A especificidade do trabalho de Pontas no Ensino Artístico Especializado

Relatório Final de Estágio apresentado à Escola Superior de Dança com vista à obtenção do Grau de Mestre em Ensino de Dança.

As emoções e o desenvolvimento da criatividade dos alunos de 3º ciclo, no âmbito da Composição Coreográfica, na Escola Vocacional de Dança das Caldas da Rainha

Relatório Final de Estágio apresentado à Escola Superior de Dança, com vista à obtenção do grau de Mestre em Ensino de Dança.

Exposição ocupacional a mercúrio: associação com a atividade da paraoxonase humana e vitaminas A e E

Mestrado em Segurança e Higiene no Trabalho

Avaliação ecocardiográfica da insuficiência mitral concomitante, na substituição valvular aórtica isolada: é possível prevê-la?

Mestrado em Tecnologia de Diagnóstico e Intervenção Cardiovascular - Ramo de especialização: Ultrassonografia Cardiovascular

A gestão e o controlo do grupo de crianças

Relatório da Prática Profissional Supervisionada Mestrado em Educação Pré-Escolar

Luz ao fundo do túnel? Análise de um modelo de prevenção e intervenção face ao sobreendividamento das famílias

Na actual conjuntura económica portuguesa tem-se registado uma evolução crescente de situações de sobreendividamento ou de insolvência dos agregados familiares. Associada a esta tendência, surge a preocupação, por parte dos decisores, em encontrar formas de intervenção, mais ou menos ajustadas, face aos problemas verificados. Contudo, esta problemática exige uma actuação integrada, que contemple medidas direccionadas não apenas para a intervenção mas também para a prevenção deste tipo de situações na sociedade portuguesa. Pretendemos, com a apresentação deste modelo, propor um vasto conjunto de medidas, entre as quais se conta a educação financeira, que conduzam a uma dupla actuação face à problemática do sobreendividamento (preventiva e de tratamento), atendendo aos antecedentes, de natureza diversa, que podem estar na sua origem. Este modelo será alvo de uma reflexão e análise, com vista a identificar a pertinência da sua aplicação ao actual panorama sócio-económico português.

Análise dos modos de falha e seus efeitos (FMEA) aplicada a um secador industrial

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Qualidade de vida, necessidades terapêuticas e preocupações de pais de crianças com necessidades especiais: abordagem centrada na família

Mestrado em Fisioterapia

Contribuição do isolamento térmico para o aumento da eficiência energética em edifícios

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Aparelhos de apoio em pontes: vida útil e procedimentos de substituição

Dissertação de Natureza Científica para obtenção do grau de Mestre em Engenharia Civil Perfil Estruturas

Incremental filter and wrapper approaches for feature discretization

Discrete data representations are necessary, or at least convenient, in many machine learning problems. While feature selection (FS) techniques aim at finding relevant subsets of features, the goal of feature discretization (FD) is to find concise (quantized) data representations, adequate for the learning task at hand. In this paper, we propose two incremental methods for FD. The first method belongs to the filter family, in which the quality of the discretization is assessed by a (supervised or unsupervised) relevance criterion. The second method is a wrapper, where discretized features are assessed using a classifier. Both methods can be coupled with any static (unsupervised or supervised) discretization procedure and can be used to perform FS as pre-processing or post-processing stages. The proposed methods attain efficient representations suitable for binary and multi-class problems with different types of data, being competitive with existing methods. Moreover, using well-known FS methods with the features discretized by our techniques leads to better accuracy than with the features discretized by other methods or with the original features. (C) 2013 Elsevier B.V. All rights reserved.

Dynamic peripheral visual performance relates to alpha activity in soccer players

Many studies have demonstrated the relationship between the alpha activity and the central visual ability, in which the visual ability is usually assessed through static stimuli. Besides static circumstance, however in the real environment there are often dynamic changes and the peripheral visual ability in a dynamic environment (i.e., dynamic peripheral visual ability) is important for all people. So far, no work has reported whether there is a relationship between the dynamic peripheral visual ability and the alpha activity. Thus, the objective of this study was to investigate their relationship. Sixty-two soccer players performed a newly designed peripheral vision task in which the visual stimuli were dynamic, while their EEG signals were recorded from Cz, O1, and O2 locations. The relationship between the dynamic peripheral visual performance and the alpha activity was examined by the percentage-bend correlation test. The results indicated no significant correlation between the dynamic peripheral visual performance and the alpha amplitudes in the eyes-open and eyes-closed resting condition. However, it was not the case for the alpha activity during the peripheral vision task: the dynamic peripheral visual performance showed significant positive inter-individual correlations with the amplitudes in the alpha band (8-12 Hz) and the individual alpha band (IAB) during the peripheral vision task. A potential application of this finding is to improve the dynamic peripheral visual performance by up-regulating alpha activity using neuromodulation techniques.

Sofrologia caycediana®: contributo para o tratamento da dor no doente oncológico

Mestrado em Fisioterapia

Neural-network approach to modeling liquid crystals in complex confinement

Finding the structure of a confined liquid crystal is a difficult task since both the density and order parameter profiles are nonuniform. Starting from a microscopic model and density-functional theory, one has to either (i) solve a nonlinear, integral Euler-Lagrange equation, or (ii) perform a direct multidimensional free energy minimization. The traditional implementations of both approaches are computationally expensive and plagued with convergence problems. Here, as an alternative, we introduce an unsupervised variant of the multilayer perceptron (MLP) artificial neural network for minimizing the free energy of a fluid of hard nonspherical particles confined between planar substrates of variable penetrability. We then test our algorithm by comparing its results for the structure (density-orientation profiles) and equilibrium free energy with those obtained by standard iterative solution of the Euler-Lagrange equations and with Monte Carlo simulation results. Very good agreement is found and the MLP method proves competitively fast, flexible, and refinable. Furthermore, it can be readily generalized to the richer experimental patterned-substrate geometries that are now experimentally realizable but very problematic to conventional theoretical treatments.

Global localization with non-quantized local image features

In the field of appearance-based robot localization, the mainstream approach uses a quantized representation of local image features. An alternative strategy is the exploitation of raw feature descriptors, thus avoiding approximations due to quantization. In this work, the quantized and non-quantized representations are compared with respect to their discriminativity, in the context of the robot global localization problem. Having demonstrated the advantages of the non-quantized representation, the paper proposes mechanisms to reduce the computational burden this approach would carry, when applied in its simplest form. This reduction is achieved through a hierarchical strategy which gradually discards candidate locations and by exploring two simplifying assumptions about the training data. The potential of the non-quantized representation is exploited by resorting to the entropy-discriminativity relation. The idea behind this approach is that the non-quantized representation facilitates the assessment of the distinctiveness of features, through the entropy measure. Building on this finding, the robustness of the localization system is enhanced by modulating the importance of features according to the entropy measure. Experimental results support the effectiveness of this approach, as well as the validity of the proposed computation reduction methods.