993 resultados para Interface Modelling


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Esta dissertação apresenta o desenvolvimento de uma plataforma multimodal de aquisição e processamento de sinais. O projeto proposto insere-se no contexto do desenvolvimento de interfaces multimodais para aplicação em dispositivos robóticos cujo propósito é a reabilitação motora adaptando o controle destes dispositivos de acordo com a intenção do usuário. A interface desenvolvida adquire, sincroniza e processa sinais eletroencefalográficos (EEG), eletromiográficos (EMG) e sinais provenientes de sensores inerciais (IMUs). A aquisição dos dados é feita em experimentos realizados com sujeitos saudáveis que executam tarefas motoras de membros inferiores. O objetivo é analisar a intenção de movimento, a ativação muscular e o início efetivo dos movimentos realizados, respectivamente, através dos sinais de EEG, EMG e IMUs. Para este fim, uma análise offline foi realizada. Nessa análise, são utilizadas técnicas de processamento dos sinais biológicos e técnicas para processar sinais provenientes de sensores inerciais. A partir destes, os ângulos da articulação do joelho também são aferidos ao longo dos movimentos. Um protocolo experimental de testes foi proposto para as tarefas realizadas. Os resultados demonstraram que o sistema proposto foi capaz de adquirir, sincronizar, processar e classificar os sinais combinadamente. Análises acerca da acurácia dos classificadores utilizados mostraram que a interface foi capaz de identificar intenção de movimento em 76, 0 ± 18, 2% dos movimentos. A maior média de tempo de antecipação ao movimento foi obtida através da análise do sinal de EEG e foi de 716, 0±546, 1 milisegundos. A partir da análise apenas do sinal de EMG, este valor foi de 88, 34 ± 67, 28 milisegundos. Os resultados das etapas de processamento dos sinais biológicos, a medição dos ângulos da articulação, bem como os valores de acurácia e tempo de antecipação ao movimento se mostraram em conformidade com a literatura atual relacionada.

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Molecular dynamics simulations were employed to analyze the mechanical properties of polymer-based nanocomposites with varying nanofiber network parameters. The study was focused on nanofiber aspect ratio, concentration and initial orientation. The reinforcing phase affects the behavior of the polymeric nanocomposite. Simulations have shown that the fiber concentration has a significant effect on the properties, with higher loadings resulting in higher stress levels and higher stiffness, matching the general behavior from experimental knowledge in this field. The results also indicate that, within the studied range, the observed effect of the aspect ratio and initial orientation is smaller than that of the concentration, and that these two parameters are interrelated.

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Laparoscopy is a surgical procedure on which operations in the abdomen are performed through small incisions using several specialized instruments. The laparoscopic surgery success greatly depends on surgeon skills and training. To achieve these technical high-standards, different apprenticeship methods have been developed, many based on in vivo training, an approach that involves high costs and complex setup procedures. This paper explores Virtual Reality (VR) simulation as an alternative for novice surgeons training. Even though several simulators are available on the market claiming successful training experiences, their use is extremely limited due to the economic costs involved. In this work, we present a low-cost laparoscopy simulator able to monitor and assist the trainee’s surgical movements. The developed prototype consists of a set of inexpensive sensors, namely an accelerometer, a gyroscope, a magnetometer and a flex sensor, attached to specific laparoscopic instruments. Our approach allows repeated assisted training of an exercise, without time constraints or additional costs, since no human artificial model is needed. A case study of our simulator applied to instrument manipulation practice (hand-eye coordination) is also presented.

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Recent progresses in the software development world has assisted a change in hardware from heavy mainframes and desktop machines to unimaginable small devices leading to the prophetic "third computing paradigm", Ubiquitous Computing. Still, this novel unnoticeable devices lack in various capabilities, like computing power, storage capacity and human interface. Connectivity associated to this devices is also considered an handicap which comes generally associated expensive and limited protocols like GSM and UMTS. Considering this scenario as background, this paper presents a minimal communication protocol introducing better interfaces for limited devices. Special attention has been paid to the limitations of connectivity, storage capacity and scalability of the developed software applications. Illustrating this new protocol, a case-study is presented addressing car sensors communicating with a central

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GUIsurfer: A Reverse Engineering Framework for User Interface Software

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In the context of an e ort to develop methodologies to support the evaluation of interactive system, this paper investigates an approach to detect graphical user interface bad smells. Our approach consists in detecting user interface bad smells through model-based reverse engineering from source code. Models are used to de ne which widgets are present in the interface, when can particular graphical user interface (GUI) events occur, under which conditions, which system actions are executed, and which GUI state is generated next.

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Pectus excavatum is the most common deformity of the thorax and usually comprises Computed Tomography (CT) examination for pre-operative diagnosis. Aiming at the elimination of the high amounts of CT radiation exposure, this work presents a new methodology for the replacement of CT by a laser scanner (radiation-free) in the treatment of pectus excavatum using personally modeled prosthesis. The complete elimination of CT involves the determination of ribs external outline, at the maximum sternum depression point for prosthesis placement, based on chest wall skin surface information, acquired by a laser scanner. The developed solution resorts to artificial neural networks trained with data vectors from 165 patients. Scaled Conjugate Gradient, Levenberg-Marquardt, Resilient Back propagation and One Step Secant gradient learning algorithms were used. The training procedure was performed using the soft tissue thicknesses, determined using image processing techniques that automatically segment the skin and rib cage. The developed solution was then used to determine the ribs outline in data from 20 patient scanners. Tests revealed that ribs position can be estimated with an average error of about 6.82±5.7 mm for the left and right side of the patient. Such an error range is well below current prosthesis manual modeling (11.7±4.01 mm) even without CT imagiology, indicating a considerable step forward towards CT replacement by a 3D scanner for prosthesis personalization.

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Neste artigo é apresentado um Sistema de Apoio à Decisão Espacial (SADE) onde os decisores podem facilmente definir diferentes tipos de problemas espaciais recorrendo a diferentes categorias de objetos, pré-definidas ou a definir, associando- lhes características com ou sem dependência espacial, e indicando formas de interferência (impactos) entre essas caracte- rísticas/propriedades. A análise espacial para determinação ou avaliação de configurações alternativas para a localização de diferentes tipos de ocorrências espaciais será feita através da utilização interativa do SADE de acordo com conjuntos de regras intrínsecas aos vários elementos gráficos (objetos, categorias, características, impactos) utilizados na definição dos problemas. O teste à generalidade representativa e analítica do SADE proposto é efectuado recorrendo a um problema concreto, suficientemente específico e complexo, relativo à aplicação de modelos gaussianos para o estudo da dispersão atmosférica de eventuais poluentes resultantes do tratamento de resíduos sólidos. A região em estudo está limitada, neste exemplo, ao município de Coimbra, Portugal. Para este município estão acessíveis, e são utilizados, os dados demográficos ao nível da secção de voto (censos oficiais) e, como tal, é possível a realização de um estudo realístico do impacto com populações humanas.

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The mycelium and young fruiting bodies of Agaricus blazei were submitted to supercritical CO2 extraction, in a modified commercial flow apparatus, at temperatures from 40 to 80 ºC, pressures up to 600 bar and CO2 flow-rates from 2.0 to 9.0 g.min-1. The best extraction conditions of secondary metabolites, whereby the degree of solubilization (g extract/100 g of fungi) is the highest, was obtained with pure CO2 at 400 bar, 70 ºC and a CO2 flow rate of 5.7g.min-1. The extract in that conditions were analysed by GC-Ms. In order to increase the extraction yield of secondary metabolites, which are mostly present in glycolipid fractions, a polar compound (ethanol) was used as co-solvent in the proportions of 5 and 10 % (mol/mol). The presence of ethanol increased the yield when compared with the extraction with pure CO2. Moreover, a simple model was applied to the supercritical CO2 extraction of secondary metabolites from Agaricus blazei.

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Earthquakes and tsunamis along Morocco's coasts have been reported since historical times. The threat posed by tsunamis must be included in coastal risk studies. This study focuses on the tsunami impact and vulnerability assessment of the Casablanca harbour and surrounding area using a combination of tsunami inundation numerical modelling, field survey data and geographic information system. The tsunami scenario used here is compatible with the 1755 Lisbon event that we considered to be the worst case tsunami scenario. Hydrodynamic modelling was performed with an adapted version of the Cornell Multigrid Coupled Tsunami Model from Cornell University. The simulation covers the eastern domain of the Azores-Gibraltar fracture zone corresponding to the largest tsunamigenic area in the North Atlantic. The proposed vulnerability model attempts to provide an insight into the tsunami vulnerability of building stock. Results in the form of a vulnerability map will be useful for decision makers and local authorities in preventing the community resiliency for tsunami hazards.