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authorKarl Berry <karl@freefriends.org>2013-09-21 21:33:49 +0000
committerKarl Berry <karl@freefriends.org>2013-09-21 21:33:49 +0000
commit0bc09e46cbdb904897c028cca4c170792f03b32f (patch)
tree876119f2cf5d09a60f766297bdf6f911dcf16423 /Master/texmf-dist/doc/latex/suftesi
parent91196b7f1f05127d784069b65ec8c445fa6364ba (diff)
suftesi (21sep13)
git-svn-id: svn://tug.org/texlive/trunk@31713 c570f23f-e606-0410-a88d-b1316a301751
Diffstat (limited to 'Master/texmf-dist/doc/latex/suftesi')
-rw-r--r--Master/texmf-dist/doc/latex/suftesi/README35
-rw-r--r--Master/texmf-dist/doc/latex/suftesi/suftesi.pdfbin1436414 -> 511701 bytes
-rw-r--r--Master/texmf-dist/doc/latex/suftesi/templates/collection/collection-art1.tex149
-rw-r--r--Master/texmf-dist/doc/latex/suftesi/templates/collection/collection.tex39
-rw-r--r--Master/texmf-dist/doc/latex/suftesi/templates/tesi-magistrale/cognome-tesi.pdfbin253726 -> 0 bytes
-rw-r--r--Master/texmf-dist/doc/latex/suftesi/templates/tesi-triennale/cognome-tesi.pdfbin241462 -> 0 bytes
6 files changed, 188 insertions, 35 deletions
diff --git a/Master/texmf-dist/doc/latex/suftesi/README b/Master/texmf-dist/doc/latex/suftesi/README
index a92d0038139..fb91cff9098 100644
--- a/Master/texmf-dist/doc/latex/suftesi/README
+++ b/Master/texmf-dist/doc/latex/suftesi/README
@@ -28,7 +28,6 @@ This work consists of the following files:
tesi-triennale/
conome-tesi.tex
conome-tesi.bib
- conome-tesi.pdf
immagini/
don.png
lamport-png
@@ -36,7 +35,6 @@ This work consists of the following files:
tesi-magistrale/
conome-tesi.tex
conome-tesi.bib
- conome-tesi.pdf
immagini/
don.png
lamport-png
@@ -75,40 +73,7 @@ $ pdflatex suftesi-frn.tex
$ biber suftesi
$ makeindex -s gind.ist -o suftesi.ind suftesi.idx
$ makeindex -s gglo.ist -o suftesi.gls suftesi.glo
-$ xelatex style-roman1.tex
-$ xelatex style-roman2.tex
-$ xelatex style-roman3.tex
-$ xelatex style-roman4.tex
-$ xelatex style-roman5.tex
-$ xelatex style-roman6.tex
-$ xelatex style-italic1.tex
-$ xelatex style-italic2.tex
-$ xelatex style-italic3.tex
-$ xelatex style-italic4.tex
-$ xelatex style-italic5.tex
-$ xelatex style-italic6.tex
-$ xelatex style-italic7.tex
-$ xelatex style-italic8.tex
-$ xelatex style-italic9.tex
-$ xelatex style-italic10.tex
-$ xelatex style-italic11.tex
-$ xelatex style-italic12.tex
-$ xelatex style-smallcaps1.tex
-$ xelatex style-smallcaps2.tex
-$ xelatex style-smallcaps3.tex
-$ xelatex style-smallcaps4.tex
-$ xelatex style-smallcaps5.tex
-$ xelatex style-smallcaps6.tex
-$ xelatex style-smallcaps7.tex
-$ xelatex style-smallcaps8.tex
-$ xelatex style-smallcaps9.tex
-$ xelatex style-smallcaps10.tex
-$ xelatex style-smallcaps11.tex
-$ xelatex style-smallcaps12.tex
-$ xelatex style-elements.tex
-$ xelatex style-sufelements.tex
$ pdflatex frontespizio.tex
-$ pdflatex collect-examples.tex
$ pdflatex suftesi.dtx
$ pdflatex suftesi.dtx
diff --git a/Master/texmf-dist/doc/latex/suftesi/suftesi.pdf b/Master/texmf-dist/doc/latex/suftesi/suftesi.pdf
index bfdf7288750..1c683f7213d 100644
--- a/Master/texmf-dist/doc/latex/suftesi/suftesi.pdf
+++ b/Master/texmf-dist/doc/latex/suftesi/suftesi.pdf
Binary files differ
diff --git a/Master/texmf-dist/doc/latex/suftesi/templates/collection/collection-art1.tex b/Master/texmf-dist/doc/latex/suftesi/templates/collection/collection-art1.tex
new file mode 100644
index 00000000000..e6f1f39496f
--- /dev/null
+++ b/Master/texmf-dist/doc/latex/suftesi/templates/collection/collection-art1.tex
@@ -0,0 +1,149 @@
+% !TEX root = collection.tex
+% !TEX encoding = UTF-8 Unicode
+
+\title{Contrasting Smalltalk and Object-Oriented Languages}
+\author{George Forebrain}
+\maketitle
+
+
+
+\begin{abstract}
+ Simulated annealing and systems, while compelling in theory, have not
+ until recently been considered unfortunate. In fact, few systems
+ engineers would disagree with the visualization of rasterization, which
+ embodies the theoretical principles of algorithms. In order to fulfill
+ this intent, we propose a novel methodology for the understanding of
+ journaling file systems ({JOGGER}), proving that agents can be made
+ pseudorandom, omniscient, and perfect.
+\end{abstract}
+
+
+
+\section{The JOGGER symmetric encryption}
+
+ Hash tables must work. The shortcoming of this type of solution,
+ however, is that information retrieval systems can be made
+ metamorphic, replicated, and linear-time. Though conventional wisdom
+ states that this quandary is usually solved by the deployment of
+ e-commerce, we believe that a different approach is necessary. To what
+ extent can write-back caches be investigated to answer this quandary?
+
+ In order to surmount this problem, we discover how local-area networks
+ can be applied to the synthesis of von Neumann machines. For example,
+ many heuristics analyze the deployment of e-business. Despite the fact
+ that it at first glance seems unexpected, it has ample historical
+ precedence. The basic tenet of this solution is the synthesis of
+ erasure coding. Thus, we see no reason not to use the compelling
+ unification of IPv4 and local-area networks to evaluate the evaluation
+ of voice-over-IP.
+
+ Motivated by these observations, the location-identity split and the
+ UNIVAC computer have been extensively investigated by systems
+ engineers. Although previous solutions to this challenge are outdated,
+ none have taken the certifiable approach we propose in this work. Two
+ properties make this solution perfect: we allow thin clients to store
+ authenticated technology without the exploration of the
+ location-identity split, and also JOGGER is copied from the principles
+ of artificial intelligence. Unfortunately, this approach is often
+ well-received. Despite the fact that such a hypothesis at first glance
+ seems unexpected, it has ample historical precedence. Unfortunately,
+ semantic theory might not be the panacea that information theorists
+ expected. Combined with voice-over-IP, such a hypothesis enables a
+ ``fuzzy'' tool for enabling I/O automata.
+
+ In this work, we make four main contributions. First, we propose new
+ large-scale methodologies ({JOGGER}), which we use to disconfirm that
+ neural networks and symmetric encryption can interact to address this
+ obstacle. We describe a novel algorithm for the intuitive unification
+ of courseware and Moore's Law ({JOGGER}), verifying that the Ethernet
+ can be made multimodal, pseudorandom, and pseudorandom. We prove that
+ while Moore's Law and SCSI disks are largely incompatible, consistent
+ hashing and courseware can agree to accomplish this objective. Lastly, we prove not only that
+ the seminal flexible algorithm for the refinement of access points by
+ Kristen Nygaard et al. is impossible, but that the same is true for
+ redundancy.
+
+ We proceed as follows. First, we motivate the need for lambda calculus.
+ Second, we show the simulation of IPv6. As a result, we conclude.
+
+ Hash tables must work. The shortcoming of this type of solution,
+ however, is that information retrieval systems can be made
+ metamorphic, replicated, and linear-time. Though conventional wisdom
+ states that this quandary is usually solved by the deployment of
+ e-commerce, we believe that a different approach is necessary. To what
+ extent can write-back caches be investigated to answer this quandary?
+
+ In order to surmount this problem, we discover how local-area networks
+ can be applied to the synthesis of von Neumann machines. For example,
+ many heuristics analyze the deployment of e-business. Despite the fact
+ that it at first glance seems unexpected, it has ample historical
+ precedence. The basic tenet of this solution is the synthesis of
+ erasure coding. Thus, we see no reason not to use the compelling
+ unification of IPv4 and local-area networks to evaluate the evaluation
+ of voice-over-IP.
+
+ Motivated by these observations, the location-identity split and the
+ UNIVAC computer have been extensively investigated by systems
+ engineers. Although previous solutions to this challenge are outdated,
+ none have taken the certifiable approach we propose in this work. Two
+ properties make this solution perfect: we allow thin clients to store
+ authenticated technology without the exploration of the
+ location-identity split, and also JOGGER is copied from the principles
+ of artificial intelligence. Unfortunately, this approach is often
+ well-received. Despite the fact that such a hypothesis at first glance
+ seems unexpected, it has ample historical precedence. Unfortunately,
+ semantic theory might not be the panacea that information theorists
+ expected. Combined with voice-over-IP, such a hypothesis enables a
+ ``fuzzy'' tool for enabling I/O automata.
+
+ In this work, we make four main contributions. First, we propose new
+ large-scale methodologies ({JOGGER}), which we use to disconfirm that
+ neural networks and symmetric encryption can interact to address this
+ obstacle. We describe a novel algorithm for the intuitive unification
+ of courseware and Moore's Law ({JOGGER}), verifying that the Ethernet
+ can be made multimodal, pseudorandom, and pseudorandom. We prove that
+ while Moore's Law and SCSI disks are largely incompatible, consistent
+ hashing and courseware can agree to accomplish this objective. Lastly, we prove not only that
+ the seminal flexible algorithm for the refinement of access points by
+ Kristen Nygaard et al. is impossible, but that the same is true for
+ redundancy.
+
+ We proceed as follows. First, we motivate the need for lambda calculus.
+ Second, we show the simulation of IPv6. As a result, we conclude.
+
+ In order to surmount this problem, we discover how local-area networks
+ can be applied to the synthesis of von Neumann machines. For example,
+ many heuristics analyze the deployment of e-business. Despite the fact
+ that it at first glance seems unexpected, it has ample historical
+ precedence. The basic tenet of this solution is the synthesis of
+ erasure coding. Thus, we see no reason not to use the compelling
+ unification of IPv4 and local-area networks to evaluate the evaluation
+ of voice-over-IP.
+
+ Motivated by these observations, the location-identity split and the
+ UNIVAC computer have been extensively investigated by systems
+ engineers. Although previous solutions to this challenge are outdated,
+ none have taken the certifiable approach we propose in this work. Two
+ properties make this solution perfect: we allow thin clients to store
+ authenticated technology without the exploration of the
+ location-identity split, and also JOGGER is copied from the principles
+ of artificial intelligence. Unfortunately, this approach is often
+ well-received. Despite the fact that such a hypothesis at first glance
+ seems unexpected, it has ample historical precedence. Unfortunately,
+ semantic theory might not be the panacea that information theorists
+ expected. Combined with voice-over-IP, such a hypothesis enables a
+ ``fuzzy'' tool for enabling I/O automata.
+
+ In this work, we make four main contributions. First, we propose new
+ large-scale methodologies ({JOGGER}), which we use to disconfirm that
+ neural networks and symmetric encryption can interact to address this
+ obstacle. We describe a novel algorithm for the intuitive unification
+ of courseware and Moore's Law ({JOGGER}), verifying that the Ethernet
+ can be made multimodal, pseudorandom, and pseudorandom. We prove that
+ while Moore's Law and SCSI disks are largely incompatible, consistent
+ hashing and courseware can agree to accomplish this objective. Lastly, we prove not only that
+ the seminal flexible algorithm for the refinement of access points by
+ Kristen Nygaard et al. is impossible, but that the same is true for
+ redundancy.
+
+
diff --git a/Master/texmf-dist/doc/latex/suftesi/templates/collection/collection.tex b/Master/texmf-dist/doc/latex/suftesi/templates/collection/collection.tex
new file mode 100644
index 00000000000..e134b7fa1ea
--- /dev/null
+++ b/Master/texmf-dist/doc/latex/suftesi/templates/collection/collection.tex
@@ -0,0 +1,39 @@
+% !TEX encoding = UTF-8 Unicode
+\documentclass[
+pagelayout=periodicalaureo,
+documentstructure=collection,
+version=screen,
+%%twocolcontents=toc,
+%tocstyle=standard,
+%smallcapsstyle=low,
+%headerstyle=authortitlecenter,%plain,
+%headerfont=roman,%italic,smallcaps
+%authorfont=italic,%roman,smallcaps
+%titlefont=roman,%italic,smallcaps
+%papertitlestyle=left,%center,right,
+]{suftesi}
+
+\usepackage[T1]{fontenc}
+\usepackage[utf8]{inputenc}
+\usepackage{kantlipsum}
+
+\collectiontitle{The intuitive unification
+ of courseware and Moore's Law}
+\collectioneditor{Edited by\\ Mark Runsilk and Catherine Harroth}
+\date{2013}
+
+\begin{document}
+
+\frontispiece
+\bookcolophon
+ {@ 2013 Ivan Valbusa}
+ {This work has been typeset with \LaTeX{}
+ using the \textsf{suftesi} class by Ivan Valbusa.}
+
+\tableofcontents
+
+\includeart{collection-art1}
+%\includeart{collection-art2}
+%\includeart{collection-art3}
+
+\end{document}
diff --git a/Master/texmf-dist/doc/latex/suftesi/templates/tesi-magistrale/cognome-tesi.pdf b/Master/texmf-dist/doc/latex/suftesi/templates/tesi-magistrale/cognome-tesi.pdf
deleted file mode 100644
index 364a46b3121..00000000000
--- a/Master/texmf-dist/doc/latex/suftesi/templates/tesi-magistrale/cognome-tesi.pdf
+++ /dev/null
Binary files differ
diff --git a/Master/texmf-dist/doc/latex/suftesi/templates/tesi-triennale/cognome-tesi.pdf b/Master/texmf-dist/doc/latex/suftesi/templates/tesi-triennale/cognome-tesi.pdf
deleted file mode 100644
index 4c48bf31690..00000000000
--- a/Master/texmf-dist/doc/latex/suftesi/templates/tesi-triennale/cognome-tesi.pdf
+++ /dev/null
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