Usabilidade nos portais web

Mestrado em Engenharia Informática. Sistemas Gráficos e Multimédia.

Abordagem à previsão do preço de energia elétrica via métodos de suavização exponencial

Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

A satisfação no trabalho : uma aplicação às instituições particulares de solidariedade social em São Miguel, Açores

Dissertação de Mestrado em Gestão de Empresas/MBA.

Redes sociais e a sua utilização no marketing

Dissertação de Mestrado em Ciências Económicas e Empresariais.

Contributo do iPad® para o desenvolvimento de crianças com necessidades educativas especiais

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção do grau de Mestre em Ciências da Educação, Especialidade Intervenção Precoce

Embedded platform for ECG biometric recognition

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Efeito de metais pesados na alga Pseudokirchneriella subcapitata

O impacto dos metais pesados em ambientes aquáticos, incluindo águas residuais, é vulgarmente determinado através de testes de toxicidade. A microalga Pseudokirchneriella subcapitata é usada nos métodos de toxicidade recomendados por organismos Internacionais como a EPA (Environmental Protection Agency) e a OCDE (Organização para a Cooperação e Desenvolvimento Económico). O presente trabalho teve como objectivo avaliar o impacto do cádmio e do zinco no crescimento, na autofluorescência e na actividade metabólica da alga P. subcapitata. Para tal, a alga, em fase exponencial de crescimento, foi inoculada no meio de cultura contendo Cd (150, 500 ou 700 nmol/l) ou Zn (300, 1800 ou 6000 nmol/l). A concentração mais baixa de Cd e Zn não provocou qualquer efeito inibitório. Para uma concentração intermédia de Cd e Zn, observou-se uma redução do crescimento, ao fim de 72 h, de 63 e 50 %, respectivamente. No caso da concentração mais elevada de Cd e de Zn, observou-se uma redução do crescimento, ao fim de 72 h, de 83 e 97 %, respectivamente. A perda de autofluorescência da alga, devido à presença de Cd e de Zn, seguiu um padrão similar ao efeito sobre o crescimento. Resultados preliminares mostraram que a exposição das células de P. subcapitata a 700 nmol/ de Cd, durante 1h, induziu uma inibição da actividade esterásica de 52 %, enquanto que a incubação com 6000 nmol/l de Zn, durante 6 h, provocou uma redução da actividade esterásica de ~ 50 %. Em conclusão, os resultados obtidos mostram que o Cd é mais tóxico que o Zn para a alga P. subcapitata. A perda de autofluorescência, devido à exposição aos metais pesados em estudo, ocorreu segundo um padrão similar ao efeito inibitório sobre o crescimento. O Cd e Zn provocaram uma rápida perda (no espaço de 6 h) da actividade esterásica. Estes resultados sugerem que a avaliação da actividade esterásica da alga P. subcapitata poderá constituir um indicador sensível na avaliação da toxicidade.

Uma abordagem comunicativa à aprendizagem da língua em contexto educativo pré-escolar e escolar (1.º ciclo do Ensino Básico)

Mestrado, Educação Pré-Escolar e Ensino do 1.º Ciclo do Ensino Básico, 19 de Junho 2015, Universidade dos Açores.

Adaptive learning in agents behaviour: a framework for electricity markets simulation

Electricity markets are complex environments with very particular characteristics. A critical issue regarding these specific characteristics concerns the constant changes they are subject to. This is a result of the electricity markets’ restructuring, which was performed so that the competitiveness could be increased, but it also had exponential implications in the increase of the complexity and unpredictability in those markets scope. The constant growth in markets unpredictability resulted in an amplified need for market intervenient entities in foreseeing market behaviour. The need for understanding the market mechanisms and how the involved players’ interaction affects the outcomes of the markets, contributed to the growth of usage of simulation tools. Multi-agent based software is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This dissertation presents ALBidS – Adaptive Learning strategic Bidding System, a multiagent system created to provide decision support to market negotiating players. This system is integrated with the MASCEM electricity market simulator, so that its advantage in supporting a market player can be tested using cases based on real markets’ data. ALBidS considers several different methodologies based on very distinct approaches, to provide alternative suggestions of which are the best actions for the supported player to perform. The approach chosen as the players’ actual action is selected by the employment of reinforcement learning algorithms, which for each different situation, simulation circumstances and context, decides which proposed action is the one with higher possibility of achieving the most success. Some of the considered approaches are supported by a mechanism that creates profiles of competitor players. These profiles are built accordingly to their observed past actions and reactions when faced with specific situations, such as success and failure. The system’s context awareness and simulation circumstances analysis, both in terms of results performance and execution time adaptation, are complementary mechanisms, which endow ALBidS with further adaptation and learning capabilities.

Controlo e gestão da rede de postos de abastecimento : o caso da J.H. Ornelas & Suc., Lda.

Dissertação de Mestrado, Ciências Económicas e Empresariais, 15 de Dezembro de 2015, Universidade dos Açores.

Happiness, hope, and affection as predictors of quality of life and functionality of individuals with heart failure at three-month follow-up

The scientific evidence supporting the management of the chronically ill in a positive psychological perspective in opposition to traditional pathological approach is scarce. This study examines issues associated with recovery of health status in heart failure, in particular hope, affection, and happiness. We use a longitudinal study of 128 symptomatic patients who after medical intervention reported improved quality of life and function at 3-month follow-up. We evaluated the contribution of happiness, hope and affection, individually and as a whole, in the quality of life and functionality of individuals with heart failure. Happiness (Subjective Happiness Scale), Hope (HOPE Scale), and affection (PANAS (positive and negative affect schedule)) were determined before medical intervention. Individually, we found that happiness is correlated with the quality of life and functionality, hope to self-efficacy dimension of the quality of life scale, positive affect to functionality and negative affect with symptoms dimension, quality of life dimension, and overall sum of the quality of life scale. Overall, we found that happiness has a unique contribution to the quality of life, except in self-efficacy dimension where hope takes this contribution and positive affect has a unique contribution to the functionality in this short-term follow-up. The results highlight the importance of positive variables to health outcomes for people with heart failure and should be considered in intervention programs for this syndrome.

Biaxial Nematic Order in the Hard-boomerang Fluid

We consider a fluid of hard boomerangs, each composed of two hard spherocylinders joined at their ends at an angle Psi. The resulting particle is nonconvex and biaxial. The occurence of nematic order in such a system has been investigated using Straley's theory, which is a simplificaton of Onsager's second-virial treatment of long hard rods, and by bifurcation analysis. The excluded volume of two hard boomerangs has been approximated by the sum of excluded volumes of pairs of constituent spherocylinders, and the angle-dependent second-virial coefficient has been replaced by a low-order interpolating function. At the so-called Landau point, Psi(Landau)approximate to 107.4 degrees, the fluid undergoes a continuous transition from the isotropic to a biaxial nematic (B) phase. For Psi not equal Psi(Landau) ordering is via a first-order transition into a rod-like uniaxial nematic phase (N(+)) if Psi > Psi(Landau), or a plate-like uniaxial nematic (N(-)) phase if Psi < Psi(Landau). The B phase is separated from the N(+) and N(-) phases by two lines of continuous transitions meeting at the Landau point. This topology of the phase diagram is in agreement with previous studies of spheroplatelets and biaxial ellipsoids. We have checked the accuracy of our theory by performing numerical calculations of the angle-dependent second virial coefficient, which yields Psi(Landau)approximate to 110 degrees for very long rods, and Psi(Landau)approximate to 90 degrees for short rods. In the latter case, the I-N transitions occur at unphysically high packing fractions, reflecting the inappropriateness of the second-virial approximation in this limit.

Does independent component analysis play a role in unmixing hyperspectral data?

Independent component analysis (ICA) has recently been proposed as a tool to unmix hyperspectral data. ICA is founded on two assumptions: 1) the observed spectrum vector is a linear mixture of the constituent spectra (endmember spectra) weighted by the correspondent abundance fractions (sources); 2)sources are statistically independent. Independent factor analysis (IFA) extends ICA to linear mixtures of independent sources immersed in noise. Concerning hyperspectral data, the first assumption is valid whenever the multiple scattering among the distinct constituent substances (endmembers) is negligible, and the surface is partitioned according to the fractional abundances. The second assumption, however, is violated, since the sum of abundance fractions associated to each pixel is constant due to physical constraints in the data acquisition process. Thus, sources cannot be statistically independent, this compromising the performance of ICA/IFA algorithms in hyperspectral unmixing. This paper studies the impact of hyperspectral source statistical dependence on ICA and IFA performances. We conclude that the accuracy of these methods tends to improve with the increase of the signature variability, of the number of endmembers, and of the signal-to-noise ratio. In any case, there are always endmembers incorrectly unmixed. We arrive to this conclusion by minimizing the mutual information of simulated and real hyperspectral mixtures. The computation of mutual information is based on fitting mixtures of Gaussians to the observed data. A method to sort ICA and IFA estimates in terms of the likelihood of being correctly unmixed is proposed.

Dependent component analysis: a hyperspectral unmixing algorithm

Linear unmixing decomposes a hyperspectral image into a collection of reflectance spectra of the materials present in the scene, called endmember signatures, and the corresponding abundance fractions at each pixel in a spatial area of interest. This paper introduces a new unmixing method, called Dependent Component Analysis (DECA), which overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical properties of hyperspectral data. DECA models the abundance fractions as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. The mixing matrix is inferred by a generalized expectation-maximization (GEM) type algorithm. The performance of the method is illustrated using simulated and real data.

Does Independent Component Analysis Play a Role in Unmixing Hyperspectral Data?

Chapter in Book Proceedings with Peer Review First Iberian Conference, IbPRIA 2003, Puerto de Andratx, Mallorca, Spain, JUne 4-6, 2003. Proceedings