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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
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Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
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Showing 51 to 54 of 54 (0.042 seconds)| 51 |
含遺失值之列聯表最大概似估計量及模式的探討 / Maximum Likelihood Estimation in Contingency Tables with Missing Data黃珮菁, Huang, Pei-Ching Unknown Date (has links)
在處理具遺失值之類別資料時，傳統的方法是將資料捨棄，但是這通常不是明智之舉，這些遺失某些分類訊息的資料通常還是可以提供其它重要的訊息，尤其當這類型資料的個數佔大多數時，將其捨棄可能使得估計的變異數增加，甚至影響最後的決策。如何將這些遺失某些訊息的資料納入考慮，作出完整的分析是最近幾十年間頗為重要的課題。本文主要整理了五種分析這類型資料的方法，分別為單樣本方法、多樣本方法、概似方程式因式分解法、EM演算法，以上四種方法可使用在資料遺失呈隨機分佈的條件成立下來進行分析。第五種則為樣本遺失不呈隨機分佈之分析方法。 / Traditionally, the simple way to deal with observations for which some of the variables are missing so that they cannot cross-classified into a contingency table simply excludes them from any analysis. However, it is generally agreed that such a practice would usually affect both the accuracy and the precision of the results. The purpose of the study is to bring together some of the sound alternatives available in the literature, and provide a comprehensive review. Four methods for handling data missing at random are discussed, they are single-sample method, multiple-sample method, factorization of the likelihood method, and EM algorithm. In addition, one way of handling data missing not at random is also reviewed.
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Probabilistic and Bayesian nonparametric approaches for recommender systems and networks / Approches probabilistes et bayésiennes non paramétriques pour les systemes de recommandation et les réseauxTodeschini, Adrien 10 November 2016 (has links)
Nous proposons deux nouvelles approches pour les systèmes de recommandation et les réseaux. Dans la première partie, nous donnons d’abord un aperçu sur les systèmes de recommandation avant de nous concentrer sur les approches de rang faible pour la complétion de matrice. En nous appuyant sur une approche probabiliste, nous proposons de nouvelles fonctions de pénalité sur les valeurs singulières de la matrice de rang faible. En exploitant une représentation de modèle de mélange de cette pénalité, nous montrons qu’un ensemble de variables latentes convenablement choisi permet de développer un algorithme espérance-maximisation afin d’obtenir un maximum a posteriori de la matrice de rang faible complétée. L’algorithme résultant est un algorithme à seuillage doux itératif qui adapte de manière itérative les coefficients de réduction associés aux valeurs singulières. L’algorithme est simple à mettre en œuvre et peut s’adapter à de grandes matrices. Nous fournissons des comparaisons numériques entre notre approche et de récentes alternatives montrant l’intérêt de l’approche proposée pour la complétion de matrice à rang faible. Dans la deuxième partie, nous présentons d’abord quelques prérequis sur l’approche bayésienne non paramétrique et en particulier sur les mesures complètement aléatoires et leur extension multivariée, les mesures complètement aléatoires composées. Nous proposons ensuite un nouveau modèle statistique pour les réseaux creux qui se structurent en communautés avec chevauchement. Le modèle est basé sur la représentation du graphe comme un processus ponctuel échangeable, et généralise naturellement des modèles probabilistes existants à structure en blocs avec chevauchement au régime creux. Notre construction s’appuie sur des vecteurs de mesures complètement aléatoires, et possède des paramètres interprétables, chaque nœud étant associé un vecteur représentant son niveau d’affiliation à certaines communautés latentes. Nous développons des méthodes pour simuler cette classe de graphes aléatoires, ainsi que pour effectuer l’inférence a posteriori. Nous montrons que l’approche proposée peut récupérer une structure interprétable à partir de deux réseaux du monde réel et peut gérer des graphes avec des milliers de nœuds et des dizaines de milliers de connections. / We propose two novel approaches for recommender systems and networks. In the first part, we first give an overview of recommender systems and concentrate on the low-rank approaches for matrix completion. Building on a probabilistic approach, we propose novel penalty functions on the singular values of the low-rank matrix. By exploiting a mixture model representation of this penalty, we show that a suitably chosen set of latent variables enables to derive an expectation-maximization algorithm to obtain a maximum a posteriori estimate of the completed low-rank matrix. The resulting algorithm is an iterative soft-thresholded algorithm which iteratively adapts the shrinkage coefficients associated to the singular values. The algorithm is simple to implement and can scale to large matrices. We provide numerical comparisons between our approach and recent alternatives showing the interest of the proposed approach for low-rank matrix completion. In the second part, we first introduce some background on Bayesian nonparametrics and in particular on completely random measures (CRMs) and their multivariate extension, the compound CRMs. We then propose a novel statistical model for sparse networks with overlapping community structure. The model is based on representing the graph as an exchangeable point process, and naturally generalizes existing probabilistic models with overlapping block-structure to the sparse regime. Our construction builds on vectors of CRMs, and has interpretable parameters, each node being assigned a vector representing its level of affiliation to some latent communities. We develop methods for simulating this class of random graphs, as well as to perform posterior inference. We show that the proposed approach can recover interpretable structure from two real-world networks and can handle graphs with thousands of nodes and tens of thousands of edges.
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Web applications using the Google Web Toolkit / Webanwendungen unter Verwendung des Google Web Toolkitsvon Wenckstern, Michael 04 June 2013 (has links) (PDF)
This diploma thesis describes how to create or convert traditional Java programs to desktop-like rich internet applications with the Google Web Toolkit.
The Google Web Toolkit is an open source development environment, which translates Java code to browser and device independent HTML and JavaScript.
Most of the GWT framework parts, including the Java to JavaScript compiler as well as important security issues of websites will be introduced.
The famous Agricola board game will be implemented in the Model-View-Presenter pattern to show that complex user interfaces can be created with the Google Web Toolkit.
The Google Web Toolkit framework will be compared with the JavaServer Faces one to find out which toolkit is the right one for the next web project. / Diese Diplomarbeit beschreibt die Erzeugung desktopähnlicher Anwendungen mit dem Google Web Toolkit und die Umwandlung klassischer Java-Programme in diese.
Das Google Web Toolkit ist eine Open-Source-Entwicklungsumgebung, die Java-Code in browserunabhängiges als auch in geräteübergreifendes HTML und JavaScript übersetzt.
Vorgestellt wird der Großteil des GWT Frameworks inklusive des Java zu JavaScript-Compilers sowie wichtige Sicherheitsaspekte von Internetseiten.
Um zu zeigen, dass auch komplizierte graphische Oberflächen mit dem Google Web Toolkit erzeugt werden können, wird das bekannte Brettspiel Agricola mittels Model-View-Presenter Designmuster implementiert.
Zur Ermittlung der richtigen Technologie für das nächste Webprojekt findet ein Vergleich zwischen dem Google Web Toolkit und JavaServer Faces statt.
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Web applications using the Google Web Toolkitvon Wenckstern, Michael 05 June 2013 (has links)
This diploma thesis describes how to create or convert traditional Java programs to desktop-like rich internet applications with the Google Web Toolkit.
The Google Web Toolkit is an open source development environment, which translates Java code to browser and device independent HTML and JavaScript.
Most of the GWT framework parts, including the Java to JavaScript compiler as well as important security issues of websites will be introduced.
The famous Agricola board game will be implemented in the Model-View-Presenter pattern to show that complex user interfaces can be created with the Google Web Toolkit.
The Google Web Toolkit framework will be compared with the JavaServer Faces one to find out which toolkit is the right one for the next web project.:I Abstract
II Contents
III Acronyms and Glossary
III.I Acronyms
III.II Glossary
IV Credits
1 Introduction
2 Basics
2.1 Development of the World Wide Web
2.2 Hypertext Markup Language
2.3 Cascading Style Sheets
2.4 JavaScript
2.5 Hypertext Markup Language Document Object Model
2.6 Asynchronous JavaScript and XML
3 GWT toolbox and compiler
3.1 GWT in action
3.2 A short overview of the toolkit
3.3 GWT compiler and JSNI
3.3.1 Overview of GWT compiler and JSNI
3.3.2 Deferred binding and bootstrapping process
3.3.3 GWT compiler steps and optimizations
3.4 Java Runtime Environment Emulation
3.5 Widgets and Panels
3.5.1 Overview of GWT Widgets
3.5.2 Event handlers in GWT Widgets
3.5.3 Manipulating browser’s DOM with GWT DOM class
3.5.4 GWT Designer and view optimization using UiBinder
3.6 Remote Procedure Calls
3.6.1 Comparison of Remote Procedure Calls with Remote Method Invocations
3.6.2 GWT’s RPC service and serializable whitelist
3.7 History Management
3.8 Client Bundle
3.8.1 Using ImageResources in the ClientBundle interface
3.8.2 Using CssResources in the ClientBundle interface
4 Model-View-Presenter Architecture
4.1 Comparison of MVP and MVC
4.2 GWT Model-View-Presenter pattern example: Agricola board game
4.3 Extending the Agricola web application with mobile views
4.4 Introducing activities in the Agricola Model-View-Presenter pattern enabling browser history
5 Comparison of the two web frameworks: GWT and JSF
5.1 Definitions of comparison fields
5.2 Comparison in category 1: Nearly completely static sites with a little bit of dynamic content, e.g. news update
5.3 Comparison in category 2: Doing a survey in both technologies
5.4 Comparison in category 3: Creating a forum to show data
5.5 Comparison in category 4: Writing a chat application
5.6 Comparison in category 5: Writing the speed game Snake
5.7 Summary
6 Security
6.1 Download Tomcat
6.2 Dynamic Web Application Project with GWT and Tomcat
6.3 Establish HTTPS connections in Tomcat
6.3.1 Create a pem certificate
6.3.2 Convert pem certificate into a key store object
6.3.3 Configure Tomcat’s XML files to enable HTPPS
6.4 Establish a database connection in Tomcat
6.4.1 Create TomcatGWT user and schema, and add the table countries
6.4.2 Configure Tomcat’s XML files to get access to the database connection
6.4.3 PreparedStatements avoid MySQL injections
6.5 Login mechanism in Tomcat
6.6 SafeHtml
7 Presenting a complex software application written in GWT
8 Conclusions
8.1 Summary
8.2 Future work
A Appendix
A 1 Configure the Google Web Toolkit framework in Eclipse
A 1.1 Install the Java Developer Kit
A 1.2 Download Eclipse
A 1.3 Install the GWT plugin in Eclipse
A 1.4 Create first GWT Java Project
A 2 Figures
A 3 Listings
A 3.1 Source code of the Agricola board game
A 3.2 Source code of GWT and JSF comparison
A 4 Tables
R Lists and References
R 1 Lists
R 1.1 List of Tables
R 1.2 List of Figures
R 1.3 List of Listings
R 2 References
R 2.1 Books
R 2.2 Online resources / Diese Diplomarbeit beschreibt die Erzeugung desktopähnlicher Anwendungen mit dem Google Web Toolkit und die Umwandlung klassischer Java-Programme in diese.
Das Google Web Toolkit ist eine Open-Source-Entwicklungsumgebung, die Java-Code in browserunabhängiges als auch in geräteübergreifendes HTML und JavaScript übersetzt.
Vorgestellt wird der Großteil des GWT Frameworks inklusive des Java zu JavaScript-Compilers sowie wichtige Sicherheitsaspekte von Internetseiten.
Um zu zeigen, dass auch komplizierte graphische Oberflächen mit dem Google Web Toolkit erzeugt werden können, wird das bekannte Brettspiel Agricola mittels Model-View-Presenter Designmuster implementiert.
Zur Ermittlung der richtigen Technologie für das nächste Webprojekt findet ein Vergleich zwischen dem Google Web Toolkit und JavaServer Faces statt.:I Abstract
II Contents
III Acronyms and Glossary
III.I Acronyms
III.II Glossary
IV Credits
1 Introduction
2 Basics
2.1 Development of the World Wide Web
2.2 Hypertext Markup Language
2.3 Cascading Style Sheets
2.4 JavaScript
2.5 Hypertext Markup Language Document Object Model
2.6 Asynchronous JavaScript and XML
3 GWT toolbox and compiler
3.1 GWT in action
3.2 A short overview of the toolkit
3.3 GWT compiler and JSNI
3.3.1 Overview of GWT compiler and JSNI
3.3.2 Deferred binding and bootstrapping process
3.3.3 GWT compiler steps and optimizations
3.4 Java Runtime Environment Emulation
3.5 Widgets and Panels
3.5.1 Overview of GWT Widgets
3.5.2 Event handlers in GWT Widgets
3.5.3 Manipulating browser’s DOM with GWT DOM class
3.5.4 GWT Designer and view optimization using UiBinder
3.6 Remote Procedure Calls
3.6.1 Comparison of Remote Procedure Calls with Remote Method Invocations
3.6.2 GWT’s RPC service and serializable whitelist
3.7 History Management
3.8 Client Bundle
3.8.1 Using ImageResources in the ClientBundle interface
3.8.2 Using CssResources in the ClientBundle interface
4 Model-View-Presenter Architecture
4.1 Comparison of MVP and MVC
4.2 GWT Model-View-Presenter pattern example: Agricola board game
4.3 Extending the Agricola web application with mobile views
4.4 Introducing activities in the Agricola Model-View-Presenter pattern enabling browser history
5 Comparison of the two web frameworks: GWT and JSF
5.1 Definitions of comparison fields
5.2 Comparison in category 1: Nearly completely static sites with a little bit of dynamic content, e.g. news update
5.3 Comparison in category 2: Doing a survey in both technologies
5.4 Comparison in category 3: Creating a forum to show data
5.5 Comparison in category 4: Writing a chat application
5.6 Comparison in category 5: Writing the speed game Snake
5.7 Summary
6 Security
6.1 Download Tomcat
6.2 Dynamic Web Application Project with GWT and Tomcat
6.3 Establish HTTPS connections in Tomcat
6.3.1 Create a pem certificate
6.3.2 Convert pem certificate into a key store object
6.3.3 Configure Tomcat’s XML files to enable HTPPS
6.4 Establish a database connection in Tomcat
6.4.1 Create TomcatGWT user and schema, and add the table countries
6.4.2 Configure Tomcat’s XML files to get access to the database connection
6.4.3 PreparedStatements avoid MySQL injections
6.5 Login mechanism in Tomcat
6.6 SafeHtml
7 Presenting a complex software application written in GWT
8 Conclusions
8.1 Summary
8.2 Future work
A Appendix
A 1 Configure the Google Web Toolkit framework in Eclipse
A 1.1 Install the Java Developer Kit
A 1.2 Download Eclipse
A 1.3 Install the GWT plugin in Eclipse
A 1.4 Create first GWT Java Project
A 2 Figures
A 3 Listings
A 3.1 Source code of the Agricola board game
A 3.2 Source code of GWT and JSF comparison
A 4 Tables
R Lists and References
R 1 Lists
R 1.1 List of Tables
R 1.2 List of Figures
R 1.3 List of Listings
R 2 References
R 2.1 Books
R 2.2 Online resources
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