Master of Science / Department of Computing and Information Sciences / Doina Caragea / Social media affects our daily lives. It is one of the first sources for finding breaking news. In particular, Twitter is one of the popular social media platforms, with around 330 million monthly users. From local events such as Fake Patty's Day to across the world happenings - Twitter gets there first. During a disaster, tweets can be used to post warnings, status of available medical and food supply, emergency personnel, and updates. Users were practically tweeting about the Hurricane Sandy, despite lack of network during the storm. Analysis of these tweets can help monitor the disaster, plan and manage the crisis, and aid in research. In this research, we use the publicly available tweets posted during several disasters and identify the relevant tweets. As the languages in the datasets are different, Bing translation API has been used to detect and translate the tweets. The translations are then, used as training datasets for supervised machine learning algorithms. Supervised learning is the process of learning from a labeled training dataset. This learned classifier can then be used to predict the correct output for any valid input. When trained to more observations, the algorithm improves its predictive performance.

The theme of this work is the conversion of Word 2007 document to the HTML format. The work contains the analysis of existing convertors and description of their disadvantages and errors. The format of the OOXML document, especially WordprocessingML document, is described in detail. API used for work with OOXML documents is described too. The main contribution of this work is development of a new convertor of WordprocessingML documents to HTML format. This converor enables to divide the output to more parts. User can choose type of dividing: by sections or by style(s) of paragraph. The convertor is described in the last chapter.

This diploma thesis describes new HTML5 standard. The aim is to show the potential uses and benefits of HTML5 compared to HTML4. Another objective is to analyze the support of HTML5 in most advanced web browsers on desktops and mobile devices. The thesis is divided into theoretical and practical parts. The theoretical part is divided into 5 chapters. The first chapter describes the introduction to the main concepts and definitions. The second chapter describes the differences between HTML4 and HTML5 elements. The third chapter describes HTML5 API. The fourth chapter analyzes the support of HTML5 featu- res in web browsers. Last chapter of the theoretical part discusses tools based on best practices which are useful for developing HTML5 applications. In the practical part, there are implemented real examples of HTML5 features. Practical examples are described as a tutorial. The contribution of this work is a demonstration of the advantages of HTML5 over the old standard. Contribution is also analysis of support of HTML5 features in web browsers. The diploma thesis is intended primarily for web developers and can be used as a reference guide. HTML5 is the standard of the future, and web developers can contribute to the overall improvement of the web by using it.

This Thesis is focused on the ways of getting information from the World Wide Web source . The Introduction pays attention to the theoretical approach towards data collection options . The main part of the Introduction is engaged in the Web Crawler program as the possibility of data collection from internet and consequently they are followed by alternative methods of data collection. E.g. Google Search API. The next part of the Thesis is dedicated to SAS products and their meanings in the context of reporting and internet monitoring. SAS Intelligence platform is presented as the crucial Company platform In the framework of the platform there could be found concrete SAS solutions. SAS Web Crawler and Semantic Server are described in SAS Content Categorization solution. Whilst the first two parts of Thesis are focused on the theory , the third and closing part pays attention to practical examples. There are illustrated examples of Internet Data collection, which are mainly realized in SAS. The practical part of Thesis follows the theoretical one and it cannot be detached.

Este trabalho mostra o desenvolvimento de uma Interface de Programação de Aplicativos (Application Program Interface - API) para um gerenciador de dados orientado a objetos. A API é composta por um conjunto de primitivas que integram a definição e a manipulação de objetos em uma representação compatível com uma linguagem de programação orientada a objetos. A definição da API explora os recursos básicos de modelos de dados orientados a objetos e baseia-se nas extensões de um metamodelo baseado em quatro abstrações: classificação, generalização, agregação e composição. O suporte à abstração de classificação com hierarquias em múltiplos níveis é tratado com especial destaque, pois resulta em uma das características predominantes da API: o tratamento homogêneo de tipos e instâncias em tempo de execução, unificando comandos usualmente separados em DDL (Data Definition Language) e DML (Data Manipulation Language). A implementação da API sobre um gerenciador relacional emula um gerenciador de dados orientado a objetos. Os conceitos envolvidos no trabalho de emulação foram aplicados no desenvolvimento de uma versão com núcleo relacional do Gerenciador de Objetos SIRIUS, criando em ambiente experimental, precursor à versão com núcleo nativo desse gerenciador. A API definida neste trabalho é compatível com ambas as versões do Gerenciador SIRIUS, permitindo que uma aplicação utilize qualquer uma das versões sem alterações em seu código fonte. Para exemplificar a utilização prática da API, foi implementado um utilitário de bases de dados destinado à representação de modelagens baseadas no modelo de dados SIRIUS usando a versão relacional do Gerenciador de Objetos SIRIUS. Esse utilitário, além de demonstrar a utilização da API, demonstra também como as operações típicas da DDL e da DML são integradas em um único conjunto de comandos que não faz diferença entre a definição de tipos e de instâncias.

Advanced computer technologies can transform the traditional electrocardiogram (ECG) monitoring system for better efficiency and accuracy. ECG records a heart's electrical activity using electrodes placed on the skin, and it has become an essential tool for arrhythmia detection. The complexity comes from the variety of patients' heartbeats and massive amounts of information for humans to process correctly. The first part of the thesis presents an image based two-dimensional convolution neural network (CNN) to classify the arrhythmia heartbeats with inter-patient paradigm. It includes a new data pre-processing method. The inter-patient paradigm simulates the practical use case of an ECG heartbeat classifier. Compared to the reported work in the literature, the proposed solution achieves superior experiment results. The rest of the thesis introduces the remote ECG monitoring system. The RESTful API design concepts of the system are described. The proposed API supports an efficient and secure way of interaction between each module in this remote monitoring system. / Graduate

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Within Mater’s Thesis a design of the communication module for X-Plane simulator was worked out. It will enable to read data from simulation model or change current flight situation.

The diploma thesis deals with the analysis of the company and the focus on data security. Based on the company analysis and requirements is designed a new system of employee authorization in CMS systems of the company. The design of the employee authorization API solution is based on the OAuth 2.0 protocol.

Tor is a distributed network providing privacy and anonymity on the Internet. Information about Tor is publicly available in a form of consensus documents. Existing tools that are able to display this information do not provide both historical and detailed view of it. A tool named Consensus Parser that provides a detailed, historical view of this information and extends it with geolocation and DNS information, was created as a part of TARZAN research project at Brno University of Technology. It stores the information in regular files on disk and makes it accessible via REST API. This thesis extends Consensus Parser with MariaDB ColumnStore database with a schema designed to conform to OLAP needs. The searching capabilities of Consensus Parser were enhanced by adding 109 new endpoints to 12 existing ones and adding the ability to limit the retrieved information to certain fields only. Disk space needed for storing the information was reduced by a factor of five.