<p>The total population of GPS-enabled location-based services (LBS) subscribers is constantly increasing. This fact implies new research possibilities for visualizing geospatial data produced by these mobile devices. The aim of this thesis is to explore novel techniques and methods to visualize the content of voice notes (messages recorded by users on GPS-enabled devices) that will be placed in maps using GPS coordinates, and visualize the semantical, temporal, and spatial relations between the notes. Our research is part of the Geovisualization field which deals with geospatial data.</p><p>Based on our research and analyzes of this problem, we combined different visualization and interaction techniques, thus providing a novel approach to achieve the research aim. We have built a prototype application, called GNV System (GeoAudio Notes Visualization System), that demonstrates our achievements.</p>

The total population of GPS-enabled location-based services (LBS) subscribers is constantly increasing. This fact implies new research possibilities for visualizing geospatial data produced by these mobile devices. The aim of this thesis is to explore novel techniques and methods to visualize the content of voice notes (messages recorded by users on GPS-enabled devices) that will be placed in maps using GPS coordinates, and visualize the semantical, temporal, and spatial relations between the notes. Our research is part of the Geovisualization field which deals with geospatial data. Based on our research and analyzes of this problem, we combined different visualization and interaction techniques, thus providing a novel approach to achieve the research aim. We have built a prototype application, called GNV System (GeoAudio Notes Visualization System), that demonstrates our achievements.

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Master of Science / Department of Computing and Information Sciences / Xinming Ou / Attack graphs present a visual representation of all the potential vulnerabilities and attack paths in a network. They act as a vital security tool in finding the critical attack paths in the enterprise wide networks. Generated attack graphs for complex networks present thousands of attack paths to visualize and represent to the end user. Enhancing the visualization of attack graphs by adding user interactivity will greatly improve in analyzing attack graphs and identifying the critical attack paths in the enterprise network. The layout of the attack graph can be adjusted to represent the layout of the real world enterprise network. Adding user interactivity to attack graphs is done using Prefuse, a software framework written in Java for information visualization. Prefuse is flexible and got the ability to render large amounts of data in an efficient manner. The visualization framework for the attack graphs provides a GUI tool for interacting with attack graph. The framework is a layered architecture with two important layers, the static layer and the dynamic layer. The static layer translates the attack graph trace generated from MuLVAL into a standard graphviz dot language descriptive file. The dynamic layer translates the graphviz dot file into a graph object that can be interpreted and visualized using the prefuse software framework. Preliminary result in this work has been published in [19].

Particle Image Velocimetry (PIV) is an optical technique used to display and evaluate the motion of fine particles in a flow. In this experimental study, velocity profiles are examined by PIV system and basic analysis methods are compared.

Orientador: Ricardo da Silva Torres / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-17T03:09:27Z (GMT). No. of bitstreams: 1 Caceres_SheilaMaricelaPinto_M.pdf: 5019224 bytes, checksum: cf87ae15c741c8322d4d398124abee74 (MD5) Previous issue date: 2010 / Resumo: Um sistema de Recuperação de Imagens por Conteúdo (CBIR) oferece mecanismos necessários para busca e recuperação de imagens baseando-se em propriedades visuais como cor, textura, forma, etc. Em um processo de busca de imagens, a apresentação de resultados é um componente essencial, na medida em que a obtenção desses resultados é o motivo da existência do sistema. Consequentemente, o uso de técnicas de visualização apropriadas pode determinar o sucesso ou o fracasso de um sistema CBIR. Técnicas de visualização são valiosas ferramentas na exploração de grandes quantidades de dados, como coleções de imagens. Contudo, técnicas para visualizar imagens retornadas por sistemas CBIR têm sido pobremente exploradas. Este trabalho apresenta um estudo comparativo e avaliação de várias técnicas de visualização para sistemas CBIR. Como resultado desse estudo, propõe-se um conjunto de técnicas originais que tentam suprir algumas das limitações identificadas em métodos da literatura. Dentre as características das técnicas propostas, destacam-se o enfoque baseado no centro e o uso de técnicas de agrupamento de dados para representar a similaridade intrínseca entre as imagens retornadas. Resultados experimentais mostram que os métodos propostos superam outras estratégias de visualização, considerando-se diversos critérios, como adequação para mostrar resultados em sistemas CBIR, quantidade de informação oferecida, satisfação de usuário, etc. As principais contribuições deste trabalho são: (i) estudo comparativo e análise de sete técnicas de visualização, quatro delas existentes na literatura e três técnicas novas propostas; (ii) avaliação de duas técnicas da literatura nunca antes avaliadas: anéis concêntricos e espiral; (iii) especificação e implementação de três novas técnicas de visualização baseadas em agrupamento; (iv) especificação e implementação de um framework para desenvolvimento de novas estruturas visuais para sistemas CBIR no qual foram implementadas as técnicas de visualização estudadas / Abstract: A Content-Based Image Retrieval (CBIR) system offers mechanisms needed to search and retrieve images based on visual properties such as color, texture, shape, etc. In an image search process, the presentation of results is an essential component as the retrieval of relevant images is the reason of the system existence. Consequently, the use of appropriate visualization techniques may determine the success of a CBIR system. Visualization techniques are valuable tools for the exploration of a great quantity of data, such as images collections. However, techniques for visualizing images in CBIR systems have been poorly explored. This work presents a comparative study of several visualization techniques for CBIR systems. As a result of this study, several original techniques were proposed trying to fulfill some of the absent characteristics in existing methods, such as the central-based focus and the use of clustering approaches to represent the intrinsic similarity between retrieved images. Experimental results show that the proposed methods overcome other visualization strategies by considering several criteria such as adaptation to show CBIR results, information load, user satisfaction, etc. The main contributions of this work are: (i) comparative study and analysis of seven visualization techniques, four of them from the literature and three new ones; (ii) validation of two techniques never evaluated before: concentric rings and spiral; (iii) specification and implementation of three new techniques of visualization based on clustering; (iv) specification and implementation of a framework for developing new visual structures for content-based image retrieval systems. The studied techniques were implemented by using this framework / Mestrado / Ciência da Computação / Mestre em Ciência da Computação

Flow visualization has been a very active subfield of scientific visualization in recent years. From the resulting large variety of methods this paper discusses partition-based techniques. The aim of these approaches is to partition the flow in areas of common structure. Based on this partitioning, subsequent visualization techniques can be applied. A classification is suggested and advantages/disadvantages of the different techniques are discussed as well.

Alla människor uppfattar och registrerar data. Hur data visualiseras kommer påverka hur enkelt vi människor förstår informationen. Detta projekt undersöker hur ett system ska utvecklas för att en datavisualisering av betalingnstider enkelt ska presenteras på en webbsida. Olika idéer och designer av webbsidan framställdes och analyserades. Fokuset är på hur data ska visas i olika diagram och tabeller. En utvecklingsmiljö formades med en databas och slumpgenererad data för att testa systemet för applikationen. Resultatet blev en färdig webbapplikation som hämtar data från en databas med SQL-frågor. Därefter mellanlagras den användbara data i JSON-filer och sedan visualiseras statistiken på en webbapplikation med hjälp av JavaScript biblioteket Chart.js. Webbsidan utvärderades med användbarhetstester som visade på att det fanns otydligheter i topp- och bottenlistor samt en sökfunktion. Användbarhetstesterna visade även att webbsidan var mycket strukturerad och att det var enkelt att hitta och extrahera information. / All individuals perceive and register data. How data is visualized will affect how easily we humans understand the information. This project investigates how a system should be developed to present a data visualization of payment deadlines easily on a website. Various ideas and designs for the webpage were created and analyzed. The focus is on how data should be displayed in different charts and tables. A development environment was set up with a database and randomly generated data to test the system for the application. The result was a completed web application that retrieves data from a database using SQL queries. The useful data is then cached in JSON-files and the statistics are visualized on a website using the JavaScript library Chart.js. The usability of the website was evaluated through usability testing, which revealed ambiguities in the top and bottom lists as well as a search function. The usability tests also showed that the website was highly structured and it was easy to find and extract information.

Performance regression testing is a difficult task with several intricacies and complexities. In the absence of analysis tools, manual analysis must be conducted which is undoubtedly infeasible. Thereby, in this thesis, an automated performance analysis framework is proposed, aiming to mitigate the faced issues. To make this possible, the adequacy of the data needed to be established. Additionally, a fault detection algorithm had to be developed. From investigating the current state-of-the-art of performance anomaly detection, evidently, statistical models have been utilised far more than classical machine learning, and deep learning. Consequently, based on this knowledge and based on the types of anomalies present in the data, a cumulative sum based statistical method is proposed. The findings demonstrate that the data is adequate for detecting faults, and verifying their validity, as they are consistently observable in several test configurations. However, tests are not performed frequently enough which consequently leads to challenges in identifying the exact locations of faults. The algorithm was evaluated on artificial data with injected faults and could detect over 90 % of anomalies if they were prominent enough. Longer sequences before fault deviations occur, improved the ability of detecting the faults. Thus, further motivating the need to collect data more frequently. On a final note, the automated performance analysis framework successfully improved the efficiency of fault detection, and greater contextual data awareness were achieved through the visualization features. Manual analysis can however detect faults with greater accuracy. On that ground, these results should be interpreted with caution.

Técnicas de visualização de informações multidimensionais têm o potencial de auxiliar na análise visual e exploração de grandes conjuntos de dados, através do emprego de mecanismos que buscam tanto representar visualmente os dados quanto permitir ao usuário a interação com estas representações. Neste contexto, diversas técnicas têm sido desenvolvidas, muitas delas sem uma avaliação detalhada e aprofundada tanto de eficiência como de utilidade no suporte às necessidades dos usuários. Contudo, há relativamente pouco tempo começaram a ser publicados trabalhos abordando as diversas questões relacionadas à avaliação de usabilidade de sistemas ou das aplicações que implementam estas técnicas como forma de promover sua eficiente e efetiva utilização. A avaliação de usabilidade de interfaces de sistemas de visualização representa um desafio de pesquisa uma vez que elas apresentam significativas diferenças com relação a outros tipos de interface. Neste sentido, existe uma carência de sistematização (incluindo o uso de métodos e técnicas de avaliação de usabilidade) que explore e considere as características deste tipo de interface de maneira adequada. Esta tese investiga soluções viáveis para o desenvolvimento de uma abordagem sistemática para avaliação de usabilidade de técnicas de visualização de informações multidimensionais e apresenta as seguintes soluções ao problema em estudo: 1) determinação de uma taxonomia de tarefas específica relacionada ao uso de visualizações multidimensionais no processo de análise de dados e 2) adaptação de técnicas e métodos de avaliação de usabilidade, com o objetivo de torná-los mais efetivos ao contexto de sistemas de visualização de informações multidimensionais. / Multidimensional visualization techniques have the potential of supporting the visual analysis and exploration of large datasets, by means of providing visual representations and interaction techniques which allow users to interact with the data through their graphical representation. In this context, several techniques have been developed, most of them being reported without a broad and deep evaluation both regarding their efficiency and utility in supporting users tasks. Few years ago, thus quite recently, several works have been published reporting many issues related to the evaluation of visualization systems and applications, as a means of promoting their efficiency and effective use. In spite of these works, the usability evaluation of visualization systems’ graphical interfaces remains a challenge because of the significant differences between these interfaces and those of other systems. This way, there is a need of finding a systematic approach for such evaluations, including the definition of which usability methods and techniques are best suited for this kind of interfaces. This thesis reports our investigation of viable solutions for the development of a systematic approach for the usability evaluation of multidimensional information visualizations. We have conducted several case studies and experiments with users and have achieved the following contributions: 1) a taxonomy of visualization tasks, that is related to the use of interactive visualization techniques for the exploration and analysis of multidimensional datasets and 2) adaptation of usability evaluation techniques with the goal of making them more effective in the context of multidimensional information visualizations.