A trajectória do auto-retrato pintado na história da arte em Portugal : da emergência à afirmação do género, na contemporaneidade, 1470-1975

Tese de doutoramento, História (História da Arte), Universidade de Lisboa, Faculdade de Letras, 2015

Design e auto-produção : novos paradigmas para o design de artefactos na sociedade pós-industrial : a contribuição das tecnologias digitais

Tese de doutoramento, Belas-Artes (Design de Equipamento), Universidade de Lisboa, Faculdade de Belas-Artes, 2015

A Community-Level, Mesoscale Analysis of Fish Assemblage Structure in Shoreline Habitats of a Large River Using Multivariate Regression Trees.

The mesoscale (100–102 m) of river habitats has been identified as the scale that simultaneously offers insights into ecological structure and falls within the practical bounds of river management. Mesoscale habitat (mesohabitat) classifications for relatively large rivers, however, are underdeveloped compared with those produced for smaller streams. Approaches to habitat modelling have traditionally focused on individual species or proceeded on a species-by-species basis. This is particularly problematic in larger rivers where the effects of biological interactions are more complex and intense. Community-level approaches can rapidly model many species simultaneously, thereby integrating the effects of biological interactions while providing information on the relative importance of environmental variables in structuring the community. One such community-level approach, multivariate regression trees, was applied in order to determine the relative influences of abiotic factors on fish assemblages within shoreline mesohabitats of San Pedro River, Chile, and to define reference communities prior to the planned construction of a hydroelectric power plant. Flow depth, bank materials and the availability of riparian and instream cover, including woody debris, were the main variables driving differences between the assemblages. Species strongly indicative of distinctive mesohabitat types included the endemic Galaxias platei. Among other outcomes, the results provide information on the impact of non-native salmonids on river-dwelling Galaxias platei, suggesting a degree of habitat segregation between these taxa based on flow depth. The results support the use of the mesohabitat concept in large, relatively pristine river systems, and they represent a basis for assessing the impact of any future hydroelectric power plant construction and operation. By combing community classifications with simple sets of environmental rules, the multivariate regression trees produced can be used to predict the community structure of any mesohabitat along the reach.

Inferring Big 5 Personality from Online Social Networks

Thesis (Master's)--University of Washington, 2014

Long-term price range forecast applied to risk management using regression models

Long-term contractual decisions are the basis of an efficient risk management. However those types of decisions have to be supported with a robust price forecast methodology. This paper reports a different approach for long-term price forecast which tries to give answers to that need. Making use of regression models, the proposed methodology has as main objective to find the maximum and a minimum Market Clearing Price (MCP) for a specific programming period, and with a desired confidence level α. Due to the problem complexity, the meta-heuristic Particle Swarm Optimization (PSO) was used to find the best regression parameters and the results compared with the obtained by using a Genetic Algorithm (GA). To validate these models, results from realistic data are presented and discussed in detail.

Programa de intervenção segundo o modelo de auto-regulação na esclerose múltipla

A esclerose múltipla é um doença crónica do sistema nervoso central, que afecta mais frequentemente adultos jovens, no auge da sua carreira profissional e desenvolvimento pessoal, sem cura e de causas desconhecidas. Os sintomas e sinais mais comuns são a fadiga, fraqueza muscular, alterações da sensibilidade, ataxia, alterações do equilíbrio, dificuldades na marcha, dificuldades de memória, alterações cognitivas e dificuldades na resolução de problemas. A esclerose múltipla é uma doença progressiva e imprevisível, resultando, nalguns casos, em incapacidades e limitações de actividade de vida diária, causando danos irreparáveis para os indivíduos. Esta doença pode surgir através de surtos ou de uma forma progressiva.

Avaliação da auto-suficiência energética na indústria nacional arrozeira

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

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

Reflexão e auto-avaliação do/a educador/a

Relatório da Prática Profissional Supervisionada Mestrado em Educação Pré-Escolar

Simulation of the magnetic induction vector of a magnetic core to be used in FFC NMR relaxometry

This paper is a contribution for the assessment and comparison of magnet properties based on magnetic field characteristics particularly concerning the magnetic induction uniformity in the air gaps. For this aim, a solver was developed and implemented to determine the magnetic field of a magnetic core to be used in Fast Field Cycling (FFC) Nuclear Magnetic Resonance (NMR) relaxometry. The electromagnetic field computation is based on a 2D finite-element method (FEM) using both the scalar and the vector potential formulation. Results for the magnetic field lines and the magnetic induction vector in the air gap are presented. The target magnetic induction is 0.2 T, which is a typical requirement of the FFC NMR technique, which can be achieved with a magnetic core based on permanent magnets or coils. In addition, this application requires high magnetic induction uniformity. To achieve this goal, a solution including superconducting pieces is analyzed. Results are compared with a different FEM program.

A motivação da aprendizagem de um instrumento musical em alunos do ensino básico articulado sob a perspectiva da teoria da auto-determinação no Conservatório Regional de Setúbal: relatório de estágio

O presente relatório, no âmbito da obtenção do grau de Mestre no Ensino da Música, na Escola Superior de Música de Lisboa, descreve o estágio efectuado no Conservatório Regional de Setúbal e analisa a prática pedagógica do professor através de três alunos de violino e viola d´arco de níveis diferentes: Iniciação (violino); 4º grau, Ensino Básico (viola d´arco) e 7º grau, Ensino Secundário (viola d´arco). São descritas e analisadas as práticas pedagógicas desenvolvidas com base na filosofia do Método Suzuki e na Teoria da Auto-­determinação de Edward L. Deci e Richard M. Ryan. O objectivo fundamental do processo de ensino-­ aprendizagem é a criação de condições para que os alunos se motivem autonomamente e atinjam níveis altos de motivação intrínseca (Teoria da Auto-­determinação), e que se tornem bons instrumentistas e melhores seres humanos (Método Suzuki).

Contributos maternos para a auto-regulação do bebé na situação experimental face-to-face still-face

Dissertação apresentada na Escola Superior de Educação de Lisboa para obtenção do grau de Mestre em Intervenção Precoce

Cinema na primeira pessoa: auto-representação e auto reflexividade no documentário contemporâneo: trabalho de projecto

Trabalho de Projeto submetido à Escola Superior de Teatro e Cinema para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Desenvolvimento do Projeto Cinematográfico - especialização em Dramaturgia e Realização.

Multiple Linear Regression and Artificial Neural Networks to Predict Time and Efficiency of Soil Vapor Extraction

The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.

Short-term Wind Speed Forecasting using Support Vector Machines

Wind speed forecasting has been becoming an important field of research to support the electricity industry mainly due to the increasing use of distributed energy sources, largely based on renewable sources. This type of electricity generation is highly dependent on the weather conditions variability, particularly the variability of the wind speed. Therefore, accurate wind power forecasting models are required to the operation and planning of wind plants and power systems. A Support Vector Machines (SVM) model for short-term wind speed is proposed and its performance is evaluated and compared with several artificial neural network (ANN) based approaches. A case study based on a real database regarding 3 years for predicting wind speed at 5 minutes intervals is presented.