Big data is a term used to describe large amounts of data. The aim of the work has been to develop an efcient system that analyzes large quantities of data. Which in this case is the transport of wood between forest and industry. By man- aging this amount of data, the user can quickly receive information about the lo- cation of the timber and compare historical data regarding it. This report de- scribes the work of implementing a dashboard that compiles "Big data" in real time and in a comprehensible way. The project uses scrum as a project tool. This means an iterative development where you work towards smaller sub-goals. The report also includes evaluations conducted with a focus on usability and also a compilation of research within the subject of data visualization and BI. The evalu- ation indicated that by using the developed dashboard, it took a standard com- puter user an average of 3.4 seconds to fnd the requested information. Before, programming skills would be required and it would take much longer to obtain corresponding information. / Big data är ett begrepp som idag används flr att beskriva stora datamängder. Må- let med arbetet har varit att utveckla ett efektivt system som analyserar stora mängder data. I det här fallet transportfldet av virke mellan skog och industri. Genom att hantera den här mängden data får användaren snabbt fram information om vart virket befnner sig och mljlighet till att jämflra historiska data. Den här rapporten beskriver arbetet med att implementera en dashboard som i realtid sammanställer Big data på ett begripligt sätt. Projektet använder sig av scrum som projektverktyg. Det betyder ett iterativt arbete där man arbetar mot delmål. Rap- porten innehåller även utvärderingar som genomflrts med användbarhet i fokus samt en sammanställning av forskning inom området datavisualisering och BI. Utvärderingen visade att med den utvecklade dashboarden så tog det flr en nor- mal datoranvändare i snitt 3,4 sekunder att hitta den efterslka information. Tidi- gare så krävdes det programmeringskunskaper och betydligt längre tid flr att få fram motsvarade information.

<p>Diabetes is a prevalent disease nowadays, and it is a big challenge, especially for seniors. The biggest challenge for seniors with diabetes is that they need to prick their fingers to test their blood which is painful and horrible. Also, the current glucose meter does not make good use of the glucose data to help them better treat the diabetes. Also, seniors live alone and lag off behind the diabetes information & technology. Therefore, based on seniors’ characteristics, I want to employ new technologies, such as data visualization and AI technology, in the design to help them manage their diabetes more easily. </p> <p><br></p> <p>Through the literature review, I learned the disease information of diabetes, investigated the diabetes situation in the seniors’ group, and studied the seniors’ characteristics, which can make the designs more suitable for seniors. To better understand diabetic seniors’ conditions, needs and wishes, I took part in several diabetes events in Lafayette Indiana, volunteered in the retirement village and conducted a series of interviews in these two settings. By analyzing the peer products, daily self-measurement of my own sugar level and keeping diaries, I learned what do the similar products look like, got some inspiration from them and found problems in the current products. After drawing a bunch of sketches to explore the idea, HTA chart, wireframe, low-fidelity prototype and mockups were developed in the first design iteration. I came up with the smart product system, based on the seniors’ characteristics, combined with new technologies to help seniors with diabetes easily manage their diabetes. Then I conducted the usability testing with the prototype & physical models to refine my design. Finally, usability testing was conducted again to make sure my products provide a pleasant experience for seniors with diabetes. With this smart system, testing blood becomes a happy & relaxing experience and seniors can join the diabetes group to support each other. Moreover, Seniors with diabetes can get feedback and suggestions from the system. </p>

Nowadays, there has been an increasing interest in using 360degrees video in medical education. Recent efforts are starting to explore how nurse students experience and interact with 360degrees videos. However, once these interactions have been registered in a database, there is a lack of ways to analyze these data, which generates a necessity of creating a reliable method that can manage all this collected data, and visualize the valuable insights of the data. Hence, the main goal of this thesis is to address this challenge by designing an approach to analyze and visualize this kind of data. This will allow teachers in health care education, and medical specialists to understand the collected data in a meaningful way. To get the most suitable solution, several meetings with nursing teachers took place to draw the first draft structure of an application which acts as the needed approach. Then, the application was used to analyze collected data in a study made in December. Finally, the application was evaluated through a questionnaire that involved a group of medical specialists related to education. The initial outcome from those testing and evaluations indicate that the application successfully achieves the main goals of the project, and it has allowed discussing some ideas that will help in the future to improve the 360degrees video experience and evaluation in the nursing education field providing an additional tool to analyze, compare and assess students.

Email provides the average person with the ability to instantaneously communicate with people across the planet. However, the ease of this communication not only allows people to exchange information, but can also generate a large volume of messages. The methods of interacting with this repository currently in use are far from adequate. This thesis focuses on the development of a new interface for managing one's inbox and mail folders. The approach provides the user with a data visualization of an overview of the entire mailbox, or a chosen subset, at once. The tool includes interactions that allow a user to focus his or her attention on specific email and delve deeper into it in a simple intuitive fashion. A user study confirmed the usefulness of the resulting system.

Submitted by Filipe dos Santos (fsantos@pucsp.br) on 2016-09-22T18:33:26Z No. of bitstreams: 1 Marcelo Stoppa Augusto Corrêa.pdf: 12054164 bytes, checksum: 1d76d1664521ddad6653a226c9ccfe4b (MD5) / Made available in DSpace on 2016-09-22T18:33:26Z (GMT). No. of bitstreams: 1 Marcelo Stoppa Augusto Corrêa.pdf: 12054164 bytes, checksum: 1d76d1664521ddad6653a226c9ccfe4b (MD5) Previous issue date: 2016-04-15 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Pontifícia Universidade Católica de São Paulo / The modern spirit performed deep, structural transformations in society. The new and more fluid socio-political settings changed not only the way interpersonal relations happen, but also the arrangements by which individuals may attach to one another: groups, multitudes or communities have evolved to a new dimension. The socio-political changes and the growing sophistication of media render the groupings ephemeral, empowers the crowds and favors the creation of new and hybrid communicational and cultural codes through cultural identity clashes caused by faster economic exchange. The present work lays out a methodology that aims the collaboration to research relational, cultural and social phenomena in groups, to analyze crowd and community dynamics through an ensemble of techniques to crawl, analyze and visualize data and build relational and affinity topologies which we named affinimaps. This transdisciplinary methodology stands on Big Data, Open Data, analytics, ontologies and complex data visualization algorithms, as the technical axis; on the works of Jacob Levy Moreno and Timothy Leary, as the psychological and sociometric axis; and on infographics and topology, on the artistic axis. It intends to offer the representation of complex relations of different sorts of actors so as to transcend the vision and improve the detection of arrangement and behavior patterns. This way, it might contribute to the research conducted by different knowledge areas investigating the relationships between men and the world / O espírito moderno trouxe profundas transformações estruturais à sociedade. Os novos arranjos político-sociais, mais fluidos, mudaram não apenas as formas com que se dão as relações interpessoais, mas também como se formam os arranjos sociais pelos quais os indivíduos se vinculam uns aos outros: os grupos, as multidões e as comunidades não são os mesmos. As mutações sócio-políticas, com a sofisticação cada vez maior dos meios de comunicação, aumentam a efemeridade dos agrupamentos, dando às multidões o poder se auto-organizarem e as diferentes comunidades do planeta efetuam trocas econômicas com muita rapidez e que, pelo confronto de identidades culturais, tecem códigos de comunicação e cultura cada vez mais híbridos. O presente trabalho propõe a construção de uma metodologia que visa colaborar com a investigação de fenômenos relacionais, culturais e sociais nos grupos, bem como investigar a dinâmica nas multidões e nas comunidades por meio de um conjunto de técnicas de captura, análise e visualização de dados para a construção de topologias relacionais e de afinidade, que nomeamos afinimapas. Esta metodologia transdisciplinar apoia-se em Big Data, Open Data, analytics, ontologia e algoritmos de visualização de dados complexos, no eixo técnico; nas obras de Jacob Levy Moreno e Timothy Leary, no eixo psicológico e sociométrico; e na infografia e na topologia, no eixo artístico. Ela pretende fornecer a representação da complexidade das relações de diferentes tipos de atores para transcender a visão e favorecer a detecção de padrões de arranjos e comportamentos. Deste modo, deseja-se contribuir com as investigações conduzidas por diferentes áreas do saber que levem em conta as relações entre o homem e o mundo

Os rankings musicais destinam-se principalmente a fins de marketing, mas também ajudam os usuários a descobrir novas músicas, bem como a comparar artistas, álbuns, etc. Este trabalho apresenta uma ferramenta interativa para visualizar, encontrar e comparar rankings musicais usando diferentes técnicas além de exibir atributos das músicas. A técnica foi concebida após uma pesquisa remota que coletou dados sobre como as pessoas escolhem música. As técnicas de visualização tornam mais fácil obter informações sobre artistas e faixas, e também comparar os dados obtidos a partir dos dois principais rankings de música, Billboard e Spotify. A ferrament também permite a interação com dados pessoais. Resultados de experimentos conduzidos com usuários potenciais mostraram que a ferramenta foi considerada interessante, com um layout atrativo. Comparando com as formas tradicionais de visualizar rankings de músicas, usuários preferiram a ferramenta aqui desenvolvida, mas a diferença para Billboard e Spotify não foi grande. Entretanto, quando avaliada a usabilidade da ferramenta, os resultados foram melhores, principalmente no que se refere à filtragem e às técnicas de comparação. MusicVis foi também considerado fácil de aprender. / Music rankings are mainly aimed at marketing purposes but also help users in discovering new music as well as comparing songs, artists, albums, etc. This work presents an interactive way to visualize, find and compare music rankings using different techniques, including the display of music attributes. The technique was conceived after a remote survey we conducted to collect data about how people choose music. Our visualization makes easier to obtain information about artists and tracks, and also to compare the data gathered from the two major music rankings, namely Billboard and Spotify. The tool also provides interaction with personal data. The results obtained from experiments with potential users showed that the tool was considered interesting, with an attractive layout. Compared to traditional music ranking tools users preferred ours, but with not such a large difference from using Billboard or Spotify. However, when evaluating the usability of our tool, results are positive, mainly concerning to data filtering and comparison features. MusicVis was also considered easy to learn.

As pessoas estão ficando cada vez mais interessadas no uso de monitores de atividade. A quantidade de dados de indivíduos disponível está ajudando na expansão e desenvolvimento de novas aplicações e projetos de visualizações para ser usados em casa, em ciência (e.g. para entender melhor o comportamento de populações) ou em governos interessados em desenvolver cidades inteligentes. Nesse trabalho é apresentada uma visualização simples e intuitiva que permite a exploração de dados pessoais por pessoas comuns. Com foco em ajudar as pessoas a compreenderem a si mesmas melhor e perceber coisas novas sobre seus dados. A visualização construída neste projeto é baseada em metáforas de calendários, relógios e mapas, além de utilizar gráficos de barra para explorar dados crus. A exploração desses dados se dá pela interação entre essas visualizações. Para avaliar o produto do trabalho são apresentados dois casos de uso onde alguns usuários tiveram a oportunidade de observar e discutir suas informações de dois pontos de vista diferente: exploração de dados pessoais para auto-aperfeiçoamento e o uso do Everyday Visualization por cientistas da saúde. Em nenhum dos casos houve treinamento. As visualizações resultantes agregam diversas fontes de dados, indo além de outros trabalhos de visualização casual e pessoal. Os resultados promissores demonstram a viabilidade de tais técnicas para visualização de dados pessoais. / People are becoming increasingly more interested in the use of activity monitors and selfimprovement. The availability of individuals’ data is also pushing the development of new applications and data visualization projects to be used at home, in science (e.g. to better understand the behavior of populations) or for governments interested in developing intelligent cities. In this work, we present an easy and intuitive set of visualizations to allow the exploration of personal data by common people. We focus on helping people to know themselves better and to make sense of their own data. Our visualizations are based on the metaphors of calendars, clocks, and maps, as well as on the use of bar charts to explore raw data. Data exploration is therefore guaranteed by the interaction between them. In order to evaluate our work we present two use cases, where few users observe and discuss the data from different points of view: the exploration of personal data for self-improvement purposes, and the use of Everyday Visualization by health scientists. Both use cases were ran without any training session. The resulting visualization aggregates several different data sources, going beyond many of the personal and casual visualization works. The promising results achieved demonstrated the viability of the use of such techniques for personal data visualizations and sense making.

The overall goal of this dissertation is to elucidate the cellular and circuit mechanisms underlying flexible behavior in the prefrontal cortex. We are often faced with situations in which the appropriate behavior in one context is inappropriate in others. If these situations are familiar, we can perform the appropriate behavior without relearning how the context relates to the behavior — an important hallmark of intelligence. Neuroimaging and lesion studies have shown that this dynamic, flexible process of remapping context to behavior (task switching) is dependent on prefrontal cortex, but the precise contributions and interactions of prefrontal subdivisions are still unknown. This dissertation investigates two prefrontal areas that are thought to be involved in distinct, but complementary executive roles in task switching — the dorsolateral prefrontal cortex (dlPFC) and the anterior cingulate cortex (ACC). Using electrophysiological recordings from macaque monkeys, I show that synchronous network oscillations in the dlPFC provide a mechanism to flexibly coordinate context representations (rules) between groups of neurons during task switching. Then, I show that, wheras the ACC neurons can represent rules at the cellular level, they do not play a significant role in switching between contexts — rather they seem to be more related to errors and motivational drive. Finally, I develop a set of web-enabled interactive visualization tools designed to provide a multi-dimensional integrated view of electrophysiological datasets. Taken together, these results contribute to our understanding of task switching by investigating new mechanisms for coordination of neurons in prefrontal cortex, clarifying the roles of prefrontal subdivisions during task switching, and providing visualization tools that enhance exploration and understanding of large, complex and multi-scale electrophysiological data.

This body of work explores multiple technical and aesthetic methods of representing complex statistical information in an approachable visual language, bridging the boundaries between data science, graphic design and fine arts. Ordinary data charts are combined together with other charts and diagrams and transformed in unexpected ways in order to form the basic structure of mythical landscape scenes. Line plots over time become the rising and falling curves of hills and mountains, bar charts are morphed into industrial factories on the horizon, and bubble charts become billowing smoke, a forest of trees, or a school of fish. The hope is that the work will act as an engaging alternative to traditional data representation and will encourage curiosity and a fresh perspective.

This dissertation explores Random Neural Networks (RNNs) in several aspects and their applications. First, Novel RNNs have been proposed for dimensionality reduction and visualization. Based on Extreme Learning Machines (ELMs) and Self-Organizing Maps (SOMs) a new method is created to identify the important variables and visualize the data. This technique reduces the curse of dimensionality and improves furthermore the interpretability of the visualization and is tested on real nursing survey datasets. ELM-SOM+ is an autoencoder created to preserves the intrinsic quality of SOM and also brings continuity to the projection using two ELMs. This new methodology shows considerable improvement over SOM on real datasets. Second, as a Supervised Learning method, ELMs has been applied to the hierarchical multiscale method to bridge the the molecular dynamics to continua. The method is tested on simulation data and proven to be efficient for passing the information from one scale to another. Lastly, the regularization of ELMs has been studied and a new regularization algorithm for ELMs is created using a modified Lanczos Algorithm. The Lanczos ELM on average divide computational time by 20 and reduce the Normalized MSE by 14% comparing with regular ELMs.