A formação profissional e a qualidade dos serviços prestados a idosos institucionalizados

Dissertação de Mestrado, Ciências da Educação - Educação e Formação de Adultos, Faculdade de Ciências Humanas e Sociais, Universidade do Algarve; Escola Superior de Educação, Instituto Politécnico de Beja, 2008

O fuso e a trama: génese e identidade da ordem da Imaculada

Tese de mestrado, Estudos Românicos (Cultura Portuguesa), Universidade de Lisboa, Faculdade de Letras, 2011

Avaliação para as aprendizagens de alunos com necessidades educativas especiais no 1º ciclo de ensino básico : da diversidade da avaliação à avaliação da diversidade

Tese de doutoramento, Educação (Avaliação em Educação), Universidade de Lisboa, Instituto de Educação, 2014

L. T. hobhouse’s new liberalism and the reformulation of ideology

Tese de doutoramento, Estudos de Literatura e de Cultura (Estudos Ingleses), Universidade de Lisboa, Faculdade de Letras, 2014

Valorização de resíduos carbonosos de gasificação como precursores de materiais para adsorção de poluentes em fase aquosa

Tese de doutoramento, Energia e Ambiente (Energia e Desenvolvimento Sustentável), Universidade de Lisboa, Faculdade de Ciências, 2014

Development of new technologies for the selective removal of volatile compounds with applications in forensic science and natural aromas

Tese de doutoramento, Farmácia (Química Farmacêutica e Terapêutica), Universidade de Lisboa, Faculdade de Farmácia, 2015

Essays on Applications of the Factor Model

Thesis (Ph.D.)--University of Washington, 2013

Micromorphology of the labellum and structure of the osmophore in a group of closely related species of the sexually deceptive Orchid genus Ophrys (orchidaceae)

Tese de doutoramento, Biologia (Biologia Celular), Universidade de Lisboa, Faculdade de Ciências, 2016

O doente geriátrico em cuidados paliativos

Tese de mestrado, Cuidados Paliativos, Faculdade de Medicina, Universidade de Lisboa, 2016

Should I stay or should I go? Sibling effects in household formation

This paper analyzes peer effects among siblings in the decision to leave parental home. Estimating peer effects is challenging because of problems of refection, endogenous group formation, and correlated unobservables. We overcome these issues using the exogenous variation in siblings' household formation implied by the eligibility rules for a Spanish rental subsidy. Our results show that sibling effects are negative and that these effects can be explained by the presence of old or ill parents. Sibling effects turn positive from older to younger close-in-age siblings, when imitation is more likely to prevail. Our findings indicate that policy makers who aim at fostering household formation should target the household rather than the individual and combine policies for young adults with policies for the elderly.

An artificial neural network approach for short-term wind power forecasting in Portugal

This paper presents an artificial neural network approach for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated against persistence and ARIMA approaches, reporting the numerical results from a real-world case study.

A risk-averse optimization model for trading wind energy in a market environment under uncertainty

In this paper, a stochastic programming approach is proposed for trading wind energy in a market environment under uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain parameter is modeled by scenarios, where each scenario represents a plausible realization of the uncertain parameters with an associated occurrence probability. Also, an appropriate risk measurement is considered. The proposed approach is applied on a realistic case study, based on a wind farm in Portugal. Finally, conclusions are duly drawn. (C) 2011 Elsevier Ltd. All rights reserved.

Application of adaptive neuro-fuzzy inference for wind power short-term forecasting

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. In this paper, an adaptive neuro-fuzzy inference approach is proposed for short-term wind power forecasting. Results from a real-world case study are presented. A thorough comparison is carried out, taking into account the results obtained with other approaches. Numerical results are presented and conclusions are duly drawn. (C) 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

A short-term risk management tool applied to OMEL electricity market using particle swarm optimization

Short-term risk management is highly dependent on long-term contractual decisions previously established; risk aversion factor of the agent and short-term price forecast accuracy. Trying to give answers to that problem, this paper provides a different approach for short-term risk management on electricity markets. Based on long-term contractual decisions and making use of a price range forecast method developed by the authors, the short-term risk management tool presented here has as main concern to find the optimal spot market strategies that a producer should have for a specific day in function of his risk aversion factor, with the objective to maximize the profits and simultaneously to practice the hedge against price market volatility. Due to the complexity of the optimization problem, the authors make use of Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data, namely from OMEL electricity market, are presented and discussed in detail.

A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn.