ├── OSdeel03.jpg │ │ ├── OSdeel04.jpg │ │ ├── OSdeel05.jpg │ │ ├── OSdeel06.jpg │ │ ├── OSdeel07.jpg │ │ ├── OSdeel08.jpg │ │ ├── OSdeel09.jpg │ │ ├── OSdeel10.jpg │ │ ├── OSdeel11.jpg │ │ ├── OSdeel12.jpg │ │ ├── OSdeel13.jpg │ │ ├── OSdeel14.jpg │ │ ├── OSdeel15.jpg │ │ ├── OSdeel16.jpg │ │ ├── OSdeel17.jpg │ │ ├── OSdeel18.jpg │ │ ├── OSdeel19.jpg │ │ ├── OSdeel20.jpg │ │ ├── OSdeel21.jpg │ │ ├── OSdeel22.jpg │ │ ├── OSdeel23.jpg │ │ ├── OSdeel24.jpg │ │ ├── OSdeel25.jpg │ │ ├── OSdeel26.jpg │ │ ├── OSdeel27.jpg │ │ ├── OSdeel28.jpg │ │ ├── OSdeel29.jpg │ │ ├── OSdeel30.jpg │ │ ├── OSdeel31.jpg │ │ ├── OSdeel32.jpg │ │ ├── OSdeel33.jpg │ │ ├── OSdeel34.jpg │ │ ├── OSdeel35.jpg │ │ ├── OSdeel36.jpg │ │ └── OSdeel37.jpg │ └── Samenvatting Midas │ │ └── BesturingsSystemen.tex ├── LineaireAlgebra │ ├── .gitignore │ ├── Notities Hanne │ │ ├── Week 8 │ │ │ ├── week 8 pagina 1.jpg │ │ │ ├── week 8 pagina 2.jpg │ │ │ ├── week 8 pagina 3.jpg │ │ │ ├── week 8 pagina 4.jpg │ │ │ ├── week 8 pagina 5.jpg │ │ │ ├── week 8 pagina 6.jpg │ │ │ ├── week 8 pagina 7.jpg │ │ │ └── week 8 pagina 8.jpg │ │ ├── Week10 │ │ │ ├── week 10 pagina 1.jpg │ │ │ ├── week 10 pagina 2.jpg │ │ │ ├── week 10 pagina 3.jpg │ │ │ ├── week 10 pagina 4.jpg │ │ │ ├── week 10 pagina 5.jpg │ │ │ └── week 10 pagina 6.jpg │ │ ├── Week12 │ │ │ ├── week 12 pagina 1.jpg │ │ │ ├── week 12 pagina 2.jpg │ │ │ ├── week 12 pagina 3.jpg │ │ │ ├── week 12 pagina 4.jpg │ │ │ ├── week 12 pagina 5.jpg │ │ │ └── week 12 pagina 6.jpg │ │ ├── Week13 │ │ │ ├── week 13 pagina 1.jpg │ │ │ ├── week 13 pagina 2.jpg │ │ │ ├── week 13 pagina 3.jpg │ │ │ ├── week 13 pagina 4.jpg │ │ │ ├── week 13 pagina 5.jpg │ │ │ └── week 13 pagina 6.jpg │ │ ├── Week6 │ │ │ ├── 1.jpg │ │ │ ├── 2.jpg │ │ │ ├── 3.jpg │ │ │ ├── 4.jpg │ │ │ ├── 5.jpg │ │ │ ├── 6.jpg │ │ │ ├── 7.jpg │ │ │ └── 8.jpg │ │ ├── Week7 │ │ │ ├── 1.jpg │ │ │ ├── 2.jpg │ │ │ ├── 3.jpg │ │ │ ├── 4.jpg │ │ │ ├── 5.jpg │ │ │ ├── 6.jpg │ │ │ └── 7.jpg │ │ └── Week9 │ │ │ ├── week 9 pagina 1.jpg │ │ │ ├── week 9 pagina 2.jpg │ │ │ ├── week 9 pagina 3.jpg │ │ │ ├── week 9 pagina 4.jpg │ │ │ ├── week 9 pagina 5.jpg │ │ │ └── week 9 pagina 6.jpg │ └── samenvattingJonasMichael.txt ├── MinorBusinessAndInnovation │ ├── .gitignore │ └── Principles of Economics for Scientists │ │ ├── Assignment sessions Information and Innovation │ │ └── Assignment session 2 │ │ │ ├── PES page 1.jpg │ │ │ ├── PES page 2.jpg │ │ │ ├── PES page 3.jpg │ │ │ ├── PES page 4.jpg │ │ │ ├── PES page 5.jpg │ │ │ └── PES page 6.jpg │ │ ├── README.md │ │ └── Summary and course notes document │ │ ├── BerninoSansOffc-Bold.otf │ │ ├── BerninoSansOffc.otf │ │ ├── BerninoSansOffcBold.otf │ │ ├── BerninoSansOffcBoldIt.otf │ │ ├── BerninoSansOffcExb.otf │ │ ├── BerninoSansOffcExbIt.otf │ │ ├── BerninoSansOffcIt.otf │ │ ├── BerninoSansOffcLt.otf │ │ ├── BerninoSansOffcLtIt.otf │ │ ├── BerninoSansOffcSb.otf │ │ ├── BerninoSansOffcSbIt.otf │ │ ├── ConsumptionExternalities.png │ │ ├── ElasticityTable.png │ │ ├── EquilibriumShortageSurplus.png │ │ ├── Externalities.png │ │ ├── OpenDyslexic-Regular.otf │ │ ├── PigouvianTax.png │ │ ├── PriceCeiling.png │ │ ├── PriceFloor.png │ │ ├── Taxation.png │ │ ├── consumersurplus.png │ │ ├── economics.tex │ │ ├── freight-text-bold.otf │ │ ├── freight-text-book.ttf │ │ ├── freight-text-italic.otf │ │ ├── monopoly2prices.png │ │ ├── monopoly_profit.png │ │ ├── perfect_price_discrimination.png │ │ ├── price_increase_quantity_increase.png │ │ ├── pricesupply.png │ │ ├── pricesupplyprofit.png │ │ ├── substitution_effect.png │ │ ├── utility.png │ │ └── utility_drs_cr.jpg ├── MinorVerbreding │ └── KeuzeDeelBedrijfsEconomie │ │ ├── .gitignore │ │ ├── BusinessInformationSystems │ │ ├── Notities Ekonomika │ │ │ └── notas-Marchal2.docx │ │ ├── Notities Mathias │ │ │ ├── Les 1 - Information systems.docx │ │ │ ├── Les 1 - Information systems.tex │ │ │ ├── Les 2 - Information systems part 2.docx │ │ │ ├── Les 2 - Information systems part 2.tex │ │ │ ├── Les 3 - Information systems part 3.docx │ │ │ └── Les 3 - Information systems part 3.tex │ │ ├── Notities Midas │ │ │ ├── .gitignore │ │ │ ├── BIS.tex │ │ │ └── Keywords.tex │ │ └── README.md │ │ └── LineaireOptimalisatie │ │ ├── Oefeningen │ │ └── H3 │ │ │ ├── 3.2.mod │ │ │ ├── 3.21.dat │ │ │ ├── 3.21.mod │ │ │ ├── 3.21.xlsx │ │ │ ├── 3.3.mod │ │ │ ├── 3.5.dat │ │ │ ├── 3.5.mod │ │ │ ├── 3.5.xlsx │ │ │ ├── 3.7.dat │ │ │ └── 3.7.mod │ │ └── Samenvatting Midas │ │ └── SuperSummary.tex └── StatistiekEnWetenschap │ ├── Project │ └── Titlepage.tex │ └── Samenvatting Kevin │ ├── README.md │ ├── images │ └── boxplot.png │ ├── samenvatting.tex │ └── voorblad.tex └── Sem2 ├── Gegevensbanken ├── Oefenzittingen │ ├── Oefenzitting5 │ │ ├── Oefeningen │ │ │ ├── Oef1.tex │ │ │ ├── Oef2.tex │ │ │ └── Oef3.tex │ │ └── Oefenzitting5.tex │ ├── oefenzitting 3.sql │ └── oefenzitting4.sql ├── Project │ ├── README.md │ ├── bottom.tpl.php │ └── top.tpl.php └── samenvatting_gegevensbanken.txt ├── Marketing Engineering ├── Groei berekene case prijs.docx ├── Perceptual Map in STATA.pptx └── les 25-03-16.docx ├── MinorVerbreding └── Economie │ └── samenvatting_economie_JonasSoenen.txt ├── Natuurkunde voor informatica II; Magnetisme ├── Oefenzitting 4 │ ├── Oefeningen │ │ ├── Oef1.tex │ │ ├── Oef2.tex │ │ └── Oef3.tex │ └── Oefenzitting4.tex └── samenvatting_natuurkunde_JonasSoenen.txt ├── NumeriekeWiskunde └── Oefenzittingen │ ├── Oefenzitting 02 │ ├── image1.JPG │ ├── image2.JPG │ ├── image3 (1).JPG │ ├── image4.JPG │ └── image5.JPG │ ├── Oefenzitting 05 │ └── Oefenzitting5.m │ ├── Oefenzitting 06 │ ├── Oefeningen │ │ ├── Oef1.tex │ │ ├── Oef10.tex │ │ ├── Oef2.tex │ │ ├── Oef4.tex │ │ └── Oef5.tex │ └── Oefenzitting6.tex │ ├── Oefenzitting 07 │ └── Oefenzitting7.m │ ├── Oefenzitting 08 │ ├── 1 Functies, function handles en anonieme functies │ │ ├── evalueer_lagrange.m │ │ ├── evalueer_lagrange2.m │ │ ├── f1.m │ │ ├── test_lagrange.m │ │ ├── test_lagrange2.m │ │ └── test_lagrange3.m │ └── 2 De MATLAB debugger │ │ ├── filming_the_rocket.m │ │ └── getrocketposition.m │ ├── Oefenzitting 09 │ ├── Bsplinestelsel.m │ ├── evalBspline.m │ ├── evalspline.m │ ├── oefenzitting9.m │ ├── splinematrix.m │ └── splinestelsel.m │ ├── Oefenzitting 11 │ ├── 20160522_191323_resized_1.jpg │ ├── 20160522_191330_resized_1.jpg │ └── 20160522_191335_resized_1.jpg │ ├── Oefenzitting 12 │ ├── eerste_opgave.zip │ ├── eerste_opgave │ │ └── oefz12 │ │ │ ├── bisection.m │ │ │ ├── comprelerr.m │ │ │ ├── halley.m │ │ │ ├── muller.m │ │ │ ├── newton.m │ │ │ ├── oefz12.m │ │ │ ├── ofactor.m │ │ │ ├── secant.m │ │ │ └── uitleg.txt │ ├── tweede_opgave │ │ ├── Probleem2.asv │ │ ├── Probleem2.m │ │ ├── Uitleg.txt │ │ ├── methode1.asv │ │ ├── methode1.m │ │ ├── methode2.m │ │ ├── methode3.m │ │ └── methode4.m │ ├── vierde_opgave.zip │ └── vierde_opgave │ │ ├── bisect.m │ │ ├── dekker.m │ │ └── secant.m │ └── Oefenzitting 17 │ ├── invmachten.m │ ├── invmachten_adaptief.m │ ├── jacobi.m │ ├── machten.m │ ├── probleem1.m │ └── probleem2.m └── ToepassingenVanMeetkundeInDeInformatica ├── bewijs meetkunde les 2.jpg └── samenvatting_TMI_JonasSoenen.txt /.gitignore: -------------------------------------------------------------------------------- 1 | ##Our own list: 2 | *.pdf 3 | *.tcp 4 | *.tps 5 | *.DS_Store 6 | 7 | 8 | ## Core latex/pdflatex auxiliary files: 9 | *.aux 10 | *.lof 11 | *.log 12 | *.lot 13 | *.fls 14 | *.out 15 | *.toc 16 | *.fmt 17 | *.fot 18 | *.cb 19 | *.cb2 20 | 21 | ## Intermediate documents: 22 | *.dvi 23 | *-converted-to.* 24 | # these rules might exclude image files for figures etc. 25 | # *.ps 26 | # *.eps 27 | # *.pdf 28 | 29 | ## Bibliography auxiliary files (bibtex/biblatex/biber): 30 | *.bbl 31 | *.bcf 32 | *.blg 33 | *-blx.aux 34 | *-blx.bib 35 | *.brf 36 | *.run.xml 37 | 38 | ## Build tool auxiliary files: 39 | *.fdb_latexmk 40 | *.synctex 41 | *.synctex.gz 42 | *.synctex.gz(busy) 43 | *.pdfsync 44 | 45 | ## Auxiliary and intermediate files from other packages: 46 | # algorithms 47 | *.alg 48 | *.loa 49 | 50 | # achemso 51 | acs-*.bib 52 | 53 | # amsthm 54 | *.thm 55 | 56 | # beamer 57 | *.nav 58 | *.snm 59 | *.vrb 60 | 61 | # cprotect 62 | *.cpt 63 | 64 | # fixme 65 | *.lox 66 | 67 | #(r)(e)ledmac/(r)(e)ledpar 68 | *.end 69 | *.?end 70 | *.[1-9] 71 | *.[1-9][0-9] 72 | *.[1-9][0-9][0-9] 73 | *.[1-9]R 74 | *.[1-9][0-9]R 75 | *.[1-9][0-9][0-9]R 76 | *.eledsec[1-9] 77 | *.eledsec[1-9]R 78 | *.eledsec[1-9][0-9] 79 | *.eledsec[1-9][0-9]R 80 | *.eledsec[1-9][0-9][0-9] 81 | *.eledsec[1-9][0-9][0-9]R 82 | 83 | # glossaries 84 | *.acn 85 | *.acr 86 | *.glg 87 | *.glo 88 | *.gls 89 | *.glsdefs 90 | 91 | # gnuplottex 92 | *-gnuplottex-* 93 | 94 | # hyperref 95 | *.brf 96 | 97 | # knitr 98 | *-concordance.tex 99 | # TODO Comment the next line if you want to keep your tikz graphics files 100 | *.tikz 101 | *-tikzDictionary 102 | 103 | # listings 104 | *.lol 105 | 106 | # makeidx 107 | *.idx 108 | *.ilg 109 | *.ind 110 | *.ist 111 | 112 | # minitoc 113 | *.maf 114 | *.mlf 115 | *.mlt 116 | *.mtc 117 | *.mtc[0-9] 118 | *.mtc[1-9][0-9] 119 | 120 | # minted 121 | _minted* 122 | *.pyg 123 | 124 | # morewrites 125 | *.mw 126 | 127 | # mylatexformat 128 | *.fmt 129 | 130 | # nomencl 131 | *.nlo 132 | 133 | # sagetex 134 | *.sagetex.sage 135 | *.sagetex.py 136 | *.sagetex.scmd 137 | 138 | # sympy 139 | *.sout 140 | *.sympy 141 | sympy-plots-for-*.tex/ 142 | 143 | # pdfcomment 144 | *.upa 145 | *.upb 146 | 147 | # pythontex 148 | *.pytxcode 149 | pythontex-files-*/ 150 | 151 | # thmtools 152 | *.loe 153 | 154 | # TikZ & PGF 155 | *.dpth 156 | *.md5 157 | *.auxlock 158 | 159 | # todonotes 160 | *.tdo 161 | 162 | # xindy 163 | *.xdy 164 | 165 | # xypic precompiled matrices 166 | *.xyc 167 | 168 | # endfloat 169 | *.ttt 170 | *.fff 171 | 172 | # Latexian 173 | TSWLatexianTemp* 174 | 175 | ## Editors: 176 | # WinEdt 177 | *.bak 178 | *.sav 179 | 180 | # Texpad 181 | .texpadtmp 182 | 183 | # Kile 184 | *.backup 185 | 186 | # KBibTeX 187 | *~[0-9]* 188 | 189 | 190 | -------------------------------------------------------------------------------- /.gitmodules: -------------------------------------------------------------------------------- 1 | [submodule "Sem1/ArtificialIntelligence/SummaryJO0st"] 2 | path = Sem1/ArtificialIntelligence/SummaryJO0st 3 | url = git://github.com/JO0st/samenvatting_AI.git 4 | [submodule "Sem1/LineaireAlgebra/SamenvattingNorFairKing"] 5 | path = Sem1/LineaireAlgebra/SamenvattingNorFairKing 6 | url = https://github.com/NorfairKing/lineairealgebra.git 7 | [submodule "Gegevensbanken Boeksamenvatting"] 8 | path = Sem2/Gegevensbanken/Boeksamenvatting 9 | url = https://github.com/th0rgall/Databases.git 10 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # 2BachInfo 2 | Collection of summaries for the courses for second bachelor IT at KU Leuven. 3 | # Helping 4 | Feel free to contribute to this repository! 5 | I'm not that good with Latex, so changing some stupid stuff i did is also very welcome. 6 | If you find a mistake, please let us know. 7 | 8 | #Guidelines 9 | * Since we're ICT students, try to use .tex-files as much as possible. 10 | * Please keep everything structured. 11 | * If you contribute, don't forget to add your name to the list (see below). 12 | * Only add pdf's that are not generated from tex files in here, the .gitignore includes .pdf, so if you want to add a .pdf, you must change the .gitignore at the root (other .gitignores are only to make the directory-structure appear on git). 13 | 14 | #How to use the submodules: 15 | If you fork/clone this repository, you will find that the directories for the submodules are empty. To solve this, run "git submodule init" in the submodule directory and then "git submodule update", this will pull all the submodules files onto your computer. 16 | 17 | #Contributions 18 | * [Midas Lambrichts](https://github.com/MidasLamb) 19 | * [Mathias Spanhove](https://github.com/Cptmathix) 20 | * [Joppe Geluykens](https://github.com/joppegeluykens) 21 | * [Hanne Peeters](https://github.com/HannePeeters) 22 | * [Stijn Caerts](https://github.com/StijnCaerts) 23 | * [Kiefer van Bel](https://github.com/Highlordgimli) 24 | * [Thor Galle](https://github.com/th0rgall) 25 | * [Kevin Coorens](https://github.com/coorenskevin) 26 | * [Jonas Soenen](https://github.com/magicalJohn) 27 | 28 | #Other useful links 29 | * [KULeuven-CS repository](https://github.com/KULeuven-CS/kuleuven-cs.github.io) 30 | * [Wina Wiki](https://wiki.wina.be/examens/index.php/Categorie:2bi) 31 | 32 | # Extra stuff 33 | * [A curated list of awesome lists](https://github.com/sindresorhus/awesome) 34 | * [Path to a free self-taught education in Computer Science!](https://github.com/open-source-society/computer-science) 35 | 36 | 37 | -------------------------------------------------------------------------------- /Sem1/ArtificialIntelligence/Heuristic Search Overview/heuristicsearch.tex: -------------------------------------------------------------------------------- 1 | \documentclass[11pt] {article} 2 | \usepackage{amsthm} 3 | \usepackage{graphicx, amsmath, amssymb} 4 | \usepackage{amsfonts, enumerate} 5 | \usepackage{algorithmic, algorithm} 6 | \usepackage[usenames]{color} 7 | 8 | \setlength{\textwidth}{6in} 9 | \addtolength{\hoffset}{-0.5in} 10 | \setlength{\topmargin}{-0.2in} 11 | \setlength{\textheight}{9in} 12 | 13 | \newcommand{\algorithmicinput}{\textbf{Input:}} 14 | \newcommand{\algorithmicoutput}{\textbf{Output:}} 15 | \newcommand{\algorithmicinit}{\textbf{Initialize:}} 16 | \newcommand{\INPUT}{\item[\algorithmicinput]} 17 | \newcommand{\OUTPUT}{\item[\algorithmicoutput]} 18 | \newcommand{\INIT}{\item[\algorithmicinit]} 19 | \newcommand{\algorithmicalgo}{\textbf{Algorithm:}} 20 | \newcommand{\ALGO}{\item[\algorithmicalgo]} 21 | 22 | \begin{document} 23 | \pagestyle{empty} 24 | 25 | 26 | \begin{center} 27 | \LARGE 28 | \textbf{AI algorithms: Heuristic Search}\\ 29 | \end{center} 30 | \vspace{1cm} 31 | 32 | \noindent \textcolor{blue}{hill climbing 1}\\ 33 | \textcolor[rgb]{1,0,1}{beam search}\\ 34 | \textcolor{red}{hill climbing 2}\\ 35 | \textcolor{green}{greedy search}\\ 36 | 37 | \begin{algorithmic} 38 | \INPUT 39 | \STATE A graph of nodes, a start node $S$ and a goal node $G$ 40 | \STATE A queue Q of possible paths 41 | \STATE \textcolor[rgb]{1,0,1}{A natural number WIDTH $\leq$ min branching factor} 42 | \STATE A heuristic function $H$ of the distance to $G$ 43 | 44 | \OUTPUT 45 | \STATE A path from $S$ to $G$ 46 | \end{algorithmic} 47 | 48 | \begin{algorithmic} 49 | \ALGO 50 | \STATE $Q$ $\leftarrow$ $S$ 51 | \WHILE{$Q$ not empty AND $G$ not reached} 52 | \STATE $p$ $\leftarrow$ get (and remove) first path from $Q$ 53 | \STATE \hspace{3.73cm} \textcolor[rgb]{1,0,1}{all paths} 54 | \STATE $P$ $\leftarrow$ all paths to children of $p$ 55 | \STATE \hspace{4.75cm} \textcolor[rgb]{1,0,1}{of all paths in p} 56 | \STATE Remove all paths from $P$ containing loops 57 | \STATE \textcolor[rgb]{1,0,1}{(optimization: remove paths in P without successor)} 58 | \STATE \textcolor{blue}{Sort $P$ according to $H$} \textcolor[rgb]{1,0,1}{(idem)} 59 | \STATE Add \textcolor{red}{best of all} paths of $P$ to front of $Q$ 60 | \STATE \hspace{0.7cm} \textcolor[rgb]{1,0,1}{WIDTH best} 61 | \STATE \textcolor{green}{Sort $Q$ according to $H$} 62 | \ENDWHILE 63 | \IF{$G$ reached} 64 | \STATE Succes 65 | \ELSE 66 | \STATE Failure 67 | \ENDIF 68 | \end{algorithmic} 69 | 70 | \end{document} 71 | -------------------------------------------------------------------------------- /Sem1/ArtificialIntelligence/Heuristic Search Overview/readme.md: -------------------------------------------------------------------------------- 1 | Deze originele versie van deze overview, inclusief de .tex sources, kan gevonden worden op de AI site hier: 2 | https://dtai.cs.kuleuven.be/education/ai/Downloads/algos.zip 3 | 4 | Beam search zit echter niet bij de overview in het origineel omdat het algoritme een oefening is van een oefenzitting. 5 | Om toch een volledig overzicht te krijgen, staat hier een versie van het overzicht waar Beam search bij zit. 6 | 7 | Ik heb nog een assumptie gemaakt, namelijk dat WIDTH <= de minimale branching factor van de boom. -------------------------------------------------------------------------------- /Sem1/ArtificialIntelligence/Samenvatting Midas/README.md: -------------------------------------------------------------------------------- 1 | #Disclaimer: 2 | Deze samenvatting is bedoeld als samenvatting van de [samenvatting van Joost](https://github.com/JO0st/samenvatting_AI). Deze is vooral bedoeld om de kern uit de samenvatting van Joost te halen en de dingen die je moet weten nog eens apart ergens te zetten, samen met een super korte beschrijving van algoritmes. Deze samenvatting gaat niet helpen om de leerstof te begrijpen. 3 | -------------------------------------------------------------------------------- /Sem1/ArtificialIntelligence/Samenvatting Midas/Samenvatting.tex: -------------------------------------------------------------------------------- 1 | \documentclass{report} 2 | 3 | \begin{document} 4 | \chapter{Search} 5 | \begin{itemize} 6 | \item b: (gemiddelde) branching factor. 7 | \item d: diepte. 8 | \item m: diepte van de ondiepste oplossing. 9 | \end{itemize} 10 | \section{Blind Search} 11 | \subsection{Diepte-eerst} 12 | \begin{itemize} 13 | \item \textbf{Snelheid}: $O(b^d)$ 14 | \item \textbf{Geheugen}: $O(d \times b)$ 15 | \end{itemize} 16 | \subsection{Breedte-eerst} 17 | \begin{itemize} 18 | \item \textbf{Snelheid}: $O(b^m)$ 19 | \item \textbf{Geheugen}: $b^m$ 20 | \end{itemize} 21 | \subsection{Non-deterministic search} 22 | \begin{itemize} 23 | \item Eerste pad van de queue verwijderen en kinderen op willekeurige plaatsen toevoegen. 24 | \end{itemize} 25 | \subsection{Iterative Deepening Search (IDS)} 26 | \begin{itemize} 27 | \item Diepte eerst met een maximale diepte die wordt vergroot als de oplossing niet wordt gevonden. 28 | \item \textbf{Snelheid}: $O(b^m)$ 29 | \item \textbf{Geheugen}: $b \times m$ 30 | \end{itemize} 31 | \subsection{Bidirectional search} 32 | \begin{itemize} 33 | \item Begin zowel van doel als van begintoestand, werk naar elkaar toe. 34 | \item \textbf{Snelheid}: $O(b^{m/2})$ 35 | \item \textbf{Geheugen}: $O(b^{m/2})$ 36 | \end{itemize} 37 | 38 | \section{Heuristic Search} 39 | \subsection{Hill Climbing} 40 | \begin{itemize} 41 | \item Diepte eerst op basis van heuristiek. 42 | \item \textbf{Snelheid}: $O(b^{d})$ 43 | \item \textbf{Geheugen}: $O(b \times d)$ 44 | \end{itemize} 45 | \subsection{Beam Search} 46 | \begin{itemize} 47 | \item Breedte eerst met maximale breedte, de gekozen bomen zijn degene met de beste heuristische waarde. 48 | \item \textbf{Snelheid}: $width \times m \times b$ 49 | \item \textbf{Geheugen}: $O(width)$ 50 | \end{itemize} 51 | \subsection{Hill Climbing 2} 52 | \begin{itemize} 53 | \item Beam Search met maximale breedte=1. 54 | \end{itemize} 55 | \subsection{Greedy Search} 56 | \begin{itemize} 57 | \item Knoop met beste heuristische waarde uitbreiden. 58 | \end{itemize} 59 | \subsection{Uniform Cost Algorithm} 60 | \begin{itemize} 61 | \item Knoop expanderen dat de laagste kost heeft geacumuleerd. 62 | \end{itemize} 63 | \subsection{Branch and Bound principle} 64 | \begin{itemize} 65 | \item Als er een pad naar de doelknoop is, alle paden met een hogere kost verwijderen. 66 | \end{itemize} 67 | \subsection{Estimate-extended uniform cost algorithm} 68 | \begin{itemize} 69 | \item Uniform Cost op basis van $geacumuleerde kost + heuristiek$ 70 | \end{itemize} 71 | \subsection{path deletion} 72 | \begin{itemize} 73 | \item Meerdere paden naar dezelfde knoop, alleen 'goedkoopste' pad bijhouden. 74 | \end{itemize} 75 | \subsection{A* Search} 76 | \begin{itemize} 77 | \item Estimate-extended uniform cost algorithm + branch and bound en path deletion. 78 | \end{itemize} 79 | \subsection{Iterative deepening A*} 80 | \begin{itemize} 81 | \item A* met maximale f-waarde die bereikt mag worden. De f-waarde wordt altijd minimaal verhoogt. 82 | \item B: best path, $\delta$: Minimale kost van een boog. 83 | \item \textbf{Snelheid}: $O(n^2)$ 84 | \item \textbf{Geheugen}: $O(b \times (cost(B)/\delta))$ 85 | \end{itemize} 86 | 87 | \section{Version Spaces} 88 | \begin{itemize} 89 | \item Find S: Positive training examples. 90 | \item Dual Find S: Negative training examples. 91 | \item Version Spaces: Find S + Dual Find S + Alle minimale generalisaties (ipv 1). 92 | \item Optimalisaties: 93 | \begin{itemize} 94 | \item Schrappen redundante hypotheses (Aan algemene kant iets hebben dat nog algemener is). 95 | \item Als positief voorbeeld wordt toegevoegd, kijken of er aan de algemene kant hypotheses geschrapt kunnen worden (kan ook omgekeerd). 96 | \item Alle veralgemeningen tegelijk toevoegen. 97 | \end{itemize} 98 | \end{itemize} 99 | 100 | \section{Constraint Processing} 101 | 102 | \section{STRIPS Planning} 103 | 104 | \section{Automatisch Redeneren} 105 | \end{document} 106 | -------------------------------------------------------------------------------- /Sem1/BesturingsSystemen/Database Begrippen/bs_db.csv: -------------------------------------------------------------------------------- 1 | H1,operating system,"A program that manages a computer's hardware, provides a basis for application programs and acts as an intermediary between user and hardware." 2 | H1,personal computer (PC),"An operating system that sports complex games, business applications and everything in between." 3 | H1,the four main components of a computer system,"the hardware, te operating system, the application programs and the users" 4 | H1,hardware,"The central processing unit (CPU), the memory and the input/output (I/O) devices provide the basic computing resources for the system." 5 | H1,application programs,"Those define the way in which the resources are used to solve users' computing problems. some examples: word processors, spreadsheets, compilers, web browsers" 6 | H1,resource utilisation,how various hardware and software resources are shared 7 | H1,the principle of mainframes and minicomputers,"Many users access the same computer through other terminals. These users share resources and may exchange information. The operating system is designed to maximise resource utilisation, to assure that hardware is used efficiently and to assure that no user takes more than its fair share." 8 | H1,the principle of workstations,"Many users can access a network of other workstations and servers. They have dedicated resources, but also share resources such as networking and servers, including file, compute and print servers. Their operating system is designed to compromise between individual usability and resource utilisation." 9 | H1,touch screen,A screen used by mobile computers. The user interacts with the system by pressing and swiping fingers across the screen rather than using a physical keyboard and mouse. 10 | H1,resource allocator,An operating system can be seen as a resource allocator for computer system. It acts as the manager of resources and must decide how to allocate them to specific programs and users so that it can operate the computer system efficiently and fairly. 11 | H1,control program,An operating system is a control program. It has to manage the execution of user programs to prevent errors and improper use of the computers. It needs to control various I/O devices too. 12 | H1,Moore's prediciton,The number of transistors on an integrated circuit will double every 18 months. 13 | H1,the three types of programs,"kernel, system programs, application programs" 14 | H1,kernel,the one program running at all times 15 | H1,system programs,"programs associated with the operating system, but not necessarily part of the kernel" 16 | H1,application programs,all programs not associated with the operation of the system 17 | H1,middleware,"a set of software frameworks that provide additional services to application developpers; examples: databases, multimedia and graphics supporting middleware" 18 | H1,bootstrap program,"This is the program a computer initially needs to start running. It is usually simple and is typically stored in ROM or EEPROM. It is generally known by the term firmware. It initialises all aspects of the system and it must know how to load the operating system, as well as how to start executing that system.The bootstrap program must locate the operating-system kernel and load it into memory." 19 | H1,ROM,"read-only memory, bootstrap program often resides on ROM" 20 | H1,EEPROM,"electrically erasable programmable read-only memory, bootstrap program often resides on EEPROM" 21 | H1,system process/system daemon,This is a system program that is loaded in to memory at boot time. It runs the entire time the kernel is running. 22 | H1,interrupt,"This signals the occurence of an event. Hardware may trigger interruptsat any time by sending a signal to the CPU, usually using the system bus. Software may trigger an interrupt by executing a special operation called a system call (also monitor call)." 23 | H1,system call,a software-generated interrupt 24 | H1,interrupt vector,"a table of pointers, stored in low memory, containing the adresses of the interrupt service routines for the various devices. " 25 | H1,RAM,"random-access memory or main memory, which is rewritable, whence general-purpose computers run their programs" 26 | H1,DRAM,"dynamic random-access memory, common implementation of RAM using semiconductor technology" 27 | H1,von Neumann architecture,computer architecture that is used in nearly all modern general-usage computers 28 | H1,instruction register,"the register where the instruction to be executed is stored in a typical instruction-execution cycle, as executed on a system with a von Neumann architecture" 29 | H1,volatile storage,"storage that needs power to maintain information, examples: registers, cache, main memory" 30 | H1,secondary storage,"an extension of the main memory that most computer systems provide, able to hold large quantities of data permanently" 31 | H1,magnetic disk,most common secondary-storage device 32 | H1,the hierarchy of storage devices,registers - cache - main memory - solid-state disk - magnetic disk - optical disk - magnetic tapes 33 | H1,semiconductor memory,"memory that uses semiconductor technology, is fast and relatively cheap, examples: registers, cache, main memory, solid-state disk" 34 | H1,non-volatile storage,"storage that does not need power to maintain information, examples: solid-state disk, magnetic disk, optical disk, magnetic tapes" 35 | H1,Solid-state disks,"storage device that is faster than magnetic disks and non-volatile, there are multiple types of solid-state disks" 36 | H1,PDA,personal digital assistant 37 | H1,NVRAM,"non-volatile RAM, consists of DRAM with battery backup power, is as fast as DRAM as long as the battery lasts" 38 | H1,SCSI,"small computer-system interface, device controller to which seven or more devices can be attached" 39 | H1,device controller,"is in charge of a specific type of device, maintains some local buffer storage and a set of special-purpose registers, is responsible for moving data between the peripheral device and the local buffer storage" 40 | H1,device driver,"operating systems have one for each device controller, understands the device controller, provides the rest of the operating system with a uniform interface to the device" 41 | H1,DMA,"direct memory access, transfer of entire block of data directly to/from memory from/to device controller buffer, only one interrupt is generated per block, CPU can do other work concurrently" 42 | H1,special-purpose processor,"runs a limited instruction set, does not run user processes, sometimes managed by operating system, relieves CPU of some tasks/overhead, sometimes low-level autonomous components, in that case operating system can not commmunicate with these special-purpose processors" 43 | H1,multiprocessor/parallel/multicore systems,"systems with two or more processors in close communication, sharing bus, sometimes sharing clock, memory and peripheral devices" 44 | H1,three advantages of multiprocessors,"increased throughput, economy of scale, increased reliability" 45 | H1,increased throughput due to multiprocessors,"more processors = more work done, speed up ratio of N processors is lower than N due to overhead" 46 | H1,economy of scale due to multiprocessors,"more processors on one bus= less cost, shared peripherals, mass storage and power supplies" 47 | H1,increased reliability due to multiprocessors,"more processors = less chance of total failure, other processors can pick up a share of work when one fails" 48 | H1,graceful degradation,the ability to continue providing service proportional to the level of surviving hardware 49 | H1,fault tolerance,"the ability to suffer a failure of any single component and still continue operation, requires a mechanism to detect, diagnose and correct failure" 50 | H1,asymmetric multiprocessing,"each processor has a specific task, one is the boss processor and controls the system, other processors look to the boss for instructions or have predefined tasks" 51 | H1,symmetric multiprocessing,"each processor performs all tasks within the operating system, all processors are peers, each processor has its own set of registers and private/local cache, pysical memory is shared, " 52 | H1,uniform memory access (UMA),the situation in which access to any RAM from any CPU takes the same amount of time 53 | H1,non-uniform memory access (NUMA),"the situation in which access to some parts of memory may take longer to access than other parts, creating a performance penalty" 54 | H1,computing core,"independent actual processing unit, a multicore CPU consists of more computing cores" 55 | H1,multicore processor,a processor with multiple computing cores 56 | H1,benefits of multicore processors,"on-chip communication is faster than between-chip communication, one chip with multiple processors uses significantly less power than multiple single-core chips" 57 | H1,blade server,"processor boards, I/O boards, networking boards are placed in the same chassis, each blade-processor boots independently and runs its own operating system, some blade server boards are multiprocessor as well these severs consist of multiple independent multiprocessor systems" 58 | H1,clustered system,"type of multiprocessor system which gathers together multiple CPU's, composed of two or more individual systems joined together (loosely coupled), each node may be a single processor system or a multicore system" 59 | H1,loosely coupled,composed of two or more systems joined together 60 | H1,high availibility service,"service that will continue even if one or more systems in the cluster fail, generally obtained by adding a level of redundancy to the system" 61 | H1,assymetric clustering,"one machine in hot-standby mode while other is running the applications, hot-standby host machine only monitors, on failure it becomes the active server " 62 | H1,symmetric clustering,"two or more hosts are running applications and are monitoring each other, does require more than one available application to run" 63 | H1,high-performance computing environment system,"system that can supplysignificantly greater computational power than single-procesor or even SMP systems, can run an application concurrently on all computers in the cluster, requires the application to be written specifically to take advantage of the cluster" 64 | H1,parallelisation,"division of a program in separate components that run in parallel on individual computers in the cluster, typically designed so that once each computing node in the cluster has solved its portion of the problem, the results from all the nodes are combined in a final solution" 65 | H1,distributed locking manager (DLM),access control and locking to ensure that no conflicting operations occur 66 | H1,storage area network (SAN),"allow many systems to attach a pool of storage, if application and data stored on SAN then cluster software can assign application to run on any host that is attached to the SAN, if the host fails any other host can take over, dozens of hosts can share the same daabase, greatly increasing performance and reliability" 67 | H1,multiprogramming,"operating system keeps several jobs in main memory simultaneously, actually in job pool (physical memory) because main memory is too small, CPU utilisation is increased by organising jobs so that the CPU always has one to execute, operating system picks a job and begins to execute it in memory, eventually will have to wait (e.g. I/O) -> switches to other job" 68 | H1,timesharing/multitasking,"logical extension to multprogamming, CPU executes multiple job by switching among them, switches occur so frequently that the user can interact with each running program" 69 | H1,interactive computer system,"provides direct communication between user and system, user gives instructinos to operating system or program directly using input devices and wait for immediate results on an output device." 70 | H1,response time,"time between input and output, should typically be less than a second on interactive computer systems" 71 | H1,process,a program loaded into memory and executing 72 | H1,job scheduling,"If several jobs are ready to be brought into memory and there is not enough room for all of them, the system must choose among them." 73 | H1,CPU scheduling,"If several jobs are ready to run, the system must choose which job it will run first." 74 | H1,swapping,processes are swapped in and out of main memory to the disk 75 | H1,virtual memory,"a technique that allow the execution of a process that is not completely in main memory, enables to run programs that are larger than physical memory, abstracts main memory into a large uniform array of storage, separating logical memory from physical memory, frees programmers from concerns over memory-storage limitations" 76 | H1,logical memory,memory as viewed by the user 77 | H1,physical memory,memory as it actually is 78 | H1,interrupt driven,"If the operating system has no work, it will sit quietly, waiting for something to happen. Events are signaled y the occurence of an interrupt or trap." 79 | H1,trap/exception,"a software-generated interrupt, caused either by an error or by a specific requestfrom a user programthat an operating system service be performed" 80 | H1,mode bit,"located in the hardware of of the computer, indicates current mode: kernel or user, used to distinguish between an operating system task and a user task" 81 | H1,user mode,when the system is executing on behalf of a user appication 82 | H1,kernel/supervisor/system/priviliged mode,"When a user application requests a service from the operating system, the system must transition from user mode to kernel mode to fulfill the request." 83 | H1,privileged instructions,"some of the machine instructions that may cause harm and can only be executed in kernel mode, any attempt to execute them in user mode results in the hardware denying execution, examples: switching to kernel mode, I/O control, timer management, interrupt management" 84 | H1,virtual machine manager (VMM),"creates and manages virtual machines, changes the CPU stat to do so, has more privileges than user mode, but less than kernel mode" 85 | H1,life cycle of instruction execution,"initially kernel mode, control is given to user application and mode is user mode, via interrupt, trap or system call control is switched back to operating system" 86 | H1,timer,"can be set to interrupt the computer after a specified period, is ensured to be set to interrupt before turning control over to user" 87 | H1,program counter,specifies the next instruction to execute 88 | H1,file,"logical storage unit, a collection of related information defined by its creator" 89 | H1,tertiary storage,storage that is slower and lower in cost 90 | H1,WORM,"write once, read many times" 91 | H1,RW,read-write 92 | H1,caching,"As information is used, it is copied into a faster storage system (cache) temporarily. When information is needed, cache is checked first. If it is present, it is used. If it is not, source information is used and is brought into the cache." 93 | H1,cache management,the design problem concerning size and replacement policy of the cache 94 | H1,cache coherency,An update of a value in one cache is immediately reflected in all other caches containing that value. 95 | H1,I/O subsystem,"This is a component that hides the peculiarities of I/O devices. It consists of a memory-management component that includes buffering, ceching and spooling. It has a general device-driver interface and drivers for specific hardware devices. Only the device driver knows the peculiarities of the specific device." 96 | H1,protection,"any mechanism for controlling the access of processesor users to the resources defined by a computer system, must provide means to specify the controls to be imposed and to enforce the controls" 97 | H1,security,"prevention of inappropriate access even when prevention is working, also prevents attacks (e.g. viruses worms, DoS, identity theft and theft of service" 98 | H1,user ID,"user identifier, unique, required by protection and security to be able to distinguish users" 99 | H1,security ID,user ID in Windows parlance 100 | H1,group identifier,"identifier for a group of users, unique, required by protection and security to be able to distinguish groups of users" 101 | H1,escalate privileges,action that allows access to a device that is restricted 102 | H1,effective UID,"the user ID that is actually used for a process, for example when escalating privileges" 103 | H1,portals,"provide web accessibility to internal servers, used by companies" 104 | H1,network computers/thin clients,"terminals that understand web-based computing, used when more security or easier maintenance is desired" 105 | H1,firewall,protects network from security breaches 106 | H1,mobile computing,computing on handheld smartphones and tablet computers 107 | H1,network,a communication path between two or more systems 108 | H1,TCP/IP,"most common network protocol, provides the fundamental architecture of the internet" 109 | H1,LAN,"network that spans a room, building or campus, local-area network" 110 | H1,WAN,"network that spans buildings, cities or even countries, wide-area network" 111 | H1,PAN,"network that spans several metres, personal-area network" 112 | H1,MAN,"network that spans buildings within a city, metropolitan-area network" 113 | H1,network operating system,"an operating system that provides features such as file sharing across the network, along with a communication scheme that allows different processes on different computers to exchange messages." 114 | H1,server system,system that satisfies requests by client systems in a client-server system 115 | H1,client system,system that requests services from server systems in a client-server system 116 | H1,client-server system,a distriuted system containing server systems and client systems 117 | H1,compute-server system,"type of server-system, provides interface to which a client can send a request to perform an action, server executes action and sends results to the client in response (e.g. database server)" 118 | H1,file-server system,"provides a file-system interface where clients can create, update, read and delete files (e.g. web server that delivers files to clients running web browsers" 119 | H1,peer-to-peer system,distributed system model where clients and servers are not distinguished from one another 120 | H1,VoIP,voice over IP (e.g. Skype) 121 | H1,emulation,virtualisation technique that is used when the source CPU type is different from the target CPU type. 122 | H1,virtualisation,technology that allows operating systems to run as applications within another operating system 123 | H1,guest operating system,an operating system running its own applications within another operating system (virtualisation) 124 | H1,host operating system,an operating system in which other operating systems run their own applications (virtualisation) 125 | H1,cloud computing,"type of computing that delivers computing, storage and even applications as a service across a network." 126 | H1,public cloud,cloud available via the internet to anyone who is willing to pay for the services 127 | H1,private cloud,cloud run by a company for that company's own use 128 | H1,hybrid cloud,a cloud that includes both public and private cloud components 129 | H1,SaaS,"software as a service, one or more applications available via the internet" 130 | H1,PaaS,"platform as a service, software stack ready for application use via the internet" 131 | H1,Iaas,"infrastructure as a service, servers or sorage available over the internet" 132 | H1,embedded system,"system on devices with very specific tasks, usually primitive with little to no user interface, prefers to spend time monitoring and managing hardware devices" 133 | H1,ASIC,"application-specific integrated circuit, performs tasks without a operating system" 134 | H1,real-time operating system,"system used when rigid time measurements have been placed on the operation of a processor or the flow of data, almost always used on embeded systems" 135 | H1,Open-source operating system,OS available in source-code rather than as compiled binary code 136 | H1,Closed-source operating system,OS available as comiled binary code rather than in source-code 137 | H1,reverse engineering,"converting binary files to source code, information such as comments are lost though" 138 | H1,DRM,"digital rights management, limitation of the ability to play back movies and music or display ebooks" 139 | H1,copy protection,limitation of the ability to play back movies and music or display ebooks 140 | H1,FSF,"free software foundation, encourages the free axchange of software source code and the free use of that software" 141 | H1,GPL,"GNU public license, common license underwhich free software is released, requires source code to be sdistributed with any binaries and any changes to source code be released under GPL too" 142 | H1,GNU/Linux,"open-source operating system, started by Linus Torvalds, contributed to by thousands of programmers over the internet" 143 | H1,distribution,"variant (custom build) of an (open-source) operating system (e.g. RedHat, SUSE, Fedora, Debian, Ubuntu, MenuetOS for the GNU/Linux project)" 144 | H1,LiveCD,"operating residing on a CD-ROM, can booted and run from the CD-ROM without being installed on a systems hard disk" 145 | H1,LiveDVD,"operating residing on a DVD, can booted and run from the DVD without being installed on a systems hard disk" 146 | H1,BSD UNIX,"open-source operating system of Berkeley University (examples: FreeBSD, OpenBSD, NetBSD, DragonflyBSD)" 147 | H1,Solaris,"based on BSD UNIX, previously known as SunOS, UNIX-based OS of Sun MicroSystems, purchase of Sun by Oracle left the state of the project unclear, Project Illumoshas expanded from OpenSolaris" 148 | H2,User Interface,"tool to execute user-entered commands, common forms are command-line interface, batch inteface and graphical user interface" 149 | H2,command-line interface,uses text commands and a specific method for entering them 150 | H2,batch interface,"commands and directives to control those are entered into files, then those are executed" 151 | H2,graphical user interface,"window system with a pointing device to direct I/O, choose from menus and make selections, a keyboard to enter text" 152 | H2,shared memory,two or more processes read and write to a shared section of memory 153 | H2,message passing,packets of information in predefined formats are moved between processes by the OS 154 | H2,common classes of operating-system services,"User interface, Program execution, I/O operations, File-system manipulation, Communications, Error detection, Resource allocation, Accounting, Protection and security" 155 | H2,command interpreter,command-line interface that allows user to directly enter commands to be performed by the operating system 156 | H2,shell,command interpreter on a system with multiple command interpreters 157 | H2,desktop GUI,"mouse-based window-and-menu system, user moves mouse to position its pointer to images or icons on the screen that represent programs, directories, files and system functions" 158 | H2,folder,directory 159 | H2,gestures,actions to interact on a touchscreen desktop interface 160 | H2,sysadmins,System administrators manage computers 161 | H2,power users,have an advanced knowledge of a system 162 | H2,shell script,program that is not compiled into code but rather is interpreted by the command-line interface 163 | H2,system call,"provide an interface to the services made available by an OS, generally available as routines written in C or C++ (assembly for low-level tasks)" 164 | H2,API,"Application programming interface, specifies a set of functions that are available to an application programmer, including parameters and return values" 165 | H2,libc,library for programs written in the C language for UNIX and Linux 166 | H2,system-call interface,"serves as the link to system calls made available by the operating system, provided by the run-time support system" 167 | H2,run-time support system,a set of functions built into libraries included with a compiler 168 | H2,the six major categories of system calls,"process control, file manipulation, device manipulation, information maintenance, communications and protection" 169 | H2,debugger,system program designed to aid the programmer in finding and correcting errors 170 | H2,bugs,errors 171 | H2,types of process control system calls,"end, abort, load, execute, create/terminate process, get/set process attributes, wait for time, wait/signal event, allocate/free memory" 172 | H2,types of file management system calls,"create/delete file, open/close file, read/write/reposition file, get/set file attributes" 173 | H2,types of device management system calls,"request/release device, read/write/reposition, ge/set device attributes, logically atach/detach devices" 174 | H2,types of information maintenance system calls,"get/set time or date, get/set system data, get/set process, file, or device attributes" 175 | H2,types of communications system calls,"create/delete communication connection, send/receive messages, transfer status information, attach/detach remote devices" 176 | H2,lock,can be introduced when sharing data to ensure the integrity of shared data 177 | H2,single step,CPU mode in which a trap is executed after every instruction 178 | H2,message passing model,interprocess communication model in which the communicating processes exchange messages with one another to transfer information 179 | H2,host name,unique name by which a computer is known in a network 180 | H2,process name,unique name which is translated into an identifier by which the operating system can refer to the process 181 | H2,daemon,"special-purpose process most process that receive are daemons, system programs provided for that purpose" 182 | H2,client (concerning daemons),the source of the communication 183 | H2,server (concerning daemons),the receiving daemon 184 | H2,shared-memory model,"interprocess communication model in which the communicating processes agree to share a region of memory, data is written into and read out of the shared regions, processes are responsible for ensuring that they are not writing to the same location simultaneously." 185 | H2,system programs,"provide a convenient environment for program development and execution, also known as system utilities" 186 | H2,system utilities,"provide a convenient environment for program development and execution, also known as system programs" 187 | H2,categories of system programs/system utilities,"file management, status information, file modification, programming-language support, program loading and execution, communications, background services" 188 | H2,system programs concerning file management,"create, delete, copy, rename, print, dump, list and generally manipulate files and directories" 189 | H2,system programs concerning status information,"ask status information such as time, date, amount of available memory or disk space, number of users..., typically format and print to the terminal, other output device, files or display it in a window of the GUI" 190 | H2,registry,"used to store and retrieve configuration information, system program concerning status information" 191 | H2,system programs concerning file modification,"text editors to create and modify the content of files, maybe also special commands to search contents of files or perform transformations of the text" 192 | H2,system programs concerning programming-language support,"compilers, assemblers, debuggers, interpreters for common programming languages, often either included or separately downloadable" 193 | H2,system programs concerning program loading and execution,"absolute loaders, relocatable loaders, linkage editors, overlay loaders, debugging systems for higher-level languages or machine language" 194 | H2,system programs concerning communications,"mechanisms for creating virtual connections among processes, users and computer systems, they allow users to send messages, browse web pages, send e-mails, log in remotely or transfer files among machines" 195 | H2,system programs concerning background services,"start at boot-time, may halt or continue execution, known as services, subsystems or daemons, examples: network daemon, process schedulers, system error monitoring services, prints servers, ..., important activities that run in user mode rather than in kernel mode use background services" 196 | H2,"services, subsystems, daemons",system-program processes that are constantly running 197 | H2,two basic groups of design goals,user goals and system goals 198 | H2,examples of user goals,"system is convenient to use, easy to learn and use, reliable, safe and fast (no general agreement how to achieve them)" 199 | H2,examples of system goals,"system is easy to design, implement and maintain, it should be flexible, reliale, error free and efficient" 200 | H2,separation of policy and mechanism,policy: what to do; mechanism: how to do it 201 | H2,porting an OS,to move an OS to some other hardware 202 | H2,emulator,program that duplicates the functionality of one system to another system 203 | H2,monolithic system,system in which the tasks are not partitioned into small components but interwoven in one large component 204 | H2,layered approach system,"system in which the operating system is broken into a number of layers, the lowest layer being the hardware, each layer can invoke lower-level operations, each layer is implemented only with operations provided by lower-level layers" 205 | H2,microkernel,method that structures the operating system by removing all nonessential components from the kernel and implementing them as user-level programs 206 | H2,Mach,operating system developed by Carnegie Mellon University that modularises the kernel using the microkernel approach 207 | H2,Darwin,"kernel of Mac OS X, partly based on Mach" 208 | H2,loadable kernel module,"kernel that has a set of core components and links in additional services via modules, either at boot time or during run time, idea is to provide core services while other services are implemented dynamically, as the kernel is running, produces a system that resembles one with layered approach, but more flexible, since every module can call any other module" 209 | H2,Cocoa,"environment that specifies an API for objective-C, used for development of Mac OS X applications" 210 | H2,kernel extensions,dynamically loadable modules as referred to in Mac OS X 211 | H2,Cocoa Touch,API for Objective-C that provides frameworks for developping applications for iOS devices 212 | H2,media services layer (iOS),"layer tht provides services for graphics, audio and video" 213 | H2,core services layer (iOS),"provides a variety of features, including support for cloud computing and databases" 214 | H2,Dalvik Virtual Machine,virtual machine that is designed for android and is optimised for mobile devices with limited memory and CPU processing capabilities 215 | H2,debugging,"the activity of finding and fixing errors in a system, both in hardware and in software" 216 | H2,performance tuning,type of debugging that seeks to improve performance by removing processing bottlenecks 217 | H2,log file,where an OS writes error information to if a process fails 218 | H2,core dump,"a capture of the memory of the process, which the OS can store in a file for later analysis" 219 | H2,crash,failure in the kernel 220 | H2,crash dump,"When a crash occurs, error information is saved to a log file and the memory state is saved to a crash dump. It is often written to a section of the disk that is set aside for this purpose." 221 | H2,Windows Task Manager,"performance tuning tool for Windows system, includes information for current applications as well as processes, CPU and memory usage and networking statistics" 222 | H2,SYSGEN,"system generation, a system is configured or generated for each specific computer site used for most OS, since they are designed to run on any class of machines at a variety of sites" 223 | H2,booting,the procedure of startin a computer by loading the kernel 224 | H2,bootstrap program/bootstrap loader,"small piece of code that locates the kernel, loads it into memory and starts its execution, usually resides in ROM" 225 | H2,firmware,"part of the operating system with characteristics that fal somewhere between software and hardware, all forms or ROM are known as firmware" 226 | H2,boot block,single block at a fixed location containing a program that may be sophisticated enough to load the entire OS into memory and begin its execution 227 | H2,GRUB,open-source bootstrap program for linux systems 228 | H2,boot disk/system disk,a disk that has a boot partition 229 | H3,process,"program in execution, the unit of work in a modern time-sharing system" 230 | H3,jobs,what CPU activities are called in a batch system 231 | H3,tasks/user programs,what CPU activities are called in a time-sharing system 232 | H3,text section,program code 233 | H3,program counter,"current activity of the program, along with the contents of the processor register" 234 | H3,stack,data structure that contains temporary data 235 | H3,data section,contains global variables 236 | H3,heap,memory that is dynamically allocated during process run time 237 | H3,process state,defined by the current activity of that process 238 | H3,possible process states,"new (process is being created), running (instructions are being executed), waiting (process is waiting for some event to occur (I/O or reception of a signal)), ready (process is waiting to be assigned to a processor), terminated (process has finished execution); names may vary across OS" 239 | H3,PCB,"process control block/task control block, where each process is represented in the OS, contains many pieces of information" 240 | H3,pieces of information in PCB,"process state, program counter, CPU registers, CPU scheduling information, memory management information, accounting information, I/O status information" 241 | H3,thread (of execution),"component of a process, multiple threads can exist in the same process, running concurrently with the same resources" 242 | H3,process scheduler,selects an available process for program execution on the CPU 243 | H3,job queue,queue that consists of all processes in the system 244 | H3,ready queue,"queue that contains all processes that are residing in main memory and are ready and waiting to execute, often implemented as a linked list" 245 | H3,device queue,"queue that contains all proceses that are waiting for a particular I/O device, each device has its own device queue" 246 | H3,queueing diagram,"common representation of process scheduling, rectangles present queues, circles present resources, arrows indicate the flow processes in the system" 247 | H3,dispatched,selected for execution 248 | H3,long-term scheduler/job scheduler, -------------------------------------------------------------------------------- /Sem1/BesturingsSystemen/Database Begrippen/bs_py.py: -------------------------------------------------------------------------------- 1 | # Door Dries De Proost 2 | # Een CLI script dat de begrippen van BS ondervraagt en een modelantwoord. 3 | # Er is een database met begrippen en modelantwoorden nodig. Er is een in de repo. 4 | # De nieuwste versie van de database wordt bijgehouden in de volgende Google Docs Spreadsheet: 5 | # https://goo.gl/GxMnQq (help gerust met deze aan te vullen)!. 6 | # Download de spreadsheet als .csv en vervang bs_db.csv uit de repo ermee. 7 | 8 | # Suggesties voor verbetering van dit script: 9 | # - duidelijkere print formatting 10 | # - een mode aanbieden die er voor zorgt dat al 11 | # beantwoorde begrippen niet opnieuw gevraagd worden 12 | # tot dat elk begrip een keer beantwoord is. 13 | # - een readme.md maken ipv deze comments. 14 | 15 | import csv 16 | from random import randint 17 | 18 | 19 | db = open('bs_db.csv', 'r') 20 | reader = csv.reader(db) 21 | lst = [] 22 | 23 | 24 | for row in reader: 25 | tmp = [] 26 | for el in row: 27 | tmp.append(el) 28 | lst.append(tmp) 29 | 30 | 31 | lstlen=len(lst) 32 | stop='stop' 33 | print("Geef 'stop' in om te stoppen, iets anders voor een nieuw begrip") 34 | while True: 35 | trigger = input("") 36 | 37 | if trigger != 'stop': 38 | the_chosen_one = randint(0,lstlen-1) 39 | print("Uit "+ lst[the_chosen_one][0]+", wat weet je over "+lst[the_chosen_one][1]+"?") 40 | 41 | inp = input("") 42 | if inp == stop: 43 | break 44 | 45 | print("Uitleg uit de database: ", lst[the_chosen_one][2]) 46 | 47 | else: 48 | break 49 | 50 | -------------------------------------------------------------------------------- /Sem1/BesturingsSystemen/README.md: -------------------------------------------------------------------------------- 1 | #Besturings Systemen 2 | 3 | #Niet te kennen delen: 4 | * Hoofdstuk 2: 5 | * 2.8 - Operating-System Debugging 6 | * 2.8.3 - DTrace 7 | * Hoofdstuk 3: 8 | * 3.6 - Communication in client-server systems 9 | * Hoofdstuk 4: 10 | * 4.4 Alleen inleiding tot 4.4.1 11 | * 4.6.5 - Scheduler Activations 12 | * 4.7 Operating systems examples 13 | * Hoofdstuk 5: 14 | * 5.7: Operating system examples (wel de stukken uit H16 en H17) 15 | * Hoofdstuk 6: 16 | * 6.9 Synchronization examples 17 | * Hoofdstuk 8: 18 | * 8.7 Intel example 19 | * 8.8 ARM example 20 | * Hoofdstuk 9: 21 | * 9.10 Operating system examples (wel de stukken uit H16 en H17) 22 | * Hoofdstuk 10: 23 | * 10.5.2 Remote File Systems 24 | * Hoofdstuk 11: 25 | * 11.5.5 Space Maps 26 | * 11.8 NFS 27 | * 11.9 WAFL File System 28 | * Hoofdstuk 12: 29 | * 12.3 Disk Attachment 30 | * Hoofdstuk 13: 31 | * 13.6 STREAMS 32 | * Hoofdstuk 14: 33 | * 14.8 - Capability-Based Systems 34 | * Hoofdstuk 15: 35 | * Geen enkele "formule" kennen 36 | 37 | #Te kennen, maar niet in het boek: 38 | * De laatste oefenzitting omtrent Hypervisors (Uitleggen waarom en hoe, geen code kunnen geven) 39 | 40 | #Wordt uitgedeeld op het examen: 41 | Onderstaande stukken worden uit het boek gekopieerd en op het examen uitgedeeld, het is dus niet nodig om deze stukken vanbuiten te leren, maar bekijk ze zeker op voorhand! 42 | * Hoofdstuk 3: 43 | * 3.5 - Examples of IPC Systems 44 | * Hoofdstuk 4: 45 | * 4.3 - Thread libraries 46 | * 4.5 - Operating Systems Examples 47 | * Hoofdstuk 6: 48 | * 6.9 - Synchronization Examples (? staat niet in document op toledo ?) 49 | * Hoofdstuk 16 (volledig) 50 | * Hoofdstuk 17 (volledig) 51 | 52 | #Gezien in SOCS: 53 | Hieronder vind je de stukken die we bij SOCS al gezien hadden, en wat dus verondersteld word nog te weten. 54 | * Hoofdstuk 12: 55 | * 12.1 - Overview of Mass-Storage Structure 56 | * 12.2 - Disk Structure 57 | * 12.3 - Disk Attachment 58 | * 12.7 - RAID Structure 59 | * Hoofdstuk 13: 60 | * 13.1: Overview 61 | * 13.2: I/O Hardware 62 | -------------------------------------------------------------------------------- /Sem1/BesturingsSystemen/Samenvatting Jérôme/Chapter-10-File-System.docx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem1/BesturingsSystemen/Samenvatting Jérôme/Chapter-10-File-System.docx 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Jonas en Michael op google drive 2 | map met alle hoofdstukken: https://drive.google.com/drive/folders/0Byb0moQzmpI_aWtOcWNFb0F3RUE?usp=sharing 3 | HF0: README --> https://docs.google.com/document/d/1hLijz3EFAPC8OCIPiW44chB1wi7LgqN8mvEQYP1td_c/edit?usp=sharing 4 | HF1: Eerstegraadsvergelijkingen en matrices --> https://docs.google.com/document/d/1n_xh-_-Dmf3oRXiCWpQD1z9XEYB6Lh2Sc5Q7vRN6i60/edit?usp=sharing 5 | HF2: Determinanten --> https://docs.google.com/document/d/1pveiMJfanbG7C_xYqN13v-9xycAvq7UnHDI7zW20lOo/edit?usp=sharing 6 | HF3: Vectorruimten --> https://docs.google.com/document/d/12Tco1CTIe7l3JILDmyaQEJm-rt8sImEm4ljBkR6Bw0E/edit?usp=sharing 7 | HF4: Lineaire afbeeldingen en lineaire transformaties --> https://docs.google.com/document/d/1Mh4UX4BfRXx_5f3i5Os_Y2u3orjCbzuNKIUPtAs9mWU/edit?usp=sharing 8 | HF5: Eigenwaarden, eigenvectoren en diagonaliseerbaarheid --> https://docs.google.com/document/d/1167-PyXzI6puR_zJNX2rXnRS1Ix9zf_mx6TSqMiNiYg/edit?usp=sharing 9 | HF6: Inproductruimten en Euclidische ruimten --> https://docs.google.com/document/d/1VS0FiC9M2YkCr-TP-_xGdSI_w7c9pgv6tMmALBItrng/edit?usp=sharing 10 | 11 | -------------------------------------------------------------------------------- /Sem1/MinorBusinessAndInnovation/.gitignore: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem1/MinorBusinessAndInnovation/.gitignore -------------------------------------------------------------------------------- /Sem1/MinorBusinessAndInnovation/Principles of Economics for Scientists/Assignment sessions Information and Innovation/Assignment session 2/PES page 1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem1/MinorBusinessAndInnovation/Principles of Economics for Scientists/Assignment sessions 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-------------------------------------------------------------------------------- /Sem1/MinorBusinessAndInnovation/Principles of Economics for Scientists/README.md: -------------------------------------------------------------------------------- 1 | #About Principles of Economics for Scientists 2 | A summary/course notes collection in Latex is currently being worked on at [ShareLatex](https://www.sharelatex.com/project/56239aff652e7ed02a181c63) 3 | 4 | A snapshot of the document after the last class has been added to this repo, but a lot of sections are incomplete and the document needs to be checked for consistency and spelling mistakes. 5 | For the latest version, refer to the ShareLatex project linked above. 6 | 7 | #IMPORTANT NOTE 8 | When compiling the snapshot on your own machine, you will need to use the [XeLaTex](https://en.wikipedia.org/wiki/XeTeX) compiler. 9 | (confirmed working a with a Miktex + Texmaker install on Windows) 10 | 11 | Major credits go to Michael Vanderstuyft, 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-------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/BusinessInformationSystems/Notities Mathias/Les 1 - Information systems.tex: -------------------------------------------------------------------------------- 1 | \documentclass{article} 2 | \setlength\parindent{0pt} 3 | 4 | \begin{document} 5 | 6 | \section{Introduction} 7 | 8 | The Challenges that today's companies are confronted with due to the technology explosion: 9 | 10 | \begin{enumerate} 11 | \item Many new Competitors 12 | 13 | \begin{itemize} 14 | \renewcommand{\labelitemi}{$\Rightarrow$} 15 | \item Everyone has their own systems and strategies 16 | \end{itemize} 17 | 18 | \item Who is responsible in the new business firm? 19 | 20 | \begin{itemize} 21 | \renewcommand{\labelitemi}{$\Rightarrow$} 22 | \item Decisions: IT and CEO not only the IT 23 | \end{itemize} 24 | 25 | \item You need people that are capable with IT and the technological challenges that come with it. You can't start a new `successful' company without IT. 26 | 27 | \begin{itemize} 28 | \renewcommand{\labelitemi}{$\Rightarrow$} 29 | \item People that know and can use the new technological changes to keep a business running. 30 | \end{itemize} 31 | \end{enumerate} 32 | 33 | What are the things companies need to do to hit their digital sweet spot? 34 | 35 | \begin{enumerate} 36 | \item They need to have priorities 37 | 38 | \item You will have to make decisions where the technological challenges will create new opportunities 39 | 40 | \item Where and how to invest in IT, how to spread this? Do you have the skills to realize this? 41 | 42 | \item Create an end-to-end view with the costumers: Don't only think about the strategies, also think about the costumers. Otherwise your business model will fail! 43 | \end{enumerate} 44 | 45 | If you as a company try to go digital, only a third of all the companies who try this will succeed! 46 | 47 | \begin{itemize} 48 | \item This is because most of this project are created by IT people who don't really use a business model that is correct for their project. 49 | 50 | \item Only 8\% of the IT budget create new successful projects, this is a third of the new project. 75\% of the IT-budget is needed to maintain your current IT-frame; 51 | \end{itemize} 52 | 53 | The problem: The gap between IT and business is too big with a lot of new IT projects! 54 | 55 | \begin{itemize} 56 | \item You need planning, resources and user involvement 57 | 58 | \item A project doesn't immediately work at start-up (unrealistic expectations). 59 | \end{itemize} 60 | 61 | \section{How big is the impact of IT?} 62 | 63 | \subsection{Macro-economic impact of IT:} 64 | 65 | The world became flat (See Toledo TheWorldIsFlat -- ThomasLFriedman) 66 | 67 | \begin{itemize} 68 | \item Communication between two places on earth is immediate 69 | \end{itemize} 70 | 71 | \subsection{Micro-economic impact of IT:} 72 | 73 | IT doesn't matter (See Toledo ITDoesntMatter -- NichalosGCarr) 74 | 75 | \begin{itemize} 76 | \item Follow IT advancement don't lead or you have a bigger chance to fail 77 | 78 | \item Invest only if others have succeeded! 79 | \end{itemize} 80 | 81 | Counter-perspective on IT doesn't matter 82 | 83 | \begin{itemize} 84 | \item The value of the IT is not in the technology itself but in the reasoning between your business model and your costumers to create a good business. 85 | 86 | \item The article of Nichalos Carr was written after the `dotcom bubble' where a lot of IT businesses went bankrupt. 87 | 88 | \item If you look at the current businesses we do find that IT is productive 89 | 90 | \item It is not only about automating your company with IT, you also need to rethink about your business model with recent IT technologies. 91 | 92 | \item IT doesn't only automate your company, but it can process all the new information a lot faster and efficient. 93 | \end{itemize} 94 | 95 | \section{What is an information system (IS)?} 96 | 97 | Data vs Information 98 | 99 | \begin{itemize} 100 | \item Data is raw observed facts without a real context/meaning 101 | 102 | \item Information is knowledge with a context that you can understand! 103 | \end{itemize} 104 | 105 | Metadata 106 | 107 | \begin{itemize} 108 | \item Making information more comprehensible to humans and computers 109 | 110 | \item Example: xml files 111 | \end{itemize} 112 | 113 | We need data/information but we also need a system 114 | 115 | \begin{itemize} 116 | \item You need elements, relations between these elements and a purpose for the system to work 117 | \end{itemize} 118 | 119 | \end{document} 120 | 121 | -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/BusinessInformationSystems/Notities Mathias/Les 2 - Information systems part 2.docx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/BusinessInformationSystems/Notities Mathias/Les 2 - Information systems part 2.docx -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/BusinessInformationSystems/Notities Mathias/Les 2 - Information systems part 2.tex: -------------------------------------------------------------------------------- 1 | \documentclass{article} 2 | \setlength\parindent{0pt} 3 | 4 | \begin{document} 5 | 6 | \section{Business Information systems} 7 | 8 | You need three components to create a system (see system les 1), difference with a business information system 9 | 10 | \begin{enumerate} 11 | \item Elements 12 | 13 | \item Relations: collect, search, process, store and distribute information. 14 | 15 | \item Purpose: control decision making processes and coordination. 16 | \end{enumerate} 17 | 18 | Input of the system is raw data without context and the system will process this to create relevant information for the business. 19 | 20 | \hfill \newline A business information system is a carbon copy of a business system but they don't exist physically anymore, they exist in IT. 21 | 22 | \begin{itemize} 23 | \item The copy of the business system must be perfect or the business information system will fail! 24 | \end{itemize} 25 | 26 | \section{Types of information systems} 27 | 28 | In many organizations are a lot of business information systems separate from each other. 29 | 30 | \begin{itemize} 31 | \item Example: Sales and Production 32 | \end{itemize} 33 | 34 | \subsection{Management level} 35 | 36 | \begin{itemize} 37 | \item Strategic: Long term decisions 38 | 39 | \item Tactical: Mid long term decisions (more internal) 40 | 41 | \item Operational: Daily operations and decisions with immediate results. 42 | \end{itemize} 43 | 44 | \subsection{Operational information systems} 45 | 46 | This is typically information from inside the company (see slides for info) 47 | 48 | \hfill \newline 49 | Example: Online Transaction system: Monthly pay check for employees 50 | 51 | \subsection{Enterprise resource planning systems (ERP)} 52 | 53 | For any functional area (Sales, Finance, Human recourses, Production), you will use the same centralised database so the systems are not separated. 54 | 55 | \hfill \newline 56 | A lot of companies use the same information to run the company. Plain vanilla ERP systems are such ``off the shelf'' systems that almost every company can use without any configuration specific for the company. 57 | 58 | \hfill \newline 59 | You need this type of system to support the next systems which are more advanced (Management systems and executive systems) 60 | 61 | \subsection{Information systems on tactical levels} 62 | 63 | Tactical decisions that are decided every month, like do we need to change something? Do we need to adept? 64 | 65 | \hfill \newline 66 | This information is not always ``clear'', you often need humans to make tactical decisions. It is also possible that you need external information for a tactical decision. 67 | 68 | \hfill \newline 69 | Management information system: 70 | 71 | \begin{itemize} 72 | \item A system that covers almost the complete company to make decisions 73 | 74 | \item Outputs reports, charts or a summary which is often used by managers to create a decision or track the decisions that they made before. 75 | 76 | \item The output is often in real-time for quick decision making 77 | \end{itemize} 78 | 79 | Decision support system: 80 | 81 | \begin{itemize} 82 | \item A system that covers a specific area of the company 83 | 84 | \item Makes special reports of simulations of what may happen with the current course of business model. These are tailored to a specific system. 85 | 86 | \item Example: How to ship your product to the client? Is it cheaper by plane, boat or maybe truck? The system will recalculate to make adaptions. These are not everyday calculations. 87 | \end{itemize} 88 | 89 | \subsection{Strategic information systems} 90 | 91 | These systems are difficult to make and are really advances because you need a lot of information. 92 | 93 | \hfill \newline 94 | The system needs to process a lot of information and get the information to make a decision to maybe change your production plan (very drastic decision). 95 | 96 | \hfill \newline 97 | Executive support system: 98 | 99 | \begin{itemize} 100 | \item Communication and calculations on strategic levels 101 | 102 | \item Looks like a management information system but is far more advanced because it searches and uses the correct information to make a decision. (a lot of information processing) 103 | \end{itemize} 104 | 105 | \subsection{Other systems} 106 | 107 | Office Automation Systems: 108 | 109 | \begin{itemize} 110 | \item Is used by almost all people in the company 111 | 112 | \item Office, email client, \dots 113 | \end{itemize} 114 | 115 | Knowledge work systems: 116 | 117 | \begin{itemize} 118 | \item Specialized systems for a specific job 119 | \end{itemize} 120 | 121 | \section{Information systems strategy} 122 | 123 | \subsection{How are information systems developed?} 124 | 125 | \paragraph{Porter priority model:} 126 | 127 | \begin{itemize} 128 | \item Threat of new entrants 129 | 130 | \begin{itemize} 131 | \item How difficult it is to access an industry 132 | 133 | \item Create a new pizza company: fairly easy 134 | 135 | \item Create a new chip company: almost impossible because of a lot of research, knowledge and money 136 | \end{itemize} 137 | 138 | \item Bargaining power of suppliers 139 | 140 | \begin{itemize} 141 | \item Many types of companies with a lot of competition vs monopoly 142 | 143 | \item Consequence: different prices and quality 144 | 145 | \item The company needs to have a system that is profitable. 146 | \end{itemize} 147 | 148 | \item Bargaining power of buyers 149 | 150 | \begin{itemize} 151 | \item How sensitive costumers are to buy a product 152 | 153 | \item If costumers are willing to pay a high price, the company can sell their product for a high price (example: Apple) 154 | \end{itemize} 155 | 156 | \item Threat of substitute products or services 157 | 158 | \begin{itemize} 159 | \item New services may cause a huge problem for current organisation because the new service is a lot more efficient. 160 | 161 | \item Example: Airlines vs collaborative video meeting solutions 162 | 163 | \item Example: Taxi companies vs Uber 164 | \end{itemize} 165 | 166 | \item Rivalry among existing competitors 167 | 168 | \begin{itemize} 169 | \item How do you compete with the current competitors? 170 | 171 | \item Can the organisations avoid competing about the price, if this is the case it may destroy the industry because the prices aren't profitable anymore. 172 | 173 | \item Counter-logical strategy: Colruyt =$>$ lowest price, by saying this they avoid a price wars because they say that they will always have the lowest price. 174 | \end{itemize} 175 | \end{itemize} 176 | 177 | \paragraph{Porter's competitive forces theory: Summary} 178 | 179 | \begin{itemize} 180 | \item + : Generic, applicable to any company in any industry 181 | 182 | \item + : Provides detailed explanations for firm/industry profitability 183 | 184 | \item + : Reason about an organisation's strategic position with respect to its external environment 185 | 186 | \item -- : Of limited use for determining future strategy 187 | 188 | \item -- : Few concrete guidelines on how to operationalize 189 | \end{itemize} 190 | 191 | \section{Competitive advantage and information systems} 192 | 193 | \subsection{Value chain model} 194 | 195 | Sequence of activities through which inputs are transformed into more valuable outputs. 196 | 197 | \hfill \newline 198 | This value chain doesn't exist on its own, you don't only need to look internally also externally. You need a value chain system which brings together the value chain of the suppliers, customers and your own. And also the value chains of your competitors. 199 | 200 | \hfill \newline 201 | A value chain on its own is useless and thus cannot be used to create efficient decisions. 202 | 203 | \hfill \newline 204 | Value Chain + Information system 205 | 206 | \begin{itemize} 207 | \item Create and sustain your current business model without losing to the competition. 208 | \end{itemize} 209 | 210 | \end{document} 211 | 212 | -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/BusinessInformationSystems/Notities Mathias/Les 3 - Information systems part 3.docx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/BusinessInformationSystems/Notities Mathias/Les 3 - Information systems part 3.docx -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/BusinessInformationSystems/Notities Mathias/Les 3 - Information systems part 3.tex: -------------------------------------------------------------------------------- 1 | \documentclass{article} 2 | \setlength\parindent{0pt} 3 | 4 | \begin{document} 5 | 6 | \section {Value chain \& information systems} 7 | 8 | \subsection{Primary activities} 9 | 10 | Inbound logistics (getting resources and checking them to sell) 11 | 12 | \begin{itemize} 13 | \item Example: Delhaize automating a factory, able to deliver fresher products. 14 | 15 | \begin{itemize} 16 | \item Rivalry among existing competition =$>$ Delhaize has fresh products 17 | 18 | \item Threat of New entrants =$>$ Delhaize invested a lot, this discourages new companies to try to setup something equal. 19 | 20 | \item Bargaining power of buyers =$>$ they have the freshest products, so they can raise their price. 21 | \end{itemize} 22 | \end{itemize} 23 | 24 | Operations (how to make the product, with manufacturing and maintenance) 25 | 26 | \begin{itemize} 27 | \item Example: Ryanair will only serve their customers through their website 28 | \end{itemize} 29 | 30 | Outbound logistics (delivering the product or service) 31 | 32 | \begin{itemize} 33 | \item Example: Amazon wants to use drones to deliver their products, they even claim that they know what you will buy before you even click the order button. 34 | \end{itemize} 35 | 36 | Marketing and Sales (promoting and selling products) 37 | 38 | \begin{itemize} 39 | \item Example: Colruyt delivers \underbar{personalized} folders with promotions! 40 | \end{itemize} 41 | 42 | Customer service 43 | 44 | \begin{itemize} 45 | \item Example: Booking.com where they ask the costumers for feedback, so they can get a lot of information about the hotels and costumers. 46 | \end{itemize} 47 | 48 | \subsection{Support activities} 49 | 50 | HR analytics 51 | 52 | \begin{itemize} 53 | \item Gaining knowledge about which employee may leave the company 54 | 55 | \item With this information you can attract new employees and create a good environment so your employees don't leave 56 | \end{itemize} 57 | 58 | \subsection{Key message} 59 | 60 | \begin{itemize} 61 | \item Alignment between your business model and your IT strategy is needed for your organization to be successful 62 | \end{itemize} 63 | 64 | \section{Linking business \& IS strategy} 65 | 66 | \subsection{Strategic alignment model} 67 | 68 | The ICT strategy is created with respect to the external market and what other competitors do. 69 | 70 | \hfill \newline 71 | Two models: 72 | 73 | \begin{itemize} 74 | \item Strategic fit (Business) 75 | 76 | \begin{itemize} 77 | \item How your strategy matches with your business model. 78 | \end{itemize} 79 | 80 | \item Strategic fit (IT) 81 | 82 | \begin{itemize} 83 | \item How your IT strategy matches with your operations 84 | \end{itemize} 85 | 86 | \item Functional fit 87 | 88 | \begin{itemize} 89 | \item Whether your business model and IT strategy are aligned. 90 | \end{itemize} 91 | \end{itemize} 92 | 93 | \subsection{Strategic transformation} 94 | 95 | \begin{itemize} 96 | \item First create business model and then setup your ICT operations to support this model 97 | \end{itemize} 98 | 99 | \subsection{Technology transformation} 100 | 101 | \begin{itemize} 102 | \item Create an ICT infrastructure to accomplish your business model 103 | \end{itemize} 104 | 105 | \subsection{Competitive potential} 106 | 107 | \begin{itemize} 108 | \item What technologies do I already have to create a good business model around it. 109 | \end{itemize} 110 | 111 | \subsection{Service level} 112 | 113 | \begin{itemize} 114 | \item Create an ICT strategy, create and develop the system and notice that you can sell this technology to other companies. (You create a business system around it) 115 | \end{itemize} 116 | 117 | \section{IT governance} 118 | 119 | \subsection{Governance} 120 | 121 | Governance is a control system to decide about IT and business strategy and making sure that the strategy is executed. 122 | 123 | \hfill \newline 124 | Corporate governance and fraud 125 | 126 | \begin{itemize} 127 | \item Led to new regulations (SOX) 128 | \end{itemize} 129 | 130 | \subsection{Internal control (structure)} 131 | 132 | A dynamic process that is effected by the board of directors, designed to provide reasonable assurance regarding the achievement of objectives relating to everything about running a business. 133 | 134 | \hfill \newline 135 | Build frameworks that allow organizations to demonstrate that this control system is in place. 136 | 137 | \begin{itemize} 138 | \item COSO internal control (framework) 139 | 140 | \begin{itemize} 141 | \item Demonstrates that the SOX compliance is in place. 142 | 143 | \item No IT 144 | \end{itemize} 145 | \end{itemize} 146 | 147 | \subsection{IT governance} 148 | 149 | IT governance is the organizational capacity exercised by the board of directors, executive management and IT management to control the formulation and implementation of IT strategy and in this way ensure the fusion of business and IT. 150 | 151 | \begin{itemize} 152 | \item Goal: 153 | 154 | \begin{itemize} 155 | \item Better organizational performance 156 | 157 | \item Better alignment between your business and IT 158 | \end{itemize} 159 | \end{itemize} 160 | 161 | COBIT 162 | 163 | \begin{itemize} 164 | \item show compliance with the SOX act 165 | 166 | \item professional framework 167 | \end{itemize} 168 | 169 | COBIT principles 170 | 171 | \begin{itemize} 172 | \item read text Toledo 173 | \end{itemize} 174 | 175 | \end{document} 176 | 177 | -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/BusinessInformationSystems/Notities Midas/.gitignore: -------------------------------------------------------------------------------- 1 | *.bbl 2 | *.blg 3 | *.toc -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/BusinessInformationSystems/Notities Midas/BIS.tex: -------------------------------------------------------------------------------- 1 | %% Based on a TeXnicCenter-Template by Tino Weinkauf. 2 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 3 | 4 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 5 | %% HEADER 6 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 7 | \documentclass[a4paper,twoside,10pt]{report} 8 | % Alternative Options: 9 | % Paper Size: a4paper / a5paper / b5paper / letterpaper / legalpaper / executivepaper 10 | % Duplex: oneside / twoside 11 | % Base Font Size: 10pt / 11pt / 12pt 12 | 13 | 14 | %% Language %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 15 | \usepackage[USenglish]{babel} %francais, polish, spanish, ... 16 | \usepackage[T1]{fontenc} 17 | \usepackage[ansinew]{inputenc} 18 | 19 | 20 | 21 | \usepackage{lmodern} %Type1-font for non-english texts and characters 22 | 23 | 24 | 25 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 26 | %% DOCUMENT 27 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 28 | \begin{document} 29 | 30 | \pagestyle{empty} %No headings for the first pages. 31 | 32 | 33 | %% Title Page %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 34 | %% ==> Write your text here or include other files. 35 | 36 | %% The simple version: 37 | \title{Business Information Systems \\ 2015-2016} 38 | \author{Midas Lambrichts} 39 | %\date{} %%If commented, the current date is used. 40 | \maketitle 41 | 42 | 43 | %% Inhaltsverzeichnis %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 44 | \tableofcontents %Table of contents 45 | \cleardoublepage %The first chapter should start on an odd page. 46 | 47 | \pagestyle{plain} %Now display headings: headings / fancy / ... 48 | 49 | 50 | \chapter{Business Intelligence and Data Analytics} 51 | \section{Business Intelligence} 52 | \subsection{Intro} 53 | \begin{itemize} 54 | \item Until 1990, organisations invested in IT to increase efficiency/production. 55 | \item After 1990, analyzing the data become more important $\Rightarrow$ Transactional systems were not good for this $\Rightarrow$ even more pressure. 56 | \end{itemize} 57 | 58 | In Business Intelligence, you need to query a lot of data (which are all transactions) $\Rightarrow$ You need high performance queries $\Leftrightarrow$ Normalised database would require lot of (time consuming) JOINS. 59 | \\ 60 | A transactional system is a system which queries 1 record at a time. 61 | 62 | \subsection{Business Intelligence Techniques} 63 | \begin{itemize} 64 | \item \textbf{Verifaction based techniques:} Shows what we already know, does not generate new data. Summarize already existing data. Used for reporting. 65 | \item \textbf{Disovery based techniques:} Generates new data, shows new things. (e.g. Will people leave the company) 66 | \end{itemize} 67 | \subsubsection{Verification based techniques} 68 | \paragraph{Enterprise reporting} Analytic applications that offer ready-made report templates for industry specific metrics and thresholds for alerts. \\ 69 | Examples: 70 | \begin{itemize} 71 | \item Balanced scoreboards 72 | \item Digital dashboards 73 | \item Customized reports 74 | \end{itemize} 75 | \subparagraph{Balanced scorecards} 76 | \begin{itemize} 77 | \item Strategic level BI technique! 78 | \item Provides overall view of company $\rightarrow$ See how well company is performing. 79 | \end{itemize} 80 | \subparagraph{Digital dashboards or BI dashboards} 81 | \begin{itemize} 82 | \item Visual representation of information. 83 | \item Tailor-mode for each organisation. 84 | \item Often browser based. 85 | \end{itemize} 86 | 87 | \paragraph{Corporate Performance Management} 88 | \begin{itemize} 89 | \item Tactical level (Sales, products,...) 90 | \item Dashboard for operations $\rightarrow$ NOT strategic. 91 | \item More detailed than balanced scorecards. 92 | \item Functionally oriented. 93 | \end{itemize} 94 | \subparagraph{Businesss Activity Monitoring} 95 | \begin{itemize} 96 | \item Real-time reporting. 97 | \item Summary statistics. 98 | \item Operational level 99 | \end{itemize} 100 | 101 | \paragraph{OLAP} 102 | \begin{itemize} 103 | \item \textbf{OLAP:} \textbf{O}n\textbf{L}ine \textbf{A}nalytical \textbf{P}rocessing. 104 | \item Interactively and dynamically querying organizational databases 105 | \item OLAP cube 106 | \end{itemize} 107 | 108 | \paragraph{Data mining} 109 | \begin{itemize} 110 | \item BI software includes techniques that can be used for the exploration and analysis of large amounts of data, not just producing or querying information (understanding what happens), but also knowledge (understanding which actions to take). 111 | \end{itemize} 112 | 113 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 114 | \section{Data Warehousing} 115 | %--------------------------------------------- 116 | \subsection{Introduction} 117 | In a transactional system, everything is often silo'd, instead, we can use one big database, a \textbf{Data Warehouse database} 118 | \begin{itemize} 119 | \item Data warehousing is the design and exploitation of a data warehouse database, with 120 | \begin{itemize} 121 | \item Data from operational (OLTP) databases 122 | \item Enriched with data from other sources 123 | \end{itemize} 124 | \item Organized around the most important subjects of a company, instead of applications and systems. 125 | \end{itemize} 126 | %-------------------------- 127 | \subsection{OLTP vs OLAP} 128 | \textbf{OLTP:} 129 | \begin{itemize} 130 | \item Designed to support daily operations 131 | \item Ensure fast, concurrent access to data 132 | \item Normalization is crucial (Preventing anomalies) 133 | \item $\Rightarrow$ Poor performance for executing more complex queries. 134 | \end{itemize} 135 | ~\\ 136 | \textbf{OLAP:} (Data warehouse) 137 | \begin{itemize} 138 | \item Focused on analytical queries 139 | \item Queries involve aggregation (Traversing all records) 140 | \item $\Rightarrow$ Normalization would be suboptimal because of high number of joins. 141 | \item $\Rightarrow$ Anomalies are impossible because you only add records, not change them. 142 | \end{itemize} 143 | 144 | \paragraph{Data warehouse} 145 | \textbf{``A subject-oriented, integrated, time-variant, and non-volatile 146 | collection of data in support of management's decision-making 147 | process''} \\ 148 | The purpose of a warehouse is to integrate data from various sources into a uniform view. It is centralized and cross functional. \\ 149 | Examples of data sources are: OLTP systems, Legacy systems, External data,... \\ 150 | The \textbf{Data integration} is about 80\% of the data warehouse building effort. It is dificult because of lack of metadata, bad data quality, different codings, inconsistent semantics,... 151 | 152 | 153 | 154 | \section{Data Analytics} 155 | 156 | \end{document} 157 | 158 | -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/BusinessInformationSystems/Notities Midas/Keywords.tex: -------------------------------------------------------------------------------- 1 | \documentclass[]{report} 2 | 3 | \begin{document} 4 | \section{UML} 5 | \begin{itemize} 6 | \item \textbf{Complete}: A superclass is abstract, all instances are one of the subclasses $\leftrightarrow$ \textbf{Incomplete} 7 | \item \textbf{Disjoint}: No object can be in two subclasses at the same time $\leftrightarrow$ \textbf{Overlap} 8 | \end{itemize} 9 | 10 | \section{Logical Data Modeling} 11 | \begin{itemize} 12 | \item \textbf{Candidate key}: A minimal (no attribute can be removed) determinant (uniquely identifies) of a relation. 13 | \item \textbf{Primary key}: An assigned Candidate key. 14 | \item \textbf{Alternate key}: All Candidate keys except for the primary key. 15 | \item \textbf{Foreign key}: Set of attributes in a relation that refers to a Primary key in another relation. 16 | \end{itemize} 17 | 18 | \subsection{Normalisation} 19 | \begin{itemize} 20 | \item \textbf{First Normal Form} 21 | \begin{itemize} 22 | \item Each attribute is atomic 23 | \item Each attribute contains 1 value (so no 2 locations in location column) 24 | \end{itemize} 25 | \item Second Normal Form 26 | \begin{itemize} 27 | \item In First Normal Form 28 | \item Full functional dependency from the key (If only dependent on part of key, split away) 29 | \end{itemize} 30 | \item \textbf{Third Normal Form} 31 | \begin{itemize} 32 | \item In Second Normal Form 33 | \item No transitive dependencies (Professor(\textbf{EmpID}, EmpName, \textbf{Faculty}, \textbf{FacultyWebSite})) 34 | \end{itemize} 35 | \end{itemize} 36 | 37 | \chapter{BI and Data Analytics} 38 | \section{Business Intelligence} 39 | \begin{itemize} 40 | \item BI: Interactive process for exploring, analyzing, and reporting data. Deriving insights and drawing conclusions. 41 | \item Developed to support strategical and tactical decisions and to asses business performance. 42 | \item Verification based and Discovery based techniques. 43 | \end{itemize} 44 | 45 | \section{Data Warehousing} 46 | \begin{itemize} 47 | \item OLTP (On-line Transaction Processing) 48 | \begin{itemize} 49 | \item Normalization! 50 | \item Fast concurrent data acces 51 | \item Poor performance with lots of joins 52 | \end{itemize} 53 | \item OLAP (On-line Analytical Processing) 54 | \begin{itemize} 55 | \item Focused on analytical queries. 56 | \item No normalization. 57 | \end{itemize} 58 | \item Data Warehouse: 59 | \begin{itemize} 60 | \item Data integration: 80\% of building effort. 61 | \item Time variant: snapshots 62 | \item Non-volatile 63 | \end{itemize} 64 | \item Logical Data warehouse design 65 | \begin{itemize} 66 | \item Relational OLAP (ROLAP) 67 | \begin{itemize} 68 | \item Star schema: Facts table (normalized) + Dimension tables (Not normalized) 69 | \item Snowflake schema: Star schema with normalized dimension tables. 70 | \end{itemize} 71 | \item Multidimensionsal OLAP (MOLAP) 72 | \item Hybrid OLAP (HOLAP) 73 | \item OLAP operations: 74 | \begin{itemize} 75 | \item Roll up: Aggregate dimensions into fewer (Cities $\rightarrow$ Countries) 76 | \item Drill down: Reverse of Roll up 77 | \item Slice: For only 1 item of a certain dimensions, removes a dimension (Look at the results where City= Paris) 78 | \item Dice: Look at results for a subset. (City = Paris or Lyon and Quarter = Q1 or Q3) 79 | \end{itemize} 80 | \end{itemize} 81 | \item Data Staging: 82 | \begin{itemize} 83 | \item Data cleaning (KUL, KU Leuven,...) 84 | \item Data transformation 85 | \item Load 86 | \item Refresh 87 | \end{itemize} 88 | \item Data mart: Supports decisions of a specific group and is a part of the warehouse. 89 | \item Data warehouse usage: 90 | \begin{itemize} 91 | \item Verification and Discovery 92 | \end{itemize} 93 | 94 | \end{itemize} 95 | 96 | 97 | \section{Data Analytics} 98 | \subsection{Big Data} 99 | \begin{itemize} 100 | \item Huge: Shitton of data 101 | \item Everywhere: Data is acquired everywhere 102 | \item Job oppertunities are sky-rocketing: High demand for Big Data Analysis skills 103 | \item Scary: 104 | \item Promising: New insights and discoveries 105 | \end{itemize} 106 | 107 | \subsection{Knowledge Discovery in Databases (KDD)} 108 | \begin{itemize} 109 | \item Process of automatically identifying models and patterns from massive observational databases that are: Valid (Holds on new data as well), Novel (Not obvious), Useful, Understandable. 110 | \item Data Pre-processing: 111 | \begin{itemize} 112 | \item How to deal with missing values? 113 | \item What to do with Outliers? 114 | \item Defintion of target variable? (What is a "churner"?) 115 | \end{itemize} 116 | \item Data mining tasks: 117 | \begin{itemize} 118 | \item Predictive methods (supervised) 119 | \begin{itemize} 120 | \item Learn based on labeled data (Good-Bad is known) 121 | \end{itemize} 122 | \item Descriptive methods (unsupervised) 123 | \end{itemize} 124 | \end{itemize} 125 | \subsection{Predictive Data mining} 126 | 127 | 128 | 129 | \chapter{Powerpoint exercises} 130 | \begin{itemize} 131 | \item PPT 5B slide 41: Impurities 132 | \end{itemize} 133 | 134 | 135 | 136 | D&M 137 | 138 | System Quality 139 | Information Quality 140 | Service Quality 141 | Intention to use 142 | User Satisfaction 143 | Net Benefits 144 | 145 | 146 | TAM 147 | Perceived usefulness 148 | Perceived ease of use 149 | Attitude 150 | Behavioral intentions 151 | actual use 152 | 153 | \end{document} 154 | -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/BusinessInformationSystems/README.md: -------------------------------------------------------------------------------- 1 | #Business Information Systems 2 | 3 | #Summary on the Ekowiki 4 | [Ekowiki](http://ekowiki.ekonomika.be/wiki/index.php?title=Business_Information_Systems) 5 | 6 | #Summary from few years ago (dropbox): 7 | [Link](https://www.dropbox.com/sh/3c08ajx4nuxdo23/AABKnINBc9agQPiaOkEYh21Qa?dl=0) 8 | -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/LineaireOptimalisatie/Oefeningen/H3/3.2.mod: -------------------------------------------------------------------------------- 1 | /********************************************* 2 | * OPL 12.5.1.0 Model 3 | * Author: Stijn 4 | * Creation Date: 15-dec.-2015 at 20:48:24 5 | *********************************************/ 6 | 7 | int nbLegeringen = 2; 8 | int nbMetalen = 4; 9 | int nbErtsen = 3; 10 | 11 | range legeringen = 1..nbLegeringen; 12 | range metalen = 1..nbMetalen; 13 | range ertsen = 1..nbErtsen; 14 | 15 | dvar float+ mengen[legeringen, metalen]; 16 | dvar float+ erts[ertsen]; 17 | int kostErts[1..3] = [900, 1200, 1500]; 18 | 19 | dvar float winst; 20 | 21 | maximize winst; 22 | 23 | subject to { 24 | 25 | winst == -sum(i in ertsen)(kostErts[i]*erts[i]) + 8000*(sum(m in metalen)(mengen[1, m])) + 9000*(sum(m in metalen)(mengen[2, m])); 26 | 27 | sum(m in metalen)(mengen[1, m]) >= 1000; 28 | sum(m in metalen)(mengen[2, m]) >= 2000; 29 | 30 | forall(i in ertsen) { 31 | erts[i] <= 2000; 32 | } 33 | 34 | mengen[1, 1] <= 0.10 * (sum(m in metalen)(mengen[1, m])); 35 | mengen[1, 2] <= 0.10 * (sum(m in metalen)(mengen[1, m])); 36 | mengen[1, 4] >= 0.25 * (sum(m in metalen)(mengen[1, m])); 37 | 38 | mengen[2, 2] >= 0.10 * (sum(m in metalen)(mengen[2, m])); 39 | mengen[2, 3] >= 0.35 * (sum(m in metalen)(mengen[2, m])); 40 | mengen[2, 4] <= 0.25 * (sum(m in metalen)(mengen[2, m])); 41 | 42 | mengen[1,1] + mengen[2, 1] <= 0.20*erts[1] + 0.10*erts[2] + 0.05*erts[3]; 43 | mengen[1,2] + mengen[2, 2] <= 0.10*erts[1] + 0.20*erts[2] + 0.05*erts[3]; 44 | mengen[1,3] + mengen[2, 3] <= 0.30*erts[1] + 0.30*erts[2] + 0.70*erts[3]; 45 | mengen[1,4] + mengen[2, 4] <= 0.30*erts[1] + 0.30*erts[2] + 0.20*erts[3]; 46 | } -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/LineaireOptimalisatie/Oefeningen/H3/3.21.dat: -------------------------------------------------------------------------------- 1 | /********************************************* 2 | * OPL 12.5.1.0 Data 3 | * Author: Stijn 4 | * Creation Date: 16-dec.-2015 at 21:46:52 5 | *********************************************/ 6 | nbAfdelingen = 2; 7 | nbDelen = 3; 8 | 9 | SheetConnection bestand("3.21.xlsx"); 10 | productieritme from SheetRead(bestand, "C2:E3"); 11 | capaciteit from SheetRead(bestand, "B2:B3"); 12 | 13 | uren to SheetWrite(bestand, "F2:F3"); -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/LineaireOptimalisatie/Oefeningen/H3/3.21.mod: -------------------------------------------------------------------------------- 1 | /********************************************* 2 | * OPL 12.5.1.0 Model 3 | * Author: Stijn 4 | * Creation Date: 16-dec.-2015 at 20:27:36 5 | *********************************************/ 6 | int nbAfdelingen = ...; 7 | range afdelingen = 1 .. nbAfdelingen; 8 | 9 | int nbDelen = ...; 10 | range delen = 1 .. nbDelen; 11 | 12 | int productieritme[afdelingen][delen] = ...; 13 | int capaciteit[afdelingen] = ...; 14 | 15 | dvar float+ uren[afdelingen]; 16 | dvar float+ verschil[delen][delen]; 17 | 18 | dvar float totaalVerschil; 19 | 20 | minimize totaalVerschil; 21 | 22 | subject to { 23 | totaalVerschil == sum(d in delen, e in delen)(verschil[d][e]); 24 | 25 | forall(d in delen, e in delen) { 26 | verschil[d, e] >= sum(a in afdelingen)(uren[a] * (productieritme[a][d] - productieritme[a][e])); 27 | } 28 | 29 | forall(a in afdelingen) { 30 | uren[a] <= capaciteit[a]; 31 | } 32 | 33 | forall(d in delen) { 34 | sum(a in afdelingen)(productieritme[a][d] * uren[a]) >= 1000; 35 | } 36 | } -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/LineaireOptimalisatie/Oefeningen/H3/3.21.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/LineaireOptimalisatie/Oefeningen/H3/3.21.xlsx -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/LineaireOptimalisatie/Oefeningen/H3/3.3.mod: -------------------------------------------------------------------------------- 1 | /********************************************* 2 | * OPL 12.5.1.0 Model 3 | * Author: Stijn 4 | * Creation Date: 16-dec.-2015 at 15:14:14 5 | *********************************************/ 6 | 7 | 8 | 9 | dvar float winst; 10 | dvar float+ reclameHuis; 11 | dvar float+ reclameBenz; 12 | dvar float+ mengen[1..2][1..2]; 13 | /* mengen[huisbrandolie/benzine][olie1/olie2] */ 14 | 15 | maximize winst; 16 | 17 | subject to { 18 | winst == 75 * sum(i in 1..2)(mengen[2][i]) + 60 * sum(i in 1..2)(mengen[1][i]) - reclameBenz - reclameHuis; 19 | sum(i in 1..2)(mengen[1][i]) <= 10 * reclameHuis; 20 | sum(i in 1..2)(mengen[2][i]) <= 5 * reclameBenz; 21 | 22 | (10 * mengen[1][1] + 2 * mengen[1][2]) >= 6 * sum(i in 1..2)(mengen[1][i]); 23 | (10 * mengen[2][1] + 2 * mengen[2][2]) >= 8 * sum(i in 1..2)(mengen[2][i]); 24 | 25 | sum(i in 1..2)(mengen[i][1]) <= 5000; 26 | sum(i in 1..2)(mengen[i][1]) <= 10000; 27 | } -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/LineaireOptimalisatie/Oefeningen/H3/3.5.dat: -------------------------------------------------------------------------------- 1 | /********************************************* 2 | * OPL 12.5.1.0 Data 3 | * Author: Stijn 4 | * Creation Date: 16-dec.-2015 at 16:49:23 5 | *********************************************/ 6 | 7 | nbInspecteurs = 3; 8 | 9 | SheetConnection bestand("3.5.xlsx"); 10 | 11 | // uurloon = [18, 12, 21]; 12 | // snelheid = [360, 270, 210]; 13 | // accuraatheid = [0.98, 0.99, 96]; 14 | 15 | uurloon from SheetRead(bestand, "D2:D4"); 16 | snelheid from SheetRead(bestand, "B2:B4"); 17 | accuraatheid from SheetRead(bestand, "C2:C4"); 18 | 19 | werkuren to SheetWrite(bestand, "E2:E4"); -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/LineaireOptimalisatie/Oefeningen/H3/3.5.mod: -------------------------------------------------------------------------------- 1 | /********************************************* 2 | * OPL 12.5.1.0 Model 3 | * Author: Stijn 4 | * Creation Date: 16-dec.-2015 at 15:48:29 5 | *********************************************/ 6 | 7 | int nbInspecteurs = ...; 8 | range inspecteurs = 1..nbInspecteurs; 9 | 10 | dvar float+ werkuren[inspecteurs]; 11 | float uurloon[inspecteurs] = ...; 12 | float snelheid[inspecteurs] = ...; 13 | float accuraatheid[inspecteurs] = ...; 14 | 15 | dvar float kost; 16 | 17 | minimize kost; 18 | 19 | subject to { 20 | kost == sum(i in inspecteurs)(uurloon[i] * werkuren[i]); 21 | 22 | sum(i in inspecteurs)(werkuren[i]) <= 8; 23 | sum(i in inspecteurs)(werkuren[i] * snelheid[i]) >= 1800; 24 | forall(i in inspecteurs) { 25 | werkuren[i] <= 4; 26 | } 27 | 28 | sum(i in inspecteurs)(werkuren[i] * snelheid[i] * accuraatheid[i]) >= 0.98 * sum(i in inspecteurs)(werkuren[i] * snelheid[i]); 29 | } -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/LineaireOptimalisatie/Oefeningen/H3/3.5.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/LineaireOptimalisatie/Oefeningen/H3/3.5.xlsx -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/LineaireOptimalisatie/Oefeningen/H3/3.7.dat: -------------------------------------------------------------------------------- 1 | /********************************************* 2 | * OPL 12.5.1.0 Data 3 | * Author: Stijn 4 | * Creation Date: 11-dec.-2015 at 21:01:59 5 | *********************************************/ 6 | 7 | nrPeriodes = 4; 8 | vraag = [4000, 2000, 3000, 10000]; -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/LineaireOptimalisatie/Oefeningen/H3/3.7.mod: -------------------------------------------------------------------------------- 1 | /********************************************* 2 | * OPL 12.5.1.0 Model 3 | * Author: Stijn 4 | * Creation Date: 11-dec.-2015 at 21:01:36 5 | *********************************************/ 6 | 7 | /** VRAAG: 4000 | 2000 | 3000 | 10000 */ 8 | 9 | /** VARIABELEN: werknemers in dienst die niet werken in een periode, voorraad 10 | * minimaliseer de kosten: aantal werknemers zo laag mogelijk, zo klein mogelijke opslag 11 | */ 12 | 13 | int nrPeriodes = ...; 14 | range periodes = 1..nrPeriodes; 15 | 16 | dvar float+ werknemersVerlof[periodes]; 17 | dvar float+ voorraad[periodes]; 18 | 19 | int vraag[periodes] = ...; 20 | 21 | minimize 8000 * sum(p in periodes)(werknemersVerlof[p]) + 5 * sum(p in periodes)(voorraad[p]); 22 | 23 | 24 | 25 | subject to { 26 | 500 * (sum(q in periodes)(werknemersVerlof[q]) - werknemersVerlof[1]) + 1000 - vraag[1] == voorraad[1]; 27 | forall(p in 2..nrPeriodes) { 28 | 500 * (sum(q in periodes)(werknemersVerlof[q]) - werknemersVerlof[p]) + voorraad[p-1] - vraag[p] == voorraad[p]; 29 | } 30 | 31 | // 500 * (werknemersVerlof[2] + werknemersVerlof[3] + werknemersVerlof[4]) + 1000 - vraag[1] == voorraad[1]; 32 | // 500 * (werknemersVerlof[1] + werknemersVerlof[3] + werknemersVerlof[4]) + voorraad[1] - vraag[2] == voorraad[2]; 33 | // 500 * (werknemersVerlof[1] + werknemersVerlof[2] + werknemersVerlof[4]) + voorraad[2] - vraag[3] == voorraad[3]; 34 | // 500 * (werknemersVerlof[1] + werknemersVerlof[2] + werknemersVerlof[3]) + voorraad[3] - vraag[4] == voorraad[4]; 35 | } -------------------------------------------------------------------------------- /Sem1/MinorVerbreding/KeuzeDeelBedrijfsEconomie/LineaireOptimalisatie/Samenvatting Midas/SuperSummary.tex: -------------------------------------------------------------------------------- 1 | \documentclass[10pt]{report} 2 | 3 | \usepackage{pdfpages} 4 | 5 | \begin{document} 6 | \titlepage 7 | 8 | \chapter{Algemene opmerkingen:} 9 | \includepdf[pages={2,4,6}, nup=2x3]{pdfFiles/Opmerkingen.pdf} 10 | 11 | \chapter{Hoofdstuk 6} 12 | \section{Twee fasen methode:} 13 | \begin{itemize} 14 | \item Als er constanten aan de rechterkant kleiner zijn dan nul. (eg: $ 5x_1 + 4x_2 \leq -5$) 15 | \item Introduceer hulpprobleem met $x_0$. Doelfunctie wordt: $min\; x_0$ en aan alle beperkingen wordt $-x_0$ toegevoegd. 16 | \item Kies als uitgaande degene met de meest negatieve waarde. 17 | \item Als de eerste fase afloopt en $x_0$ heeft een positieve waarde, dan kent het originele probleem geen toelaatbare oplossingen. 18 | \end{itemize} 19 | 20 | \chapter{Hoofdstuk 7} 21 | \section{Complementary Slackness} 22 | \begin{itemize} 23 | \item Als een optimale oplossing van de primaal groter dan nul is: Aan de overeenkomstige beperking van de duaal wordt voldaan. 24 | \item Als er te kort wordt gedaan aan de beperking (dus linkerdeel is niet gelijk aan rechterdeel), dan is de y van die rij 0. 25 | \item Dan moet er aan alle beperkingen worden voldaan met de gevonden oplossingen, en alle y's moeten positief zijn. 26 | \end{itemize} 27 | 28 | 29 | \chapter{Hoofdstuk 8} 30 | \section{Stabiliteitsinterval coefficient doelfunctie} 31 | \begin{itemize} 32 | \item Bepaal laatste dictionair, haal hier $B^{-1}$ uit. 33 | \item Bepaal $c_B$ door de coefficienten van de basisvariabelen uit de laatste dictionair, uit de doelfunctie te halen (vergeet delta niet!). 34 | \item Reken $c_N - c_B B^{-1} A_N$ uit voor de spelingsvariabelen. 35 | \item Hierbij is $c_N$ dus 0 en $A_N$ is $(1, 0, 0)^T,\; (0, 1, 0)^T, ...$ 36 | \item Stel de hierbij gevonden waarde $\leq 0$, om zo delta te bepalen. 37 | \end{itemize} 38 | 39 | \section{Stabiliteitsinterval b waarde} 40 | \begin{itemize} 41 | \item Reken $B^{-1} b$ uit (met delta!) 42 | \item Iedere rij moet $\geq 0$ zijn. 43 | \item Kan ook variabele invullen ipv waarde met delta! 44 | \end{itemize} 45 | 46 | \section{Stabiliteitsinterval a waarde} 47 | \begin{itemize} 48 | \item $a_{ij}$: ide rij, jde kolom 49 | \item Vindt optimale oplossing en vul in in relevante beperking. 50 | \item Vindt optimale oplossing duaal (compl slackness), vul in in relevante beperking. 51 | 52 | \end{itemize} 53 | 54 | \chapter{Hoofdstuk 9} 55 | \section{Spelstrategie} 56 | \begin{itemize} 57 | \item Matrix opstellen. 58 | \item Speel als rijspeler 59 | \item Primaal: max v; v $\leq$ kolom 1, ... 60 | \item Som van x = 1; 61 | \end{itemize} 62 | \end{document} 63 | -------------------------------------------------------------------------------- /Sem1/StatistiekEnWetenschap/Project/Titlepage.tex: -------------------------------------------------------------------------------- 1 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 2 | %Hoe te gebruiken%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 3 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 4 | %Gebruik dit .tex bestand als input (\intput{Titlepage.tex}) 5 | %na begin \begin{document}, in het hoofddocument, gebruik de 6 | %packages: \usepackage{standalone} en \usepackage{framed} 7 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 8 | 9 | 10 | \documentclass{article} 11 | 12 | 13 | \usepackage[paper=a4paper,top=2.85cm, right=2.5cm,left=2.5cm]{geometry} 14 | \usepackage{helvet} 15 | 16 | \renewcommand{\maketitle}{\bgroup\setlength{\parindent}{0pt} 17 | \begin{flushleft} 18 | \textbf{\@title} 19 | 20 | \@author 21 | \end{flushleft}\egroup 22 | } 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | \begin{document} 31 | \begin{titlepage} 32 | \renewcommand{\familydefault}{\sfdefault} 33 | \normalfont 34 | \begin{center} 35 | \begin{framed} 36 | \LARGE{ 37 | \vspace{0.7cm} 38 | G0N11C Statistiek \& data-analyse \\ 39 | Project eerste zittijd 2015-2016 40 | \vspace{0.8cm} 41 | }% 42 | \end{framed} 43 | \end{center} 44 | 45 | \vspace{0.7cm} 46 | \hfill 47 | \\ 48 | \large{ 49 | \textbf{Naam 1:} Naam1 \hfill \textbf{Studierichting 1:} richting 50 | \\ 51 | \hfill 52 | \\ 53 | \textbf{Naam 2:} Naam2 \hfill \textbf{Studierichting 2:} richting 54 | \\ 55 | \hfill 56 | \\ 57 | \textbf{Groepsnummer:} 000 58 | } 59 | \end{titlepage} 60 | %Resets the normal margins after the titlepage. 61 | 62 | 63 | 64 | \end{document} -------------------------------------------------------------------------------- /Sem1/StatistiekEnWetenschap/Samenvatting Kevin/README.md: -------------------------------------------------------------------------------- 1 | # Samenvatting statistiek 2 | Samenvatting is vooral gebaseerd op de belangrijkste delen van het boek, deze delen werden grotendeels letterlijk overgeschreven! 3 | Wie fouten ziet mag ze ook steeds aanpassen :) 4 | -------------------------------------------------------------------------------- /Sem1/StatistiekEnWetenschap/Samenvatting Kevin/images/boxplot.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem1/StatistiekEnWetenschap/Samenvatting Kevin/images/boxplot.png -------------------------------------------------------------------------------- /Sem1/StatistiekEnWetenschap/Samenvatting Kevin/voorblad.tex: -------------------------------------------------------------------------------- 1 | \newcommand{\HRule}{\rule{\linewidth}{0.5mm}} 2 | \center 3 | \textsc{\LARGE KU Leuven}\\[1.5cm] 4 | \textsc{\Large Informatica}\\[0.5cm] 5 | \textsc{\large Statiestiek en Data-analyse}\\[0.5cm] 6 | \HRule \\[0.4cm] 7 | { \huge \bfseries Samenvatting}\\[0.4cm]\HRule \\[1.5cm] 8 | \Large \emph{Autheur:}\\ 9 | Kevin \textsc{Coorens}\\[3cm] 10 | {\large \today}\\[2cm] 11 | \vfill 12 | -------------------------------------------------------------------------------- /Sem2/Gegevensbanken/Oefenzittingen/Oefenzitting5/Oefeningen/Oef1.tex: -------------------------------------------------------------------------------- 1 | \documentclass[../Oefenzitting5.tex]{subfiles} 2 | \begin{document} 3 | \subsection{Oefening 1:} 4 | \begin{enumerate}[label=\alph*)] 5 | \item 6 | $ 7 | \{ t | R(t) \wedge t.A = t.C \} 8 | $ 9 | \item 10 | $ 11 | \{ t.A, t.B | R(t) \} 12 | $ 13 | \item 14 | $ 15 | \{ t.A, t.B, t.C, s.D, s.E | R(t) \wedge S(s) \wedge t.C = s.C \} 16 | $ 17 | \item 18 | $ 19 | \{ t | R(t) \vee S(t) \} 20 | $ 21 | \item 22 | $ 23 | \{ t | R(t) \wedge S(t) \} 24 | $ 25 | \item 26 | $ 27 | \{ t | R(t) \wedge \neg S(t) \} 28 | $ 29 | \item 30 | $ 31 | \{ t,s | R(t) \wedge S(s) \} 32 | $ 33 | \item 34 | $ 35 | \{ t.B | R(t) \wedge \forall(s) (\neq S(s) \vee ( \exists (x) R(x) \wedge t.B = x.B \wedge x.A = s.A)) \} 36 | $ 37 | 38 | \end{enumerate} 39 | 40 | 41 | 42 | \end{document} 43 | -------------------------------------------------------------------------------- /Sem2/Gegevensbanken/Oefenzittingen/Oefenzitting5/Oefeningen/Oef2.tex: -------------------------------------------------------------------------------- 1 | \documentclass[../Oefenzitting5.tex]{subfiles} 2 | \begin{document} 3 | \subsection{Oefening 2:} 4 | \begin{enumerate} 5 | \item 6 | $ \{ t.Naam , t.Functie, s.Naam \mid M(t) \wedge A(s) \wedge t.Afd = s.Afnr \} $ 7 | 8 | \item 9 | % Niet zeker dat deze juist is 10 | $ \{ t.Naam \mid M(t) \wedge C(s) \wedge s.Type = BLD \wedge I(i) \wedge s.Code = i.Cursus\_code \wedge t.Mnr = i.Cursist \} $ 11 | 12 | \item 13 | $ \{ t.Naam \mid M(t) \wedge ((\exists{m}) (M(m) \wedge m.Chef = t.Mnr) \vee (\exists{u}) (U(u) \wedge u.Docent = m.Mnr )) \} $ 14 | 15 | \item 16 | $ \{ t.Naam \mid M(t) \wedge \neg (\exists{m})(M(m) \wedge m.Chef = t.Mnr) \wedge (\exists{n})(M(n) \wedge (\exists{o})(M(o) \wedge o.Chef = n.Mnr) \wedge n.Salaris < t.Salaris) \} $ 17 | 18 | \item 19 | $ \{ t.Naam \mid M(t) \wedge (\forall{c}) (C(c) \Rightarrow (\exists{i}) (I(i) \wedge c.Code = i.Cursus\_code \wedge i.Cursist = t.Mnr)) \} $ 20 | 21 | \item 22 | $ \{ t.Naam \mid M(t) \wedge (\forall{i}) (I(i) \wedge i.Cursist = t.Mnr \Rightarrow i.Evaluatie \geq 4) \} $ 23 | 24 | \item 25 | $ \{ c.Code, c.Omschrijving \mid C(c) \wedge (\forall{u}) (U(u) \wedge c.Code = u.Cursus\_code \Rightarrow u.Locatie = Leuven) \} $ 26 | 27 | \item 28 | $ \{ c.Code, c.Omschrijving \mid C(c) \wedge (\forall{m}) (M(M) \Rightarrow (\exists{i}) (I(i) \wedge m.Mnr = i.Cursist \wedge c.Code = i.Cursus\_code)) \} $ 29 | 30 | \end{enumerate} 31 | 32 | 33 | 34 | \end{document} 35 | -------------------------------------------------------------------------------- /Sem2/Gegevensbanken/Oefenzittingen/Oefenzitting5/Oefeningen/Oef3.tex: -------------------------------------------------------------------------------- 1 | \documentclass[../Oefenzitting5.tex]{subfiles} 2 | \begin{document} 3 | \subsection{Oefening 3:} 4 | \begin{enumerate} 5 | \item 6 | $ \{ t, s \mid Person(t) \wedge Parent\_of(s) \wedge t.Ssn = s.Pssn\} $ 7 | 8 | \item 9 | $ \{ t, s \mid Person(t) \wedge Works\_for(s) \wedge t.Ssn = s.Ssn \} $ 10 | 11 | \item 12 | \emph{null}-waarden kunnen niet uitgedrukt worden in relationele calculus, dus is een left-outer join niet mogelijk 13 | 14 | \end{enumerate} 15 | 16 | \end{document} 17 | -------------------------------------------------------------------------------- /Sem2/Gegevensbanken/Oefenzittingen/Oefenzitting5/Oefenzitting5.tex: -------------------------------------------------------------------------------- 1 | \documentclass{article} 2 | \usepackage{subfiles} 3 | \usepackage{enumitem} 4 | \begin{document} 5 | \section{Oefenzitting 5:} 6 | \subfile{Oefeningen/Oef1.tex} 7 | \subfile{Oefeningen/Oef2.tex} 8 | \subfile{Oefeningen/Oef3.tex} 9 | 10 | \end{document} 11 | -------------------------------------------------------------------------------- /Sem2/Gegevensbanken/Oefenzittingen/oefenzitting 3.sql: -------------------------------------------------------------------------------- 1 | # Exercise 6.16 a 2 | SELECT FName, LName 3 | FROM employee AS E INNER JOIN works_on AS W ON E.Ssn = W.ESsn 4 | INNER JOIN project AS P ON W.PNo = P.PNumber 5 | WHERE P.PName = 'ProductX' AND W.Hours >= 10 AND E.DNo = 5; 6 | 7 | # Exercise 6.16 b 8 | SELECT FName, LName 9 | FROM employee AS E INNER JOIN dependent AS D ON Ssn = ESsn 10 | WHERE E.FName = D.Dependent_Name; 11 | 12 | 13 | # Exercise 3.11 a 14 | -- OK 15 | INSERT INTO employee VALUES ('Robert', 'F', 'Scott', '943775543', '1972-06-21', '2365 Newcastle Rd, Bellaire, TX', 'M', 58000, '888665555', 1); 16 | 17 | # Exercise 3.11 b 18 | -- no department with DNum 2 ERROR 19 | INSERT INTO project VALUES ('ProductA', 4, 'Bellaire', 2); 20 | 21 | # Exercise 3.11 c 22 | -- Duplicate entry '4' for key 'PRIMARY' 23 | INSERT INTO department VALUES ('Production', 4, '943775543', '2007-10-01'); 24 | 25 | # Exercise 3.11 d 26 | -- Column 'PNo' cannot be null 27 | INSERT INTO works_on VALUES ('677678989', NULL, '40.0'); 28 | 29 | # Exercise 3.11 e 30 | -- OK 31 | INSERT INTO dependent VALUES ('453453453', 'John', 'M', '1990-12-12', 'spouse'); 32 | 33 | # Exercise 3.11 f 34 | -- 4 rijen verwijderd. 35 | DELETE FROM works_on WHERE ESsn = '333445555'; 36 | 37 | # Exercise 3.11 g 38 | -- Cannot delete or update a parent row: a foreign key constraint fails (`company`.`employee`, CONSTRAINT `employee_superssn` FOREIGN KEY (`SuperSsn`) REFERENCES `employee` (`Ssn`)) 39 | DELETE FROM employee WHERE Ssn = '987654321'; 40 | 41 | # Exercise 3.11 h 42 | -- Cannot delete or update a parent row: a foreign key constraint fails (`company`.`works_on`, CONSTRAINT `works_on_pno` FOREIGN KEY (`PNo`) REFERENCES `project` (`PNumber`)) 43 | DELETE FROM project WHERE PName = 'ProductX'; 44 | 45 | # Exercise 3.11 i 46 | -- 1 rij bijgewerkt 47 | UPDATE department SET MgrSsn = '123456789', MgrStartDate = '2007-10-01' WHERE DNumber = 5; 48 | 49 | # Exercise 3.11 j 50 | -- 1 rij bijgewerkt. 51 | UPDATE employee SET SuperSsn = '943775543' WHERE Ssn = '999887777'; 52 | 53 | # Exercise 3.11 k 54 | -- 1 rij bijgewerkt. 55 | UPDATE works_on SET Hours = '5.0' WHERE (ESsn = '999887777' AND PNo = 10); 56 | 57 | # Exercise 11 58 | SELECT FName, LName, sum(works_on.Hours) AS TotalHours FROM employee, works_on WHERE Ssn = ESsn GROUP BY Ssn -------------------------------------------------------------------------------- /Sem2/Gegevensbanken/Oefenzittingen/oefenzitting4.sql: -------------------------------------------------------------------------------- 1 | # Oef 1.1 en 1.2, zie oefenzitting 3 2 | 3 | # 1.3 4 | -- 3 resultaten 5 | SELECT `FName`,`LName` 6 | FROM `employee` 7 | WHERE `SuperSsn` IN 8 | (SELECT Ssn 9 | FROM `employee` 10 | WHERE `FName` = 'Franklin' AND `LName` = 'Wong') 11 | 12 | # 1.4 13 | -- GROUP BY collapsed op argument, SUM is nodig omdat SQL niet weet wat te doen met de columns die niet in het argument voorkomen. 14 | SELECT W.Pno, SUM(W.Hours) 15 | FROM `works_on` AS W JOIN `project` AS P ON W.Pno = P.Pnumber 16 | GROUP BY W.Pno 17 | 18 | -- 1.5 en 1.6 in omgewisselde volgorde omdat assistent dat zegt. 19 | # 1.6 20 | -- Omweg: 21 | SELECT * 22 | FROM `employee` AS E LEFT JOIN `works_on` AS W ON E.Ssn = W.Essn 23 | WHERE W.ESsn IS NULL 24 | 25 | -- Assistent zijn methode: 26 | SELECT `FName`,`LName` 27 | FROM `employee` AS E 28 | WHERE NOT EXISTS 29 | (SELECT W.ESsn 30 | FROM `works_on` AS W 31 | WHERE E.Ssn = W.Essn) 32 | 33 | # 1.5 34 | -- Uitleg? 35 | SELECT `FName`,`LName` 36 | FROM `employee` AS E 37 | WHERE NOT EXISTS 38 | (SELECT P.PNumber 39 | FROM `project` AS P 40 | WHERE NOT EXISTS 41 | (SELECT W.ESsn 42 | FROM `works_on` AS W 43 | WHERE E.Ssn = W.Essn AND W.PNo = P.PNumber)) 44 | 45 | # 1.7 46 | -- 47 | SELECT D.DName, AVG(E.Salary) 48 | FROM `department` AS D JOIN `employee` AS E ON D.Dnumber = E.Dno 49 | GROUP BY D.Dnumber 50 | 51 | # 1.8 52 | SELECT AVG(E.Salary) 53 | FROM `employee` AS E 54 | WHERE E.Sex = 'F' 55 | 56 | # 2.a 57 | SELECT D.DName AS 'Department Name', COUNT(E.Ssn) AS 'Number of Employees' 58 | FROM `department` AS D JOIN `employee` AS E ON D.Dnumber = E.Dno 59 | GROUP BY D.Dnumber 60 | HAVING AVG(E.Salary) > 30000 61 | 62 | # 2.b 63 | -- WHERE is applied voor GROUP BY 64 | SELECT D.DName AS 'Department Name', COUNT(E.Ssn) AS 'Number of Employees' 65 | FROM `department` AS D JOIN `employee` AS E ON D.Dnumber = E.Dno 66 | WHERE E.Sex = 'M' 67 | GROUP BY D.Dnumber 68 | 69 | # 3.a 70 | CREATE VIEW dept_managment(Department_name, Manager_name, Manager_salary) 71 | AS SELECT D.Dname, E.Fname, E.Salary 72 | FROM `department` AS D JOIN `employee` AS E ON D.MgrSsn = E.Ssn 73 | 74 | 75 | -------------------------------------------------------------------------------- /Sem2/Gegevensbanken/Project/README.md: -------------------------------------------------------------------------------- 1 | # Project 2 | ## Bootstrap 3 | De twee bestanden ´bottom.tpl.php´ en ´top.tpl.php´ in deze map zorgen ervoor dat de site van het project gebruik maakt van boostrap in plaats van de afschuwelijke css die het project oorspronkelijk bezit. 4 | 5 | ## Hoe te gebruiken 6 | Vervang de twee bestanden in ´db2016´ door de bestanden in deze map. 7 | -------------------------------------------------------------------------------- /Sem2/Gegevensbanken/Project/bottom.tpl.php: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | -------------------------------------------------------------------------------- /Sem2/Gegevensbanken/Project/top.tpl.php: -------------------------------------------------------------------------------- 1 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | <?php print $title;?> 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 44 | 45 | 46 | 47 |
48 |
49 | 50 | 51 | 52 |

53 | -------------------------------------------------------------------------------- /Sem2/Gegevensbanken/samenvatting_gegevensbanken.txt: -------------------------------------------------------------------------------- 1 | samenvatting gegevensbanken op google drive (in verschillende delen): 2 | https://drive.google.com/open?id=0Byb0moQzmpI_UXROYmc3QVF1bU0 3 | Geschreven door Jonas Soenen 4 | 5 | Geen garantie tot correctheid of volledigheid :) 6 | 7 | -------------------------------------------------------------------------------- /Sem2/Marketing Engineering/Groei berekene case prijs.docx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem2/Marketing Engineering/Groei berekene case prijs.docx -------------------------------------------------------------------------------- /Sem2/Marketing Engineering/Perceptual Map in STATA.pptx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem2/Marketing Engineering/Perceptual Map in STATA.pptx -------------------------------------------------------------------------------- /Sem2/Marketing Engineering/les 25-03-16.docx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem2/Marketing Engineering/les 25-03-16.docx -------------------------------------------------------------------------------- /Sem2/MinorVerbreding/Economie/samenvatting_economie_JonasSoenen.txt: -------------------------------------------------------------------------------- 1 | Samenvatting economie: 2 | in google docs te bereiken via: 3 | https://docs.google.com/document/d/1r5hesbWUqACdTJkzifv3atEYuC6dwsyN9Bx2ekzwY1U/edit?usp=sharing 4 | Geschreven door Jonas Soenen 5 | 6 | Niet helemaal volledig/helemaal in orde wel heel wat duidelijker dan zijn dia's en eenvoudiger dan het boek. 7 | 8 | -------------------------------------------------------------------------------- /Sem2/Natuurkunde voor informatica II; Magnetisme/Oefenzitting 4/Oefeningen/Oef1.tex: -------------------------------------------------------------------------------- 1 | \documentclass[../Oefenzitting4.tex]{subfiles} 2 | \begin{document} 3 | \subsection{Oefening 1:} 4 | Twee delen: de buitenste cirkel en de binneste cirkel, want het punt ligt in de verlenging van de rechte stukken, dus die dragen niets bij. 5 | \\ 6 | $ 7 | B = \int dB = \int k_{m} \frac{I d\vec{s} \times \hat{r}}{r^{2}} 8 | $ 9 | \\ 10 | $\Downarrow$ $B_{1}$: $r=b$ en $I$ is constant. 11 | \\ 12 | $ 13 | B_{1} = \int dB = \int k_{m} \frac{I d\vec{s} \times \hat{b}}{b^{2}} 14 | \\ 15 | B_{1} = k_{m}\frac{I}{b^{2}} \int d\vec{s} 16 | \\ 17 | B_{1} = k_{m}\frac{I}{b^{2}} \int_0^{\frac{1}{3}\pi b} d\vec{s} 18 | \\ 19 | = \frac{\mu_{0}I}{4\pi b^{2}} \frac{1}{3} \pi b 20 | \\ 21 | = \frac{\mu_{0}I}{4b} \frac{1}{3} 22 | \\ 23 | = \frac{\mu_{0}I}{12b} 24 | $ 25 | \\ 26 | Volledig analoog voor $B_{2}$ 27 | \\ 28 | $ 29 | B_{2} = \frac{\mu_{0}I}{12a} 30 | $ 31 | \\ 32 | Totaal magnetisch veld: 33 | \\ 34 | $ 35 | \hat{B}_{T} = \hat{B}_{2} - \hat{B}_{1} 36 | \\ 37 | = \frac{\mu_{0}Ib - \mu_{0}Ia}{8ab} 38 | \\ 39 | = \frac{\mu_{0}I(b-a)}{8ab} 40 | \\ 41 | $ 42 | \end{document} 43 | -------------------------------------------------------------------------------- /Sem2/Natuurkunde voor informatica II; Magnetisme/Oefenzitting 4/Oefeningen/Oef2.tex: -------------------------------------------------------------------------------- 1 | \documentclass[../Oefenzitting4.tex]{subfiles} 2 | \begin{document} 3 | \subsection{Oefening 2:} 4 | 5 | \end{document} 6 | -------------------------------------------------------------------------------- /Sem2/Natuurkunde voor informatica II; Magnetisme/Oefenzitting 4/Oefeningen/Oef3.tex: -------------------------------------------------------------------------------- 1 | \documentclass[../Oefenzitting4.tex]{subfiles} 2 | \begin{document} 3 | \subsection{Oefening 3:} 4 | \begin{itemize} 5 | \item a) \\ 6 | $ 7 | B = \int dB = \int k_{m} \frac{I d\vec{s} \times \hat{r}}{r^{2}} 8 | $ \\ 9 | $\Downarrow $ Q ligt evenwijdig met segment: $ sin(0) = sin(\pi) = 0 $ 10 | \\ 11 | $ 12 | B = 0 13 | $ 14 | \item b) \\ 15 | Formule: \\ 16 | $ 17 | B = \int dB = \int k_{m} \frac{I d\vec{s} \times \vec{r}}{r^{2}} 18 | $ 19 | \\ 20 | $\Downarrow$$k_{m}$ en $I$ zijn constant 21 | \\ 22 | $ 23 | = k_{m}I \int \frac{d\vec{s} \times \vec{r}}{r^{2}} 24 | $ 25 | \\ 26 | $\Downarrow$$\sin(\theta) = \frac{y}{r}$ 27 | \\ 28 | $ 29 | = k_{m}I \int \frac{ydx}{r^{3}} 30 | $ 31 | \\ 32 | $\Downarrow$ $y$ is constante 33 | \\ 34 | $ 35 | = k_{m}Iy \int \frac{dx}{r^{3}} 36 | $ 37 | \\ 38 | $\Downarrow$ $r= \sqrt{x^{2}+y^{2}}$ 39 | \\ 40 | $ 41 | = k_{m}Iy \int \frac{dx}{(x^{2}+y^{2})^{3/2}} 42 | \\ 43 | = k_{m}Iy \left[ \frac{x}{y^{2}(x^{2} + y^{2})^{1/2}} \right]^{0}_{-d} 44 | \\ 45 | = k_{m}Iy \left[ \frac{d}{y^{2}(d^{2} + y^{2})^{1/2}} \right] 46 | $ 47 | 48 | \end{itemize} 49 | \end{document} 50 | -------------------------------------------------------------------------------- /Sem2/Natuurkunde voor informatica II; Magnetisme/Oefenzitting 4/Oefenzitting4.tex: -------------------------------------------------------------------------------- 1 | \documentclass{report} 2 | \usepackage{subfiles} 3 | \begin{document} 4 | \section{Oefenzitting 4:} 5 | \subfile{Oefeningen/Oef1.tex} 6 | \subfile{Oefeningen/Oef2.tex} 7 | \subfile{Oefeningen/Oef3.tex} 8 | 9 | \end{document} 10 | -------------------------------------------------------------------------------- /Sem2/Natuurkunde voor informatica II; Magnetisme/samenvatting_natuurkunde_JonasSoenen.txt: -------------------------------------------------------------------------------- 1 | Samenvatting natuurkunde 2: 2 | https://docs.google.com/document/d/1rTPNutmIpy36ugIWPeDpvWWKdKrqXKKrhl0LgRUl1E4/edit?usp=sharing 3 | 4 | PAS OP! niet echt een samenvatting! 5 | Eerder een aanvulling voor als ge de slides moeilijk kunt volgen! 6 | Kan handig zijn om gewoon eens door te lezen om de grote lijn duidelijker te zien :) 7 | 8 | Geschreven door Jonas Soenen 9 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 02/image1.JPG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 02/image1.JPG -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 02/image2.JPG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 02/image2.JPG -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 02/image3 (1).JPG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 02/image3 (1).JPG -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 02/image4.JPG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 02/image4.JPG -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 02/image5.JPG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 02/image5.JPG -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 05/Oefenzitting5.m: -------------------------------------------------------------------------------- 1 | % Probleem 1 ------------------------------------------------------------------------------- 2 | n = -1:-0.1:-15; 3 | h = 10.^n; 4 | 5 | y1 = (5*exp(h) - 5)./h; 6 | y2 = (5*exp(h) - 5*exp(-h))./(2*h); 7 | 8 | rel1 = abs(5-y1)/5; %Relatieve fout is (verwacht-uitgekomen)/verwacht 9 | rel2 = abs(5-y2)/5; 10 | 11 | figure; 12 | loglog(h, rel1); 13 | hold on; %Nodig zodat beide plots getekend worden, ofanders wordt de eerste door de tweede overschreven. 14 | loglog(h, rel2); 15 | %Twee soorten fouten: benaderingsfout & afrondingsfout 16 | % f'(x) != (f(x+h) - f(x) / h) alleen juist voor als h oneindig klein is, matlab kan niet zo klein, dus quotient heeft grote relatieve fout. 17 | % Als h kleiner wordt wordt benadering beter, daarna gaat afrondingsfout belangrijker worden. 18 | 19 | 20 | % Probleem 2 ------------------------------------------------------------------------------- 21 | hold on; 22 | k1 = 1; 23 | hk1 = h .^k1; 24 | loglog(h, hk1, '--'); 25 | hold on; 26 | k2 = 2; 27 | hk2 = h .^k2; 28 | loglog(h, hk2, '--'); 29 | 30 | 31 | % Probleem 3 ------------------------------------------------------------------------------- 32 | hold on; 33 | grens_afrondingsfout = h.^(-1)*eps; 34 | loglog(h, grens_afrondingsfout, '-.'); 35 | hold on; 36 | x(1:141) = eps; 37 | plot(h, x, '--'); 38 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 06/Oefeningen/Oef1.tex: -------------------------------------------------------------------------------- 1 | \documentclass[../Oefenzitting6.tex]{subfiles} 2 | \begin{document} 3 | \subsection{Oefening 1:} 4 | Beschouw de tweede-graadsveelterm $f(x) = 2x^{2} + 4x -5$ 5 | \begin{itemize} 6 | \item a) Bereken de interpolerende veelterm $y_{1}(x)$ in de punten $\{-1, 1 \} $ met de methode van Lagrange en met de methode van Newton. 7 | \\ 8 | $ 9 | x_{0} = 1, f_{0} = f(1) = 1 10 | \\ 11 | x_{1} = -1, f_{1} = f(-1) = -7 12 | \\ 13 | l_{0} = \frac{x+1}{1-(-1)} = \frac{1}{2}x + \frac{1}{2} 14 | \\ 15 | l_{1} = \frac{x-1}{-1-1} = \frac{-1}{2}x + \frac{1}{2} 16 | \\ 17 | y_{1} = \frac{1}{2}x + \frac{1}{2} - 7(\frac{-1}{2}x \frac{1}{2}) 18 | \\ 19 | = 4x -3 20 | $ 21 | \\ 22 | Methode van newton: 23 | \\ 24 | $ 25 | \begin{matrix} 26 | 1 & 1 \\ 27 | 1 & -7 28 | \end{matrix} 29 | \\ 30 | \Rightarrow \frac{-7 - 1}{-1 - 1} = 4 31 | \\ 32 | y_{1} = 1+4(x-1) = 4x - 3 33 | $ 34 | 35 | \item b) Stel het Vandermonde stelsel op en ga na dat je oplossing hieraan voldoet. 36 | \\ 37 | $ 38 | \begin{bmatrix} 39 | 1 & 1 \\ 40 | 1 & -1 41 | \end{bmatrix} 42 | \begin{bmatrix} 43 | -3 \\ 44 | 4 45 | \end{bmatrix} 46 | = 47 | \begin{bmatrix} 48 | 1 \\ 49 | -7 50 | \end{bmatrix} 51 | $ 52 | 53 | \item c) Bereken de interpolatiefout $E_{1}(x)$ ... 54 | \\ 55 | $ 56 | E_{1}(x) = 2x^{2} + 4x -5 - (4x -3) 57 | \\ 58 | = 2x^{2} - 2 59 | $ 60 | \end{itemize} 61 | \end{document} 62 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 06/Oefeningen/Oef10.tex: -------------------------------------------------------------------------------- 1 | \documentclass[../Oefenzitting6.tex]{subfiles} 2 | \begin{document} 3 | \subsection{Oefening 10:} 4 | \begin{itemize} 5 | \item Interpolerende kwadratuurformule voor n+1 ptn heeft $NKG \geq n $ 6 | \item Kwadratuurformule met n+1 ptn met $NKG \geq n$ is interpolerend. 7 | \end{itemize} 8 | 9 | 10 | 11 | \end{document} 12 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 06/Oefeningen/Oef2.tex: -------------------------------------------------------------------------------- 1 | \documentclass[../Oefenzitting6.tex]{subfiles} 2 | \begin{document} 3 | \subsection{Oefening 2:} 4 | Beschouw dezelfde tweede-graadsveelterm $f(x) = 2x^{2} + 4x -5$ en herhaal probleem 1 met de interpolatiepunten $ \{ -1,0,1 \} $ waarbij je voor de methode van Newton de twee soorten tabellen van gedeelde differenties opstelt. Wat is de waarde van $ E_{2}(x)$? Verklaar. 5 | \begin{itemize} 6 | \item a) Bereken de interpolerende veelterm $y_{1}(x)$ in de punten $\{-1, 1 \} $ met de methode van Lagrange en met de methode van Newton. 7 | \\ 8 | $ 9 | x_{0} = -1, f_{0} = f(1) = -7 10 | \\ 11 | x_{1} = 0, f_{1} = f(0) = -5 12 | \\ 13 | x_{2} = 1, f_{2} = f(1) = 1 14 | \\ 15 | l_{0} = \frac{(x-0)(x-1)}{(-1-0)(-1-1)} = \frac{1}{2}x(x-1) 16 | \\ 17 | l_{1} = ... = 1-x^{2} 18 | \\ 19 | l_{2} = ... = \frac{1}{2}x(x+1) 20 | \\ 21 | y_{2} = \frac{-7}{2}x(x-1) - 5(1-x^{2}) + frac{1}{2}x(x+1) 22 | \\ 23 | = 2x^{2} + 4x - 5 24 | $ 25 | \\ 26 | Methode van newton: 27 | \\ 28 | $ 29 | \begin{matrix} 30 | -1 & -7 \\ 31 | 0 & -5 \\ 32 | 1 & 1 33 | \end{matrix} 34 | \\ 35 | \Rightarrow 36 | \\ \frac{-5+7}{0+1} = 2 37 | \\ \frac{1+5}{1-0} = 6 38 | \\ 39 | \Rightarrow 40 | \\ \frac{6-2}{1+1} = 2 41 | \\ 42 | y_{2} = -7 +2(x+1) + 2(x+1)x = 2x^{2} + 4x - 5 43 | 44 | $ 45 | 46 | \item b) Stel het Vandermonde stelsel op en ga na dat je oplossing hieraan voldoet. 47 | \\ 48 | $ 49 | \begin{bmatrix} 50 | 1 & 1 \\ 51 | 1 & -1 52 | \end{bmatrix} 53 | \begin{bmatrix} 54 | -3 \\ 55 | 4 56 | \end{bmatrix} 57 | = 58 | \begin{bmatrix} 59 | 1 \\ 60 | -7 61 | \end{bmatrix} 62 | $ 63 | 64 | \item c) Bereken de interpolatiefout $E_{1}(x)$ ... 65 | \\ 66 | $ 67 | E_{1}(x) = 2x^{2} + 4x -5 - (4x -3) 68 | \\ 69 | = 2x^{2} - 2 70 | $ 71 | \end{itemize} 72 | 73 | 74 | \end{document} 75 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 06/Oefeningen/Oef4.tex: -------------------------------------------------------------------------------- 1 | \documentclass[../Oefenzitting6.tex]{subfiles} 2 | \begin{document} 3 | \subsection{Oefening 4:} 4 | 5 | $ 6 | \{ (x_{i}, 1) \}_{i=0}^{n} 7 | y_{n}(x) = \sum_{i=0}^{n} l_{i}(x) = 1 8 | $ 9 | \\ want interpolerende veelterm is uniek. 10 | $ 11 | \{ (x_{i}, x-{i}^{k}) \}_{i=0}^{n} 12 | y_{n}(x) = \sum_{i=0}^{n} l_{i}(x)x_{i}^{k} = x^{k} als k \leq n 13 | $ 14 | 15 | 16 | \end{document} 17 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 06/Oefeningen/Oef5.tex: -------------------------------------------------------------------------------- 1 | \documentclass[../Oefenzitting6.tex]{subfiles} 2 | \begin{document} 3 | \subsection{Oefening 5:} 4 | 5 | $ 6 | y_{n-1}(x) + (f_{n} - y{n-1}(x_{n})) l_{n}(x) =? y_{n}(x) 7 | $ 8 | \\ heeft graad $\leq$ n 9 | \\ Interpolerend? 10 | \begin{itemize} 11 | \item i $\neq$ \\ 12 | $ 13 | y_{n-1}(x_{i}) + (f_{n} - y_{n-1}(x_{n}))l_{n}(x_{i}) 14 | \\ 15 | \Downarrow l_{n}(x_{i}) = 0 16 | \\ 17 | = y_{n-1}(x_{i}) = f_{i} 18 | $ 19 | \item $i = n$ \\ 20 | $ 21 | y_{n-1}(x_{i}) + (f_{n} - y_{n-1}(x_{n}))l_{n}(x_{n}) 22 | \\ 23 | \Downarrow l_{n}(x_{n}) = 1 24 | \\ 25 | = y_{n-1}(x_{n}) + f_{n} - y_{n-1}(x_{n}) = f_{n} 26 | $ 27 | 28 | 29 | 30 | 31 | 32 | 33 | \end{document} 34 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 06/Oefenzitting6.tex: -------------------------------------------------------------------------------- 1 | \documentclass{report} 2 | \usepackage{subfiles} 3 | \begin{document} 4 | \section{Oefenzitting 6:} 5 | \subfile{Oefeningen/Oef1.tex} 6 | \subfile{Oefeningen/Oef2.tex} 7 | \subfile{Oefeningen/Oef4.tex} 8 | 9 | \end{document} 10 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 07/Oefenzitting7.m: -------------------------------------------------------------------------------- 1 | % Oefening 1a 2 | A = [7 8 0; 1 2 3; 4 5 6]; 3 | 4 | [L,U] = lu(A); 5 | 6 | det(A) 7 | prod(diag(L)) * prod(diag(U)) 8 | 9 | % Oefening 1b 10 | A = [1 4 3; 4 3 5; 9 8 0]; 11 | [L,U] = lu(A) 12 | % L is geen benedendriehoeksmatrix 13 | % rijen verwisselen -> numeriek stabieler 14 | 15 | 16 | % Oefening 2a 17 | format long; 18 | M = genmatrix1(6); 19 | M_G1 = gauss1(M); 20 | M_G2 = gauss2(M); 21 | [M_Q, M_R] = qr(M); 22 | 23 | x1 = asubst(M_G1); 24 | x2 = asubst(M_G2); 25 | x3 = asubst(M_R); 26 | 27 | x = round(x3); 28 | 29 | norm(x1 - x) / norm(x) 30 | norm(x2 - x) / norm(x) 31 | norm(x3 - x) / norm(x) 32 | 33 | 34 | % Oefening 2b 35 | M = genmatrix2(6); 36 | M_G1 = gauss1(M); 37 | M_G2 = gauss2(M); 38 | [M_Q, M_R] = qr(M); 39 | 40 | x1 = asubst(M_G1); 41 | x2 = asubst(M_G2); 42 | x3 = asubst(M_R); 43 | 44 | x = round(x3); 45 | 46 | norm(x1 - x) / norm(x) 47 | norm(x2 - x) / norm(x) 48 | norm(x3 - x) / norm(x) 49 | 50 | % Oefening 3 51 | M = genmatrixc(6); 52 | M_G1 = gauss1(M); 53 | M_G2 = gauss2(M); 54 | [M_Q, M_R] = qr(M); 55 | 56 | x1 = asubst(M_G1); 57 | x2 = asubst(M_G2); 58 | x3 = asubst(M_R); 59 | 60 | x = round(x3); 61 | 62 | norm(x1 - x) / norm(x) 63 | norm(x2 - x) / norm(x) 64 | norm(x3 - x) / norm(x) 65 | 66 | % Oefening 3a 67 | M = genmatrix1(6); 68 | M_A = M(:,1:end-1); 69 | M_b = M(:,end); 70 | M_G1 = gauss1(M); 71 | M_G2 = gauss2(M); 72 | [M_Q, M_R] = qr(M); 73 | 74 | x1 = asubst(M_G1); 75 | x2 = asubst(M_G2); 76 | x3 = asubst(M_R); 77 | 78 | r1 = M_A * x1 - M_b; 79 | r2 = M_A * x2 - M_b; 80 | r3 = M_A * x3 - M_b; 81 | 82 | norm(r1)/norm(M_b) 83 | norm(r2)/norm(M_b) 84 | norm(r3)/norm(M_b) 85 | 86 | 87 | M = genmatrix2(6); 88 | M_A = M(:,1:end-1); 89 | M_b = M(:,end); 90 | M_G1 = gauss1(M); 91 | M_G2 = gauss2(M); 92 | [M_Q, M_R] = qr(M); 93 | 94 | x1 = asubst(M_G1); 95 | x2 = asubst(M_G2); 96 | x3 = asubst(M_R); 97 | 98 | r1 = M_A * x1 - M_b; 99 | r2 = M_A * x2 - M_b; 100 | r3 = M_A * x3 - M_b; 101 | 102 | norm(r1)/norm(M_b) 103 | norm(r2)/norm(M_b) 104 | norm(r3)/norm(M_b) 105 | 106 | 107 | M = genmatrixc(6); 108 | M_A = M(:,1:end-1); 109 | M_b = M(:,end); 110 | M_G1 = gauss1(M); 111 | M_G2 = gauss2(M); 112 | [M_Q, M_R] = qr(M); 113 | 114 | x1 = asubst(M_G1); 115 | x2 = asubst(M_G2); 116 | x3 = asubst(M_R); 117 | 118 | r1 = M_A * x1 - M_b; 119 | r2 = M_A * x2 - M_b; 120 | r3 = M_A * x3 - M_b; 121 | 122 | norm(r1)/norm(M_b) 123 | norm(r2)/norm(M_b) 124 | norm(r3)/norm(M_b) 125 | 126 | % de qr methode is het meest stabiel 127 | % Methode die gebruik maakt van orthogonale matrices over het algemeen stabiel 128 | 129 | % Gauss2 en qr goed geconditioneerd -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 08/1 Functies, function handles en anonieme functies/evalueer_lagrange.m: -------------------------------------------------------------------------------- 1 | function y = evalueer_lagrange(x, f, z) 2 | 3 | y = 0; 4 | for i = 1:numel(x) 5 | t= f(i); 6 | for j = 1:numel(x) 7 | if (j ~= i) 8 | t = t.*(z-x(j))/(x(i) - x(j)); 9 | end 10 | end 11 | y = y + t; 12 | end 13 | 14 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 08/1 Functies, function handles en anonieme functies/evalueer_lagrange2.m: -------------------------------------------------------------------------------- 1 | function y = evalueer_lagrange(x, f, z) 2 | 3 | y = 0; 4 | for i = 1:numel(x) 5 | t= f(x(i)); 6 | for j = 1:numel(x) 7 | if (j ~= i) 8 | t = t.*(z-x(j))/(x(i) - x(j)); 9 | end 10 | end 11 | y = y + t; 12 | end 13 | 14 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 08/1 Functies, function handles en anonieme functies/f1.m: -------------------------------------------------------------------------------- 1 | function y = f1(x) 2 | y = 1/(1+25*x^2); -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 08/1 Functies, function handles en anonieme functies/test_lagrange.m: -------------------------------------------------------------------------------- 1 | %% interpolerende veelterm van graad n-1 van Runge functie 2 | 3 | n = 10; 4 | x = linspace(-1,1,n); %interpolatiepunten 5 | fx = 1./(1+25*x.^2); 6 | 7 | z = linspace(-1,1,1000); %evaluatiepunten 8 | y = evalueer_lagrange(x,fx,z); 9 | 10 | fz = 1./(1+25*z.^2); 11 | 12 | figure(1),clf 13 | plot(z,fz) 14 | hold on 15 | plot(z,y,'r') 16 | legend('functie','int. veelterm') -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 08/1 Functies, function handles en anonieme functies/test_lagrange2.m: -------------------------------------------------------------------------------- 1 | %% interpolerende veelterm van graad n-1 van Runge functie 2 | 3 | n = 10; 4 | x = linspace(-1,1,n); %interpolatiepunten 5 | fx = @f1; 6 | 7 | z = linspace(-1,1,1000); %evaluatiepunten 8 | y = evalueer_lagrange2(x,fx,z); 9 | 10 | fz = 1./(1+25*z.^2); 11 | 12 | figure(1),clf 13 | plot(z,fz) 14 | hold on 15 | plot(z,y,'r') 16 | legend('functie','int. veelterm') -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 08/1 Functies, function handles en anonieme functies/test_lagrange3.m: -------------------------------------------------------------------------------- 1 | %% interpolerende veelterm van graad n-1 van Runge functie 2 | 3 | n = 10; 4 | x = linspace(-1,1,n); %interpolatiepunten 5 | fx = @(x) 1/(1+25*x^2); 6 | 7 | z = linspace(-1,1,1000); %evaluatiepunten 8 | y = evalueer_lagrange2(x,fx,z); 9 | 10 | fz = 1./(1+25*z.^2); 11 | 12 | figure(1),clf 13 | plot(z,fz) 14 | hold on 15 | plot(z,y,'r') 16 | legend('functie','int. veelterm') -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 08/2 De MATLAB debugger/filming_the_rocket.m: -------------------------------------------------------------------------------- 1 | % Met de functie getrocketposition.m wordt de positie van een raket in 2 | % Cartesische coordinaten bekomen in functie van de tijd. 3 | % 4 | % De bedoeling is om de raket met een camera vanuit de oorsprong te volgen. 5 | % 6 | % De positie van de raket wordt omgezet naar de hoek in poolcoordinaten en 7 | % hieruit wordt de hoeksnelheid omega van de camera afegeleid als een 8 | % eindige differentie. 9 | 10 | %% 11 | % Omzetten van Cartesische coordinaten naar poolcoordinaten: 12 | % x(1) = r*cos(theta) 13 | % x(2) = r*sin(theta) 14 | % oplossen: 15 | % * r = norm(x) 16 | % * tan(theta) = x(2) / x(1) 17 | %% PROBLEEM ZIT HIERONDER!!! 18 | % Bij atan gaat er informatie verloren door de deling, terwijl bij atan2 19 | % die informatie niet verloren gaat. 20 | bereken_hoek = @(x) atan2( x(2),x(1) ); 21 | 22 | 23 | % vector met tijdstippen 24 | N = 100; 25 | t = linspace(0,2,N); 26 | 27 | % reserveer geheugen 28 | omega = zeros(N-1,1); 29 | x = zeros(N,2); 30 | 31 | % initializatie 32 | x(1,:) = getrocketposition(t(1)); 33 | hoek_vorige = bereken_hoek(x(1,:)); 34 | 35 | for k = 2:N 36 | 37 | % bereken de hoek 38 | x(k,:) = getrocketposition(t(k)); 39 | hoek = bereken_hoek(x(k,:)); 40 | 41 | % bereken de hoeksnelheid 42 | %% PROBLEEM 43 | % Hier beginnen zoeken van probleem! Reverse engineer that shit!! 44 | omega(k-1) = (hoek - hoek_vorige)/(t(k) - t(k-1)); 45 | 46 | 47 | 48 | % update hoek_vorige 49 | hoek_vorige = hoek; 50 | end 51 | 52 | % plot resultaten 53 | figure(1),clf 54 | 55 | subplot(211) 56 | hold on 57 | plot(0, 0, 'r.', 'markersize', 20) 58 | plot(1, 0, 'm.', 'markersize', 20) 59 | plot(x(:, 1), x(:, 2), 'b-') 60 | for k = 1:round(N/10):N 61 | plot([0 x(k,1)],[0 x(k,2)],'k--*') 62 | end 63 | plot(0, 0, 'r.', 'markersize', 20) 64 | plot(1, 0, 'm.', 'markersize', 20) 65 | grid on 66 | xlabel('x-positie') 67 | ylabel('y-positie') 68 | title('Positie raket','fontsize',16) 69 | legend('Camera','Positie t=0','location','northeast') 70 | 71 | subplot(212) 72 | plot(t(2:end), omega, 'b-') 73 | axis([min(t) max(t) -5 5]) 74 | xlabel('tijd t') 75 | title('hoeksnelheid camera in (0,0)','fontsize',16) 76 | grid on 77 | 78 | 79 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 08/2 De MATLAB debugger/getrocketposition.m: -------------------------------------------------------------------------------- 1 | function [ pos ] = getrocketposition( t ) 2 | 3 | pos = [1 - 3*t/2, -t.^2 + 3*t]; 4 | 5 | end 6 | 7 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 09/Bsplinestelsel.m: -------------------------------------------------------------------------------- 1 | function [A,b] = Bsplinestelsel( t,f ) 2 | %BSPLINEMATRIX Berekent het stelsel Ac=b van interpolatievoorwaarden en 3 | %natuurlijke voorwaarden in de (genormaliseerde) B-spline basis, voor 4 | %equidistante knooppunten t(4),t(5),...,t(end-3) en een function handle 5 | %f. 6 | 7 | ft = f(t(4:end-3)); % negeer 3 eerste en 3 laatste knooppunten 8 | b = [0; ft(:); 0]; 9 | 10 | n = length(t)-7; 11 | A = zeros(n+3); 12 | 13 | % interpolatievoorwaarden in t_0,...,t_n 14 | for k = 2:n+2 15 | A(k,k-1:k+1) = [ 1/6 4/6 1/6 ]; 16 | end 17 | % natuurlijke voorwaarden in t_0 en t_n 18 | A(1,1:3) = [ 1 -2 1 ]; 19 | A(n+3,n+1:n+3) = [ 1 -2 1 ]; 20 | 21 | end 22 | 23 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 09/evalBspline.m: -------------------------------------------------------------------------------- 1 | function y = evalBspline( t, c, x ) 2 | %EVALBSPLINE Evalueer kubische spline met knooppunten t en met c de 3 | %coefficienten in de B-spline basis: 4 | % s(x) = SUM_{j=-3...n-1} c_j N_j(x) 5 | % 6 | % -> c heeft lengte n + 3 7 | % -> t heeft lengte n + 7 : 8 | % t_{-3}, t_{-2}, t_{-1}, t_0,...,t_n, t_{n+1},t_{n+2},t_{n+3} 9 | % 10 | % @PRE: de waarden in t zijn geordend van klein naar groot 11 | % @PRE: length(c) == length(t) - 4 12 | 13 | if length(c) + 4 ~= length(t) 14 | error('t moet precies 4 elementen meer hebben dan c.') 15 | end 16 | % voeg nullen toe aan c en begin en eindpunten aan t. De waarde van deze 17 | % extra punten in t maken niet uit: 18 | c_ext = [0;0;0; c(:) ;0;0;0]; 19 | dt = t(2)-t(1); 20 | t_ext = [t(1)-dt*[3;2;1] ; t(:) ; t(end)+dt*[1;2;3]]; 21 | 22 | y = 0*x; 23 | for k = 1:length(x) 24 | % bepaal j zodat x(k) in [t(j),t(j+1)]: 25 | j = find(x(k) >= t,1,'last'); 26 | if isempty(j) 27 | % x(k) < t(1) 28 | j = 0; 29 | end 30 | % --> j is een van de waarden uit 0,1,2,...,N=length(t) 31 | % t(1) t(2) t(3) t(4) t(5) ... t(N) 32 | % j: 0 1 2 3 4 N 33 | if x(k) <= t(1) || x(k) >= t(end) 34 | % j == 0 || j == N 35 | y(k) = 0; 36 | else 37 | cc = c_ext(j:j+3); 38 | tt = t_ext(j:j+6); 39 | for i = 1:3 40 | % c[i]_m voor m=j-3+i...j 41 | for m = 4:-1:i+1 42 | % dalende volgorde, zodat we enkel die c's overschrijven die in de i-de stap niet meer gebruikt worden 43 | alpha = (x(k)-tt(m))/(tt(m+4-i)-tt(m)); 44 | cc(m) = alpha*cc(m) + (1-alpha)*cc(m-1); 45 | end 46 | end 47 | y(k) = cc(4); 48 | end 49 | end 50 | 51 | end -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 09/evalspline.m: -------------------------------------------------------------------------------- 1 | % eerst kijken in welk knooppuntinterval x ligt 2 | % dan veelterm berekenen voor dit interval 3 | % evalueren in punt x 4 | 5 | function y = evalspline(t, c, x) 6 | for (i = 1:length(x)) 7 | j = 1; 8 | % waarom -2? 9 | while (j <= length(t)-2) 10 | if (x(i) >= t(j) && x(i) < t(j+1)) 11 | break; 12 | end 13 | j = j+1; 14 | end 15 | start = 4*(j-1) + 1; 16 | p = c(start:start+3); 17 | y(i) = polyval(p, x(i)); 18 | end 19 | end 20 | 21 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 09/oefenzitting9.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 09/oefenzitting9.m -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 09/splinematrix.m: -------------------------------------------------------------------------------- 1 | function A = splinematrix(t) 2 | 3 | n = length(t)-1; 4 | 5 | A = zeros(3*(n-1),4*n); 6 | 7 | for k = 1:n-1 8 | A(3*k-2:3*k,4*k-3:4*k+4) = ... 9 | [ t(k+1)^3 t(k+1)^2 t(k+1) 1 -t(k+1)^3 -t(k+1)^2 -t(k+1) -1; 10 | 3*t(k+1)^2 2*t(k+1) 1 0 -3*t(k+1)^2 -2*t(k+1) -1 0 ; 11 | 6*t(k+1) 2 0 0 -6*t(k+1) -2 0 0 ]; 12 | end 13 | 14 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 09/splinestelsel.m: -------------------------------------------------------------------------------- 1 | function [A,b] = splinestelsel( t,f ) 2 | %BSPLINEMATRIX Berekent voor kubische splines het stelsel Ac=b van 3 | %continuiteitsvoorwaarden, interpolatievoorwaarden en natuurlijke 4 | %voorwaarden in de klassieke basis 5 | % s(x) = aj x^3 + bj x^2 + cj x + dj, x in [t(j),t(j+1)], 6 | %voor knooppunten t(4),t(5),...,t(end-3) en een function handle f. 7 | 8 | n = length(t)-1; 9 | 10 | A = zeros(4*n); 11 | b = zeros(4*n,1); 12 | 13 | A(1:3*(n-1),:) = splinematrix(t); 14 | 15 | % interpolatievoorwaarden 16 | % t_0,...,t_(n-1) 17 | for k = 1:n 18 | A(3*(n-1)+k,4*k-3:4*k) = [ t(k)^3 t(k)^2 t(k) 1 ]; 19 | b(3*(n-1)+k) = f(t(k)); 20 | end 21 | % t_n 22 | A(4*n-2,4*n-3:4*n) = [ t(n+1)^3 t(n+1)^2 t(n+1) 1 ]; 23 | b(4*n-2) = f(t(n+1)); 24 | 25 | % natuurlijke voorwaarden in t_0 en t_n 26 | % ------------- 27 | A(4*n-1,1:4) = [6*t(1) 2 0 0]; 28 | b(4*n-1) = 0; 29 | A(4*n,4*n-3:4*n) = [6*t(n+1) 2 0 0]; 30 | b(4*n) = 0; 31 | 32 | % % -- not-a-knot (zoals in MATLAB spline.m) -- 33 | % % ------------------------------------------- 34 | % % 3e afg in t_1 en t_(n-1) is ook continu 35 | % A(4*n-1,1:8) = [ 6 0 0 0 -6 0 0 0]; 36 | % A(4*n,4*n-7:4*n) = [ 6 0 0 0 -6 0 0 0]; 37 | 38 | 39 | end 40 | 41 | 42 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 11/20160522_191323_resized_1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 11/20160522_191323_resized_1.jpg -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 11/20160522_191330_resized_1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 11/20160522_191330_resized_1.jpg -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 11/20160522_191335_resized_1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 11/20160522_191335_resized_1.jpg -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/eerste_opgave.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/eerste_opgave.zip -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/eerste_opgave/oefz12/bisection.m: -------------------------------------------------------------------------------- 1 | function [napprox, approx] = bisection(f, aa, bb, K) 2 | % f - function to compute roots of 3 | % [aa, bb] - interval to compute roots of 4 | % K - maximal number of iterations 5 | 6 | a = aa; 7 | b = bb; 8 | 9 | x = aa; 10 | fa = vpa(subs(f)); 11 | x = bb; 12 | fb = vpa(subs(f)); 13 | 14 | approx = vpa(zeros(1, K)); 15 | napprox = 0; 16 | 17 | if fa * fb >= 0 18 | approx = approx(1:napprox); 19 | return; 20 | end 21 | 22 | for i = 1:K 23 | m = vpa((a+b)/2); 24 | approx(i) = m; 25 | napprox = napprox + 1; 26 | x = m; 27 | fm = vpa(subs(f)); 28 | if fm*fa < 0 29 | b = m; 30 | fb = fm; 31 | else 32 | a = m; 33 | fa = fm; 34 | end 35 | end 36 | 37 | approx = approx(1:napprox); 38 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/eerste_opgave/oefz12/comprelerr.m: -------------------------------------------------------------------------------- 1 | function relerr = comprelerr(approx,zero,hp,n) 2 | 3 | if nargin < 3 4 | hp = 100; 5 | end 6 | if nargin < 4 7 | n = length(approx); 8 | end 9 | 10 | relerr = double(vpa(abs((approx(1:n) - zero)/zero), hp)); 11 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/eerste_opgave/oefz12/halley.m: -------------------------------------------------------------------------------- 1 | function [napprox, approx] = halley(f, df, ddf, aa, K) 2 | % f - function to compute roots of 3 | % df - first-order derivative of f 4 | % ddf - second-order derivative of f 5 | % aa - starting point 6 | % K - maximal number of iterations 7 | 8 | a = aa; 9 | approx = vpa(zeros(1, K)); 10 | napprox = 0; 11 | 12 | for i = 1:K 13 | x = a; 14 | fa = vpa(subs(f)); 15 | dfa = vpa(subs(df)); 16 | ddfa = vpa(subs(ddf)); 17 | den = vpa(2*(dfa^2) - fa*ddfa); 18 | if den == 0 19 | approx = approx(1:napprox); 20 | return 21 | end 22 | b = vpa(a - 2*fa*dfa/den); 23 | approx(i) = b; 24 | napprox = napprox+1; 25 | a = b; 26 | end 27 | 28 | approx = approx(1:napprox); 29 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/eerste_opgave/oefz12/muller.m: -------------------------------------------------------------------------------- 1 | function [napprox, approx] = muller(f, xx0, xx1, xx2, K) 2 | % f - function to compute roots of 3 | % [xx0, xx1, xx2] - starting points 4 | % K - maximal number of iterations 5 | 6 | x0 = xx0; 7 | x = x0; 8 | c0 = vpa(subs(f)); 9 | 10 | x1 = xx1; 11 | x = x1; 12 | c1 = vpa(subs(f)); 13 | 14 | x2 = xx2; 15 | x = x2; 16 | d1 = vpa(subs(f)); 17 | 18 | approx = vpa(zeros(1, K)); 19 | napprox = 0; 20 | 21 | for i = 1:K 22 | x = x2; 23 | c2 = vpa(subs(f)); 24 | if x2 - x1 == 0 25 | approx = approx(1:napprox); 26 | return 27 | end 28 | d2 = vpa((c2-c1)/(x2-x1)); 29 | if x2 - x0 == 0 30 | approx = approx(1:napprox); 31 | return 32 | end 33 | a = vpa((d2-d1)/(x2-x0)); 34 | b = vpa(d2 + (x2-x1)*a); 35 | x0 = x1; 36 | x1 = x2; 37 | c1 = c2; 38 | d1 = d2; 39 | if (b+sign(b)*sqrt(b^2-4*a*c2)) == 0 40 | approx = approx(1:napprox); 41 | return 42 | end 43 | x2 = vpa(x2 - 2*c2/(b+sign(b)*sqrt(b^2-4*a*c2))); 44 | approx(i) = x2; 45 | napprox = napprox + 1; 46 | end 47 | 48 | approx = approx(1:napprox); 49 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/eerste_opgave/oefz12/newton.m: -------------------------------------------------------------------------------- 1 | function [napprox, approx] = newton(f, df, aa, K) 2 | % f - function to compute roots of 3 | % df - first-order derivative of f 4 | % aa - starting point 5 | % K - maximal number of iterations 6 | 7 | a = aa; 8 | approx = vpa(zeros(1, K)); 9 | napprox = 0; 10 | 11 | for i = 1:K 12 | x = a; 13 | fa = vpa(subs(f)); 14 | dfa = vpa(subs(df)); 15 | if dfa == 0 16 | approx = approx(1:napprox); 17 | return 18 | end 19 | b = vpa(a - fa/dfa); 20 | approx(i) = b; 21 | napprox = napprox+1; 22 | a = b; 23 | end 24 | 25 | approx = approx(1:napprox); 26 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/eerste_opgave/oefz12/oefz12.m: -------------------------------------------------------------------------------- 1 | % Define a function f(x) on the domain [a, b]. 2 | close all 3 | syms x a b 4 | a = 1; 5 | b = 2; 6 | %f = 4*x^4 - 5*x - 3; 7 | %f = (x^2 - 2); 8 | f = (x - 1.1)^2; 9 | %f = (x - 1.4)^3; 10 | %f = cos(x); 11 | %f = (x - 1.4)*cos(x/2); 12 | %f = (x - 1.4)^2*cos(x/2); 13 | %f = (x - 1.4)^3*cos(x/2); 14 | disp('Defined the function f(x), press a key to continue...') 15 | f 16 | pause 17 | 18 | % Compute the first- and second-order derivatives of f. 19 | df = diff(f, x); 20 | ddf = diff(df, x); 21 | disp('Computed first- and second-order derivatives of f:') 22 | df 23 | ddf 24 | pause 25 | 26 | % Set the variable precision to 100 digits. 27 | lp = 70; 28 | hp = 100; 29 | digits(hp); 30 | 31 | % Compute the roots of f in high precision. 32 | z = solve(f, x); 33 | z = vpa(z); 34 | disp('The roots of f are') 35 | z 36 | disp('Press a key to plot f on [a, b]') 37 | pause 38 | 39 | % Plot f on [a, b]). 40 | ezplot(f, [a b]) 41 | 42 | % Set the variable precision to low precision. 43 | digits(lp); 44 | 45 | % Run all the solvers. 46 | K = 100; % Number of iterations. 47 | z = z(z > a & z < b); % Which root to search for. 48 | z = z(1); 49 | disp('Press any key to search for root z = ') 50 | z 51 | pause 52 | close all 53 | 54 | [n, secantapprox] = secant(f, a, b, 20); 55 | secantrelerr = comprelerr(secantapprox, z, hp); 56 | figure(1);plot(secantapprox); hold all; 57 | figure(2);semilogy(secantrelerr); hold all; 58 | order = 1.618; 59 | secantfactor = ofactor(secantapprox,z,order,hp); 60 | figure(3);semilogy(secantfactor); hold all; 61 | 62 | [n, newtonapprox] = newton(f, df, a, 20); 63 | newtonrelerr = comprelerr(newtonapprox, z, hp); 64 | figure(1);plot(newtonapprox); 65 | figure(2);semilogy(newtonrelerr); 66 | order = 2.0; 67 | newtonfactor = ofactor(newtonapprox,z,order,hp); 68 | figure(3);semilogy(newtonfactor); 69 | 70 | [n, mullerapprox] = muller(f, a, b, (a+b)/2, 20); 71 | mullerapprox = abs(mullerapprox); 72 | mullerrelerr = comprelerr(mullerapprox, z, hp); 73 | figure(1);plot(mullerapprox); 74 | figure(2);semilogy(mullerrelerr); 75 | order = 1.839; 76 | mullerfactor = ofactor(mullerapprox,z,order,hp); 77 | figure(3);semilogy(mullerfactor); 78 | 79 | [n, halleyapprox] = halley(f, df, ddf, a, 20); 80 | halleyrelerr = comprelerr(halleyapprox, z, hp); 81 | figure(1);plot(halleyapprox); 82 | figure(2);semilogy(halleyrelerr); 83 | order = 3; 84 | halleyfactor = ofactor(halleyapprox,z,order,hp); 85 | figure(3);semilogy(halleyfactor); 86 | 87 | [n, bisecapprox] = bisection(f, a, b, K); 88 | bisecrelerr = comprelerr(bisecapprox, z, hp); 89 | figure(1);plot(bisecapprox); 90 | figure(2);semilogy(bisecrelerr); 91 | order = 1.0; 92 | bisecfactor = ofactor(bisecapprox,z,order,hp); 93 | figure(3);semilogy(bisecfactor); 94 | 95 | figure(1); 96 | xlim([0, 20]); 97 | xlabel('iteration'); 98 | ylabel('root'); 99 | 100 | figure(2); 101 | xlabel('iteration'); 102 | ylabel('relative error'); 103 | legend('Secant','Newton','Muller','Halley','Bisection','location','ne'); 104 | 105 | figure(3); 106 | xlim([0, 20]); 107 | xlabel('iteration'); 108 | ylabel('convergence factor'); 109 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/eerste_opgave/oefz12/ofactor.m: -------------------------------------------------------------------------------- 1 | function o = ofactor(approx,zero,order,hp,n,lp) 2 | 3 | if nargin < 4 4 | hp = 100; 5 | end 6 | if nargin < 5 7 | n = length(approx); 8 | end 9 | if nargin < 6 10 | lp = 70; 11 | end 12 | 13 | err = vpa(abs(approx(1:n) - zero), hp); 14 | err = err(err > 10^(-lp+5)); 15 | 16 | o = double(vpa(err(2:end) ./ err(1:end-1).^order, hp)); 17 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/eerste_opgave/oefz12/secant.m: -------------------------------------------------------------------------------- 1 | function [napprox, approx] = secant(f, aa, bb, K) 2 | % f - function to compute roots of 3 | % [aa, bb] - interval to compute roots of 4 | % K - maximal number of iterations 5 | 6 | a = aa; 7 | b = bb; 8 | 9 | x = aa; 10 | fa = vpa(subs(f)); 11 | 12 | approx = vpa(zeros(1, K)); 13 | napprox = 0; 14 | 15 | for i = 1:K 16 | x = b; 17 | fb = vpa(subs(f)); 18 | if fb - fa == 0 19 | approx = approx(1:napprox); 20 | return 21 | end 22 | c = vpa(b - fb * (b - a) / (fb - fa)); 23 | approx(i) = c; 24 | napprox = napprox + 1; 25 | a = b; 26 | fa = fb; 27 | b = c; 28 | end 29 | 30 | approx = approx(1:napprox); 31 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/eerste_opgave/oefz12/uitleg.txt: -------------------------------------------------------------------------------- 1 | Eerste functie 2 | 3 | we zien op die figuur drie dat die oranje zou moeten convergeren in kubische tijd, maar dit gebeurd niet, de methodes falen omdat er dubbele nulpunten zijn. 4 | 5 | Tweede functie, we zien dat het hier veel beter is. 6 | 7 | derde functie 8 | 9 | halley de paarse haalt zijn convergentie factor niet, want die gaat tot 10^20 10 | 11 | de gele is al na stappen aan de machine preciesie (zie grafiek relatieve fout) dus deze kunnen we niet bekijken -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/tweede_opgave/Probleem2.asv: -------------------------------------------------------------------------------- 1 | % methode 1 2 | % relatieve fout 3 | 4 | K = 100; 5 | waardes = vpa(zeros(1, K)); 6 | 7 | for k = 0:1:K 8 | waardes(k) = -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/tweede_opgave/Probleem2.m: -------------------------------------------------------------------------------- 1 | % methode 1 2 | % relatieve fout 3 | 4 | K = 20; 5 | waardes = vpa(zeros(1, K)); 6 | 7 | % waardes berekenen 8 | 9 | for k = 1:1:K 10 | %waardes(k) = methode1(k); 11 | %waardes(k) = methode2(k); 12 | %waardes(k) = methode3(k); 13 | waardes(k) = methode4(k); 14 | end 15 | 16 | figure(1); plot(1:1:K, waardes) 17 | 18 | % relatieve fout plotten 19 | 20 | relatievefout = (waardes - (sqrt(5)-1)/2)/(sqrt(5)-1)/2; 21 | 22 | figure(2); plot(1:1:K, relatievefout) 23 | 24 | 25 | 26 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/tweede_opgave/Uitleg.txt: -------------------------------------------------------------------------------- 1 | Eerste methode 2 | 3 | duidelijk te zien dat de relatieve fout toeneemt 4 | 5 | en aan de andere plot zie je ook duidelijk dat de functie divergeert 6 | 7 | Tweede methode 8 | 9 | Convergeert perfect je ziet duidelijk hoe de relatieve fout naar nul gaat en de waaarde naar de juiste waarde gaat naarmate het aantal iteraties toeneemt 10 | 11 | Derde methode 12 | 13 | Convergeert maar niet monotoom, je zit ook duidelijk hoe de relatieve fout naar nul gaat en de waarde naar de juiste waarde gaat. 14 | 15 | Omdat deze zo op en neer gaat, dat omhoog en omlaag gaan op het begin, betekend dat de functie monotoom is 16 | 17 | Vierde methode convergeert ook perfect, heel duidelijk -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/tweede_opgave/methode1.asv: -------------------------------------------------------------------------------- 1 | function [ output ] = methode1( x, k ) 2 | if k == 0 3 | output = 0; 4 | return; 5 | else 6 | return 7 | end 8 | 9 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/tweede_opgave/methode1.m: -------------------------------------------------------------------------------- 1 | function [ output ] = methode1( k ) 2 | if k == 0 3 | output = 0.7; 4 | return; 5 | else 6 | output = 1 - methode1(k-1)^2; 7 | return; 8 | end 9 | 10 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/tweede_opgave/methode2.m: -------------------------------------------------------------------------------- 1 | function [ output ] = methode2( k ) 2 | if k == 0 3 | output = 0.7; 4 | return; 5 | else 6 | value = methode2(k-1); 7 | output = (3*(value)^2-value+1)/(4*value); 8 | return; 9 | end 10 | 11 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/tweede_opgave/methode3.m: -------------------------------------------------------------------------------- 1 | function [ output ] = methode3( k ) 2 | if k == 0 3 | output = 0.7; 4 | return; 5 | else 6 | value = methode3(k-1); 7 | output = (4-value)/(4*value+3); 8 | return; 9 | end 10 | 11 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/tweede_opgave/methode4.m: -------------------------------------------------------------------------------- 1 | function [ output ] = methode4( k ) 2 | if k == 0 3 | output = 0.7; 4 | return; 5 | else 6 | value = methode4(k-1); 7 | output = value - (value^2+value-1)/(2*value+1) 8 | return; 9 | end 10 | 11 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/vierde_opgave.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/vierde_opgave.zip -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/vierde_opgave/bisect.m: -------------------------------------------------------------------------------- 1 | function [y] = bisect(fun,a,b,epsilon) 2 | 3 | i = 1; 4 | x0 = a; 5 | x1 = b; 6 | f0 = feval(fun,x0); 7 | f1 = feval(fun,x1); 8 | 9 | if ((f0*f1) > 0) 10 | print ='stop...error' 11 | return 12 | end 13 | while (abs(x1-x0) > 2*epsilon), 14 | x2 = (x0+x1)/2; 15 | f2=feval(fun,x2); 16 | y(i) = x2; 17 | i = i + 1; 18 | if (f0*f2 < 0); 19 | x1 = x2; 20 | else 21 | x0 = x2; 22 | f0 = f2; 23 | end 24 | end 25 | x2 = (x0+x1)/2; 26 | y(i) = x2; 27 | y = y'; 28 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/vierde_opgave/dekker.m: -------------------------------------------------------------------------------- 1 | function [y] = dekker(fun,a,b,epsilon) 2 | 3 | x0=a; 4 | f0 = feval(fun,x0); 5 | x1=b; 6 | f1 = feval(fun,x1); 7 | 8 | if ( f0*f1 > 0 ) 9 | print = 'fout, stop...' 10 | return 11 | end 12 | k=1; 13 | y1=x0; 14 | y_1=y1+1; 15 | y0=y1+0.5; 16 | while ( abs(y1-x1) > 2*epsilon ) 17 | if ( ~(y1==y_1) ) 18 | d = f1*(x1-x0)/(f1-f0); 19 | if ( ( (x1-y1)*d < 0 ) | ( abs(d) > abs(x1-y1) ) ) 20 | d = (x1-y1)/2; 21 | end 22 | else 23 | d = (x1-y1)/2; 24 | end 25 | x0 = x1; 26 | f0 =f1; 27 | y_1 = y0; 28 | y0 = y1; 29 | x1 = x1 - d; 30 | f1 = feval(fun,x1); 31 | if ( f0*f1 < 0 ) 32 | y1 = x0; 33 | end 34 | y(k)=(x1+y1)/2; 35 | k=k+1; 36 | end 37 | y=y'; 38 | print ='convergentie bereikt' 39 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 12/vierde_opgave/secant.m: -------------------------------------------------------------------------------- 1 | function [y] = secant(fun,a,b,epsilon,kmax) 2 | 3 | i = 1; 4 | x0 = a; 5 | x1 = b; 6 | 7 | f0 = feval(fun,x0); 8 | for k = 1:kmax, 9 | if ( abs(x1-x0) < epsilon ) 10 | print = 'convergentie bereikt' 11 | y = y'; 12 | return 13 | else 14 | f1 = feval(fun,x1); 15 | x2 = x1 - (x1-x0)*f1/(f1-f0); 16 | y(i) = x2; 17 | i = i + 1; 18 | x0 = x1; 19 | f0 = f1; 20 | x1 = x2; 21 | end 22 | end 23 | print = 'geen convergentie bereikt na kmax stappen' 24 | y = y'; 25 | 26 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 17/invmachten.m: -------------------------------------------------------------------------------- 1 | function [x,mu] = invmachten(A,x0,sigma,n) 2 | % Methode van de inverse machten met verschuiving sigma toegepast op de 3 | % matrix A met startwaarde x0, n iteratiestappen 4 | % 5 | % OUTPUT: de benaderde eigenvector x en de opeenvolgende benaderingen mu 6 | % van de bijhorende eigenwaarde. 7 | 8 | x0 = x0/norm(x0); 9 | for i=1:n, 10 | x1 = (sigma*eye(size(A,1))-A)\x0; 11 | mu(i) = 1/norm(x1); 12 | if x0'*x1<0, 13 | mu(i) = -mu(i); 14 | end 15 | x0 = x1*mu(i); 16 | end 17 | % mu bevat opeenvolgende benaderingen voor (sigma-lambda_1(A)) 18 | x = x0; 19 | mu = (sigma-mu)'; 20 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 17/invmachten_adaptief.m: -------------------------------------------------------------------------------- 1 | function [x,sigma] = invmachten_adaptief(A,x0,sigma,n) 2 | % Methode van de inverse machten met adaptieve verschuiving toegepast op de 3 | % matrix A met startwaarde x0, n iteratiestappen en sigma de waarde van de 4 | % eerste verschuiving. 5 | % 6 | % OUTPUT: de benaderde eigenvector x en de opeenvolgende benaderingen mu 7 | % van de bijhorende eigenwaarde. 8 | 9 | x0 = x0/norm(x0); 10 | for i=1:n, 11 | x1 = (sigma(i)*eye(size(A,1))-A)\x0; 12 | mu = 1/norm(x1); 13 | if x0'*x1<0, 14 | mu = -mu; 15 | end 16 | x0 = x1*mu; 17 | sigma(i+1) = sigma(i) - mu; 18 | end 19 | % mu bevat opeenvolgende benaderingen voor lambda_1(A) 20 | x = x0; 21 | sigma = sigma'; 22 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 17/jacobi.m: -------------------------------------------------------------------------------- 1 | function fout=jacobi(a,b,x0,xe,n) 2 | [ra,ca]=size(a); 3 | x=x0; 4 | r=a*x-b; 5 | fout(1)=norm(x-xe)/norm(xe); 6 | for k=2:n+1; 7 | for i=1:ra; 8 | x(i)=x(i)-r(i)/a(i,i); 9 | end; 10 | fout(k)=norm(x-xe)/norm(xe); 11 | r=a*x-b; 12 | end 13 | fout = fout'; -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 17/machten.m: -------------------------------------------------------------------------------- 1 | function [x,mu]=machten(A,x0,n) 2 | % Methode van de machten toegepast op de matrix A met startwaarde x0, 3 | % n iteratiestappen 4 | % 5 | % OUTPUT: de benaderde eigenvector x en de opeenvolgende benaderingen mu 6 | % van de bijhorende eigenwaarde. 7 | 8 | x0 = x0/norm(x0); 9 | for i=1:n 10 | x1 = A*x0; 11 | mu(i) = norm(x1); 12 | if x0'*x1<0, 13 | mu(i) = -mu(i); 14 | end 15 | x0 = x1/mu(i); 16 | end 17 | % mu bevat opeenvolgende benaderingen voor lambda_1(A) 18 | x = x0; 19 | mu = mu'; 20 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 17/probleem1.m: -------------------------------------------------------------------------------- 1 | n = 1:20; 2 | %x0 = [1; 0; 0]; 3 | x0 = [1; 1; 1]; 4 | 5 | A = [102 -201 100; 1 0 0; 0 1 0]; 6 | B = [-1 4 0; -2 5 0; 0 1 2]; 7 | 8 | %eigenwaarden = eig(A); 9 | eigenwaarden = eig(B); 10 | eigenwaarden = sort(eigenwaarden, 'descend'); 11 | 12 | %[x, mu] = machten(A, x0, 20); 13 | [x, mu] = machten(B, x0, 20); 14 | rel_fout = abs(eigenwaarden(1) - mu) / abs(eigenwaarden(1)); 15 | 16 | % slechts tot 8, omdat vanaf 9 rel fout = 0 17 | semilogy(n, rel_fout); 18 | 19 | % convergentiefactor: E_k = cte * rho^k 20 | % log(E_k) = log(cte) + k log(rho) 21 | % E_k+1 / E_k = rho --> afwijkingen uitmiddelen E_k+10 / E_k = rho^10 22 | %berekende_convergentiefactor = nthroot(rel_fout(8) / rel_fout(6), 2) 23 | berekende_convergentiefactor = nthroot(rel_fout(14) / rel_fout(11), 3) 24 | exacte_convergentiefactor = eigenwaarden(2) / eigenwaarden(1) 25 | 26 | -------------------------------------------------------------------------------- /Sem2/NumeriekeWiskunde/Oefenzittingen/Oefenzitting 17/probleem2.m: -------------------------------------------------------------------------------- 1 | % A x = lambda x 2 | % A^-1 x = (1 / lambda) x --> zelfde eigenvectoren, omgekeerde eigenwaarden 3 | 4 | % (A - sigma I) x 5 | % = A x - sigma x 6 | % = (lambda - sigma) x 7 | 8 | % kracht van methode: alle eigenwaarden kunnen berekend worden 9 | % sigma dicht bij eigenwaarde 10 | 11 | B = [-1 4 0; -2 5 0; 0 1 2]; 12 | eigenwaarden = eig(B); 13 | eigenwaarden = sort(eigenwaarden, 'descend'); 14 | 15 | n = 1:20; 16 | x0 = [1; 0; 0]; 17 | sigma = 2.99; 18 | 19 | [x, mu] = invmachten(B, x0, sigma, 20); 20 | rel_fout_invmachten = abs(eigenwaarden(1) - mu) / abs(eigenwaarden(1)); 21 | [x, mu] = machten(B, x0, 20); 22 | rel_fout_machten = abs(eigenwaarden(1) - mu) / abs(eigenwaarden(1)); 23 | 24 | semilogy(n, rel_fout_invmachten); 25 | hold on; 26 | semilogy(n, rel_fout_machten); 27 | xlabel('aantal iteraties'); 28 | ylabel('relatieve fout'); 29 | legend('Inverse machten', 'Machten'); 30 | 31 | % theoretische convergentiefactor 32 | theoretische_convergentiefactor = (1/(sigma - eigenwaarden(2))) / (1/(sigma - eigenwaarden(1))) 33 | berekende_convergentiefactor = nthroot(rel_fout_invmachten(6) / rel_fout_invmachten(4), 2) -------------------------------------------------------------------------------- /Sem2/ToepassingenVanMeetkundeInDeInformatica/bewijs meetkunde les 2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MidasLamb/2BachInfo/fea729319e3669c970d04da191dde727415d1599/Sem2/ToepassingenVanMeetkundeInDeInformatica/bewijs meetkunde les 2.jpg -------------------------------------------------------------------------------- /Sem2/ToepassingenVanMeetkundeInDeInformatica/samenvatting_TMI_JonasSoenen.txt: -------------------------------------------------------------------------------- 1 | Samenvatting van TMI 2 | deel 1 (computer aided design) 3 | https://docs.google.com/document/d/1pgBRmaKV8SfBWcWRAWAIz_nAEDEk6CcmaphKINTuWsY/edit?usp=sharing 4 | deel 2 (algoritmen voor discrete meetkundige problemen) 5 | https://docs.google.com/document/d/1FeTkmF9DbWhVIVsH6RWp3cgI6DkzxeFuqCYTZcC5Cpg/edit?usp=sharing 6 | 7 | Geschreven door Jonas Soenen 8 | --------------------------------------------------------------------------------