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Diffstat (limited to 'Master/texmf-dist/doc/latex')
| -rw-r--r-- | Master/texmf-dist/doc/latex/suftesi/README | 35 | ||||
| -rw-r--r-- | Master/texmf-dist/doc/latex/suftesi/suftesi.pdf | bin | 1436414 -> 511701 bytes | |||
| -rw-r--r-- | Master/texmf-dist/doc/latex/suftesi/templates/collection/collection-art1.tex | 149 | ||||
| -rw-r--r-- | Master/texmf-dist/doc/latex/suftesi/templates/collection/collection.tex | 39 | ||||
| -rw-r--r-- | Master/texmf-dist/doc/latex/suftesi/templates/tesi-magistrale/cognome-tesi.pdf | bin | 253726 -> 0 bytes | |||
| -rw-r--r-- | Master/texmf-dist/doc/latex/suftesi/templates/tesi-triennale/cognome-tesi.pdf | bin | 241462 -> 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 Binary files differindex bfdf7288750..1c683f7213d 100644 --- a/Master/texmf-dist/doc/latex/suftesi/suftesi.pdf +++ b/Master/texmf-dist/doc/latex/suftesi/suftesi.pdf 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 Binary files differdeleted file mode 100644 index 364a46b3121..00000000000 --- a/Master/texmf-dist/doc/latex/suftesi/templates/tesi-magistrale/cognome-tesi.pdf +++ /dev/null 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 Binary files differdeleted file mode 100644 index 4c48bf31690..00000000000 --- a/Master/texmf-dist/doc/latex/suftesi/templates/tesi-triennale/cognome-tesi.pdf +++ /dev/null |