Robótica móvel: sistema de condução autónoma

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo Automação e Electrónica Industrial

Conceções e práticas de ciência de educadores de infância

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção do grau de Mestre em Ciências da Educação Especialidade em Didáctica das Ciências da Natureza

A arte contemporânea enquanto elemento facilitador da auto valorização dos jovens perante as suas criações artísticas

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Educação Artística, na Especialização de Artes Plásticas na Educação

Prática de ensino supervisionado no 1.º e 2.º ciclo do ensino básico: o TEA como estratégia de implicação do aluno no seu processo de ensino aprendizagem

Relatório Final apresentado à Escola Superior de Educação de Lisboa para obtenção do grau de mestre em Ensino do 1º e do 2º Ciclo de Ensino Básico

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.

Implementação das medidas de autoproteção em edifícios escolares

Mestrado em Segurança e Higiene no Trabalho

Crianças mais autónomas são crianças mais felizes: O Educador de Infância na promoção de autonomia

Relatório da Prática Profissional Supervisionada Mestrado em Educação Pré-Escolar

O impacto da formação contínua no desenvolvimento pessoal e profissional dos técnicos de Análises Clínicas e Saúde Pública

Mestrado em Intervenção Sócio-Organizaional na Saúde - Ramo de especialização: Intervenção Comunitária

Avaliação de fiabilidade de sistemas elétricos e de automação em instalações de frio industrial

Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia/Automação e Eletrónica Industrial

Sistema de visão para aterragem automática de UAV

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial

O controlo interno nos serviços e fundos autónomos

Mestrado em Auditoria

A metáfora e a imagem : estratégias para a transmissão de conteúdos técnicos na aula de Dança Clássica com alunos do 1º ano da Escola de Dança de Ana Luísa Mendonça

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

Autonomic workflow activities: the award framework

Workflows have been successfully applied to express the decomposition of complex scientific applications. This has motivated many initiatives that have been developing scientific workflow tools. However the existing tools still lack adequate support to important aspects namely, decoupling the enactment engine from workflow tasks specification, decentralizing the control of workflow activities, and allowing their tasks to run autonomous in distributed infrastructures, for instance on Clouds. Furthermore many workflow tools only support the execution of Direct Acyclic Graphs (DAG) without the concept of iterations, where activities are executed millions of iterations during long periods of time and supporting dynamic workflow reconfigurations after certain iteration. We present the AWARD (Autonomic Workflow Activities Reconfigurable and Dynamic) model of computation, based on the Process Networks model, where the workflow activities (AWA) are autonomic processes with independent control that can run in parallel on distributed infrastructures, e. g. on Clouds. Each AWA executes a Task developed as a Java class that implements a generic interface allowing end-users to code their applications without concerns for low-level details. The data-driven coordination of AWA interactions is based on a shared tuple space that also enables support to dynamic workflow reconfiguration and monitoring of the execution of workflows. We describe how AWARD supports dynamic reconfiguration and discuss typical workflow reconfiguration scenarios. For evaluation we describe experimental results of AWARD workflow executions in several application scenarios, mapped to a small dedicated cluster and the Amazon (Elastic Computing EC2) Cloud.

Genus for knots and links in renormalizable templates with several branch nodes

We apply kneading theory to describe the knots and links generated by the iteration of renormalizable nonautonomous dynamical systems with reducible kneading invariants, in terms of the links corresponding to each factor. As a consequence we obtain explicit formulas for the genus for this kind of knots and links.

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.