Ser mulher, aqui: teatro, género e comunidade

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Educação Artística, na especialização de Teatro na Educação

“Os crescidos vão para o colo dos crescidos … é só os crescidos!” direitos de participação das crianças em centros de acolhimento temporário

Dissertação apresentada à Escola Superior de Educação de Lisboa para a obtenção de grau de mestre em Ciências da Educação, Especialização em Intervenção Precoce

e-Recruitment: descrição e inferência sobre oferta e procura

Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Informática e de Computadores

An Evaluation of Local Feature Combiners for Robot Visual Localization

In the last decade, local image features have been widely used in robot visual localization. To assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image to those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, we compare several candidate combiners with respect to their performance in the visual localization task. A deeper insight into the potential of the sum and product combiners is provided by testing two extensions of these algebraic rules: threshold and weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance. The voting method, whilst competitive to the algebraic rules in their standard form, is shown to be outperformed by both their modified versions.

Diagnóstico de avarias em máquinas rotativas utilizando a análise de órbitas

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica Perfil Manutenção e Produção

O corpo como imagem e as imagens do corpo na contemporaneidade

Tese de doutoramento, Belas-Artes (Teoria da Imagem), Universidade de Lisboa, Faculdade de Belas-Artes, 2013

Reafirmar a Identidade cultural local: o património cultural imaterial local como recurso

Dissertação conducente à obtenção do grau de Mestre em Educação Social e Intervenção Comunitária, sob orientação do Professor Doutor Luís Manuel Costa Moreno

Radiopharmaceuticals for myocardial perfusion imaging: SPECT & PET

Myocardial perfusion imaging (MPI) is used on a daily basis to access coronary blood flow in patients that are suspected or have known Coronary Artery Disease (CAD). A Single Photon Emission Computed Tomography (SPECT) or and Positron Emission Tomography (PET) scan are used to access regional blood flow quantification either at rest or stress, the imaging acquisition is connected to an Electrocardiogram (ECG) and it is able to determine and quantify other myocardial parameters like myocardial wall thickness and wall motion. PET is not used so broadly due to its high procedure cost, the proximity with cyclotron, where are produced the majority of radiopharmaceuticals used in PET, due to their shor thalf-life. This work is intended to carry out a review of the tests relating to radiopharmaceuticals that are used in clinical practice in SPECT or PET for assessment of myocardial perfusion, also focusing very promising radiopharmaceuticals that are under investigation or in clinical trials with great potential for conventional nuclear medicine or PET, proceeding to a comparative analysis of both techniques and respective radiopharmaceuticals used.

Hydrogenating activity of Pt/zeolite catalysts focusing acid support and metal dispersion influence

Toluene hydrogenation was studied over catalysts based on Pt supported on large pore zeolites (HUSY and HBEA) with different metal/acid ratios. Acidity of zeolites was assessed by pyridine adsorption followed by FTIR showing only small changes before and after Pt introduction. Metal dispersion was determined by H2–O2 titration and verified by a linear correlation with the intensity of Pt0–CO band obtained by in situ FTIR. It was also observed that the electronic properties of Pt0 clusters were similar for the different catalysts. Catalytic tests showed rapid catalyst deactivation with an activity loss of 80–95% after 60 min of reaction. The turnover frequency of fresh catalysts depended both on metal dispersion and the support. For the same support, it changed by a 1.7-fold (HBEA) and 4.0-fold (HUSY) showing that toluene hydrogenation is structure-sensitive, i.e. hydrogenating activity is not a unique function of accessible metal. This was proposed to be due to the contribution to the overall activity of the hydrogenation of adsorbed toluene on acid sites via hydrogen spillover. Taking into account the role of zeolite acidity, the catalysts series were compared by the activity per total adsorbing sites which was observed to increase steadily with nPt/(nPt + nA). An increase of the accessible Pt atoms leads to an increase on the amount of spilled over hydrogen available in acid sites therefore increasing the overall activity. Pt/HBEA catalysts were found to be more active per total adsorbing site than Pt/HUSY which is proposed to be due to an augmentation in the efficiency of spilled over hydrogen diffusion related to the proximity between Pt clusters and acid sites. The intervention of Lewis acid sites in a greater extent than that measured by pyridine adsorption may also contribute to this higher activity of Pt/HBEA catalysts. These results reinforce the importance of model reactions as a closer perspective to the relevant catalyst properties in reaction conditions.

Robot visual localization through local feature fusion: an evaluation of multiple classifiers combination approaches

In the last decade, local image features have been widely used in robot visual localization. In order to assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image with those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, in this paper we compare several candidate combiners with respect to their performance in the visual localization task. For this evaluation, we selected the most popular methods in the class of non-trained combiners, namely the sum rule and product rule. A deeper insight into the potential of these combiners is provided through a discriminativity analysis involving the algebraic rules and two extensions of these methods: the threshold, as well as the weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. Furthermore, we address the process of constructing a model of the environment by describing how the model granularity impacts upon performance. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance, confirming the general agreement on the robustness of this rule in other classification problems. The voting method, whilst competitive with the product rule in its standard form, is shown to be outperformed by its modified versions.