A decision-support system based on particle swarm optimization for multiperiod hedging in electricity markets

This paper proposes a particle swarm optimization (PSO) approach to support electricity producers for multiperiod optimal contract allocation. The producer risk preference is stated by a utility function (U) expressing the tradeoff between the expectation and variance of the return. Variance estimation and expected return are based on a forecasted scenario interval determined by a price range forecasting model developed by the authors. A certain confidence level is associated to each forecasted scenario interval. The proposed model makes use of contracts with physical (spot and forward) and financial (options) settlement. PSO performance was evaluated by comparing it with a genetic algorithm-based approach. This model can be used by producers in deregulated electricity markets but can easily be adapted to load serving entities and retailers. Moreover, it can easily be adapted to the use of other type of contracts.

Probabilistic Stereo Egomotion Transform

In this paper we propose a novel fully probabilistic solution to the stereo egomotion estimation problem. We extend the notion of probabilistic correspondence to the stereo case which allow us to compute the whole 6D motion information in a probabilistic way. We compare the developed approach against other known state-of-the-art methods for stereo egomotion estimation, and the obtained results compare favorably both for the linear and angular velocities estimation.

All About Portugal - Website dedicado ao turismo externo em Portugal

Grande parte do tráfego online tem origem em páginas de resultados de motores de de pesquisa. Estes constituem hoje uma ferramenta fundamental de que os turistas se socorrem para pesquisar e filtrar a informação necessária ao planeamento das suas viagens, sendo, por isso, bastante tidos em conta pelas entidades ligadas ao turismo no momento da definição das suas estratégias de marketing. No presente documento é descrita a investigação feita em torno do modo de funcionamento do motor de pesquisa Google e das métricas que utiliza para avaliação de websites e páginas web. Desta investigação resultou a implementação de um website de conteúdos afetos ao mercado de turismo e viagens em Portugal, focado no mercado do turismo externo – All About Portugal. A implementação do website pretende provar, sustentando-se em orientações da área do SEO, que a propagação de conteúdos baseada unicamente nos motores de pesquisa é viável, confirmando, deste modo, a sua importância. Os dados de utilização desse mesmo website introduzem novos elementos que poderão servir de base a novos estudos.

Adaptive modeling and high quality spectral estimation for speech enhancement

In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.