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pdf2htmlEX/doc/tb108wang.html
2014-09-22 19:00:49 +08:00

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<!DOCTYPE html>
<!-- Created by pdf2htmlEX (https://github.com/coolwanglu/pdf2htmlex) -->
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta charset="utf-8"/>
<meta name="generator" content="pdf2htmlEX"/>
<meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1"/>
<style type="text/css">
/*!
* Base CSS for pdf2htmlEX
* Copyright 2012,2013 Lu Wang <coolwanglu@gmail.com>
* https://github.com/coolwanglu/pdf2htmlEX/blob/master/share/LICENSE
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/*!
* Fancy styles for pdf2htmlEX
* Copyright 2012,2013 Lu Wang <coolwanglu@gmail.com>
* https://github.com/coolwanglu/pdf2htmlEX/blob/master/share/LICENSE
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')format("woff");}.ff1{font-family:ff1;line-height:1.000000;font-style:normal;font-weight:normal;visibility:visible;}
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')format("woff");}.ff4{font-family:ff4;line-height:1.000000;font-style:normal;font-weight:normal;visibility:visible;}
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<ul><li><a class="l" href="#pf1" data-dest-detail='[1,"XYZ",72,289.393,null]'>Introduction</a></li><li><a class="l" href="#pf2" data-dest-detail='[2,"XYZ",72,393.281,null]'>Preliminaries</a></li><li><a class="l" href="#pf3" data-dest-detail='[3,"XYZ",72,207.402,null]'>Existing approaches</a><ul><li><a class="l" href="#pf3" data-dest-detail='[3,"XYZ",314.092,457.174,null]'>Raster image-based approaches</a></li><li><a class="l" href="#pf4" data-dest-detail='[4,"XYZ",72,353.319,null]'>SVG-based approaches</a></li><li><a class="l" href="#pf4" data-dest-detail='[4,"XYZ",314.092,399.048,null]'>Semantic HTML-based approaches</a></li><li><a class="l" href="#pf5" data-dest-detail='[5,"XYZ",72,194.028,null]'>Presentation HTML-based approaches</a></li><li><a class="l" href="#pf5" data-dest-detail='[5,"XYZ",314.092,368.706,null]'>JavaScript-based approaches for TeX</a></li><li><a class="l" href="#pf6" data-dest-detail='[6,"XYZ",72,650.815,null]'>JavaScript-based approaches for PDF</a></li><li><a class="l" href="#pf6" data-dest-detail='[6,"XYZ",72,333.007,null]'>Plugin-based approaches</a></li><li><a class="l" href="#pf6" data-dest-detail='[6,"XYZ",314.092,672.054,null]'>Third-party services</a></li><li><a class="l" href="#pf6" data-dest-detail='[6,"XYZ",314.092,318.777,null]'>Discussion</a></li></ul></li><li><a class="l" href="#pf7" data-dest-detail='[7,"XYZ",72,584.101,null]'>A tour of pdf2htmlEX</a><ul><li><a class="l" href="#pf7" data-dest-detail='[7,"XYZ",314.092,552.39,null]'>Quick start</a></li><li><a class="l" href="#pf7" data-dest-detail='[7,"XYZ",314.092,247.802,null]'>Separating resource files</a></li><li><a class="l" href="#pf8" data-dest-detail='[8,"XYZ",72,157.886,null]'>Splitting pages</a></li><li><a class="l" href="#pf8" data-dest-detail='[8,"XYZ",314.092,110.342,null]'>Image format for backgrounds</a></li><li><a class="l" href="#pf9" data-dest-detail='[9,"XYZ",72,610.282,null]'>Customizing the output</a></li><li><a class="l" href="#pf9" data-dest-detail='[9,"XYZ",72,323.671,null]'>Secrets of pdf2htmlEX</a></li><li><a class="l" href="#pf9" data-dest-detail='[9,"XYZ",314.092,432.467,null]'>Future work</a></li><li><a class="l" href="#pfb" data-dest-detail='[11,"XYZ",314.092,386.695,null]'>Discussion</a></li></ul></li><li><a class="l" href="#pfb" data-dest-detail='[11,"XYZ",314.092,266.479,null]'>Conclusion</a></li></ul></div>
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"/><div class="t m0 x0 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">TUGb<span class="_ _0"></span>oat,<span class="_ _1"> </span>V<span class="_ _2"></span>olume<span class="_ _1"> </span>34<span class="_ _1"> </span>(2013),<span class="_ _1"> </span>No.<span class="_ _1"> </span>3<span class="_ _3"> </span>313</div><div class="t m0 x0 h3 y2 ff2 fs0 fc0 sc0 ls0 ws0">Online<span class="_ _4"> </span>publishing<span class="_ _4"> </span>via<span class="_ _4"> </span>p<span class="_ _0"></span>df2h<span class="_ _5"></span>tml<span class="ff3 fs1">EX</span></div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0">Lu<span class="_ _1"> </span>W<span class="_ _2"></span>ang<span class="_ _1"> </span>and<span class="_ _1"> </span>W<span class="_ _2"></span>anmin<span class="_ _1"> </span>Liu</div><div class="t m0 x0 h3 y4 ff2 fs0 fc0 sc0 ls0 ws0">Abstract</div><div class="t m1 x0 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0">The<span class="_ _1"> </span>W<span class="_ _2"></span>eb<span class="_ _4"> </span>has<span class="_ _1"> </span>long<span class="_ _1"> </span>b<span class="_ _0"></span>ecome<span class="_ _1"> </span>an<span class="_ _4"> </span>essen<span class="_ _5"></span>tial<span class="_ _1"> </span>part<span class="_ _1"> </span>of<span class="_ _1"> </span>our</div><div class="t m1 x0 h2 y6 ff1 fs0 fc0 sc0 ls0 ws0">liv<span class="_ _5"></span>es.<span class="_ _6"> </span>While<span class="_ _7"> </span>w<span class="_ _5"></span>eb<span class="_ _7"> </span>tec<span class="_ _5"></span>hnologies<span class="_ _7"> </span>ha<span class="_ _5"></span>v<span class="_ _5"></span>e<span class="_ _7"> </span>b<span class="_ _0"></span>een<span class="_ _7"> </span>activ<span class="_ _5"></span>ely</div><div class="t m2 x0 h2 y7 ff1 fs0 fc0 sc0 ls0 ws0">dev<span class="_ _5"></span>elop<span class="_ _0"></span>ed for<span class="_ _1"> </span>y<span class="_ _5"></span>ears,<span class="_ _8"> </span>there<span class="_ _8"> </span>is still<span class="_ _8"> </span>a<span class="_ _8"> </span>large<span class="_ _8"> </span>gap<span class="_ _8"> </span>b<span class="_ _0"></span>etw<span class="_ _5"></span>een</div><div class="t m3 x0 h2 y8 ff1 fs0 fc0 sc0 ls0 ws0">w<span class="_ _5"></span>eb<span class="_ _1"> </span>and<span class="_ _1"> </span>traditional<span class="_ _1"> </span>pap<span class="_ _0"></span>er<span class="_ _1"> </span>publishing.<span class="_ _7"> </span>F<span class="_ _2"></span>or<span class="_ _8"> </span>example,</div><div class="t m2 x0 h2 y9 ff1 fs0 fc0 sc0 ls0 ws0">the <span class="ff4 fs1">PDF </span>format,<span class="_ _8"> </span>the <span class="ff5">de<span class="_ _8"> </span>facto<span class="_ _8"> </span></span>standard for publishing,</div><div class="t m1 x0 h2 ya ff1 fs0 fc0 sc0 ls0 ws0">is<span class="_ _7"> </span>not<span class="_ _4"> </span>supp<span class="_ _0"></span>orted<span class="_ _7"> </span>in<span class="_ _7"> </span>the<span class="_ _4"> </span><span class="ff4 fs1">HTML<span class="_ _7"> </span></span>standard;<span class="_ _7"> </span>and<span class="_ _7"> </span>the</div><div class="t m1 x0 h2 yb ff1 fs0 fc0 sc0 ls0 ws0">most<span class="_ _1"> </span>pow<span class="_ _5"></span>erful<span class="_ _8"> </span>typesetting<span class="_ _1"> </span>system,<span class="_ _1"> </span>T</div><div class="t m0 x2 h2 yc ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 x3 h2 yb ff1 fs0 fc0 sc0 ls0 ws0">X,<span class="_ _1"> </span>cannot<span class="_ _8"> </span>b<span class="_ _0"></span>e</div><div class="t m0 x0 h2 yd ff1 fs0 fc0 sc0 ls0 ws0">in<span class="_ _5"></span>tegrated<span class="_ _1"> </span>p<span class="_ _0"></span>erfectly<span class="_ _2"></span>.</div><div class="t m1 x1 h2 ye ff1 fs0 fc0 sc0 ls0 ws0">Despite<span class="_ _8"> </span>of<span class="_ _1"> </span>the<span class="_ _1"> </span>long<span class="_ _1"> </span>history<span class="_ _1"> </span>of<span class="_ _1"> </span>p<span class="_ _0"></span>eople<span class="_ _8"> </span>trying<span class="_ _1"> </span>to</div><div class="t m2 x0 h2 yf ff1 fs0 fc0 sc0 ls0 ws0">con<span class="_ _5"></span>v<span class="_ _5"></span>ert T</div><div class="t m0 x4 h2 y10 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m2 x5 h2 yf ff1 fs0 fc0 sc0 ls0 ws0">X or <span class="ff4 fs1">PDF </span>into <span class="ff4 fs1">HTML</span>, some are fo<span class="_ _0"></span>cused on</div><div class="t m4 x0 h2 y11 ff1 fs0 fc0 sc0 ls0 ws0">only<span class="_ _1"> </span>a<span class="_ _1"> </span>small<span class="_ _1"> </span>fraction<span class="_ _1"> </span>of<span class="_ _1"> </span>features,<span class="_ _1"> </span><span class="ff5">e.g.<span class="_ _1"> </span></span>text,<span class="_ _1"> </span>formulas</div><div class="t m5 x0 h2 y12 ff1 fs0 fc0 sc0 ls0 ws0">or<span class="_ _1"> </span>images;<span class="_ _1"> </span>some<span class="_ _1"> </span>are<span class="_ _1"> </span>to<span class="_ _0"></span>o<span class="_ _1"> </span>old<span class="_ _4"> </span>to<span class="_ _8"> </span>supp<span class="_ _0"></span>ort<span class="_ _1"> </span>new<span class="_ _1"> </span>features</div><div class="t m1 x0 h2 y13 ff1 fs0 fc0 sc0 ls0 ws0">in<span class="_ _4"> </span>the<span class="_ _4"> </span><span class="ff4 fs1">HTML<span class="_ _4"> </span></span>standard<span class="_ _4"> </span>such<span class="_ _4"> </span>as<span class="_ _4"> </span>fon<span class="_ _5"></span>t<span class="_ _4"> </span>em<span class="_ _5"></span>bedding<span class="_ _4"> </span>or</div><div class="t m6 x0 h2 y14 ff1 fs0 fc0 sc0 ls0 ws0">linear<span class="_ _8"> </span>transformations<span class="_ _1"> </span>(<span class="ff5">e.g.<span class="_ _1"> </span></span>rotation);<span class="_ _1"> </span>some<span class="_ _1"> </span>display</div><div class="t m0 x0 h2 y15 ff1 fs0 fc0 sc0 ls0 ws0">ev<span class="_ _5"></span>erything<span class="_ _1"> </span>in<span class="_ _1"> </span>images<span class="_ _1"> </span>at<span class="_ _1"> </span>the<span class="_ _1"> </span>cost<span class="_ _1"> </span>of<span class="_ _1"> </span>larger<span class="_ _1"> </span>sizes.</div><div class="t m1 x1 h2 y16 ff1 fs0 fc0 sc0 ls0 ws0">In<span class="_ _7"> </span>this<span class="_ _9"> </span>article,<span class="_ _7"> </span>while<span class="_ _7"> </span>w<span class="_ _5"></span>e<span class="_ _9"> </span>survey<span class="_ _9"> </span>and<span class="_ _9"> </span>compare</div><div class="t m1 x0 h2 y17 ff1 fs0 fc0 sc0 ls0 ws0">existing<span class="_ _4"> </span>metho<span class="_ _0"></span>ds<span class="_ _4"> </span>of<span class="_ _9"> </span>publishing<span class="_ _4"> </span>T</div><div class="t m0 x6 h2 y18 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 x7 h2 y17 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _4"> </span>or<span class="_ _4"> </span><span class="ff4 fs1">PDF<span class="_ _9"> </span></span>docu-</div><div class="t m2 x0 h2 y19 ff1 fs0 fc0 sc0 ls0 ws0">men<span class="_ _5"></span>ts<span class="_ _8"> </span>online,<span class="_ _1"> </span>a<span class="_ _8"> </span>new<span class="_ _8"> </span>approach<span class="_ _8"> </span>is<span class="_ _8"> </span>attempted<span class="_ _1"> </span>to<span class="_ _8"> </span>attack</div><div class="t m1 x0 h2 y1a ff1 fs0 fc0 sc0 ls0 ws0">this<span class="_ _4"> </span>issue.<span class="_ _a"> </span>W<span class="_ _2"></span>e<span class="_ _4"> </span>introduce<span class="_ _4"> </span>an<span class="_ _4"> </span>op<span class="_ _0"></span>en<span class="_ _4"> </span>source<span class="_ _4"> </span>program,</div><div class="t m2 x0 h2 y1b ff1 fs0 fc0 sc0 ls0 ws0">called<span class="_ _8"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX</span>, which is<span class="_ _1"> </span>a<span class="_ _8"> </span>general<span class="_ _8"> </span><span class="ff4 fs1">PDF<span class="_ _8"> </span></span>to<span class="_ _8"> </span><span class="ff4 fs1">HTML</span></div><div class="t m1 x0 h2 y1c ff1 fs0 fc0 sc0 ls0 ws0">con<span class="_ _5"></span>v<span class="_ _5"></span>erter<span class="_ _1"> </span>and<span class="_ _1"> </span>publishing<span class="_ _1"> </span>to<span class="_ _0"></span>ol<span class="_ _1"> </span>with<span class="_ _1"> </span>high<span class="_ _1"> </span>fidelity<span class="_ _2"></span>.<span class="_ _9"> </span>It</div><div class="t m1 x0 h2 y1d ff1 fs0 fc0 sc0 ls0 ws0">presen<span class="_ _5"></span>ts<span class="_ _9"> </span><span class="ff4 fs1">PDF<span class="_ _9"> </span></span>elements<span class="_ _4"> </span>with<span class="_ _7"> </span>corresp<span class="_ _0"></span>onding<span class="_ _9"> </span>native</div><div class="t m1 x0 h2 y1e ff4 fs1 fc0 sc0 ls0 ws0">HTML<span class="_ _1"> </span><span class="ff1 fs0">elements,<span class="_ _1"> </span>in<span class="_ _1"> </span>order<span class="_ _4"> </span>to<span class="_ _8"> </span>achiev<span class="_ _5"></span>e<span class="_ _1"> </span>high<span class="_ _1"> </span>accuracy</span></div><div class="t m1 x0 h2 y1f ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _9"> </span>small<span class="_ _7"> </span>size.<span class="_ _b"> </span>The<span class="_ _9"> </span>flexible<span class="_ _7"> </span>design<span class="_ _9"> </span>also<span class="_ _7"> </span>makes<span class="_ _9"> </span>it</div><div class="t m7 x0 h2 y20 ff1 fs0 fc0 sc0 ls0 ws0">useful<span class="_ _1"> </span>for<span class="_ _1"> </span>a<span class="_ _1"> </span>v<span class="_ _5"></span>ariet<span class="_ _5"></span>y<span class="_ _8"> </span>of<span class="_ _1"> </span>use<span class="_ _1"> </span>cases<span class="_ _1"> </span>in<span class="_ _1"> </span>online<span class="_ _1"> </span>publishing.</div><div class="t m8 x0 h2 y21 ff1 fs0 fc0 sc0 ls0 ws0">Ob<span class="_ _5"></span>viously<span class="_ _8"> </span>T</div><div class="t m0 x8 h2 y22 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m8 x9 h2 y21 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _8"> </span>users<span class="_ _1"> </span>can<span class="_ _1"> </span>immediately<span class="_ _1"> </span>b<span class="_ _0"></span>enefit<span class="_ _1"> </span>with</div><div class="t m2 x0 h2 y23 ff1 fs0 fc0 sc0 ls0 ws0">zero learning cost, just like</div><div class="t m0 xa h4 y23 ff6 fs0 fc0 sc0 ls0 ws0">dvipdf</div><div class="t m2 xb h2 y23 ff1 fs0 fc0 sc0 ls0 ws0">while p<span class="_ _0"></span>eople were</div><div class="t m9 x0 h2 y24 ff1 fs0 fc0 sc0 ls0 ws0">still<span class="_ _1"> </span>using<span class="_ _1"> </span><span class="ff4 fs1">DVI</span>.<span class="_ _9"> </span>More<span class="_ _1"> </span>information<span class="_ _4"> </span>is<span class="_ _8"> </span>av<span class="_ _2"></span>ailable<span class="_ _1"> </span>at<span class="_ _1"> </span>the</div><div class="t m0 x0 h2 y25 ff1 fs0 fc0 sc0 ls0 ws0">home<span class="_ _1"> </span>page:</div><div class="t m0 x0 h4 y26 ff6 fs0 fc0 sc0 ls0 ws0">https://github.com/coolwanglu/pdf2htmlex</div><div class="t m0 x0 h3 y27 ff2 fs0 fc0 sc0 ls0 ws0">1<span class="_ _c"> </span>In<span class="_ _5"></span>tro<span class="_ _0"></span>duction</div><div class="t ma xc h2 y28 ff1 fs0 fc0 sc0 ls0 ws0">rguably<span class="_ _2"></span>,<span class="_ _1"> </span>for<span class="_ _1"> </span>man<span class="_ _5"></span>y<span class="_ _1"> </span>p<span class="_ _0"></span>eople<span class="_ _1"> </span>the<span class="_ _1"> </span>W<span class="_ _2"></span>orld<span class="_ _1"> </span>Wide</div><div class="t m2 xc h2 y29 ff1 fs0 fc0 sc0 ls0 ws0">W<span class="_ _2"></span>eb<span class="_ _1"> </span><span class="ff5">is<span class="_ _9"> </span></span>the<span class="_ _1"> </span>In<span class="_ _5"></span>ternet.<span class="_ _7"> </span>Indeed,<span class="_ _1"> </span>web<span class="_ _8"> </span>technolo-</div><div class="t m2 xc h2 y2a ff1 fs0 fc0 sc0 ls0 ws0">gies<span class="_ _8"> </span>hav<span class="_ _5"></span>e<span class="_ _8"> </span>b<span class="_ _0"></span>een<span class="_ _1"> </span>so<span class="_ _8"> </span>actively<span class="_ _8"> </span>developed<span class="_ _1"> </span>in<span class="_ _8"> </span>the</div><div class="t m1 xc h2 y2b ff1 fs0 fc0 sc0 ls0 ws0">past<span class="_ _9"> </span>few<span class="_ _7"> </span>years,<span class="_ _7"> </span>now<span class="_ _5"></span>ada<span class="_ _5"></span>ys<span class="_ _9"> </span>web<span class="_ _9"> </span>pages<span class="_ _7"> </span>far</div><div class="t m1 x0 h2 y2c ff1 fs0 fc0 sc0 ls0 ws0">surpass<span class="_ _4"> </span>plain<span class="_ _4"> </span>text<span class="_ _4"> </span>and<span class="_ _4"> </span>images.<span class="_ _a"> </span><span class="ff4 fs1">HTML</span>5<span class="_ _4"> </span>brings<span class="_ _4"> </span>au-</div><div class="t m2 x0 h2 y2d ff1 fs0 fc0 sc0 ls0 ws0">dio,<span class="_ _8"> </span>video,<span class="_ _8"> </span>3<span class="ff4 fs1">D<span class="_ _8"> </span></span>graphics<span class="_ _8"> </span>and<span class="_ _8"> </span>many other<span class="_ _8"> </span>rich features;</div><div class="t m2 x0 h2 y2e ff4 fs1 fc0 sc0 ls0 ws0">CSS<span class="ff1 fs0">3 defines<span class="_ _d"> </span>brand new<span class="_ _d"> </span>visual effects, and Ja<span class="_ _e"></span>v<span class="_ _e"></span>aScript</span></div><div class="t m1 x0 h2 y2f ff1 fs0 fc0 sc0 ls0 ws0">allo<span class="_ _5"></span>ws<span class="_ _1"> </span>different<span class="_ _8"> </span>kinds<span class="_ _1"> </span>of<span class="_ _1"> </span>user<span class="_ _1"> </span>interactions.<span class="_ _7"> </span>Mo<span class="_ _0"></span>dern</div><div class="t m1 x0 h2 y30 ff1 fs0 fc0 sc0 ls0 ws0">w<span class="_ _5"></span>eb<span class="_ _9"> </span>bro<span class="_ _e"></span>wsers<span class="_ _9"> </span>are<span class="_ _9"> </span>literally<span class="_ _9"> </span>op<span class="_ _0"></span>erating<span class="_ _9"> </span>systems,<span class="_ _7"> </span>and</div><div class="t mb x0 h2 y31 ff1 fs0 fc0 sc0 ls0 ws0">the<span class="_ _8"> </span>b<span class="_ _0"></span>oundary<span class="_ _1"> </span>b<span class="_ _0"></span>etw<span class="_ _e"></span>een<span class="_ _1"> </span>web<span class="_ _8"> </span>apps<span class="_ _1"> </span>and<span class="_ _1"> </span>lo<span class="_ _0"></span>cal<span class="_ _1"> </span>soft<span class="_ _e"></span>ware</div><div class="t m1 x0 h2 y32 ff1 fs0 fc0 sc0 ls0 ws0">has<span class="_ _1"> </span>been<span class="_ _1"> </span>blurred.<span class="_ _7"> </span>T<span class="_ _2"></span>o<span class="_ _0"></span>day<span class="_ _2"></span>,<span class="_ _8"> </span>we<span class="_ _8"> </span>can<span class="_ _1"> </span>access<span class="_ _1"> </span>the<span class="_ _1"> </span><span class="ff4 fs1">WWW</span></div><div class="t m1 x0 h2 y33 ff1 fs0 fc0 sc0 ls0 ws0">with<span class="_ _4"> </span>all<span class="_ _9"> </span>kinds<span class="_ _9"> </span>of<span class="_ _4"> </span>devices<span class="_ _9"> </span>suc<span class="_ _5"></span>h<span class="_ _4"> </span>as<span class="_ _9"> </span>watc<span class="_ _e"></span>hes,<span class="_ _9"> </span>phones,</div><div class="t mc x0 h2 y34 ff1 fs0 fc0 sc0 ls0 ws0">tablets,<span class="_ _1"> </span>computers<span class="_ _8"> </span>and<span class="_ _1"> </span>even<span class="_ _8"> </span>glasses.<span class="_ _7"> </span>It<span class="_ _1"> </span>has<span class="_ _1"> </span>b<span class="_ _0"></span>ecome</div><div class="t m0 x0 h2 y35 ff1 fs0 fc0 sc0 ls0 ws0">an<span class="_ _1"> </span>essen<span class="_ _5"></span>tial<span class="_ _1"> </span>part<span class="_ _1"> </span>of<span class="_ _1"> </span>our<span class="_ _1"> </span>liv<span class="_ _5"></span>es.</div><div class="t m1 x1 h2 y36 ff1 fs0 fc0 sc0 ls0 ws0">The<span class="_ _4"> </span>w<span class="_ _e"></span>eb<span class="_ _4"> </span>tec<span class="_ _e"></span>hnologies<span class="_ _4"> </span>pro<span class="_ _e"></span>vide<span class="_ _4"> </span>brand<span class="_ _1"> </span>new<span class="_ _4"> </span>user</div><div class="t mc x0 h2 y37 ff1 fs0 fc0 sc0 ls0 ws0">exp<span class="_ _0"></span>eriences<span class="_ _1"> </span>compared<span class="_ _1"> </span>to<span class="_ _1"> </span>traditional<span class="_ _8"> </span>media.<span class="_ _7"> </span>T<span class="_ _2"></span>aking</div><div class="t m2 x0 h2 y38 ff1 fs0 fc0 sc0 ls0 ws0">Wikip<span class="_ _0"></span>edia as<span class="_ _8"> </span>an<span class="_ _8"> </span>example,<span class="_ _8"> </span>it<span class="_ _8"> </span>has <span class="ff5">rich<span class="_ _1"> </span>c<span class="_ _e"></span>ontents<span class="ff1">:<span class="_ _7"> </span>inside</span></span></div><div class="t md xd h2 y39 ff1 fs0 fc0 sc0 ls0 ws0">an<span class="_ _1"> </span>article,<span class="_ _1"> </span>b<span class="_ _0"></span>esides<span class="_ _1"> </span>plain<span class="_ _4"> </span>text,<span class="_ _8"> </span>there<span class="_ _1"> </span>are<span class="_ _4"> </span>often<span class="_ _8"> </span>images,</div><div class="t m2 xd h2 y3a ff1 fs0 fc0 sc0 ls0 ws0">animations,<span class="_ _1"> </span>audio<span class="_ _1"> </span>and<span class="_ _1"> </span>video<span class="_ _1"> </span>that<span class="_ _1"> </span>are<span class="_ _4"> </span>relev<span class="_ _2"></span>ant<span class="_ _8"> </span>to<span class="_ _1"> </span>the</div><div class="t m1 xd h2 y3b ff1 fs0 fc0 sc0 ls0 ws0">topic;<span class="_ _4"> </span>it<span class="_ _1"> </span>is<span class="_ _4"> </span><span class="ff5">wel<span class="_ _0"></span>l<span class="_ _4"> </span>or<span class="_ _e"></span>ganize<span class="_ _e"></span>d<span class="ff1">:<span class="_ _f"> </span>users<span class="_ _1"> </span>may<span class="_ _1"> </span>jump<span class="_ _4"> </span>to<span class="_ _1"> </span>rele-</span></span></div><div class="t me xd h2 y3c ff1 fs0 fc0 sc0 ls0 ws0">v<span class="_ _e"></span>an<span class="_ _e"></span>t<span class="_ _1"> </span>articles<span class="_ _4"> </span>b<span class="_ _e"></span>y<span class="_ _1"> </span>clicking<span class="_ _8"> </span>links;<span class="_ _1"> </span>it<span class="_ _1"> </span>is<span class="_ _4"> </span><span class="ff5">inter<span class="_ _2"></span>active<span class="ff1">:<span class="_ _7"> </span>users</span></span></div><div class="t mf xd h2 y3d ff1 fs0 fc0 sc0 ls0 ws0">ma<span class="_ _e"></span>y<span class="_ _1"> </span>create<span class="_ _1"> </span>or<span class="_ _1"> </span>edit<span class="_ _1"> </span>an<span class="_ _1"> </span>article;<span class="_ _1"> </span>it<span class="_ _1"> </span>is<span class="_ _1"> </span><span class="ff5">p<span class="_ _e"></span>ersonalize<span class="_ _e"></span>d<span class="ff1">:<span class="_ _7"> </span>the</span></span></div><div class="t m2 xd h2 y3e ff1 fs0 fc0 sc0 ls0 ws0">app<span class="_ _0"></span>earance of the<span class="_ _d"> </span>w<span class="_ _e"></span>eb site resp<span class="_ _0"></span>ects users preferences</div><div class="t m2 xd h2 y3f ff1 fs0 fc0 sc0 ls0 ws0">suc<span class="_ _e"></span>h<span class="_ _1"> </span>as<span class="_ _1"> </span>language,<span class="_ _1"> </span>theme<span class="_ _1"> </span>or<span class="_ _1"> </span>format;<span class="_ _1"> </span>it<span class="_ _8"> </span>is<span class="_ _1"> </span><span class="ff5">so<span class="_ _e"></span>cial<span class="ff1">:<span class="_ _7"> </span>users</span></span></div><div class="t m5 xd h2 y40 ff1 fs0 fc0 sc0 ls0 ws0">ma<span class="_ _e"></span>y<span class="_ _4"> </span>lea<span class="_ _e"></span>ve<span class="_ _8"> </span>comments<span class="_ _8"> </span>and<span class="_ _4"> </span>ha<span class="_ _e"></span>v<span class="_ _e"></span>e<span class="_ _4"> </span>discussions<span class="_ _8"> </span>regarding</div><div class="t m0 xd h2 y41 ff1 fs0 fc0 sc0 ls0 ws0">an<span class="_ _1"> </span>article.</div><div class="t m5 xe h2 y42 ff1 fs0 fc0 sc0 ls0 ws0">Compared<span class="_ _1"> </span>with<span class="_ _1"> </span>traditional<span class="_ _1"> </span>publishing<span class="_ _1"> </span>media,<span class="_ _4"> </span>it</div><div class="t m1 xd h2 y43 ff1 fs0 fc0 sc0 ls0 ws0">is<span class="_ _9"> </span>more<span class="_ _9"> </span>conv<span class="_ _e"></span>enien<span class="_ _5"></span>t<span class="_ _9"> </span>and<span class="_ _9"> </span>easier<span class="_ _9"> </span>for<span class="_ _9"> </span>users<span class="_ _9"> </span>to<span class="_ _9"> </span>obtain,</div><div class="t md xd h2 y44 ff1 fs0 fc0 sc0 ls0 ws0">view<span class="_ _1"> </span>and<span class="_ _1"> </span>share<span class="_ _1"> </span>the<span class="_ _4"> </span>con<span class="_ _e"></span>ten<span class="_ _e"></span>ts.<span class="_ _f"> </span>While<span class="_ _8"> </span>most<span class="_ _1"> </span>features<span class="_ _4"> </span>in</div><div class="t m10 xd h2 y45 ff4 fs1 fc0 sc0 ls0 ws0">HTML<span class="_ _8"> </span><span class="ff1 fs0">are<span class="_ _1"> </span>targeting<span class="_ _1"> </span>visual<span class="_ _1"> </span>effects,<span class="_ _1"> </span>multimedia<span class="_ _8"> </span>and</span></div><div class="t m1 xd h2 y46 ff1 fs0 fc0 sc0 ls0 ws0">ric<span class="_ _5"></span>h<span class="_ _1"> </span>Internet<span class="_ _8"> </span>applications,<span class="_ _4"> </span>there<span class="_ _8"> </span>is<span class="_ _1"> </span>still<span class="_ _4"> </span>a<span class="_ _8"> </span>large<span class="_ _1"> </span>gap</div><div class="t m11 xd h2 y47 ff1 fs0 fc0 sc0 ls0 ws0">b<span class="_ _0"></span>et<span class="_ _e"></span>ween<span class="_ _1"> </span>the<span class="_ _8"> </span>W<span class="_ _2"></span>eb<span class="_ _1"> </span>and<span class="_ _1"> </span>traditional<span class="_ _1"> </span>publishing.<span class="_ _7"> </span>Many</div><div class="t m12 xd h2 y48 ff1 fs0 fc0 sc0 ls0 ws0">existing<span class="_ _1"> </span>publishing<span class="_ _1"> </span>technologies<span class="_ _8"> </span>cannot<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>p<span class="_ _0"></span>erfectly</div><div class="t m1 xd h2 y49 ff1 fs0 fc0 sc0 ls0 ws0">in<span class="_ _5"></span>tegrated<span class="_ _1"> </span>online<span class="_ _10"> </span>—<span class="_ _10"> </span>especially<span class="_ _4"> </span>t<span class="_ _e"></span>w<span class="_ _5"></span>o<span class="_ _1"> </span>of<span class="_ _1"> </span>them<span class="_ _4"> </span>focused</div><div class="t m2 xd h2 y4a ff1 fs0 fc0 sc0 ls0 ws0">on<span class="_ _1"> </span>in<span class="_ _1"> </span>this<span class="_ _1"> </span>article,<span class="_ _4"> </span><span class="ff4 fs1">PDF<span class="_ _8"> </span></span>and<span class="_ _4"> </span>T</div><div class="t m0 xf h2 y4b ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m2 x10 h2 y4a ff1 fs0 fc0 sc0 ls0 ws0">X,<span class="_ _1"> </span>which<span class="_ _8"> </span>are<span class="_ _1"> </span>the<span class="_ _4"> </span>most</div><div class="t m13 xd h2 y4c ff1 fs0 fc0 sc0 ls0 ws0">p<span class="_ _0"></span>opular<span class="_ _1"> </span>format<span class="_ _1"> </span>and<span class="_ _8"> </span>typesetting<span class="_ _1"> </span>system<span class="_ _1"> </span>resp<span class="_ _0"></span>ectively<span class="_ _2"></span>.</div><div class="t m0 xd h5 y4d ff3 fs1 fc0 sc0 ls0 ws0">PDF</div><div class="t m14 x11 h2 y4d ff1 fs0 fc0 sc0 ls0 ws0">The<span class="_ _8"> </span>Portable<span class="_ _8"> </span>Do<span class="_ _0"></span>cument<span class="_ _8"> </span>F<span class="_ _2"></span>ormat,<span class="_ _1"> </span>developed</div><div class="t m2 xd h2 y4e ff1 fs0 fc0 sc0 ls0 ws0">b<span class="_ _e"></span>y<span class="_ _8"> </span>Adob<span class="_ _0"></span>e,<span class="_ _8"> </span>is<span class="_ _8"> </span>one of<span class="_ _8"> </span>the most<span class="_ _8"> </span>p<span class="_ _0"></span>opular formats<span class="_ _8"> </span>for dig-</div><div class="t m15 xd h2 y4f ff1 fs0 fc0 sc0 ls0 ws0">ital<span class="_ _1"> </span>documents.<span class="_ _9"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>is<span class="_ _1"> </span>known<span class="_ _8"> </span>for<span class="_ _1"> </span>its<span class="_ _1"> </span>wide<span class="_ _1"> </span>supp<span class="_ _0"></span>ort</div><div class="t mf xd h2 y50 ff1 fs0 fc0 sc0 ls0 ws0">of<span class="_ _1"> </span>differen<span class="_ _e"></span>t<span class="_ _1"> </span>types<span class="_ _1"> </span>of<span class="_ _1"> </span>fonts,<span class="_ _8"> </span>enco<span class="_ _0"></span>dings,<span class="_ _1"> </span>raster<span class="_ _1"> </span>images,</div><div class="t m16 xd h2 y51 ff1 fs0 fc0 sc0 ls0 ws0">v<span class="_ _5"></span>ector<span class="_ _8"> </span>graphics,<span class="_ _1"> </span>and<span class="_ _1"> </span>many<span class="_ _8"> </span>other<span class="_ _1"> </span>features<span class="_ _8"> </span>from<span class="_ _1"> </span>pre-</div><div class="t m1 xd h2 y52 ff1 fs0 fc0 sc0 ls0 ws0">press<span class="_ _7"> </span>pro<span class="_ _0"></span>cessing<span class="_ _7"> </span>to<span class="_ _11"> </span>user<span class="_ _7"> </span>interaction.<span class="_ _6"> </span>It<span class="_ _7"> </span>is<span class="_ _11"> </span>widely</div><div class="t m2 xd h2 y53 ff1 fs0 fc0 sc0 ls0 ws0">supp<span class="_ _0"></span>orted<span class="_ _8"> </span>in<span class="_ _8"> </span>different op<span class="_ _0"></span>erating<span class="_ _8"> </span>systems<span class="_ _8"> </span>and<span class="_ _8"> </span>devices.</div><div class="t m17 xd h2 y54 ff1 fs0 fc0 sc0 ls0 ws0">No<span class="_ _e"></span>wada<span class="_ _e"></span>ys,<span class="_ _4"> </span>almost<span class="_ _8"> </span>all<span class="_ _1"> </span>do<span class="_ _0"></span>cuments<span class="_ _8"> </span>can<span class="_ _4"> </span>be<span class="_ _1"> </span>exp<span class="_ _0"></span>orted<span class="_ _1"> </span>to</div><div class="t m2 xd h2 y55 ff4 fs1 fc0 sc0 ls0 ws0">PDF<span class="ff1 fs0">.<span class="_ _7"> </span>Notably<span class="_ _2"></span>,<span class="_ _8"> </span>with<span class="_ _1"> </span>a<span class="_ _8"> </span>virtual<span class="_ _1"> </span><span class="ff4 fs1">PDF<span class="_ _8"> </span></span>printer,<span class="_ _8"> </span>any do<span class="_ _0"></span>cu-</span></div><div class="t m2 xd h2 y56 ff1 fs0 fc0 sc0 ls0 ws0">men<span class="_ _e"></span>t<span class="_ _4"> </span>that<span class="_ _8"> </span>can<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>printed<span class="_ _8"> </span>on<span class="_ _1"> </span>pap<span class="_ _0"></span>er<span class="_ _1"> </span>can<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>conv<span class="_ _e"></span>erted</div><div class="t m1 xd h2 y57 ff1 fs0 fc0 sc0 ls0 ws0">to<span class="_ _9"> </span><span class="ff4 fs1">PDF</span>.<span class="_ _12"> </span>It<span class="_ _9"> </span>has<span class="_ _4"> </span>b<span class="_ _0"></span>ecome<span class="_ _9"> </span>the<span class="_ _9"> </span><span class="ff5">de<span class="_ _9"> </span>facto<span class="_ _9"> </span></span>standard<span class="_ _9"> </span>for</div><div class="t m3 xd h2 y58 ff1 fs0 fc0 sc0 ls0 ws0">academic<span class="_ _1"> </span>articles,<span class="_ _8"> </span>technical<span class="_ _8"> </span>rep<span class="_ _0"></span>orts,<span class="_ _1"> </span>manuals,<span class="_ _8"> </span>news-</div><div class="t m9 xd h2 y59 ff1 fs0 fc0 sc0 ls0 ws0">pap<span class="_ _0"></span>ers<span class="_ _1"> </span>and<span class="_ _1"> </span>eb<span class="_ _0"></span>o<span class="_ _0"></span>oks.<span class="_ _7"> </span>As<span class="_ _1"> </span>an<span class="_ _1"> </span>example,<span class="_ _1"> </span>the<span class="_ _1"> </span>final<span class="_ _4"> </span>format</div><div class="t m0 xd h2 y5a ff1 fs0 fc0 sc0 ls0 ws0">for<span class="_ _1"> </span><span class="ff7">TUGb<span class="_ _0"></span>oat<span class="_ _1"> </span></span>is<span class="_ _1"> </span><span class="ff4 fs1">PDF</span>.</div><div class="t m1 xe h2 y5b ff4 fs1 fc0 sc0 ls0 ws0">PDF<span class="_ _4"> </span><span class="ff1 fs0">is<span class="_ _1"> </span>a<span class="_ _4"> </span>prin<span class="_ _e"></span>t-ready<span class="_ _4"> </span>format;<span class="_ _4"> </span>it<span class="_ _4"> </span>is<span class="_ _1"> </span>designed<span class="_ _4"> </span>to</span></div><div class="t m18 xd h2 y5c ff1 fs0 fc0 sc0 ls0 ws0">completely<span class="_ _1"> </span>describ<span class="_ _0"></span>e<span class="_ _1"> </span>a<span class="_ _1"> </span>fixed-lay<span class="_ _e"></span>out<span class="_ _1"> </span>flat<span class="_ _1"> </span>do<span class="_ _0"></span>cument.<span class="_ _9"> </span>A</div><div class="t ma xd h2 y5d ff4 fs1 fc0 sc0 ls0 ws0">PDF<span class="_ _1"> </span><span class="ff1 fs0">file<span class="_ _1"> </span>clearly<span class="_ _1"> </span>defines<span class="_ _1"> </span>the<span class="_ _1"> </span>app<span class="_ _0"></span>earance<span class="_ _1"> </span>of<span class="_ _1"> </span>the<span class="_ _1"> </span>do<span class="_ _0"></span>cu-</span></div><div class="t m0 xd h2 y5e ff1 fs0 fc0 sc0 ls0 ws0">men<span class="_ _e"></span>t,<span class="_ _4"> </span>ind<span class="_ _5"></span>ep<span class="_ _0"></span>enden<span class="_ _5"></span>t<span class="_ _1"> </span>of<span class="_ _1"> </span>particular<span class="_ _1"> </span>devices<span class="_ _1"> </span>or<span class="_ _1"> </span>view<span class="_ _5"></span>ers.</div><div class="t m1 xe h2 y5f ff4 fs1 fc0 sc0 ls0 ws0">PDF<span class="_ _4"> </span><span class="ff1 fs0">is<span class="_ _4"> </span>not<span class="_ _4"> </span>supp<span class="_ _0"></span>orted<span class="_ _4"> </span>in<span class="_ _4"> </span>the<span class="_ _4"> </span></span>HTML<span class="_ _4"> </span><span class="ff1 fs0">standard,</span></div><div class="t m2 xd h2 y60 ff1 fs0 fc0 sc0 ls0 ws0">but it<span class="_ _8"> </span>can<span class="_ _8"> </span>b<span class="_ _0"></span>e<span class="_ _8"> </span>viewed directly in<span class="_ _8"> </span>several web bro<span class="_ _e"></span>wsers.</div><div class="t m2 xd h2 y61 ff1 fs0 fc0 sc0 ls0 ws0">Users of<span class="_ _d"> </span>other<span class="_ _d"> </span>w<span class="_ _e"></span>eb bro<span class="_ _e"></span>wsers usually<span class="_ _d"> </span>ha<span class="_ _e"></span>ve<span class="_ _d"> </span>to<span class="_ _d"> </span>read<span class="_ _d"> </span><span class="ff4 fs1">PDF</span></div><div class="t m10 xd h2 y62 ff1 fs0 fc0 sc0 ls0 ws0">do<span class="_ _0"></span>cumen<span class="_ _e"></span>ts<span class="_ _1"> </span>with<span class="_ _1"> </span>web<span class="_ _8"> </span>browser<span class="_ _8"> </span>plugins,<span class="_ _1"> </span>or<span class="_ _1"> </span>do<span class="_ _5"></span>wnload</div><div class="t m2 xd h2 y63 ff1 fs0 fc0 sc0 ls0 ws0">the files<span class="_ _8"> </span>and<span class="_ _8"> </span>then<span class="_ _8"> </span>read<span class="_ _8"> </span>them<span class="_ _8"> </span>with<span class="_ _8"> </span>a<span class="_ _8"> </span>lo<span class="_ _0"></span>cal <span class="ff4 fs1">PDF<span class="_ _8"> </span></span>reader.</div><div class="t m1 xd h2 y64 ff1 fs0 fc0 sc0 ls0 ws0">In<span class="_ _1"> </span>all<span class="_ _4"> </span>these<span class="_ _1"> </span>cases,<span class="_ _4"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>files<span class="_ _4"> </span>are<span class="_ _1"> </span>viewed<span class="_ _1"> </span>in<span class="_ _4"> </span>a<span class="_ _1"> </span>closed</div><div class="t m1 xd h2 y65 ff1 fs0 fc0 sc0 ls0 ws0">en<span class="_ _5"></span>vironmen<span class="_ _e"></span>t<span class="_ _9"> </span>where<span class="_ _9"> </span>users<span class="_ _9"> </span>cannot<span class="_ _9"> </span>utilize<span class="_ _9"> </span>most<span class="_ _9"> </span>w<span class="_ _e"></span>eb</div><div class="t m0 xd h2 y66 ff1 fs0 fc0 sc0 ls0 ws0">features.</div><div class="t m0 x12 h6 y67 ff8 fs2 fc0 sc0 ls0 ws0">1</div><div class="t m0 xd h3 y68 ff2 fs0 fc0 sc0 ls0 ws0">T</div><div class="t m0 x13 h3 y69 ff2 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m0 x14 h3 y68 ff2 fs0 fc0 sc0 ls0 ws0">X</div><div class="t m1 x15 h2 y68 ff1 fs0 fc0 sc0 ls0 ws0">Designed<span class="_ _9"> </span>and<span class="_ _9"> </span>written<span class="_ _9"> </span>by<span class="_ _4"> </span>Professor<span class="_ _9"> </span>Donald</div><div class="t m19 xd h2 y6a ff1 fs0 fc0 sc0 ls0 ws0">Kn<span class="_ _e"></span>uth,<span class="_ _4"> </span>T</div><div class="t m0 x16 h2 y6b ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m19 x17 h2 y6a ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _1"> </span>is<span class="_ _1"> </span>one<span class="_ _1"> </span>of<span class="_ _1"> </span>the<span class="_ _1"> </span>most<span class="_ _1"> </span>p<span class="_ _0"></span>ow<span class="_ _e"></span>erful<span class="_ _1"> </span>typesetting</div><div class="t m1a xd h2 y6c ff1 fs0 fc0 sc0 ls0 ws0">systems<span class="_ _1"> </span>in<span class="_ _1"> </span>the<span class="_ _1"> </span>w<span class="_ _5"></span>orld.</div><div class="t m0 x18 h6 y6d ff8 fs2 fc0 sc0 ls0 ws0">2</div><div class="t m1a x19 h2 y6c ff1 fs0 fc0 sc0 ls0 ws0">It<span class="_ _1"> </span>is<span class="_ _1"> </span>w<span class="_ _5"></span>ell-kno<span class="_ _e"></span>wn<span class="_ _4"> </span>for<span class="_ _8"> </span>its<span class="_ _1"> </span>capa-</div><div class="t m1b xd h2 y6e ff1 fs0 fc0 sc0 ls0 ws0">bilit<span class="_ _e"></span>y<span class="_ _4"> </span>of<span class="_ _8"> </span>pro<span class="_ _0"></span>ducing<span class="_ _4"> </span>high<span class="_ _8"> </span>quality<span class="_ _8"> </span>formulas<span class="_ _1"> </span>and<span class="_ _1"> </span>figures</div><div class="t m0 x1a h7 y6f ff9 fs3 fc0 sc0 ls0 ws0">1</div><div class="t m0 x1b h6 y70 ff8 fs2 fc0 sc0 ls0 ws0">PDF</div><div class="t m1 x16 h8 y70 ffa fs4 fc0 sc0 ls0 ws0">does<span class="_ _4"> </span>include<span class="_ _1"> </span>features<span class="_ _4"> </span>suc<span class="_ _5"></span>h<span class="_ _1"> </span>as<span class="_ _4"> </span>external<span class="_ _1"> </span>links<span class="_ _4"> </span>and</div><div class="t m1c xd h8 y71 ffa fs4 fc0 sc0 ls0 ws0">interactiv<span class="_ _e"></span>e<span class="_ _8"> </span>functions<span class="_ _d"> </span>within<span class="_ _8"> </span>a<span class="_ _13"> </span>document,<span class="_ _13"> </span>but<span class="_ _13"> </span>these<span class="_ _13"> </span>are<span class="_ _13"> </span>quite</div><div class="t m0 xd h8 y72 ffa fs4 fc0 sc0 ls0 ws0">limited<span class="_ _13"> </span>compared<span class="_ _13"> </span>to<span class="_ _13"> </span><span class="ff8 fs2">HTML</span>.</div><div class="t m0 x1a h7 y73 ff9 fs3 fc0 sc0 ls0 ws0">2</div><div class="t m1 x1b h8 y74 ffa fs4 fc0 sc0 ls0 ws0">When<span class="_ _8"> </span>using<span class="_ _8"> </span>T</div><div class="t m0 x1c h8 y75 ffa fs4 fc0 sc0 ls0 ws0">E</div><div class="t m1 x1d h8 y74 ffa fs4 fc0 sc0 ls0 ws0">X<span class="_ _8"> </span>in<span class="_ _8"> </span>this<span class="_ _8"> </span>article,<span class="_ _8"> </span>most<span class="_ _8"> </span>of<span class="_ _8"> </span>the<span class="_ _8"> </span>time<span class="_ _8"> </span>we</div><div class="t m0 xd h8 y38 ffa fs4 fc0 sc0 ls0 ws0">will<span class="_ _13"> </span>b<span class="_ _0"></span>e<span class="_ _13"> </span>referring<span class="_ _13"> </span>to<span class="_ _13"> </span>the<span class="_ _8"> </span>whole<span class="_ _13"> </span>T</div><div class="t m0 x1e h8 y76 ffa fs4 fc0 sc0 ls0 ws0">E</div><div class="t m0 x1f h8 y38 ffa fs4 fc0 sc0 ls0 ws0">X<span class="_ _13"> </span>family<span class="_ _2"></span>.</div><div class="t m0 x1c h2 y77 ff1 fs0 fc0 sc0 ls0 ws0">Online<span class="_ _1"> </span>publishing<span class="_ _1"> </span>via<span class="_ _1"> </span>p<span class="_ _0"></span>df2h<span class="_ _e"></span>tm<span class="_ _0"></span>l<span class="ff4 fs1">EX</span></div><a class="l" href="https://github.com/coolwanglu/pdf2htmlex"><div class="d m1d" style="border-style:none;position:absolute;left:118.804078px;bottom:507.642980px;width:211.206000px;height:11.125000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf1" 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<div id="pf2" class="pf w0 h0" data-page-no="2"><div class="pc pc2 w0 h0"><img class="bi x0 y78 w2 h9" alt="" 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"/><div class="t m0 x0 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">314<span class="_ _3"> </span>TUGb<span class="_ _0"></span>oat,<span class="_ _1"> </span>V<span class="_ _2"></span>olume<span class="_ _1"> </span>34<span class="_ _1"> </span>(2013),<span class="_ _1"> </span>No.<span class="_ _1"> </span>3</div><div class="t m1 x0 h2 y39 ff1 fs0 fc0 sc0 ls0 ws0">in<span class="_ _4"> </span>many<span class="_ _4"> </span>differen<span class="_ _e"></span>t<span class="_ _4"> </span>areas.<span class="_ _a"> </span>While<span class="_ _9"> </span>it<span class="_ _4"> </span>is<span class="_ _4"> </span>most<span class="_ _4"> </span>p<span class="_ _0"></span>opular</div><div class="t m1 x0 h2 y3a ff1 fs0 fc0 sc0 ls0 ws0">in<span class="_ _4"> </span>academia,<span class="_ _9"> </span>it<span class="_ _4"> </span>is<span class="_ _9"> </span>also<span class="_ _4"> </span>used<span class="_ _9"> </span>for<span class="_ _4"> </span>typesetting<span class="_ _4"> </span>b<span class="_ _0"></span>o<span class="_ _0"></span>oks,</div><div class="t m0 x0 h2 y3b ff1 fs0 fc0 sc0 ls0 ws0">magazines<span class="_ _1"> </span>and<span class="_ _1"> </span>sheet<span class="_ _1"> </span>m<span class="_ _5"></span>usic.</div><div class="t m0 x1 h2 y3c ff1 fs0 fc0 sc0 ls0 ws0">T</div><div class="t m0 x20 h2 y79 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m0 x21 h2 y3c ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _1"> </span>is<span class="_ _1"> </span>a<span class="_ _1"> </span>source<span class="_ _1"> </span>format<span class="_ _8"> </span>for<span class="_ _1"> </span><span class="ff5">authors</span>.<span class="_ _7"> </span>It<span class="_ _1"> </span>contains</div><div class="t m18 x0 h2 y3d ff1 fs0 fc0 sc0 ls0 ws0">structured<span class="_ _1"> </span>con<span class="_ _5"></span>ten<span class="_ _5"></span>ts<span class="_ _1"> </span>including<span class="_ _1"> </span>text,<span class="_ _1"> </span>formulas,<span class="_ _8"> </span>figures</div><div class="t m1 x0 h2 y3e ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _1"> </span>p<span class="_ _0"></span>ossibly<span class="_ _1"> </span>cross<span class="_ _1"> </span>references<span class="_ _1"> </span>b<span class="_ _0"></span>etw<span class="_ _e"></span>een<span class="_ _1"> </span>them.<span class="_ _11"> </span>Users</div><div class="t m1 x0 h2 y3f ff1 fs0 fc0 sc0 ls0 ws0">can<span class="_ _7"> </span>define<span class="_ _7"> </span>their<span class="_ _7"> </span>own<span class="_ _9"> </span>concepts<span class="_ _7"> </span>by<span class="_ _9"> </span>writing<span class="_ _7"> </span>macros.</div><div class="t m1 x0 h2 y40 ff1 fs0 fc0 sc0 ls0 ws0">T<span class="_ _5"></span>ypically<span class="_ _4"> </span>the<span class="_ _4"> </span>lay<span class="_ _e"></span>out<span class="_ _4"> </span>of<span class="_ _4"> </span>the<span class="_ _9"> </span>document<span class="_ _4"> </span>m<span class="_ _e"></span>ust<span class="_ _9"> </span>be<span class="_ _9"> </span>de-</div><div class="t m1e x0 h2 y41 ff1 fs0 fc0 sc0 ls0 ws0">termined<span class="_ _1"> </span>by<span class="_ _8"> </span><span class="ff5">c<span class="_ _e"></span>ompiling<span class="_ _1"> </span><span class="ff1">the<span class="_ _1"> </span>file<span class="_ _1"> </span>with<span class="_ _1"> </span>a<span class="_ _1"> </span>T</span></span></div><div class="t m0 x22 h2 y7a ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1e x23 h2 y41 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _1"> </span>compiler;</div><div class="t m2 x0 h2 y42 ff1 fs0 fc0 sc0 ls0 ws0">differen<span class="_ _e"></span>t compilers<span class="_ _14"> </span>ma<span class="_ _e"></span>y produce<span class="_ _d"> </span>differen<span class="_ _e"></span>t results<span class="_ _14"> </span>from</div><div class="t m0 x0 h2 y43 ff1 fs0 fc0 sc0 ls0 ws0">the<span class="_ _1"> </span>same<span class="_ _1"> </span>T</div><div class="t m0 x24 h2 y7b ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m0 x8 h2 y43 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _1"> </span>source<span class="_ _1"> </span>file.</div><div class="t m2 x1 h2 y44 ff1 fs0 fc0 sc0 ls0 ws0">P<span class="_ _e"></span>eople started<span class="_ _d"> </span>trying to<span class="_ _14"> </span>connect T</div><div class="t m0 x25 h2 y7c ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m2 x26 h2 y44 ff1 fs0 fc0 sc0 ls0 ws0">X to<span class="_ _14"> </span>the W<span class="_ _2"></span>eb</div><div class="t m1e x0 h2 y45 ff1 fs0 fc0 sc0 ls0 ws0">nearly<span class="_ _1"> </span>since<span class="_ _1"> </span>the<span class="_ _1"> </span>W<span class="_ _2"></span>eb<span class="_ _1"> </span>b<span class="_ _0"></span>egan.<span class="_ _7"> </span>There<span class="_ _1"> </span>were<span class="_ _8"> </span>some<span class="_ _1"> </span>early</div><div class="t m2 x0 h2 y46 ff1 fs0 fc0 sc0 ls0 ws0">o<span class="_ _e"></span>verviews, suc<span class="_ _e"></span>h as [</div><div class="t m0 x27 h2 y46 ff1 fs0 fc0 sc0 ls0 ws0">31</div><div class="t m2 x28 h2 y46 ff1 fs0 fc0 sc0 ls0 ws0">,</div><div class="t m0 x29 h2 y46 ff1 fs0 fc0 sc0 ls0 ws0">32</div><div class="t m2 x2a h2 y46 ff1 fs0 fc0 sc0 ls0 ws0">], [</div><div class="t m0 x2b h2 y46 ff1 fs0 fc0 sc0 ls0 ws0">34</div><div class="t m2 x2c h2 y46 ff1 fs0 fc0 sc0 ls0 ws0">, c<span class="_ _e"></span>hapter 7], but w<span class="_ _e"></span>e are</div><div class="t m0 x0 h2 y47 ff1 fs0 fc0 sc0 ls0 ws0">not<span class="_ _1"> </span>a<span class="_ _5"></span>w<span class="_ _e"></span>are<span class="_ _1"> </span>of<span class="_ _4"> </span>an<span class="_ _e"></span>y<span class="_ _1"> </span>recen<span class="_ _e"></span>t<span class="_ _1"> </span>surveys<span class="_ _1"> </span>on<span class="_ _1"> </span>the<span class="_ _1"> </span>topic.<span class="_ _9"> </span>Early</div><div class="t m1f x0 h2 y48 ff1 fs0 fc0 sc0 ls0 ws0">w<span class="_ _5"></span>orks<span class="_ _8"> </span>were<span class="_ _8"> </span>mainly<span class="_ _1"> </span>fo<span class="_ _0"></span>cusing<span class="_ _1"> </span>on<span class="_ _1"> </span>correctly<span class="_ _1"> </span>displa<span class="_ _e"></span>ying</div><div class="t m1 x0 h2 y49 ff1 fs0 fc0 sc0 ls0 ws0">form<span class="_ _5"></span>ulas<span class="_ _4"> </span>pro<span class="_ _0"></span>duced<span class="_ _4"> </span>by<span class="_ _4"> </span>T</div><div class="t m0 x2a h2 y7d ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 x2d h2 y49 ff1 fs0 fc0 sc0 ls0 ws0">X.<span class="_ _a"> </span>Different<span class="_ _4"> </span>metho<span class="_ _0"></span>ds<span class="_ _4"> </span>in-</div><div class="t m1 x0 h2 y4a ff1 fs0 fc0 sc0 ls0 ws0">clude<span class="_ _9"> </span>using<span class="_ _7"> </span>images,<span class="_ _11"> </span>Unico<span class="_ _0"></span>de<span class="_ _7"> </span>c<span class="_ _5"></span>haracters,<span class="_ _7"> </span>Math<span class="ff4 fs1">ML</span></div><div class="t m1 x0 h2 y4c ff1 fs0 fc0 sc0 ls0 ws0">or<span class="_ _1"> </span><span class="ff4 fs1">HTML</span>5.<span class="_ _11"> </span>How<span class="_ _e"></span>ever<span class="_ _1"> </span>the<span class="_ _1"> </span>p<span class="_ _0"></span>ow<span class="_ _e"></span>er<span class="_ _1"> </span>of<span class="_ _4"> </span>T</div><div class="t m0 x2e h2 y7e ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 x2f h2 y4c ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _1"> </span>is<span class="_ _1"> </span>far<span class="_ _4"> </span>more</div><div class="t m1 x0 h2 y7f ff1 fs0 fc0 sc0 ls0 ws0">than<span class="_ _9"> </span>formulas,<span class="_ _9"> </span>it<span class="_ _7"> </span>is<span class="_ _9"> </span>also<span class="_ _9"> </span>famous<span class="_ _7"> </span>for<span class="_ _9"> </span>its<span class="_ _9"> </span>capability</div><div class="t m20 x0 h2 y80 ff1 fs0 fc0 sc0 ls0 ws0">of<span class="_ _1"> </span>handling<span class="_ _1"> </span>mathematical<span class="_ _1"> </span>spacing,<span class="_ _1"> </span>hyphenation<span class="_ _1"> </span>and</div><div class="t m0 x0 h2 y81 ff1 fs0 fc0 sc0 ls0 ws0">justification,<span class="_ _1"> </span>whic<span class="_ _e"></span>h<span class="_ _4"> </span>is<span class="_ _8"> </span>often<span class="_ _1"> </span>ignored<span class="_ _1"> </span>in<span class="_ _1"> </span>these<span class="_ _1"> </span>cases.</div><div class="t m2 x0 h2 y82 ff1 fs0 fc0 sc0 ls0 ws0">In<span class="_ _d"> </span>the<span class="_ _14"> </span>following<span class="_ _14"> </span>sections, we<span class="_ _14"> </span>are<span class="_ _d"> </span>going<span class="_ _d"> </span>to<span class="_ _14"> </span>describ<span class="_ _0"></span>e and</div><div class="t m21 x0 h2 y83 ff1 fs0 fc0 sc0 ls0 ws0">compare<span class="_ _1"> </span>some<span class="_ _1"> </span>p<span class="_ _0"></span>opular<span class="_ _1"> </span>existing<span class="_ _1"> </span>approaches.<span class="_ _7"> </span>W<span class="_ _2"></span>e<span class="_ _1"> </span>will</div><div class="t m2 x0 h2 y84 ff1 fs0 fc0 sc0 ls0 ws0">also<span class="_ _8"> </span>introduce<span class="_ _1"> </span>a<span class="_ _8"> </span>new<span class="_ _1"> </span>program,<span class="_ _8"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX<span class="_ _8"> </span></span>[</div><div class="t m0 x30 h2 y84 ff1 fs0 fc0 sc0 ls0 ws0">25</div><div class="t m2 x31 h2 y84 ff1 fs0 fc0 sc0 ls0 ws0">],<span class="_ _8"> </span>and</div><div class="t m2 x0 h2 y85 ff1 fs0 fc0 sc0 ls0 ws0">discuss its<span class="_ _8"> </span>adv<span class="_ _e"></span>antages and<span class="_ _8"> </span>limitations<span class="_ _8"> </span>with<span class="_ _8"> </span>examples.</div><div class="t m0 x0 h3 y86 ff2 fs0 fc0 sc0 ls0 ws0">2<span class="_ _c"> </span>Preliminaries</div><div class="t m22 xc h2 y87 ff1 fs0 fc0 sc0 ls0 ws0">he<span class="_ _1"> </span>target<span class="_ _8"> </span>audience<span class="_ _1"> </span>of<span class="_ _1"> </span>this<span class="_ _1"> </span>article<span class="_ _1"> </span>includes</div><div class="t m2 xc h2 y88 ff1 fs0 fc0 sc0 ls0 ws0">those<span class="_ _1"> </span>who<span class="_ _1"> </span>need<span class="_ _1"> </span>to<span class="_ _1"> </span>publish<span class="_ _1"> </span>b<span class="_ _0"></span>oth<span class="_ _1"> </span>online<span class="_ _1"> </span>ver-</div><div class="t m2 xc h2 y89 ff1 fs0 fc0 sc0 ls0 ws0">sions and print versions of their do<span class="_ _0"></span>cuments</div><div class="t m2 xc h2 y8a ff1 fs0 fc0 sc0 ls0 ws0">at<span class="_ _14"> </span>the<span class="_ _14"> </span>same<span class="_ _14"> </span>time, especially<span class="_ _d"> </span>those<span class="_ _14"> </span>who<span class="_ _14"> </span>wan<span class="_ _e"></span>t</div><div class="t m0 x0 h2 y8b ff1 fs0 fc0 sc0 ls0 ws0">to<span class="_ _1"> </span>publish<span class="_ _1"> </span>existing<span class="_ _1"> </span>do<span class="_ _0"></span>cumen<span class="_ _5"></span>ts<span class="_ _1"> </span>online.</div><div class="t m2 x1 h2 y8c ff1 fs0 fc0 sc0 ls0 ws0">W<span class="_ _2"></span>e assume<span class="_ _d"> </span>that the existing<span class="_ _14"> </span>do<span class="_ _0"></span>cument is<span class="_ _d"> </span>in <span class="ff4 fs1">PDF</span></div><div class="t m2 x0 h2 y8d ff1 fs0 fc0 sc0 ls0 ws0">format.<span class="_ _9"> </span>It<span class="_ _8"> </span>could<span class="_ _8"> </span>b<span class="_ _0"></span>e<span class="_ _8"> </span>generated from<span class="_ _8"> </span>T</div><div class="t m0 x32 h2 y8e ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m2 x25 h2 y8d ff1 fs0 fc0 sc0 ls0 ws0">X or<span class="_ _8"> </span>any other</div><div class="t m1 x0 h2 y8f ff1 fs0 fc0 sc0 ls0 ws0">to<span class="_ _0"></span>ol.<span class="_ _15"> </span>W<span class="_ _2"></span>e<span class="_ _4"> </span>do<span class="_ _4"> </span>not<span class="_ _9"> </span>assume<span class="_ _4"> </span>that<span class="_ _4"> </span>the<span class="_ _9"> </span>publisher<span class="_ _4"> </span>is<span class="_ _4"> </span>the</div><div class="t m23 x0 h2 y90 ff1 fs0 fc0 sc0 ls0 ws0">author,<span class="_ _8"> </span><span class="ff5">i.e.<span class="_ _1"> </span></span>the<span class="_ _1"> </span>source<span class="_ _1"> </span>files<span class="_ _1"> </span>may<span class="_ _8"> </span>not<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>a<span class="_ _e"></span>v<span class="_ _e"></span>ailable<span class="_ _1"> </span>to</div><div class="t m0 x0 h2 y91 ff1 fs0 fc0 sc0 ls0 ws0">the<span class="_ _1"> </span>publisher.</div><div class="t m11 x1 h2 y92 ff1 fs0 fc0 sc0 ls0 ws0">W<span class="_ _2"></span>e<span class="_ _1"> </span>b<span class="_ _0"></span>eliev<span class="_ _e"></span>e<span class="_ _1"> </span>that<span class="_ _1"> </span>the<span class="_ _1"> </span>following<span class="_ _8"> </span>requirements<span class="_ _8"> </span>are</div><div class="t m2 x0 h2 y93 ff1 fs0 fc0 sc0 ls0 ws0">essen<span class="_ _e"></span>tial for most users.<span class="_ _7"> </span>They are also the criteria w<span class="_ _e"></span>e</div><div class="t m20 x0 h2 y94 ff1 fs0 fc0 sc0 ls0 ws0">will<span class="_ _1"> </span>use<span class="_ _1"> </span>to<span class="_ _1"> </span>discuss<span class="_ _1"> </span>and<span class="_ _1"> </span>compare<span class="_ _1"> </span>existing<span class="_ _4"> </span>approac<span class="_ _e"></span>hes.</div><div class="t m0 x0 h3 y95 ff2 fs0 fc0 sc0 ls0 ws0">Con<span class="_ _e"></span>venience</div><div class="t m1 x33 h2 y95 ff1 fs0 fc0 sc0 ls0 ws0">The<span class="_ _9"> </span>publishing<span class="_ _9"> </span>pro<span class="_ _0"></span>cess<span class="_ _9"> </span>should<span class="_ _9"> </span>b<span class="_ _0"></span>e</div><div class="t m1 x0 h2 y96 ff1 fs0 fc0 sc0 ls0 ws0">automated,<span class="_ _7"> </span>with<span class="_ _9"> </span>minimal<span class="_ _9"> </span>manual<span class="_ _4"> </span>adjustments<span class="_ _4"> </span>in-</div><div class="t m0 x0 h2 y97 ff1 fs0 fc0 sc0 ls0 ws0">v<span class="_ _e"></span>olved,<span class="_ _1"> </span>suc<span class="_ _e"></span>h<span class="_ _1"> </span>that<span class="_ _1"> </span>publishers<span class="_ _1"> </span>need<span class="_ _1"> </span>fo<span class="_ _0"></span>cus<span class="_ _1"> </span>on<span class="_ _1"> </span>only<span class="_ _1"> </span>one</div><div class="t m2 x0 h2 y98 ff1 fs0 fc0 sc0 ls0 ws0">v<span class="_ _e"></span>ersion,<span class="_ _8"> </span>while the other can b<span class="_ _0"></span>e<span class="_ _8"> </span>generated accordingly<span class="_ _2"></span>.</div><div class="t m0 x0 h3 y31 ff2 fs0 fc0 sc0 ls0 ws0">Consistency</div><div class="t m2 x34 h2 y31 ff1 fs0 fc0 sc0 ls0 ws0">Both<span class="_ _d"> </span>the<span class="_ _14"> </span>online v<span class="_ _e"></span>ersion and<span class="_ _14"> </span>the prin<span class="_ _e"></span>t</div><div class="t m14 x0 h2 y32 ff1 fs0 fc0 sc0 ls0 ws0">v<span class="_ _5"></span>ersion<span class="_ _8"> </span>should<span class="_ _1"> </span>hav<span class="_ _e"></span>e<span class="_ _1"> </span>a<span class="_ _1"> </span>consisten<span class="_ _5"></span>t<span class="_ _8"> </span>app<span class="_ _0"></span>earance,<span class="_ _1"> </span>some-</div><div class="t m0 x0 h2 y33 ff1 fs0 fc0 sc0 ls0 ws0">times<span class="_ _1"> </span>including<span class="_ _1"> </span>the<span class="_ _1"> </span>same<span class="_ _1"> </span>la<span class="_ _5"></span>y<span class="_ _5"></span>out<span class="_ _1"> </span>and<span class="_ _1"> </span>format.</div><div class="t m1 x1 h2 y34 ff1 fs0 fc0 sc0 ls0 ws0">Eviden<span class="_ _5"></span>tly<span class="_ _9"> </span>the<span class="_ _7"> </span>conten<span class="_ _e"></span>ts<span class="_ _9"> </span>should<span class="_ _7"> </span>never<span class="_ _9"> </span>v<span class="_ _e"></span>ary<span class="_ _9"> </span>b<span class="_ _0"></span>e-</div><div class="t m1 x0 h2 y35 ff1 fs0 fc0 sc0 ls0 ws0">t<span class="_ _5"></span>w<span class="_ _5"></span>een<span class="_ _11"> </span>the<span class="_ _11"> </span>tw<span class="_ _e"></span>o<span class="_ _11"> </span>versions,<span class="_ _11"> </span>but<span class="_ _f"> </span>one<span class="_ _11"> </span>may<span class="_ _7"> </span>argue<span class="_ _11"> </span>that</div><div class="t m1e x0 h2 y36 ff1 fs0 fc0 sc0 ls0 ws0">screen<span class="_ _1"> </span>and<span class="_ _1"> </span>pap<span class="_ _0"></span>er<span class="_ _1"> </span>are<span class="_ _1"> </span>tw<span class="_ _e"></span>o<span class="_ _1"> </span>completely<span class="_ _1"> </span>different<span class="_ _8"> </span>kinds</div><div class="t m1 x0 h2 y37 ff1 fs0 fc0 sc0 ls0 ws0">of<span class="_ _9"> </span>media,<span class="_ _11"> </span>and<span class="_ _7"> </span>so<span class="_ _7"> </span>fonts,<span class="_ _7"> </span>spacing<span class="_ _7"> </span>and<span class="_ _7"> </span>ev<span class="_ _5"></span>en<span class="_ _9"> </span>lay<span class="_ _e"></span>outs</div><div class="t m2 x0 h2 y38 ff1 fs0 fc0 sc0 ls0 ws0">should b<span class="_ _0"></span>e<span class="_ _8"> </span>optimized<span class="_ _8"> </span>individually<span class="_ _2"></span>.<span class="_ _7"> </span>F<span class="_ _2"></span>or<span class="_ _8"> </span>example,<span class="_ _8"> </span>users</div><div class="c x35 y99 w3 ha"><div class="t m0 x36 hb y9a ffb fs5 fc0 sc0 ls0 ws0">1</div><div class="t m0 x37 hc y9b ffb fs6 fc0 sc0 ls0 ws0">Le<span class="_ _10"> </span>premier<span class="_ _10"> </span>lire<span class="_ _10"> </span>de<span class="_ _10"> </span>Moyſe,</div><div class="t m0 x38 hd y9c ffb fs7 fc0 sc0 ls0 ws0">Di<span class="_ _16"> </span>Geneſe.</div><div class="t m0 x39 hd y9d ffb fs7 fc0 sc0 ls0 ws0">❦</div><div class="t m0 x3a hb y9e ffb fs5 fc0 sc0 ls0 ws0"><span class="_ _10"> </span><span class="_ _10"> </span><span class="_ _10"> </span><span class="_ _10"> </span><span class="_ _10"> </span><span class="_ _17"> </span><span class="_ _17"> </span> .</div><div class="t m0 x3b he y9f ffc fs8 fc0 sc0 ls0 ws0">Ce<span class="_ _18"> </span>premier<span class="_ _18"> </span>lire<span class="_ _18"> </span>comprend<span class="_ _18"> </span>lorigine<span class="_ _18"> </span><span class="_ _18"> </span>caſes<span class="_ _18"> </span>de<span class="_ _18"> </span>totes<span class="_ _18"> </span>choſes,<span class="_ _18"> </span>principalement<span class="_ _18"> </span>la<span class="_ _18"> </span>creation<span class="_ _18"> </span>de<span class="_ _18"> </span>lhomme,<span class="_ _18"> </span>qil<span class="_ _18"> </span>a<span class="_ _18"> </span>eſté<span class="_ _18"> </span>d</div><div class="t m0 x3c he ya0 ffc fs8 fc0 sc0 ls0 ws0">commencement,<span class="_ _18"> </span>ſa<span class="_ _18"> </span>chete<span class="_ _18"> </span><span class="_ _18"> </span>releement<span class="_ _18"> </span>:<span class="_ _16"> </span>comment<span class="_ _0"> </span>dn<span class="_ _18"> </span>tos<span class="_ _18"> </span>ont<span class="_ _18"> </span>eſté<span class="_ _18"> </span>procreés,<span class="_ _16"> </span><span class="_ _0"> </span>por<span class="_ _18"> </span>lers<span class="_ _18"> </span>enormes<span class="_ _18"> </span>pechés<span class="_ _18"> </span>Die</div><div class="t m0 x3c he ya1 ffc fs8 fc0 sc0 ls0 ws0">les<span class="_ _0"> </span>a<span class="_ _18"> </span>conſmés,<span class="_ _18"> </span>par<span class="_ _18"> </span>le<span class="_ _18"> </span>delge,<span class="_ _18"> </span>reſeré<span class="_ _0"> </span>hi,<span class="_ _18"> </span>dont<span class="_ _18"> </span>la<span class="_ _18"> </span>ſemence<span class="_ _18"> </span>a<span class="_ _18"> </span>rempli<span class="_ _0"> </span>tote<span class="_ _18"> </span>la<span class="_ _18"> </span>terre.<span class="_ _18"> </span>Pis<span class="_ _18"> </span>il<span class="_ _18"> </span>deſcrit<span class="_ _18"> </span>les<span class="_ _18"> </span>ies,<span class="_ _18"> </span>fais,<span class="_ _0"> </span>reli-</div><div class="t m0 x3c he ya2 ffc fs8 fc0 sc0 ls0 ws0">gion,<span class="_ _0"> </span><span class="_ _18"> </span>lignees<span class="_ _18"> </span>des<span class="_ _18"> </span>ſaints<span class="_ _0"> </span>Patriarches,<span class="_ _18"> </span>qi<span class="_ _18"> </span>ont<span class="_ _18"> </span>eſc<span class="_ _0"> </span>deant<span class="_ _18"> </span>la<span class="_ _18"> </span>Loy<span class="_ _18"> </span>:<span class="_ _18"> </span>Les<span class="_ _18"> </span>benediions,<span class="_ _0"> </span>promees,<span class="_ _18"> </span><span class="_ _18"> </span>alliances<span class="_ _18"> </span>d<span class="_ _0"> </span>Sei-</div><div class="t m0 x3c he ya3 ffc fs8 fc0 sc0 ls0 ws0">gner<span class="_ _0"> </span>faies<span class="_ _18"> </span>aec<span class="_ _0"> </span>icex<span class="_ _18"> </span>:<span class="_ _18"> </span>Comment<span class="_ _0"> </span>de<span class="_ _18"> </span>le<span class="_ _0"> </span>la<span class="_ _18"> </span>terre<span class="_ _0"> </span>de<span class="_ _18"> </span>Chanaan<span class="_ _0"> </span>ſont<span class="_ _18"> </span>deſcends<span class="_ _0"> </span>en<span class="_ _18"> </span>Epte.<span class="_ _18"> </span>Acns<span class="_ _18"> </span>ont<span class="_ _0"> </span>appelé<span class="_ _18"> </span>ce<span class="_ _0"> </span>lire,<span class="_ _18"> </span>le</div><div class="t m0 x3c he ya4 ffc fs8 fc0 sc0 ls0 ws0">lire<span class="_ _18"> </span>des<span class="_ _18"> </span>Iſtes.<span class="_ _16"> </span>T<span class="_ _e"></span>otefois<span class="_ _18"> </span>ceci<span class="_ _18"> </span>a<span class="_ _18"> </span>obten<span class="_ _18"> </span>entre<span class="_ _18"> </span>nos<span class="_ _18"> </span>predeceers<span class="_ _18"> </span><span class="_ _18"> </span>nos,<span class="_ _18"> </span>qil<span class="_ _18"> </span>eſt<span class="_ _18"> </span>appelé<span class="_ _18"> </span>Geneſe,<span class="_ _18"> </span>qi<span class="_ _18"> </span>eſt<span class="_ _18"> </span>n<span class="_ _18"> </span>mot<span class="_ _18"> </span>Grec,</div><div class="t m0 x3c he ya5 ffc fs8 fc0 sc0 ls0 ws0">gnifiant<span class="_ _0"> </span>generation<span class="_ _18"> </span><span class="_ _18"> </span>origine<span class="_ _18"> </span>:<span class="_ _18"> </span>datant<span class="_ _18"> </span>qen<span class="_ _18"> </span>iceli<span class="_ _18"> </span>eſt<span class="_ _0"> </span>deſcrite<span class="_ _18"> </span>lorigine<span class="_ _18"> </span><span class="_ _18"> </span>procreation<span class="_ _18"> </span>de<span class="_ _18"> </span>totes<span class="_ _0"> </span>choſes<span class="_ _18"> </span>:<span class="_ _16"> </span><span class="_ _0"></span>nom-</div><div class="t m0 x3c he ya6 ffc fs8 fc0 sc0 ls0 ws0">mément<span class="_ _0"> </span>des<span class="_ _18"> </span>Peres<span class="_ _18"> </span>anciens,<span class="_ _18"> </span>qi<span class="_ _0"> </span>ont<span class="_ _18"> </span>eſté<span class="_ _18"> </span>tant<span class="_ _18"> </span>deant<span class="_ _0"> </span>qapres<span class="_ _18"> </span>le<span class="_ _18"> </span>delge,<span class="_ _18"> </span><span class="_ _0"> </span>e<span class="_ _18"> </span>eſgard<span class="_ _18"> </span>à<span class="_ _18"> </span><span class="ffb"><span class="_ _18"> </span><span class="_ _18"> </span><span class="_ _18"> </span><span class="_ _18"> </span><span class="_ _8"> </span><span class="_ _18"> </span><span class="_ _18"> </span><span class="_ _18"> </span><span class="_ _18"> </span><span class="_ _18"> </span> </span>deſcen-</div><div class="t m0 x3c he ya7 ffc fs8 fc0 sc0 ls0 ws0">d<span class="_ _0"> </span>dicex<span class="_ _18"> </span>ſelon<span class="_ _18"> </span>la<span class="_ _18"> </span>chair.</div><div class="t m0 x3d hb ya8 ffb fs5 fc0 sc0 ls0 ws0"><span class="_ _17"> </span> <span class="_ _17"> </span><span class="_ _10"> </span><span class="_ _10"> </span><span class="_ _17"> </span> <span class="_ _11"> </span>.</div><div class="t m0 x3e hf ya9 ffc fs9 fc0 sc0 ls0 ws0">I</div><div class="t m0 x3f he yaa ffc fs8 fc0 sc0 ls0 ws0">Creation<span class="_ _18"> </span>d<span class="_ _18"> </span>ciel<span class="_ _18"> </span><span class="_ _18"> </span>de<span class="_ _18"> </span>la<span class="_ _18"> </span>terre,<span class="_ _18"> </span>II,<span class="_ _18"> </span>10.<span class="_ _16"> </span><span class="_ _18"> </span>de<span class="_ _18"> </span>tot<span class="_ _18"> </span>ce<span class="_ _18"> </span>qi<span class="_ _16"> </span>y<span class="_ _0"> </span>eſt</div><div class="t m0 x40 he yab ffc fs8 fc0 sc0 ls0 ws0">comprins.<span class="_ _16"> </span>3.14. De<span class="_ _0"> </span>la<span class="_ _16"> </span>lmiere<span class="_ _0"> </span>a,<span class="_ _16"> </span>26<span class="_ _18"> </span><span class="_ _18"> </span>de<span class="_ _18"> </span>lhomme,<span class="_ _16"> </span>18</div><div class="t m0 x40 he yac ffc fs8 fc0 sc0 ls0 ws0">qel<span class="_ _0"> </span>tot<span class="_ _18"> </span>eſt<span class="_ _18"> </span>abietti.<span class="_ _16"> </span>2.2.<span class="_ _18"> </span>18<span class="_ _18"> </span>Die<span class="_ _18"> </span>benit<span class="_ _18"> </span>totes<span class="_ _18"> </span>ſes<span class="_ _0"> </span>œ-</div><div class="t m0 x40 he yad ffc fs8 fc0 sc0 ls0 ws0">res,<span class="_ _0"> </span>31<span class="_ _18"> </span>qil<span class="_ _18"> </span>a<span class="_ _18"> </span>accomplies<span class="_ _18"> </span>en<span class="_ _18"> </span>x<span class="_ _0"> </span>iors.</div><div class="t m0 x3a h10 yae ffb fs8 fc0 sc0 ls0 ws0">1</div><div class="t m0 x41 hb yaf ffb fs5 fc0 sc0 ls0 ws0">Ie</div><div class="t m0 x20 h10 yae ffb fs8 fc0 sc0 ls0 ws0">a</div><div class="t m0 x42 hb yaf ffb fs5 fc0 sc0 ls0 ws0">crea</div><div class="t m0 x3a h10 yb0 ffb fs8 fc0 sc0 ls0 ws0">b</div><div class="t m0 x1 hb yb1 ffb fs5 fc0 sc0 ls0 ws0">a<span class="_ _14"> </span>com</div><div class="t m0 x3a hb yb2 ffb fs5 fc0 sc0 ls0 ws0">mence<span class="_ _1"> </span>-</div><div class="t m0 x3a hb yb3 ffb fs5 fc0 sc0 ls0 ws0">ment</div><div class="t m0 x43 h10 yb4 ffb fs8 fc0 sc0 ls0 ws0">c</div><div class="t m0 x44 hb yb3 ffb fs5 fc0 sc0 ls0 ws0">le</div><div class="t m0 x3a hb yb5 ffb fs5 fc0 sc0 ls0 ws0">ciel<span class="_ _10"> </span>&amp;<span class="_ _10"> </span>la</div><div class="t m0 x3a hb yb6 ffb fs5 fc0 sc0 ls0 ws0">terre.</div><div class="t m0 x3a hb yb7 ffb fs5 fc0 sc0 ls0 ws0">2<span class="_ _4"> </span>Or la</div><div class="t m0 x3a hb yb8 ffb fs5 fc0 sc0 ls0 ws0">terre<span class="_ _1"> </span>eſ-</div><div class="t m0 x3a hb yb9 ffb fs5 fc0 sc0 ls0 ws0">toit<span class="_ _d"> </span>ſans</div><div class="t m0 x3a hb yba ffb fs5 fc0 sc0 ls0 ws0">forme,<span class="_ _16"> </span>&amp;</div><div class="t m0 x40 hb ybb ffb fs5 fc0 sc0 ls0 ws0">vide,<span class="_ _17"> </span>&amp;<span class="_ _17"> </span>les<span class="_ _16"> </span>tenebres<span class="_ _17"> </span>eſtoyent<span class="_ _16"> </span>ſr<span class="_ _17"> </span>les</div><div class="t m0 x40 hb ybc ffb fs5 fc0 sc0 ls0 ws0">abyſmes<span class="_ _17"> </span>: &amp;<span class="_ _10"> </span>lEſprit<span class="_ _17"> </span>de<span class="_ _17"> </span>Die</div><div class="t m0 x45 h10 ybd ffb fs8 fc0 sc0 ls0 ws0">d</div><div class="t m0 x38 hb ybc ffb fs5 fc0 sc0 ls0 ws0">eſtoit</div><div class="t m0 x40 hb ybe ffb fs5 fc0 sc0 ls0 ws0">eſpand<span class="_ _16"> </span>par<span class="_ _18"> </span>des<span class="_ _16"> </span>les<span class="_ _18"> </span>eax.</div><div class="t m0 x3e hb ybf ffb fs5 fc0 sc0 ls0 ws0">3<span class="_ _9"> </span>Adonc<span class="_ _16"> </span>Die<span class="_ _16"> </span>dît,</div><div class="t m0 x46 h10 yc0 ffb fs8 fc0 sc0 ls0 ws0">2</div><div class="t m0 x47 hb ybf ffb fs5 fc0 sc0 ls0 ws0">il<span class="_ _16"> </span>y<span class="_ _16"> </span>ait<span class="_ _18"> </span>lmie-</div><div class="t m0 x40 hb yc1 ffb fs5 fc0 sc0 ls0 ws0">re.</div><div class="t m0 x48 h10 yc2 ffb fs8 fc0 sc0 ls0 ws0">e</div><div class="t m0 x49 hb yc1 ffb fs5 fc0 sc0 ls0 ws0">Et<span class="_ _18"> </span>la<span class="_ _16"> </span>lmiere<span class="_ _16"> </span>ft.</div><div class="t m0 x3e hb yc3 ffb fs5 fc0 sc0 ls0 ws0">4<span class="_ _9"> </span>Et<span class="_ _16"> </span>Die<span class="_ _18"> </span>vid<span class="_ _16"> </span>q</div><div class="t m0 x4a hb yc4 ffb fs5 fc0 sc0 ls0 ws0">̃</div><div class="t m0 x0 hb yc3 ffb fs5 fc0 sc0 ls0 ws0">la<span class="_ _16"> </span>lmiere<span class="_ _18"> </span>eſtoit<span class="_ _16"> </span>bon-</div><div class="t m0 x40 hb yc5 ffb fs5 fc0 sc0 ls0 ws0">ne<span class="_ _16"> </span>:<span class="_ _16"> </span>&amp;<span class="_ _18"> </span>ſepara<span class="_ _16"> </span>la<span class="_ _16"> </span>lmiere<span class="_ _18"> </span>des<span class="_ _16"> </span>tenebres.</div><div class="t m0 x3e hb yc6 ffb fs5 fc0 sc0 ls0 ws0">5<span class="_ _9"> </span>Et<span class="_ _18"> </span>Die<span class="_ _16"> </span>appela<span class="_ _18"> </span>la<span class="_ _16"> </span>lmiere<span class="_ _18"> </span>ior,&amp;<span class="_ _16"> </span>les</div><div class="t m0 x40 hb yc7 ffb fs5 fc0 sc0 ls0 ws0">tenebres<span class="_ _16"> </span>ni.<span class="_ _16"> </span>Lors<span class="_ _18"> </span>ft<span class="_ _16"> </span>fai<span class="_ _18"> </span>le</div><div class="t m0 x4b h10 yc8 ffb fs8 fc0 sc0 ls0 ws0">f</div><div class="t m0 x45 hb yc7 ffb fs5 fc0 sc0 ls0 ws0">ſoir<span class="_ _16"> </span>&amp;</div><div class="t m0 x40 hb yc9 ffb fs5 fc0 sc0 ls0 ws0">le<span class="_ _16"> </span>matin<span class="_ _18"> </span>d<span class="_ _16"> </span>premier<span class="_ _18"> </span>ior.</div><div class="t m0 x3e hb yca ffb fs5 fc0 sc0 ls0 ws0">6<span class="_ _9"> </span>¶<span class="_ _16"> </span>Pis<span class="_ _18"> </span>Die<span class="_ _18"> </span>dît,</div><div class="t m0 x4c h10 ycb ffb fs8 fc0 sc0 ls0 ws0">3</div><div class="t m0 x46 hb yca ffb fs5 fc0 sc0 ls0 ws0">il<span class="_ _18"> </span>y<span class="_ _16"> </span>ait<span class="_ _18"> </span>ne</div><div class="t m0 x4d h10 ycb ffb fs8 fc0 sc0 ls0 ws0">g</div><div class="t m0 x43 hb yca ffb fs5 fc0 sc0 ls0 ws0">eſ-</div><div class="t m0 x40 hb ycc ffb fs5 fc0 sc0 ls0 ws0">tende<span class="_ _16"> </span>entre<span class="_ _16"> </span>les<span class="_ _16"> </span>eax,<span class="_ _16"> </span>&amp;<span class="_ _16"> </span>qelle<span class="_ _16"> </span>ſepare</div><div class="t m0 x40 hb ycd ffb fs5 fc0 sc0 ls0 ws0">les</div><div class="t m0 x3c h10 yce ffb fs8 fc0 sc0 ls0 ws0">h</div><div class="t m0 x49 hb ycd ffb fs5 fc0 sc0 ls0 ws0">eax<span class="_ _16"> </span>daec<span class="_ _18"> </span>les<span class="_ _16"> </span>eax.</div><div class="t m0 x3e hb ycf ffb fs5 fc0 sc0 ls0 ws0">7<span class="_ _9"> </span>Die<span class="_ _17"> </span>donc<span class="_ _17"> </span>fit<span class="_ _10"> </span>leſtende,<span class="_ _10"> </span>&amp;<span class="_ _17"> </span>diiſa</div><div class="t m0 x4e h11 yd0 ffb fsa fc0 sc0 ls0 ws0">I</div><div class="t m0 x4f h12 yd1 ffb fs9 fc0 sc0 ls0 ws0">Ce premier<span class="_ _18"> </span>cha-</div><div class="t m0 x50 h12 yd2 ffb fs9 fc0 sc0 ls0 ws0">pitre<span class="_ _18"> </span>eſt fort<span class="_ _18"> </span>diffi-</div><div class="t m0 x50 h12 yd3 ffb fs9 fc0 sc0 ls0 ws0">cile<span class="_ _18"> </span>: &amp;<span class="_ _0"> </span>por<span class="_ _18"> </span>cette</div><div class="t m0 x50 h12 yd4 ffb fs9 fc0 sc0 ls0 ws0">caſe, il<span class="_ _18"> </span>eſtoit de-</div><div class="t m0 x50 h12 yd5 ffb fs9 fc0 sc0 ls0 ws0">fend<span class="_ _18"> </span>entre<span class="_ _18"> </span>les<span class="_ _18"> </span>He</div><div class="t m0 x50 h12 yd6 ffb fs9 fc0 sc0 ls0 ws0">briex<span class="_ _18"> </span>de<span class="_ _18"> </span>le<span class="_ _18"> </span>lire &amp;</div><div class="t m0 x50 h12 yd7 ffb fs9 fc0 sc0 ls0 ws0">interpreter deant</div><div class="t m0 x50 h12 yd8 ffb fs9 fc0 sc0 ls0 ws0">laage<span class="_ _14"> </span>de<span class="_ _14"> </span>trente</div><div class="t m0 x50 h12 yd9 ffb fs9 fc0 sc0 ls0 ws0">ans.</div><div class="t m0 x4e h11 yda ffb fsa fc0 sc0 ls0 ws0">a</div><div class="t m0 x4f h12 ydb ffb fs9 fc0 sc0 ls0 ws0">Fit de rien,<span class="_ _17"> </span>&amp;</div><div class="t m0 x50 h12 ydc ffb fs9 fc0 sc0 ls0 ws0">ſans<span class="_ _17"> </span>acne<span class="_ _17"> </span>ma-</div><div class="t m0 x50 h12 ydd ffb fs9 fc0 sc0 ls0 ws0">tiere.</div><div class="t m0 x4e h11 yde ffb fsa fc0 sc0 ls0 ws0">1</div><div class="t m0 x4f hf ydf ffc fs9 fc0 sc0 ls0 ws0">Iob <span class="ffb">38.4, </span>Pſea.</div><div class="t m0 x50 hf ye0 ffb fs9 fc0 sc0 ls0 ws0">33.6,<span class="_ _d"> </span><span class="ffc"><span class="_ _14"> </span></span>89.12.,</div><div class="t m0 x50 hf ye1 ffb fs9 fc0 sc0 ls0 ws0">135.5,<span class="_ _d"> </span><span class="ffc">Eccleſtiaſti.</span></div><div class="t m0 x50 hf ye2 ffb fs9 fc0 sc0 ls0 ws0">13.1,<span class="_ _17"> </span><span class="ffc">A.<span class="_ _8"> </span></span>14-15,</div><div class="t m0 x50 hf ye3 ffc fs9 fc0 sc0 ls0 ws0"><span class="_ _0"> </span><span class="ffb">17.14</span></div><div class="t m0 x4e h11 ye4 ffb fsa fc0 sc0 ls0 ws0">b</div><div class="t m0 x51 h12 ye5 ffb fs9 fc0 sc0 ls0 ws0">T<span class="_ _e"></span>ot<span class="_ _17"> </span>premiere-</div><div class="t m0 x50 h12 ye6 ffb fs9 fc0 sc0 ls0 ws0">ment,<span class="_ _0"> </span>&amp;<span class="_ _18"> </span>aãt<span class="_ _18"> </span>qil</div><div class="t m0 x50 h12 ye7 ffb fs9 fc0 sc0 ls0 ws0">y<span class="_ _18"> </span>et acne<span class="_ _0"> </span>crea-</div><div class="t m0 x50 hf ye8 ffb fs9 fc0 sc0 ls0 ws0">tre,<span class="_ _0"> </span><span class="ffc">Iean<span class="_ _18"> </span></span>1.10.</div><div class="t m0 x50 h11 ye9 ffb fsa fc0 sc0 ls0 ws0">2</div><div class="t m0 x4e hf yea ffc fs9 fc0 sc0 ls0 ws0">Hebr.<span class="_ _0"> </span><span class="ffb">11.3.</span></div><div class="t m0 x4f h11 yeb ffb fsa fc0 sc0 ls0 ws0">c</div><div class="t m0 x51 h12 yec ffb fs9 fc0 sc0 ls0 ws0">Le<span class="_ _17"> </span>ciel<span class="_ _10"> </span>&amp;<span class="_ _10"> </span>la</div><div class="t m0 x50 h12 yed ffb fs9 fc0 sc0 ls0 ws0">terre, les<span class="_ _18"> </span>eax, les</div><div class="t m0 x50 h12 yee ffb fs9 fc0 sc0 ls0 ws0">abyſmes, ſe<span class="_ _17"> </span>pren-</div><div class="t m0 x50 h12 yef ffb fs9 fc0 sc0 ls0 ws0">nent ici<span class="_ _18"> </span>por vne</div><div class="t m0 x50 h12 yf0 ffb fs9 fc0 sc0 ls0 ws0">meſme<span class="_ _18"> </span>choſe<span class="_ _18"> </span>: aſç.</div><div class="t m0 x50 h12 yf1 ffb fs9 fc0 sc0 ls0 ws0">por ne matiere</div><div class="t m0 x50 h12 yf2 ffb fs9 fc0 sc0 ls0 ws0">cõfſe<span class="_ _18"> </span>&amp; ſans<span class="_ _18"> </span>for-</div><div class="t m0 x50 h12 yf3 ffb fs9 fc0 sc0 ls0 ws0">me,<span class="_ _18"> </span>q</div><div class="t m0 x52 h12 yf4 ffb fs9 fc0 sc0 ls0 ws0">̃</div><div class="t m0 x53 h12 yf3 ffb fs9 fc0 sc0 ls0 ws0">Die<span class="_ _18"> </span>forma</div><div class="t m0 x50 h12 yf5 ffb fs9 fc0 sc0 ls0 ws0">&amp;<span class="_ _14"> </span>agença<span class="_ _10"> </span>apres</div><div class="t m0 x50 h12 yf6 ffb fs9 fc0 sc0 ls0 ws0">par<span class="_ _0"> </span>ſa<span class="_ _18"> </span>Parole.</div><div class="t m0 x4f h11 yf7 ffb fsa fc0 sc0 ls0 ws0">d</div><div class="t m0 x51 h12 yf8 ffb fs9 fc0 sc0 ls0 ws0">O,<span class="_ _10"> </span>ſe<span class="_ _10"> </span>mo-</div><div class="t m0 x50 h12 yf9 ffb fs9 fc0 sc0 ls0 ws0">voit.<span class="_ _17"> </span>Ceſt,<span class="_ _18"> </span>ſoſte-</div><div class="t m0 x50 h12 yfa ffb fs9 fc0 sc0 ls0 ws0">noit et conſeroit</div><div class="t m0 x50 h12 yfb ffb fs9 fc0 sc0 ls0 ws0">en ſon eſtre cette</div><div class="t m0 x50 h12 yfc ffb fs9 fc0 sc0 ls0 ws0">matiere<span class="_ _0"> </span>confſe.</div><div class="t m0 x50 h12 yfd ffb fs9 fc0 sc0 ls0 ws0">Car il<span class="_ _18"> </span>eſt impo-</div><div class="t m0 x50 h12 yfe ffb fs9 fc0 sc0 ls0 ws0">ble,<span class="_ _18"> </span>q</div><div class="t m0 x52 h12 yff ffb fs9 fc0 sc0 ls0 ws0">̃</div><div class="t m0 x53 h12 yfe ffb fs9 fc0 sc0 ls0 ws0">acne<span class="_ _18"> </span>cho-</div><div class="t m0 x50 h12 y100 ffb fs9 fc0 sc0 ls0 ws0">ſe apres<span class="_ _18"> </span>aoir eſté</div><div class="t m0 x50 h12 y101 ffb fs9 fc0 sc0 ls0 ws0">faies,pie<span class="_ _18"> </span>ſb-</div><div class="t m0 x50 h12 y102 ffb fs9 fc0 sc0 ls0 ws0">ſter<span class="_ _17"> </span>n ſel<span class="_ _17"> </span>mo-</div><div class="t m0 x50 h12 y103 ffb fs9 fc0 sc0 ls0 ws0">ment,<span class="_ _0"> </span><span class="_ _18"> </span>Die<span class="_ _18"> </span>ne<span class="_ _18"> </span>la</div><div class="t m0 x50 h12 y104 ffb fs9 fc0 sc0 ls0 ws0">ſoſtient &amp; cõſer-</div><div class="t m0 x50 h12 y105 ffb fs9 fc0 sc0 ls0 ws0">ve<span class="_ _17"> </span>par<span class="_ _17"> </span>ſa<span class="_ _10"> </span>vert,</div><div class="t m0 x50 hf y106 ffc fs9 fc0 sc0 ls0 ws0">Pſea.<span class="_ _0"> </span><span class="ffb">130.</span></div><div class="t m0 x4f h11 y107 ffb fsa fc0 sc0 ls0 ws0">e</div><div class="t m0 x51 h12 y108 ffb fs9 fc0 sc0 ls0 ws0">Cette<span class="_ _10"> </span>lmiere</div><div class="t m0 x50 h12 y109 ffb fs9 fc0 sc0 ls0 ws0">neſtoit<span class="_ _17"> </span>point en-</div><div class="t m0 x50 h12 y10a ffb fs9 fc0 sc0 ls0 ws0">core a ſoleil, car</div><div class="t m0 x50 h12 y10b ffb fs9 fc0 sc0 ls0 ws0">il naoit pas eſté</div><div class="t m0 x50 h12 y10c ffb fs9 fc0 sc0 ls0 ws0">creé,<span class="_ _18"> </span>mais<span class="_ _0"> </span>eſtoit<span class="_ _18"> </span>en</div><div class="t m0 x50 h12 y10d ffb fs9 fc0 sc0 ls0 ws0">la main de Die,</div><div class="t m0 x50 h12 y10e ffb fs9 fc0 sc0 ls0 ws0">ayãt<span class="_ _18"> </span>ſon<span class="_ _18"> </span>ordre<span class="_ _18"> </span>ſc-</div><div class="t m0 x50 h12 y10f ffb fs9 fc0 sc0 ls0 ws0">cef<span class="_ _18"> </span>aec<span class="_ _0"> </span>les<span class="_ _18"> </span>tene-</div><div class="t m0 x50 h12 y110 ffb fs9 fc0 sc0 ls0 ws0">bres, por<span class="_ _18"> </span>faire le</div><div class="t m0 x50 h12 y111 ffb fs9 fc0 sc0 ls0 ws0">ior<span class="_ _18"> </span>&amp; la<span class="_ _18"> </span>ni<span class="_ _18"> </span>&amp;</div><div class="t m0 x50 h12 y112 ffb fs9 fc0 sc0 ls0 ws0">ce<span class="_ _18"> </span>iſqes<span class="_ _18"> </span>a qa-</div><div class="t m0 x50 h12 y113 ffb fs9 fc0 sc0 ls0 ws0">trieme<span class="_ _17"> </span>ior,<span class="_ _17"> </span>qe</div><div class="t m0 x50 h12 y114 ffb fs9 fc0 sc0 ls0 ws0">Die<span class="_ _17"> </span>fit le<span class="_ _17"> </span>ſoleil</div><div class="t m0 x50 h12 y115 ffb fs9 fc0 sc0 ls0 ws0">por<span class="_ _0"> </span>eſtre<span class="_ _18"> </span>miniſtre</div><div class="t m0 x50 h12 y116 ffb fs9 fc0 sc0 ls0 ws0">&amp; diſpenſater<span class="_ _18"> </span>de</div><div class="t m0 x50 h12 y117 ffb fs9 fc0 sc0 ls0 ws0">cette<span class="_ _18"> </span>lmiere,<span class="_ _18"> </span>aec</div><div class="t m0 x50 h12 y118 ffb fs9 fc0 sc0 ls0 ws0">la<span class="_ _0"> </span>lne<span class="_ _18"> </span>&amp;<span class="_ _0"> </span>eſtoilles.</div><div class="t m0 x4e h11 y119 ffb fsa fc0 sc0 ls0 ws0">3</div><div class="t m0 x4f hf y11a ffc fs9 fc0 sc0 ls0 ws0">Pſea. <span class="ffb">33.6,<span class="_ _17"> </span></span></div><div class="t m0 x50 h12 y11b ffb fs9 fc0 sc0 ls0 ws0">136.5.</div><div class="t m0 x50 hf y11c ffc fs9 fc0 sc0 ls0 ws0">Ierem.<span class="_ _14"> </span><span class="ffb">10.11<span class="_ _14"> </span></span></div><div class="t m0 x50 h12 y11d ffb fs9 fc0 sc0 ls0 ws0">51.15.</div><div class="t m0 x50 h11 y11e ffb fsa fc0 sc0 ls0 ws0">f</div><div class="t m0 x4e h12 y11f ffb fs9 fc0 sc0 ls0 ws0">Ici<span class="_ _0"> </span>eſt<span class="_ _18"> </span>la<span class="_ _0"> </span>caſe</div><div class="t m0 x4 hb ya8 ffb fs5 fc0 sc0 ls0 ws0">les<span class="_ _17"> </span>eax,<span class="_ _17"> </span>qi<span class="_ _16"> </span>eſtoyent<span class="_ _17"> </span>ſos<span class="_ _16"> </span>leſtende,</div><div class="t m0 x4 hb y120 ffb fs5 fc0 sc0 ls0 ws0">daec<span class="_ _17"> </span>celles, qi<span class="_ _17"> </span>eſtoyent<span class="_ _17"> </span>ſr<span class="_ _10"> </span>leſten-</div><div class="t m0 x4 hb y121 ffb fs5 fc0 sc0 ls0 ws0">de.<span class="_ _16"> </span>Et<span class="_ _16"> </span>ft<span class="_ _18"> </span>ain<span class="_ _16"> </span>fai.</div><div class="t m0 x54 hb y122 ffb fs5 fc0 sc0 ls0 ws0">8<span class="_ _9"> </span>Et<span class="_ _18"> </span>Die<span class="_ _18"> </span>appela<span class="_ _18"> </span>leſtende,<span class="_ _18"> </span>Ciel.<span class="_ _16"> </span>Lors</div><div class="t m0 x4 hb y123 ffb fs5 fc0 sc0 ls0 ws0">ft<span class="_ _16"> </span>fai<span class="_ _17"> </span>le<span class="_ _16"> </span>ſoir<span class="_ _17"> </span>&amp;<span class="_ _16"> </span>le<span class="_ _17"> </span>matin<span class="_ _16"> </span>d<span class="_ _17"> </span>ſecond</div><div class="t m0 x4 hb y124 ffb fs5 fc0 sc0 ls0 ws0">ior.</div><div class="t m0 x54 hb y125 ffb fs5 fc0 sc0 ls0 ws0">9<span class="_ _9"> </span>¶<span class="_ _18"> </span>Pis<span class="_ _16"> </span>Die<span class="_ _18"> </span>dît,</div><div class="t m0 x55 h10 y126 ffb fs8 fc0 sc0 ls0 ws0">4<span class="_ _16"> </span>i</div><div class="t m0 x33 hb y125 ffb fs5 fc0 sc0 ls0 ws0">e<span class="_ _18"> </span>les<span class="_ _16"> </span>eax,<span class="_ _18"></span>qi</div><div class="t m0 x4 hb y127 ffb fs5 fc0 sc0 ls0 ws0">ſont<span class="_ _16"> </span>ſos<span class="_ _17"> </span>le<span class="_ _16"> </span>ciel,<span class="_ _17"> </span>ſoyent<span class="_ _17"> </span>aemblees<span class="_ _16"> </span>en</div><div class="t m0 x4 hb y128 ffb fs5 fc0 sc0 ls0 ws0">n<span class="_ _16"> </span>lie,<span class="_ _16"> </span>&amp;<span class="_ _18"> </span>qe<span class="_ _16"> </span>le<span class="_ _16"> </span>ſec<span class="_ _16"> </span>apparoie.<span class="_ _16"> </span>Et<span class="_ _16"> </span>ft</div><div class="t m0 x4 hb y129 ffb fs5 fc0 sc0 ls0 ws0">ain<span class="_ _16"> </span>fai.</div><div class="t m0 x54 hb y12a ffb fs5 fc0 sc0 ls0 ws0">10<span class="_ _9"> </span>Et<span class="_ _18"> </span>Die<span class="_ _18"> </span>appeꝉale<span class="_ _18"> </span>ſec,T<span class="_ _e"></span>erre,&amp;<span class="_ _18"> </span>laem</div><div class="t m0 x4 hb y12b ffb fs5 fc0 sc0 ls0 ws0">blee<span class="_ _16"> </span>des<span class="_ _17"> </span>eax,<span class="_ _16"> </span>mers. Et<span class="_ _17"> </span>Die<span class="_ _16"> </span>vid<span class="_ _16"> </span>qe</div><div class="t m0 x4 hb y12c ffb fs5 fc0 sc0 ls0 ws0">celà<span class="_ _16"> </span>eſtoit<span class="_ _18"> </span>bon.</div><div class="t m0 x54 hb y12d ffb fs5 fc0 sc0 ls0 ws0">11<span class="_ _9"> </span>Et<span class="_ _16"> </span>Die<span class="_ _17"> </span>dît,<span class="_ _16"> </span>e<span class="_ _17"> </span>la<span class="_ _16"> </span>terre<span class="_ _17"> </span>prodiſe</div><div class="t m0 x4 hb y12e ffb fs5 fc0 sc0 ls0 ws0">verdre,<span class="_ _16"> </span>herbe<span class="_ _18"> </span>prodiſant<span class="_ _16"> </span>ſemence,<span class="_ _16"> </span>&amp;</div><div class="t m0 x4 hb y12f ffb fs5 fc0 sc0 ls0 ws0">arbre<span class="_ _16"> </span>friier,<span class="_ _16"> </span>faiſant<span class="_ _17"> </span>fri<span class="_ _16"> </span>ſelon<span class="_ _16"> </span>ſon</div><div class="t m0 x4 hb y130 ffb fs5 fc0 sc0 ls0 ws0">eſpece,<span class="_ _16"> </span>leqel<span class="_ _18"> </span>ait<span class="_ _16"> </span>ſa<span class="_ _16"> </span>ſemẽce<span class="_ _18"> </span>en<span class="_ _16"> </span>ſoy-meſ-</div><div class="t m0 x4 hb y131 ffb fs5 fc0 sc0 ls0 ws0">me<span class="_ _16"> </span>ſr<span class="_ _18"> </span>la<span class="_ _16"> </span>terre.<span class="_ _16"> </span>Et<span class="_ _16"> </span>ft<span class="_ _18"> </span>ain<span class="_ _16"> </span>fai.</div><div class="t m0 x54 hb y132 ffb fs5 fc0 sc0 ls0 ws0">12<span class="_ _9"> </span>La<span class="_ _18"> </span>terre<span class="_ _16"> </span>dõc<span class="_ _18"> </span>prodit<span class="_ _18"> </span>verdre,<span class="_ _16"> </span>her-</div><div class="t m0 x4 hb y133 ffb fs5 fc0 sc0 ls0 ws0">be<span class="_ _16"> </span>prodiſant<span class="_ _18"> </span>ſemẽce<span class="_ _16"> </span>ſelon<span class="_ _18"> </span>ſon<span class="_ _16"> </span>eſpece,</div><div class="t m0 x4 hb y134 ffb fs5 fc0 sc0 ls0 ws0">&amp; arbre<span class="_ _10"> </span>ſans fri, leqel<span class="_ _10"> </span>aoit ſa</div><div class="t m0 x4 hb y135 ffb fs5 fc0 sc0 ls0 ws0">ſemence<span class="_ _17"> </span>en<span class="_ _16"> </span>ſoymeſme<span class="_ _17"> </span>ſelon<span class="_ _16"> </span>ſon<span class="_ _17"> </span>eſpe-</div><div class="t m0 x4 hb y136 ffb fs5 fc0 sc0 ls0 ws0">ce.<span class="_ _16"> </span>Et<span class="_ _16"> </span>Die<span class="_ _18"> </span>vid<span class="_ _16"> </span>qe<span class="_ _16"> </span>celà<span class="_ _18"> </span>eſtoit<span class="_ _16"> </span>bon.</div><div class="t m0 x54 hb y137 ffb fs5 fc0 sc0 ls0 ws0">13<span class="_ _9"> </span>Lors<span class="_ _16"> </span>ft<span class="_ _16"> </span>fai<span class="_ _16"> </span>le<span class="_ _16"> </span>ſoir<span class="_ _16"> </span>&amp;<span class="_ _16"> </span>le<span class="_ _16"> </span>matin<span class="_ _16"> </span>d</div><div class="t m0 x4 hb y138 ffb fs5 fc0 sc0 ls0 ws0">troieme<span class="_ _16"> </span>ior.</div><div class="t m0 x54 hb y139 ffb fs5 fc0 sc0 ls0 ws0">14<span class="_ _9"> </span>¶<span class="_ _18"> </span>Apres<span class="_ _18"> </span>Die<span class="_ _18"> </span>dît,</div><div class="t m0 x33 h10 y13a ffb fs8 fc0 sc0 ls0 ws0">5<span class="_ _16"> </span>k</div><div class="t m0 x56 hb y139 ffb fs5 fc0 sc0 ls0 ws0">il<span class="_ _18"> </span>y<span class="_ _18"> </span>ait<span class="_ _18"> </span>lmi</div><div class="t m0 x4 hb y13b ffb fs5 fc0 sc0 ls0 ws0">naires<span class="_ _16"> </span>en<span class="_ _16"> </span>leſtende<span class="_ _16"> </span>d<span class="_ _16"> </span>ciel,<span class="_ _16"> </span>por<span class="_ _16"> </span>ſepa-</div><div class="t m0 x4 hb y13c ffb fs5 fc0 sc0 ls0 ws0">rer<span class="_ _18"> </span>la<span class="_ _16"> </span>ni<span class="_ _0"></span>d<span class="_ _16"> </span>ior<span class="_ _18"> </span>:<span class="_ _16"> </span>&amp;<span class="_ _18"> </span>ſoyẽt<span class="_ _16"> </span>en</div><div class="t m0 x57 h10 y13d ffb fs8 fc0 sc0 ls0 ws0">l</div><div class="t m0 x58 hb y13c ffb fs5 fc0 sc0 ls0 ws0">gnes,</div><div class="t m0 x58 hb y13e ffb fs5 fc0 sc0 ls0 ws0">a<span class="_ _9"> </span>en</div><div class="t m0 x59 h12 y13f ffb fs9 fc0 sc0 ls0 ws0">porqoy les He-</div><div class="t m0 x59 h12 y140 ffb fs9 fc0 sc0 ls0 ws0">briex cõmencent</div><div class="t m0 x59 h12 y141 ffb fs9 fc0 sc0 ls0 ws0">le ior natrel le</div><div class="t m0 x59 h12 y142 ffb fs9 fc0 sc0 ls0 ws0">ſoir apres le<span class="_ _18"> </span>ſoleil</div><div class="t m0 x59 h12 y143 ffb fs9 fc0 sc0 ls0 ws0">cochant.</div><div class="t m0 x5a h11 y144 ffb fsa fc0 sc0 ls0 ws0">g</div><div class="t m0 x2a h12 y145 ffb fs9 fc0 sc0 ls0 ws0">Ce mot<span class="_ _17"> </span>dEſtẽ</div><div class="t m0 x59 h12 y146 ffb fs9 fc0 sc0 ls0 ws0">de,<span class="_ _0"> </span>comprẽd<span class="_ _18"> </span>tot</div><div class="t m0 x59 h12 y147 ffb fs9 fc0 sc0 ls0 ws0">ce qi<span class="_ _18"> </span>ſe voit par</div><div class="t m0 x59 h12 y148 ffb fs9 fc0 sc0 ls0 ws0">des<span class="_ _18"> </span>nos,<span class="_ _18"> </span>tãt<span class="_ _18"> </span>en</div><div class="t m0 x59 h12 y149 ffb fs9 fc0 sc0 ls0 ws0">la<span class="_ _17"> </span>region<span class="_ _17"> </span>celeſte,</div><div class="t m0 x59 h12 y14a ffb fs9 fc0 sc0 ls0 ws0">qelementaire.</div><div class="t m0 x59 h11 y14b ffb fsa fc0 sc0 ls0 ws0">4</div><div class="t m0 x5a hf y14c ffc fs9 fc0 sc0 ls0 ws0">Pſea.<span class="_ _0"> </span><span class="ffb">33.7.</span></div><div class="t m0 x5a h11 y14d ffb fsa fc0 sc0 ls0 ws0">h</div><div class="t m0 x2a h12 y14e ffb fs9 fc0 sc0 ls0 ws0">Il eſt<span class="_ _17"> </span>ici parlé</div><div class="t m0 x59 h12 y14f ffb fs9 fc0 sc0 ls0 ws0">de dex manieres</div><div class="t m0 x59 h12 y150 ffb fs9 fc0 sc0 ls0 ws0">deax :<span class="_ _10"> </span>asçaoir,</div><div class="t m0 x59 h12 y151 ffb fs9 fc0 sc0 ls0 ws0">celles q ſont ſos</div><div class="t m0 x59 h12 y152 ffb fs9 fc0 sc0 ls0 ws0">leſtende, comme</div><div class="t m0 x59 h12 y153 ffb fs9 fc0 sc0 ls0 ws0">la<span class="_ _18"> </span>mer,<span class="_ _18"> </span>les flees,</div><div class="t m0 x59 h12 y154 ffb fs9 fc0 sc0 ls0 ws0">&amp; atres<span class="_ _18"> </span>qi ſont</div><div class="t m0 x59 h12 y155 ffb fs9 fc0 sc0 ls0 ws0">ſr la<span class="_ _18"> </span>terre &amp;<span class="_ _18"> </span>cel-</div><div class="t m0 x59 h12 y156 ffb fs9 fc0 sc0 ls0 ws0">les,<span class="_ _17"> </span>qi<span class="_ _17"> </span>ſont ſr</div><div class="t m0 x59 h12 y157 ffb fs9 fc0 sc0 ls0 ws0">leſtende, comme</div><div class="t m0 x59 h12 y158 ffb fs9 fc0 sc0 ls0 ws0">ſont<span class="_ _18"> </span>les<span class="_ _18"> </span>nees<span class="_ _18"> </span>plei-</div><div class="t m0 x59 h12 y159 ffb fs9 fc0 sc0 ls0 ws0">nes dea ça hat</div><div class="t m0 x59 h12 y15a ffb fs9 fc0 sc0 ls0 ws0">en lair par des</div><div class="t m0 x59 h12 y15b ffb fs9 fc0 sc0 ls0 ws0">nos.<span class="_ _17"> </span>Die<span class="_ _18"> </span>a mis</div><div class="t m0 x59 h12 y15c ffb fs9 fc0 sc0 ls0 ws0">entre<span class="_ _18"> </span>ces dex<span class="_ _18"> </span>for</div><div class="t m0 x59 h12 y15d ffb fs9 fc0 sc0 ls0 ws0">ces deax<span class="_ _18"> </span>ne grã</div><div class="t m0 x59 h12 y15e ffb fs9 fc0 sc0 ls0 ws0">de<span class="_ _18"> </span>eſtende,<span class="_ _18"> </span>qon</div><div class="t m0 x59 h12 y15f ffb fs9 fc0 sc0 ls0 ws0">appelle<span class="_ _18"> </span>le<span class="_ _18"> </span>ciel : de</div><div class="t m0 x59 h12 y160 ffb fs9 fc0 sc0 ls0 ws0">là<span class="_ _17"> </span>nos appelons</div><div class="t m0 x59 h12 y161 ffb fs9 fc0 sc0 ls0 ws0">les<span class="_ _0"> </span>oiſeax<span class="_ _18"> </span>d<span class="_ _0"> </span>ciel.</div><div class="t m0 x5b h11 y162 ffb fsa fc0 sc0 ls0 ws0">i</div><div class="t m0 x5a h12 y163 ffb fs9 fc0 sc0 ls0 ws0">Ceci<span class="_ _18"> </span>appartiẽt<span class="_ _18"> </span>a</div><div class="t m0 x59 h12 y164 ffb fs9 fc0 sc0 ls0 ws0">ſecõd<span class="_ _18"> </span>ior, aqel</div><div class="t m0 x59 h12 y165 ffb fs9 fc0 sc0 ls0 ws0">Die<span class="_ _18"> </span>ſepara, &amp;<span class="_ _18"> </span>fit</div><div class="t m0 x59 h12 y166 ffb fs9 fc0 sc0 ls0 ws0">apparoir<span class="_ _0"> </span>la<span class="_ _0"> </span>terre<span class="_ _0"> </span>d</div><div class="t m0 x59 h12 y167 ffb fs9 fc0 sc0 ls0 ws0">milie<span class="_ _0"> </span>des<span class="_ _18"> </span>eax.</div><div class="t m0 x5a h11 y168 ffb fsa fc0 sc0 ls0 ws0">k</div><div class="t m0 x2a h12 y169 ffb fs9 fc0 sc0 ls0 ws0">Il<span class="_ _17"> </span>inſtite<span class="_ _10"> </span>n</div><div class="t m0 x59 h12 y16a ffb fs9 fc0 sc0 ls0 ws0">noel<span class="_ _17"> </span>ordre<span class="_ _17"> </span>en</div><div class="t m0 x59 h12 y16b ffb fs9 fc0 sc0 ls0 ws0">natre,<span class="_ _17"> </span>qand<span class="_ _17"> </span>il</div><div class="t m0 x59 h12 y16c ffb fs9 fc0 sc0 ls0 ws0">fat<span class="_ _18"> </span>&amp;<span class="_ _18"> </span>ordonne le</div><div class="t m0 x59 h12 y16d ffb fs9 fc0 sc0 ls0 ws0">ſoleil<span class="_ _17"> </span>diſtribter</div><div class="t m0 x59 h12 y16e ffb fs9 fc0 sc0 ls0 ws0">de<span class="_ _17"> </span>cette<span class="_ _10"> </span>lmiere</div><div class="t m0 x59 h12 y16f ffb fs9 fc0 sc0 ls0 ws0">qil<span class="_ _17"> </span>aoit<span class="_ _10"> </span>creée</div><div class="t m0 x59 h12 y170 ffb fs9 fc0 sc0 ls0 ws0">aant<span class="_ _18"> </span>li,<span class="_ _18"> </span>&amp;<span class="_ _18"> </span>aant</div><div class="t m0 x59 h12 y171 ffb fs9 fc0 sc0 ls0 ws0">la lne &amp;<span class="_ _17"> </span>les eſ-</div><div class="t m0 x59 h12 y172 ffb fs9 fc0 sc0 ls0 ws0">toilles.</div><div class="t m0 x59 h11 y173 ffb fsa fc0 sc0 ls0 ws0">5</div><div class="t m0 x5a hf y174 ffc fs9 fc0 sc0 ls0 ws0">Pſea.<span class="_ _0"> </span><span class="ffb">136.7</span></div><div class="t m0 x5a h11 y175 ffb fsa fc0 sc0 ls0 ws0">l</div><div class="t m0 x2a h12 y176 ffb fs9 fc0 sc0 ls0 ws0">Ceſt<span class="_ _10"> </span>por<span class="_ _10"> </span>-</div><div class="t m0 x59 h12 y177 ffb fs9 fc0 sc0 ls0 ws0">gnifier<span class="_ _18"> </span>dierſes di-</div><div class="t m0 x59 h12 y178 ffb fs9 fc0 sc0 ls0 ws0">ſpotions qe les</div><div class="t m0 x59 h12 y179 ffb fs9 fc0 sc0 ls0 ws0">corps ĩferiers ſe-</div><div class="t m0 x59 h12 y17a ffb fs9 fc0 sc0 ls0 ws0">lon lordre de na-</div><div class="t m0 x59 h12 y17b ffb fs9 fc0 sc0 ls0 ws0">tre<span class="_ _18"> </span>ont des<span class="_ _0"> </span>corps</div><div class="t m0 x59 h12 y17c ffb fs9 fc0 sc0 ls0 ws0">celeſtes, cõme ca</div><div class="t m0 x59 h12 y17d ffb fs9 fc0 sc0 ls0 ws0">ſes ſecõdes ordon</div><div class="t m0 x59 h12 y17e ffb fs9 fc0 sc0 ls0 ws0">nees<span class="_ _18"> </span>de<span class="_ _18"> </span>Die à<span class="_ _18"> </span>ce-</div><div class="t m0 x59 h12 y17f ffb fs9 fc0 sc0 ls0 ws0">là.<span class="_ _10"> </span>En qoy<span class="_ _18"> </span>to-</div><div class="t m0 x59 h12 y180 ffb fs9 fc0 sc0 ls0 ws0">teſfois<span class="_ _0"> </span>fat<span class="_ _18"> </span>fir<span class="_ _18"> </span>c-</div><div class="t m0 x59 h12 y181 ffb fs9 fc0 sc0 ls0 ws0">rioté &amp; ſperſti-</div><div class="t m0 x59 h12 y182 ffb fs9 fc0 sc0 ls0 ws0">tion q</div><div class="t m0 x5c h12 y183 ffb fs9 fc0 sc0 ls0 ws0">̃</div><div class="t m0 x5d h12 y182 ffb fs9 fc0 sc0 ls0 ws0">les hõmes</div><div class="t m0 x59 h12 y184 ffb fs9 fc0 sc0 ls0 ws0">ont cõtroee<span class="_ _18"> </span>ſr</div><div class="t m0 x59 h12 y185 ffb fs9 fc0 sc0 ls0 ws0">celà.</div></div><div class="t m0 xd h5 y186 ff3 fs1 fc0 sc0 ls0 ws0">Figure<span class="_ _8"> </span>1</div><div class="t m1 x5e h13 y186 ff4 fs1 fc0 sc0 ls0 ws0">:<span class="_ _7"> </span>Bible<span class="_ _8"> </span>de<span class="_ _8"> </span>Gen`<span class="_ _19"></span>ev<span class="_ _5"></span>e,<span class="_ _8"> </span>1564<span class="_ _13"> </span>[</div><div class="t m0 x5f h13 y186 ff4 fs1 fc0 sc0 ls0 ws0">8</div><div class="t m1 x60 h13 y186 ff4 fs1 fc0 sc0 ls0 ws0">],<span class="_ _8"> </span>t<span class="_ _5"></span>yp<span class="_ _0"></span>eset<span class="_ _13"> </span>by</div><div class="t m1 xd h13 y187 ff4 fs1 fc0 sc0 ls0 ws0">Rapha<span class="_ _5"></span>¨<span class="_ _19"></span>el<span class="_ _8"> </span>Pinson<span class="_ _8"> </span>with</div><div class="t m0 x61 h13 y187 ff4 fs1 fc0 sc0 ls0 ws0">X</div><div class="t m24 x19 h13 y188 ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 x62 h13 y187 ff4 fs1 fc0 sc0 ls0 ws0">T</div><div class="t m0 x63 h13 y188 ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 x64 h13 y187 ff4 fs1 fc0 sc0 ls0 ws0">X.<span class="_ _7"> </span>The<span class="_ _8"> </span>drop<span class="_ _8"> </span>cap,<span class="_ _8"> </span>fonts,</div><div class="t m1 xd h13 y189 ff4 fs1 fc0 sc0 ls0 ws0">spacing<span class="_ _8"> </span>and<span class="_ _13"> </span>lay<span class="_ _5"></span>out<span class="_ _8"> </span>w<span class="_ _e"></span>ere<span class="_ _8"> </span>carefully<span class="_ _8"> </span>tuned<span class="_ _8"> </span>in<span class="_ _8"> </span>order<span class="_ _8"> </span>to</div><div class="t m0 xd h13 y18a ff4 fs1 fc0 sc0 ls0 ws0">duplicate<span class="_ _8"> </span>the<span class="_ _8"> </span>16th<span class="_ _8"> </span>century<span class="_ _13"> </span>F<span class="_ _2"></span>rench<span class="_ _8"> </span>Bible.</div><div class="t m1 xd h2 y18b ff1 fs0 fc0 sc0 ls0 ws0">migh<span class="_ _5"></span>t<span class="_ _7"> </span>wan<span class="_ _e"></span>t<span class="_ _11"> </span>text<span class="_ _7"> </span>in<span class="_ _11"> </span>the<span class="_ _7"> </span>do<span class="_ _0"></span>cument<span class="_ _7"> </span>to<span class="_ _11"> </span>b<span class="_ _0"></span>e<span class="_ _7"> </span>reflow<span class="_ _e"></span>ed</div><div class="t m0 xd h2 y18c ff1 fs0 fc0 sc0 ls0 ws0">according<span class="_ _1"> </span>to<span class="_ _1"> </span>the<span class="_ _1"> </span>screen<span class="_ _1"> </span>size<span class="_ _1"> </span>of<span class="_ _1"> </span>their<span class="_ _1"> </span>mobile<span class="_ _1"> </span>devices.</div><div class="t m19 xe h2 y18d ff1 fs0 fc0 sc0 ls0 ws0">Ho<span class="_ _e"></span>wev<span class="_ _e"></span>er,<span class="_ _1"> </span>in<span class="_ _4"> </span>man<span class="_ _e"></span>y<span class="_ _1"> </span>cases,<span class="_ _1"> </span>fonts,<span class="_ _8"> </span>spacing<span class="_ _1"> </span>and<span class="_ _1"> </span>lay-</div><div class="t m1 xd h2 y18e ff1 fs0 fc0 sc0 ls0 ws0">outs<span class="_ _9"> </span>are<span class="_ _7"> </span>carefully<span class="_ _7"> </span>designed<span class="_ _9"> </span>to<span class="_ _7"> </span>assist<span class="_ _9"> </span>reading,<span class="_ _11"> </span>and</div><div class="t m21 xd h2 y18f ff1 fs0 fc0 sc0 ls0 ws0">sometimes<span class="_ _1"> </span>they<span class="_ _1"> </span>hav<span class="_ _e"></span>e<span class="_ _1"> </span>already<span class="_ _1"> </span>b<span class="_ _0"></span>ecome<span class="_ _1"> </span>essential<span class="_ _8"> </span>parts</div><div class="t m1 xd h2 y190 ff1 fs0 fc0 sc0 ls0 ws0">of<span class="_ _4"> </span>the<span class="_ _1"> </span>do<span class="_ _0"></span>cumen<span class="_ _5"></span>t,<span class="_ _4"> </span>see<span class="_ _1"> </span>Figures<span class="_ _4"> </span>1<span class="_ _1"> </span>and<span class="_ _4"> </span>2<span class="_ _1"> </span>as<span class="_ _4"> </span>examples.</div><div class="t mc xd h2 y191 ff1 fs0 fc0 sc0 ls0 ws0">In<span class="_ _1"> </span>suc<span class="_ _e"></span>h<span class="_ _1"> </span>cases,<span class="_ _1"> </span>a<span class="_ _1"> </span>complete<span class="_ _1"> </span>redesign<span class="_ _1"> </span>may<span class="_ _8"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>inv<span class="_ _e"></span>olved</div><div class="t m0 xd h2 y192 ff1 fs0 fc0 sc0 ls0 ws0">in<span class="_ _1"> </span>order<span class="_ _1"> </span>to<span class="_ _1"> </span>optimize<span class="_ _1"> </span>for<span class="_ _1"> </span>sp<span class="_ _0"></span>ecific<span class="_ _1"> </span>media.</div><div class="t m1 xe h2 y193 ff1 fs0 fc0 sc0 ls0 ws0">In<span class="_ _4"> </span>our<span class="_ _9"> </span>opinion<span class="_ _4"> </span>b<span class="_ _0"></span>oth<span class="_ _4"> </span>situations<span class="_ _9"> </span>are<span class="_ _4"> </span>imp<span class="_ _0"></span>ortant,</div><div class="t m9 xd h2 y194 ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _1"> </span>we<span class="_ _8"> </span>will<span class="_ _1"> </span>try<span class="_ _1"> </span>to<span class="_ _1"> </span>cov<span class="_ _e"></span>er<span class="_ _1"> </span>b<span class="_ _0"></span>oth<span class="_ _1"> </span>of<span class="_ _4"> </span>them<span class="_ _8"> </span>in<span class="_ _1"> </span>this<span class="_ _1"> </span>article.</div><div class="t m0 xd h3 y195 ff2 fs0 fc0 sc0 ls0 ws0">Flexibilit<span class="_ _e"></span>y</div><div class="t m1 x65 h2 y195 ff1 fs0 fc0 sc0 ls0 ws0">An<span class="_ _9"> </span>imp<span class="_ _0"></span>ortant<span class="_ _4"> </span>purp<span class="_ _0"></span>ose<span class="_ _7"> </span>of<span class="_ _9"> </span>the<span class="_ _9"> </span>online</div><div class="t m19 xd h2 y196 ff1 fs0 fc0 sc0 ls0 ws0">v<span class="_ _e"></span>ersion<span class="_ _4"> </span>is<span class="_ _8"> </span>to<span class="_ _1"> </span>provide<span class="_ _8"> </span>b<span class="_ _0"></span>etter<span class="_ _1"> </span>services<span class="_ _1"> </span>and<span class="_ _1"> </span>user<span class="_ _4"> </span>experi-</div><div class="t m2 xd h2 y197 ff1 fs0 fc0 sc0 ls0 ws0">ence.<span class="_ _9"> </span>This version of the<span class="_ _d"> </span>do<span class="_ _0"></span>cumen<span class="_ _e"></span>t should b<span class="_ _0"></span>e flexible</div><div class="t m4 xd h2 y198 ff1 fs0 fc0 sc0 ls0 ws0">enough<span class="_ _1"> </span>for<span class="_ _1"> </span>fron<span class="_ _5"></span>t-end<span class="_ _1"> </span>designers<span class="_ _1"> </span>to<span class="_ _1"> </span>design<span class="_ _1"> </span>interactiv<span class="_ _e"></span>e</div><div class="t m0 xd h2 y199 ff1 fs0 fc0 sc0 ls0 ws0">w<span class="_ _e"></span>eb<span class="_ _4"> </span>pages.</div><div class="t m1 xe h2 y19a ff1 fs0 fc0 sc0 ls0 ws0">F<span class="_ _2"></span>or<span class="_ _7"> </span>example,<span class="_ _11"> </span>text<span class="_ _7"> </span>and<span class="_ _7"> </span>other<span class="_ _7"> </span>elements<span class="_ _9"> </span>in<span class="_ _7"> </span>the</div><div class="t m2 xd h2 y19b ff1 fs0 fc0 sc0 ls0 ws0">do<span class="_ _0"></span>cumen<span class="_ _e"></span>ts should be accessible suc<span class="_ _e"></span>h that extra<span class="_ _14"> </span>styles</div><div class="t m2 xd h2 y19c ff1 fs0 fc0 sc0 ls0 ws0">or<span class="_ _14"> </span>effects<span class="_ _14"> </span>can<span class="_ _14"> </span>b<span class="_ _0"></span>e<span class="_ _14"> </span>sp<span class="_ _0"></span>ecified; the<span class="_ _14"> </span>whole<span class="_ _14"> </span>do<span class="_ _0"></span>cument<span class="_ _14"> </span>should</div><div class="t m2 xd h2 y19d ff1 fs0 fc0 sc0 ls0 ws0">b<span class="_ _0"></span>e<span class="_ _14"> </span>able<span class="_ _14"> </span>to be<span class="_ _14"> </span>embedded<span class="_ _d"> </span>in<span class="_ _e"></span>to existing<span class="_ _14"> </span>framew<span class="_ _e"></span>orks<span class="_ _14"> </span>with</div><div class="t m0 xd h2 y19e ff1 fs0 fc0 sc0 ls0 ws0">w<span class="_ _e"></span>ell-defined<span class="_ _4"> </span>behaviou<span class="_ _5"></span>rs<span class="_ _1"> </span>and<span class="_ _1"> </span>themes<span class="_ _1"> </span>applied.</div><div class="t m0 xd h3 y37 ff2 fs0 fc0 sc0 ls0 ws0">Optimization</div><div class="t m2 x66 h2 y37 ff1 fs0 fc0 sc0 ls0 ws0">There are concerns for w<span class="_ _e"></span>eb services</div><div class="t m5 xd h2 y38 ff1 fs0 fc0 sc0 ls0 ws0">whic<span class="_ _e"></span>h<span class="_ _4"> </span>ma<span class="_ _e"></span>y<span class="_ _1"> </span>not<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>cov<span class="_ _e"></span>ered<span class="_ _1"> </span>by<span class="_ _1"> </span>traditional<span class="_ _1"> </span>media:<span class="_ _7"> </span>the</div><div class="t m0 x0 h2 y77 ff1 fs0 fc0 sc0 ls0 ws0">Lu<span class="_ _1"> </span>W<span class="_ _2"></span>ang<span class="_ _1"> </span>and<span class="_ _1"> </span>W<span class="_ _2"></span>anmin<span class="_ _1"> </span>Liu</div><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",314.092,576.538,null]'><div class="d m1d" style="border-style:none;position:absolute;left:255.158379px;bottom:922.990431px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",314.092,541.669,null]'><div class="d m1d" style="border-style:none;position:absolute;left:280.642928px;bottom:922.990431px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",314.092,460.971,null]'><div class="d m1d" style="border-style:none;position:absolute;left:315.460601px;bottom:922.990431px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,129.215,null]'><div class="d m1d" style="border-style:none;position:absolute;left:436.525176px;bottom:692.951843px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,535.691,null]'><div class="d m1d" style="border-style:none;position:absolute;left:762.449987px;bottom:669.202405px;width:6.600000px;height:7.771000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf2" data-dest-detail='[2,"XYZ",359.747,411.908,null]'><div class="d m1d" style="border-style:none;position:absolute;left:745.801621px;bottom:453.839477px;width:7.073000px;height:10.848000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf3" data-dest-detail='[3,"XYZ",117.655,412.133,null]'><div class="d m1d" style="border-style:none;position:absolute;left:793.901176px;bottom:453.839477px;width:7.073000px;height:10.848000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.673203,0.000000,0.000000,1.673203,0.000000,0.000000]}'></div></div>
<div id="pf3" class="pf w0 h0" data-page-no="3"><div class="pc pc3 w0 h0"><img class="bi x0 y19f w4 h14" alt="" 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"/><div class="t m0 x0 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">TUGb<span class="_ _0"></span>oat,<span class="_ _1"> </span>V<span class="_ _2"></span>olume<span class="_ _1"> </span>34<span class="_ _1"> </span>(2013),<span class="_ _1"> </span>No.<span class="_ _1"> </span>3<span class="_ _3"> </span>315</div><div class="c x67 y1a0 w5 h15"><div class="t m0 x68 h16 y1a1 ffd fsb fc0 sc0 ls0 ws0">Organic<span class="_ _18"> </span>Trader<span class="_ _18"> </span>Pty<span class="_ _16"> </span>Ltd.<span class="_ _18"> </span>Ph.<span class="_ _16"> </span>02<span class="_ _18"> </span>8399<span class="_ _16"> </span>0122,<span class="_ _18"> </span>Fax<span class="_ _18"> </span>02<span class="_ _16"> </span>8399<span class="_ _18"> </span>1766.<span class="_ _16"> </span>Order<span class="_ _18"> </span>by<span class="_ _16"> </span>the<span class="_ _18"> </span>carton<span class="_ _16"> </span>and<span class="_ _18"> </span>save<span class="_ _18"> </span>5%.<span class="_ _1a"> </span>21</div><div class="t m0 x69 h17 y1a2 ffd fsc fc0 sc0 ls0 ws0">.<span class="_ _0"> </span>.<span class="_ _18"> </span>.<span class="_ _0"> </span>continued<span class="_ _18"> </span>from<span class="_ _16"> </span>previous<span class="_ _0"> </span>page.</div><div class="t m0 x69 h18 y1a3 ffe fsc fc1 sc0 ls0 ws0">Product<span class="_ _18"> </span>Description<span class="_ _1b"> </span>Carton($)<span class="_ _7"> </span>Unit($)<span class="_ _9"> </span>U/C<span class="_ _4"> </span>RRP($)<span class="_ _f"> </span>Item<span class="_ _16"> </span>No<span class="_ _9"> </span>GST<span class="_ _d"> </span>Barcode<span class="_ _1c"> </span>Organic</div><div class="t m0 x6a h16 y1a4 ffd fsc fc2 sc0 ls0 ws0">NEW<span class="_ _10"> </span><span class="fsb fc0">BC<span class="_ _16"> </span>Red<span class="_ _18"> </span>Wine<span class="_ _16"> </span>Vinegar<span class="_ _18"> </span>Chips<span class="_ _16"> </span>142g<span class="_ _1d"> </span><span class="ffe">3.33<span class="_ _b"> </span></span>3.51<span class="_ _f"> </span>12<span class="_ _12"> </span>5.50<span class="_ _9"> </span>9197006<span class="_ _1"> </span>10%<span class="_ _14"> </span>708163114878</span></div><div class="t m0 x6a h16 y1a5 ffd fsc fc2 sc0 ls0 ws0">NEW<span class="_ _10"> </span><span class="fsb fc0">BC<span class="_ _16"> </span>Hummus<span class="_ _18"> </span>Sesame<span class="_ _16"> </span>Chips<span class="_ _18"> </span>142g<span class="_ _1e"> </span><span class="ffe">3.75<span class="_ _b"> </span></span>3.95<span class="_ _f"> </span>12<span class="_ _12"> </span>5.95<span class="_ _9"> </span>9197051<span class="_ _1"> </span>10%<span class="_ _14"> </span>708163300219</span></div><div class="t m0 x6b h19 y1a6 ffd fsd fc1 sc0 ls0 ws0">Chic<span class="_ _16"> </span>Nuts<span class="_ _18"> </span>-<span class="_ _16"> </span>Roasted<span class="_ _16"> </span>Chickpeas<span class="_ _18"> </span>&amp;<span class="_ _16"> </span>Broad<span class="_ _16"> </span>Beans</div><div class="t m0 x6c h19 y1a7 ffd fsd fc0 sc0 ls0 ws0">Fantastic<span class="_ _18"> </span>packaging,<span class="_ _16"> </span>available<span class="_ _18"> </span>in<span class="_ _16"> </span>200g<span class="_ _16"> </span>bags<span class="_ _18"> </span>or<span class="_ _16"> </span>mini<span class="_ _16"> </span>packs,<span class="_ _18"> </span>these<span class="_ _16"> </span>scrumptious<span class="_ _16"> </span>savoury<span class="_ _16"> </span>snacks</div><div class="t m0 x6c h19 y1a8 ffd fsd fc0 sc0 ls0 ws0">are<span class="_ _16"> </span>best-sellers!<span class="_ _18"> </span>Toasted,<span class="_ _18"> </span>roasted<span class="_ _16"> </span>chick<span class="_ _16"> </span>peas<span class="_ _16"> </span>and<span class="_ _18"> </span>broad<span class="_ _16"> </span>(fava)<span class="_ _18"> </span>beans.<span class="_ _16"> </span>The<span class="_ _16"> </span>oil<span class="_ _16"> </span>used<span class="_ _18"> </span>is<span class="_ _16"> </span>Monola,</div><div class="t m0 x6c h19 y1a9 ffd fsd fc0 sc0 ls0 ws0">which<span class="_ _16"> </span>has<span class="_ _16"> </span>been<span class="_ _18"> </span>developed<span class="_ _16"> </span>through<span class="_ _16"> </span>normal<span class="_ _16"> </span>breeding<span class="_ _16"> </span>of<span class="_ _16"> </span>non<span class="_ _18"> </span>GMO<span class="_ _16"> </span>canola<span class="_ _16"> </span>oil.<span class="_ _16"> </span>100%<span class="_ _16"> </span>Australian</div><div class="t m0 x6c h19 y1aa ffd fsd fc0 sc0 ls0 ws0">owned<span class="_ _16"> </span>and<span class="_ _18"> </span>grown.</div><div class="t m0 x69 h18 y1ab ffe fsc fc1 sc0 ls0 ws0">Product<span class="_ _18"> </span>Description<span class="_ _1b"> </span>Carton($)<span class="_ _7"> </span>Unit($)<span class="_ _9"> </span>U/C<span class="_ _4"> </span>RRP($)<span class="_ _f"> </span>Item<span class="_ _16"> </span>No<span class="_ _9"> </span>GST<span class="_ _d"> </span>Barcode<span class="_ _1c"> </span>Organic</div><div class="t m0 x69 h16 y1ac ffd fsb fc0 sc0 ls0 ws0">CN<span class="_ _18"> </span>Chic<span class="_ _16"> </span>Nuts<span class="_ _18"> </span>-<span class="_ _16"> </span>Lightly<span class="_ _18"> </span>Salted<span class="_ _16"> </span>200g<span class="_ _1f"> </span><span class="ffe">3.95<span class="_ _20"> </span></span>N/A<span class="_ _12"> </span>5<span class="_ _15"> </span>6.45<span class="_ _9"> </span>9304201<span class="_ _1"> </span>10%<span class="_ _14"> </span>9318471000520</div><div class="t m0 x69 h16 y1ad ffd fsb fc0 sc0 ls0 ws0">CN<span class="_ _18"> </span>Chic<span class="_ _16"> </span>Nuts<span class="_ _18"> </span>-<span class="_ _16"> </span>Siciln<span class="_ _18"> </span>Herb<span class="_ _16"> </span>&amp;<span class="_ _18"> </span>Garlic200g<span class="_ _1e"> </span><span class="ffe">3.95<span class="_ _20"> </span></span>N/A<span class="_ _12"> </span>5<span class="_ _15"> </span>6.45<span class="_ _9"> </span>9304202<span class="_ _1"> </span>10%<span class="_ _14"> </span>9318471000537</div><div class="t m0 x69 h16 y1ae ffd fsb fc0 sc0 ls0 ws0">CN<span class="_ _18"> </span>Fava<span class="_ _18"> </span>Nuts<span class="_ _16"> </span>-<span class="_ _18"> </span>Lightly<span class="_ _16"> </span>Salted<span class="_ _18"> </span>200g<span class="_ _1f"> </span><span class="ffe">3.95<span class="_ _20"> </span></span>N/A<span class="_ _15"> </span>5<span class="_ _12"> </span>6.45<span class="_ _9"> </span>9304203<span class="_ _1"> </span>10%<span class="_ _14"> </span>9318471000568</div><div class="t m0 x69 h16 y1af ffd fsb fc0 sc0 ls0 ws0">CN<span class="_ _18"> </span>Chic<span class="_ _16"> </span>Nuts<span class="_ _18"> </span>-<span class="_ _16"> </span>Lightly<span class="_ _18"> </span>Salted<span class="_ _16"> </span>6x25g<span class="_ _21"> </span><span class="ffe">4.00<span class="_ _20"> </span></span>N/A<span class="_ _12"> </span>5<span class="_ _15"> </span>6.95<span class="_ _9"> </span>9304301<span class="_ _1"> </span>10%<span class="_ _14"> </span>9318471000544</div><div class="t m0 x69 h16 y1b0 ffd fsb fc0 sc0 ls0 ws0">CN<span class="_ _18"> </span>Fava<span class="_ _18"> </span>Nuts<span class="_ _16"> </span>-<span class="_ _18"> </span>Lightly<span class="_ _16"> </span>Salted<span class="_ _18"> </span>6x25g<span class="_ _21"> </span><span class="ffe">4.00<span class="_ _20"> </span></span>N/A<span class="_ _15"> </span>5<span class="_ _12"> </span>6.95<span class="_ _9"> </span>9304302<span class="_ _1"> </span>10%<span class="_ _14"> </span>9318471000551</div><div class="t m0 x69 h16 y1b1 ffd fsb fc0 sc0 ls0 ws0">CN<span class="_ _18"> </span>Split<span class="_ _16"> </span>Chics<span class="_ _18"> </span>-<span class="_ _16"> </span>Lightly<span class="_ _18"> </span>Salted<span class="_ _16"> </span>6x25g<span class="_ _22"> </span><span class="ffe">4.00<span class="_ _20"> </span></span>N/A<span class="_ _12"> </span>5<span class="_ _15"> </span>6.95<span class="_ _9"> </span>9304303<span class="_ _1"> </span>10%<span class="_ _14"> </span>9318471000582</div><div class="t m0 x69 h16 y1b2 ffd fsb fc0 sc0 ls0 ws0">CN<span class="_ _18"> </span>Fava<span class="_ _18"> </span>Nuts<span class="_ _16"> </span>-<span class="_ _18"> </span>Moroccan<span class="_ _16"> </span>Roast<span class="_ _18"> </span>6x25g<span class="_ _23"> </span><span class="ffe">4.00<span class="_ _20"> </span></span>N/A<span class="_ _12"> </span>5<span class="_ _15"> </span>6.95<span class="_ _9"> </span>9304304<span class="_ _1"> </span>10%<span class="_ _14"> </span>9318471000575</div><div class="t m0 x6b h19 y1b3 ffd fsd fc1 sc0 ls0 ws0">Cobs<span class="_ _16"> </span>-<span class="_ _18"> </span>Favourites<span class="_ _18"> </span>Range</div><div class="t m0 x6c h19 y1b4 ffd fsd fc0 sc0 ls0 ws0">Welcome<span class="_ _16"> </span>to<span class="_ _16"> </span>the<span class="_ _16"> </span>new<span class="_ _18"> </span>range<span class="_ _16"> </span>of<span class="_ _16"> </span>pop-choco-liscious<span class="_ _16"> </span>treats.<span class="_ _16"> </span>If<span class="_ _16"> </span>youre<span class="_ _18"> </span>devoted<span class="_ _16"> </span>to<span class="_ _16"> </span>your<span class="_ _16"> </span>popcorn,<span class="_ _16"> </span>then<span class="_ _16"> </span>youll</div><div class="t m0 x6c h19 y1b5 ffd fsd fc0 sc0 ls0 ws0">love<span class="_ _16"> </span>our<span class="_ _16"> </span>latest<span class="_ _16"> </span>-<span class="_ _16"> </span>a<span class="_ _16"> </span>delectable<span class="_ _16"> </span>coating<span class="_ _16"> </span>of<span class="_ _17"> </span>caramel,<span class="_ _16"> </span>smooth<span class="_ _16"> </span>milk<span class="_ _16"> </span>or<span class="_ _16"> </span>decadent<span class="_ _16"> </span>dark<span class="_ _16"> </span>chocolate<span class="_ _16"> </span>over<span class="_ _16"> </span>Cobs</div><div class="t m0 x6c h19 y1b6 ffd fsd fc0 sc0 ls0 ws0">pure<span class="_ _16"> </span>popcorn.<span class="_ _16"> </span>Chocolate<span class="_ _16"> </span>varieties<span class="_ _16"> </span>are<span class="_ _16"> </span>only<span class="_ _18"> </span>available<span class="_ _16"> </span>in<span class="_ _16"> </span>the<span class="_ _16"> </span>Sydney<span class="_ _18"> </span>Metro<span class="_ _16"> </span>Area<span class="_ _16"> </span>-<span class="_ _16"> </span>extra<span class="_ _16"> </span>freight<span class="_ _16"> </span>charges</div><div class="t m0 x6c h19 y1b7 ffd fsd fc0 sc0 ls0 ws0">apply<span class="_ _e"></span>.</div><div class="t m0 x69 h18 y1b8 ffe fsc fc1 sc0 ls0 ws0">Product<span class="_ _18"> </span>Description<span class="_ _1b"> </span>Carton($)<span class="_ _7"> </span>Unit($)<span class="_ _9"> </span>U/C<span class="_ _4"> </span>RRP($)<span class="_ _f"> </span>Item<span class="_ _16"> </span>No<span class="_ _9"> </span>GST<span class="_ _d"> </span>Barcode<span class="_ _1c"> </span>Organic</div><div class="t m0 x69 h16 y1b9 ffd fsb fc0 sc0 ls0 ws0">COBS<span class="_ _18"> </span>Caramel<span class="_ _16"> </span>Popcorn<span class="_ _18"> </span>125g<span class="_ _24"> </span><span class="ffe">2.43<span class="_ _20"> </span></span>N/A<span class="_ _f"> </span>10<span class="_ _12"> </span>3.95<span class="_ _9"> </span>9381400<span class="_ _1"> </span>10%<span class="_ _14"> </span>9334714000225</div><div class="t m0 x69 h16 y1ba ffd fsb fc0 sc0 ls0 ws0">COBS<span class="_ _18"> </span>Milk<span class="_ _16"> </span>Chocolate<span class="_ _18"> </span>Caramel<span class="_ _16"> </span>Popcorn<span class="_ _18"> </span>175g<span class="_ _25"> </span><span class="ffe">5.00<span class="_ _20"> </span></span>N/A<span class="_ _f"> </span>10<span class="_ _12"> </span>8.25<span class="_ _9"> </span>9381401<span class="_ _1"> </span>10%<span class="_ _14"> </span>9334714000232</div><div class="t m0 x69 h16 y1bb ffd fsb fc0 sc0 ls0 ws0">COBS<span class="_ _18"> </span>Dar<span class="_ _0"></span>k<span class="_ _18"> </span>Chocolate<span class="_ _16"> </span>Caramel<span class="_ _18"> </span>Popcorn<span class="_ _16"> </span>175g<span class="_ _26"> </span><span class="ffe">5.00<span class="_ _20"> </span></span>N/A<span class="_ _f"> </span>10<span class="_ _12"> </span>8.25<span class="_ _9"> </span>9381402<span class="_ _1"> </span>10%<span class="_ _14"> </span>9334714000249</div><div class="t m0 x6b h19 y1bc ffd fsd fc1 sc0 ls0 ws0">Cobs<span class="_ _16"> </span>Organic<span class="_ _18"> </span>&amp;<span class="_ _16"> </span>Natural<span class="_ _16"> </span>P<span class="_ _5"></span>opcorn</div><div class="t m0 x6c h19 y1bd ffd fsd fc0 sc0 ls0 ws0">This<span class="_ _16"> </span>popcorn<span class="_ _17"> </span>is<span class="_ _16"> </span>completely<span class="_ _16"> </span>gratifying<span class="_ _16"> </span>and<span class="_ _17"> </span>unquestionably<span class="_ _16"> </span>delicious.<span class="_ _16"> </span>It<span class="_ _16"> </span>is<span class="_ _16"> </span>very</div><div class="t m0 x6c h19 y1be ffd fsd fc0 sc0 ls0 ws0">crunchy<span class="_ _16"> </span>and<span class="_ _16"> </span>fresh<span class="_ _18"> </span>and<span class="_ _16"> </span>comes<span class="_ _16"> </span>in<span class="_ _16"> </span>three<span class="_ _16"> </span>great<span class="_ _16"> </span>flavours<span class="_ _e"></span>.<span class="_ _16"> </span>The<span class="_ _16"> </span>original<span class="_ _16"> </span>recipe<span class="_ _16"> </span>pop-</div><div class="t m0 x6c h19 y1bf ffd fsd fc0 sc0 ls0 ws0">corn<span class="_ _18"> </span>is<span class="_ _16"> </span>slightly<span class="_ _18"> </span>sweet<span class="_ _18"> </span>and<span class="_ _18"> </span>slightly<span class="_ _16"> </span>salty<span class="_ _e"></span>,<span class="_ _18"> </span>and<span class="_ _16"> </span>for<span class="_ _0"> </span>those<span class="_ _16"> </span>who<span class="_ _18"> </span>prefer<span class="_ _18"> </span>a<span class="_ _18"> </span>more<span class="_ _16"> </span>sav<span class="_ _e"></span>our<span class="_ _0"></span>y</div><div class="t m0 x6c h19 y1c0 ffd fsd fc0 sc0 ls0 ws0">flavour<span class="_ _e"></span>,<span class="_ _16"> </span>Sea<span class="_ _16"> </span>Salt<span class="_ _16"> </span>is<span class="_ _18"> </span>perfect.<span class="_ _16"> </span>For<span class="_ _18"> </span>optimal<span class="_ _16"> </span>freshness<span class="_ _16"> </span>it<span class="_ _18"> </span>has<span class="_ _16"> </span>a<span class="_ _16"> </span>34<span class="_ _18"> </span>month<span class="_ _16"> </span>shelf<span class="_ _16"> </span>life<span class="_ _e"></span>,</div><div class="t m0 x6c h19 y1c1 ffd fsd fc0 sc0 ls0 ws0">but<span class="_ _16"> </span>it<span class="_ _18"> </span>is<span class="_ _16"> </span>so<span class="_ _16"> </span>popular<span class="_ _18"> </span>you<span class="_ _16"> </span>wont<span class="_ _16"> </span>hav<span class="_ _e"></span>e<span class="_ _16"> </span>any<span class="_ _16"> </span>trouble<span class="_ _18"> </span>keeping<span class="_ _16"> </span>it<span class="_ _16"> </span>moving.</div><div class="t m0 x69 h18 y1c2 ffe fsc fc1 sc0 ls0 ws0">Product<span class="_ _18"> </span>Description<span class="_ _1b"> </span>Carton($)<span class="_ _7"> </span>Unit($)<span class="_ _9"> </span>U/C<span class="_ _4"> </span>RRP($)<span class="_ _f"> </span>Item<span class="_ _16"> </span>No<span class="_ _9"> </span>GST<span class="_ _d"> </span>Barcode<span class="_ _1c"> </span>Organic</div><div class="t m0 x69 h16 y1c3 ffd fsb fc0 sc0 ls0 ws0">COBS<span class="_ _18"> </span>Or<span class="_ _0"></span>iginal<span class="_ _18"> </span>Organic<span class="_ _16"> </span>Popcorn<span class="_ _18"> </span>125g<span class="_ _27"> </span><span class="ffe">2.72<span class="_ _20"> </span></span>N/A<span class="_ _f"> </span>10<span class="_ _12"> </span>4.95<span class="_ _9"> </span>9381001<span class="_ _1"> </span>10%<span class="_ _14"> </span>9334714000010<span class="_ _20"> </span><span class="fsc">ACO</span></div><div class="t m0 x69 h16 y1c4 ffd fsb fc0 sc0 ls0 ws0">COBS<span class="_ _18"> </span>Or<span class="_ _0"></span>iginal<span class="_ _18"> </span>Organic<span class="_ _16"> </span>Popcorn<span class="_ _18"> </span>40g<span class="_ _28"> </span><span class="ffe">1.22<span class="_ _b"> </span></span>1.28<span class="_ _f"> </span>24<span class="_ _12"> </span>2.20<span class="_ _9"> </span>9381002<span class="_ _1"> </span>10%<span class="_ _14"> </span>9334714000102<span class="_ _29"> </span><span class="fsc">ACO</span></div><div class="t m0 x69 h16 y1c5 ffd fsb fc0 sc0 ls0 ws0">COBS<span class="_ _18"> </span>Sea<span class="_ _16"> </span>Salt<span class="_ _18"> </span>Organic<span class="_ _16"> </span>Popcorn<span class="_ _18"> </span>80g<span class="_ _1a"> </span><span class="ffe">1.86<span class="_ _20"> </span></span>N/A<span class="_ _11"> </span>10<span class="_ _12"> </span>3.30<span class="_ _9"> </span>9381101<span class="_ _1"> </span>10%<span class="_ _14"> </span>9334714000041<span class="_ _29"> </span><span class="fsc">ACO</span></div><div class="t m0 x69 h16 y1c6 ffd fsb fc0 sc0 ls0 ws0">COBS<span class="_ _18"> </span>Sea<span class="_ _16"> </span>Salt<span class="_ _18"> </span>Organic<span class="_ _16"> </span>Popcorn<span class="_ _18"> </span>25g<span class="_ _1a"> </span><span class="ffe">1.11<span class="_ _b"> </span></span>1.17<span class="_ _f"> </span>24<span class="_ _12"> </span>1.95<span class="_ _9"> </span>9381102<span class="_ _8"> </span>10%<span class="_ _14"> </span>9334714000058<span class="_ _29"> </span><span class="fsc">ACO</span></div><div class="t m0 x69 h16 y1c7 ffd fsb fc0 sc0 ls0 ws0">COBS<span class="_ _18"> </span>Cheddar<span class="_ _16"> </span>Cheese<span class="_ _18"> </span>Popcorn<span class="_ _16"> </span>100g<span class="_ _2a"> </span><span class="ffe">2.00<span class="_ _20"> </span></span>N/A<span class="_ _f"> </span>10<span class="_ _12"> </span>3.30<span class="_ _9"> </span>9381251<span class="_ _1"> </span>10%<span class="_ _14"> </span>9334714000140</div><div class="t m0 x69 h16 y1c8 ffd fsb fc0 sc0 ls0 ws0">COBS<span class="_ _18"> </span>Coco<span class="_ _16"> </span>Crunch<span class="_ _18"> </span>Popcorn<span class="_ _16"> </span>120g<span class="_ _1f"> </span><span class="ffe">2.00<span class="_ _20"> </span></span>N/A<span class="_ _f"> </span>10<span class="_ _12"> </span>3.30<span class="_ _9"> </span>9381253<span class="_ _1"> </span>10%<span class="_ _14"> </span>9334714000218</div><div class="t m0 x6a h16 y1c9 ffd fsc fc2 sc0 ls0 ws0">NEW<span class="_ _10"> </span><span class="fsb fc0">COBS<span class="_ _16"> </span>Natural<span class="_ _18"> </span>Sweet&amp;Salty<span class="_ _18"> </span>Popcorn<span class="_ _16"> </span>120g<span class="_ _2b"> </span><span class="ffe">2.00<span class="_ _20"> </span></span>N/A<span class="_ _f"> </span>10<span class="_ _12"> </span>3.30<span class="_ _9"> </span>9381254<span class="_ _1"> </span>10%<span class="_ _14"> </span>9334714000157</span></div><div class="t m0 x6a h16 y1ca ffd fsc fc2 sc0 ls0 ws0">NEW<span class="_ _10"> </span><span class="fsb fc0">COBS<span class="_ _16"> </span>Natural<span class="_ _18"> </span>SeaSalt<span class="_ _16"> </span>P<span class="_ _e"></span>opcor<span class="_ _0"></span>n<span class="_ _18"> </span>80g<span class="_ _2c"> </span><span class="ffe">1.57<span class="_ _20"> </span></span>N/A<span class="_ _f"> </span>10<span class="_ _12"> </span>2.60<span class="_ _9"> </span>9381257<span class="_ _1"> </span>10%<span class="_ _14"> </span>9334714000096</span></div><div class="t m0 x69 h16 y1cb ffd fsb fc0 sc0 ls0 ws0">COBS<span class="_ _18"> </span>Popcorn<span class="_ _16"> </span>Multipack<span class="_ _18"> </span>(10x13g)<span class="_ _16"> </span>130g<span class="_ _1e"> </span><span class="ffe">3.39<span class="_ _20"> </span></span>N/A<span class="_ _15"> </span>8<span class="_ _12"> </span>5.95<span class="_ _9"> </span>9381300<span class="_ _8"> </span>10%<span class="_ _14"> </span>9334714000164</div><div class="t m0 x6b h19 y1cc ffd fsd fc1 sc0 ls0 ws0">Cocolo<span class="_ _16"> </span>Organic<span class="_ _18"> </span>Fairtrade<span class="_ _16"> </span>Chocolate</div><div class="t m0 x6c h19 y1cd ffd fsd fc0 sc0 ls0 ws0">V<span class="_ _5"></span>elvety<span class="_ _e"></span>,<span class="_ _16"> </span>smooth<span class="_ _16"> </span>and<span class="_ _16"> </span>delicious,<span class="_ _16"> </span>Cocolo<span class="_ _16"> </span>contains<span class="_ _16"> </span>no<span class="_ _16"> </span>refined<span class="_ _16"> </span>sugar,</div><div class="t m0 x6c h19 y1ce ffd fsd fc0 sc0 ls0 ws0">only<span class="_ _16"> </span>evaporated<span class="_ _16"> </span>cane<span class="_ _16"> </span>juice.<span class="_ _16"> </span>Cocolo<span class="_ _17"> </span>is<span class="_ _16"> </span>made<span class="_ _16"> </span>in<span class="_ _16"> </span>Switzerland<span class="_ _16"> </span>from</div><div class="t m0 x6c h19 y1cf ffd fsd fc0 sc0 ls0 ws0">the<span class="_ _18"> </span>finest<span class="_ _16"> </span>Organic<span class="_ _18"> </span>and<span class="_ _16"> </span>F<span class="_ _e"></span>air<span class="_ _0"></span>trade<span class="_ _18"> </span>ingredients.<span class="_ _16"> </span>The<span class="_ _18"> </span>cocoa<span class="_ _18"> </span>and<span class="_ _16"> </span>evap-</div><div class="t m0 x6c h19 y1d0 ffd fsd fc0 sc0 ls0 ws0">orated<span class="_ _18"> </span>cane<span class="_ _16"> </span>juice<span class="_ _18"> </span>come<span class="_ _16"> </span>from<span class="_ _18"> </span>Fairtrade<span class="_ _16"> </span>co-operatives.<span class="_ _18"> </span>These<span class="_ _18"> </span>com-</div><div class="t m0 x6c h19 y1d1 ffd fsd fc0 sc0 ls0 ws0">munities<span class="_ _16"> </span>are<span class="_ _16"> </span>able<span class="_ _16"> </span>to<span class="_ _16"> </span>reinvest<span class="_ _16"> </span>in<span class="_ _16"> </span>their<span class="_ _16"> </span>farms,<span class="_ _16"> </span>schools<span class="_ _16"> </span>and<span class="_ _16"> </span>commu-</div><div class="t m0 x6c h19 y1d2 ffd fsd fc0 sc0 ls0 ws0">nities<span class="_ _16"> </span>by<span class="_ _18"> </span>selling<span class="_ _16"> </span>their<span class="_ _18"> </span>beans<span class="_ _16"> </span>through<span class="_ _16"> </span>the<span class="_ _18"> </span>Fairtrade<span class="_ _16"> </span>market.<span class="_ _18"> </span>We<span class="_ _16"> </span>find</div><div class="t m0 x6c h19 y1d3 ffd fsd fc0 sc0 ls0 ws0">this<span class="_ _16"> </span>very<span class="_ _17"> </span>exciting,<span class="_ _16"> </span>and<span class="_ _16"> </span>we<span class="_ _16"> </span>hope<span class="_ _17"> </span>you<span class="_ _16"> </span>do<span class="_ _16"> </span>too!<span class="_ _17"> </span>We<span class="_ _16"> </span>choose<span class="_ _16"> </span>to<span class="_ _17"> </span>k<span class="_ _5"></span>eep</div><div class="t m0 x6c h19 y1d4 ffd fsd fc0 sc0 ls0 ws0">Cocolo<span class="_ _17"> </span>absolutely<span class="_ _16"> </span>GMO<span class="_ _17"> </span>free.<span class="_ _17"> </span>We<span class="_ _16"> </span>only<span class="_ _17"> </span>use<span class="_ _17"> </span>ingredients<span class="_ _17"> </span>that<span class="_ _16"> </span>are</div><div class="t m0 x6c h19 y1d5 ffd fsd fc0 sc0 ls0 ws0">produced<span class="_ _16"> </span>in<span class="_ _16"> </span>the<span class="_ _16"> </span>traditional<span class="_ _16"> </span>wa<span class="_ _5"></span>y<span class="_ _e"></span>,<span class="_ _16"> </span>with<span class="_ _16"> </span>special<span class="_ _16"> </span>attention<span class="_ _16"> </span>to<span class="_ _16"> </span>purity<span class="_ _16"> </span>of<span class="_ _16"> </span>the<span class="_ _16"> </span>product<span class="_ _16"> </span>and<span class="_ _16"> </span>sustainability<span class="_ _16"> </span>of<span class="_ _16"> </span>production.<span class="_ _16"> </span>All<span class="_ _16"> </span>dark<span class="_ _16"> </span>flavours<span class="_ _16"> </span>are<span class="_ _16"> </span>dairy</div><div class="t m0 x6c h19 y1d6 ffd fsd fc0 sc0 ls0 ws0">free<span class="_ _18"> </span>and<span class="_ _16"> </span>the<span class="_ _18"> </span>whole<span class="_ _16"> </span>range<span class="_ _18"> </span>is<span class="_ _16"> </span>gluten<span class="_ _18"> </span>and<span class="_ _16"> </span>soy<span class="_ _18"> </span>free.<span class="_ _16"> </span>Cocolo<span class="_ _18"> </span>Display<span class="_ _18"> </span>Kit<span class="_ _16"> </span>includes<span class="_ _18"> </span>12<span class="_ _16"> </span>units<span class="_ _18"> </span>each<span class="_ _16"> </span>of<span class="_ _18"> </span>Dark<span class="_ _16"> </span>Orange,<span class="_ _18"> </span>Milk,<span class="_ _16"> </span>70%<span class="_ _18"> </span>Dark<span class="_ _16"> </span>and<span class="_ _18"> </span>Dark<span class="_ _16"> </span>Mint.</div><div class="t m0 x6c h19 y1d7 ffd fsd fc0 sc0 ls0 ws0">Ask<span class="_ _16"> </span>us<span class="_ _18"> </span>if<span class="_ _16"> </span>you<span class="_ _16"> </span>prefer<span class="_ _18"> </span>a<span class="_ _16"> </span>different<span class="_ _18"> </span>configuration.</div><div class="t m25 x6d h1a y1d8 ffe fse fc1 sc0 ls0 ws0">Grocery</div></div><div class="t m0 x0 h5 y1d9 ff3 fs1 fc0 sc0 ls0 ws0">Figure<span class="_ _8"> </span>2</div><div class="t m1 x6e h13 y1d9 ff4 fs1 fc0 sc0 ls0 ws0">:<span class="_ _7"> </span>One<span class="_ _8"> </span>page<span class="_ _8"> </span>from<span class="_ _8"> </span>a<span class="_ _8"> </span>product<span class="_ _8"> </span>catalogue</div><div class="t m1 x0 h13 y1da ff4 fs1 fc0 sc0 ls0 ws0">generated<span class="_ _8"> </span>with<span class="_ _13"> </span>L</div><div class="t m0 x6f h7 y1db ff9 fs3 fc0 sc0 ls0 ws0">A</div><div class="t m1 x70 h13 y1da ff4 fs1 fc0 sc0 ls0 ws0">T</div><div class="t m0 x56 h13 y1dc ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 x27 h13 y1da ff4 fs1 fc0 sc0 ls0 ws0">X.<span class="_ _7"> </span>T<span class="_ _2"></span>ext<span class="_ _8"> </span>paragraphs,<span class="_ _8"> </span>images<span class="_ _8"> </span>and</div><div class="t m1 x0 h13 y1dd ff4 fs1 fc0 sc0 ls0 ws0">tables<span class="_ _8"> </span>are<span class="_ _13"> </span>well-organized<span class="_ _13"> </span>for<span class="_ _8"> </span>each<span class="_ _13"> </span>category<span class="_ _e"></span>.<span class="_ _7"> </span>The<span class="_ _8"> </span>whole</div><div class="t m1 x0 h13 y1de ff4 fs1 fc0 sc0 ls0 ws0">catalogue<span class="_ _8"> </span>con<span class="_ _5"></span>tains<span class="_ _13"> </span>more<span class="_ _8"> </span>than<span class="_ _8"> </span>70<span class="_ _8"> </span>pages,<span class="_ _8"> </span>including</div><div class="t m1 x0 h13 y1df ff4 fs1 fc0 sc0 ls0 ws0">information<span class="_ _8"> </span>on<span class="_ _13"> </span>8001000<span class="_ _8"> </span>pro<span class="_ _0"></span>ducts.<span class="_ _11"> </span>Courtesy<span class="_ _8"> </span>of</div><div class="t m0 x0 h13 y1e0 ff4 fs1 fc0 sc0 ls0 ws0">Jason<span class="_ _8"> </span>Lewis<span class="_ _8"> </span>[35].</div><div class="t m2 x0 h2 y1e1 ff1 fs0 fc0 sc0 ls0 ws0">size of the files should b<span class="_ _0"></span>e as small as p<span class="_ _0"></span>ossible in order</div><div class="t m16 x0 h2 y1e2 ff1 fs0 fc0 sc0 ls0 ws0">to<span class="_ _8"> </span>sav<span class="_ _e"></span>e<span class="_ _1"> </span>storage<span class="_ _1"> </span>space;<span class="_ _1"> </span>the<span class="_ _1"> </span>cache<span class="_ _8"> </span>mec<span class="_ _e"></span>hanism<span class="_ _1"> </span>of<span class="_ _1"> </span>web</div><div class="t m22 x0 h2 y1e3 ff1 fs0 fc0 sc0 ls0 ws0">bro<span class="_ _e"></span>w<span class="_ _0"></span>sers<span class="_ _8"> </span>should<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>utilized<span class="_ _1"> </span>when<span class="_ _1"> </span>p<span class="_ _0"></span>ossible,<span class="_ _8"> </span>in<span class="_ _1"> </span>order</div><div class="t m1 x0 h2 y1e4 ff1 fs0 fc0 sc0 ls0 ws0">to<span class="_ _1"> </span>sav<span class="_ _e"></span>e<span class="_ _1"> </span>bandwidth;<span class="_ _4"> </span>the<span class="_ _8"> </span>readers<span class="_ _1"> </span>should<span class="_ _4"> </span>not<span class="_ _8"> </span>need<span class="_ _1"> </span>to</div><div class="t m11 x0 h2 y1e5 ff1 fs0 fc0 sc0 ls0 ws0">w<span class="_ _e"></span>ait<span class="_ _1"> </span>long<span class="_ _1"> </span>b<span class="_ _0"></span>efore<span class="_ _1"> </span>viewing<span class="_ _1"> </span>the<span class="_ _1"> </span>first<span class="_ _1"> </span>few<span class="_ _1"> </span>pages,<span class="_ _1"> </span>even<span class="_ _8"> </span>if</div><div class="t m0 x0 h2 y1e6 ff1 fs0 fc0 sc0 ls0 ws0">there<span class="_ _1"> </span>are<span class="_ _1"> </span>thousands<span class="_ _1"> </span>of<span class="_ _1"> </span>pages<span class="_ _1"> </span>in<span class="_ _1"> </span>the<span class="_ _1"> </span>do<span class="_ _0"></span>cumen<span class="_ _5"></span>t.</div><div class="t m1 x1 h2 y1e7 ff1 fs0 fc0 sc0 ls0 ws0">Therefore<span class="_ _9"> </span>sp<span class="_ _0"></span>ecial<span class="_ _9"> </span>optimizations<span class="_ _9"> </span>are<span class="_ _9"> </span>necessary</div><div class="t m26 x0 h2 y1e8 ff1 fs0 fc0 sc0 ls0 ws0">when<span class="_ _1"> </span>pro<span class="_ _0"></span>ducing<span class="_ _1"> </span>an<span class="_ _1"> </span>online<span class="_ _1"> </span>version<span class="_ _8"> </span>from<span class="_ _4"> </span>a<span class="_ _8"> </span>traditional</div><div class="t m0 x0 h2 y1e9 ff1 fs0 fc0 sc0 ls0 ws0">do<span class="_ _0"></span>cumen<span class="_ _e"></span>t.</div><div class="t m0 x0 h3 y1ea ff2 fs0 fc0 sc0 ls0 ws0">3<span class="_ _c"> </span>Existing<span class="_ _4"> </span>approac<span class="_ _e"></span>hes</div><div class="t m1 x5 h2 y1eb ff1 fs0 fc0 sc0 ls0 ws0">uite<span class="_ _9"> </span>a<span class="_ _9"> </span>num<span class="_ _e"></span>b<span class="_ _0"></span>er<span class="_ _9"> </span>of<span class="_ _7"> </span>approaches<span class="_ _4"> </span>hav<span class="_ _e"></span>e<span class="_ _7"> </span>b<span class="_ _0"></span>een</div><div class="t m2 x5 h2 y1ec ff1 fs0 fc0 sc0 ls0 ws0">dev<span class="_ _e"></span>elop<span class="_ _0"></span>ed<span class="_ _8"> </span>to publish T</div><div class="t m0 x71 h2 y1ed ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m2 x72 h2 y1ec ff1 fs0 fc0 sc0 ls0 ws0">X or <span class="ff4 fs1">PDF<span class="_ _13"> </span></span>conten<span class="_ _e"></span>ts</div><div class="t m1 x5 h2 y1ee ff1 fs0 fc0 sc0 ls0 ws0">online.<span class="_ _a"> </span>P<span class="_ _e"></span>ossible<span class="_ _4"> </span>workflo<span class="_ _e"></span>ws<span class="_ _4"> </span>are<span class="_ _4"> </span>shown<span class="_ _4"> </span>in</div><div class="t m20 x5 h2 y1ef ff1 fs0 fc0 sc0 ls0 ws0">Figure<span class="_ _1"> </span>3.<span class="_ _7"> </span>It<span class="_ _1"> </span>is<span class="_ _1"> </span>p<span class="_ _0"></span>ossible<span class="_ _1"> </span>to<span class="_ _1"> </span><span class="ff5">c<span class="_ _e"></span>ompile</span></div><div class="t m0 x30 h6 y1f0 ff8 fs2 fc0 sc0 ls0 ws0">3</div><div class="t m20 x73 h2 y1ef ff1 fs0 fc0 sc0 ls0 ws0">a<span class="_ _1"> </span>T</div><div class="t m0 x74 h2 y1f1 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m20 x75 h2 y1ef ff1 fs0 fc0 sc0 ls0 ws0">X</div><div class="t m17 x0 h2 y1f2 ff1 fs0 fc0 sc0 ls0 ws0">file<span class="_ _1"> </span>into<span class="_ _8"> </span><span class="ff4 fs1">HTML</span>;<span class="_ _1"> </span>or<span class="_ _1"> </span>to<span class="_ _4"> </span><span class="ff5">c<span class="_ _2"></span>onvert</span></div><div class="t m0 x76 h6 y1f3 ff8 fs2 fc0 sc0 ls0 ws0">4</div><div class="t m17 x77 h2 y1f2 ff1 fs0 fc0 sc0 ls0 ws0">a<span class="_ _1"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>do<span class="_ _0"></span>cument<span class="_ _8"> </span>into</div><div class="t m0 x0 h2 y1f4 ff4 fs1 fc0 sc0 ls0 ws0">HTML<span class="ff1 fs0">.</span></div><div class="t m0 x78 h7 y1f5 ff9 fs3 fc0 sc0 ls0 ws0">3</div><div class="t m12 x41 h8 y71 ffa fs4 fc0 sc0 ls0 ws0">T<span class="_ _2"></span>o<span class="_ _13"> </span>determine<span class="_ _8"> </span>the<span class="_ _13"> </span>lay<span class="_ _e"></span>out<span class="_ _13"> </span>based<span class="_ _8"> </span>on<span class="_ _13"> </span>the<span class="_ _13"> </span>information<span class="_ _13"> </span>from</div><div class="t m0 x0 h8 y72 ffa fs4 fc0 sc0 ls0 ws0">the<span class="_ _13"> </span>source.</div><div class="t m0 x78 h7 y73 ff9 fs3 fc0 sc0 ls0 ws0">4</div><div class="t m2 x41 h8 y74 ffa fs4 fc0 sc0 ls0 ws0">T<span class="_ _2"></span>o<span class="_ _13"> </span>transform<span class="_ _8"> </span>b<span class="_ _0"></span>etw<span class="_ _e"></span>een<span class="_ _13"> </span>two<span class="_ _d"> </span>presentation<span class="_ _13"> </span>formats,<span class="_ _13"> </span>in<span class="_ _8"> </span>b<span class="_ _0"></span>oth</div><div class="t m0 x0 h8 y38 ffa fs4 fc0 sc0 ls0 ws0">of<span class="_ _13"> </span>which<span class="_ _d"> </span>lay<span class="_ _e"></span>out<span class="_ _8"> </span>and<span class="_ _13"> </span>app<span class="_ _0"></span>earance<span class="_ _13"> </span>are<span class="_ _13"> </span>clearly<span class="_ _13"> </span>defined.</div><div class="t m1 xe h2 y39 ff1 fs0 fc0 sc0 ls0 ws0">Con<span class="_ _5"></span>v<span class="_ _5"></span>erting<span class="_ _4"> </span>a<span class="_ _9"> </span>large<span class="_ _4"> </span>T</div><div class="t m0 x79 h2 y1f6 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 x7a h2 y39 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _4"> </span>file<span class="_ _9"> </span>with<span class="_ _4"> </span>complicated</div><div class="t m1 xd h2 y3a ff1 fs0 fc0 sc0 ls0 ws0">la<span class="_ _5"></span>y<span class="_ _5"></span>outs<span class="_ _1"> </span>into<span class="_ _1"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>is<span class="_ _4"> </span>usually<span class="_ _1"> </span>not<span class="_ _1"> </span>a<span class="_ _4"> </span>fast<span class="_ _8"> </span>pro<span class="_ _0"></span>cess.<span class="_ _f"> </span>Be-</div><div class="t m26 xd h2 y3b ff1 fs0 fc0 sc0 ls0 ws0">cause<span class="_ _1"> </span>of<span class="_ _1"> </span>this,<span class="_ _1"> </span>it<span class="_ _1"> </span>is<span class="_ _1"> </span>a<span class="_ _4"> </span>common<span class="_ _8"> </span>practice<span class="_ _1"> </span>to<span class="_ _1"> </span>conv<span class="_ _e"></span>ert<span class="_ _1"> </span>the</div><div class="t m5 xd h2 y3c ff1 fs0 fc0 sc0 ls0 ws0">source<span class="_ _1"> </span>format<span class="_ _1"> </span>into<span class="_ _8"> </span>web<span class="_ _8"> </span>pages<span class="_ _1"> </span>on<span class="_ _4"> </span>the<span class="_ _8"> </span>server<span class="_ _8"> </span>side,<span class="_ _1"> </span>the</div><div class="t m2 xd h2 y3d ff1 fs0 fc0 sc0 ls0 ws0">results can b<span class="_ _0"></span>e stored on the serv<span class="_ _e"></span>ers,<span class="_ _8"> </span>and sent to users</div><div class="t m0 xd h2 y3e ff1 fs0 fc0 sc0 ls0 ws0">up<span class="_ _0"></span>on<span class="_ _1"> </span>request.</div><div class="t m1 xe h2 y3f ff1 fs0 fc0 sc0 ls0 ws0">On<span class="_ _8"> </span>the<span class="_ _1"> </span>other<span class="_ _1"> </span>hand,<span class="_ _1"> </span>no<span class="_ _5"></span>w<span class="_ _5"></span>ada<span class="_ _5"></span>ys<span class="_ _8"> </span>Jav<span class="_ _2"></span>aScript<span class="_ _1"> </span>is<span class="_ _1"> </span>al-</div><div class="t m2 xd h2 y40 ff1 fs0 fc0 sc0 ls0 ws0">ready<span class="_ _8"> </span>p<span class="_ _0"></span>ow<span class="_ _e"></span>erful<span class="_ _8"> </span>enough<span class="_ _8"> </span>for<span class="_ _1"> </span>many tasks,<span class="_ _1"> </span>and<span class="_ _8"> </span>it<span class="_ _8"> </span>can<span class="_ _1"> </span>b<span class="_ _0"></span>e</div><div class="t m4 x7b h1b y41 ff5 fs0 fc0 sc0 ls0 ws0">emb<span class="_ _e"></span>e<span class="_ _e"></span>dde<span class="_ _e"></span>d</div><div class="t m0 x7c h6 y1f7 ff8 fs2 fc0 sc0 ls0 ws0">5</div><div class="t m4 x7d h2 y41 ff1 fs0 fc0 sc0 ls0 ws0">in<span class="_ _e"></span>to<span class="_ _1"> </span><span class="ff4 fs1">HTML</span>,<span class="_ _1"> </span>in<span class="_ _1"> </span>which<span class="_ _8"> </span>case<span class="_ _1"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>is<span class="_ _1"> </span>used</div><div class="t m2 xd h2 y42 ff1 fs0 fc0 sc0 ls0 ws0">as<span class="_ _1"> </span>a<span class="_ _8"> </span>c<span class="_ _0"></span>on<span class="_ _e"></span>tainer<span class="_ _10"> </span>—<span class="_ _10"> </span>the<span class="_ _1"> </span>embedded<span class="_ _1"> </span>files<span class="_ _1"> </span>are<span class="_ _1"> </span>to<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>parsed</div><div class="t m0 xd h2 y43 ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _1"> </span>rendered<span class="_ _1"> </span>on<span class="_ _1"> </span>the<span class="_ _1"> </span>clien<span class="_ _5"></span>t<span class="_ _1"> </span>side<span class="_ _1"> </span>with<span class="_ _1"> </span>Ja<span class="_ _5"></span>v<span class="_ _e"></span>aScript.</div><div class="t m2 xe h2 y44 ff1 fs0 fc0 sc0 ls0 ws0">In order to utilize existing technologies, it is also</div><div class="t m1 xd h2 y45 ff1 fs0 fc0 sc0 ls0 ws0">common<span class="_ _1"> </span>to<span class="_ _4"> </span>in<span class="_ _e"></span>tro<span class="_ _0"></span>duce<span class="_ _4"> </span>in<span class="_ _e"></span>termediate<span class="_ _4"> </span>formats,<span class="_ _4"> </span>whic<span class="_ _e"></span>h</div><div class="t m1 xd h2 y46 ff1 fs0 fc0 sc0 ls0 ws0">are<span class="_ _9"> </span>to<span class="_ _9"> </span>b<span class="_ _0"></span>e<span class="_ _9"> </span>conv<span class="_ _e"></span>erted<span class="_ _9"> </span>or<span class="_ _9"> </span>embedded<span class="_ _9"> </span>into<span class="_ _4"> </span><span class="ff4 fs1">HTML</span>.<span class="_ _2d"> </span>In</div><div class="t m1 xd h2 y47 ff1 fs0 fc0 sc0 ls0 ws0">particular,<span class="_ _1"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>ma<span class="_ _e"></span>y<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>viewed<span class="_ _8"> </span>as<span class="_ _1"> </span>an<span class="_ _1"> </span>intermediate</div><div class="t m0 xd h2 y48 ff1 fs0 fc0 sc0 ls0 ws0">format<span class="_ _1"> </span>while<span class="_ _1"> </span>compiling<span class="_ _1"> </span>T</div><div class="t m0 x64 h2 y1f8 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m0 x1e h2 y48 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _1"> </span>to<span class="_ _1"> </span><span class="ff4 fs1">HTML</span>,</div><div class="t m9 xe h2 y49 ff1 fs0 fc0 sc0 ls0 ws0">In<span class="_ _1"> </span>this<span class="_ _1"> </span>section<span class="_ _1"> </span>we<span class="_ _8"> </span>try<span class="_ _1"> </span>to<span class="_ _1"> </span>describ<span class="_ _0"></span>e<span class="_ _4"> </span>the<span class="_ _8"> </span>most<span class="_ _1"> </span>p<span class="_ _0"></span>op-</div><div class="t m11 xd h2 y4a ff1 fs0 fc0 sc0 ls0 ws0">ular<span class="_ _1"> </span>approac<span class="_ _e"></span>hes<span class="_ _1"> </span>and<span class="_ _1"> </span>discuss<span class="_ _1"> </span>them<span class="_ _1"> </span>from<span class="_ _1"> </span>different<span class="_ _8"> </span>as-</div><div class="t m2 xd h2 y4c ff1 fs0 fc0 sc0 ls0 ws0">p<span class="_ _0"></span>ects.<span class="_ _9"> </span>Although<span class="_ _14"> </span>some of<span class="_ _14"> </span>them<span class="_ _14"> </span>might<span class="_ _14"> </span>not<span class="_ _14"> </span>b<span class="_ _0"></span>e originally</div><div class="t m7 xd h2 y7f ff1 fs0 fc0 sc0 ls0 ws0">designed<span class="_ _1"> </span>for<span class="_ _1"> </span>publishing,<span class="_ _1"> </span>they<span class="_ _1"> </span>are<span class="_ _1"> </span>still<span class="_ _1"> </span>listed<span class="_ _1"> </span>here<span class="_ _1"> </span>b<span class="_ _0"></span>e-</div><div class="t m0 xd h2 y80 ff1 fs0 fc0 sc0 ls0 ws0">cause<span class="_ _1"> </span>they<span class="_ _1"> </span>can<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>used<span class="_ _1"> </span>to<span class="_ _1"> </span>facilitate<span class="_ _1"> </span>the<span class="_ _1"> </span>pro<span class="_ _0"></span>cess.</div><div class="t m0 xd h3 y1f9 ff2 fs0 fc0 sc0 ls0 ws0">3.1<span class="_ _c"> </span>Raster<span class="_ _4"> </span>image-based<span class="_ _4"> </span>approac<span class="_ _e"></span>hes</div><div class="t m2 x7b h2 y1fa ff1 fs0 fc0 sc0 ls0 ws0">Approac<span class="_ _e"></span>hes of this type<span class="_ _8"> </span>render source files in<span class="_ _e"></span>to raster</div><div class="t m2 xd h2 y1fb ff1 fs0 fc0 sc0 ls0 ws0">images<span class="_ _14"> </span>(<span class="ff5">e.g. <span class="ff4 fs1">PNG</span></span>, <span class="ff4 fs1">JPEG</span>),<span class="_ _14"> </span>usually<span class="_ _d"> </span>one<span class="_ _14"> </span>image<span class="_ _d"> </span>per page,</div><div class="t m1b x7b h2 y1fc ff1 fs0 fc0 sc0 ls0 ws0">whic<span class="_ _e"></span>h<span class="_ _4"> </span>are<span class="_ _8"> </span>then<span class="_ _1"> </span>embedded<span class="_ _4"> </span>in<span class="_ _e"></span>to<span class="_ _1"> </span><span class="ff4 fs1">HTML</span>.<span class="_ _7"> </span>Popular<span class="_ _1"> </span>to<span class="_ _0"></span>ols</div><div class="t m0 xd h2 y1fd ff1 fs0 fc0 sc0 ls0 ws0">of<span class="_ _1"> </span>this<span class="_ _1"> </span>t<span class="_ _5"></span>yp<span class="_ _0"></span>e<span class="_ _1"> </span>include:</div><div class="t m0 x7e h2 y1fe fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">p<span class="_ _0"></span>dfto<span class="_ _0"></span>cairo<span class="_ _1"> </span>from<span class="_ _1"> </span>P<span class="_ _5"></span>oppler<span class="_ _1"> </span>[27]</span></div><div class="t m0 x7e h2 y1ff fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">ImageMagic<span class="_ _5"></span>k<span class="_ _1"> </span>[20]</span></div><div class="t m0 x7e h2 y200 fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">mathT</span></div><div class="t m0 x7d h2 y201 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m0 x7f h2 y200 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _1"> </span>[9]</div><div class="t m0 x7e h2 y202 fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">“fallbac<span class="_ _5"></span>k”<span class="_ _1"> </span>mo<span class="_ _0"></span>de<span class="_ _1"> </span>of<span class="_ _1"> </span>p<span class="_ _0"></span>df2h<span class="_ _5"></span>tml<span class="ff4 fs1">EX</span></span></div><div class="t m0 xd h3 y203 ff2 fs0 fc0 sc0 ls0 ws0">Pros</div><div class="t m2 x80 h2 y203 ff1 fs0 fc0 sc0 ls0 ws0">Raster images<span class="_ _d"> </span>w<span class="_ _e"></span>ere introduced in a<span class="_ _d"> </span>v<span class="_ _e"></span>ery early</div><div class="t m2 xd h2 y204 ff1 fs0 fc0 sc0 ls0 ws0">stage<span class="_ _d"> </span>of<span class="_ _d"> </span><span class="ff4 fs1">HTML</span>, and<span class="_ _14"> </span>so are<span class="_ _14"> </span>highly compatible<span class="_ _14"> </span>with old</div><div class="t m23 x7b h2 y205 ff1 fs0 fc0 sc0 ls0 ws0">w<span class="_ _5"></span>eb<span class="_ _8"> </span>browsers.<span class="_ _9"> </span>All<span class="_ _1"> </span>visual<span class="_ _1"> </span>elements<span class="_ _8"> </span>can<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>display<span class="_ _e"></span>ed</div><div class="t m0 xd h2 y206 ff1 fs0 fc0 sc0 ls0 ws0">correctly<span class="_ _2"></span>.</div><div class="t m0 x7c h6 y207 ff8 fs2 fc0 sc0 ls0 ws0">6</div><div class="t m0 xd h3 y208 ff2 fs0 fc0 sc0 ls0 ws0">Cons</div><div class="t m1 x81 h2 y208 ff1 fs0 fc0 sc0 ls0 ws0">The<span class="_ _4"> </span>main<span class="_ _4"> </span>disadv<span class="_ _e"></span>antage<span class="_ _4"> </span>of<span class="_ _4"> </span>this<span class="_ _4"> </span>type<span class="_ _9"> </span>of<span class="_ _4"> </span>ap-</div><div class="t m1 xd h2 y209 ff1 fs0 fc0 sc0 ls0 ws0">proac<span class="_ _5"></span>h<span class="_ _1"> </span>is<span class="_ _4"> </span>that<span class="_ _8"> </span>the<span class="_ _4"> </span>image<span class="_ _1"> </span>sizes<span class="_ _1"> </span>are<span class="_ _4"> </span>usually<span class="_ _8"> </span>huge.<span class="_ _11"> </span>It</div><div class="t m1 xd h2 y20a ff1 fs0 fc0 sc0 ls0 ws0">is<span class="_ _4"> </span>costly<span class="_ _4"> </span>to<span class="_ _1"> </span>conv<span class="_ _e"></span>ert<span class="_ _4"> </span>text<span class="_ _4"> </span>into<span class="_ _1"> </span>images<span class="_ _4"> </span>and<span class="_ _4"> </span>it<span class="_ _4"> </span>is<span class="_ _4"> </span>usu-</div><div class="t m5 xd h2 y20b ff1 fs0 fc0 sc0 ls0 ws0">ally<span class="_ _1"> </span>not<span class="_ _1"> </span>easy<span class="_ _1"> </span>to<span class="_ _1"> </span>balance<span class="_ _1"> </span>quality<span class="_ _1"> </span>and<span class="_ _1"> </span>size.<span class="_ _7"> </span>Large<span class="_ _1"> </span>files</div><div class="t mc xd h2 y20c ff1 fs0 fc0 sc0 ls0 ws0">consume<span class="_ _1"> </span>large<span class="_ _1"> </span>bandwidth<span class="_ _8"> </span>o<span class="_ _0"></span>f<span class="_ _8"> </span>b<span class="_ _0"></span>oth<span class="_ _1"> </span>server<span class="_ _8"> </span>and<span class="_ _1"> </span>client,</div><div class="t m1 x7b h2 y20d ff1 fs0 fc0 sc0 ls0 ws0">whic<span class="_ _5"></span>h<span class="_ _4"> </span>also<span class="_ _4"> </span>cause<span class="_ _9"> </span>dela<span class="_ _e"></span>ys.<span class="_ _15"> </span>Another<span class="_ _9"> </span>issue<span class="_ _4"> </span>is<span class="_ _4"> </span>that<span class="_ _9"> </span>all</div><div class="t m2 xd h2 y20e ff1 fs0 fc0 sc0 ls0 ws0">seman<span class="_ _e"></span>tic information is lost, users can no longer cop<span class="_ _e"></span>y</div><div class="t m0 xd h2 y20f ff1 fs0 fc0 sc0 ls0 ws0">text<span class="_ _1"> </span>out<span class="_ _1"> </span>from<span class="_ _1"> </span>the<span class="_ _1"> </span>do<span class="_ _0"></span>cumen<span class="_ _5"></span>t,<span class="_ _1"> </span>nor<span class="_ _1"> </span>follo<span class="_ _5"></span>w<span class="_ _1"> </span>the<span class="_ _1"> </span>links.</div><div class="t m1 xd h2 y210 ff1 fs0 fc0 sc0 ls0 ws0">Raster<span class="_ _1"> </span>image-based<span class="_ _1"> </span>approaches<span class="_ _8"> </span>are<span class="_ _4"> </span>“univ<span class="_ _e"></span>ersal”,<span class="_ _1"> </span>in</div><div class="t m1 xd h2 y211 ff1 fs0 fc0 sc0 ls0 ws0">that<span class="_ _9"> </span>they<span class="_ _9"> </span>are<span class="_ _9"> </span>widely<span class="_ _9"> </span>used<span class="_ _9"> </span>to<span class="_ _9"> </span>publish<span class="_ _9"> </span>man<span class="_ _5"></span>y<span class="_ _9"> </span>differ-</div><div class="t m1 xd h2 y212 ff1 fs0 fc0 sc0 ls0 ws0">en<span class="_ _5"></span>t<span class="_ _4"> </span>formats,<span class="_ _9"> </span>not<span class="_ _4"> </span>limited<span class="_ _4"> </span>to<span class="_ _9"> </span>T</div><div class="t m0 x82 h2 y213 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 x83 h2 y212 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _4"> </span>or<span class="_ _4"> </span><span class="ff4 fs1">PDF</span>.<span class="_ _15"> </span>F<span class="_ _2"></span>amous</div><div class="t m2 xd h2 y214 ff1 fs0 fc0 sc0 ls0 ws0">examples<span class="_ _8"> </span>include<span class="_ _8"> </span>the<span class="_ _8"> </span><span class="ff5">L<span class="_ _e"></span>o<span class="_ _e"></span>ok<span class="_ _1"> </span>Inside<span class="_ _8"> </span><span class="ff1">feature<span class="_ _8"> </span>of<span class="_ _8"> </span>Springer-</span></span></div><div class="t m0 xd h2 y215 ff1 fs0 fc0 sc0 ls0 ws0">Link<span class="_ _1"> </span>[11]<span class="_ _1"> </span>and<span class="_ _1"> </span>Go<span class="_ _0"></span>ogle<span class="_ _1"> </span>Do<span class="_ _0"></span>cs<span class="_ _1"> </span>View<span class="_ _5"></span>er<span class="_ _1"> </span>[3].</div><div class="t m0 x1a h7 y1f5 ff9 fs3 fc0 sc0 ls0 ws0">5</div><div class="t m2 x1b h8 y71 ffa fs4 fc0 sc0 ls0 ws0">T<span class="_ _2"></span>o k<span class="_ _e"></span>eep<span class="_ _14"> </span>the<span class="_ _10"> </span>source format<span class="_ _10"> </span>as it<span class="_ _10"> </span>is inside<span class="_ _10"> </span>the target<span class="_ _10"> </span>format.</div><div class="t m0 x1a h7 y216 ff9 fs3 fc0 sc0 ls0 ws0">6</div><div class="t m18 x1b h8 y217 ffa fs4 fc0 sc0 ls0 ws0">F<span class="_ _2"></span>or<span class="_ _13"> </span>T</div><div class="t m0 x5e h8 y218 ffa fs4 fc0 sc0 ls0 ws0">E</div><div class="t m18 x84 h8 y217 ffa fs4 fc0 sc0 ls0 ws0">X<span class="_ _13"> </span>and</div><div class="t m0 x85 h6 y217 ff8 fs2 fc0 sc0 ls0 ws0">PDF</div><div class="t m18 x86 h8 y217 ffa fs4 fc0 sc0 ls0 ws0">,<span class="_ _13"> </span>there<span class="_ _13"> </span>are<span class="_ _8"> </span>also<span class="_ _13"> </span>adv<span class="_ _e"></span>anced<span class="_ _8"> </span>features<span class="_ _13"> </span>like</div><div class="t m2 xd h8 y74 ffa fs4 fc0 sc0 ls0 ws0">audio,<span class="_ _13"> </span>video,<span class="_ _13"> </span>animation<span class="_ _13"> </span>or<span class="_ _13"> </span>annotation,<span class="_ _13"> </span><span class="ff10">etc.</span>,<span class="_ _13"> </span>which<span class="_ _d"> </span>are<span class="_ _13"> </span>b<span class="_ _0"></span>eyond</div><div class="t m0 xd h8 y38 ffa fs4 fc0 sc0 ls0 ws0">the<span class="_ _13"> </span>scop<span class="_ _0"></span>e<span class="_ _13"> </span>of<span class="_ _13"> </span>this<span class="_ _13"> </span>article.</div><div class="t m0 x1c h2 y77 ff1 fs0 fc0 sc0 ls0 ws0">Online<span class="_ _1"> </span>publishing<span class="_ _1"> </span>via<span class="_ _1"> </span>p<span class="_ _0"></span>df2h<span class="_ _e"></span>tm<span class="_ _0"></span>l<span class="ff4 fs1">EX</span></div><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",314.092,428.095,null]'><div class="d m1d" style="border-style:none;position:absolute;left:208.949542px;bottom:577.897412px;width:11.208000px;height:7.771000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf4" data-dest-detail='[4,"XYZ",243.799,570.088,null]'><div class="d m1d" style="border-style:none;position:absolute;left:245.775059px;bottom:235.431320px;width:6.924000px;height:12.040000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf3" data-dest-detail='[3,"XYZ",91.289,110.326,null]'><div class="d m1d" style="border-style:none;position:absolute;left:436.896627px;bottom:235.431320px;width:6.462000px;height:12.040000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf3" data-dest-detail='[3,"XYZ",91.289,91.357,null]'><div class="d m1d" style="border-style:none;position:absolute;left:326.358170px;bottom:215.428183px;width:6.462000px;height:12.040000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf3" data-dest-detail='[3,"XYZ",333.381,110.326,null]'><div class="d m1d" style="border-style:none;position:absolute;left:591.592575px;bottom:1019.766797px;width:6.462000px;height:12.039000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",314.092,694.097,null]'><div class="d m1d" style="border-style:none;position:absolute;left:743.263373px;bottom:633.273725px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,259.726,null]'><div class="d m1d" style="border-style:none;position:absolute;left:663.712627px;bottom:613.270588px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,511.781,null]'><div class="d m1d" style="border-style:none;position:absolute;left:636.390902px;bottom:593.265778px;width:6.974000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf3" data-dest-detail='[3,"XYZ",333.381,100.822,null]'><div class="d m1d" style="border-style:none;position:absolute;left:590.643869px;bottom:481.783634px;width:6.462000px;height:12.040000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,463.96,null]'><div class="d m1d" style="border-style:none;position:absolute;left:567.167163px;bottom:203.642144px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,668.194,null]'><div class="d m1d" style="border-style:none;position:absolute;left:783.893752px;bottom:203.642144px;width:6.974000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" 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<div id="pf4" class="pf w0 h0" data-page-no="4"><div class="pc pc4 w0 h0"><img class="bi x2d y219 w6 h1c" alt="" 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"/><div class="t m0 x0 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">316<span class="_ _3"> </span>TUGb<span class="_ _0"></span>oat,<span class="_ _1"> </span>V<span class="_ _2"></span>olume<span class="_ _1"> </span>34<span class="_ _1"> </span>(2013),<span class="_ _1"> </span>No.<span class="_ _1"> </span>3</div><div class="t m0 x87 h1d y21a ff11 fsf fc0 sc0 ls0 ws0">T</div><div class="t m0 x88 h1d y21b ff11 fsf fc0 sc0 ls0 ws0">E</div><div class="t m0 x89 h1d y21a ff11 fsf fc0 sc0 ls0 ws0">X</div><div class="t m27 x88 h13 y21c ff4 fs1 fc0 sc0 ls0 ws0">compile</div><div class="t m0 x2e h1e y21d ff12 fs0 fc0 sc0 ls0 ws0"><span class="ff13"></span></div><div class="t m28 x8a h1f y21e ff4 fs10 fc0 sc0 ls0 ws0">compile</div><div class="t m0 x8b h1e y21f ff12 fs0 fc0 sc0 ls0 ws0">%<span class="ff13">%</span></div><div class="t m29 x8c h20 y220 ff4 fs11 fc0 sc0 ls0 ws0">compile/em<span class="_ _5"></span>b<span class="_ _0"></span>ed</div><div class="t m0 x8d h1e y221 ff12 fs0 fc0 sc0 ls0 ws0">&amp;<span class="ff13">&amp;</span></div><div class="t m0 x8e h2 y222 ff1 fs0 fc0 sc0 ls0 ws0">In<span class="_ _e"></span>termediate</div><div class="t m0 x8f h2 y223 ff1 fs0 fc0 sc0 ls0 ws0">F<span class="_ _2"></span>ormats</div><div class="t m0 x5e h2 y224 ff1 fs0 fc0 sc0 ls0 ws0">con<span class="_ _e"></span>vert/em<span class="_ _e"></span>b<span class="_ _0"></span>ed</div><div class="t m0 x79 h1e y225 ff12 fs0 fc0 sc0 ls0 ws0">/<span class="ff13">/</span></div><div class="t m2a x90 h21 y226 ff4 fs12 fc0 sc0 ls0 ws0">con<span class="_ _5"></span>vert</div><div class="t m0 x91 h1e y227 ff12 fs0 fc0 sc0 ls0 ws0">}<span class="ff13">}</span></div><div class="t m0 xf h2 y228 ff1 fs0 fc0 sc0 ls0 ws0">HTML</div><div class="t m0 x92 h2 y229 ff1 fs0 fc0 sc0 ls0 ws0">Other</div><div class="t m0 x70 h2 y22a ff1 fs0 fc0 sc0 ls0 ws0">Sources</div><div class="t m0 x93 h1e y22b ff12 fs0 fc0 sc0 ls0 ws0">/<span class="ff13">/</span></div><div class="t m0 x6 h1d y22c ff11 fsf fc0 sc0 ls0 ws0">PDF</div><div class="t m2a x94 h21 y22d ff4 fs12 fc0 sc0 ls0 ws0">con<span class="_ _5"></span>vert</div><div class="t m0 x95 h1e y22e ff12 fs0 fc0 sc0 ls0 ws0">=<span class="ff13">=</span></div><div class="t m2b x1a h20 y22f ff4 fs11 fc0 sc0 ls0 ws0">con<span class="_ _5"></span>vert/em<span class="_ _e"></span>b<span class="_ _0"></span>ed</div><div class="t m0 x79 h1e y230 ff12 fs0 fc0 sc0 ls0 ws0">8<span class="ff13">8</span></div><div class="t m0 x96 h13 y231 ff3 fs1 fc0 sc0 ls0 ws0">Figure<span class="_ _1"> </span>3<span class="ff4">:<span class="_ _9"> </span>Different<span class="_ _13"> </span>approaches<span class="_ _8"> </span>to<span class="_ _8"> </span>publishing<span class="_ _8"> </span>online.</span></div><div class="t m1 x1 h2 y232 ff1 fs0 fc0 sc0 ls0 ws0">The<span class="_ _1"> </span>disadv<span class="_ _e"></span>antages<span class="_ _1"> </span>can<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _4"> </span>compensated<span class="_ _4"> </span>for<span class="_ _1"> </span>to</div><div class="t m1 x0 h2 y233 ff1 fs0 fc0 sc0 ls0 ws0">some<span class="_ _4"> </span>extent:<span class="_ _2e"> </span>A<span class="_ _4"> </span>hidden<span class="_ _9"> </span>text<span class="_ _4"> </span>lay<span class="_ _e"></span>er<span class="_ _9"> </span>can<span class="_ _9"> </span>be<span class="_ _9"> </span>ov<span class="_ _e"></span>erlaid</div><div class="t m2 x0 h2 y234 ff1 fs0 fc0 sc0 ls0 ws0">ab<span class="_ _0"></span>o<span class="_ _e"></span>ve<span class="_ _8"> </span>the<span class="_ _8"> </span>images<span class="_ _8"> </span>in<span class="_ _8"> </span>order<span class="_ _8"> </span>to<span class="_ _8"> </span>simulate user<span class="_ _8"> </span>text<span class="_ _8"> </span>selec-</div><div class="t m2 x0 h2 y235 ff1 fs0 fc0 sc0 ls0 ws0">tion, how<span class="_ _e"></span>ever<span class="_ _d"> </span>generating this text la<span class="_ _e"></span>yer<span class="_ _d"> </span>itself actually</div><div class="t m0 x0 h2 y236 ff1 fs0 fc0 sc0 ls0 ws0">in<span class="_ _e"></span>volv<span class="_ _e"></span>es<span class="_ _1"> </span>other<span class="_ _1"> </span>conv<span class="_ _e"></span>ersion<span class="_ _1"> </span>technologies;<span class="_ _8"> </span>for<span class="_ _1"> </span>a<span class="_ _1"> </span>resp<span class="_ _0"></span>on-</div><div class="t m1 x0 h2 y237 ff1 fs0 fc0 sc0 ls0 ws0">siv<span class="_ _5"></span>e<span class="_ _9"> </span>user<span class="_ _9"> </span>exp<span class="_ _0"></span>erience,<span class="_ _7"> </span>the<span class="_ _9"> </span>input<span class="_ _9"> </span>do<span class="_ _0"></span>cumen<span class="_ _5"></span>t<span class="_ _9"> </span>ma<span class="_ _5"></span>y<span class="_ _9"> </span>b<span class="_ _0"></span>e</div><div class="t m2 x0 h2 y238 ff1 fs0 fc0 sc0 ls0 ws0">con<span class="_ _e"></span>verted<span class="_ _8"> </span>into<span class="_ _8"> </span>images<span class="_ _1"> </span>with<span class="_ _1"> </span>different<span class="_ _8"> </span>resolutions,<span class="_ _1"> </span>and</div><div class="t m8 x0 h2 y239 ff1 fs0 fc0 sc0 ls0 ws0">images<span class="_ _8"> </span>with<span class="_ _1"> </span>high<span class="_ _1"> </span>resolutions<span class="_ _1"> </span>can<span class="_ _1"> </span>then<span class="_ _8"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>split<span class="_ _1"> </span>into</div><div class="t m1 x0 h2 y23a ff1 fs0 fc0 sc0 ls0 ws0">small<span class="_ _4"> </span>blo<span class="_ _0"></span>cks.<span class="_ _15"> </span>When<span class="_ _4"> </span>the<span class="_ _9"> </span>document<span class="_ _4"> </span>is<span class="_ _9"> </span>rendered<span class="_ _4"> </span>on</div><div class="t m1 x0 h2 y23b ff1 fs0 fc0 sc0 ls0 ws0">the<span class="_ _1"> </span>client<span class="_ _8"> </span>side,<span class="_ _1"> </span>only<span class="_ _4"> </span>the<span class="_ _8"> </span>blo<span class="_ _0"></span>ck<span class="_ _8"> </span>b<span class="_ _0"></span>eing<span class="_ _1"> </span>viewed<span class="_ _1"> </span>by<span class="_ _8"> </span>the</div><div class="t m20 x0 h2 y23c ff1 fs0 fc0 sc0 ls0 ws0">user<span class="_ _1"> </span>is<span class="_ _1"> </span>needed<span class="_ _1"> </span>to<span class="_ _1"> </span>transfer.<span class="_ _7"> </span>How<span class="_ _e"></span>ever<span class="_ _8"> </span>muc<span class="_ _e"></span>h<span class="_ _1"> </span>more<span class="_ _1"> </span>disk</div><div class="t m1 x0 h2 y23d ff1 fs0 fc0 sc0 ls0 ws0">storage<span class="_ _1"> </span>and<span class="_ _4"> </span>net<span class="_ _e"></span>work<span class="_ _1"> </span>bandwidth<span class="_ _4"> </span>is<span class="_ _1"> </span>required<span class="_ _1"> </span>in<span class="_ _4"> </span>this</div><div class="t m2 x0 h2 y23e ff1 fs0 fc0 sc0 ls0 ws0">w<span class="_ _e"></span>ay<span class="_ _2"></span>,<span class="_ _8"> </span>which might not<span class="_ _8"> </span>b<span class="_ _0"></span>e<span class="_ _8"> </span>affordable<span class="_ _1"> </span>for<span class="_ _8"> </span>all<span class="_ _8"> </span>publishers,</div><div class="t m0 x0 h2 y23f ff1 fs0 fc0 sc0 ls0 ws0">esp<span class="_ _0"></span>ecially<span class="_ _1"> </span>individuals.</div><div class="t m0 x0 h3 y240 ff2 fs0 fc0 sc0 ls0 ws0">3.2<span class="_ _c"> </span>SV<span class="_ _e"></span>G-based<span class="_ _4"> </span>approaches</div><div class="t mf x0 h2 y241 ff1 fs0 fc0 sc0 ls0 ws0">Scalable<span class="_ _1"> </span>V<span class="_ _2"></span>ector<span class="_ _1"> </span>Graphics,<span class="_ _1"> </span>dev<span class="_ _e"></span>elop<span class="_ _0"></span>ed<span class="_ _1"> </span>by<span class="_ _8"> </span><span class="ff4 fs1">W</span>3<span class="ff4 fs1">C</span>,<span class="_ _1"> </span>is<span class="_ _1"> </span>an</div><div class="t m1 x0 h2 y242 ff4 fs1 fc0 sc0 ls0 ws0">XML<span class="ff1 fs0">-based<span class="_ _9"> </span>format<span class="_ _9"> </span>for<span class="_ _4"> </span>presenting<span class="_ _4"> </span>2<span class="_ _0"></span></span>D<span class="_ _9"> </span><span class="ff1 fs0">graphics.<span class="_ _12"> </span>It</span></div><div class="t ma x0 h2 y243 ff1 fs0 fc0 sc0 ls0 ws0">supp<span class="_ _0"></span>orts<span class="_ _1"> </span>a<span class="_ _1"> </span>similar<span class="_ _1"> </span>set<span class="_ _1"> </span>of<span class="_ _1"> </span>features<span class="_ _1"> </span>as<span class="_ _1"> </span><span class="ff4 fs1">PDF</span>,<span class="_ _1"> </span>including</div><div class="t m1 x0 h2 y244 ff1 fs0 fc0 sc0 ls0 ws0">color,<span class="_ _1"> </span>gradients,<span class="_ _1"> </span>patterns,<span class="_ _4"> </span>pain<span class="_ _e"></span>tings<span class="_ _4"> </span>and<span class="_ _1"> </span>raster<span class="_ _4"> </span>im-</div><div class="t m0 x0 h2 y245 ff1 fs0 fc0 sc0 ls0 ws0">ages.<span class="_ _7"> </span>It<span class="_ _1"> </span>also<span class="_ _1"> </span>supp<span class="_ _0"></span>orts<span class="_ _1"> </span>font<span class="_ _8"> </span>definition<span class="_ _1"> </span>within<span class="_ _1"> </span><span class="ff4 fs1">SVG<span class="_ _8"> </span></span>as</div><div class="t m0 x0 h2 y246 ff1 fs0 fc0 sc0 ls0 ws0">w<span class="_ _e"></span>ell<span class="_ _4"> </span>as<span class="_ _8"> </span>external<span class="_ _1"> </span>fonts<span class="_ _8"> </span>defined<span class="_ _1"> </span>in<span class="_ _1"> </span><span class="ff4 fs1">CSS</span>.</div><div class="t m1 x1 h2 y247 ff1 fs0 fc0 sc0 ls0 ws0">Due<span class="_ _9"> </span>to<span class="_ _9"> </span>the<span class="_ _9"> </span>large<span class="_ _7"> </span>feature<span class="_ _9"> </span>set,<span class="_ _7"> </span>most<span class="_ _9"> </span>visual<span class="_ _9"> </span>ele-</div><div class="t m2c x0 h2 y248 ff1 fs0 fc0 sc0 ls0 ws0">men<span class="_ _e"></span>ts<span class="_ _4"> </span>can<span class="_ _8"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>rendered<span class="_ _4"> </span>with<span class="_ _8"> </span><span class="ff4 fs1">SVG<span class="_ _8"> </span></span>counterparts.<span class="_ _9"> </span>Pop-</div><div class="t m0 x0 h2 y249 ff1 fs0 fc0 sc0 ls0 ws0">ular<span class="_ _1"> </span>to<span class="_ _0"></span>ols<span class="_ _1"> </span>in<span class="_ _1"> </span>this<span class="_ _1"> </span>category<span class="_ _1"> </span>include:</div><div class="t m0 x97 h2 y24a fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">Inkscap<span class="_ _0"></span>e<span class="_ _1"> </span>[21]</span></div><div class="t m0 x97 h2 y24b fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">p<span class="_ _0"></span>dfto<span class="_ _0"></span>cairo<span class="_ _1"> </span>from<span class="_ _1"> </span>P<span class="_ _5"></span>oppler<span class="_ _1"> </span>[27]</span></div><div class="t m0 x97 h2 y24c fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">p<span class="_ _0"></span>df2svg<span class="_ _1"> </span>[26]</span></div><div class="t m0 x97 h2 y24d fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">dvisvgm<span class="_ _1"> </span>[17]</span></div><div class="t m0 x97 h2 y24e fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">“fallbac<span class="_ _5"></span>k”<span class="_ _1"> </span>mo<span class="_ _0"></span>de<span class="_ _1"> </span>of<span class="_ _1"> </span>p<span class="_ _0"></span>df2h<span class="_ _5"></span>tml<span class="ff4 fs1">EX</span></span></div><div class="t m0 x0 h2 y32 ff2 fs0 fc0 sc0 ls0 ws0">Pros<span class="_ _2f"> </span><span class="ff1">Due<span class="_ _1"> </span>to<span class="_ _1"> </span>the<span class="_ _1"> </span>similar<span class="_ _1"> </span>nature<span class="_ _1"> </span>b<span class="_ _0"></span>etw<span class="_ _e"></span>een<span class="_ _1"> </span><span class="ff4 fs1">SV<span class="_ _5"></span>G<span class="_ _1"> </span><span class="ff1 fs0">and</span></span></span></div><div class="t m2 x0 h2 y33 ff4 fs1 fc0 sc0 ls0 ws0">PDF<span class="ff1 fs0">,<span class="_ _8"> </span>it<span class="_ _1"> </span>is<span class="_ _1"> </span>relatively<span class="_ _8"> </span>easy<span class="_ _8"> </span>to<span class="_ _1"> </span>find<span class="_ _1"> </span>an<span class="_ _8"> </span></span>SVG<span class="_ _8"> </span><span class="ff1 fs0">counterpart</span></div><div class="t m22 x0 h2 y34 ff1 fs0 fc0 sc0 ls0 ws0">for<span class="_ _8"> </span>each<span class="_ _8"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>element.<span class="_ _9"> </span><span class="ff4 fs1">SVG<span class="_ _8"> </span></span>is<span class="_ _1"> </span>one<span class="_ _1"> </span>of<span class="_ _1"> </span>the<span class="_ _1"> </span>few<span class="_ _8"> </span>meth-</div><div class="t m1 x0 h2 y35 ff1 fs0 fc0 sc0 ls0 ws0">o<span class="_ _0"></span>ds<span class="_ _1"> </span>that<span class="_ _1"> </span>supp<span class="_ _0"></span>ort<span class="_ _4"> </span>adv<span class="_ _2"></span>anced<span class="_ _1"> </span>lay<span class="_ _e"></span>out<span class="_ _4"> </span>features<span class="_ _8"> </span>such<span class="_ _1"> </span>as</div><div class="t m0 x0 h2 y36 ff1 fs0 fc0 sc0 ls0 ws0">c<span class="_ _e"></span>haracters<span class="_ _4"> </span>along<span class="_ _8"> </span>a<span class="_ _1"> </span>curved<span class="_ _8"> </span>path<span class="_ _1"> </span>and<span class="_ _1"> </span>image<span class="_ _1"> </span>clipping.</div><div class="t m1 x1 h2 y37 ff4 fs1 fc0 sc0 ls0 ws0">SV<span class="_ _5"></span>G<span class="_ _4"> </span><span class="ff1 fs0">is<span class="_ _9"> </span>based<span class="_ _4"> </span>on<span class="_ _4"> </span></span>XML<span class="ff1 fs0">,<span class="_ _9"> </span>hence<span class="_ _9"> </span>it<span class="_ _4"> </span>can<span class="_ _9"> </span>be<span class="_ _9"> </span>easily</span></div><div class="t m1 x0 h2 y38 ff1 fs0 fc0 sc0 ls0 ws0">parsed<span class="_ _4"> </span>or<span class="_ _9"> </span>edited<span class="_ _9"> </span>man<span class="_ _5"></span>ually<span class="_ _2"></span>.<span class="_ _12"> </span><span class="ff4 fs1">SV<span class="_ _e"></span>G<span class="_ _9"> </span><span class="ff1 fs0">can<span class="_ _9"> </span>be<span class="_ _9"> </span>well<span class="_ _4"> </span>inte-</span></span></div><div class="t m2 xd h2 y232 ff1 fs0 fc0 sc0 ls0 ws0">grated with<span class="_ _d"> </span><span class="ff4 fs1">HTML</span>/<span class="ff4 fs1">CSS</span>, and it<span class="_ _d"> </span>can be easily accessed</div><div class="t m0 xd h2 y233 ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _1"> </span>manipulated<span class="_ _1"> </span>b<span class="_ _5"></span>y<span class="_ _1"> </span>Ja<span class="_ _e"></span>v<span class="_ _e"></span>aScript.</div><div class="t m0 xd h3 y24f ff2 fs0 fc0 sc0 ls0 ws0">Cons</div><div class="t m2d x81 h2 y24f ff1 fs0 fc0 sc0 ls0 ws0">Old<span class="_ _1"> </span>w<span class="_ _5"></span>eb<span class="_ _1"> </span>bro<span class="_ _5"></span>wsers<span class="_ _1"> </span>do<span class="_ _1"> </span>not<span class="_ _1"> </span>supp<span class="_ _0"></span>ort<span class="_ _1"> </span><span class="ff4 fs1">SVG</span>,<span class="_ _8"> </span>and</div><div class="t m2 xd h2 y250 ff1 fs0 fc0 sc0 ls0 ws0">the<span class="_ _8"> </span>degree<span class="_ _8"> </span>of<span class="_ _1"> </span>supp<span class="_ _0"></span>ort<span class="_ _8"> </span>for<span class="_ _8"> </span><span class="ff4 fs1">SVG<span class="_ _8"> </span></span>v<span class="_ _e"></span>aries<span class="_ _8"> </span>for<span class="_ _8"> </span>mo<span class="_ _0"></span>dern<span class="_ _1"> </span>web</div><div class="t m0 xd h2 y251 ff1 fs0 fc0 sc0 ls0 ws0">bro<span class="_ _e"></span>wsers.</div><div class="t m2 x7b h2 y252 ff1 fs0 fc0 sc0 ls0 ws0">While <span class="ff4 fs1">SVG</span>-based approaches are p<span class="_ _0"></span>ow<span class="_ _e"></span>erful<span class="_ _8"> </span>when<span class="_ _8"> </span>inte-</div><div class="t m4 xd h2 y253 ff1 fs0 fc0 sc0 ls0 ws0">grated<span class="_ _1"> </span>with<span class="_ _1"> </span><span class="ff4 fs1">HTML</span>,<span class="_ _1"> </span><span class="ff4 fs1">CSS<span class="_ _8"> </span></span>and<span class="_ _1"> </span>Jav<span class="_ _2"></span>aScript,<span class="_ _1"> </span>most<span class="_ _1"> </span>to<span class="_ _0"></span>ols</div><div class="t m1 xd h2 y254 ff1 fs0 fc0 sc0 ls0 ws0">in<span class="_ _4"> </span>this<span class="_ _9"> </span>category<span class="_ _9"> </span>do<span class="_ _4"> </span>not<span class="_ _9"> </span>supp<span class="_ _0"></span>ort<span class="_ _4"> </span>such<span class="_ _4"> </span>integrations,</div><div class="t m2 xd h2 y255 ff1 fs0 fc0 sc0 ls0 ws0">probably<span class="_ _8"> </span>b<span class="_ _0"></span>ecause<span class="_ _1"> </span>they<span class="_ _1"> </span>w<span class="_ _5"></span>ere<span class="_ _8"> </span>designed<span class="_ _1"> </span>as<span class="_ _1"> </span>an<span class="_ _8"> </span><span class="ff4 fs1">SVG<span class="_ _8"> </span></span>con-</div><div class="t m0 x7b h2 y256 ff1 fs0 fc0 sc0 ls0 ws0">v<span class="_ _e"></span>erter<span class="_ _4"> </span>instead<span class="_ _8"> </span>of<span class="_ _1"> </span>an<span class="_ _1"> </span>online<span class="_ _1"> </span>publishing<span class="_ _1"> </span>to<span class="_ _0"></span>ol.</div><div class="t m0 xd h3 y257 ff2 fs0 fc0 sc0 ls0 ws0">3.3<span class="_ _c"> </span>Seman<span class="_ _e"></span>tic<span class="_ _4"> </span>HTML-based<span class="_ _4"> </span>approaches</div><div class="t m1 x7b h2 y258 ff1 fs0 fc0 sc0 ls0 ws0">Approac<span class="_ _5"></span>hes<span class="_ _9"> </span>of<span class="_ _9"> </span>this<span class="_ _9"> </span>type<span class="_ _7"> </span>try<span class="_ _9"> </span>to<span class="_ _9"> </span>find<span class="_ _7"> </span>the<span class="_ _9"> </span>matching</div><div class="t m1 xd h2 y259 ff4 fs1 fc0 sc0 ls0 ws0">HTML<span class="_ _4"> </span><span class="ff1 fs0">elemen<span class="_ _e"></span>t<span class="_ _4"> </span>for<span class="_ _1"> </span>each<span class="_ _1"> </span>T</span></div><div class="t m0 x1e h2 y25a ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 x1f h2 y259 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _4"> </span>elemen<span class="_ _e"></span>t,<span class="_ _4"> </span>for<span class="_ _1"> </span>example</div><div class="t m0 x98 h4 y25b ff6 fs0 fc0 sc0 ls0 ws0">\section</div><div class="t m1 x84 h2 y25b ff1 fs0 fc0 sc0 ls0 ws0">and</div><div class="t m0 x99 h4 y25b ff6 fs0 fc0 sc0 ls0 ws0">\textbf</div><div class="t m1 x9a h2 y25b ff1 fs0 fc0 sc0 ls0 ws0">in<span class="_ _1"> </span>T</div><div class="t m0 x9b h2 y25c ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 x9c h2 y25b ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _1"> </span>might<span class="_ _8"> </span>b<span class="_ _0"></span>ecome</div><div class="t m0 x9d h4 y25b ff6 fs0 fc0 sc0 ls0 ws0">&lt;h1&gt;</div><div class="t m2 xd h2 y25d ff1 fs0 fc0 sc0 ls0 ws0">and</div><div class="t m0 x1b h4 y25d ff6 fs0 fc0 sc0 ls0 ws0">&lt;b&gt;</div><div class="t m2 x5e h2 y25d ff1 fs0 fc0 sc0 ls0 ws0">in<span class="_ _1"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>resp<span class="_ _0"></span>ectively<span class="_ _2"></span>.<span class="_ _9"> </span>Popular<span class="_ _1"> </span>to<span class="_ _0"></span>ols<span class="_ _1"> </span>in<span class="_ _1"> </span>this</div><div class="t m0 xd h2 y25e ff1 fs0 fc0 sc0 ls0 ws0">category<span class="_ _1"> </span>include</div><div class="t m0 x7e h2 y25f fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff4 fs1">HEVEA<span class="_ _1"> </span></span><span class="ff1">[19]</span></div><div class="t m0 x7e h2 y260 fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">L</span></div><div class="t m0 x9e h6 y261 ff8 fs2 fc0 sc0 ls0 ws0">A</div><div class="t m0 x9f h2 y260 ff1 fs0 fc0 sc0 ls0 ws0">T</div><div class="t m0 x11 h2 y262 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m0 x5e h2 y260 ff1 fs0 fc0 sc0 ls0 ws0">X2<span class="ff4 fs1">HTML<span class="_ _1"> </span></span>[1,<span class="_ _1"> </span>37]</div><div class="t m0 x7e h2 y263 fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">L</span></div><div class="t m0 x9e h6 y264 ff8 fs2 fc0 sc0 ls0 ws0">A</div><div class="t m0 x9f h2 y263 ff1 fs0 fc0 sc0 ls0 ws0">T</div><div class="t m0 x11 h2 y265 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m0 x5e h2 y263 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="ff4 fs1">ML<span class="_ _1"> </span></span>[24]</div><div class="t m0 x7e h2 y266 fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">plasT</span></div><div class="t m0 xa0 h2 y267 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m0 x7d h2 y266 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _1"> </span>[5,<span class="_ _1"> </span>29]</div><div class="t m0 x7e h2 y268 fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">T</span></div><div class="t m0 xa1 h2 y269 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m0 x15 h2 y268 ff1 fs0 fc0 sc0 ls0 ws0">X4h<span class="_ _e"></span>t<span class="_ _1"> </span>[6,<span class="_ _4"> </span>33]</div><div class="t m0 x7e h2 y26a fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">T</span></div><div class="t m0 xa1 h2 y26b ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m0 x15 h2 y26a ff1 fs0 fc0 sc0 ls0 ws0">X2page<span class="_ _1"> </span>[14]</div><div class="t m0 x7e h2 y26c fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff4 fs1">TtH<span class="_ _1"> </span></span><span class="ff1">[12]</span></div><div class="t m1 xd h2 y26d ff1 fs0 fc0 sc0 ls0 ws0">all<span class="_ _7"> </span>of<span class="_ _7"> </span>which<span class="_ _7"> </span>are<span class="_ _7"> </span>designed<span class="_ _7"> </span>to<span class="_ _7"> </span>pro<span class="_ _0"></span>cess<span class="_ _11"> </span>general<span class="_ _7"> </span>T</div><div class="t m0 xa2 h2 y26e ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 xa3 h2 y26d ff1 fs0 fc0 sc0 ls0 ws0">X</div><div class="t m2 xd h2 y26f ff1 fs0 fc0 sc0 ls0 ws0">files.<span class="_ _9"> </span>There<span class="_ _8"> </span>are also<span class="_ _8"> </span>programs designed<span class="_ _8"> </span>for particular</div><div class="t m0 xd h2 y270 ff1 fs0 fc0 sc0 ls0 ws0">do<span class="_ _0"></span>cumen<span class="_ _e"></span>ts,<span class="_ _1"> </span>for<span class="_ _4"> </span>example</div><div class="t m0 x7e h2 y271 fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">The<span class="_ _1"> </span>F<span class="_ _2"></span>eynman<span class="_ _1"> </span>Lectures<span class="_ _1"> </span>on<span class="_ _1"> </span>Ph<span class="_ _5"></span>ysics<span class="_ _1"> </span>[28]</span></div><div class="t m0 x7e h2 y272 fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">The<span class="_ _1"> </span>Stac<span class="_ _5"></span>ks<span class="_ _1"> </span>Pro<span class="_ _18"></span>ject<span class="_ _1"> </span>[38]</span></div><div class="t m0 x7e h2 y273 fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">The<span class="_ _1"> </span><span class="ff4 fs1">TUG<span class="_ _1"> </span></span>In<span class="_ _5"></span>terviews<span class="_ _1"> </span>Pro<span class="_ _18"></span>ject<span class="_ _1"> </span>[30]</span></div><div class="t m0 xd h3 y32 ff2 fs0 fc0 sc0 ls0 ws0">Pros</div><div class="t mf x80 h2 y32 ff1 fs0 fc0 sc0 ls0 ws0">Seman<span class="_ _e"></span>tic<span class="_ _1"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>files<span class="_ _1"> </span>are<span class="_ _1"> </span>normally<span class="_ _1"> </span>exp<span class="_ _0"></span>ected</div><div class="t m14 xd h2 y33 ff1 fs0 fc0 sc0 ls0 ws0">b<span class="_ _5"></span>y<span class="_ _8"> </span>most<span class="_ _1"> </span>users.<span class="_ _7"> </span>Semantic<span class="_ _8"> </span>information<span class="_ _1"> </span>is<span class="_ _1"> </span>retained<span class="_ _1"> </span>in</div><div class="t m16 xd h2 y34 ff1 fs0 fc0 sc0 ls0 ws0">an<span class="_ _8"> </span><span class="ff4 fs1">XML</span>-like<span class="_ _8"> </span>format,<span class="_ _1"> </span>such<span class="_ _8"> </span>that<span class="_ _1"> </span>they<span class="_ _1"> </span>can<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _8"> </span>read<span class="_ _1"> </span>or</div><div class="t m1 xd h2 y35 ff1 fs0 fc0 sc0 ls0 ws0">edited<span class="_ _9"> </span>by<span class="_ _9"> </span>a<span class="_ _9"> </span>human<span class="_ _9"> </span>or<span class="_ _9"> </span>further<span class="_ _7"> </span>pro<span class="_ _0"></span>cessed<span class="_ _7"> </span>b<span class="_ _e"></span>y<span class="_ _7"> </span>other</div><div class="t m0 xd h2 y36 ff1 fs0 fc0 sc0 ls0 ws0">programs.</div><div class="t m1 xe h2 y37 ff1 fs0 fc0 sc0 ls0 ws0">Basic<span class="_ _1"> </span>elements<span class="_ _8"> </span>such<span class="_ _8"> </span>as<span class="_ _1"> </span>colors,<span class="_ _1"> </span>font<span class="_ _1"> </span>family<span class="_ _1"> </span>and</div><div class="t m2 xd h2 y38 ff1 fs0 fc0 sc0 ls0 ws0">sizes,<span class="_ _1"> </span>paragraphs,<span class="_ _8"> </span>links,<span class="_ _1"> </span>images<span class="_ _1"> </span>can<span class="_ _1"> </span>all<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>supp<span class="_ _0"></span>orted.</div><div class="t m0 x0 h2 y77 ff1 fs0 fc0 sc0 ls0 ws0">Lu<span class="_ _1"> </span>W<span class="_ _2"></span>ang<span class="_ _1"> </span>and<span class="_ _1"> </span>W<span class="_ _2"></span>anmin<span class="_ _1"> </span>Liu</div><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,235.816,null]'><div class="d m1d" style="border-style:none;position:absolute;left:225.858928px;bottom:353.633046px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",314.092,694.097,null]'><div class="d m1d" style="border-style:none;position:absolute;left:338.192732px;bottom:333.629908px;width:11.956000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",314.092,718.007,null]'><div class="d m1d" style="border-style:none;position:absolute;left:218.449987px;bottom:313.626771px;width:11.956000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,331.706,null]'><div class="d m1d" style="border-style:none;position:absolute;left:222.617935px;bottom:293.623634px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,285.629,null]'><div class="d m1d" style="border-style:none;position:absolute;left:623.070536px;bottom:517.242144px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,705.056,null]'><div class="d m1d" style="border-style:none;position:absolute;left:664.979242px;bottom:497.239007px;width:6.974000px;height:8.412000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",314.092,347.397,null]'><div class="d m1d" style="border-style:none;position:absolute;left:683.501595px;bottom:497.239007px;width:11.955000px;height:8.412000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,153.126,null]'><div class="d m1d" style="border-style:none;position:absolute;left:633.946353px;bottom:477.234196px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,607.422,null]'><div class="d m1d" style="border-style:none;position:absolute;left:627.223425px;bottom:457.231059px;width:6.974000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",314.092,657.235,null]'><div class="d m1d" style="border-style:none;position:absolute;left:645.745778px;bottom:457.231059px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,585.504,null]'><div class="d m1d" style="border-style:none;position:absolute;left:622.038170px;bottom:437.227922px;width:6.973000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",314.092,495.841,null]'><div class="d m1d" style="border-style:none;position:absolute;left:640.558850px;bottom:437.227922px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,405.181,null]'><div class="d m1d" style="border-style:none;position:absolute;left:640.095373px;bottom:417.224784px;width:11.956000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,450.76,null]'><div class="d m1d" style="border-style:none;position:absolute;left:596.093490px;bottom:397.221647px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",314.092,680.897,null]'><div class="d m1d" style="border-style:none;position:absolute;left:817.996967px;bottom:306.547451px;width:11.956000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",314.092,299.577,null]'><div class="d m1d" style="border-style:none;position:absolute;left:707.145621px;bottom:286.544314px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",314.092,622.366,null]'><div class="d m1d" style="border-style:none;position:absolute;left:775.790431px;bottom:266.541176px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.673203,0.000000,0.000000,1.673203,0.000000,0.000000]}'></div></div>
<div id="pf5" class="pf w0 h0" data-page-no="5"><div class="pc pc5 w0 h0"><div class="t m0 x0 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">TUGb<span class="_ _0"></span>oat,<span class="_ _1"> </span>V<span class="_ _2"></span>olume<span class="_ _1"> </span>34<span class="_ _1"> </span>(2013),<span class="_ _1"> </span>No.<span class="_ _1"> </span>3<span class="_ _3"> </span>317</div><div class="t m1 x0 h2 y39 ff4 fs1 fc0 sc0 ls0 ws0">CSS<span class="_ _1"> </span><span class="ff1 fs0">can<span class="_ _4"> </span>be<span class="_ _4"> </span>used<span class="_ _1"> </span>to<span class="_ _4"> </span>specify<span class="_ _4"> </span>the<span class="_ _1"> </span>la<span class="_ _e"></span>yout<span class="_ _1"> </span>and<span class="_ _4"> </span>appear-</span></div><div class="t m1f x0 h2 y3a ff1 fs0 fc0 sc0 ls0 ws0">ance.<span class="_ _9"> </span>Math<span class="_ _1"> </span>formulas<span class="_ _8"> </span>may<span class="_ _8"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>semantically<span class="_ _8"> </span>retained</div><div class="t m3 x0 h2 y3b ff1 fs0 fc0 sc0 ls0 ws0">via<span class="_ _1"> </span>Unico<span class="_ _0"></span>de<span class="_ _1"> </span>c<span class="_ _5"></span>haracters,<span class="_ _1"> </span>Math<span class="ff4 fs1">ML<span class="_ _1"> </span></span>or<span class="_ _1"> </span>embedded<span class="_ _1"> </span>T</div><div class="t m0 x74 h2 y274 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m3 x75 h2 y3b ff1 fs0 fc0 sc0 ls0 ws0">X</div><div class="t m0 x0 h2 y3c ff1 fs0 fc0 sc0 ls0 ws0">snipp<span class="_ _0"></span>ets<span class="_ _1"> </span>(see<span class="_ _1"> </span>Section<span class="_ _1"> </span>3.5).</div><div class="t m8 x1 h2 y3d ff1 fs0 fc0 sc0 ls0 ws0">Approac<span class="_ _5"></span>hes<span class="_ _8"> </span>of<span class="_ _1"> </span>this<span class="_ _1"> </span>type<span class="_ _1"> </span>can<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>used<span class="_ _1"> </span>when<span class="_ _8"> </span>the</div><div class="t m9 x0 h2 y3e ff1 fs0 fc0 sc0 ls0 ws0">publisher<span class="_ _1"> </span>do<span class="_ _0"></span>es<span class="_ _1"> </span>not<span class="_ _1"> </span>rely<span class="_ _1"> </span>on<span class="_ _1"> </span>the<span class="_ _1"> </span>lay<span class="_ _e"></span>out<span class="_ _1"> </span>pro<span class="_ _0"></span>duced<span class="_ _4"> </span>b<span class="_ _e"></span>y<span class="_ _1"> </span>a</div><div class="t m15 x0 h2 y3f ff1 fs0 fc0 sc0 ls0 ws0">T</div><div class="t m0 x47 h2 y275 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m15 xa4 h2 y3f ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _8"> </span>compiler.<span class="_ _7"> </span>They<span class="_ _1"> </span>are<span class="_ _1"> </span>often<span class="_ _1"> </span>used<span class="_ _1"> </span>for<span class="_ _8"> </span>simple<span class="_ _1"> </span>text-</div><div class="t m1 x0 h2 y40 ff1 fs0 fc0 sc0 ls0 ws0">based<span class="_ _4"> </span>files<span class="_ _1"> </span>without<span class="_ _4"> </span>complicated<span class="_ _1"> </span>lay<span class="_ _e"></span>outs.<span class="_ _30"> </span>The<span class="_ _4"> </span>final</div><div class="t m1 x0 h2 y41 ff1 fs0 fc0 sc0 ls0 ws0">la<span class="_ _5"></span>y<span class="_ _e"></span>o<span class="_ _0"></span>ut<span class="_ _1"> </span>is<span class="_ _4"> </span>determined<span class="_ _8"> </span>by<span class="_ _1"> </span>the<span class="_ _1"> </span>web<span class="_ _1"> </span>browser<span class="_ _8"> </span>based<span class="_ _4"> </span>on</div><div class="t m0 x0 h2 y42 ff1 fs0 fc0 sc0 ls0 ws0">the<span class="_ _1"> </span>seman<span class="_ _5"></span>tic<span class="_ _1"> </span>structure<span class="_ _1"> </span>and<span class="_ _1"> </span><span class="ff4 fs1">CSS<span class="_ _1"> </span></span>rules.</div><div class="t m0 x0 h3 y276 ff2 fs0 fc0 sc0 ls0 ws0">Cons</div><div class="t m2e x39 h2 y276 ff1 fs0 fc0 sc0 ls0 ws0">Approac<span class="_ _e"></span>hes<span class="_ _1"> </span>of<span class="_ _1"> </span>this<span class="_ _1"> </span>type<span class="_ _1"> </span>usually<span class="_ _1"> </span>dont<span class="_ _1"> </span>w<span class="_ _5"></span>ork</div><div class="t m2 x0 h2 y277 ff1 fs0 fc0 sc0 ls0 ws0">w<span class="_ _e"></span>ell for<span class="_ _14"> </span><span class="ff4 fs1">PDF </span>files.<span class="_ _4"> </span>In general,<span class="_ _d"> </span><span class="ff4 fs1">PDF </span>files<span class="_ _14"> </span>do<span class="_ _14"> </span>not con<span class="_ _e"></span>tain</div><div class="t m2 x0 h2 y278 ff1 fs0 fc0 sc0 ls0 ws0">seman<span class="_ _e"></span>tic information,<span class="_ _8"> </span>and so <span class="ff5">r<span class="_ _e"></span>e<span class="_ _e"></span>c<span class="_ _e"></span>o<span class="_ _e"></span>gnition<span class="_ _13"> </span><span class="ff1">is inevitable</span></span></div><div class="t m19 x0 h2 y279 ff1 fs0 fc0 sc0 ls0 ws0">to<span class="_ _1"> </span>detect<span class="_ _1"> </span>semantic<span class="_ _8"> </span>meanings,<span class="_ _1"> </span>which<span class="_ _8"> </span>is<span class="_ _1"> </span>considered<span class="_ _1"> </span>to</div><div class="t m2 x0 h2 y27a ff1 fs0 fc0 sc0 ls0 ws0">b<span class="_ _0"></span>e<span class="_ _8"> </span>hard.<span class="_ _9"> </span>This<span class="_ _8"> </span>is<span class="_ _8"> </span>also<span class="_ _8"> </span>true<span class="_ _8"> </span>for<span class="_ _8"> </span>other<span class="_ _8"> </span>intermediate files.</div><div class="t m2 x1 h2 y27b ff1 fs0 fc0 sc0 ls0 ws0">On the other<span class="_ _8"> </span>hand, T</div><div class="t m0 xa5 h2 y27c ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m2 xa6 h2 y27b ff1 fs0 fc0 sc0 ls0 ws0">X users do<span class="_ _8"> </span>not necessarily</div><div class="t m1 x0 h2 y27d ff1 fs0 fc0 sc0 ls0 ws0">exp<span class="_ _0"></span>ect<span class="_ _9"> </span>the<span class="_ _9"> </span>same<span class="_ _9"> </span>app<span class="_ _0"></span>earance<span class="_ _9"> </span>as<span class="_ _7"> </span>compiled<span class="_ _9"> </span>by<span class="_ _4"> </span>T</div><div class="t m0 xa7 h2 y27e ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 xa8 h2 y27d ff1 fs0 fc0 sc0 ls0 ws0">X.</div><div class="t m1 x0 h2 y27f ff1 fs0 fc0 sc0 ls0 ws0">Most<span class="_ _1"> </span>adv<span class="_ _e"></span>anced<span class="_ _1"> </span>la<span class="_ _5"></span>y<span class="_ _5"></span>outs<span class="_ _1"> </span>in<span class="_ _1"> </span>T</div><div class="t m0 xa9 h2 y280 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 x2c h2 y27f ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _1"> </span>cannot<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>used,<span class="_ _1"> </span>for</div><div class="t m2f x0 h2 y281 ff1 fs0 fc0 sc0 ls0 ws0">example,<span class="_ _1"> </span>double<span class="_ _1"> </span>columns.<span class="_ _7"> </span>Sp<span class="_ _0"></span>ecific<span class="_ _1"> </span>lay<span class="_ _e"></span>outs<span class="_ _1"> </span>might<span class="_ _8"> </span>b<span class="_ _0"></span>e</div><div class="t m17 x0 h2 y282 ff1 fs0 fc0 sc0 ls0 ws0">sim<span class="_ _e"></span>ulated,<span class="_ _4"> </span>but<span class="_ _8"> </span>it<span class="_ _1"> </span>is<span class="_ _4"> </span>hard<span class="_ _8"> </span>in<span class="_ _1"> </span>general<span class="_ _1"> </span>due<span class="_ _4"> </span>to<span class="_ _8"> </span>the<span class="_ _1"> </span>essen-</div><div class="t m4 x0 h2 y283 ff1 fs0 fc0 sc0 ls0 ws0">tial<span class="_ _1"> </span>differences<span class="_ _1"> </span>b<span class="_ _0"></span>et<span class="_ _e"></span>ween<span class="_ _1"> </span>the<span class="_ _1"> </span>page<span class="_ _1"> </span>model<span class="_ _1"> </span>of<span class="_ _1"> </span>T</div><div class="t m0 xaa h2 y284 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m4 xab h2 y283 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _1"> </span>and</div><div class="t m7 x0 h2 y285 ff4 fs1 fc0 sc0 ls0 ws0">HTML<span class="ff1 fs0">.<span class="_ _7"> </span>While<span class="_ _1"> </span>font<span class="_ _8"> </span>embedding<span class="_ _1"> </span>is<span class="_ _1"> </span>p<span class="_ _0"></span>ossible<span class="_ _1"> </span>now<span class="_ _e"></span>adays,</span></div><div class="t m0 x0 h2 y286 ff1 fs0 fc0 sc0 ls0 ws0">most<span class="_ _1"> </span>to<span class="_ _0"></span>ols<span class="_ _1"> </span>of<span class="_ _1"> </span>this<span class="_ _1"> </span>kind<span class="_ _1"> </span>do<span class="_ _1"> </span>not<span class="_ _1"> </span>supp<span class="_ _0"></span>ort<span class="_ _1"> </span>it.</div><div class="t m1e x1 h2 y287 ff1 fs0 fc0 sc0 ls0 ws0">F<span class="_ _2"></span>urthermore,<span class="_ _1"> </span>this<span class="_ _1"> </span>type<span class="_ _1"> </span>of<span class="_ _1"> </span>approach<span class="_ _8"> </span>can<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>con-</div><div class="t m1 x0 h2 y288 ff1 fs0 fc0 sc0 ls0 ws0">sidered<span class="_ _1"> </span>a<span class="_ _1"> </span>re-implementation<span class="_ _8"> </span>of<span class="_ _1"> </span>T</div><div class="t m0 xac h2 y289 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 xad h2 y288 ff1 fs0 fc0 sc0 ls0 ws0">X,<span class="_ _1"> </span>as<span class="_ _1"> </span>these<span class="_ _1"> </span>to<span class="_ _0"></span>ols</div><div class="t mf x0 h2 y28a ff1 fs0 fc0 sc0 ls0 ws0">parse<span class="_ _1"> </span>and<span class="_ _1"> </span>pro<span class="_ _0"></span>cess<span class="_ _1"> </span>T</div><div class="t m0 xae h2 y28b ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t mf x28 h2 y28a ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _1"> </span>syn<span class="_ _e"></span>tax<span class="_ _1"> </span>in<span class="_ _1"> </span>their<span class="_ _1"> </span>own<span class="_ _8"> </span>engines,</div><div class="t m1 x0 h2 y28c ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _4"> </span>therefore<span class="_ _4"> </span>some<span class="_ _4"> </span>macros<span class="_ _4"> </span>and<span class="_ _4"> </span>pack<span class="_ _2"></span>ages<span class="_ _4"> </span>may<span class="_ _4"> </span>not</div><div class="t m26 x0 h2 y28d ff1 fs0 fc0 sc0 ls0 ws0">w<span class="_ _e"></span>ork<span class="_ _4"> </span>with<span class="_ _8"> </span>them,<span class="_ _1"> </span>esp<span class="_ _0"></span>ecially<span class="_ _1"> </span>those<span class="_ _4"> </span>related<span class="_ _8"> </span>to<span class="_ _1"> </span>drawing,</div><div class="t md x0 h2 y28e ff1 fs0 fc0 sc0 ls0 ws0">page<span class="_ _1"> </span>lay<span class="_ _e"></span>out<span class="_ _1"> </span>or<span class="_ _1"> </span><span class="ff4 fs1">PDF</span>-sp<span class="_ _0"></span>ecific<span class="_ _1"> </span>features.<span class="_ _7"> </span>Sometimes<span class="_ _4"> </span>the</div><div class="t m1 x0 h2 y28f ff1 fs0 fc0 sc0 ls0 ws0">authors<span class="_ _9"> </span>ha<span class="_ _5"></span>v<span class="_ _5"></span>e<span class="_ _9"> </span>to<span class="_ _9"> </span>prepare<span class="_ _9"> </span>different<span class="_ _4"> </span>versions<span class="_ _4"> </span>of<span class="_ _9"> </span>T</div><div class="t m0 x74 h2 y290 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 x75 h2 y28f ff1 fs0 fc0 sc0 ls0 ws0">X</div><div class="t m2 x0 h2 y291 ff1 fs0 fc0 sc0 ls0 ws0">files<span class="_ _8"> </span>for<span class="_ _1"> </span>b<span class="_ _0"></span>oth<span class="_ _8"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>and<span class="_ _8"> </span><span class="ff4 fs1">PDF</span>,<span class="_ _1"> </span>and<span class="_ _8"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>kno<span class="_ _e"></span>wledge</div><div class="t m0 x0 h2 y292 ff1 fs0 fc0 sc0 ls0 ws0">migh<span class="_ _e"></span>t<span class="_ _4"> </span>also<span class="_ _8"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>required.</div><div class="t m4 x0 h2 y293 ff1 fs0 fc0 sc0 ls0 ws0">It<span class="_ _1"> </span>is<span class="_ _1"> </span>possible<span class="_ _1"> </span>to<span class="_ _1"> </span>achiev<span class="_ _e"></span>e<span class="_ _1"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>do<span class="_ _0"></span>cuments<span class="_ _8"> </span>in<span class="_ _1"> </span>rather</div><div class="t m2 x0 h2 y294 ff1 fs0 fc0 sc0 ls0 ws0">go<span class="_ _0"></span>o<span class="_ _0"></span>d quality<span class="_ _2"></span>, while<span class="_ _8"> </span>reserving<span class="_ _8"> </span>not<span class="_ _8"> </span>only<span class="_ _8"> </span>semantic infor-</div><div class="t m0 x0 h2 y295 ff1 fs0 fc0 sc0 ls0 ws0">mation,<span class="_ _1"> </span>but<span class="_ _1"> </span>also<span class="_ _1"> </span>w<span class="_ _5"></span>ell<span class="_ _1"> </span>organized<span class="_ _1"> </span>links,<span class="_ _1"> </span>elegant<span class="_ _8"> </span>styles</div><div class="t m2 x0 h2 y296 ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _1"> </span>MathJaX-based<span class="_ _1"> </span>math<span class="_ _1"> </span>form<span class="_ _e"></span>ulas.<span class="_ _11"> </span>Go<span class="_ _0"></span>o<span class="_ _0"></span>d<span class="_ _1"> </span>examples</div><div class="t m1 x0 h2 y297 ff1 fs0 fc0 sc0 ls0 ws0">are<span class="_ _9"> </span>[</div><div class="t m0 xaf h2 y297 ff1 fs0 fc0 sc0 ls0 ws0">28</div><div class="t m1 x44 h2 y297 ff1 fs0 fc0 sc0 ls0 ws0">]<span class="_ _9"> </span>and<span class="_ _4"> </span>[</div><div class="t m0 xb0 h2 y297 ff1 fs0 fc0 sc0 ls0 ws0">38</div><div class="t m1 x70 h2 y297 ff1 fs0 fc0 sc0 ls0 ws0">].<span class="_ _12"> </span>Ho<span class="_ _e"></span>wev<span class="_ _e"></span>er,<span class="_ _7"> </span>most<span class="_ _9"> </span>of<span class="_ _4"> </span>them<span class="_ _9"> </span>employ</div><div class="t m1 x0 h2 y298 ff1 fs0 fc0 sc0 ls0 ws0">pro<span class="_ _18"></span>ject-sp<span class="_ _0"></span>ecific<span class="_ _4"> </span>tools<span class="_ _4"> </span>and<span class="_ _4"> </span>lots<span class="_ _4"> </span>of<span class="_ _1"> </span>engineering<span class="_ _4"> </span>work,</div><div class="t m1 x0 h2 y299 ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _1"> </span>there<span class="_ _1"> </span>are<span class="_ _1"> </span>also<span class="_ _4"> </span>limitations<span class="_ _8"> </span>or<span class="_ _1"> </span>paradigms<span class="_ _4"> </span>for<span class="_ _8"> </span>au-</div><div class="t m8 x0 h2 y29a ff1 fs0 fc0 sc0 ls0 ws0">thors.<span class="_ _9"> </span>Therefore<span class="_ _1"> </span>their<span class="_ _1"> </span>metho<span class="_ _0"></span>ds<span class="_ _1"> </span>might<span class="_ _8"> </span>not<span class="_ _1"> </span>work<span class="_ _8"> </span>for</div><div class="t m0 x0 h2 y29b ff1 fs0 fc0 sc0 ls0 ws0">general<span class="_ _1"> </span>do<span class="_ _0"></span>cumen<span class="_ _e"></span>ts.</div><div class="t m0 x0 h3 y97 ff2 fs0 fc0 sc0 ls0 ws0">3.4<span class="_ _c"> </span>Presen<span class="_ _e"></span>tation<span class="_ _4"> </span>HTML-based<span class="_ _4"> </span>approaches</div><div class="t m1 x0 h2 y30 ff1 fs0 fc0 sc0 ls0 ws0">Approac<span class="_ _5"></span>hes<span class="_ _7"> </span>of<span class="_ _11"> </span>this<span class="_ _11"> </span>type<span class="_ _7"> </span>fo<span class="_ _0"></span>cus<span class="_ _11"> </span>on<span class="_ _11"> </span>the<span class="_ _7"> </span>lay<span class="_ _e"></span>out<span class="_ _11"> </span>and</div><div class="t m1 x0 h2 y31 ff1 fs0 fc0 sc0 ls0 ws0">app<span class="_ _0"></span>earance<span class="_ _1"> </span>of<span class="_ _4"> </span>the<span class="_ _1"> </span>result,<span class="_ _1"> </span>utilizing<span class="_ _4"> </span><span class="ff4 fs1">CSS<span class="_ _1"> </span></span>rules<span class="_ _4"> </span>to<span class="_ _8"> </span>set</div><div class="t m23 x0 h2 y32 ff1 fs0 fc0 sc0 ls0 ws0">accurate<span class="_ _1"> </span>p<span class="_ _0"></span>osition<span class="_ _8"> </span>and<span class="_ _1"> </span>size<span class="_ _1"> </span>for<span class="_ _1"> </span>each<span class="_ _8"> </span>element,<span class="_ _8"> </span>mostly</div><div class="t m1 x0 h2 y33 ff1 fs0 fc0 sc0 ls0 ws0">text.<span class="_ _9"> </span>Non-text<span class="_ _1"> </span>elements<span class="_ _8"> </span>are<span class="_ _1"> </span>usually<span class="_ _8"> </span>conv<span class="_ _e"></span>erted<span class="_ _1"> </span>into</div><div class="t m21 x0 h2 y34 ff1 fs0 fc0 sc0 ls0 ws0">images,<span class="_ _1"> </span>raster<span class="_ _1"> </span>or<span class="_ _1"> </span>vector,<span class="_ _8"> </span>which<span class="_ _8"> </span>are<span class="_ _4"> </span>em<span class="_ _e"></span>b<span class="_ _0"></span>edded<span class="_ _1"> </span>in<span class="_ _1"> </span>the</div><div class="t m1 x0 h2 y35 ff4 fs1 fc0 sc0 ls0 ws0">HTML<span class="ff1 fs0">.<span class="_ _2d"> </span>They<span class="_ _7"> </span>are<span class="_ _7"> </span>still<span class="_ _9"> </span>significantly<span class="_ _9"> </span>differen<span class="_ _e"></span>t<span class="_ _7"> </span>from</span></div><div class="t m1 x0 h2 y36 ff1 fs0 fc0 sc0 ls0 ws0">raster<span class="_ _7"> </span>image<span class="_ _11"> </span>based<span class="_ _11"> </span>approaches<span class="_ _9"> </span>or<span class="_ _11"> </span><span class="ff4 fs1">SVG<span class="_ _7"> </span></span>based<span class="_ _11"> </span>ap-</div><div class="t m1 x0 h2 y37 ff1 fs0 fc0 sc0 ls0 ws0">proac<span class="_ _5"></span>hes<span class="_ _1"> </span>mentioned<span class="_ _1"> </span>ab<span class="_ _0"></span>ov<span class="_ _e"></span>e,<span class="_ _4"> </span>as<span class="_ _4"> </span>they<span class="_ _1"> </span>do<span class="_ _1"> </span>not<span class="_ _4"> </span>con<span class="_ _e"></span>vert</div><div class="t m0 x0 h2 y38 ff1 fs0 fc0 sc0 ls0 ws0">the<span class="_ _1"> </span>whole<span class="_ _1"> </span>do<span class="_ _0"></span>cumen<span class="_ _5"></span>t<span class="_ _1"> </span>in<span class="_ _e"></span>to<span class="_ _4"> </span>i<span class="_ _5"></span>mages.</div><div class="t m2 xe h2 y39 ff1 fs0 fc0 sc0 ls0 ws0">Prior to<span class="_ _8"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX</span>, the p<span class="_ _0"></span>dftohtml utilit<span class="_ _5"></span>y from</div><div class="t m21 xd h2 y3a ff1 fs0 fc0 sc0 ls0 ws0">P<span class="_ _e"></span>oppler<span class="_ _4"> </span>[</div><div class="t m0 x16 h2 y3a ff1 fs0 fc0 sc0 ls0 ws0">27</div><div class="t m21 xb1 h2 y3a ff1 fs0 fc0 sc0 ls0 ws0">]<span class="_ _1"> </span>is<span class="_ _1"> </span>probably<span class="_ _1"> </span>the<span class="_ _1"> </span>b<span class="_ _0"></span>est<span class="_ _1"> </span>known<span class="_ _1"> </span>to<span class="_ _0"></span>ol<span class="_ _1"> </span>that<span class="_ _1"> </span>is</div><div class="t m1a xd h2 y3b ff1 fs0 fc0 sc0 ls0 ws0">freely<span class="_ _1"> </span>a<span class="_ _5"></span>v<span class="_ _e"></span>ailable<span class="_ _1"> </span>to<span class="_ _1"> </span>the<span class="_ _1"> </span>communit<span class="_ _e"></span>y<span class="_ _2"></span>.<span class="_ _7"> </span>While<span class="_ _1"> </span>p<span class="_ _0"></span>dftoh<span class="_ _5"></span>tml</div><div class="t m1 xd h2 y3c ff1 fs0 fc0 sc0 ls0 ws0">fo<span class="_ _0"></span>cuses<span class="_ _7"> </span>more<span class="_ _11"> </span>on<span class="_ _7"> </span>extracting<span class="_ _11"> </span>semantic<span class="_ _7"> </span>information,</div><div class="t m1 xd h2 y3d ff1 fs0 fc0 sc0 ls0 ws0">p<span class="_ _0"></span>df2h<span class="_ _e"></span>tml<span class="ff4 fs1">EX<span class="_ _4"> </span></span>fo<span class="_ _0"></span>cuses<span class="_ _4"> </span>on<span class="_ _4"> </span>precise<span class="_ _4"> </span>la<span class="_ _e"></span>yout<span class="_ _1"> </span>and<span class="_ _4"> </span>app<span class="_ _0"></span>ear-</div><div class="t m13 xd h2 y3e ff1 fs0 fc0 sc0 ls0 ws0">ance.<span class="_ _7"> </span>There<span class="_ _1"> </span>seems<span class="_ _1"> </span>not<span class="_ _1"> </span>to<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>any<span class="_ _8"> </span>to<span class="_ _0"></span>ols<span class="_ _1"> </span>that<span class="_ _1"> </span>directly</div><div class="t m17 xd h2 y3f ff1 fs0 fc0 sc0 ls0 ws0">pro<span class="_ _0"></span>duce<span class="_ _1"> </span>presentation<span class="_ _8"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>files<span class="_ _4"> </span>from<span class="_ _8"> </span>T</div><div class="t m0 xb2 h2 y275 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m17 xb3 h2 y3f ff1 fs0 fc0 sc0 ls0 ws0">X,<span class="_ _1"> </span>b<span class="_ _0"></span>ecause</div><div class="t m1 xd h2 y40 ff1 fs0 fc0 sc0 ls0 ws0">of<span class="_ _4"> </span>course<span class="_ _1"> </span>T</div><div class="t m0 xb1 h2 y29c ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 xb4 h2 y40 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _4"> </span>users<span class="_ _1"> </span>may<span class="_ _1"> </span>pro<span class="_ _0"></span>duce<span class="_ _4"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>files<span class="_ _4"> </span>b<span class="_ _0"></span>efore</div><div class="t m0 xd h2 y41 ff1 fs0 fc0 sc0 ls0 ws0">further<span class="_ _1"> </span>con<span class="_ _e"></span>verting<span class="_ _1"> </span>it<span class="_ _1"> </span>in<span class="_ _e"></span>to<span class="_ _1"> </span><span class="ff4 fs1">HTML</span>.</div><div class="t m0 xd h3 y29d ff2 fs0 fc0 sc0 ls0 ws0">Pros</div><div class="t m1f x80 h2 y29d ff1 fs0 fc0 sc0 ls0 ws0">Comparing<span class="_ _8"> </span>this<span class="_ _1"> </span>output<span class="_ _1"> </span>with<span class="_ _1"> </span>images,<span class="_ _1"> </span>text<span class="_ _1"> </span>is</div><div class="t m1 xd h2 y29e ff1 fs0 fc0 sc0 ls0 ws0">no<span class="_ _5"></span>w<span class="_ _8"> </span>represented<span class="_ _8"> </span>with<span class="_ _1"> </span>native<span class="_ _8"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>elements,<span class="_ _8"> </span>such</div><div class="t m2 xd h2 y29f ff1 fs0 fc0 sc0 ls0 ws0">that they<span class="_ _8"> </span>can b<span class="_ _0"></span>e<span class="_ _8"> </span>selected<span class="_ _8"> </span>by users or<span class="_ _8"> </span>easily extracted</div><div class="t m15 xd h2 y2a0 ff1 fs0 fc0 sc0 ls0 ws0">b<span class="_ _5"></span>y<span class="_ _8"> </span>programs;<span class="_ _1"> </span>the<span class="_ _1"> </span>file<span class="_ _1"> </span>size<span class="_ _1"> </span>is<span class="_ _1"> </span>heavily<span class="_ _8"> </span>reduced<span class="_ _1"> </span>in<span class="_ _1"> </span>this</div><div class="t m1 x7b h2 y2a1 ff1 fs0 fc0 sc0 ls0 ws0">w<span class="_ _5"></span>a<span class="_ _5"></span>y<span class="_ _2"></span>.<span class="_ _f"> </span>Also<span class="_ _4"> </span>it<span class="_ _1"> </span>is<span class="_ _1"> </span>easier<span class="_ _4"> </span>to<span class="_ _1"> </span>apply<span class="_ _4"> </span><span class="ff4 fs1">CSS<span class="_ _1"> </span></span>and<span class="_ _1"> </span>Jav<span class="_ _2"></span>aScript</div><div class="t m0 xd h2 y2a2 ff1 fs0 fc0 sc0 ls0 ws0">to<span class="_ _1"> </span>t<span class="_ _5"></span>w<span class="_ _e"></span>eak<span class="_ _1"> </span>the<span class="_ _1"> </span>app<span class="_ _0"></span>earance.</div><div class="t m1 xe h2 y2a3 ff1 fs0 fc0 sc0 ls0 ws0">Comparing<span class="_ _1"> </span>with<span class="_ _4"> </span>seman<span class="_ _e"></span>tic<span class="_ _4"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>files,<span class="_ _4"> </span>the<span class="_ _4"> </span>ap-</div><div class="t m2 xd h2 y2a4 ff1 fs0 fc0 sc0 ls0 ws0">p<span class="_ _0"></span>earance of presen<span class="_ _e"></span>tation <span class="ff4 fs1">HTML </span>output is often closer</div><div class="t m2 xd h2 y2a5 ff1 fs0 fc0 sc0 ls0 ws0">or ev<span class="_ _e"></span>en iden<span class="_ _e"></span>tical to the<span class="_ _d"> </span>original document.<span class="_ _9"> </span>T</div><div class="t m0 xb5 h2 y2a6 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m2 xb6 h2 y2a5 ff1 fs0 fc0 sc0 ls0 ws0">X users</div><div class="t m4 xd h2 y2a7 ff1 fs0 fc0 sc0 ls0 ws0">are<span class="_ _1"> </span>free<span class="_ _1"> </span>to<span class="_ _1"> </span>use<span class="_ _8"> </span>any<span class="_ _1"> </span>adv<span class="_ _2"></span>anced<span class="_ _1"> </span>lay<span class="_ _e"></span>out,<span class="_ _1"> </span>macro<span class="_ _1"> </span>or<span class="_ _1"> </span>pack-</div><div class="t mb xd h2 y2a8 ff1 fs0 fc0 sc0 ls0 ws0">age,<span class="_ _1"> </span>fine-tuning<span class="_ _8"> </span>will<span class="_ _1"> </span>also<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>reflected<span class="_ _1"> </span>in<span class="_ _1"> </span>the<span class="_ _1"> </span>output,</div><div class="t m0 xd h2 y2a9 ff1 fs0 fc0 sc0 ls0 ws0">as<span class="_ _1"> </span>the<span class="_ _1"> </span>T</div><div class="t m0 x81 h2 y2aa ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m0 x7c h2 y2a9 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _1"> </span>page<span class="_ _1"> </span>mo<span class="_ _0"></span>del<span class="_ _1"> </span>is<span class="_ _1"> </span>sim<span class="_ _5"></span>ulated<span class="_ _1"> </span>in<span class="_ _1"> </span><span class="ff4 fs1">HTML</span>.</div><div class="t m0 xd h3 y2ab ff2 fs0 fc0 sc0 ls0 ws0">Cons</div><div class="t m1 x81 h2 y2ab ff1 fs0 fc0 sc0 ls0 ws0">While<span class="_ _7"> </span>text<span class="_ _7"> </span>is<span class="_ _7"> </span>still<span class="_ _11"> </span>av<span class="_ _2"></span>ailable,<span class="_ _11"> </span>the<span class="_ _7"> </span>semantic</div><div class="t m2f xd h2 y2ac ff1 fs0 fc0 sc0 ls0 ws0">meanings<span class="_ _1"> </span>(<span class="ff5">e.g.<span class="_ _1"> </span></span>title,<span class="_ _1"> </span>section,<span class="_ _1"> </span>table<span class="_ _1"> </span><span class="ff5">etc.</span>)<span class="_ _1"> </span>are<span class="_ _1"> </span>likely<span class="_ _1"> </span>to</div><div class="t mb xd h2 y2ad ff1 fs0 fc0 sc0 ls0 ws0">b<span class="_ _0"></span>e<span class="_ _1"> </span>lost.<span class="_ _9"> </span>The<span class="_ _1"> </span>conten<span class="_ _e"></span>t<span class="_ _1"> </span>may<span class="_ _8"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>to<span class="_ _0"></span>o<span class="_ _1"> </span>complicated<span class="_ _1"> </span>to<span class="_ _1"> </span>b<span class="_ _0"></span>e</div><div class="t m1 xd h2 y2ae ff1 fs0 fc0 sc0 ls0 ws0">further<span class="_ _4"> </span>pro<span class="_ _0"></span>cessed.<span class="_ _12"> </span>Precise<span class="_ _9"> </span>la<span class="_ _e"></span>yout<span class="_ _4"> </span>and<span class="_ _9"> </span>app<span class="_ _0"></span>earance</div><div class="t m12 xd h2 y2af ff1 fs0 fc0 sc0 ls0 ws0">rely<span class="_ _1"> </span>on<span class="_ _1"> </span>adv<span class="_ _e"></span>anced<span class="_ _1"> </span><span class="ff4 fs1">CSS<span class="_ _1"> </span></span>features,<span class="_ _1"> </span>lik<span class="_ _5"></span>e<span class="_ _1"> </span>fon<span class="_ _5"></span>t<span class="_ _1"> </span>em<span class="_ _5"></span>b<span class="_ _0"></span>edding,</div><div class="t m2 xd h2 y2b0 ff1 fs0 fc0 sc0 ls0 ws0">absolute<span class="_ _14"> </span>p<span class="_ _0"></span>ositioning<span class="_ _14"> </span>and linear<span class="_ _14"> </span>transformation,<span class="_ _14"> </span>which</div><div class="t m0 xd h2 y2b1 ff1 fs0 fc0 sc0 ls0 ws0">migh<span class="_ _e"></span>t<span class="_ _4"> </span>not<span class="_ _8"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>supp<span class="_ _0"></span>orted<span class="_ _1"> </span>by<span class="_ _8"> </span>old<span class="_ _1"> </span>web<span class="_ _8"> </span>browsers.</div><div class="t m0 xd h3 y2b2 ff2 fs0 fc0 sc0 ls0 ws0">3.5<span class="_ _c"> </span>Ja<span class="_ _e"></span>v<span class="_ _e"></span>aScript-based<span class="_ _4"> </span>approaches<span class="_ _4"> </span>for<span class="_ _4"> </span>T</div><div class="t m0 xb7 h3 y2b3 ff2 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m0 x9d h3 y2b2 ff2 fs0 fc0 sc0 ls0 ws0">X</div><div class="t m17 x7b h2 y2b4 ff1 fs0 fc0 sc0 ls0 ws0">While<span class="_ _1"> </span>T</div><div class="t m0 xb8 h2 y2b5 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m17 x16 h2 y2b4 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _1"> </span>is<span class="_ _1"> </span>not<span class="_ _1"> </span>directly<span class="_ _4"> </span>supported<span class="_ _1"> </span>in<span class="_ _1"> </span><span class="ff4 fs1">HTML</span>,<span class="_ _1"> </span>mo<span class="_ _0"></span>d-</div><div class="t m4 xd h2 y2b6 ff1 fs0 fc0 sc0 ls0 ws0">ern<span class="_ _1"> </span>Ja<span class="_ _5"></span>v<span class="_ _e"></span>aScript<span class="_ _1"> </span>tec<span class="_ _e"></span>hnologies<span class="_ _1"> </span>allow<span class="_ _8"> </span>us<span class="_ _1"> </span>to<span class="_ _1"> </span><span class="ff5">emb<span class="_ _5"></span>e<span class="_ _e"></span>d<span class="_ _1"> </span><span class="ff1">these</span></span></div><div class="t m1 xd h2 y2b7 ff1 fs0 fc0 sc0 ls0 ws0">files<span class="_ _9"> </span>in<span class="_ _9"> </span><span class="ff4 fs1">HTML</span>,<span class="_ _9"> </span>such<span class="_ _9"> </span>that<span class="_ _9"> </span>they<span class="_ _9"> </span>will<span class="_ _9"> </span>be<span class="_ _9"> </span>parsed<span class="_ _9"> </span>and</div><div class="t m2d xd h2 y2b8 ff1 fs0 fc0 sc0 ls0 ws0">rendered<span class="_ _1"> </span>directly<span class="_ _1"> </span>in<span class="_ _1"> </span>the<span class="_ _1"> </span>web<span class="_ _8"> </span>browsers.<span class="_ _9"> </span>Similar<span class="_ _1"> </span>tech-</div><div class="t m0 xd h2 y2b9 ff1 fs0 fc0 sc0 ls0 ws0">nologies<span class="_ _1"> </span>for<span class="_ _1"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>are<span class="_ _1"> </span>co<span class="_ _5"></span>v<span class="_ _5"></span>ered<span class="_ _1"> </span>in<span class="_ _1"> </span>Section<span class="_ _1"> </span>3.6.</div><div class="t m2 xe h2 y2ba ff1 fs0 fc0 sc0 ls0 ws0">MathJaX<span class="_ _14"> </span>[</div><div class="t m0 xb9 h2 y2ba ff1 fs0 fc0 sc0 ls0 ws0">7</div><div class="t m2 xba h2 y2ba ff1 fs0 fc0 sc0 ls0 ws0">]<span class="_ _14"> </span>is<span class="_ _14"> </span>a<span class="_ _d"> </span>Ja<span class="_ _e"></span>v<span class="_ _e"></span>aScript<span class="_ _d"> </span>displa<span class="_ _e"></span>y engine<span class="_ _14"> </span>whic<span class="_ _e"></span>h</div><div class="t m19 xd h2 y2bb ff1 fs0 fc0 sc0 ls0 ws0">parses<span class="_ _1"> </span>and<span class="_ _1"> </span>renders<span class="_ _1"> </span>T</div><div class="t m0 x61 h2 y2bc ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m19 xbb h2 y2bb ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _1"> </span>snipp<span class="_ _0"></span>ets<span class="_ _1"> </span>on<span class="_ _1"> </span>web<span class="_ _8"> </span>pages<span class="_ _1"> </span>with</div><div class="t me xd h2 y2bd ff4 fs1 fc0 sc0 ls0 ws0">HTML<span class="ff1 fs0">/</span>CSS<span class="ff1 fs0">,<span class="_ _1"> </span></span>SVG<span class="_ _8"> </span><span class="ff1 fs0">or<span class="_ _1"> </span>Math</span>ML<span class="ff1 fs0">.<span class="_ _11"> </span>MathJaX<span class="_ _1"> </span>is<span class="_ _1"> </span>designed</span></div><div class="t m1 xd h2 y2be ff1 fs0 fc0 sc0 ls0 ws0">for<span class="_ _1"> </span>online<span class="_ _4"> </span>comm<span class="_ _e"></span>unications<span class="_ _4"> </span>where<span class="_ _1"> </span>users<span class="_ _4"> </span>w<span class="_ _e"></span>an<span class="_ _5"></span>t<span class="_ _1"> </span>to<span class="_ _4"> </span>di-</div><div class="t m1 xd h2 y2bf ff1 fs0 fc0 sc0 ls0 ws0">rectly<span class="_ _9"> </span>input<span class="_ _9"> </span>form<span class="_ _e"></span>ulas<span class="_ _9"> </span>in<span class="_ _9"> </span>the<span class="_ _9"> </span>T</div><div class="t m0 x83 h2 y2c0 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 xbc h2 y2bf ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _9"> </span>syn<span class="_ _e"></span>tax.<span class="_ _2d"> </span>Similar</div><div class="t m0 xd h2 y2c1 ff1 fs0 fc0 sc0 ls0 ws0">pro<span class="_ _18"></span>jects<span class="_ _1"> </span>include<span class="_ _1"> </span>jsT<span class="_ _2"></span>eX<span class="_ _1"> </span>[2],<span class="_ _1"> </span>and<span class="_ _1"> </span>jsMath<span class="_ _1"> </span>[4].</div><div class="t m1 xe h2 y2c2 ff1 fs0 fc0 sc0 ls0 ws0">L</div><div class="t m0 x9e h6 y2c3 ff8 fs2 fc0 sc0 ls0 ws0">A</div><div class="t m1 x9f h2 y2c2 ff1 fs0 fc0 sc0 ls0 ws0">T</div><div class="t m0 x80 h2 y2c4 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 x5e h2 y2c2 ff1 fs0 fc0 sc0 ls0 ws0">X2<span class="ff4 fs1">HTML</span>5<span class="_ _4"> </span>[</div><div class="t m0 xbd h2 y2c2 ff1 fs0 fc0 sc0 ls0 ws0">22</div><div class="t m1 x19 h2 y2c2 ff1 fs0 fc0 sc0 ls0 ws0">]<span class="_ _4"> </span>is<span class="_ _4"> </span>able<span class="_ _4"> </span>to<span class="_ _1"> </span>pro<span class="_ _0"></span>duce<span class="_ _4"> </span>interac-</div><div class="t m1a xd h2 y2c5 ff1 fs0 fc0 sc0 ls0 ws0">tiv<span class="_ _e"></span>e<span class="_ _4"> </span>diagrams<span class="_ _8"> </span>from<span class="_ _1"> </span>PST<span class="_ _2"></span>ricks<span class="_ _8"> </span>macros;<span class="_ _1"> </span>it<span class="_ _1"> </span>also<span class="_ _1"> </span>utilizes</div><div class="t m0 xd h2 y2c6 ff1 fs0 fc0 sc0 ls0 ws0">MathJaX<span class="_ _1"> </span>for<span class="_ _1"> </span>rendering<span class="_ _1"> </span>math<span class="_ _1"> </span>form<span class="_ _5"></span>ulas.</div><div class="t m0 xd h3 y2c7 ff2 fs0 fc0 sc0 ls0 ws0">Pros</div><div class="t m1 x80 h2 y2c7 ff1 fs0 fc0 sc0 ls0 ws0">This<span class="_ _4"> </span>kind<span class="_ _9"> </span>of<span class="_ _4"> </span>approach<span class="_ _4"> </span>is<span class="_ _9"> </span>best<span class="_ _9"> </span>for<span class="_ _9"> </span>dynamic</div><div class="t m1 xd h2 y2c8 ff1 fs0 fc0 sc0 ls0 ws0">con<span class="_ _5"></span>ten<span class="_ _5"></span>t,<span class="_ _9"> </span>esp<span class="_ _0"></span>ecially<span class="_ _4"> </span>that<span class="_ _9"> </span>intended<span class="_ _4"> </span>to<span class="_ _4"> </span>b<span class="_ _0"></span>e<span class="_ _9"> </span>created<span class="_ _9"> </span>or</div><div class="t m1 xd h2 y2c9 ff1 fs0 fc0 sc0 ls0 ws0">mo<span class="_ _0"></span>dified<span class="_ _1"> </span>by<span class="_ _1"> </span>users.<span class="_ _11"> </span>Any<span class="_ _1"> </span>mo<span class="_ _0"></span>dification<span class="_ _1"> </span>to<span class="_ _4"> </span>the<span class="_ _8"> </span>source</div><div class="t m4 xd h2 y2ca ff1 fs0 fc0 sc0 ls0 ws0">can<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>reflected<span class="_ _1"> </span>in<span class="_ _1"> </span>the<span class="_ _1"> </span>result<span class="_ _1"> </span>promptly<span class="_ _1"> </span>without<span class="_ _1"> </span>any</div><div class="t m26 xd h2 y2cb ff1 fs0 fc0 sc0 ls0 ws0">net<span class="_ _e"></span>work<span class="_ _1"> </span>transmission.<span class="_ _7"> </span>It<span class="_ _1"> </span>can<span class="_ _1"> </span>also<span class="_ _1"> </span>handle<span class="_ _4"> </span>documents</div><div class="t m2 x7b h2 y2cc ff1 fs0 fc0 sc0 ls0 ws0">with<span class="_ _8"> </span>simple<span class="_ _8"> </span>lay<span class="_ _e"></span>out,<span class="_ _8"> </span>while<span class="_ _8"> </span>formatting<span class="_ _8"> </span>can<span class="_ _8"> </span>b<span class="_ _0"></span>e<span class="_ _8"> </span>sp<span class="_ _0"></span>ecified</div><div class="t m0 x7b h2 y2cd ff1 fs0 fc0 sc0 ls0 ws0">with<span class="_ _1"> </span><span class="ff4 fs1">CSS</span>.</div><div class="t m0 xd h3 y37 ff2 fs0 fc0 sc0 ls0 ws0">Cons</div><div class="t m1 x81 h2 y37 ff1 fs0 fc0 sc0 ls0 ws0">Approac<span class="_ _5"></span>hes<span class="_ _4"> </span>of<span class="_ _9"> </span>this<span class="_ _4"> </span>kind<span class="_ _9"> </span>are<span class="_ _4"> </span>usually<span class="_ _9"> </span>fo<span class="_ _0"></span>cus-</div><div class="t m10 xd h2 y38 ff1 fs0 fc0 sc0 ls0 ws0">ing<span class="_ _8"> </span>on<span class="_ _1"> </span>sp<span class="_ _0"></span>ecific<span class="_ _1"> </span>elements;<span class="_ _8"> </span>while<span class="_ _1"> </span>they<span class="_ _8"> </span>may<span class="_ _8"> </span>supp<span class="_ _0"></span>ort<span class="_ _1"> </span>a</div><div class="t m0 x1c h2 y77 ff1 fs0 fc0 sc0 ls0 ws0">Online<span class="_ _1"> </span>publishing<span class="_ _1"> </span>via<span class="_ _1"> </span>p<span class="_ _0"></span>df2h<span class="_ _e"></span>tm<span class="_ _0"></span>l<span class="ff4 fs1">EX</span></div><a class="l" href="#pf5" data-dest-detail='[5,"XYZ",314.092,368.706,null]'><div class="d m1d" style="border-style:none;position:absolute;left:276.053333px;bottom:1118.857203px;width:14.722000px;height:11.956000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",314.092,680.897,null]'><div class="d m1d" style="border-style:none;position:absolute;left:153.198431px;bottom:430.240627px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",314.092,299.577,null]'><div class="d m1d" style="border-style:none;position:absolute;left:220.613438px;bottom:430.240627px;width:11.956000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",314.092,694.097,null]'><div class="d m1d" style="border-style:none;position:absolute;left:589.695163px;bottom:1163.031425px;width:11.956000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf6" data-dest-detail='[6,"XYZ",72,650.815,null]'><div class="d m1d" style="border-style:none;position:absolute;left:815.741490px;bottom:488.565124px;width:14.723000px;height:10.848000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,559.601,null]'><div class="d m1d" style="border-style:none;position:absolute;left:632.915660px;bottom:471.802980px;width:6.974000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,689.863,null]'><div class="d m1d" style="border-style:none;position:absolute;left:697.282092px;bottom:371.785621px;width:6.974000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,642.54,null]'><div class="d m1d" style="border-style:none;position:absolute;left:814.061595px;bottom:371.785621px;width:6.974000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,211.905,null]'><div class="d m1d" style="border-style:none;position:absolute;left:676.213124px;bottom:351.782484px;width:11.956000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.673203,0.000000,0.000000,1.673203,0.000000,0.000000]}'></div></div>
<div id="pf6" class="pf w0 h0" data-page-no="6"><div class="pc pc6 w0 h0"><div class="t m0 x0 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">318<span class="_ _3"> </span>TUGb<span class="_ _0"></span>oat,<span class="_ _1"> </span>V<span class="_ _2"></span>olume<span class="_ _1"> </span>34<span class="_ _1"> </span>(2013),<span class="_ _1"> </span>No.<span class="_ _1"> </span>3</div><div class="t m1 x0 h2 y39 ff1 fs0 fc0 sc0 ls0 ws0">small<span class="_ _4"> </span>set<span class="_ _4"> </span>of<span class="_ _4"> </span>T</div><div class="t m0 xb0 h2 y1f6 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 x6f h2 y39 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _4"> </span>syn<span class="_ _e"></span>tax,<span class="_ _9"> </span>they<span class="_ _4"> </span>are<span class="_ _4"> </span>not<span class="_ _4"> </span>designed<span class="_ _4"> </span>as</div><div class="t mc x0 h2 y3a ff1 fs0 fc0 sc0 ls0 ws0">a<span class="_ _1"> </span>Ja<span class="_ _e"></span>v<span class="_ _e"></span>aScript<span class="_ _1"> </span>implementation<span class="_ _8"> </span>of<span class="_ _1"> </span>T</div><div class="t m0 x72 h2 y2ce ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t mc xbe h2 y3a ff1 fs0 fc0 sc0 ls0 ws0">X.<span class="_ _9"> </span>Therefore<span class="_ _1"> </span>ad-</div><div class="t m18 x0 h2 y3b ff1 fs0 fc0 sc0 ls0 ws0">v<span class="_ _e"></span>anced<span class="_ _1"> </span>commands<span class="_ _1"> </span>or<span class="_ _1"> </span>macros<span class="_ _1"> </span>may<span class="_ _8"> </span>not<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>supp<span class="_ _0"></span>orted,</div><div class="t m19 x0 h2 y3c ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _1"> </span>usually<span class="_ _1"> </span>they<span class="_ _1"> </span>are<span class="_ _1"> </span>not<span class="_ _1"> </span>capable<span class="_ _1"> </span>of<span class="_ _1"> </span>typesetting<span class="_ _4"> </span>gen-</div><div class="t m0 x0 h2 y3d ff1 fs0 fc0 sc0 ls0 ws0">eral<span class="_ _1"> </span>do<span class="_ _0"></span>cumen<span class="_ _e"></span>ts<span class="_ _4"> </span>with<span class="_ _8"> </span>complicated<span class="_ _1"> </span>lay<span class="_ _e"></span>out.</div><div class="t m0 x0 h3 y2cf ff2 fs0 fc0 sc0 ls0 ws0">3.6<span class="_ _c"> </span>Ja<span class="_ _e"></span>v<span class="_ _e"></span>aScript-based<span class="_ _4"> </span>approaches<span class="_ _4"> </span>for<span class="_ _4"> </span>PDF</div><div class="t m2 x0 h2 y2d0 ff4 fs1 fc0 sc0 ls0 ws0">PDF<span class="_ _31"></span><span class="ff1 fs0">.<span class="_ _16"></span>js<span class="_ _8"> </span>[</span></div><div class="t m0 xbf h2 y2d0 ff1 fs0 fc0 sc0 ls0 ws0">13</div><div class="t m2 xc0 h2 y2d0 ff1 fs0 fc0 sc0 ls0 ws0">]<span class="_ _8"> </span>is a<span class="_ _8"> </span>Jav<span class="_ _2"></span>aScript<span class="_ _8"> </span>library<span class="_ _8"> </span>for<span class="_ _8"> </span>rendering<span class="_ _8"> </span><span class="ff4 fs1">PDF</span>;</div><div class="t m1 x0 h2 y2d1 ff1 fs0 fc0 sc0 ls0 ws0">it<span class="_ _9"> </span>is<span class="_ _9"> </span>now<span class="_ _9"> </span>a<span class="_ _9"> </span>part<span class="_ _9"> </span>of<span class="_ _9"> </span>Mozilla<span class="_ _9"> </span>Firefox.<span class="_ _2d"> </span>It<span class="_ _9"> </span>is<span class="_ _9"> </span>lik<span class="_ _5"></span>e<span class="_ _9"> </span>the</div><div class="t m1 x0 h2 y2d2 ff1 fs0 fc0 sc0 ls0 ws0">raster<span class="_ _4"> </span>image-based<span class="_ _4"> </span>approaches<span class="_ _4"> </span>except<span class="_ _4"> </span>that<span class="_ _4"> </span>all<span class="_ _4"> </span>the</div><div class="t m1 x0 h2 y2d3 ff1 fs0 fc0 sc0 ls0 ws0">parsing<span class="_ _4"> </span>and<span class="_ _9"> </span>rendering<span class="_ _4"> </span>are<span class="_ _9"> </span>done<span class="_ _4"> </span>on<span class="_ _9"> </span>the<span class="_ _4"> </span>client<span class="_ _4"> </span>side.</div><div class="t m1 x0 h2 y2d4 ff1 fs0 fc0 sc0 ls0 ws0">Recen<span class="_ _5"></span>t<span class="_ _4"> </span>w<span class="_ _e"></span>eb<span class="_ _4"> </span>bro<span class="_ _e"></span>wsers<span class="_ _4"> </span>are<span class="_ _1"> </span>necessary<span class="_ _4"> </span>to<span class="_ _1"> </span>supp<span class="_ _0"></span>ort<span class="_ _4"> </span>the</div><div class="t m0 x0 h2 y2d5 ff1 fs0 fc0 sc0 ls0 ws0">tec<span class="_ _e"></span>hnologies<span class="_ _4"> </span>used<span class="_ _8"> </span>by<span class="_ _8"> </span>the<span class="_ _1"> </span>library<span class="_ _2"></span>.</div><div class="t m1 x1 h2 y2d6 ff4 fs1 fc0 sc0 ls0 ws0">PDF<span class="_ _31"></span><span class="ff1 fs0">.<span class="_ _16"></span>js<span class="_ _9"> </span>is<span class="_ _7"> </span>one<span class="_ _9"> </span>of<span class="_ _7"> </span>a<span class="_ _7"> </span>kind;<span class="_ _11"> </span>there<span class="_ _7"> </span>are<span class="_ _9"> </span>no<span class="_ _7"> </span>similar</span></div><div class="t m0 x0 h2 y2d7 ff1 fs0 fc0 sc0 ls0 ws0">alternativ<span class="_ _e"></span>es<span class="_ _4"> </span>to<span class="_ _8"> </span>the<span class="_ _1"> </span>b<span class="_ _0"></span>est<span class="_ _1"> </span>of<span class="_ _1"> </span>our<span class="_ _1"> </span>knowledge.</div><div class="t m0 x0 h3 y2d8 ff2 fs0 fc0 sc0 ls0 ws0">Pros</div><div class="t m2 xc1 h2 y2d8 ff4 fs1 fc0 sc0 ls0 ws0">PDF<span class="_ _31"></span><span class="ff1 fs0">.<span class="_ _16"></span>js<span class="_ _8"> </span>renders<span class="_ _1"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>files<span class="_ _1"> </span>in<span class="_ _5"></span>to<span class="_ _8"> </span>an<span class="_ _1"> </span><span class="ff4 fs1">HTML</span>5<span class="_ _1"> </span>can-</span></div><div class="t m1 x0 h2 y2d9 ff1 fs0 fc0 sc0 ls0 ws0">v<span class="_ _e"></span>as,<span class="_ _4"> </span>which<span class="_ _4"> </span>is<span class="_ _4"> </span>similar<span class="_ _4"> </span>to<span class="_ _4"> </span>a<span class="_ _4"> </span>raster<span class="_ _4"> </span>image;<span class="_ _9"> </span>most<span class="_ _4"> </span><span class="ff4 fs1">PDF</span></div><div class="t m1a x0 h2 y2da ff1 fs0 fc0 sc0 ls0 ws0">elemen<span class="_ _e"></span>ts<span class="_ _4"> </span>can<span class="_ _8"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>rendered<span class="_ _1"> </span>correctly<span class="_ _2"></span>.<span class="_ _7"> </span>F<span class="_ _2"></span>urthermore,<span class="_ _1"> </span>it</div><div class="t m2 x0 h2 y2db ff1 fs0 fc0 sc0 ls0 ws0">do<span class="_ _0"></span>es<span class="_ _1"> </span>not<span class="_ _1"> </span>suffer<span class="_ _1"> </span>from<span class="_ _8"> </span>a<span class="_ _1"> </span>huge<span class="_ _8"> </span>netw<span class="_ _e"></span>ork<span class="_ _1"> </span>cost<span class="_ _1"> </span>as<span class="_ _1"> </span>only<span class="_ _1"> </span>the</div><div class="t m0 x0 h2 y2dc ff1 fs0 fc0 sc0 ls0 ws0">original<span class="_ _1"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>file<span class="_ _1"> </span>need<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>transferred.</div><div class="t m1 x1 h2 y2dd ff1 fs0 fc0 sc0 ls0 ws0">The<span class="_ _4"> </span>library<span class="_ _4"> </span>can<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _4"> </span>embedded<span class="_ _4"> </span>in<span class="_ _e"></span>to<span class="_ _4"> </span>web<span class="_ _4"> </span>pages,</div><div class="t m0 x0 h2 y2de ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _1"> </span>can<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>extended<span class="_ _1"> </span>b<span class="_ _5"></span>y<span class="_ _1"> </span>publishers<span class="_ _1"> </span>if<span class="_ _1"> </span>needed.</div><div class="t m0 x0 h3 y2df ff2 fs0 fc0 sc0 ls0 ws0">Cons</div><div class="t m1 xbf h2 y2df ff4 fs1 fc0 sc0 ls0 ws0">PDF<span class="_ _31"></span><span class="ff1 fs0">.<span class="_ _16"></span>js<span class="_ _f"> </span>relies<span class="_ _f"> </span>heavily<span class="_ _f"> </span>on<span class="_ _f"> </span>the<span class="_ _f"> </span>computation</span></div><div class="t m1 x0 h2 y2e0 ff1 fs0 fc0 sc0 ls0 ws0">p<span class="_ _0"></span>o<span class="_ _e"></span>wer<span class="_ _7"> </span>on<span class="_ _11"> </span>the<span class="_ _7"> </span>client<span class="_ _7"> </span>side,<span class="_ _f"> </span>which<span class="_ _9"> </span>might<span class="_ _7"> </span>cause<span class="_ _11"> </span>p<span class="_ _0"></span>er-</div><div class="t m0 x0 h2 y2e1 ff1 fs0 fc0 sc0 ls0 ws0">formance<span class="_ _1"> </span>issues<span class="_ _1"> </span>in<span class="_ _1"> </span>some<span class="_ _1"> </span>en<span class="_ _5"></span>vironmen<span class="_ _5"></span>ts.</div><div class="t m3 x1 h2 y2e2 ff1 fs0 fc0 sc0 ls0 ws0">It<span class="_ _1"> </span>is<span class="_ _1"> </span>designed<span class="_ _1"> </span>as<span class="_ _1"> </span>a<span class="_ _1"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>reader,<span class="_ _1"> </span>and<span class="_ _1"> </span>it<span class="_ _1"> </span>do<span class="_ _0"></span>es<span class="_ _1"> </span>not</div><div class="t m2 x0 h2 y2e3 ff1 fs0 fc0 sc0 ls0 ws0">optimize for<span class="_ _8"> </span>online publishing;<span class="_ _8"> </span>for<span class="_ _8"> </span>example<span class="_ _8"> </span>users still</div><div class="t m1 x0 h2 y2e4 ff1 fs0 fc0 sc0 ls0 ws0">ha<span class="_ _5"></span>v<span class="_ _e"></span>e<span class="_ _7"> </span>to<span class="_ _7"> </span>wait<span class="_ _9"> </span>for<span class="_ _9"> </span>the<span class="_ _7"> </span>entire<span class="_ _9"> </span>file<span class="_ _9"> </span>to<span class="_ _7"> </span>b<span class="_ _0"></span>e<span class="_ _7"> </span>downloaded</div><div class="t m0 x0 h2 y2e5 ff1 fs0 fc0 sc0 ls0 ws0">b<span class="_ _0"></span>efore<span class="_ _1"> </span>they<span class="_ _1"> </span>can<span class="_ _1"> </span>read<span class="_ _1"> </span>an<span class="_ _5"></span>y<span class="_ _1"> </span>page.</div><div class="t m1b x1 h2 y2e6 ff4 fs1 fc0 sc0 ls0 ws0">PDF<span class="_ _1"> </span><span class="ff1 fs0">elements<span class="_ _8"> </span>are<span class="_ _1"> </span>rendered<span class="_ _4"> </span>in<span class="_ _e"></span>to<span class="_ _1"> </span>an<span class="_ _1"> </span><span class="ff4 fs1">HTML</span>5<span class="_ _4"> </span>can-</span></div><div class="t m2 x0 h2 y2e7 ff1 fs0 fc0 sc0 ls0 ws0">v<span class="_ _e"></span>as,<span class="_ _8"> </span>which<span class="_ _8"> </span>may<span class="_ _8"> </span>not<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>flexible<span class="_ _1"> </span>enough<span class="_ _1"> </span>for<span class="_ _1"> </span>publishers.</div><div class="t m0 x0 h3 y2e8 ff2 fs0 fc0 sc0 ls0 ws0">3.7<span class="_ _c"> </span>Plugin-based<span class="_ _4"> </span>approac<span class="_ _e"></span>hes</div><div class="t m21 x0 h2 y2e9 ff1 fs0 fc0 sc0 ls0 ws0">Man<span class="_ _e"></span>y<span class="_ _4"> </span>w<span class="_ _e"></span>eb<span class="_ _1"> </span>browsers<span class="_ _8"> </span>supp<span class="_ _0"></span>ort<span class="_ _1"> </span>plugins<span class="_ _1"> </span>to<span class="_ _1"> </span>add<span class="_ _4"> </span>new<span class="_ _8"> </span>fea-</div><div class="t m17 x0 h2 y2ea ff1 fs0 fc0 sc0 ls0 ws0">tures,<span class="_ _1"> </span>esp<span class="_ _0"></span>ecially<span class="_ _1"> </span>plugins<span class="_ _1"> </span>can<span class="_ _4"> </span>be<span class="_ _1"> </span>used<span class="_ _1"> </span>to<span class="_ _1"> </span>display<span class="_ _1"> </span>T</div><div class="t m0 xa7 h2 y2eb ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m17 xa8 h2 y2ea ff1 fs0 fc0 sc0 ls0 ws0">X,</div><div class="t m2 x0 h2 y2ec ff4 fs1 fc0 sc0 ls0 ws0">PDF<span class="ff1 fs0">, or other formats con<span class="_ _e"></span>verted<span class="_ _d"> </span>from them.<span class="_ _9"> </span>Publish-</span></div><div class="t m22 x0 h2 y2ed ff1 fs0 fc0 sc0 ls0 ws0">ers<span class="_ _1"> </span>ma<span class="_ _e"></span>y<span class="_ _1"> </span>also<span class="_ _1"> </span>develop<span class="_ _8"> </span>plugins<span class="_ _1"> </span>for<span class="_ _1"> </span>their<span class="_ _1"> </span>own<span class="_ _8"> </span>formats,</div><div class="t m19 x0 h2 y2ee ff1 fs0 fc0 sc0 ls0 ws0">whic<span class="_ _e"></span>h<span class="_ _4"> </span>are<span class="_ _8"> </span>otherwise<span class="_ _1"> </span>not<span class="_ _1"> </span>supp<span class="_ _0"></span>orted<span class="_ _1"> </span>by<span class="_ _8"> </span>web<span class="_ _8"> </span>browsers.</div><div class="t m1c x1 h2 y2ef ff1 fs0 fc0 sc0 ls0 ws0">Adob<span class="_ _0"></span>e<span class="_ _1"> </span>Reader<span class="_ _1"> </span>includes<span class="_ _8"> </span>plugins<span class="_ _1"> </span>to<span class="_ _1"> </span>display<span class="_ _8"> </span><span class="ff4 fs1">PDF</span></div><div class="t m1 x0 h2 y2f0 ff1 fs0 fc0 sc0 ls0 ws0">files<span class="_ _4"> </span>within<span class="_ _1"> </span>different<span class="_ _1"> </span>w<span class="_ _5"></span>eb<span class="_ _4"> </span>bro<span class="_ _e"></span>wsers.<span class="_ _30"> </span>There<span class="_ _1"> </span>are<span class="_ _4"> </span>also</div><div class="t m1 x0 h2 y2f1 ff1 fs0 fc0 sc0 ls0 ws0">similar<span class="_ _4"> </span>third-party<span class="_ _4"> </span>plugins<span class="_ _4"> </span>based<span class="_ _4"> </span>on<span class="_ _4"> </span>Adob<span class="_ _0"></span>e<span class="_ _4"> </span>Flash.</div><div class="t m2 x0 h2 y2f2 ff1 fs0 fc0 sc0 ls0 ws0">There<span class="_ _14"> </span>are<span class="_ _14"> </span>also<span class="_ _d"> </span>plugins<span class="_ _14"> </span>to<span class="_ _14"> </span>display<span class="_ _14"> </span>math<span class="_ _14"> </span>formulas<span class="_ _14"> </span>inside</div><div class="t m0 x0 h2 y2f3 ff1 fs0 fc0 sc0 ls0 ws0">w<span class="_ _e"></span>eb<span class="_ _4"> </span>bro<span class="_ _e"></span>wsers,<span class="_ _1"> </span><span class="ff5">e.g.<span class="_ _1"> </span></span>MathPla<span class="_ _e"></span>yer<span class="_ _1"> </span>[23].</div><div class="t m0 x0 h3 y2f4 ff2 fs0 fc0 sc0 ls0 ws0">Pros</div><div class="t m2e xc2 h2 y2f4 ff1 fs0 fc0 sc0 ls0 ws0">Plugins<span class="_ _1"> </span>are<span class="_ _8"> </span>not<span class="_ _1"> </span>limited<span class="_ _1"> </span>to<span class="_ _1"> </span>web<span class="_ _8"> </span>technologies,</div><div class="t m1 x0 h2 y2f5 ff1 fs0 fc0 sc0 ls0 ws0">th<span class="_ _5"></span>us<span class="_ _9"> </span>they<span class="_ _9"> </span>are<span class="_ _9"> </span>usually<span class="_ _9"> </span>b<span class="_ _0"></span>etter<span class="_ _7"> </span>in<span class="_ _9"> </span>term<span class="_ _9"> </span>of<span class="_ _9"> </span>rendering</div><div class="t m22 x0 h2 y2f6 ff1 fs0 fc0 sc0 ls0 ws0">qualit<span class="_ _e"></span>y<span class="_ _1"> </span>or<span class="_ _1"> </span>supp<span class="_ _0"></span>orted<span class="_ _1"> </span>features.<span class="_ _7"> </span>F<span class="_ _2"></span>or<span class="_ _1"> </span>example,<span class="_ _1"> </span>Adob<span class="_ _0"></span>e</div><div class="t m2 x0 h2 y2f7 ff1 fs0 fc0 sc0 ls0 ws0">Reader<span class="_ _8"> </span>should<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _8"> </span>the<span class="_ _1"> </span>plugin<span class="_ _1"> </span>with<span class="_ _8"> </span>the<span class="_ _1"> </span>most<span class="_ _8"> </span>complete</div><div class="t m0 x0 h2 y2f8 ff1 fs0 fc0 sc0 ls0 ws0">supp<span class="_ _0"></span>ort<span class="_ _1"> </span>for<span class="_ _1"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>features.</div><div class="t m0 x0 h3 y34 ff2 fs0 fc0 sc0 ls0 ws0">Cons</div><div class="t m1 x39 h2 y34 ff1 fs0 fc0 sc0 ls0 ws0">The<span class="_ _7"> </span>crucial<span class="_ _7"> </span>downside<span class="_ _7"> </span>is<span class="_ _7"> </span>that<span class="_ _11"> </span>plugins<span class="_ _7"> </span>usu-</div><div class="t m1 x0 h2 y35 ff1 fs0 fc0 sc0 ls0 ws0">ally<span class="_ _4"> </span>create<span class="_ _4"> </span>closed<span class="_ _4"> </span>en<span class="_ _5"></span>vironmen<span class="_ _5"></span>ts,<span class="_ _4"> </span>which<span class="_ _4"> </span>prev<span class="_ _e"></span>ent<span class="_ _4"> </span>an</div><div class="t m1 x0 h2 y36 ff1 fs0 fc0 sc0 ls0 ws0">in<span class="_ _5"></span>teractiv<span class="_ _e"></span>e<span class="_ _4"> </span>user<span class="_ _1"> </span>exp<span class="_ _0"></span>erience<span class="_ _4"> </span>on<span class="_ _1"> </span>the<span class="_ _4"> </span>w<span class="_ _e"></span>eb<span class="_ _1"> </span>sites.<span class="_ _30"> </span>Most</div><div class="t m2c x0 h2 y37 ff1 fs0 fc0 sc0 ls0 ws0">plugins<span class="_ _1"> </span>are<span class="_ _1"> </span>not<span class="_ _1"> </span>easily<span class="_ _1"> </span>customizable,<span class="_ _4"> </span>except<span class="_ _8"> </span>for<span class="_ _1"> </span>a<span class="_ _4"> </span>few</div><div class="t m3 x0 h2 y38 ff1 fs0 fc0 sc0 ls0 ws0">commercial<span class="_ _1"> </span>ones.<span class="_ _9"> </span>Due<span class="_ _1"> </span>to<span class="_ _1"> </span>the<span class="_ _1"> </span>active<span class="_ _8"> </span>developmen<span class="_ _e"></span>t<span class="_ _1"> </span>of</div><div class="t m2 xd h2 y39 ff4 fs1 fc0 sc0 ls0 ws0">HTML<span class="ff1 fs0">5 technologies,<span class="_ _8"> </span>plugins now<span class="_ _e"></span>adays are<span class="_ _8"> </span>no<span class="_ _8"> </span>longer</span></div><div class="t m1e xd h2 y3a ff1 fs0 fc0 sc0 ls0 ws0">so<span class="_ _1"> </span>p<span class="_ _0"></span>opular<span class="_ _1"> </span>as<span class="_ _1"> </span>b<span class="_ _0"></span>efore,<span class="_ _1"> </span>for<span class="_ _1"> </span>security<span class="_ _31"></span>,<span class="_ _1"> </span>compatibility<span class="_ _8"> </span>and</div><div class="t m0 xd h2 y3b ff1 fs0 fc0 sc0 ls0 ws0">p<span class="_ _0"></span>erformance<span class="_ _1"> </span>reasons.</div><div class="t m0 xd h3 y2f9 ff2 fs0 fc0 sc0 ls0 ws0">3.8<span class="_ _c"> </span>Third-part<span class="_ _e"></span>y<span class="_ _4"> </span>services</div><div class="t m23 x7b h2 y2fa ff1 fs0 fc0 sc0 ls0 ws0">Third-part<span class="_ _e"></span>y<span class="_ _1"> </span>services<span class="_ _1"> </span>also<span class="_ _1"> </span>exist<span class="_ _1"> </span>such<span class="_ _8"> </span>that<span class="_ _1"> </span>em<span class="_ _e"></span>b<span class="_ _0"></span>edded</div><div class="t m1 x7b h2 y2fb ff1 fs0 fc0 sc0 ls0 ws0">T</div><div class="t m0 xc3 h2 y2fc ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 x8c h2 y2fb ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _4"> </span>or<span class="_ _4"> </span><span class="ff4 fs1">PDF<span class="_ _4"> </span></span>can<span class="_ _4"> </span>b<span class="_ _0"></span>e<span class="_ _4"> </span>redirected<span class="_ _4"> </span>to<span class="_ _4"> </span>their<span class="_ _4"> </span>servers<span class="_ _4"> </span>for</div><div class="t m0 xd h2 y2fd ff1 fs0 fc0 sc0 ls0 ws0">pro<span class="_ _0"></span>cessing<span class="_ _1"> </span>and<span class="_ _1"> </span>rendering,<span class="_ _1"> </span>for<span class="_ _1"> </span>example:</div><div class="t m0 x7e h2 y2fe fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">Quic<span class="_ _5"></span>kL</span></div><div class="t m0 x7d h6 y2ff ff8 fs2 fc0 sc0 ls0 ws0">A</div><div class="t m0 xc4 h2 y2fe ff1 fs0 fc0 sc0 ls0 ws0">T</div><div class="t m0 xc5 h2 y300 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m0 x99 h2 y2fe ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _1"> </span>[10]</div><div class="t m0 x7e h2 y301 fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">mathT</span></div><div class="t m0 x7d h2 y302 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m0 x7f h2 y301 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _1"> </span>[9]</div><div class="t m0 x7e h2 y303 fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">Go<span class="_ _0"></span>ogle<span class="_ _1"> </span>Do<span class="_ _0"></span>cs<span class="_ _1"> </span>[3]</span></div><div class="t m0 x7e h2 y304 fff fs0 fc0 sc0 ls0 ws0">•<span class="_ _f"> </span><span class="ff1">Cro<span class="_ _0"></span>co<span class="_ _0"></span>do<span class="_ _0"></span>c<span class="_ _1"> </span>[15]</span></div><div class="t m1 xe h2 y305 ff1 fs0 fc0 sc0 ls0 ws0">This<span class="_ _f"> </span>kind<span class="_ _f"> </span>of<span class="_ _30"> </span>service<span class="_ _11"> </span>accepts<span class="_ _f"> </span>input<span class="_ _30"> </span>uploaded</div><div class="t m1f xd h2 y306 ff1 fs0 fc0 sc0 ls0 ws0">b<span class="_ _5"></span>y<span class="_ _8"> </span>publishers,<span class="_ _1"> </span>conv<span class="_ _e"></span>erts<span class="_ _1"> </span>it<span class="_ _1"> </span>internally<span class="_ _8"> </span>with<span class="_ _8"> </span>their<span class="_ _1"> </span>own</div><div class="t m1 xd h2 y307 ff1 fs0 fc0 sc0 ls0 ws0">implemen<span class="_ _5"></span>tations<span class="_ _9"> </span>and<span class="_ _9"> </span>redirects<span class="_ _9"> </span>the<span class="_ _9"> </span>result<span class="_ _9"> </span>to<span class="_ _9"> </span>users.</div><div class="t m1c x7b h2 y308 ff1 fs0 fc0 sc0 ls0 ws0">The<span class="_ _1"> </span>tec<span class="_ _e"></span>hnologies<span class="_ _1"> </span>b<span class="_ _0"></span>ehind<span class="_ _1"> </span>them,<span class="_ _1"> </span>op<span class="_ _0"></span>en<span class="_ _1"> </span>or<span class="_ _1"> </span>proprietary<span class="_ _2"></span>,</div><div class="t m7 xd h2 y309 ff1 fs0 fc0 sc0 ls0 ws0">should<span class="_ _1"> </span>still<span class="_ _1"> </span>fall<span class="_ _1"> </span>into<span class="_ _8"> </span>the<span class="_ _1"> </span>categories<span class="_ _1"> </span>mentioned<span class="_ _8"> </span>ab<span class="_ _0"></span>ov<span class="_ _e"></span>e.</div><div class="t m0 xd h3 y30a ff2 fs0 fc0 sc0 ls0 ws0">Pros</div><div class="t m2 x80 h2 y30a ff1 fs0 fc0 sc0 ls0 ws0">This<span class="_ _8"> </span>kind<span class="_ _1"> </span>of<span class="_ _1"> </span>service<span class="_ _1"> </span>is<span class="_ _8"> </span>usually<span class="_ _1"> </span>easy<span class="_ _1"> </span>to<span class="_ _1"> </span>deplo<span class="_ _e"></span>y<span class="_ _2"></span>,</div><div class="t m1 xd h2 y30b ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _7"> </span>con<span class="_ _5"></span>v<span class="_ _5"></span>enien<span class="_ _5"></span>t<span class="_ _7"> </span>for<span class="_ _7"> </span>publishing<span class="_ _7"> </span>a<span class="_ _7"> </span>few<span class="_ _7"> </span>simple<span class="_ _7"> </span>do<span class="_ _0"></span>cu-</div><div class="t m1 xd h2 y30c ff1 fs0 fc0 sc0 ls0 ws0">men<span class="_ _5"></span>ts.<span class="_ _2d"> </span>The<span class="_ _9"> </span>con<span class="_ _e"></span>version<span class="_ _9"> </span>process<span class="_ _9"> </span>relies<span class="_ _7"> </span>only<span class="_ _9"> </span>on<span class="_ _9"> </span>the</div><div class="t m1 xd h2 y30d ff1 fs0 fc0 sc0 ls0 ws0">computation<span class="_ _9"> </span>p<span class="_ _0"></span>ow<span class="_ _e"></span>er<span class="_ _9"> </span>of<span class="_ _7"> </span>the<span class="_ _9"> </span>third<span class="_ _7"> </span>party<span class="_ _31"></span>.<span class="_ _b"> </span>Some<span class="_ _9"> </span>ser-</div><div class="t m1b x7b h2 y30e ff1 fs0 fc0 sc0 ls0 ws0">vices<span class="_ _1"> </span>also<span class="_ _1"> </span>provide<span class="_ _8"> </span>an<span class="_ _4"> </span><span class="ff4 fs1">API<span class="_ _8"> </span></span>for<span class="_ _4"> </span>better<span class="_ _1"> </span>integration<span class="_ _8"> </span>with</div><div class="t m0 xd h2 y30f ff1 fs0 fc0 sc0 ls0 ws0">publishers<span class="_ _1"> </span>sites.</div><div class="t m0 xd h3 y310 ff2 fs0 fc0 sc0 ls0 ws0">Cons</div><div class="t m2e x81 h2 y310 ff1 fs0 fc0 sc0 ls0 ws0">A<span class="_ _1"> </span>crucial<span class="_ _8"> </span>issue<span class="_ _1"> </span>here<span class="_ _1"> </span>that<span class="_ _1"> </span>may<span class="_ _8"> </span>concern<span class="_ _1"> </span>a<span class="_ _1"> </span>lot</div><div class="t m10 xd h2 y311 ff1 fs0 fc0 sc0 ls0 ws0">of<span class="_ _8"> </span>publishers<span class="_ _1"> </span>is<span class="_ _1"> </span>that<span class="_ _1"> </span>the<span class="_ _8"> </span>files<span class="_ _1"> </span>must<span class="_ _8"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>accessible<span class="_ _1"> </span>b<span class="_ _e"></span>y</div><div class="t m1 xd h2 y312 ff1 fs0 fc0 sc0 ls0 ws0">the<span class="_ _7"> </span>third<span class="_ _7"> </span>party<span class="_ _31"></span>.<span class="_ _20"> </span>This<span class="_ _9"> </span>may<span class="_ _9"> </span>not<span class="_ _7"> </span>b<span class="_ _0"></span>e<span class="_ _11"> </span>acceptable<span class="_ _7"> </span>for</div><div class="t m1 xd h2 y313 ff1 fs0 fc0 sc0 ls0 ws0">priv<span class="_ _e"></span>ate,<span class="_ _7"> </span>confidential<span class="_ _9"> </span>or<span class="_ _7"> </span>cop<span class="_ _e"></span>yrighted<span class="_ _9"> </span>materials.<span class="_ _b"> </span>In</div><div class="t m2 xd h2 y314 ff1 fs0 fc0 sc0 ls0 ws0">addition, the publishers service<span class="_ _d"> </span>has to depend on the</div><div class="t m13 xd h2 y315 ff1 fs0 fc0 sc0 ls0 ws0">a<span class="_ _e"></span>v<span class="_ _e"></span>ailability<span class="_ _8"> </span>of<span class="_ _1"> </span>the<span class="_ _1"> </span>third<span class="_ _1"> </span>party<span class="_ _31"></span>.<span class="_ _7"> </span>F<span class="_ _2"></span>urther<span class="_ _1"> </span>developmen<span class="_ _e"></span>t</div><div class="t m1 xd h2 y316 ff1 fs0 fc0 sc0 ls0 ws0">ma<span class="_ _5"></span>y<span class="_ _4"> </span>also<span class="_ _4"> </span>be<span class="_ _4"> </span>limited<span class="_ _4"> </span>by<span class="_ _4"> </span>the<span class="_ _4"> </span><span class="ff4 fs1">API<span class="_ _4"> </span></span>pro<span class="_ _e"></span>vided<span class="_ _4"> </span>or<span class="_ _4"> </span>other</div><div class="t m0 xd h2 y317 ff1 fs0 fc0 sc0 ls0 ws0">issues<span class="_ _1"> </span>suc<span class="_ _5"></span>h<span class="_ _1"> </span>as<span class="_ _1"> </span>differen<span class="_ _5"></span>t<span class="_ _1"> </span>domains.</div><div class="t m0 xd h3 y318 ff2 fs0 fc0 sc0 ls0 ws0">3.9<span class="_ _c"> </span>Discussion</div><div class="t m8 xd h2 y319 ff1 fs0 fc0 sc0 ls0 ws0">In<span class="_ _8"> </span>this<span class="_ _1"> </span>section<span class="_ _1"> </span>we<span class="_ _8"> </span>categorized<span class="_ _1"> </span>a<span class="_ _8"> </span>num<span class="_ _e"></span>b<span class="_ _0"></span>er<span class="_ _1"> </span>of<span class="_ _1"> </span>p<span class="_ _0"></span>opular</div><div class="t m1 xd h2 y31a ff1 fs0 fc0 sc0 ls0 ws0">approac<span class="_ _5"></span>hes,<span class="_ _9"> </span>among<span class="_ _9"> </span>whic<span class="_ _e"></span>h<span class="_ _9"> </span>the<span class="_ _9"> </span>most<span class="_ _4"> </span>p<span class="_ _0"></span>opular<span class="_ _9"> </span>three</div><div class="t m0 xd h2 y31b ff1 fs0 fc0 sc0 ls0 ws0">t<span class="_ _e"></span>yp<span class="_ _0"></span>es<span class="_ _1"> </span>of<span class="_ _4"> </span>output<span class="_ _8"> </span>are:</div><div class="t m0 xd h3 y31c ff2 fs0 fc0 sc0 ls0 ws0">Image</div><div class="t mc x7c h2 y31c ff1 fs0 fc0 sc0 ls0 ws0">is<span class="_ _1"> </span>best<span class="_ _1"> </span>for<span class="_ _1"> </span>publishers<span class="_ _1"> </span>who<span class="_ _1"> </span>can<span class="_ _1"> </span>afford<span class="_ _1"> </span>large</div><div class="t m2f x7b h2 y31d ff1 fs0 fc0 sc0 ls0 ws0">v<span class="_ _e"></span>olume<span class="_ _4"> </span>of<span class="_ _8"> </span>storage<span class="_ _1"> </span>and<span class="_ _1"> </span>bandwidth.<span class="_ _7"> </span>There<span class="_ _4"> </span>is<span class="_ _8"> </span>no<span class="_ _1"> </span>need</div><div class="t m2 xd h2 y31e ff1 fs0 fc0 sc0 ls0 ws0">to fine-tune<span class="_ _8"> </span>or even redesign the do<span class="_ _0"></span>cument, as<span class="_ _8"> </span>la<span class="_ _5"></span>y<span class="_ _e"></span>out</div><div class="t m15 xd h2 y31f ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _8"> </span>format<span class="_ _1"> </span>are<span class="_ _1"> </span>already<span class="_ _1"> </span>accurately<span class="_ _1"> </span>preserved<span class="_ _8"> </span>in<span class="_ _1"> </span>the</div><div class="t m1 xd h2 y320 ff1 fs0 fc0 sc0 ls0 ws0">output.<span class="_ _2d"> </span>Y<span class="_ _2"></span>et<span class="_ _9"> </span>this<span class="_ _9"> </span>highly<span class="_ _9"> </span>compatible<span class="_ _9"> </span>result<span class="_ _9"> </span>can<span class="_ _7"> </span>b<span class="_ _0"></span>e</div><div class="t m0 x7b h2 y321 ff1 fs0 fc0 sc0 ls0 ws0">view<span class="_ _e"></span>ed<span class="_ _4"> </span>b<span class="_ _e"></span>y<span class="_ _1"> </span>most<span class="_ _1"> </span>users.</div><div class="t m0 xd h3 y322 ff2 fs0 fc0 sc0 ls0 ws0">Seman<span class="_ _e"></span>tic<span class="_ _11"> </span><span class="ff3 fs1">HTML</span></div><div class="t m1 x18 h2 y322 ff1 fs0 fc0 sc0 ls0 ws0">is<span class="_ _4"> </span>b<span class="_ _0"></span>est<span class="_ _4"> </span>for<span class="_ _4"> </span>simple<span class="_ _4"> </span>T</div><div class="t m0 xc6 h2 y323 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 xc7 h2 y322 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _4"> </span>source</div><div class="t m1 xd h2 y324 ff1 fs0 fc0 sc0 ls0 ws0">files.<span class="_ _2e"> </span>All<span class="_ _4"> </span>semantic<span class="_ _4"> </span>information<span class="_ _4"> </span>is<span class="_ _4"> </span>preserv<span class="_ _e"></span>ed<span class="_ _4"> </span>in<span class="_ _4"> </span>the</div><div class="t m1 xd h2 y325 ff1 fs0 fc0 sc0 ls0 ws0">output,<span class="_ _11"> </span>w<span class="_ _0"></span>hic<span class="_ _e"></span>h<span class="_ _11"> </span>can<span class="_ _11"> </span>b<span class="_ _0"></span>e<span class="_ _7"> </span>further<span class="_ _11"> </span>pro<span class="_ _0"></span>cessed<span class="_ _11"> </span>by<span class="_ _9"> </span>other</div><div class="t m2 xd h2 y326 ff1 fs0 fc0 sc0 ls0 ws0">to<span class="_ _0"></span>ols.<span class="_ _7"> </span>In<span class="_ _1"> </span>particular,<span class="_ _1"> </span>math<span class="_ _1"> </span>formulas<span class="_ _8"> </span>may<span class="_ _8"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>rendered</div><div class="t m0 xd h2 y327 ff1 fs0 fc0 sc0 ls0 ws0">in<span class="_ _e"></span>teractively<span class="_ _1"> </span>with<span class="_ _1"> </span>latest<span class="_ _1"> </span>w<span class="_ _e"></span>eb<span class="_ _1"> </span>technologies.</div><div class="t m0 xd h3 y35 ff2 fs0 fc0 sc0 ls0 ws0">Presen<span class="_ _e"></span>tation<span class="_ _f"> </span><span class="ff3 fs1">HTML</span></div><div class="t m1 x64 h2 y35 ff1 fs0 fc0 sc0 ls0 ws0">is<span class="_ _9"> </span>best<span class="_ _9"> </span>when<span class="_ _9"> </span>complicated</div><div class="t m2 xd h2 y36 ff1 fs0 fc0 sc0 ls0 ws0">la<span class="_ _e"></span>yout,<span class="_ _8"> </span>adv<span class="_ _e"></span>anced<span class="_ _1"> </span>T</div><div class="t m0 xc8 h2 y328 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m2 x86 h2 y36 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _8"> </span>macros<span class="_ _1"> </span>and<span class="_ _1"> </span>pac<span class="_ _5"></span>k<span class="_ _e"></span>ages<span class="_ _8"> </span>are<span class="_ _1"> </span>used.</div><div class="t m17 xd h2 y37 ff1 fs0 fc0 sc0 ls0 ws0">It<span class="_ _1"> </span>is<span class="_ _1"> </span>also<span class="_ _1"> </span>suitable<span class="_ _1"> </span>when<span class="_ _4"> </span>the<span class="_ _8"> </span>source<span class="_ _1"> </span>files<span class="_ _4"> </span>are<span class="_ _8"> </span>not<span class="_ _1"> </span>av<span class="_ _2"></span>ail-</div><div class="t m18 xd h2 y38 ff1 fs0 fc0 sc0 ls0 ws0">able<span class="_ _1"> </span>at<span class="_ _1"> </span>all.<span class="_ _7"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>files<span class="_ _1"> </span>pro<span class="_ _0"></span>duced<span class="_ _1"> </span>from<span class="_ _1"> </span>other<span class="_ _4"> </span>tools<span class="_ _1"> </span>can</div><div class="t m0 x0 h2 y77 ff1 fs0 fc0 sc0 ls0 ws0">Lu<span class="_ _1"> </span>W<span class="_ _2"></span>ang<span class="_ _1"> </span>and<span class="_ _1"> </span>W<span class="_ _2"></span>anmin<span class="_ _1"> </span>Liu</div><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,427.347,null]'><div class="d m1d" style="border-style:none;position:absolute;left:175.779974px;bottom:1043.845856px;width:11.955000px;height:8.412000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,187.995,null]'><div class="d m1d" style="border-style:none;position:absolute;left:351.762405px;bottom:332.057098px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,488.12,null]'><div class="d m1d" style="border-style:none;position:absolute;left:652.778248px;bottom:1012.551948px;width:11.956000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,511.781,null]'><div class="d m1d" 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<div id="pf7" class="pf w0 h0" data-page-no="7"><div class="pc pc7 w0 h0"><img class="bi xc9 y329 w7 h22" alt="" 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"/><div class="t m0 x0 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">TUGb<span class="_ _0"></span>oat,<span class="_ _1"> </span>V<span class="_ _2"></span>olume<span class="_ _1"> </span>34<span class="_ _1"> </span>(2013),<span class="_ _1"> </span>No.<span class="_ _1"> </span>3<span class="_ _3"> </span>319</div><div class="t m2 x0 h2 y39 ff1 fs0 fc0 sc0 ls0 ws0">also b<span class="_ _0"></span>e supp<span class="_ _0"></span>orted.<span class="_ _7"> </span>Flexibilit<span class="_ _5"></span>y of semantic <span class="ff4 fs1">HTML </span>and</div><div class="t m0 x0 h2 y3a ff1 fs0 fc0 sc0 ls0 ws0">accuracy<span class="_ _1"> </span>of<span class="_ _1"> </span>image<span class="_ _1"> </span>are<span class="_ _1"> </span>clev<span class="_ _5"></span>erly<span class="_ _1"> </span>balanced.</div><div class="t m2 x0 h2 y32a ff1 fs0 fc0 sc0 ls0 ws0">In general<span class="_ _8"> </span>there is<span class="_ _8"> </span>no b<span class="_ _0"></span>est<span class="_ _8"> </span>approach for all situations.</div><div class="t m17 x0 h2 y32b ff1 fs0 fc0 sc0 ls0 ws0">Users<span class="_ _1"> </span>should<span class="_ _1"> </span>carefully<span class="_ _1"> </span>choose<span class="_ _4"> </span>the<span class="_ _8"> </span>b<span class="_ _0"></span>est<span class="_ _1"> </span>matching<span class="_ _1"> </span>one</div><div class="t m0 x0 h2 y32c ff1 fs0 fc0 sc0 ls0 ws0">according<span class="_ _1"> </span>their<span class="_ _1"> </span>sp<span class="_ _0"></span>ecific<span class="_ _1"> </span>concerns.</div><div class="t m1 x1 h2 y32d ff1 fs0 fc0 sc0 ls0 ws0">While<span class="_ _7"> </span>we<span class="_ _9"> </span>tried<span class="_ _11"> </span>our<span class="_ _7"> </span>b<span class="_ _0"></span>est<span class="_ _7"> </span>to<span class="_ _11"> </span>b<span class="_ _0"></span>e<span class="_ _7"> </span>complete<span class="_ _7"> </span>and</div><div class="t m1 x0 h2 y32e ff1 fs0 fc0 sc0 ls0 ws0">accurate,<span class="_ _9"> </span>it<span class="_ _9"> </span>is<span class="_ _9"> </span>quite<span class="_ _9"> </span>possible<span class="_ _9"> </span>that<span class="_ _9"> </span>we<span class="_ _4"> </span>hav<span class="_ _e"></span>e<span class="_ _9"> </span>missed</div><div class="t m1 x0 h2 y32f ff1 fs0 fc0 sc0 ls0 ws0">or<span class="_ _1"> </span>misundersto<span class="_ _0"></span>o<span class="_ _0"></span>d<span class="_ _1"> </span>some<span class="_ _1"> </span>approaches<span class="_ _1"> </span>due<span class="_ _1"> </span>to<span class="_ _1"> </span>the<span class="_ _4"> </span>lim-</div><div class="t m1 x0 h2 y330 ff1 fs0 fc0 sc0 ls0 ws0">itations<span class="_ _7"> </span>of<span class="_ _11"> </span>our<span class="_ _11"> </span>knowledge.<span class="_ _20"> </span>Please<span class="_ _7"> </span>contact<span class="_ _7"> </span>us<span class="_ _11"> </span>for</div><div class="t m0 x0 h2 y331 ff1 fs0 fc0 sc0 ls0 ws0">corrections<span class="_ _1"> </span>or<span class="_ _1"> </span>suggestions,<span class="_ _1"> </span>and<span class="_ _1"> </span>thank<span class="_ _1"> </span>y<span class="_ _5"></span>ou.</div><div class="t m0 x0 h3 y332 ff2 fs0 fc0 sc0 ls0 ws0">4<span class="_ _c"> </span>A<span class="_ _4"> </span>tour<span class="_ _4"> </span>of<span class="_ _4"> </span>p<span class="_ _0"></span>df2h<span class="_ _5"></span>tmlEX</div><div class="t m1 xc h2 y333 ff1 fs0 fc0 sc0 ls0 ws0">n<span class="_ _9"> </span>this<span class="_ _9"> </span>section<span class="_ _4"> </span>we<span class="_ _4"> </span>introduce<span class="_ _9"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX</span>,</div><div class="t m1 xc h2 y334 ff1 fs0 fc0 sc0 ls0 ws0">created<span class="_ _4"> </span>and<span class="_ _1"> </span>mostly<span class="_ _4"> </span>written<span class="_ _1"> </span>by<span class="_ _4"> </span>Lu<span class="_ _1"> </span>W<span class="_ _2"></span>ang,</div><div class="t m1 xc h2 y335 ff1 fs0 fc0 sc0 ls0 ws0">whic<span class="_ _5"></span>h<span class="_ _11"> </span>is<span class="_ _11"> </span>an<span class="_ _11"> </span>op<span class="_ _0"></span>en<span class="_ _11"> </span>source<span class="_ _11"> </span><span class="ff4 fs1">PDF<span class="_ _11"> </span></span>to<span class="_ _11"> </span><span class="ff4 fs1">HTML</span></div><div class="t m2 xc h2 y336 ff1 fs0 fc0 sc0 ls0 ws0">con<span class="_ _e"></span>verter.<span class="_ _7"> </span>It<span class="_ _8"> </span>generates<span class="_ _1"> </span>presentation <span class="ff4 fs1">HTML</span></div><div class="t m1e x0 h2 y337 ff1 fs0 fc0 sc0 ls0 ws0">do<span class="_ _0"></span>cumen<span class="_ _e"></span>ts,<span class="_ _4"> </span>utilizing<span class="_ _8"> </span>mo<span class="_ _0"></span>dern<span class="_ _1"> </span>W<span class="_ _2"></span>eb<span class="_ _1"> </span>technologies<span class="_ _8"> </span>such</div><div class="t m1 x0 h2 y338 ff1 fs0 fc0 sc0 ls0 ws0">as<span class="_ _4"> </span><span class="ff4 fs1">HTML</span>5,<span class="_ _1"> </span><span class="ff4 fs1">CSS</span>3,<span class="_ _4"> </span>Jav<span class="_ _2"></span>aScript,<span class="_ _4"> </span><span class="ff5">etc.</span>,<span class="_ _4"> </span>suc<span class="_ _e"></span>h<span class="_ _4"> </span>that<span class="_ _4"> </span>most</div><div class="t m2 x0 h2 y339 ff4 fs1 fc0 sc0 ls0 ws0">PDF<span class="_ _13"> </span><span class="ff1 fs0">features can b<span class="_ _0"></span>e<span class="_ _8"> </span>retained.<span class="_ _9"> </span>Esp<span class="_ _0"></span>ecially fonts, math</span></div><div class="t m0 x0 h2 y33a ff1 fs0 fc0 sc0 ls0 ws0">form<span class="_ _e"></span>ulas<span class="_ _4"> </span>an<span class="_ _5"></span>d<span class="_ _1"> </span>images<span class="_ _1"> </span>can<span class="_ _1"> </span>all<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>display<span class="_ _e"></span>ed<span class="_ _1"> </span>correctly<span class="_ _2"></span>.</div><div class="t m0 xca h13 y33b ff3 fs1 fc0 sc0 ls0 ws0">Figure<span class="_ _1"> </span>4<span class="ff4">:<span class="_ _9"> </span>Logo<span class="_ _8"> </span>of<span class="_ _8"> </span>p<span class="_ _0"></span>df2html<span class="ffa fs4">EX</span></span></div><div class="t m1 x1 h2 y33c ff1 fs0 fc0 sc0 ls0 ws0">p<span class="_ _0"></span>df2h<span class="_ _e"></span>tml<span class="ff4 fs1">EX<span class="_ _9"> </span></span>is<span class="_ _9"> </span>not<span class="_ _4"> </span>only<span class="_ _9"> </span>a<span class="_ _4"> </span><span class="ff5">c<span class="_ _e"></span>onverter<span class="ff1">,<span class="_ _9"> </span>but<span class="_ _9"> </span>also</span></span></div><div class="t m1 x0 h2 y33d ff1 fs0 fc0 sc0 ls0 ws0">a<span class="_ _4"> </span><span class="ff5">publishing<span class="_ _1"> </span>tool</span>.<span class="_ _f"> </span>It<span class="_ _4"> </span>is<span class="_ _1"> </span>designed<span class="_ _4"> </span>for<span class="_ _1"> </span>many<span class="_ _1"> </span>different</div><div class="t m0 x0 h2 y33e ff1 fs0 fc0 sc0 ls0 ws0">situations,<span class="_ _1"> </span>for<span class="_ _1"> </span>example:</div><div class="t m0 x0 h3 y33f ff2 fs0 fc0 sc0 ls0 ws0">Scenario<span class="_ _30"> </span>1</div><div class="t m1 xcb h2 y33f ff1 fs0 fc0 sc0 ls0 ws0">My<span class="_ _7"> </span>sister<span class="_ _7"> </span>wan<span class="_ _e"></span>ts<span class="_ _11"> </span>to<span class="_ _7"> </span>put<span class="_ _7"> </span>her<span class="_ _11"> </span>resum´<span class="_ _32"></span>e</div><div class="t m1 x0 h2 y340 ff1 fs0 fc0 sc0 ls0 ws0">on<span class="_ _1"> </span>her<span class="_ _4"> </span>online<span class="_ _1"> </span>homepage.<span class="_ _f"> </span>She<span class="_ _4"> </span>w<span class="_ _e"></span>ants<span class="_ _1"> </span>the<span class="_ _1"> </span>resum´<span class="_ _32"></span>e<span class="_ _4"> </span>to</div><div class="t m1 x0 h2 y341 ff1 fs0 fc0 sc0 ls0 ws0">b<span class="_ _0"></span>e<span class="_ _7"> </span>stored<span class="_ _7"> </span>into<span class="_ _9"> </span>one<span class="_ _7"> </span>single<span class="_ _7"> </span>file<span class="_ _7"> </span>such<span class="_ _9"> </span>that<span class="_ _7"> </span>it<span class="_ _7"> </span>can<span class="_ _7"> </span>b<span class="_ _0"></span>e</div><div class="t ma x0 h2 y342 ff1 fs0 fc0 sc0 ls0 ws0">easily<span class="_ _1"> </span>do<span class="_ _e"></span>wnloaded<span class="_ _1"> </span>by<span class="_ _8"> </span>others.<span class="_ _7"> </span>She<span class="_ _1"> </span>also<span class="_ _1"> </span>needs<span class="_ _1"> </span>to<span class="_ _1"> </span>add</div><div class="t m2 x0 h2 y343 ff1 fs0 fc0 sc0 ls0 ws0">Ja<span class="_ _e"></span>v<span class="_ _e"></span>aScript<span class="_ _1"> </span>co<span class="_ _0"></span>de<span class="_ _8"> </span>to<span class="_ _8"> </span>track<span class="_ _8"> </span>how many<span class="_ _8"> </span>p<span class="_ _0"></span>eople<span class="_ _8"> </span>hav<span class="_ _e"></span>e<span class="_ _8"> </span>read</div><div class="t m0 x0 h2 y344 ff1 fs0 fc0 sc0 ls0 ws0">her<span class="_ _1"> </span>resum<span class="_ _5"></span>´<span class="_ _32"></span>e.</div><div class="t m0 x0 h3 y345 ff2 fs0 fc0 sc0 ls0 ws0">Scenario<span class="_ _4"> </span>2</div><div class="t m1 xcc h2 y345 ff1 fs0 fc0 sc0 ls0 ws0">A<span class="_ _1"> </span>b<span class="_ _0"></span>o<span class="_ _0"></span>ok<span class="_ _1"> </span>publisher<span class="_ _1"> </span>wan<span class="_ _e"></span>ts<span class="_ _1"> </span>to<span class="_ _1"> </span>put<span class="_ _1"> </span>some</div><div class="t m2 x0 h2 y346 ff1 fs0 fc0 sc0 ls0 ws0">sample<span class="_ _14"> </span>b<span class="_ _0"></span>o<span class="_ _0"></span>oks<span class="_ _14"> </span>online<span class="_ _d"> </span>to<span class="_ _14"> </span>attract<span class="_ _14"> </span>readers.<span class="_ _9"> </span>The<span class="_ _d"> </span>publisher</div><div class="t m2 x0 h2 y347 ff1 fs0 fc0 sc0 ls0 ws0">do<span class="_ _0"></span>es not<span class="_ _14"> </span>wan<span class="_ _e"></span>t readers to<span class="_ _d"> </span>w<span class="_ _e"></span>ait for too long before they</div><div class="t m2e x0 h2 y348 ff1 fs0 fc0 sc0 ls0 ws0">can<span class="_ _1"> </span>read<span class="_ _8"> </span>any<span class="_ _8"> </span>page,<span class="_ _1"> </span>thus<span class="_ _8"> </span>pages<span class="_ _1"> </span>are<span class="_ _1"> </span>b<span class="_ _0"></span>etter<span class="_ _1"> </span>conv<span class="_ _e"></span>erted</div><div class="t m7 x0 h2 y349 ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _1"> </span>stored<span class="_ _1"> </span>separately<span class="_ _2"></span>.<span class="_ _7"> </span>Images<span class="_ _1"> </span>and<span class="_ _1"> </span>fonts<span class="_ _8"> </span>should<span class="_ _1"> </span>also</div><div class="t m1 x0 h2 y34a ff1 fs0 fc0 sc0 ls0 ws0">b<span class="_ _0"></span>e<span class="_ _7"> </span>stored<span class="_ _11"> </span>in<span class="_ _11"> </span>individual<span class="_ _11"> </span>files<span class="_ _11"> </span>such<span class="_ _7"> </span>that<span class="_ _11"> </span>users<span class="_ _11"> </span>may</div><div class="t m0 x0 h2 y34b ff1 fs0 fc0 sc0 ls0 ws0">b<span class="_ _0"></span>enefit<span class="_ _1"> </span>from<span class="_ _1"> </span>w<span class="_ _5"></span>eb<span class="_ _1"> </span>cac<span class="_ _e"></span>hes.</div><div class="t m0 x0 h3 y30 ff2 fs0 fc0 sc0 ls0 ws0">Scenario 3</div><div class="t m2 xb0 h2 y30 ff1 fs0 fc0 sc0 ls0 ws0">A cloud storage<span class="_ _8"> </span>service provider w<span class="_ _e"></span>ants</div><div class="t m1 x0 h2 y31 ff1 fs0 fc0 sc0 ls0 ws0">to<span class="_ _4"> </span>provide<span class="_ _4"> </span>a<span class="_ _4"> </span><span class="ff4 fs1">PDF<span class="_ _4"> </span></span>preview<span class="_ _4"> </span>feature<span class="_ _4"> </span>to<span class="_ _4"> </span>their<span class="_ _4"> </span>service,</div><div class="t m1 x0 h2 y32 ff1 fs0 fc0 sc0 ls0 ws0">suc<span class="_ _5"></span>h<span class="_ _7"> </span>that<span class="_ _11"> </span>users<span class="_ _7"> </span>may<span class="_ _7"> </span>read<span class="_ _7"> </span>their<span class="_ _11"> </span>files<span class="_ _7"> </span>online.<span class="_ _20"> </span>The</div><div class="t m20 x0 h2 y33 ff1 fs0 fc0 sc0 ls0 ws0">service<span class="_ _1"> </span>provider<span class="_ _8"> </span>needs<span class="_ _1"> </span>to<span class="_ _1"> </span>design<span class="_ _1"> </span>their<span class="_ _4"> </span>o<span class="_ _e"></span>wn<span class="_ _1"> </span>viewer<span class="_ _8"> </span>to</div><div class="t m1 x0 h2 y34 ff1 fs0 fc0 sc0 ls0 ws0">matc<span class="_ _5"></span>h<span class="_ _4"> </span>the<span class="_ _9"> </span>theme<span class="_ _9"> </span>and<span class="_ _4"> </span>b<span class="_ _0"></span>ehaviour<span class="_ _4"> </span>of<span class="_ _9"> </span>their<span class="_ _4"> </span>web<span class="_ _4"> </span>site.</div><div class="t m1 x0 h2 y35 ff1 fs0 fc0 sc0 ls0 ws0">They<span class="_ _1"> </span>also<span class="_ _4"> </span>w<span class="_ _e"></span>ant<span class="_ _8"> </span>to<span class="_ _4"> </span>attac<span class="_ _e"></span>h<span class="_ _1"> </span>advertisemen<span class="_ _e"></span>ts<span class="_ _4"> </span>based<span class="_ _8"> </span>on</div><div class="t m1 x0 h2 y36 ff1 fs0 fc0 sc0 ls0 ws0">the<span class="_ _9"> </span>con<span class="_ _e"></span>tents<span class="_ _4"> </span>of<span class="_ _9"> </span>the<span class="_ _9"> </span>files.<span class="_ _12"> </span>Adv<span class="_ _e"></span>anced<span class="_ _9"> </span>users<span class="_ _9"> </span>may<span class="_ _4"> </span>b<span class="_ _0"></span>e</div><div class="t m2 x0 h2 y37 ff1 fs0 fc0 sc0 ls0 ws0">allo<span class="_ _e"></span>wed to leav<span class="_ _e"></span>e<span class="_ _8"> </span>marks and discuss<span class="_ _8"> </span>with others<span class="_ _8"> </span>ab<span class="_ _0"></span>out</div><div class="t m10 x0 h2 y38 ff1 fs0 fc0 sc0 ls0 ws0">particular<span class="_ _8"> </span>parts<span class="_ _1"> </span>of<span class="_ _1"> </span>the<span class="_ _1"> </span>do<span class="_ _0"></span>cumen<span class="_ _e"></span>ts.<span class="_ _7"> </span>In<span class="_ _1"> </span>this<span class="_ _1"> </span>case<span class="_ _8"> </span>the</div><div class="t m2 xd h2 y39 ff1 fs0 fc0 sc0 ls0 ws0">service<span class="_ _1"> </span>pro<span class="_ _5"></span>vider<span class="_ _1"> </span>needs<span class="_ _1"> </span>the<span class="_ _1"> </span>finest<span class="_ _1"> </span>control<span class="_ _17"> </span>—<span class="_ _10"> </span>they<span class="_ _1"> </span>need</div><div class="t m1 xd h2 y3a ff1 fs0 fc0 sc0 ls0 ws0">to<span class="_ _1"> </span>access<span class="_ _4"> </span>ev<span class="_ _e"></span>ery<span class="_ _1"> </span>single<span class="_ _4"> </span>elemen<span class="_ _e"></span>t<span class="_ _1"> </span>of<span class="_ _4"> </span>the<span class="_ _1"> </span>do<span class="_ _0"></span>cumen<span class="_ _e"></span>t<span class="_ _4"> </span>for</div><div class="t m0 xd h2 y3b ff1 fs0 fc0 sc0 ls0 ws0">their<span class="_ _1"> </span>customizations.</div><div class="t m1 x7b h2 y34c ff1 fs0 fc0 sc0 ls0 ws0">W<span class="_ _2"></span>e<span class="_ _4"> </span>can<span class="_ _4"> </span>see<span class="_ _4"> </span>that<span class="_ _4"> </span>different<span class="_ _4"> </span>forms<span class="_ _4"> </span>of<span class="_ _4"> </span><span class="ff4 fs1">HTML<span class="_ _4"> </span></span>files<span class="_ _4"> </span>are</div><div class="t m2 xd h2 y34d ff1 fs0 fc0 sc0 ls0 ws0">desired in different scenarios,<span class="_ _8"> </span>and flexibility is alwa<span class="_ _e"></span>ys</div><div class="t m1 xd h2 y34e ff1 fs0 fc0 sc0 ls0 ws0">necessary<span class="_ _2"></span>.<span class="_ _b"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX<span class="_ _9"> </span></span>is<span class="_ _7"> </span>indeed<span class="_ _7"> </span>designed<span class="_ _9"> </span>for<span class="_ _7"> </span>all</div><div class="t m2 xd h2 y2fc ff1 fs0 fc0 sc0 ls0 ws0">these<span class="_ _8"> </span>scenarios<span class="_ _1"> </span>and<span class="_ _1"> </span>many<span class="_ _8"> </span>others;<span class="_ _1"> </span>some<span class="_ _1"> </span>features<span class="_ _1"> </span>hav<span class="_ _e"></span>e</div><div class="t m0 xd h2 y34f ff1 fs0 fc0 sc0 ls0 ws0">b<span class="_ _0"></span>een<span class="_ _1"> </span>requested<span class="_ _1"> </span>or<span class="_ _1"> </span>implemen<span class="_ _5"></span>ted<span class="_ _1"> </span>b<span class="_ _5"></span>y<span class="_ _1"> </span>users.</div><div class="t m1 xe h2 y350 ff1 fs0 fc0 sc0 ls0 ws0">In<span class="_ _4"> </span>this<span class="_ _9"> </span>section<span class="_ _9"> </span>w<span class="_ _e"></span>e<span class="_ _9"> </span>will<span class="_ _9"> </span>in<span class="_ _e"></span>tro<span class="_ _0"></span>duce<span class="_ _9"> </span>a<span class="_ _9"> </span>few<span class="_ _4"> </span>useful</div><div class="t m1 xd h2 y351 ff1 fs0 fc0 sc0 ls0 ws0">features<span class="_ _4"> </span>and<span class="_ _4"> </span>explore<span class="_ _4"> </span>some<span class="_ _4"> </span>internal<span class="_ _4"> </span>mech<span class="_ _5"></span>anisms<span class="_ _4"> </span>of</div><div class="t m1 xd h2 y352 ff1 fs0 fc0 sc0 ls0 ws0">p<span class="_ _0"></span>df2h<span class="_ _e"></span>tml<span class="ff4 fs1">EX</span>.<span class="_ _6"> </span>More<span class="_ _7"> </span>information,<span class="_ _11"> </span>including<span class="_ _7"> </span>source</div><div class="t m26 xd h2 y353 ff1 fs0 fc0 sc0 ls0 ws0">co<span class="_ _0"></span>de<span class="_ _1"> </span>and<span class="_ _1"> </span>license<span class="_ _1"> </span>terms,<span class="_ _1"> </span>is<span class="_ _1"> </span>at<span class="_ _4"> </span>the<span class="_ _8"> </span>pro<span class="_ _18"></span>ject<span class="_ _1"> </span>home<span class="_ _1"> </span>page:</div><div class="t m0 xd h4 y354 ff6 fs0 fc0 sc0 ls0 ws0">https://github.com/coolwanglu/pdf2htmlEX</div><div class="t m0 xd h3 y355 ff2 fs0 fc0 sc0 ls0 ws0">4.1<span class="_ _c"> </span>Quic<span class="_ _e"></span>k<span class="_ _4"> </span>start</div><div class="t m2 x7b h2 y356 ff1 fs0 fc0 sc0 ls0 ws0">Throughout this<span class="_ _8"> </span>section,<span class="_ _8"> </span>a sample<span class="_ _8"> </span><span class="ff4 fs1">PDF<span class="_ _13"> </span></span>file<span class="_ _8"> </span>is used<span class="_ _8"> </span>to</div><div class="t m2e xd h2 y357 ff1 fs0 fc0 sc0 ls0 ws0">demonstrate<span class="_ _1"> </span>differen<span class="_ _e"></span>t<span class="_ _1"> </span>features<span class="_ _1"> </span>of<span class="_ _1"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX</span>.<span class="_ _9"> </span>The</div><div class="t m4 xd h2 y358 ff1 fs0 fc0 sc0 ls0 ws0">file,</div><div class="t m0 x1b h4 y358 ff6 fs0 fc0 sc0 ls0 ws0">integral.pdf</div><div class="t m4 xcd h2 y358 ff1 fs0 fc0 sc0 ls0 ws0">,<span class="_ _1"> </span>con<span class="_ _5"></span>tains<span class="_ _1"> </span>4<span class="_ _1"> </span>pages<span class="_ _1"> </span>from<span class="_ _1"> </span>the<span class="_ _1"> </span>b<span class="_ _0"></span>o<span class="_ _0"></span>ok</div><div class="t m1 x7b h2 y359 ff5 fs0 fc0 sc0 ls0 ws0">Differ<span class="_ _e"></span>ential<span class="_ _4"> </span>and<span class="_ _1"> </span>Inte<span class="_ _e"></span>gr<span class="_ _e"></span>al<span class="_ _4"> </span>II<span class="_ _11"> </span><span class="ff1">[</span></div><div class="t m0 xce h2 y359 ff1 fs0 fc0 sc0 ls0 ws0">16</div><div class="t m1 xcf h2 y359 ff1 fs0 fc0 sc0 ls0 ws0">,</div><div class="t m0 xbc h2 y359 ff1 fs0 fc0 sc0 ls0 ws0">36</div><div class="t m1 xd0 h2 y359 ff1 fs0 fc0 sc0 ls0 ws0">],<span class="_ _1"> </span>which<span class="_ _8"> </span>consists</div><div class="t m30 xd h2 y35a ff1 fs0 fc0 sc0 ls0 ws0">of<span class="_ _8"> </span>Japanese<span class="_ _1"> </span>characters,<span class="_ _8"> </span>mathematical<span class="_ _1"> </span>symbols<span class="_ _1"> </span>and</div><div class="t m1 xd h2 y35b ff1 fs0 fc0 sc0 ls0 ws0">form<span class="_ _5"></span>ulas,<span class="_ _1"> </span>figures,<span class="_ _4"> </span>images<span class="_ _1"> </span>and<span class="_ _4"> </span>delicate<span class="_ _1"> </span>lay<span class="_ _e"></span>outs.<span class="_ _f"> </span>W<span class="_ _2"></span>e</div><div class="t m2 xd h2 y35c ff1 fs0 fc0 sc0 ls0 ws0">b<span class="_ _0"></span>eliev<span class="_ _e"></span>e<span class="_ _1"> </span>that<span class="_ _1"> </span>it<span class="_ _1"> </span>reflects<span class="_ _8"> </span>common<span class="_ _1"> </span>elements<span class="_ _8"> </span>used<span class="_ _1"> </span>in<span class="_ _8"> </span>real</div><div class="t m0 xd h2 y35d ff1 fs0 fc0 sc0 ls0 ws0">use<span class="_ _1"> </span>cases.</div><div class="t m0 xe h2 y35e ff1 fs0 fc0 sc0 ls0 ws0">T<span class="_ _2"></span>o<span class="_ _1"> </span>start<span class="_ _1"> </span>with,<span class="_ _1"> </span>w<span class="_ _5"></span>e<span class="_ _1"> </span>simply<span class="_ _1"> </span>execute</div><div class="t m0 x9e h23 y35f ff14 fs4 fc0 sc0 ls0 ws0">$<span class="_ _9"> </span>pdf2html<span class="fs2">EX<span class="_ _9"> </span></span>--fit-width<span class="_ _9"> </span>1024<span class="_ _7"> </span>integral.pdf</div><div class="t m14 x7b h2 y360 ff1 fs0 fc0 sc0 ls0 ws0">whic<span class="_ _5"></span>h<span class="_ _8"> </span>pro<span class="_ _0"></span>duces<span class="_ _1"> </span>a<span class="_ _1"> </span><span class="ff5">single<span class="_ _1"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span></span>file</div><div class="t m0 xd1 h4 y360 ff6 fs0 fc0 sc0 ls0 ws0">integral.html</div><div class="t m14 xd2 h2 y360 ff1 fs0 fc0 sc0 ls0 ws0">.</div><div class="t m1 x7b h2 y361 ff1 fs0 fc0 sc0 ls0 ws0">The<span class="_ _8"> </span>result<span class="_ _1"> </span>is<span class="_ _1"> </span>shown<span class="_ _8"> </span>in<span class="_ _1"> </span>Figure<span class="_ _1"> </span>5,</div><div class="t m0 xbc h6 y362 ff8 fs2 fc0 sc0 ls0 ws0">7</div><div class="t m1 xd3 h2 y361 ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _8"> </span>we<span class="_ _8"> </span>challenge</div><div class="t m1 xd h2 y363 ff1 fs0 fc0 sc0 ls0 ws0">the<span class="_ _4"> </span>readers<span class="_ _4"> </span>to<span class="_ _4"> </span>find<span class="_ _9"> </span>an<span class="_ _e"></span>y<span class="_ _9"> </span>evidence<span class="_ _4"> </span>or<span class="_ _4"> </span>clues<span class="_ _4"> </span>that<span class="_ _4"> </span>the</div><div class="t md xd h2 y364 ff1 fs0 fc0 sc0 ls0 ws0">screenshot<span class="_ _1"> </span>shows<span class="_ _8"> </span>an<span class="_ _1"> </span><span class="ff4 fs1">HTML<span class="_ _4"> </span></span>file<span class="_ _8"> </span>instead<span class="_ _1"> </span>of<span class="_ _4"> </span><span class="ff4 fs1">PDF</span>.<span class="_ _9"> </span>(Ex-</div><div class="t m0 xd h2 y365 ff1 fs0 fc0 sc0 ls0 ws0">cept<span class="_ _1"> </span>for<span class="_ _1"> </span>the<span class="_ _1"> </span>title<span class="_ _1"> </span>bar<span class="_ _1"> </span>of<span class="_ _1"> </span>course.)</div><div class="t m1 xe h2 y366 ff1 fs0 fc0 sc0 ls0 ws0">The</div><div class="t m0 xa0 h4 y366 ff6 fs0 fc0 sc0 ls0 ws0">--fit-width<span class="_ _33"> </span>1024</div><div class="t m1 x82 h2 y366 ff1 fs0 fc0 sc0 ls0 ws0">option<span class="_ _f"> </span>sp<span class="_ _0"></span>ecifies<span class="_ _f"> </span>that</div><div class="t m1 xd h2 y367 ff1 fs0 fc0 sc0 ls0 ws0">eac<span class="_ _5"></span>h<span class="_ _9"> </span>page<span class="_ _9"> </span>should<span class="_ _4"> </span>b<span class="_ _0"></span>e<span class="_ _9"> </span>squeezed<span class="_ _9"> </span>or<span class="_ _9"> </span>stretched<span class="_ _4"> </span>to<span class="_ _9"> </span>the</div><div class="t m2 x7b h2 y368 ff1 fs0 fc0 sc0 ls0 ws0">width of 1024 pixels.<span class="_ _9"> </span>The zoom ratio can b<span class="_ _0"></span>e adjusted</div><div class="t m0 x7b h2 y369 ff1 fs0 fc0 sc0 ls0 ws0">with<span class="_ _1"> </span>similar<span class="_ _1"> </span>options:<span class="_ _7"> </span><span class="ff6">--fit-height<span class="_ _1"> </span></span>and<span class="_ _1"> </span><span class="ff6">--zoom</span>.</div><div class="t m1 xe h2 y36a ff1 fs0 fc0 sc0 ls0 ws0">It<span class="_ _4"> </span>is<span class="_ _1"> </span>p<span class="_ _0"></span>ossible<span class="_ _4"> </span>to<span class="_ _1"> </span>conv<span class="_ _e"></span>ert<span class="_ _4"> </span>only<span class="_ _4"> </span>a<span class="_ _1"> </span>few<span class="_ _4"> </span>pages<span class="_ _1"> </span>of<span class="_ _4"> </span>a</div><div class="t m0 xd h2 y36b ff4 fs1 fc0 sc0 ls0 ws0">PDF<span class="_ _1"> </span><span class="ff1 fs0">file,<span class="_ _1"> </span>for<span class="_ _1"> </span>example</span></div><div class="t m0 x9e h23 y36c ff14 fs4 fc0 sc0 ls0 ws0">$<span class="_ _9"> </span>pdf2html<span class="fs2">EX<span class="_ _9"> </span></span>-f<span class="_ _9"> </span>2<span class="_ _7"> </span>-l<span class="_ _9"> </span>3<span class="_ _9"> </span>integral.pdf</div><div class="t m0 xd h2 y36d ff1 fs0 fc0 sc0 ls0 ws0">con<span class="_ _e"></span>verts<span class="_ _1"> </span>only<span class="_ _1"> </span>the<span class="_ _1"> </span>second<span class="_ _1"> </span>page<span class="_ _1"> </span>and<span class="_ _1"> </span>the<span class="_ _1"> </span>third<span class="_ _1"> </span>page.</div><div class="t m0 xd h3 y36e ff2 fs0 fc0 sc0 ls0 ws0">4.2<span class="_ _c"> </span>Separating<span class="_ _4"> </span>resource<span class="_ _4"> </span>files</div><div class="t m1 xd h2 y36f ff1 fs0 fc0 sc0 ls0 ws0">By<span class="_ _4"> </span>default<span class="_ _4"> </span>everything<span class="_ _4"> </span>is<span class="_ _4"> </span>combined<span class="_ _4"> </span>in<span class="_ _e"></span>to<span class="_ _9"> </span>one<span class="_ _4"> </span>single</div><div class="t m1 xd h2 y370 ff4 fs1 fc0 sc0 ls0 ws0">HTML<span class="_ _9"> </span><span class="ff1 fs0">file,<span class="_ _9"> </span>which<span class="_ _4"> </span>is<span class="_ _9"> </span>go<span class="_ _0"></span>o<span class="_ _0"></span>d<span class="_ _9"> </span>for<span class="_ _9"> </span>creating<span class="_ _9"> </span>archiv<span class="_ _e"></span>es<span class="_ _9"> </span>or</span></div><div class="t m18 xd h2 y371 ff1 fs0 fc0 sc0 ls0 ws0">p<span class="_ _0"></span>erforming<span class="_ _1"> </span>tests.<span class="_ _7"> </span>How<span class="_ _e"></span>ev<span class="_ _e"></span>er,<span class="_ _4"> </span>it<span class="_ _8"> </span>is<span class="_ _1"> </span>not<span class="_ _1"> </span>a<span class="_ _1"> </span>go<span class="_ _0"></span>o<span class="_ _0"></span>d<span class="_ _1"> </span>practice</div><div class="t m3 x7b h2 y372 ff1 fs0 fc0 sc0 ls0 ws0">when<span class="_ _1"> </span>publishing<span class="_ _1"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>do<span class="_ _0"></span>cumen<span class="_ _5"></span>ts<span class="_ _1"> </span>online;<span class="_ _1"> </span>often<span class="_ _1"> </span>we</div><div class="t m1 x7b h2 y373 ff1 fs0 fc0 sc0 ls0 ws0">w<span class="_ _5"></span>an<span class="_ _5"></span>t<span class="_ _4"> </span>resource<span class="_ _1"> </span>files<span class="_ _4"> </span>(fon<span class="_ _e"></span>ts,<span class="_ _4"> </span><span class="ff4 fs1">CSS</span>,<span class="_ _4"> </span>Ja<span class="_ _e"></span>v<span class="_ _e"></span>aScript,<span class="_ _4"> </span>images</div><div class="t m1f x7b h2 y374 ff5 fs0 fc0 sc0 ls0 ws0">etc<span class="ff1">.)<span class="_ _8"> </span>to<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>stored<span class="_ _1"> </span>separately<span class="_ _1"> </span>in<span class="_ _1"> </span>order<span class="_ _8"> </span>to<span class="_ _1"> </span>reduce<span class="_ _1"> </span>size</span></div><div class="t m0 xd h2 y375 ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _1"> </span>impro<span class="_ _e"></span>ve<span class="_ _1"> </span>efficiency<span class="_ _2"></span>.</div><div class="t m7 xe h2 y376 ff1 fs0 fc0 sc0 ls0 ws0">With<span class="_ _1"> </span>the</div><div class="t m0 xd4 h4 y376 ff6 fs0 fc0 sc0 ls0 ws0">--embed</div><div class="t m7 xd5 h2 y376 ff1 fs0 fc0 sc0 ls0 ws0">option,<span class="_ _1"> </span>w<span class="_ _5"></span>e<span class="_ _1"> </span>can<span class="_ _1"> </span>decide<span class="_ _1"> </span>which</div><div class="t m15 xd h2 y377 ff1 fs0 fc0 sc0 ls0 ws0">t<span class="_ _5"></span>yp<span class="_ _0"></span>es<span class="_ _8"> </span>of<span class="_ _1"> </span>resource<span class="_ _1"> </span>files<span class="_ _1"> </span>are<span class="_ _1"> </span>embedded<span class="_ _1"> </span>and<span class="_ _1"> </span>whic<span class="_ _5"></span>h<span class="_ _1"> </span>are</div><div class="t m0 xd h2 y378 ff1 fs0 fc0 sc0 ls0 ws0">not.<span class="_ _7"> </span>F<span class="_ _2"></span>or<span class="_ _1"> </span>example,</div><div class="t m0 x9e h23 y379 ff14 fs4 fc0 sc0 ls0 ws0">$<span class="_ _9"> </span>pdf2html<span class="fs2">EX<span class="_ _9"> </span></span>--embed<span class="_ _9"> </span>fi<span class="_ _7"> </span>integral.pdf</div><div class="t m0 x1a h7 y73 ff9 fs3 fc0 sc0 ls0 ws0">7</div><div class="t m1 x1b h8 y74 ffa fs4 fc0 sc0 ls0 ws0">Mozilla<span class="_ _13"> </span>Firefox<span class="_ _13"> </span>24<span class="_ _8"> </span>on<span class="_ _8"> </span>Ubuntu<span class="_ _13"> </span>13.04<span class="_ _8"> </span>is<span class="_ _8"> </span>used<span class="_ _8"> </span>for<span class="_ _13"> </span>all<span class="_ _8"> </span>the</div><div class="t m0 xd h8 y38 ffa fs4 fc0 sc0 ls0 ws0">demonstrations.</div><div class="t m0 x1c h2 y77 ff1 fs0 fc0 sc0 ls0 ws0">Online<span class="_ _1"> </span>publishing<span class="_ _1"> </span>via<span class="_ _1"> </span>p<span class="_ _0"></span>df2h<span class="_ _e"></span>tm<span class="_ _0"></span>l<span class="ff4 fs1">EX</span></div><a class="l" href="https://github.com/coolwanglu/pdf2htmlEX"><div class="d m1d" style="border-style:none;position:absolute;left:523.873046px;bottom:932.609673px;width:211.206000px;height:11.124000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,355.367,null]'><div class="d m1d" style="border-style:none;position:absolute;left:734.248157px;bottom:819.613281px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",314.092,390.984,null]'><div class="d m1d" style="border-style:none;position:absolute;left:761.370771px;bottom:819.613281px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf8" data-dest-detail='[8,"XYZ",232.678,464.839,null]'><div class="d m1d" style="border-style:none;position:absolute;left:747.197072px;bottom:649.676131px;width:7.073000px;height:12.040000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf7" data-dest-detail='[7,"XYZ",333.381,91.357,null]'><div class="d m1d" style="border-style:none;position:absolute;left:760.422065px;bottom:649.676131px;width:6.461000px;height:12.040000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.673203,0.000000,0.000000,1.673203,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x0 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">320<span class="_ _3"> </span>TUGb<span class="_ _0"></span>oat,<span class="_ _1"> </span>V<span class="_ _2"></span>olume<span class="_ _1"> </span>34<span class="_ _1"> </span>(2013),<span class="_ _1"> </span>No.<span class="_ _1"> </span>3</div><div class="t m0 xa6 h13 y37b ff3 fs1 fc0 sc0 ls0 ws0">Figure<span class="_ _1"> </span>5<span class="ff4">:<span class="_ _9"> </span>An<span class="_ _8"> </span><span class="ffa fs4">HTML<span class="_ _8"> </span></span>do<span class="_ _0"></span>cument<span class="_ _8"> </span>produced<span class="_ _1"> </span>b<span class="_ _5"></span>y<span class="_ _8"> </span>p<span class="_ _0"></span>df2html<span class="ffa fs4">EX</span>.</span></div><div class="t m0 x0 h5 y37c ff3 fs1 fc0 sc0 ls0 ws0">Figure<span class="_ _8"> </span>6</div><div class="t m1 x6e h13 y37c ff4 fs1 fc0 sc0 ls0 ws0">:<span class="_ _7"> </span>Ab<span class="_ _0"></span>ov<span class="_ _e"></span>e:<span class="_ _7"> </span>by<span class="_ _13"> </span>default<span class="_ _8"> </span>all<span class="_ _8"> </span>resources<span class="_ _8"> </span>are</div><div class="t m1 x0 h13 y37d ff4 fs1 fc0 sc0 ls0 ws0">em<span class="_ _5"></span>b<span class="_ _0"></span>edded<span class="_ _13"> </span>in<span class="_ _8"> </span>the<span class="_ _8"> </span><span class="ffa fs4">HTML<span class="_ _8"> </span></span>file.<span class="_ _11"> </span>Belo<span class="_ _5"></span>w:<span class="_ _7"> </span>with<span class="_ _8"> </span>the</div><div class="t m0 xd6 h25 y37d ff15 fs1 fc0 sc0 ls0 ws0">--embed</div><div class="t m0 x0 h25 y37e ff15 fs1 fc0 sc0 ls0 ws0">fi</div><div class="t m1 x78 h13 y37e ff4 fs1 fc0 sc0 ls0 ws0">option,<span class="_ _8"> </span>fon<span class="_ _5"></span>ts<span class="_ _8"> </span>and<span class="_ _13"> </span>images<span class="_ _8"> </span>are<span class="_ _8"> </span>stored<span class="_ _8"> </span>into<span class="_ _13"> </span>separate</div><div class="t m0 x0 h13 y37f ff4 fs1 fc0 sc0 ls0 ws0">files<span class="_ _8"> </span>and<span class="_ _8"> </span>linked<span class="_ _13"> </span>to<span class="_ _8"> </span>the<span class="_ _8"> </span><span class="ffa fs4">HTML<span class="_ _1"> </span></span>file.</div><div class="t m2 x0 h2 y380 ff1 fs0 fc0 sc0 ls0 ws0">stores all<span class="_ _8"> </span>fonts and<span class="_ _8"> </span>images<span class="_ _8"> </span>in<span class="_ _8"> </span>separate<span class="_ _8"> </span>files,<span class="_ _8"> </span>as<span class="_ _8"> </span>sho<span class="_ _5"></span>wn</div><div class="t m2 x0 h2 y381 ff1 fs0 fc0 sc0 ls0 ws0">in<span class="_ _8"> </span>Figure<span class="_ _8"> </span>6.<span class="_ _7"> </span>There<span class="_ _1"> </span>are<span class="_ _8"> </span>also<span class="_ _8"> </span>sp<span class="_ _0"></span>ecific<span class="_ _1"> </span>options<span class="_ _8"> </span>including</div><div class="t m0 xd7 h2 y382 ff6 fs0 fc0 sc0 ls0 ws0">--embed-css<span class="ff1">,<span class="_ _1"> </span></span>--embed-font<span class="ff1">,<span class="_ _1"> </span></span>--embed-image<span class="ff1">,<span class="_ _1"> </span><span class="ff5">etc</span>.</span></div><div class="t m0 x0 h3 y383 ff2 fs0 fc0 sc0 ls0 ws0">4.3<span class="_ _c"> </span>Splitting<span class="_ _4"> </span>pages</div><div class="t m12 x0 h2 y33 ff1 fs0 fc0 sc0 ls0 ws0">With<span class="_ _1"> </span>a<span class="_ _1"> </span>large<span class="_ _1"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>file<span class="_ _1"> </span>containing<span class="_ _8"> </span>hundreds<span class="_ _8"> </span>of<span class="_ _1"> </span>pages,</div><div class="t m0 x0 h2 y34 ff1 fs0 fc0 sc0 ls0 ws0">often<span class="_ _1"> </span>w<span class="_ _5"></span>e<span class="_ _1"> </span>ha<span class="_ _e"></span>ve<span class="_ _1"> </span>to<span class="_ _1"> </span>do<span class="_ _e"></span>wnload<span class="_ _1"> </span>the<span class="_ _1"> </span>whole<span class="_ _1"> </span>file<span class="_ _1"> </span>even<span class="_ _8"> </span>if<span class="_ _1"> </span>we</div><div class="t m10 x0 h2 y35 ff1 fs0 fc0 sc0 ls0 ws0">w<span class="_ _5"></span>an<span class="_ _e"></span>t<span class="_ _1"> </span>to<span class="_ _1"> </span>take<span class="_ _8"> </span>a<span class="_ _1"> </span>lo<span class="_ _0"></span>ok<span class="_ _1"> </span>at<span class="_ _8"> </span>only<span class="_ _1"> </span>a<span class="_ _1"> </span>few<span class="_ _1"> </span>pages<span class="_ _1"> </span>inside.<span class="_ _9"> </span>On</div><div class="t m1 x0 h2 y36 ff1 fs0 fc0 sc0 ls0 ws0">the<span class="_ _4"> </span>other<span class="_ _4"> </span>hand,<span class="_ _4"> </span>web<span class="_ _4"> </span>pages<span class="_ _4"> </span>are<span class="_ _1"> </span>usually<span class="_ _4"> </span>stored<span class="_ _4"> </span>into</div><div class="t m1 x0 h2 y37 ff1 fs0 fc0 sc0 ls0 ws0">separate<span class="_ _4"> </span>files,<span class="_ _1"> </span>such<span class="_ _1"> </span>that<span class="_ _4"> </span>we<span class="_ _1"> </span>just<span class="_ _4"> </span>need<span class="_ _1"> </span>to<span class="_ _4"> </span>download</div><div class="t m0 x0 h2 y38 ff1 fs0 fc0 sc0 ls0 ws0">the<span class="_ _1"> </span>pages<span class="_ _1"> </span>w<span class="_ _5"></span>e<span class="_ _1"> </span>request.</div><div class="t m0 xd h5 y384 ff3 fs1 fc0 sc0 ls0 ws0">Figure<span class="_ _8"> </span>7</div><div class="t m1 x5e h13 y384 ff4 fs1 fc0 sc0 ls0 ws0">:<span class="_ _7"> </span>Ab<span class="_ _0"></span>ov<span class="_ _e"></span>e:<span class="_ _7"> </span>by<span class="_ _13"> </span>default<span class="_ _8"> </span>all<span class="_ _8"> </span>pages<span class="_ _8"> </span>are<span class="_ _8"> </span>embedded</div><div class="t mb xd h13 y385 ff4 fs1 fc0 sc0 ls0 ws0">in<span class="_ _8"> </span>the<span class="_ _8"> </span><span class="ffa fs4">HTML<span class="_ _8"> </span></span>file.<span class="_ _7"> </span>Below:<span class="_ _7"> </span>with</div><div class="t m0 xd8 h25 y385 ff15 fs1 fc0 sc0 ls0 ws0">--split-pages<span class="_ _8"> </span>1</div><div class="t mb xd9 h13 y385 ff4 fs1 fc0 sc0 ls0 ws0">,<span class="_ _8"> </span>pages</div><div class="t m1 xd h13 y386 ff4 fs1 fc0 sc0 ls0 ws0">are<span class="_ _8"> </span>stored<span class="_ _13"> </span>in<span class="_ _8"> </span>separate<span class="_ _8"> </span><span class="ffa fs4">HTML<span class="_ _8"> </span></span>snipp<span class="_ _0"></span>ets,<span class="_ _8"> </span>which<span class="_ _13"> </span>can<span class="_ _8"> </span>b<span class="_ _0"></span>e</div><div class="t m0 xd h13 y387 ff4 fs1 fc0 sc0 ls0 ws0">dynamically<span class="_ _8"> </span>loaded<span class="_ _8"> </span>to<span class="_ _8"> </span>the<span class="_ _8"> </span>main<span class="_ _8"> </span><span class="ffa fs4">HTML<span class="_ _8"> </span></span>file.</div><div class="t m10 xe h2 y388 ff1 fs0 fc0 sc0 ls0 ws0">With<span class="_ _8"> </span>the</div><div class="t m0 x99 h4 y388 ff6 fs0 fc0 sc0 ls0 ws0">--split-pages</div><div class="t m10 xda h2 y388 ff1 fs0 fc0 sc0 ls0 ws0">option,<span class="_ _8"> </span>it<span class="_ _1"> </span>is<span class="_ _1"> </span>p<span class="_ _0"></span>ossible</div><div class="t md xd h2 y389 ff1 fs0 fc0 sc0 ls0 ws0">to<span class="_ _1"> </span>store<span class="_ _1"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>pages<span class="_ _1"> </span>into<span class="_ _1"> </span>separate<span class="_ _1"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span><span class="ff5">snipp<span class="_ _e"></span>ets<span class="ff1">.<span class="_ _7"> </span>In</span></span></div><div class="t m20 xd h2 y38a ff1 fs0 fc0 sc0 ls0 ws0">this<span class="_ _1"> </span>wa<span class="_ _e"></span>y<span class="_ _2"></span>,<span class="_ _1"> </span>when<span class="_ _1"> </span>the<span class="_ _1"> </span>main<span class="_ _1"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>file<span class="_ _4"> </span>is<span class="_ _8"> </span>loaded<span class="_ _1"> </span>on<span class="_ _1"> </span>the</div><div class="t m2c xd h2 y38b ff1 fs0 fc0 sc0 ls0 ws0">clien<span class="_ _e"></span>t<span class="_ _4"> </span>side,<span class="_ _8"> </span>only<span class="_ _1"> </span>necessary<span class="_ _4"> </span>pages<span class="_ _8"> </span>will<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _4"> </span>dynamically</div><div class="t m0 xd h2 y38c ff1 fs0 fc0 sc0 ls0 ws0">loaded<span class="_ _1"> </span>via<span class="_ _1"> </span>Ajax,<span class="_ _1"> </span>as<span class="_ _1"> </span>sho<span class="_ _5"></span>wn<span class="_ _1"> </span>in<span class="_ _1"> </span>Figure<span class="_ _1"> </span>7.</div><div class="t m0 xd h3 y38d ff2 fs0 fc0 sc0 ls0 ws0">4.4<span class="_ _c"> </span>Image<span class="_ _4"> </span>format<span class="_ _4"> </span>for<span class="_ _4"> </span>bac<span class="_ _e"></span>kgrounds</div><div class="t m2d xd h2 y37 ff1 fs0 fc0 sc0 ls0 ws0">F<span class="_ _2"></span>or<span class="_ _1"> </span>each<span class="_ _8"> </span>page,<span class="_ _1"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX<span class="_ _8"> </span></span>generates<span class="_ _1"> </span>a<span class="_ _1"> </span>background</div><div class="t m1 xd h2 y38 ff1 fs0 fc0 sc0 ls0 ws0">image<span class="_ _1"> </span>to<span class="_ _1"> </span>presen<span class="_ _e"></span>t<span class="_ _1"> </span>all<span class="_ _1"> </span>non-text<span class="_ _1"> </span>elements.<span class="_ _7"> </span>By<span class="_ _1"> </span>default</div><div class="t m0 x0 h2 y77 ff1 fs0 fc0 sc0 ls0 ws0">Lu<span class="_ _1"> </span>W<span class="_ _2"></span>ang<span class="_ _1"> </span>and<span class="_ _1"> </span>W<span class="_ _2"></span>anmin<span class="_ _1"> </span>Liu</div><a class="l" href="#pf8" data-dest-detail='[8,"XYZ",117.655,265.537,null]'><div class="d m1d" style="border-style:none;position:absolute;left:188.775739px;bottom:296.217098px;width:6.875000px;height:10.848000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pf8" data-dest-detail='[8,"XYZ",359.747,252.2,null]'><div class="d m1d" style="border-style:none;position:absolute;left:791.975320px;bottom:203.540078px;width:6.974000px;height:10.849000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.673203,0.000000,0.000000,1.673203,0.000000,0.000000]}'></div></div>
<div id="pf9" class="pf w0 h0" data-page-no="9"><div class="pc pc9 w0 h0"><img class="bi x1 y38e w9 h26" alt="" src="data:image/png;base64,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"/><div class="t m0 x0 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">TUGb<span class="_ _0"></span>oat,<span class="_ _1"> </span>V<span class="_ _2"></span>olume<span class="_ _1"> </span>34<span class="_ _1"> </span>(2013),<span class="_ _1"> </span>No.<span class="_ _1"> </span>3<span class="_ _3"> </span>321</div><div class="t m2 x0 h2 y39 ff1 fs0 fc0 sc0 ls0 ws0">all<span class="_ _1"> </span>images<span class="_ _1"> </span>are<span class="_ _1"> </span>generated<span class="_ _1"> </span>in<span class="_ _1"> </span>the<span class="_ _1"> </span><span class="ff4 fs1">PNG<span class="_ _1"> </span></span>format,<span class="_ _1"> </span>and<span class="_ _1"> </span>dif-</div><div class="t m2 x0 h2 y3a ff1 fs0 fc0 sc0 ls0 ws0">feren<span class="_ _e"></span>t<span class="_ _1"> </span>formats<span class="_ _1"> </span>can<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>sp<span class="_ _0"></span>ecified<span class="_ _1"> </span>via<span class="_ _1"> </span>the</div><div class="t m0 x3 h4 y3a ff6 fs0 fc0 sc0 ls0 ws0">--bg-format</div><div class="t m0 x0 h2 y3b ff1 fs0 fc0 sc0 ls0 ws0">option.<span class="_ _7"> </span>F<span class="_ _2"></span>or<span class="_ _1"> </span>example,</div><div class="t m0 x45 h23 y38f ff14 fs4 fc0 sc0 ls0 ws0">$<span class="_ _9"> </span>pdf2html<span class="fs2">EX<span class="_ _9"> </span></span>--bg-format<span class="_ _9"> </span>jpg<span class="_ _7"> </span>integral.pdf</div><div class="t m0 x0 h2 y390 ff1 fs0 fc0 sc0 ls0 ws0">w<span class="_ _e"></span>ould<span class="_ _4"> </span>generate<span class="_ _8"> </span>all<span class="_ _1"> </span>images<span class="_ _1"> </span>in<span class="_ _1"> </span>the<span class="_ _1"> </span><span class="ff4 fs1">JPEG<span class="_ _1"> </span></span>format.</div><div class="t m2 x1 h2 y391 ff1 fs0 fc0 sc0 ls0 ws0">Curren<span class="_ _e"></span>tly<span class="_ _8"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX </span>supp<span class="_ _0"></span>orts <span class="ff4 fs1">PNG<span class="_ _8"> </span></span>and <span class="ff4 fs1">JPEG</span>.</div><div class="t m1 x0 h2 y392 ff1 fs0 fc0 sc0 ls0 ws0">There<span class="_ _4"> </span>is<span class="_ _9"> </span>also<span class="_ _4"> </span>preliminary<span class="_ _4"> </span>supp<span class="_ _0"></span>ort<span class="_ _9"> </span>for<span class="_ _4"> </span><span class="ff4 fs1">SVG</span>.<span class="_ _15"> </span>Users</div><div class="t m0 x0 h2 y393 ff1 fs0 fc0 sc0 ls0 ws0">can<span class="_ _1"> </span>also<span class="_ _1"> </span>con<span class="_ _5"></span>v<span class="_ _e"></span>ert<span class="_ _1"> </span>the<span class="_ _4"> </span>images<span class="_ _8"> </span>into<span class="_ _8"> </span>other<span class="_ _1"> </span>formats.</div><div class="t m0 x0 h3 y394 ff2 fs0 fc0 sc0 ls0 ws0">4.5<span class="_ _c"> </span>Customizing<span class="_ _4"> </span>the<span class="_ _4"> </span>output</div><div class="t m0 x0 h4 y395 ff6 fs0 fc0 sc0 ls0 ws0">integral.html</div><div class="t m2 x70 h2 y395 ff1 fs0 fc0 sc0 ls0 ws0">con<span class="_ _e"></span>tains<span class="_ _8"> </span>a<span class="_ _8"> </span>default<span class="_ _8"> </span>set of<span class="_ _8"> </span><span class="ff4 fs1">HTML</span>,<span class="_ _8"> </span><span class="ff4 fs1">CSS</span></div><div class="t m1 x0 h2 y396 ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _4"> </span>Jav<span class="_ _2"></span>aScript,<span class="_ _9"> </span>which<span class="_ _4"> </span>is<span class="_ _9"> </span>designed<span class="_ _4"> </span>for<span class="_ _9"> </span>a<span class="_ _e"></span>verage<span class="_ _4"> </span>use</div><div class="t m1 x0 h2 y397 ff1 fs0 fc0 sc0 ls0 ws0">cases.<span class="_ _b"> </span>All<span class="_ _7"> </span>of<span class="_ _7"> </span>them<span class="_ _7"> </span>can<span class="_ _7"> </span>b<span class="_ _0"></span>e<span class="_ _9"> </span>found<span class="_ _7"> </span>in<span class="_ _7"> </span>the<span class="_ _7"> </span>so-called</div><div class="t m0 x0 h4 y398 ff6 fs0 fc0 sc0 ls0 ws0">data-dir</div><div class="t m2 x5 h2 y398 ff1 fs0 fc0 sc0 ls0 ws0">(run</div><div class="t m0 x55 h4 y398 ff6 fs0 fc0 sc0 ls0 ws0">pdf2html<span class="ff15 fs1">EX<span class="_ _33"> </span></span>-v</div><div class="t m2 xdb h2 y398 ff1 fs0 fc0 sc0 ls0 ws0">to see<span class="_ _8"> </span>the lo<span class="_ _0"></span>cation),</div><div class="t m0 x0 h2 y399 ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _1"> </span>they<span class="_ _1"> </span>can<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>t<span class="_ _5"></span>w<span class="_ _e"></span>e<span class="_ _0"></span>ak<span class="_ _e"></span>ed<span class="_ _1"> </span>by<span class="_ _8"> </span>the<span class="_ _1"> </span>users.</div><div class="t m0 x0 h3 y39a ff3 fs1 fc0 sc0 ls0 ws0">HTML<span class="_ _11"> </span><span class="ff2 fs0">template</span></div><div class="t m1 x28 h2 y39a ff1 fs0 fc0 sc0 ls0 ws0">The</div><div class="t m0 x2d h4 y39a ff6 fs0 fc0 sc0 ls0 ws0">manifest</div><div class="t m1 xdc h2 y39a ff1 fs0 fc0 sc0 ls0 ws0">file<span class="_ _9"> </span>determines</div><div class="t m1e x0 h2 y39b ff1 fs0 fc0 sc0 ls0 ws0">ho<span class="_ _e"></span>w<span class="_ _4"> </span>pages<span class="_ _8"> </span>should<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>combined<span class="_ _8"> </span>into<span class="_ _8"> </span>an<span class="_ _1"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>do<span class="_ _0"></span>cu-</div><div class="t m26 x0 h2 y39c ff1 fs0 fc0 sc0 ls0 ws0">men<span class="_ _e"></span>t.<span class="_ _11"> </span>It<span class="_ _1"> </span>is<span class="_ _1"> </span>a<span class="_ _1"> </span>template<span class="_ _4"> </span>for<span class="_ _8"> </span>the<span class="_ _1"> </span>output<span class="_ _1"> </span>and<span class="_ _4"> </span>users<span class="_ _8"> </span>may</div><div class="t m2f x0 h2 y39d ff1 fs0 fc0 sc0 ls0 ws0">add<span class="_ _1"> </span>their<span class="_ _1"> </span>own<span class="_ _8"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>snipp<span class="_ _0"></span>ets<span class="_ _1"> </span>into<span class="_ _8"> </span>it.<span class="_ _7"> </span>A<span class="_ _1"> </span>typical<span class="_ _8"> </span>use</div><div class="t m2 x0 h2 y39e ff1 fs0 fc0 sc0 ls0 ws0">case is enabling a traffic statistics service on the page.</div><div class="t m0 x0 h5 y39f ff3 fs1 fc0 sc0 ls0 ws0">CSS</div><div class="t m2 x43 h2 y39f ff1 fs0 fc0 sc0 ls0 ws0">Quite<span class="_ _d"> </span>a<span class="_ _d"> </span>n<span class="_ _e"></span>umber of<span class="_ _d"> </span>features<span class="_ _d"> </span>of<span class="_ _d"> </span>p<span class="_ _0"></span>df2h<span class="_ _e"></span>tml<span class="ff4 fs1">EX </span>rely</div><div class="t m2 x0 h2 y3a0 ff1 fs0 fc0 sc0 ls0 ws0">on<span class="_ _1"> </span><span class="ff4 fs1">CSS</span>;<span class="_ _1"> </span>the<span class="_ _1"> </span>default<span class="_ _4"> </span><span class="ff4 fs1">CSS<span class="_ _8"> </span></span>styles<span class="_ _8"> </span>determine<span class="_ _1"> </span>the<span class="_ _4"> </span>correct</div><div class="t m1b x0 h2 y3a1 ff1 fs0 fc0 sc0 ls0 ws0">app<span class="_ _0"></span>earance<span class="_ _1"> </span>and<span class="_ _1"> </span>b<span class="_ _0"></span>ehavior<span class="_ _8"> </span>of<span class="_ _1"> </span>the<span class="_ _4"> </span>elemen<span class="_ _e"></span>ts.<span class="_ _7"> </span>Adv<span class="_ _e"></span>anced</div><div class="t m2e x0 h2 y3a2 ff1 fs0 fc0 sc0 ls0 ws0">users<span class="_ _1"> </span>can<span class="_ _8"> </span>ov<span class="_ _e"></span>erride<span class="_ _1"> </span>existing<span class="_ _1"> </span>prop<span class="_ _0"></span>erties<span class="_ _1"> </span>by<span class="_ _8"> </span>mo<span class="_ _0"></span>difying</div><div class="t m0 x0 h2 y3a3 ff1 fs0 fc0 sc0 ls0 ws0">the<span class="_ _1"> </span><span class="ff4 fs1">CSS<span class="_ _1"> </span></span>files.</div><div class="t m0 x0 h3 y3a4 ff2 fs0 fc0 sc0 ls0 ws0">Ja<span class="_ _e"></span>v<span class="_ _e"></span>aScript</div><div class="t m1 xcc h2 y3a4 ff1 fs0 fc0 sc0 ls0 ws0">A<span class="_ _11"> </span>simple<span class="_ _11"> </span><span class="ff4 fs1">UI<span class="_ _f"> </span></span>is<span class="_ _11"> </span>implemented<span class="_ _7"> </span>in<span class="_ _f"> </span>the</div><div class="t m1 x0 h2 y3a5 ff1 fs0 fc0 sc0 ls0 ws0">default</div><div class="t m0 x39 h4 y3a5 ff6 fs0 fc0 sc0 ls0 ws0">pdf2html<span class="ff15 fs1">EX</span>.js</div><div class="t m1 x2a h2 y3a5 ff1 fs0 fc0 sc0 ls0 ws0">file.<span class="_ _2d"> </span>This<span class="_ _9"> </span>also<span class="_ _7"> </span>serv<span class="_ _e"></span>es<span class="_ _7"> </span>as<span class="_ _9"> </span>a</div><div class="t m17 x0 h2 y3a6 ff1 fs0 fc0 sc0 ls0 ws0">demonstration<span class="_ _1"> </span>of<span class="_ _1"> </span>accessing<span class="_ _1"> </span>and<span class="_ _1"> </span>manipulating<span class="_ _4"> </span><span class="ff4 fs1">HTML</span></div><div class="t m2 x0 h2 y3a7 ff1 fs0 fc0 sc0 ls0 ws0">elemen<span class="_ _e"></span>ts<span class="_ _1"> </span>pro<span class="_ _0"></span>duced<span class="_ _8"> </span>by<span class="_ _8"> </span>p<span class="_ _0"></span>df2h<span class="_ _5"></span>tml<span class="ff4 fs1">EX</span>.<span class="_ _7"> </span>It<span class="_ _8"> </span>can<span class="_ _8"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>a<span class="_ _8"> </span>go<span class="_ _0"></span>o<span class="_ _0"></span>d</div><div class="t m2 x0 h2 y3a8 ff1 fs0 fc0 sc0 ls0 ws0">reference<span class="_ _1"> </span>for<span class="_ _1"> </span>adv<span class="_ _e"></span>anced<span class="_ _1"> </span>users<span class="_ _1"> </span>who<span class="_ _1"> </span>wan<span class="_ _e"></span>t<span class="_ _1"> </span>to<span class="_ _1"> </span>implement</div><div class="t m0 x0 h2 y3a9 ff1 fs0 fc0 sc0 ls0 ws0">their<span class="_ _1"> </span>o<span class="_ _5"></span>wn<span class="_ _1"> </span><span class="ff4 fs1">UI</span>s.</div><div class="t m0 x0 h3 y3aa ff2 fs0 fc0 sc0 ls0 ws0">4.6<span class="_ _c"> </span>Secrets<span class="_ _4"> </span>of<span class="_ _4"> </span>p<span class="_ _0"></span>df2h<span class="_ _5"></span>tmlEX</div><div class="t me x0 h2 y3ab ff1 fs0 fc0 sc0 ls0 ws0">Here<span class="_ _1"> </span>we<span class="_ _8"> </span>briefly<span class="_ _1"> </span>introduce<span class="_ _1"> </span>some<span class="_ _1"> </span>internal<span class="_ _8"> </span>mechanisms</div><div class="t m0 x0 h2 y3ac ff1 fs0 fc0 sc0 ls0 ws0">of<span class="_ _1"> </span>p<span class="_ _0"></span>df2h<span class="_ _e"></span>tml<span class="ff4 fs1">EX<span class="_ _1"> </span></span>for<span class="_ _1"> </span>the<span class="_ _4"> </span>curious<span class="_ _8"> </span>readers.</div><div class="t m0 x1 h4 y3ad ff6 fs0 fc0 sc0 ls0 ws0">integral.html</div><div class="t m12 x28 h2 y3ad ff1 fs0 fc0 sc0 ls0 ws0">consists<span class="_ _1"> </span>of<span class="_ _1"> </span>tw<span class="_ _e"></span>o<span class="_ _1"> </span>la<span class="_ _5"></span>y<span class="_ _5"></span>ers:<span class="_ _7"> </span>the<span class="_ _1"> </span>text</div><div class="t m2 x0 h2 y3ae ff1 fs0 fc0 sc0 ls0 ws0">la<span class="_ _e"></span>yer<span class="_ _14"> </span>and<span class="_ _d"> </span>the<span class="_ _14"> </span>image<span class="_ _d"> </span>la<span class="_ _e"></span>yer,<span class="_ _d"> </span>as<span class="_ _14"> </span>shown<span class="_ _14"> </span>in<span class="_ _14"> </span>Figures<span class="_ _d"> </span>8<span class="_ _14"> </span>and<span class="_ _d"> </span>9.</div><div class="t m2e x0 h2 y3af ff1 fs0 fc0 sc0 ls0 ws0">p<span class="_ _0"></span>df2h<span class="_ _e"></span>tml<span class="ff4 fs1">EX<span class="_ _1"> </span></span>parses</div><div class="t m0 xdd h4 y3af ff6 fs0 fc0 sc0 ls0 ws0">internal.pdf</div><div class="t m2e x7 h2 y3af ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _1"> </span>extracts<span class="_ _8"> </span>ele-</div><div class="t md x0 h2 y3b0 ff1 fs0 fc0 sc0 ls0 ws0">men<span class="_ _e"></span>ts<span class="_ _4"> </span>from<span class="_ _8"> </span>it.<span class="_ _7"> </span>The<span class="_ _4"> </span>elemen<span class="_ _e"></span>ts<span class="_ _1"> </span>are<span class="_ _1"> </span>then<span class="_ _1"> </span>pro<span class="_ _0"></span>cessed<span class="_ _4"> </span>and</div><div class="t m0 x0 h2 y3b1 ff1 fs0 fc0 sc0 ls0 ws0">put<span class="_ _1"> </span>in<span class="_ _e"></span>to<span class="_ _4"> </span>one<span class="_ _8"> </span>of<span class="_ _1"> </span>the<span class="_ _1"> </span>lay<span class="_ _e"></span>ers.</div><div class="t m0 x0 h3 y3b2 ff2 fs0 fc0 sc0 ls0 ws0">T<span class="_ _31"></span>ext</div><div class="t m6 xc2 h2 y3b2 ff1 fs0 fc0 sc0 ls0 ws0">Unlik<span class="_ _e"></span>e<span class="_ _1"> </span>in<span class="_ _1"> </span><span class="ff4 fs1">HTML</span>,<span class="_ _1"> </span>in<span class="_ _1"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>text<span class="_ _1"> </span>is<span class="_ _1"> </span>set<span class="_ _8"> </span>in<span class="_ _1"> </span>fixed</div><div class="t m2 x0 h2 y3b3 ff1 fs0 fc0 sc0 ls0 ws0">p<span class="_ _0"></span>ositions.<span class="_ _9"> </span>T<span class="_ _2"></span>ext<span class="_ _1"> </span>extracted<span class="_ _8"> </span>from<span class="_ _8"> </span>the<span class="_ _8"> </span><span class="ff4 fs1">PDF<span class="_ _8"> </span></span>is<span class="_ _8"> </span>translated</div><div class="t m1 x0 h2 y3b4 ff1 fs0 fc0 sc0 ls0 ws0">in<span class="_ _5"></span>to<span class="_ _4"> </span>nativ<span class="_ _e"></span>e<span class="_ _4"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>text<span class="_ _4"> </span>elements,<span class="_ _1"> </span>and<span class="_ _4"> </span>put<span class="_ _4"> </span>in<span class="_ _e"></span>to<span class="_ _4"> </span>the</div><div class="t md x0 h2 y3b5 ff1 fs0 fc0 sc0 ls0 ws0">same<span class="_ _1"> </span>p<span class="_ _0"></span>osition<span class="_ _1"> </span>in<span class="_ _1"> </span>the<span class="_ _1"> </span><span class="ff4 fs1">HTML<span class="_ _4"> </span></span>as<span class="_ _8"> </span>they<span class="_ _1"> </span>were<span class="_ _8"> </span>in<span class="_ _4"> </span><span class="ff4 fs1">PDF</span>.<span class="_ _9"> </span>In</div><div class="t m1 x0 h2 y3b6 ff1 fs0 fc0 sc0 ls0 ws0">this<span class="_ _4"> </span>w<span class="_ _e"></span>ay<span class="_ _1"> </span>text<span class="_ _4"> </span>can<span class="_ _4"> </span>be<span class="_ _4"> </span>selected<span class="_ _4"> </span>and<span class="_ _1"> </span>copied<span class="_ _4"> </span>b<span class="_ _5"></span>y<span class="_ _4"> </span>users,</div><div class="t m2 x0 h2 y3b7 ff1 fs0 fc0 sc0 ls0 ws0">while preserving the la<span class="_ _e"></span>yout.<span class="_ _4"> </span>Many fixed-position text</div><div class="t m1 x0 h2 y3b8 ff1 fs0 fc0 sc0 ls0 ws0">elemen<span class="_ _5"></span>ts<span class="_ _4"> </span>in<span class="_ _4"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>make<span class="_ _4"> </span>the<span class="_ _4"> </span>file<span class="_ _1"> </span>very<span class="_ _4"> </span>large<span class="_ _1"> </span>in<span class="_ _4"> </span>size</div><div class="t m2 x0 h2 y3b9 ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _8"> </span>v<span class="_ _e"></span>ery<span class="_ _8"> </span>slow to<span class="_ _8"> </span>render;<span class="_ _1"> </span>to<span class="_ _8"> </span>comp<span class="_ _0"></span>ensate,<span class="_ _8"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX</span></div><div class="t m3 x0 h2 y3ba ff1 fs0 fc0 sc0 ls0 ws0">tries<span class="_ _1"> </span>to<span class="_ _1"> </span>recognize<span class="_ _1"> </span>and<span class="_ _1"> </span>merge<span class="_ _1"> </span>text<span class="_ _1"> </span>lines<span class="_ _1"> </span>according<span class="_ _1"> </span>to</div><div class="t m0 x0 h2 y3bb ff1 fs0 fc0 sc0 ls0 ws0">their<span class="_ _1"> </span>geometric<span class="_ _1"> </span>metrics.</div><div class="t m0 x0 h3 y37 ff2 fs0 fc0 sc0 ls0 ws0">F<span class="_ _31"></span>ont</div><div class="t m2 xc1 h2 y37 ff1 fs0 fc0 sc0 ls0 ws0">F<span class="_ _2"></span>on<span class="_ _e"></span>t<span class="_ _8"> </span>embedding<span class="_ _8"> </span>is<span class="_ _8"> </span>one of<span class="_ _8"> </span>the<span class="_ _8"> </span>most<span class="_ _8"> </span>imp<span class="_ _0"></span>ortan<span class="_ _5"></span>t</div><div class="t m1 x0 h2 y38 ff1 fs0 fc0 sc0 ls0 ws0">features<span class="_ _4"> </span>of<span class="_ _1"> </span><span class="ff4 fs1">PDF</span>,<span class="_ _4"> </span>without<span class="_ _1"> </span>which<span class="_ _1"> </span>it<span class="_ _4"> </span>is<span class="_ _4"> </span>nearly<span class="_ _1"> </span>imp<span class="_ _0"></span>os-</div><div class="t m1 xd h2 y39 ff1 fs0 fc0 sc0 ls0 ws0">sible<span class="_ _4"> </span>to<span class="_ _1"> </span>preserve<span class="_ _1"> </span>the<span class="_ _4"> </span>appearance<span class="_ _4"> </span>of<span class="_ _1"> </span><span class="ff4 fs1">PDF<span class="_ _4"> </span></span>in<span class="_ _4"> </span><span class="ff4 fs1">HTML</span>.</div><div class="t m21 xd h2 y3a ff1 fs0 fc0 sc0 ls0 ws0">No<span class="_ _1"> </span>similar<span class="_ _1"> </span>feature<span class="_ _1"> </span>has<span class="_ _1"> </span>b<span class="_ _0"></span>een<span class="_ _1"> </span>supp<span class="_ _0"></span>orted<span class="_ _1"> </span>in<span class="_ _1"> </span>the<span class="_ _1"> </span><span class="ff4 fs1">HTML</span></div><div class="t m9 xd h2 y3b ff1 fs0 fc0 sc0 ls0 ws0">standard<span class="_ _1"> </span>until<span class="_ _8"> </span>recently<span class="_ _31"></span>.<span class="_ _7"> </span>Figure<span class="_ _1"> </span>10<span class="_ _1"> </span>shows<span class="_ _1"> </span>a<span class="_ _1"> </span>few<span class="_ _1"> </span>fonts</div><div class="t m1 xd h2 y3c ff1 fs0 fc0 sc0 ls0 ws0">used<span class="_ _4"> </span>in</div><div class="t m0 x12 h4 y3c ff6 fs0 fc0 sc0 ls0 ws0">integral.pdf</div><div class="t m1 x62 h2 y3c ff1 fs0 fc0 sc0 ls0 ws0">.<span class="_ _15"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX<span class="_ _4"> </span></span>is<span class="_ _4"> </span>able<span class="_ _9"> </span>to<span class="_ _4"> </span>ex-</div><div class="t mc xd h2 y3d ff1 fs0 fc0 sc0 ls0 ws0">tract<span class="_ _1"> </span>all<span class="_ _8"> </span>the<span class="_ _1"> </span>fonts<span class="_ _8"> </span>from<span class="_ _1"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>and<span class="_ _1"> </span>conv<span class="_ _e"></span>ert<span class="_ _1"> </span>them<span class="_ _1"> </span>into</div><div class="t m1 x7b h2 y3e ff1 fs0 fc0 sc0 ls0 ws0">w<span class="_ _5"></span>eb<span class="_ _9"> </span>fonts<span class="_ _9"> </span>via<span class="_ _7"> </span>F<span class="_ _2"></span>ontF<span class="_ _31"></span>orge<span class="_ _7"> </span>[</div><div class="t m0 xde h2 y3e ff1 fs0 fc0 sc0 ls0 ws0">18</div><div class="t m1 x9c h2 y3e ff1 fs0 fc0 sc0 ls0 ws0">];<span class="_ _11"> </span>conv<span class="_ _e"></span>erted<span class="_ _7"> </span>fonts<span class="_ _9"> </span>are</div><div class="t ma xd h2 y3f ff1 fs0 fc0 sc0 ls0 ws0">then<span class="_ _1"> </span>em<span class="_ _e"></span>b<span class="_ _0"></span>edded<span class="_ _1"> </span>or<span class="_ _1"> </span>referred<span class="_ _1"> </span>to<span class="_ _1"> </span>in<span class="_ _1"> </span>the<span class="_ _1"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>file.<span class="_ _7"> </span>All</div><div class="t m1 xd h2 y40 ff1 fs0 fc0 sc0 ls0 ws0">fon<span class="_ _5"></span>t<span class="_ _7"> </span>formats<span class="_ _7"> </span>supp<span class="_ _0"></span>orted<span class="_ _7"> </span>in<span class="_ _7"> </span><span class="ff4 fs1">PDF<span class="_ _7"> </span></span>are<span class="_ _11"> </span>supp<span class="_ _0"></span>orted<span class="_ _7"> </span>by</div><div class="t m1c xd h2 y41 ff1 fs0 fc0 sc0 ls0 ws0">p<span class="_ _0"></span>df2h<span class="_ _e"></span>tml<span class="ff4 fs1">EX</span>,<span class="_ _1"> </span>and<span class="_ _1"> </span>different<span class="_ _8"> </span>web<span class="_ _8"> </span>font<span class="_ _8"> </span>formats<span class="_ _1"> </span>can<span class="_ _1"> </span>b<span class="_ _0"></span>e</div><div class="t m0 xd h2 y42 ff1 fs0 fc0 sc0 ls0 ws0">sp<span class="_ _0"></span>ecified<span class="_ _1"> </span>for<span class="_ _1"> </span>output.</div><div class="t m0 xd h3 y3bc ff2 fs0 fc0 sc0 ls0 ws0">Enco<span class="_ _0"></span>ding</div><div class="t md xdf h2 y3bc ff1 fs0 fc0 sc0 ls0 ws0">Unlik<span class="_ _e"></span>e<span class="_ _4"> </span><span class="ff4 fs1">HTML</span>,<span class="_ _8"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>uses<span class="_ _4"> </span>t<span class="_ _e"></span>wo<span class="_ _8"> </span>sets<span class="_ _1"> </span>of<span class="_ _4"> </span>en-</div><div class="t mb xd h2 y3bd ff1 fs0 fc0 sc0 ls0 ws0">co<span class="_ _0"></span>dings<span class="_ _1"> </span>for<span class="_ _8"> </span>te<span class="_ _0"></span>xt<span class="_ _8"> </span>rendering,<span class="_ _1"> </span>one<span class="_ _1"> </span>for<span class="_ _1"> </span>choosing<span class="_ _1"> </span>correct</div><div class="t m7 xd h2 y3be ff1 fs0 fc0 sc0 ls0 ws0">glyphs<span class="_ _1"> </span>to<span class="_ _1"> </span>display<span class="_ _31"></span>,<span class="_ _1"> </span>and<span class="_ _1"> </span>the<span class="_ _1"> </span>other<span class="_ _1"> </span>for<span class="_ _1"> </span>meaningful<span class="_ _1"> </span>text</div><div class="t m2 xd h2 y3bf ff1 fs0 fc0 sc0 ls0 ws0">that<span class="_ _14"> </span>can<span class="_ _14"> </span>b<span class="_ _0"></span>e selected<span class="_ _14"> </span>and<span class="_ _14"> </span>copied<span class="_ _14"> </span>by<span class="_ _14"> </span>users.<span class="_ _4"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX</span></div><div class="t m13 xd h2 y3c0 ff1 fs0 fc0 sc0 ls0 ws0">is<span class="_ _1"> </span>able<span class="_ _1"> </span>to<span class="_ _1"> </span>com<span class="_ _5"></span>bine<span class="_ _1"> </span>b<span class="_ _0"></span>oth<span class="_ _1"> </span>sets<span class="_ _1"> </span>into<span class="_ _8"> </span>one<span class="_ _1"> </span>and<span class="_ _1"> </span>re-enco<span class="_ _0"></span>de</div><div class="t m2d xd h2 y3c1 ff1 fs0 fc0 sc0 ls0 ws0">the<span class="_ _1"> </span>fon<span class="_ _5"></span>t<span class="_ _1"> </span>accordingly<span class="_ _2"></span>,<span class="_ _1"> </span>such<span class="_ _8"> </span>that<span class="_ _1"> </span>text<span class="_ _1"> </span>in<span class="_ _1"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>is<span class="_ _1"> </span>cor-</div><div class="t m2c xd h2 y3c2 ff1 fs0 fc0 sc0 ls0 ws0">rect<span class="_ _1"> </span>b<span class="_ _0"></span>oth<span class="_ _1"> </span>visually<span class="_ _1"> </span>and<span class="_ _1"> </span>meaningfully<span class="_ _2"></span>.<span class="_ _7"> </span>This<span class="_ _4"> </span>is<span class="_ _8"> </span>another</div><div class="t m17 xd h2 y3c3 ff1 fs0 fc0 sc0 ls0 ws0">essen<span class="_ _e"></span>tial<span class="_ _4"> </span>feature<span class="_ _8"> </span>of<span class="_ _1"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX</span>,<span class="_ _1"> </span>lik<span class="_ _e"></span>e<span class="_ _4"> </span>fon<span class="_ _e"></span>t<span class="_ _1"> </span>pro<span class="_ _0"></span>cessing.</div><div class="t m0 xd h3 y3c4 ff2 fs0 fc0 sc0 ls0 ws0">Images</div><div class="t m13 x84 h2 y3c4 ff4 fs1 fc0 sc0 ls0 ws0">PDF<span class="_ _1"> </span><span class="ff1 fs0">supp<span class="_ _0"></span>orts<span class="_ _1"> </span>graphical<span class="_ _1"> </span>instructions<span class="_ _1"> </span>suc<span class="_ _e"></span>h</span></div><div class="t m1 xd h2 y3c5 ff1 fs0 fc0 sc0 ls0 ws0">as<span class="_ _4"> </span>drawing<span class="_ _4"> </span>and<span class="_ _9"> </span>image<span class="_ _4"> </span>embedding.<span class="_ _12"> </span>Suc<span class="_ _e"></span>h<span class="_ _9"> </span>elements</div><div class="t m15 xd h2 y3c6 ff1 fs0 fc0 sc0 ls0 ws0">are<span class="_ _8"> </span>all<span class="_ _1"> </span>rendered<span class="_ _1"> </span>into<span class="_ _8"> </span>images,<span class="_ _1"> </span>and<span class="_ _1"> </span>then<span class="_ _8"> </span>put<span class="_ _1"> </span>into<span class="_ _8"> </span>the</div><div class="t m0 xd h2 y3c7 ff1 fs0 fc0 sc0 ls0 ws0">image<span class="_ _1"> </span>la<span class="_ _5"></span>y<span class="_ _e"></span>er.</div><div class="t m0 xd h3 y3c8 ff2 fs0 fc0 sc0 ls0 ws0">4.7<span class="_ _c"> </span>F<span class="_ _31"></span>uture<span class="_ _4"> </span>work</div><div class="t m1 xd h2 y3c9 ff1 fs0 fc0 sc0 ls0 ws0">Sev<span class="_ _5"></span>eral<span class="_ _1"> </span>features<span class="_ _1"> </span>are<span class="_ _4"> </span>planned<span class="_ _1"> </span>in<span class="_ _1"> </span>the<span class="_ _1"> </span>future<span class="_ _4"> </span>v<span class="_ _e"></span>ersions</div><div class="t m0 xd h2 y3ca ff1 fs0 fc0 sc0 ls0 ws0">of<span class="_ _1"> </span>p<span class="_ _0"></span>df2h<span class="_ _e"></span>tml<span class="ff4 fs1">EX</span>.</div><div class="t m0 xd h3 y3cb ff2 fs0 fc0 sc0 ls0 ws0">Reflo<span class="_ _e"></span>wable<span class="_ _4"> </span>text</div><div class="t mb xe0 h2 y3cb ff1 fs0 fc0 sc0 ls0 ws0">Comparing<span class="_ _1"> </span>with<span class="_ _8"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>files<span class="_ _1"> </span>di-</div><div class="t m2 xd h2 y3cc ff1 fs0 fc0 sc0 ls0 ws0">rectly<span class="_ _8"> </span>conv<span class="_ _e"></span>erted<span class="_ _1"> </span>from<span class="_ _8"> </span>T</div><div class="t m0 x62 h2 y3cd ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m2 x63 h2 y3cc ff1 fs0 fc0 sc0 ls0 ws0">X,<span class="_ _8"> </span>text<span class="_ _1"> </span>in<span class="_ _8"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>files<span class="_ _1"> </span>gener-</div><div class="t ma xd h2 y3ce ff1 fs0 fc0 sc0 ls0 ws0">ated<span class="_ _1"> </span>b<span class="_ _5"></span>y<span class="_ _1"> </span>p<span class="_ _0"></span>df2h<span class="_ _5"></span>tml<span class="ff4 fs1">EX<span class="_ _1"> </span></span>is<span class="_ _1"> </span>generally<span class="_ _1"> </span>not<span class="_ _1"> </span>reflow<span class="_ _e"></span>able,<span class="_ _1"> </span><span class="ff5">i.e.</span></div><div class="t m2e xd h2 y3cf ff1 fs0 fc0 sc0 ls0 ws0">the<span class="_ _1"> </span>width<span class="_ _8"> </span>of<span class="_ _1"> </span>paragraphs<span class="_ _1"> </span>cannot<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>self-adapting<span class="_ _1"> </span>to</div><div class="t m13 xd h2 y3d0 ff1 fs0 fc0 sc0 ls0 ws0">the<span class="_ _1"> </span>size<span class="_ _1"> </span>of<span class="_ _1"> </span>the<span class="_ _1"> </span>viewer.<span class="_ _9"> </span>After<span class="_ _1"> </span>all,<span class="_ _1"> </span>that<span class="_ _1"> </span>information<span class="_ _1"> </span>is</div><div class="t m1 xd h2 y3d1 ff1 fs0 fc0 sc0 ls0 ws0">generally<span class="_ _4"> </span>not<span class="_ _4"> </span>a<span class="_ _e"></span>v<span class="_ _e"></span>ailable<span class="_ _4"> </span>in<span class="_ _1"> </span>a<span class="_ _4"> </span><span class="ff4 fs1">PDF<span class="_ _4"> </span></span>file,<span class="_ _4"> </span>and<span class="_ _4"> </span>it<span class="_ _1"> </span>is<span class="_ _4"> </span>not</div><div class="t m0 xd h2 y3d2 ff1 fs0 fc0 sc0 ls0 ws0">easy<span class="_ _1"> </span>for<span class="_ _1"> </span>p<span class="_ _0"></span>df2h<span class="_ _5"></span>tml<span class="ff4 fs1">EX<span class="_ _1"> </span></span>to<span class="_ _1"> </span>reco<span class="_ _5"></span>v<span class="_ _e"></span>er<span class="_ _1"> </span>it.</div><div class="t m1 xe h2 y3d3 ff1 fs0 fc0 sc0 ls0 ws0">On<span class="_ _f"> </span>the<span class="_ _33"> </span>other<span class="_ _33"> </span>hand,<span class="_ _2e"> </span>reflow<span class="_ _e"></span>able<span class="_ _33"> </span>text<span class="_ _33"> </span>ma<span class="_ _e"></span>y<span class="_ _33"> </span>b<span class="_ _0"></span>e</div><div class="t m1 xd h2 y3d4 ff1 fs0 fc0 sc0 ls0 ws0">extracted<span class="_ _4"> </span>for<span class="_ _4"> </span>specific<span class="_ _4"> </span>do<span class="_ _0"></span>cument<span class="_ _1"> </span>types<span class="_ _4"> </span>and<span class="_ _4"> </span>lay<span class="_ _e"></span>outs.</div><div class="t m1 xd h2 y3d5 ff1 fs0 fc0 sc0 ls0 ws0">Extracting<span class="_ _9"> </span>such<span class="_ _4"> </span>information<span class="_ _9"> </span>would<span class="_ _9"> </span>mak<span class="_ _e"></span>e<span class="_ _9"> </span>it<span class="_ _7"> </span>m<span class="_ _5"></span>uc<span class="_ _5"></span>h</div><div class="t m1 xd h2 y3d6 ff1 fs0 fc0 sc0 ls0 ws0">easier<span class="_ _4"> </span>to<span class="_ _9"> </span>further<span class="_ _9"> </span>process<span class="_ _9"> </span><span class="ff4 fs1">HTML<span class="_ _9"> </span></span>files<span class="_ _4"> </span>generated<span class="_ _9"> </span>b<span class="_ _e"></span>y</div><div class="t m1 xd h2 y3d7 ff1 fs0 fc0 sc0 ls0 ws0">p<span class="_ _0"></span>df2h<span class="_ _e"></span>tml<span class="ff4 fs1">EX</span>,<span class="_ _f"> </span>such<span class="_ _9"> </span>as<span class="_ _7"> </span>to<span class="_ _7"> </span>edit<span class="_ _7"> </span>manually<span class="_ _31"></span>,<span class="_ _11"> </span>to<span class="_ _7"> </span>embed</div><div class="t m1 xd h2 y3d8 ff1 fs0 fc0 sc0 ls0 ws0">accessibilit<span class="_ _5"></span>y<span class="_ _11"> </span>information<span class="_ _11"> </span>or<span class="_ _11"> </span>to<span class="_ _11"> </span>conv<span class="_ _e"></span>ert<span class="_ _11"> </span>into<span class="_ _7"> </span>other</div><div class="t m0 xd h2 y3d9 ff1 fs0 fc0 sc0 ls0 ws0">formats<span class="_ _1"> </span>lik<span class="_ _5"></span>e<span class="_ _1"> </span><span class="ff4 fs1">EPUB</span>.</div><div class="t m0 xd h3 y2d ff2 fs0 fc0 sc0 ls0 ws0">Preserving<span class="_ _4"> </span>seman<span class="_ _e"></span>tic<span class="_ _4"> </span>information</div><div class="t m2 xe1 h2 y2d ff1 fs0 fc0 sc0 ls0 ws0">While<span class="_ _8"> </span>muc<span class="_ _e"></span>h</div><div class="t m1 xd h2 y2e ff1 fs0 fc0 sc0 ls0 ws0">seman<span class="_ _5"></span>tic<span class="_ _4"> </span>information<span class="_ _4"> </span>is<span class="_ _4"> </span>lost<span class="_ _9"> </span>in<span class="_ _4"> </span><span class="ff4 fs1">PDF<span class="_ _4"> </span></span>as<span class="_ _4"> </span>mentioned</div><div class="t m3 xd h2 y2f ff1 fs0 fc0 sc0 ls0 ws0">ab<span class="_ _0"></span>o<span class="_ _e"></span>ve,<span class="_ _8"> </span>theoretically<span class="_ _1"> </span>it<span class="_ _1"> </span>is<span class="_ _1"> </span>p<span class="_ _0"></span>ossible<span class="_ _1"> </span>for<span class="_ _1"> </span>authors<span class="_ _1"> </span>to<span class="_ _1"> </span>em-</div><div class="t m1 xd h2 y30 ff1 fs0 fc0 sc0 ls0 ws0">b<span class="_ _0"></span>ed<span class="_ _4"> </span>additional<span class="_ _4"> </span>information<span class="_ _4"> </span>in<span class="_ _e"></span>to<span class="_ _4"> </span><span class="ff4 fs1">PDF</span>,<span class="_ _9"> </span>suc<span class="_ _5"></span>h<span class="_ _4"> </span>that<span class="_ _4"> </span>it</div><div class="t m5 xd h2 y31 ff1 fs0 fc0 sc0 ls0 ws0">ma<span class="_ _e"></span>y<span class="_ _4"> </span>be<span class="_ _1"> </span>further<span class="_ _1"> </span>recognized<span class="_ _4"> </span>and<span class="_ _8"> </span>used<span class="_ _1"> </span>by<span class="_ _8"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX</span>.</div><div class="t m6 x7b h2 y32 ff1 fs0 fc0 sc0 ls0 ws0">This<span class="_ _1"> </span>kind<span class="_ _8"> </span>of<span class="_ _1"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>file<span class="_ _1"> </span>is<span class="_ _1"> </span>called<span class="_ _1"> </span>a<span class="_ _1"> </span><span class="ff5">tagge<span class="_ _e"></span>d<span class="_ _1"> </span><span class="ff4 fs1">PDF</span><span class="ff1">,<span class="_ _1"> </span>whic<span class="_ _5"></span>h</span></span></div><div class="t m0 xd h2 y33 ff1 fs0 fc0 sc0 ls0 ws0">can<span class="_ _1"> </span>also<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>generated<span class="_ _1"> </span>with<span class="_ _1"> </span>other<span class="_ _1"> </span>to<span class="_ _0"></span>ols.</div><div class="t ma xe h2 y34 ff1 fs0 fc0 sc0 ls0 ws0">Esp<span class="_ _0"></span>ecially<span class="_ _1"> </span>for<span class="_ _1"> </span>T</div><div class="t m0 xe0 h2 y3da ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t ma xe2 h2 y34 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _1"> </span>users,<span class="_ _1"> </span>it<span class="_ _8"> </span>is<span class="_ _1"> </span>p<span class="_ _0"></span>ossible<span class="_ _1"> </span>to<span class="_ _1"> </span>mark</div><div class="t m13 xd h2 y35 ff1 fs0 fc0 sc0 ls0 ws0">text<span class="_ _1"> </span>paragraphs<span class="_ _1"> </span>suc<span class="_ _5"></span>h<span class="_ _1"> </span>that<span class="_ _1"> </span>text<span class="_ _1"> </span>will<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>reflow<span class="_ _e"></span>able<span class="_ _1"> </span>in</div><div class="t m4 xd h2 y36 ff4 fs1 fc0 sc0 ls0 ws0">HTML<span class="_ _1"> </span><span class="ff1 fs0">to<span class="_ _1"> </span>some<span class="_ _1"> </span>exten<span class="_ _5"></span>t;<span class="_ _1"> </span>also,<span class="_ _1"> </span>mathematical<span class="_ _1"> </span>formulas</span></div><div class="t m2 xd h2 y37 ff1 fs0 fc0 sc0 ls0 ws0">ma<span class="_ _e"></span>y<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>mark<span class="_ _e"></span>ed<span class="_ _1"> </span>such<span class="_ _8"> </span>that<span class="_ _8"> </span>they<span class="_ _1"> </span>will<span class="_ _8"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>rendered<span class="_ _1"> </span>with</div><div class="t m0 xd h2 y38 ff1 fs0 fc0 sc0 ls0 ws0">MathJaX<span class="_ _1"> </span>in<span class="_ _1"> </span><span class="ff4 fs1">HTML</span>.</div><div class="t m0 x1c h2 y77 ff1 fs0 fc0 sc0 ls0 ws0">Online<span class="_ _1"> </span>publishing<span class="_ _1"> </span>via<span class="_ _1"> </span>p<span class="_ _0"></span>df2h<span class="_ _e"></span>tm<span class="_ _0"></span>l<span class="ff4 fs1">EX</span></div><a class="l" href="#pfa" data-dest-detail='[10,"XYZ",299.219,453.316,null]'><div class="d m1d" style="border-style:none;position:absolute;left:442.185621px;bottom:429.974588px;width:6.874000px;height:10.848000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfa" data-dest-detail='[10,"XYZ",295.507,156.429,null]'><div class="d m1d" style="border-style:none;position:absolute;left:484.395503px;bottom:429.974588px;width:6.874000px;height:10.848000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfb" data-dest-detail='[11,"XYZ",262.8,419.323,null]'><div class="d m1d" style="border-style:none;position:absolute;left:751.077229px;bottom:1139.787294px;width:11.835000px;height:10.848000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="#pfc" data-dest-detail='[12,"XYZ",72,307.547,null]'><div class="d m1d" style="border-style:none;position:absolute;left:719.482144px;bottom:1083.018876px;width:11.955000px;height:8.413000px;background-color:rgba(255,255,255,0.000001);"></div></a></div><div class="pi" data-data='{"ctm":[1.673203,0.000000,0.000000,1.673203,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x0 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">322<span class="_ _3"> </span>TUGb<span class="_ _0"></span>oat,<span class="_ _1"> </span>V<span class="_ _2"></span>olume<span class="_ _1"> </span>34<span class="_ _1"> </span>(2013),<span class="_ _1"> </span>No.<span class="_ _1"> </span>3</div><div class="t m0 xe3 h13 y3dc ff3 fs1 fc0 sc0 ls0 ws0">Figure<span class="_ _1"> </span>8<span class="ff4">:<span class="_ _9"> </span>The<span class="_ _8"> </span>text<span class="_ _8"> </span>lay<span class="_ _e"></span>er</span></div><div class="t m0 xe4 h13 y3dd ff3 fs1 fc0 sc0 ls0 ws0">Figure<span class="_ _1"> </span>9<span class="ff4">:<span class="_ _9"> </span>The<span class="_ _8"> </span>image<span class="_ _8"> </span>lay<span class="_ _e"></span>er</span></div><div class="t m0 x0 h2 y77 ff1 fs0 fc0 sc0 ls0 ws0">Lu<span class="_ _1"> </span>W<span class="_ _2"></span>ang<span class="_ _1"> </span>and<span class="_ _1"> </span>W<span class="_ _2"></span>anmin<span class="_ _1"> </span>Liu</div></div><div class="pi" data-data='{"ctm":[1.673203,0.000000,0.000000,1.673203,0.000000,0.000000]}'></div></div>
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"/><div class="t m0 x0 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">TUGb<span class="_ _0"></span>oat,<span class="_ _8"> </span>V<span class="_ _2"></span>olume<span class="_ _8"> </span>34<span class="_ _8"> </span>(2013),<span class="_ _8"> </span>No.<span class="_ _8"> </span>3<span class="_ _34"> </span>323</div><div class="t m0 x71 h13 y3df ff3 fs1 fc0 sc0 ls0 ws0">Figure<span class="_ _1"> </span>10<span class="ff4">:<span class="_ _9"> </span>F<span class="_ _2"></span>onts<span class="_ _8"> </span>em<span class="_ _5"></span>b<span class="_ _0"></span>edded<span class="_ _8"> </span>in<span class="_ _8"> </span>the<span class="_ _8"> </span><span class="ffa fs4">HTML<span class="_ _8"> </span></span>file</span></div><div class="t m0 x0 h3 y3e0 ff2 fs0 fc0 sc0 ls0 ws0">Image<span class="_ _4"> </span>ov<span class="_ _e"></span>erla<span class="_ _e"></span>y</div><div class="t m1 xe5 h2 y3e0 ff1 fs0 fc0 sc0 ls0 ws0">F<span class="_ _2"></span>or<span class="_ _1"> </span>each<span class="_ _8"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>page,<span class="_ _1"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX</span></div><div class="t m19 x0 h2 y3e1 ff1 fs0 fc0 sc0 ls0 ws0">puts<span class="_ _1"> </span>all<span class="_ _1"> </span>non-text<span class="_ _1"> </span>elements<span class="_ _8"> </span>into<span class="_ _8"> </span>a<span class="_ _4"> </span>bac<span class="_ _e"></span>kground<span class="_ _1"> </span>image;</div><div class="t m1 x0 h2 y3e2 ff1 fs0 fc0 sc0 ls0 ws0">this<span class="_ _4"> </span>image<span class="_ _9"> </span>is<span class="_ _4"> </span>then<span class="_ _4"> </span>put<span class="_ _9"> </span>behind<span class="_ _9"> </span>all<span class="_ _4"> </span>the<span class="_ _9"> </span>text<span class="_ _4"> </span>in<span class="_ _4"> </span>that</div><div class="t m2 x0 h2 y3e3 ff1 fs0 fc0 sc0 ls0 ws0">page.<span class="_ _9"> </span>How<span class="_ _e"></span>ever, it is<span class="_ _8"> </span>p<span class="_ _0"></span>ossible that<span class="_ _8"> </span>some text<span class="_ _8"> </span>is<span class="_ _8"> </span>in fact</div><div class="t m2 x0 h2 y3e4 ff1 fs0 fc0 sc0 ls0 ws0">co<span class="_ _e"></span>vered by an image<span class="_ _8"> </span>in the<span class="_ _8"> </span><span class="ff4 fs1">PDF</span>,<span class="_ _8"> </span>in which case in<span class="_ _8"> </span>the</div><div class="t mc x0 h2 y3e5 ff1 fs0 fc0 sc0 ls0 ws0">corresp<span class="_ _0"></span>onding<span class="_ _1"> </span><span class="ff4 fs1">HTML<span class="_ _1"> </span></span>file<span class="_ _1"> </span>pro<span class="_ _0"></span>duced<span class="_ _1"> </span>b<span class="_ _e"></span>y<span class="_ _1"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX</span>,</div><div class="t m0 x0 h2 y3e6 ff1 fs0 fc0 sc0 ls0 ws0">the<span class="_ _1"> </span>text<span class="_ _1"> </span>will<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>visible<span class="_ _1"> </span>due<span class="_ _1"> </span>to<span class="_ _1"> </span>the<span class="_ _1"> </span>sup<span class="_ _0"></span>erimp<span class="_ _0"></span>osition.</div><div class="t m1 x1 h2 y3e7 ff1 fs0 fc0 sc0 ls0 ws0">W<span class="_ _2"></span>e<span class="_ _9"> </span>are<span class="_ _9"> </span>still<span class="_ _7"> </span>lo<span class="_ _0"></span>oking<span class="_ _9"> </span>for<span class="_ _7"> </span>efficient<span class="_ _4"> </span>solutions<span class="_ _7"> </span>for</div><div class="t m1 x0 h2 y3e8 ff1 fs0 fc0 sc0 ls0 ws0">this<span class="_ _11"> </span>issue;<span class="_ _30"> </span>fortunately<span class="_ _2"></span>,<span class="_ _33"> </span>this<span class="_ _11"> </span>issue<span class="_ _11"> </span>is<span class="_ _11"> </span>not<span class="_ _11"> </span>common,</div><div class="t m2 x0 h2 y3e9 ff1 fs0 fc0 sc0 ls0 ws0">esp<span class="_ _0"></span>ecially<span class="_ _8"> </span>for<span class="_ _1"> </span>T</div><div class="t m0 xe6 h2 y3ea ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m2 x55 h2 y3e9 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _8"> </span>users.<span class="_ _7"> </span>A<span class="_ _1"> </span>work<span class="_ _2"></span>around<span class="_ _1"> </span>is<span class="_ _1"> </span>to<span class="_ _8"> </span>use<span class="_ _1"> </span>the</div><div class="t m1 x0 h2 y3eb ff5 fs0 fc0 sc0 ls0 ws0">fal<span class="_ _0"></span>lb<span class="_ _e"></span>ack<span class="_ _9"> </span><span class="ff1">mode<span class="_ _4"> </span>of<span class="_ _4"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX<span class="_ _4"> </span></span>at<span class="_ _4"> </span>the<span class="_ _4"> </span>cost<span class="_ _4"> </span>of<span class="_ _4"> </span>larger</span></div><div class="t m0 x0 h2 y3ec ff1 fs0 fc0 sc0 ls0 ws0">file<span class="_ _1"> </span>size.</div><div class="t m0 x0 h3 y3ed ff2 fs0 fc0 sc0 ls0 ws0">Image<span class="_ _4"> </span>optimization</div><div class="t mf x2a h2 y3ed ff1 fs0 fc0 sc0 ls0 ws0">When<span class="_ _1"> </span>generating<span class="_ _1"> </span>the<span class="_ _1"> </span>bac<span class="_ _e"></span>k-</div><div class="t m1a x0 h2 y3ee ff1 fs0 fc0 sc0 ls0 ws0">ground<span class="_ _1"> </span>image,<span class="_ _1"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX<span class="_ _8"> </span></span>calculates<span class="_ _1"> </span>the<span class="_ _1"> </span>b<span class="_ _0"></span>ounding</div><div class="t m1 x0 h2 y3ef ff1 fs0 fc0 sc0 ls0 ws0">b<span class="_ _0"></span>o<span class="_ _e"></span>x<span class="_ _4"> </span>of<span class="_ _8"> </span>all<span class="_ _1"> </span>non-text<span class="_ _1"> </span>elements<span class="_ _1"> </span>in<span class="_ _1"> </span>that<span class="_ _1"> </span>page,<span class="_ _1"> </span>and<span class="_ _4"> </span>ren-</div><div class="t m11 x0 h2 y3f0 ff1 fs0 fc0 sc0 ls0 ws0">ders<span class="_ _1"> </span>ev<span class="_ _e"></span>erything<span class="_ _1"> </span>inside.<span class="_ _7"> </span>How<span class="_ _e"></span>ever,<span class="_ _8"> </span>if<span class="_ _1"> </span>there<span class="_ _1"> </span>are<span class="_ _1"> </span>only<span class="_ _1"> </span>a</div><div class="t m2 x0 h2 y3f1 ff1 fs0 fc0 sc0 ls0 ws0">few images<span class="_ _8"> </span>which are<span class="_ _8"> </span>far<span class="_ _8"> </span>aw<span class="_ _e"></span>ay from each other,<span class="_ _8"> </span>most</div><div class="t m7 x0 h2 y3f2 ff1 fs0 fc0 sc0 ls0 ws0">parts<span class="_ _1"> </span>in<span class="_ _1"> </span>the<span class="_ _1"> </span>image<span class="_ _1"> </span>are<span class="_ _1"> </span>actually<span class="_ _1"> </span>blank,<span class="_ _1"> </span>which<span class="_ _8"> </span>will<span class="_ _1"> </span>b<span class="_ _0"></span>e</div><div class="t m2 x0 h2 y3f3 ff1 fs0 fc0 sc0 ls0 ws0">a<span class="_ _8"> </span>waste of<span class="_ _8"> </span>bandwidth.<span class="_ _7"> </span>It<span class="_ _8"> </span>is<span class="_ _1"> </span>p<span class="_ _0"></span>ossible<span class="_ _8"> </span>to<span class="_ _8"> </span>recognize<span class="_ _8"> </span>and</div><div class="t m2 x0 h2 y3f4 ff1 fs0 fc0 sc0 ls0 ws0">split<span class="_ _d"> </span>those<span class="_ _14"> </span>small images<span class="_ _14"> </span>and pac<span class="_ _e"></span>k them<span class="_ _14"> </span>into<span class="_ _14"> </span>one small</div><div class="t m6 x0 h2 y3f5 ff1 fs0 fc0 sc0 ls0 ws0">image,<span class="_ _1"> </span>suc<span class="_ _e"></span>h<span class="_ _1"> </span>that<span class="_ _1"> </span>they<span class="_ _1"> </span>will<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>loaded<span class="_ _1"> </span>using<span class="_ _8"> </span>the<span class="_ _1"> </span><span class="ff4 fs1">CSS</span></div><div class="t m2e x0 h2 y3f6 ff1 fs0 fc0 sc0 ls0 ws0">sprite<span class="_ _8"> </span>technique.<span class="_ _9"> </span>In<span class="_ _1"> </span>this<span class="_ _1"> </span>wa<span class="_ _e"></span>y<span class="_ _1"> </span>significant<span class="_ _8"> </span>bandwidth</div><div class="t m0 x0 h2 y3f7 ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _1"> </span>computation<span class="_ _1"> </span>can<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>sa<span class="_ _5"></span>v<span class="_ _e"></span>e<span class="_ _0"></span>d.</div><div class="t m0 xd h3 y3e0 ff2 fs0 fc0 sc0 ls0 ws0">4.8<span class="_ _c"> </span>Discussion</div><div class="t m12 xd h2 y3f8 ff1 fs0 fc0 sc0 ls0 ws0">In<span class="_ _1"> </span>this<span class="_ _1"> </span>section<span class="_ _1"> </span>we<span class="_ _8"> </span>introduced<span class="_ _1"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX<span class="_ _8"> </span></span>from<span class="_ _1"> </span>sev-</div><div class="t m1 xd h2 y3f9 ff1 fs0 fc0 sc0 ls0 ws0">eral<span class="_ _11"> </span>p<span class="_ _0"></span>ersp<span class="_ _0"></span>ectiv<span class="_ _e"></span>es.<span class="_ _29"> </span>Due<span class="_ _11"> </span>to<span class="_ _11"> </span>space<span class="_ _11"> </span>limitations<span class="_ _11"> </span>here,</div><div class="t mb x7b h2 y3fa ff1 fs0 fc0 sc0 ls0 ws0">w<span class="_ _5"></span>e<span class="_ _8"> </span>cannot<span class="_ _1"> </span>present<span class="_ _8"> </span>everything<span class="_ _17"> </span>—<span class="_ _10"> </span>there<span class="_ _1"> </span>are<span class="_ _8"> </span>nearly<span class="_ _1"> </span>50</div><div class="t m1 xd h2 y3fb ff1 fs0 fc0 sc0 ls0 ws0">differen<span class="_ _5"></span>t<span class="_ _1"> </span>options<span class="_ _1"> </span>in<span class="_ _4"> </span>total,<span class="_ _1"> </span>and<span class="_ _1"> </span>there<span class="_ _4"> </span>are<span class="_ _8"> </span>also<span class="_ _4"> </span>tric<span class="_ _e"></span>ky</div><div class="t m2 xd h2 y3fc ff1 fs0 fc0 sc0 ls0 ws0">implemen<span class="_ _e"></span>tations<span class="_ _1"> </span>regarding<span class="_ _8"> </span>font<span class="_ _8"> </span>con<span class="_ _5"></span>v<span class="_ _e"></span>ersion,<span class="_ _1"> </span>text<span class="_ _8"> </span>han-</div><div class="t m1 xd h2 y3fd ff1 fs0 fc0 sc0 ls0 ws0">dling<span class="_ _1"> </span>and<span class="_ _1"> </span>image<span class="_ _1"> </span>pro<span class="_ _0"></span>cessing.<span class="_ _11"> </span>Interested<span class="_ _8"> </span>readers<span class="_ _4"> </span>are</div><div class="t m2f xd h2 y3fe ff1 fs0 fc0 sc0 ls0 ws0">encouraged<span class="_ _1"> </span>to<span class="_ _1"> </span>visit<span class="_ _1"> </span>the<span class="_ _1"> </span>pro<span class="_ _18"></span>ject<span class="_ _1"> </span>web<span class="_ _8"> </span>site<span class="_ _4"> </span>for<span class="_ _8"> </span>detailed</div><div class="t m0 xd h2 y3ff ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _1"> </span>up-to-date<span class="_ _1"> </span>do<span class="_ _0"></span>cumen<span class="_ _5"></span>tation.</div><div class="t m0 xd h3 y400 ff2 fs0 fc0 sc0 ls0 ws0">5<span class="_ _c"> </span>Conclusion</div><div class="t m1 xd h2 y401 ff1 fs0 fc0 sc0 ls0 ws0">In<span class="_ _4"> </span>this<span class="_ _4"> </span>article<span class="_ _4"> </span>we<span class="_ _4"> </span>tried<span class="_ _4"> </span>to<span class="_ _4"> </span>categorize<span class="_ _4"> </span>and<span class="_ _4"> </span>compare</div><div class="t m1 xd h2 y402 ff1 fs0 fc0 sc0 ls0 ws0">existing<span class="_ _8"> </span>metho<span class="_ _0"></span>ds<span class="_ _1"> </span>of<span class="_ _1"> </span>publishing<span class="_ _1"> </span>T</div><div class="t m0 xe7 h2 y403 ff1 fs0 fc0 sc0 ls0 ws0">E</div><div class="t m1 xe8 h2 y402 ff1 fs0 fc0 sc0 ls0 ws0">X<span class="_ _8"> </span>or<span class="_ _1"> </span><span class="ff4 fs1">PDF<span class="_ _1"> </span></span>online.</div><div class="t m2 x7b h2 y404 ff1 fs0 fc0 sc0 ls0 ws0">W<span class="_ _2"></span>e<span class="_ _8"> </span>hop<span class="_ _0"></span>e<span class="_ _1"> </span>that<span class="_ _1"> </span>readers<span class="_ _1"> </span>may<span class="_ _8"> </span>use<span class="_ _1"> </span>this<span class="_ _1"> </span>article<span class="_ _8"> </span>as<span class="_ _1"> </span>a<span class="_ _1"> </span>guide</div><div class="t m26 xd h2 y405 ff1 fs0 fc0 sc0 ls0 ws0">to<span class="_ _1"> </span>choose<span class="_ _1"> </span>the<span class="_ _1"> </span>prop<span class="_ _0"></span>er<span class="_ _4"> </span>tool<span class="_ _1"> </span>for<span class="_ _1"> </span>their<span class="_ _1"> </span>sp<span class="_ _0"></span>ecific<span class="_ _4"> </span>use<span class="_ _8"> </span>cases,</div><div class="t m0 xd h2 y406 ff1 fs0 fc0 sc0 ls0 ws0">or<span class="_ _1"> </span>b<span class="_ _0"></span>e<span class="_ _1"> </span>inspired<span class="_ _1"> </span>to<span class="_ _1"> </span>create<span class="_ _1"> </span>their<span class="_ _1"> </span>o<span class="_ _5"></span>wn<span class="_ _1"> </span>implemen<span class="_ _5"></span>tations.</div><div class="t m2 xe h2 y407 ff1 fs0 fc0 sc0 ls0 ws0">W<span class="_ _2"></span>e<span class="_ _1"> </span>also<span class="_ _1"> </span>in<span class="_ _e"></span>tro<span class="_ _0"></span>duced<span class="_ _1"> </span>our<span class="_ _1"> </span>program<span class="_ _1"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX</span>,<span class="_ _8"> </span>a</div><div class="t m2e xd h2 y408 ff4 fs1 fc0 sc0 ls0 ws0">PDF<span class="_ _1"> </span><span class="ff1 fs0">to<span class="_ _8"> </span></span>HTML<span class="_ _1"> </span><span class="ff1 fs0">conv<span class="_ _e"></span>erter<span class="_ _1"> </span>and<span class="_ _1"> </span>publishing<span class="_ _1"> </span>to<span class="_ _0"></span>ol<span class="_ _1"> </span>which</span></div><div class="t m1a xd h2 y409 ff1 fs0 fc0 sc0 ls0 ws0">is<span class="_ _1"> </span>accurate<span class="_ _1"> </span>and<span class="_ _1"> </span>flexible<span class="_ _1"> </span>for<span class="_ _1"> </span>many<span class="_ _8"> </span>different<span class="_ _8"> </span>use<span class="_ _1"> </span>cases.</div><div class="t m0 x7b h2 y40a ff1 fs0 fc0 sc0 ls0 ws0">W<span class="_ _2"></span>e<span class="_ _1"> </span>encourage<span class="_ _1"> </span>in<span class="_ _5"></span>terested<span class="_ _1"> </span>users<span class="_ _1"> </span>to<span class="_ _1"> </span>get<span class="_ _1"> </span>in<span class="_ _5"></span>v<span class="_ _e"></span>olved.</div><div class="t m0 xd h3 y40b ff2 fs0 fc0 sc0 ls0 ws0">Ac<span class="_ _e"></span>knowledgemen<span class="_ _e"></span>t</div><div class="t m1e x7b h2 y35 ff1 fs0 fc0 sc0 ls0 ws0">W<span class="_ _2"></span>e<span class="_ _1"> </span>thank<span class="_ _1"> </span>Professor<span class="_ _1"> </span>Haruhiko<span class="_ _8"> </span>Okumura<span class="_ _8"> </span>for<span class="_ _1"> </span>his<span class="_ _1"> </span>help</div><div class="t m2 xd h2 y36 ff1 fs0 fc0 sc0 ls0 ws0">and<span class="_ _8"> </span>great<span class="_ _8"> </span>advice.<span class="_ _7"> </span>W<span class="_ _2"></span>e<span class="_ _1"> </span>also<span class="_ _8"> </span>thank<span class="_ _8"> </span>Professor<span class="_ _1"> </span>Masatak<span class="_ _e"></span>a</div><div class="t m2 xd h2 y37 ff1 fs0 fc0 sc0 ls0 ws0">Kanek<span class="_ _e"></span>o,<span class="_ _1"> </span>Mr<span class="_ _1"> </span>Rapha<span class="_ _e"></span>¨<span class="_ _19"></span>el<span class="_ _8"> </span>Pinson<span class="_ _8"> </span>and<span class="_ _1"> </span>Mr<span class="_ _8"> </span>Jason<span class="_ _1"> </span>Lewis<span class="_ _8"> </span>for</div><div class="t m0 xd h2 y38 ff1 fs0 fc0 sc0 ls0 ws0">the<span class="_ _1"> </span>nice<span class="_ _1"> </span>sample<span class="_ _1"> </span>files<span class="_ _1"> </span>used<span class="_ _1"> </span>in<span class="_ _1"> </span>this<span class="_ _1"> </span>article.</div><div class="t m0 x66 h2 y77 ff1 fs0 fc0 sc0 ls0 ws0">Online<span class="_ _8"> </span>publishing<span class="_ _8"> </span>via<span class="_ _8"> </span>p<span class="_ _0"></span>df2html<span class="ff4 fs1">EX</span></div></div><div class="pi" data-data='{"ctm":[1.673203,0.000000,0.000000,1.673203,0.000000,0.000000]}'></div></div>
<div id="pfc" class="pf w0 h0" data-page-no="c"><div class="pc pcc w0 h0"><div class="t m0 x0 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">324<span class="_ _3"> </span>TUGb<span class="_ _0"></span>oat,<span class="_ _1"> </span>V<span class="_ _2"></span>olume<span class="_ _1"> </span>34<span class="_ _1"> </span>(2013),<span class="_ _1"> </span>No.<span class="_ _1"> </span>3</div><div class="t m0 x0 h3 y39 ff2 fs0 fc0 sc0 ls0 ws0">References</div><div class="t m0 xe9 h13 y40c ff4 fs1 fc0 sc0 ls0 ws0">[1]<span class="_ _f"> </span>L</div><div class="t m0 x4b h7 y40d ff9 fs3 fc0 sc0 ls0 ws0">A</div><div class="t m0 x20 h13 y40c ff4 fs1 fc0 sc0 ls0 ws0">T</div><div class="t m0 x44 h13 y40e ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m0 xea h13 y40c ff4 fs1 fc0 sc0 ls0 ws0">X2<span class="ffa fs4">HTML</span>.<span class="_ _9"> </span><span class="ff15">http://www.latex2html.org</span>,<span class="_ _13"> </span>2001.</div><div class="t m0 xe9 h13 y40f ff4 fs1 fc0 sc0 ls0 ws0">[2]</div><div class="t m1 x41 h13 y40f ff4 fs1 fc0 sc0 ls0 ws0">jsT</div><div class="t m0 x21 h13 y410 ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 xea h13 y40f ff4 fs1 fc0 sc0 ls0 ws0">X.</div><div class="t m0 xeb h25 y40f ff15 fs1 fc0 sc0 ls0 ws0">http://simile.mit.edu/wiki/JsTeX</div><div class="t m1 xec h13 y40f ff4 fs1 fc0 sc0 ls0 ws0">,</div><div class="t m0 x41 h13 y411 ff4 fs1 fc0 sc0 ls0 ws0">2008.</div><div class="t m0 xe9 h13 y390 ff4 fs1 fc0 sc0 ls0 ws0">[3]</div><div class="t m1 x41 h13 y390 ff4 fs1 fc0 sc0 ls0 ws0">Go<span class="_ _0"></span>ogle<span class="_ _13"> </span>Do<span class="_ _0"></span>cs<span class="_ _8"> </span>Viewer.</div><div class="t m0 x5c h25 y390 ff15 fs1 fc0 sc0 ls0 ws0">https://docs.google.com/</div><div class="t m0 x41 h13 y412 ff15 fs1 fc0 sc0 ls0 ws0">viewer<span class="ff4">,<span class="_ _8"> </span>2009.</span></div><div class="t m0 xe9 h13 y392 ff4 fs1 fc0 sc0 ls0 ws0">[4]</div><div class="t m1 x41 h13 y392 ff4 fs1 fc0 sc0 ls0 ws0">jsMath:<span class="_ _7"> </span>A<span class="_ _8"> </span>Metho<span class="_ _0"></span>d<span class="_ _8"> </span>of<span class="_ _8"> </span>Including<span class="_ _13"> </span>Mathematics<span class="_ _8"> </span>in</div><div class="t m1 x3a h13 y413 ff4 fs1 fc0 sc0 ls0 ws0">W<span class="_ _2"></span>eb<span class="_ _8"> </span>Pages.</div><div class="t m0 x70 h25 y413 ff15 fs1 fc0 sc0 ls0 ws0">http://www.math.union.edu/</div><div class="t m0 xed h25 y414 ff15 fs1 fc0 sc0 ls0 ws0">~</div><div class="t m0 xab h25 y413 ff15 fs1 fc0 sc0 ls0 ws0">dpvc/</div><div class="t m0 x41 h13 y415 ff15 fs1 fc0 sc0 ls0 ws0">jsmath<span class="ff4">,<span class="_ _8"> </span>2009.</span></div><div class="t m0 xe9 h13 y416 ff4 fs1 fc0 sc0 ls0 ws0">[5]</div><div class="t m1 x41 h13 y416 ff4 fs1 fc0 sc0 ls0 ws0">plasT</div><div class="t m0 xee h13 y417 ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 xef h13 y416 ff4 fs1 fc0 sc0 ls0 ws0">X.</div><div class="t m0 xb0 h25 y416 ff15 fs1 fc0 sc0 ls0 ws0">http://plastex.sourceforge.net</div><div class="t m1 xec h13 y416 ff4 fs1 fc0 sc0 ls0 ws0">,</div><div class="t m0 x41 h13 y418 ff4 fs1 fc0 sc0 ls0 ws0">2009.</div><div class="t m0 xe9 h13 y419 ff4 fs1 fc0 sc0 ls0 ws0">[6]</div><div class="t m1 x41 h13 y419 ff4 fs1 fc0 sc0 ls0 ws0">T</div><div class="t m0 xf0 h13 y41a ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 x43 h13 y419 ff4 fs1 fc0 sc0 ls0 ws0">X4h<span class="_ _5"></span>t:<span class="_ _7"> </span>L</div><div class="t m0 xf1 h7 y41b ff9 fs3 fc0 sc0 ls0 ws0">A</div><div class="t m1 xcb h13 y419 ff4 fs1 fc0 sc0 ls0 ws0">T</div><div class="t m0 x55 h13 y41a ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 x92 h13 y419 ff4 fs1 fc0 sc0 ls0 ws0">X<span class="_ _8"> </span>and<span class="_ _13"> </span>T</div><div class="t m0 xf2 h13 y41a ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 x2d h13 y419 ff4 fs1 fc0 sc0 ls0 ws0">X<span class="_ _8"> </span>for<span class="_ _13"> </span>Hyp<span class="_ _0"></span>ertext.</div><div class="t m0 x41 h13 y41c ff15 fs1 fc0 sc0 ls0 ws0">http://tug.org/tex4ht<span class="ff4">,<span class="_ _8"> </span>2010.</span></div><div class="t m0 xe9 h13 y41d ff4 fs1 fc0 sc0 ls0 ws0">[7]</div><div class="t m1 x41 h13 y41d ff4 fs1 fc0 sc0 ls0 ws0">MathJaX:<span class="_ _8"> </span>Beautiful<span class="_ _13"> </span>math<span class="_ _8"> </span>in<span class="_ _8"> </span>all<span class="_ _8"> </span>browsers.</div><div class="t m0 x41 h13 y41e ff15 fs1 fc0 sc0 ls0 ws0">http://www.mathjax.org<span class="ff4">,<span class="_ _8"> </span>2011.</span></div><div class="t m0 xe9 h13 y41f ff4 fs1 fc0 sc0 ls0 ws0">[8]</div><div class="t m1 x41 h13 y41f ff4 fs1 fc0 sc0 ls0 ws0">Bible<span class="_ _8"> </span>de<span class="_ _13"> </span>Gen`<span class="_ _19"></span>eve,<span class="_ _13"> </span>1564.</div><div class="t m0 xf3 h25 y41f ff15 fs1 fc0 sc0 ls0 ws0">https://github.com/</div><div class="t m0 x41 h13 y420 ff15 fs1 fc0 sc0 ls0 ws0">raphink/geneve_1564<span class="ff4">,<span class="_ _8"> </span>2012.</span></div><div class="t m0 xe9 h13 y421 ff4 fs1 fc0 sc0 ls0 ws0">[9]</div><div class="t m1 x41 h13 y421 ff4 fs1 fc0 sc0 ls0 ws0">mathT</div><div class="t m0 xef h13 y422 ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 xeb h13 y421 ff4 fs1 fc0 sc0 ls0 ws0">X.</div><div class="t m0 xf4 h25 y421 ff15 fs1 fc0 sc0 ls0 ws0">http://www.forkosh.com/mathtex.</div><div class="t m0 x41 h13 y423 ff15 fs1 fc0 sc0 ls0 ws0">html<span class="ff4">,<span class="_ _8"> </span>2012.</span></div><div class="t m0 x0 h13 y424 ff4 fs1 fc0 sc0 ls0 ws0">[10]</div><div class="t m1 x41 h13 y424 ff4 fs1 fc0 sc0 ls0 ws0">Quic<span class="_ _5"></span>kL</div><div class="t m0 xef h7 y425 ff9 fs3 fc0 sc0 ls0 ws0">A</div><div class="t m1 xf5 h13 y424 ff4 fs1 fc0 sc0 ls0 ws0">T</div><div class="t m0 xf6 h13 y426 ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 xf1 h13 y424 ff4 fs1 fc0 sc0 ls0 ws0">X<span class="_ _17"> </span>—<span class="_ _17"> </span>adv<span class="_ _e"></span>anced<span class="_ _8"> </span>L</div><div class="t m0 xf7 h7 y425 ff9 fs3 fc0 sc0 ls0 ws0">A</div><div class="t m1 x2c h13 y424 ff4 fs1 fc0 sc0 ls0 ws0">T</div><div class="t m0 xf8 h13 y426 ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 x93 h13 y424 ff4 fs1 fc0 sc0 ls0 ws0">X<span class="_ _8"> </span>w<span class="_ _5"></span>eb<span class="_ _8"> </span>rendering</div><div class="t m0 x41 h13 y427 ff4 fs1 fc0 sc0 ls0 ws0">service.<span class="_ _9"> </span><span class="ff15">http://quicklatex.com</span>,<span class="_ _13"> </span>2012.</div><div class="t m0 x0 h13 y428 ff4 fs1 fc0 sc0 ls0 ws0">[11]<span class="_ _f"> </span>SpringerLink.<span class="_ _9"> </span><span class="ff15">http://link.springer.com/</span>,<span class="_ _13"> </span>2012.</div><div class="t m0 x0 h13 y429 ff4 fs1 fc0 sc0 ls0 ws0">[12]</div><div class="t m1 x41 h13 y429 ff4 fs1 fc0 sc0 ls0 ws0">TtH:<span class="_ _8"> </span>The<span class="_ _13"> </span>T</div><div class="t m0 x6f h13 y42a ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 x33 h13 y429 ff4 fs1 fc0 sc0 ls0 ws0">X<span class="_ _8"> </span>to<span class="_ _13"> </span><span class="ffa fs4">HTML<span class="_ _8"> </span></span>translator.</div><div class="t m0 x91 h25 y429 ff15 fs1 fc0 sc0 ls0 ws0">http:</div><div class="t m0 x3a h13 y42b ff15 fs1 fc0 sc0 ls0 ws0">//hutchinson.belmont.ma.us/tth<span class="ff4">,<span class="_ _8"> </span>2012.</span></div><div class="t m0 x0 h13 y42c ff4 fs1 fc0 sc0 ls0 ws0">[13]</div><div class="t m1 x41 h13 y42c ffa fs4 fc0 sc0 ls0 ws0">PDF<span class="_ _31"></span><span class="ff4 fs1">.<span class="_ _16"></span>js.</span></div><div class="t m0 xf9 h25 y42c ff15 fs1 fc0 sc0 ls0 ws0">https://github.com/mozilla/pdf.js</div><div class="t m1 xfa h13 y42c ff4 fs1 fc0 sc0 ls0 ws0">,</div><div class="t m0 x41 h13 y42d ff4 fs1 fc0 sc0 ls0 ws0">2013.</div><div class="t m0 x0 h13 y42e ff4 fs1 fc0 sc0 ls0 ws0">[14]</div><div class="t m2 x41 h13 y42e ff4 fs1 fc0 sc0 ls0 ws0">T</div><div class="t m0 x38 h13 y42f ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m2 x43 h13 y42e ff4 fs1 fc0 sc0 ls0 ws0">X2page.</div><div class="t m0 xfb h25 y42e ff15 fs1 fc0 sc0 ls0 ws0">http://www.ccs.neu.edu/home/dorai/</div><div class="t m0 x41 h13 y430 ff15 fs1 fc0 sc0 ls0 ws0">tex2page/index.html<span class="ff4">,<span class="_ _8"> </span>2013.</span></div><div class="t m0 x0 h13 y431 ff4 fs1 fc0 sc0 ls0 ws0">[15]</div><div class="t m1 x41 h13 y431 ff4 fs1 fc0 sc0 ls0 ws0">Cro<span class="_ _0"></span>codo<span class="_ _0"></span>c:<span class="_ _11"> </span><span class="ffa fs4">HTML</span>5<span class="_ _8"> </span>Document<span class="_ _13"> </span>Embedding.</div><div class="t m0 x41 h13 y432 ff15 fs1 fc0 sc0 ls0 ws0">https://crocodoc.com<span class="ff4">,<span class="_ _8"> </span>2013.</span></div><div class="t m0 x0 h13 y433 ff4 fs1 fc0 sc0 ls0 ws0">[16]</div><div class="t m1 x41 h13 y433 ff16 fs1 fc0 sc0 ls0 ws0">Differ<span class="_ _e"></span>ential<span class="_ _8"> </span>and<span class="_ _8"> </span>Inte<span class="_ _e"></span>gr<span class="_ _e"></span>al<span class="_ _8"> </span>II<span class="ff4">.<span class="_ _11"> </span>Dai-Nipp<span class="_ _0"></span>on<span class="_ _8"> </span>T<span class="_ _e"></span>osho</span></div><div class="t m0 x41 h13 y434 ff4 fs1 fc0 sc0 ls0 ws0">Publisher,<span class="_ _8"> </span>2013.</div><div class="t m0 x0 h13 y435 ff4 fs1 fc0 sc0 ls0 ws0">[17]</div><div class="t m1 x41 h13 y435 ff4 fs1 fc0 sc0 ls0 ws0">dvisvgm:<span class="_ _7"> </span>A<span class="_ _8"> </span><span class="ffa fs4">DVI<span class="_ _13"> </span></span>to<span class="_ _8"> </span><span class="ffa fs4">SVG<span class="_ _13"> </span></span>conv<span class="_ _e"></span>erter.</div><div class="t m0 x26 h25 y435 ff15 fs1 fc0 sc0 ls0 ws0">http:</div><div class="t m0 x3a h13 y436 ff15 fs1 fc0 sc0 ls0 ws0">//dvisvgm.sourceforge.net<span class="ff4">,<span class="_ _8"> </span>2013.</span></div><div class="t m0 x0 h13 y437 ff4 fs1 fc0 sc0 ls0 ws0">[18]</div><div class="t m1 x41 h13 y437 ff4 fs1 fc0 sc0 ls0 ws0">F<span class="_ _2"></span>ontF<span class="_ _31"></span>orge:<span class="_ _11"> </span>A<span class="_ _8"> </span>fon<span class="_ _5"></span>t<span class="_ _8"> </span>editor.</div><div class="t m0 x2c h25 y437 ff15 fs1 fc0 sc0 ls0 ws0">http://fontforge.org</div><div class="t m1 xfc h13 y437 ff4 fs1 fc0 sc0 ls0 ws0">,</div><div class="t m0 x41 h13 y438 ff4 fs1 fc0 sc0 ls0 ws0">2013.</div><div class="t m0 x0 h13 y439 ff4 fs1 fc0 sc0 ls0 ws0">[19]</div><div class="t m1 x41 h13 y439 ffa fs4 fc0 sc0 ls0 ws0">HEVEA<span class="ff4 fs1">:<span class="_ _7"> </span>A<span class="_ _8"> </span>L</span></div><div class="t m0 x70 h7 y43a ff9 fs3 fc0 sc0 ls0 ws0">A</div><div class="t m1 x92 h13 y439 ff4 fs1 fc0 sc0 ls0 ws0">T</div><div class="t m0 xe5 h13 y43b ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 xfd h13 y439 ff4 fs1 fc0 sc0 ls0 ws0">X<span class="_ _8"> </span>to<span class="_ _13"> </span><span class="ffa fs4">HTML<span class="_ _8"> </span></span>translator.</div><div class="t m0 x41 h13 y43c ff15 fs1 fc0 sc0 ls0 ws0">http://hevea.inria.fr<span class="ff4">,<span class="_ _8"> </span>2013.</span></div><div class="t m0 x0 h13 y43d ff4 fs1 fc0 sc0 ls0 ws0">[20]</div><div class="t m1 x41 h13 y43d ff4 fs1 fc0 sc0 ls0 ws0">ImageMagic<span class="_ _5"></span>k:<span class="_ _7"> </span>Conv<span class="_ _e"></span>ert,<span class="_ _8"> </span>Edit,<span class="_ _8"> </span>And<span class="_ _8"> </span>Comp<span class="_ _0"></span>ose</div><div class="t m0 x41 h13 y43e ff4 fs1 fc0 sc0 ls0 ws0">Images.<span class="_ _9"> </span><span class="ff15">http://www.imagemagick.org</span>,<span class="_ _13"> </span>2013.</div><div class="t m0 x0 h13 y43f ff4 fs1 fc0 sc0 ls0 ws0">[21]</div><div class="t m2e x41 h13 y43f ff4 fs1 fc0 sc0 ls0 ws0">Inkscap<span class="_ _0"></span>e:<span class="_ _7"> </span>An<span class="_ _8"> </span>op<span class="_ _0"></span>en<span class="_ _8"> </span>source<span class="_ _8"> </span>scalable<span class="_ _8"> </span>vector<span class="_ _13"> </span>graphics</div><div class="t m0 x41 h13 y440 ff4 fs1 fc0 sc0 ls0 ws0">editor.<span class="_ _9"> </span><span class="ff15">http://inkscape.org</span>,<span class="_ _13"> </span>2013.</div><div class="t m0 x0 h13 y441 ff4 fs1 fc0 sc0 ls0 ws0">[22]</div><div class="t m1 x41 h13 y441 ff4 fs1 fc0 sc0 ls0 ws0">L</div><div class="t m0 x4b h7 y442 ff9 fs3 fc0 sc0 ls0 ws0">A</div><div class="t m1 x20 h13 y441 ff4 fs1 fc0 sc0 ls0 ws0">T</div><div class="t m0 x21 h13 y443 ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 xea h13 y441 ff4 fs1 fc0 sc0 ls0 ws0">X2<span class="ffa fs4">HTML</span>5<span class="_ _17"> </span>—<span class="_ _17"> </span>interactiv<span class="_ _e"></span>e<span class="_ _8"> </span>math<span class="_ _8"> </span>equations<span class="_ _8"> </span>and</div><div class="t m0 x41 h13 y444 ff4 fs1 fc0 sc0 ls0 ws0">diagrams.<span class="_ _9"> </span><span class="ff15">http://latex2html5.com</span>,<span class="_ _13"> </span>2013.</div><div class="t m0 x0 h13 y445 ff4 fs1 fc0 sc0 ls0 ws0">[23]</div><div class="t m1 x41 h13 y445 ff4 fs1 fc0 sc0 ls0 ws0">MathPla<span class="_ _5"></span>yer:<span class="_ _9"> </span>Display<span class="_ _13"> </span>Math<span class="ffa fs4">ML<span class="_ _8"> </span></span>in<span class="_ _8"> </span>your<span class="_ _13"> </span>browser.</div><div class="t m0 x41 h25 y446 ff15 fs1 fc0 sc0 ls0 ws0">http://www.dessci.com/en/products/</div><div class="t m0 x41 h13 y31 ff15 fs1 fc0 sc0 ls0 ws0">mathplayer<span class="ff4">,<span class="_ _8"> </span>2013.</span></div><div class="t m0 x0 h13 y447 ff4 fs1 fc0 sc0 ls0 ws0">[24]</div><div class="t m1 x41 h13 y447 ff4 fs1 fc0 sc0 ls0 ws0">L</div><div class="t m0 x4b h7 y448 ff9 fs3 fc0 sc0 ls0 ws0">A</div><div class="t m1 x20 h13 y447 ff4 fs1 fc0 sc0 ls0 ws0">T</div><div class="t m0 x21 h13 y449 ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 xea h13 y447 ff4 fs1 fc0 sc0 ls0 ws0">X<span class="ffa fs4">ML</span>:<span class="_ _7"> </span>A<span class="_ _8"> </span>L</div><div class="t m0 xfe h7 y448 ff9 fs3 fc0 sc0 ls0 ws0">A</div><div class="t m1 xe5 h13 y447 ff4 fs1 fc0 sc0 ls0 ws0">T</div><div class="t m0 xae h13 y449 ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 xff h13 y447 ff4 fs1 fc0 sc0 ls0 ws0">X<span class="_ _8"> </span>to<span class="_ _13"> </span><span class="ffa fs4">XML<span class="_ _8"> </span></span>Conv<span class="_ _e"></span>erter.</div><div class="t m0 x41 h13 y33 ff15 fs1 fc0 sc0 ls0 ws0">http://dlmf.nist.gov/LaTeXML<span class="ff4">,<span class="_ _8"> </span>2013.</span></div><div class="t m0 x0 h13 y44a ff4 fs1 fc0 sc0 ls0 ws0">[25]</div><div class="t m1 x41 h13 y44a ff4 fs1 fc0 sc0 ls0 ws0">p<span class="_ _0"></span>df2h<span class="_ _e"></span>tml<span class="ffa fs4">EX</span>:<span class="_ _11"> </span>Conv<span class="_ _e"></span>ert<span class="_ _8"> </span><span class="ffa fs4">PDF<span class="_ _8"> </span></span>to<span class="_ _8"> </span><span class="ffa fs4">HTML<span class="_ _8"> </span></span>without</div><div class="t m1 x41 h13 y35 ff4 fs1 fc0 sc0 ls0 ws0">losing<span class="_ _8"> </span>text<span class="_ _13"> </span>or<span class="_ _8"> </span>format.</div><div class="t m0 x2d h25 y35 ff15 fs1 fc0 sc0 ls0 ws0">https://github.com/</div><div class="t m0 x41 h13 y44b ff15 fs1 fc0 sc0 ls0 ws0">coolwanglu/pdf2htmlex<span class="ff4">,<span class="_ _8"> </span>2013.</span></div><div class="t m0 xd h13 y39 ff4 fs1 fc0 sc0 ls0 ws0">[26]</div><div class="t m1 x1b h13 y39 ff4 fs1 fc0 sc0 ls0 ws0">p<span class="_ _0"></span>df2svg.</div><div class="t m0 x100 h25 y39 ff15 fs1 fc0 sc0 ls0 ws0">http://www.cityinthesky.co.uk/</div><div class="t m0 x1b h13 y44c ff15 fs1 fc0 sc0 ls0 ws0">opensource/pdf2svg<span class="ff4">,<span class="_ _8"> </span>2013.</span></div><div class="t m0 xd h13 y44d ff4 fs1 fc0 sc0 ls0 ws0">[27]<span class="_ _f"> </span>Poppler.<span class="_ _4"> </span><span class="ff15">http://poppler.freedesktop.org</span>,<span class="_ _8"> </span>2013.</div><div class="t m0 xd h13 y44e ff4 fs1 fc0 sc0 ls0 ws0">[28]</div><div class="t m1 x1b h13 y44e ff4 fs1 fc0 sc0 ls0 ws0">The<span class="_ _8"> </span>F<span class="_ _2"></span>eynman<span class="_ _8"> </span>Lectures<span class="_ _8"> </span>on<span class="_ _8"> </span>Ph<span class="_ _5"></span>ysics.</div><div class="t m0 x1b h13 y3d ff15 fs1 fc0 sc0 ls0 ws0">http://www.feynmanlectures.info<span class="ff4">,<span class="_ _8"> </span>2013.</span></div><div class="t m0 xd h13 y44f ff4 fs1 fc0 sc0 ls0 ws0">[29]</div><div class="t m1 x1b h13 y44f ff4 fs1 fc0 sc0 ls0 ws0">Tim<span class="_ _8"> </span>Arnold.<span class="_ _30"> </span>Getting<span class="_ _8"> </span>started<span class="_ _8"> </span>with<span class="_ _13"> </span>plasT</div><div class="t m0 x101 h13 y450 ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 x102 h13 y44f ff4 fs1 fc0 sc0 ls0 ws0">X.</div><div class="t m1 x103 h13 y3f ff16 fs1 fc0 sc0 ls0 ws0">TUGb<span class="_ _e"></span>o<span class="_ _e"></span>at<span class="ff4">,<span class="_ _8"> </span>30(2):180182,<span class="_ _8"> </span>2009.</span></div><div class="t m0 xd3 h25 y3f ff15 fs1 fc0 sc0 ls0 ws0">http://tug.org/</div><div class="t m0 x1b h13 y451 ff15 fs1 fc0 sc0 ls0 ws0">TUGboat/tb30-<span class="_ _0"></span>2/tb95arnold.pdf<span class="ff4">.</span></div><div class="t m0 xd h13 y452 ff4 fs1 fc0 sc0 ls0 ws0">[30]</div><div class="t m1 x1b h13 y41 ff4 fs1 fc0 sc0 ls0 ws0">Karl<span class="_ _8"> </span>Berry<span class="_ _13"> </span>and<span class="_ _8"> </span>David<span class="_ _13"> </span>W<span class="_ _e"></span>alden.<span class="_ _9"> </span>T</div><div class="t m0 xd1 h13 y453 ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 x104 h13 y41 ff4 fs1 fc0 sc0 ls0 ws0">X<span class="_ _8"> </span>P<span class="_ _5"></span>eople:<span class="_ _7"> </span>The</div><div class="t m1 x1b h13 y454 ffa fs4 fc0 sc0 ls0 ws0">TUG<span class="_ _8"> </span><span class="ff4 fs1">in<span class="_ _5"></span>terviews<span class="_ _8"> </span>pro<span class="_ _0"></span>ject<span class="_ _8"> </span>and<span class="_ _8"> </span>b<span class="_ _0"></span>o<span class="_ _0"></span>ok.<span class="_ _33"> </span><span class="ff16">TUGb<span class="_ _e"></span>oat<span class="ff4">,</span></span></span></div><div class="t m1 x1b h13 y455 ff4 fs1 fc0 sc0 ls0 ws0">30(2):196202,<span class="_ _8"> </span>2009.</div><div class="t m0 x105 h25 y455 ff15 fs1 fc0 sc0 ls0 ws0">http://tug.org/TUGboat/</div><div class="t m0 x1b h13 y456 ff15 fs1 fc0 sc0 ls0 ws0">tb30-<span class="_ _0"></span>2/tb95berry-<span class="_ _18"></span>interviews.pdf<span class="ff4">.</span></div><div class="t m0 xd h13 y457 ff4 fs1 fc0 sc0 ls0 ws0">[31]</div><div class="t m1 x1b h13 y457 ff4 fs1 fc0 sc0 ls0 ws0">P<span class="_ _5"></span>eter<span class="_ _8"> </span>Flynn.<span class="_ _30"> </span>L</div><div class="t m0 x1d h7 y458 ff9 fs3 fc0 sc0 ls0 ws0">A</div><div class="t m1 x106 h13 y457 ff4 fs1 fc0 sc0 ls0 ws0">T</div><div class="t m0 xe0 h13 y459 ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 xe2 h13 y457 ff4 fs1 fc0 sc0 ls0 ws0">X<span class="_ _8"> </span>on<span class="_ _13"> </span>the<span class="_ _8"> </span>W<span class="_ _e"></span>eb.<span class="_ _30"> </span><span class="ff16">TUGb<span class="_ _e"></span>o<span class="_ _e"></span>at<span class="ff4">,</span></span></div><div class="t m1 x1b h13 y45a ff4 fs1 fc0 sc0 ls0 ws0">26(1):6667,<span class="_ _8"> </span>2005.</div><div class="t m0 x107 h25 y45a ff15 fs1 fc0 sc0 ls0 ws0">http://tug.org/TUGboat/</div><div class="t m0 x1b h13 y45b ff15 fs1 fc0 sc0 ls0 ws0">tb26-<span class="_ _0"></span>1/flynn.pdf<span class="ff4">.</span></div><div class="t m0 xd h13 y45c ff4 fs1 fc0 sc0 ls0 ws0">[32]</div><div class="t m1 x1b h13 y45c ff4 fs1 fc0 sc0 ls0 ws0">Stephen<span class="_ _8"> </span>A.<span class="_ _13"> </span>F<span class="_ _e"></span>ulling.<span class="_ _9"> </span>Keynote:<span class="_ _11"> </span>T</div><div class="t m0 xe8 h13 y45d ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 xd1 h13 y45c ff4 fs1 fc0 sc0 ls0 ws0">X<span class="_ _8"> </span>and<span class="_ _13"> </span>the<span class="_ _8"> </span>W<span class="_ _e"></span>eb</div><div class="t m2e x1b h13 y45e ff4 fs1 fc0 sc0 ls0 ws0">in<span class="_ _8"> </span>the<span class="_ _8"> </span>higher<span class="_ _8"> </span>education<span class="_ _8"> </span>of<span class="_ _8"> </span>the<span class="_ _8"> </span>future:<span class="_ _7"> </span>Dreams<span class="_ _8"> </span>and</div><div class="t m1 x1b h13 y45f ff4 fs1 fc0 sc0 ls0 ws0">difficulties.<span class="_ _9"> </span><span class="ff16">TUGb<span class="_ _e"></span>o<span class="_ _e"></span>at<span class="ff4">,<span class="_ _8"> </span>20(3):371372,<span class="_ _8"> </span>1999.</span></span></div><div class="t m0 x108 h25 y45f ff15 fs1 fc0 sc0 ls0 ws0">http:</div><div class="t m0 x1b h13 y460 ff15 fs1 fc0 sc0 ls0 ws0">//tug.org/TUGboat/tb11-<span class="_ _0"></span>3/tb29fulling.pdf<span class="ff4">.</span></div><div class="t m0 xd h13 y461 ff4 fs1 fc0 sc0 ls0 ws0">[33]</div><div class="t m1 x1b h13 y461 ff4 fs1 fc0 sc0 ls0 ws0">Eitan<span class="_ _8"> </span>Gurari.<span class="_ _30"> </span>T</div><div class="t m0 x86 h13 y462 ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 xbd h13 y461 ff4 fs1 fc0 sc0 ls0 ws0">X4h<span class="_ _5"></span>t:<span class="_ _7"> </span>HTML<span class="_ _8"> </span>pro<span class="_ _0"></span>duction.</div><div class="t m1 x103 h13 y463 ff16 fs1 fc0 sc0 ls0 ws0">TUGb<span class="_ _e"></span>o<span class="_ _e"></span>at<span class="ff4">,<span class="_ _8"> </span>25(1):3947,<span class="_ _8"> </span>2004.</span></div><div class="t m0 x109 h25 y463 ff15 fs1 fc0 sc0 ls0 ws0">http://tug.org/</div><div class="t m0 x1b h13 y464 ff15 fs1 fc0 sc0 ls0 ws0">TUGboat/tb25-<span class="_ _0"></span>1/gurari.pdf<span class="ff4">.</span></div><div class="t m0 xd h13 y465 ff4 fs1 fc0 sc0 ls0 ws0">[34]</div><div class="t m1 x1b h13 y465 ff4 fs1 fc0 sc0 ls0 ws0">Stev<span class="_ _5"></span>en<span class="_ _8"> </span>G.<span class="_ _8"> </span>Kran<span class="_ _5"></span>tz.<span class="_ _11"> </span><span class="ff16">Handb<span class="_ _e"></span>o<span class="_ _e"></span>ok<span class="_ _8"> </span>of<span class="_ _8"> </span>T<span class="_ _2"></span>ypo<span class="_ _2"></span>gr<span class="_ _e"></span>aphy<span class="_ _8"> </span>for</span></div><div class="t m1 x1b h13 y466 ff16 fs1 fc0 sc0 ls0 ws0">Mathematic<span class="_ _e"></span>al<span class="_ _8"> </span>Scienc<span class="_ _e"></span>es<span class="ff4">.<span class="_ _9"> </span>Chapman<span class="_ _8"> </span>and<span class="_ _8"> </span>Hall/<span class="ffa fs4">CRC</span>,</span></div><div class="t m0 x1b h13 y467 ff4 fs1 fc0 sc0 ls0 ws0">2000.</div><div class="t m0 xd h13 y468 ff4 fs1 fc0 sc0 ls0 ws0">[35]</div><div class="t m1 x1b h13 y468 ff4 fs1 fc0 sc0 ls0 ws0">Jason<span class="_ _8"> </span>Lewis.<span class="_ _9"> </span>Ho<span class="_ _e"></span>w<span class="_ _8"> </span>I<span class="_ _8"> </span>use<span class="_ _8"> </span>L</div><div class="t m0 x10a h7 y469 ff9 fs3 fc0 sc0 ls0 ws0">A</div><div class="t m1 xce h13 y468 ff4 fs1 fc0 sc0 ls0 ws0">T</div><div class="t m0 x82 h13 y46a ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 x83 h13 y468 ff4 fs1 fc0 sc0 ls0 ws0">X<span class="_ _8"> </span>to<span class="_ _13"> </span>make<span class="_ _13"> </span>a<span class="_ _8"> </span>pro<span class="_ _0"></span>duct</div><div class="t m1 x1b h13 y46b ff4 fs1 fc0 sc0 ls0 ws0">catalogue<span class="_ _8"> </span>that<span class="_ _13"> </span>do<span class="_ _0"></span>esnt<span class="_ _8"> </span>lo<span class="_ _0"></span>ok<span class="_ _8"> </span>like<span class="_ _13"> </span>a<span class="_ _8"> </span>dissertation.</div><div class="t m0 x103 h13 y46c ff16 fs1 fc0 sc0 ls0 ws0">TUGb<span class="_ _e"></span>o<span class="_ _e"></span>at<span class="ff4">,<span class="_ _8"> </span>34(3):263267,<span class="_ _8"> </span>2013.</span></div><div class="t m0 xd h13 y46d ff4 fs1 fc0 sc0 ls0 ws0">[36]</div><div class="t m1 x1b h13 y46d ff4 fs1 fc0 sc0 ls0 ws0">Y<span class="_ _2"></span>oshifumi<span class="_ _8"> </span>Maeda<span class="_ _8"> </span>and<span class="_ _8"> </span>Masatak<span class="_ _e"></span>a<span class="_ _8"> </span>Kaneko.</div><div class="t m1 x1b h13 y46e ff4 fs1 fc0 sc0 ls0 ws0">Making<span class="_ _8"> </span>math<span class="_ _13"> </span>textb<span class="_ _0"></span>o<span class="_ _0"></span>oks<span class="_ _8"> </span>and<span class="_ _8"> </span>materials<span class="_ _8"> </span>with</div><div class="t m1 x1b h13 y46f ff4 fs1 fc0 sc0 ls0 ws0">T</div><div class="t m0 x10b h13 y470 ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 x10c h13 y46f ff4 fs1 fc0 sc0 ls0 ws0">X+<span class="ffa fs4">KET</span>pic+h<span class="_ _5"></span>yp<span class="_ _0"></span>erlink.<span class="_ _2e"> </span>Presentation<span class="_ _13"> </span>at</div><div class="t m0 x1b h13 y471 ffa fs4 fc0 sc0 ls0 ws0">TUG<span class="_ _17"> </span><span class="ff4 fs1">2013.</span></div><div class="t m0 xd h13 y472 ff4 fs1 fc0 sc0 ls0 ws0">[37]</div><div class="t m1 x1b h13 y472 ff4 fs1 fc0 sc0 ls0 ws0">Ross<span class="_ _8"> </span>Moore.<span class="_ _a"> </span>Presenting mathematics<span class="_ _8"> </span>and</div><div class="t m1 x1b h13 y473 ff4 fs1 fc0 sc0 ls0 ws0">languages<span class="_ _8"> </span>in<span class="_ _13"> </span>W<span class="_ _e"></span>eb-pages<span class="_ _8"> </span>using<span class="_ _13"> </span>L</div><div class="t m0 x60 h7 y474 ff9 fs3 fc0 sc0 ls0 ws0">A</div><div class="t m1 x10d h13 y473 ff4 fs1 fc0 sc0 ls0 ws0">T</div><div class="t m0 x10e h13 y475 ff4 fs1 fc0 sc0 ls0 ws0">E</div><div class="t m1 x10f h13 y473 ff4 fs1 fc0 sc0 ls0 ws0">X2<span class="ffa fs4">HTML</span>.</div><div class="t m1 x103 h13 y476 ff16 fs1 fc0 sc0 ls0 ws0">TUGb<span class="_ _e"></span>o<span class="_ _e"></span>at<span class="ff4">,<span class="_ _8"> </span>19(2):195203,<span class="_ _8"> </span>1998.</span></div><div class="t m0 xd3 h25 y476 ff15 fs1 fc0 sc0 ls0 ws0">http://tug.org/</div><div class="t m0 x1b h13 y477 ff15 fs1 fc0 sc0 ls0 ws0">TUGboat/tb19-<span class="_ _0"></span>2/tb59moore.pdf<span class="ff4">.</span></div><div class="t m0 xd h13 y478 ff4 fs1 fc0 sc0 ls0 ws0">[38]</div><div class="t m1 x1b h13 y478 ff4 fs1 fc0 sc0 ls0 ws0">The<span class="_ _8"> </span>Stac<span class="_ _5"></span>ks<span class="_ _8"> </span>Pro<span class="_ _0"></span>ject<span class="_ _8"> </span>Authors.<span class="_ _9"> </span>The<span class="_ _8"> </span>Stacks<span class="_ _13"> </span>Pro<span class="_ _18"></span>ject.</div><div class="t m0 x1b h13 y479 ff15 fs1 fc0 sc0 ls0 ws0">http://stacks.math.columbia.edu<span class="ff4">,<span class="_ _8"> </span>2013.</span></div><div class="t m0 x110 h13 y47a ff17 fs1 fc0 sc0 ls0 ws0"><span class="_ _7"> </span><span class="ff4">Lu<span class="_ _8"> </span>W<span class="_ _e"></span>ang</span></div><div class="t m1 x111 h13 y47b ff4 fs1 fc0 sc0 ls0 ws0">Departmen<span class="_ _5"></span>t<span class="_ _8"> </span>of<span class="_ _8"> </span>Computer<span class="_ _13"> </span>Science</div><div class="t m0 x18 h13 y47c ff4 fs1 fc0 sc0 ls0 ws0">and<span class="_ _8"> </span>Engineering</div><div class="t m1 xc8 h13 y47d ff4 fs1 fc0 sc0 ls0 ws0">The<span class="_ _8"> </span>Hong<span class="_ _13"> </span>Kong<span class="_ _8"> </span>Universit<span class="_ _e"></span>y<span class="_ _8"> </span>of</div><div class="t m0 x18 h13 y47e ff4 fs1 fc0 sc0 ls0 ws0">Science<span class="_ _8"> </span>and<span class="_ _8"> </span>T<span class="_ _2"></span>echnology</div><div class="t m0 x111 h13 y47f ff4 fs1 fc0 sc0 ls0 ws0">Hong<span class="_ _8"> </span>Kong</div><div class="t m0 x111 h25 y480 ff15 fs1 fc0 sc0 ls0 ws0">coolwanglu<span class="_ _8"> </span>(at)<span class="_ _8"> </span>gmail<span class="_ _8"> </span>dot<span class="_ _8"> </span>com</div><div class="t m0 x111 h25 y481 ff15 fs1 fc0 sc0 ls0 ws0">http://coolwanglu.github.io/</div><div class="t m0 x110 h13 y482 ff17 fs1 fc0 sc0 ls0 ws0"><span class="_ _7"> </span><span class="ff4">W<span class="_ _2"></span>anmin<span class="_ _1"> </span>Liu</span></div><div class="t m0 x111 h13 y483 ff4 fs1 fc0 sc0 ls0 ws0">Departmen<span class="_ _5"></span>t<span class="_ _8"> </span>of<span class="_ _8"> </span>Mathematics</div><div class="t m1 xc8 h13 y484 ff4 fs1 fc0 sc0 ls0 ws0">The<span class="_ _8"> </span>Hong<span class="_ _13"> </span>Kong<span class="_ _8"> </span>Universit<span class="_ _e"></span>y<span class="_ _8"> </span>of</div><div class="t m0 x18 h13 y485 ff4 fs1 fc0 sc0 ls0 ws0">Science<span class="_ _8"> </span>and<span class="_ _8"> </span>T<span class="_ _2"></span>echnology</div><div class="t m0 x111 h13 y486 ff4 fs1 fc0 sc0 ls0 ws0">Hong<span class="_ _8"> </span>Kong</div><div class="t m0 xc8 h25 y487 ff15 fs1 fc0 sc0 ls0 ws0">wanminliu<span class="_ _8"> </span>(at)<span class="_ _8"> </span>gmail<span class="_ _8"> </span>dot<span class="_ _8"> </span>com</div><div class="t m0 x0 h2 y77 ff1 fs0 fc0 sc0 ls0 ws0">Lu<span class="_ _1"> </span>W<span class="_ _2"></span>ang<span class="_ _1"> </span>and<span class="_ _1"> </span>W<span class="_ _2"></span>anmin<span class="_ _1"> </span>Liu</div><a class="l" href="http://www.latex2html.org"><div class="d m1d" style="border-style:none;position:absolute;left:252.051242px;bottom:1154.280575px;width:119.675000px;height:10.959000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="http://simile.mit.edu/wiki/JsTeX"><div class="d m1d" 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class="d m1d" style="border-style:none;position:absolute;left:401.036549px;bottom:532.508444px;width:57.474000px;height:10.958000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="http://dvisvgm.sourceforge.net"><div class="d m1d" style="border-style:none;position:absolute;left:151.123660px;bottom:514.588444px;width:119.204000px;height:10.211000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="http://fontforge.org"><div class="d m1d" style="border-style:none;position:absolute;left:333.000784px;bottom:492.500497px;width:96.138000px;height:10.959000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="http://hevea.inria.fr"><div class="d m1d" style="border-style:none;position:absolute;left:151.123660px;bottom:434.574222px;width:100.846000px;height:10.212000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="http://www.imagemagick.org"><div class="d m1d" 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style="border-style:none;position:absolute;left:151.123660px;bottom:256.210824px;width:49.066000px;height:9.763000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="http://dlmf.nist.gov/LaTeXML"><div class="d m1d" style="border-style:none;position:absolute;left:151.123660px;bottom:216.202876px;width:133.797000px;height:10.212000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://github.com/coolwanglu/pdf2htmlex"><div class="d m1d" style="border-style:none;position:absolute;left:306.974118px;bottom:176.196601px;width:113.691000px;height:10.212000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="https://github.com/coolwanglu/pdf2htmlex"><div class="d m1d" style="border-style:none;position:absolute;left:151.123660px;bottom:157.859974px;width:100.846000px;height:10.212000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="http://www.cityinthesky.co.uk/opensource/pdf2svg"><div class="d m1d" style="border-style:none;position:absolute;left:622.863059px;bottom:1179.284915px;width:166.990000px;height:10.959000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="http://www.cityinthesky.co.uk/opensource/pdf2svg"><div class="d m1d" style="border-style:none;position:absolute;left:556.192627px;bottom:1161.364915px;width:86.724000px;height:10.212000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="http://poppler.freedesktop.org"><div class="d m1d" style="border-style:none;position:absolute;left:619.391163px;bottom:1139.278641px;width:143.211000px;height:10.959000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="http://www.feynmanlectures.info"><div class="d m1d" style="border-style:none;position:absolute;left:556.192627px;bottom:1099.687320px;width:147.919000px;height:10.212000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" 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style="border-style:none;position:absolute;left:556.192627px;bottom:964.664889px;width:148.915000px;height:10.212000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="http://tug.org/TUGboat/tb26-1/flynn.pdf"><div class="d m1d" style="border-style:none;position:absolute;left:689.320993px;bottom:924.241987px;width:127.271000px;height:10.958000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="http://tug.org/TUGboat/tb26-1/flynn.pdf"><div class="d m1d" style="border-style:none;position:absolute;left:556.192627px;bottom:906.321987px;width:77.808000px;height:10.211000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" href="http://tug.org/TUGboat/tb11-3/tb29fulling.pdf"><div class="d m1d" style="border-style:none;position:absolute;left:857.086327px;bottom:847.560784px;width:27.005000px;height:10.959000px;background-color:rgba(255,255,255,0.000001);"></div></a><a class="l" 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