Integrating interaction resources in the graphics clusters

This paper aims to describe the basic concepts and necessary for Java programs can invoke libraries of programming language C/C ++, through the JNA API. We used a library developed in C/C ++ called Glass [8], which offers a solution for viewing 3D graphics, using graphics clusters, reducing the cost of viewing. The purpose of the work is to interact with the humanoid developed using Java, which makes movements of LIBRAS language for the deaf, as Glass's, so that through this they can view the information using stereoscopic multi-view in full size. ©2010 IEEE.

3D semantic models for dental education

This paper explores the benefits of using immersive and interactive virtual reality environments to teach Dentistry. We present a tool for educators to manipulate and edit virtual models. One of the main contributions is that multimedia information can be semantically associated with parts of the model, through an ontology, enriching the experience; for example, videos can be linked to each tooth demonstrating how to extract them. The use of semantic information gives a greater flexibility to the models, since filters can be applied to create temporary models that show subsets of the original data in a human friendly way. We also explain how the software was written to run in arbitrary multi-projection environments. © 2011 Springer-Verlag.

Information Visualization to support decision making in the context of distance learning: A study with VLE TelEduc

Digital data sets constitute rich sources of information, which can be extracted and evaluated applying computational tools, for example, those ones for Information Visualization. Web-based applications, such as social network environments, forums and virtual environments for Distance Learning, are good examples for such sources. The great amount of data has direct impact on processing and analysis tasks. This paper presents the computational tool Mapper, defined and implemented to use visual representations - maps, graphics and diagrams - for supporting the decision making process by analyzing data stored in Virtual Learning Environment TelEduc-Unesp. © 2012 IEEE.

Particle competition and cooperation to prevent error propagation from mislabeled data in semi-supervised learning

Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate wrong labels to a large portion or even the entire data set. This paper aims to address this problem by presenting a graph-based (network-based) semi-supervised learning method, specifically designed to handle data sets with mislabeled samples. The method uses teams of walking particles, with competitive and cooperative behavior, for label propagation in the network constructed from the input data set. The proposed model is nature-inspired and it incorporates some features to make it robust to a considerable amount of mislabeled data items. Computer simulations show the performance of the method in the presence of different percentage of mislabeled data, in networks of different sizes and average node degree. Importantly, these simulations reveals the existence of the critical points of the mislabeled subset size, below which the network is free of wrong label contamination, but above which the mislabeled samples start to propagate their labels to the rest of the network. Moreover, numerical comparisons have been made among the proposed method and other representative graph-based semi-supervised learning methods using both artificial and real-world data sets. Interestingly, the proposed method has increasing better performance than the others as the percentage of mislabeled samples is getting larger. © 2012 IEEE.

Equity in the public budget

Includes bibliography

Fuzzy community structure detection by particle competition and cooperation

Identification and classification of overlapping nodes in networks are important topics in data mining. In this paper, a network-based (graph-based) semi-supervised learning method is proposed. It is based on competition and cooperation among walking particles in a network to uncover overlapping nodes by generating continuous-valued outputs (soft labels), corresponding to the levels of membership from the nodes to each of the communities. Moreover, the proposed method can be applied to detect overlapping data items in a data set of general form, such as a vector-based data set, once it is transformed to a network. Usually, label propagation involves risks of error amplification. In order to avoid this problem, the proposed method offers a mechanism to identify outliers among the labeled data items, and consequently prevents error propagation from such outliers. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method. © 2012 Springer-Verlag.

AR | RA: a arte na realidade aumentada

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A utilização de linguagem VRML na educação à distância em arte

Pós-graduação em Artes - IA

Reconstrução e geração de malhas em estruturas biomecânicas tridimensionais para análise por elemento finitos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Design de produtos virtuais e transdisciplinaridade: cibercepção e construção de objetos em Second Life : um estudo acerca do design de relações

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Avaliação da mobilidade, força, fadiga muscular e medo de quedas em idosas não caidoras e caidoras submetidas a um programa de exercício de fortalecimento muscular e equilíbrio

Pós-graduação em Desenvolvimento Humano e Tecnologias - IBRC

Modelagem de objetos tridimensionais para um ambiente interativo de instruções técnicas virtuais

Esta dissertação aborda metodologias de criação de objetos tridimensionais destinados a ambientes virtuais interativos, contextualizando as principais técnicas de implementação computacional envolvidas no processo. Foi utilizado como estudo de caso o Sistema de Instruções Técnicas Virtuais, desenvolvido pelo Laboratório de Realidade Virtual (LaRV) da Universidade Federal do Pará (UFPA) para as Centrais Elétricas do Norte do Brasil S/A (Eletronorte), como recurso de treinamento e simulação de procedimentos de manutenção e operação da Usina Hidrelétrica de Tucuruí.

Detecção de potenciais corticais antecipatórios em sinais de eletroencefalografia (EEG) durante a condução de carros

O reconhecimento da intenção do condutor a partir de sinais de eletroencefalografia (EEG) pode ser útil no desenvolvimento de interfaces cérebro computador (BCI) para serem usadas em sinergia com veículos inteligentes. Isso pode ser benéfico para melhorar a qualidade de interação entre o motorista e o carro, por exemplo, fornecendo uma resposta do carro inteligente alinhada com a intenção do motorista. Neste estudo, considera-se a antecipação como sendo o estado cognitivo que leva a ações especificas durante a condução de um automóvel. Portanto, propomos investigar a presença de padrões antecipatórios em sinais EEG durante a condução de veículos para determinar duas ações especifícas (1) virar à esquerda e (2) virar à direita, alguns milissegundos antes que tais ações aconteçam. Um protocolo experimental foi proposto para gravar sinais EEG de 5 indivíduos enquanto eles operam um simulador de realidade virtual não invasiva - que foi projetado para tal experimento - que simula a condução de um carro virtual. O protocolo experimental é uma variante do paradigma da variação negativa contingente (CNV) com condições Go e No-go no sistema de condução de realidade virtual. Os resultados apresentados neste estudo indicam a presença de padrões antecipatórios em potenciais corticais lentos observados no domínio do tempo (medias dos sinais EEG) e da frequência (Power Spectra e coerência de fase). Isso abre um leque de possibilidades no desenvolvimento de sistemas BCI - baseados em sinais antecipatórios - que conectem o motorista ao veiculo inteligente favorecendo uma tomada de decisão que analise as intenções dos condutores podendo eventualmente evitar acidentes durante a condução.

Effects of strength and balance training on the mobility, fear of falling and grip strength of elderly female fallers

The aim of this study was to evaluate the effects of virtual reality and strength training on the balance, fear of falling and handgrip strength of older women with a history of falls. The fear of falling, mobility and grip strength were evaluated in 11 elderly fallers (72.4 ± 5.2 years). The faller group was submitted to 12 weeks of virtual reality and muscle strength training. The results showed improvement in mobility (p = 0.0004) and in the fear of falling (p = 0.002). No significant difference was observed for hand grip strength. It can be concluded that virtual reality and muscle strength interventions are beneficial for mobility and fear of falling in older women with a history of falls.

Desenvolvimento de aplicações Web com base em modelagem 3D: módulo portal Web

This paper presents the development of a Web application called CityFreedom based on 3D modeling. The developed system demonstrates the use of most revolutionary and innovative techniques to create Web portals with the integrated 3D navigation scenarios to their own pages, without requiring any kind of plug-ins or external software. Everything works on the basis of compatible browsers. The CtyFreedom aims to give the user the feeling of immersion in virtual reality so get to interact with a three-dimensional city in order to see new places, traveling in an area of town that has always thought of knowing or even analyze establishments long before attend-them. It's the freedom to know and traveling around the city in a simple and trivial way. It is a new trend, the future of Web systems development