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.

In situ measured cross section geometry of old timber structures and its influence on structural safety

Old timber structures may show significant variation in the cross section geometry along the same element, as a result of both construction methods and deterioration. As consequence, the definition of the geometric parameters in situ may be both time consuming and costly. This work presents the results of inspections carried out in different timber structures. Based on the obtained results, different simplified geometric models are proposed in order to efficiently model the geometry variations found. Probabilistic modelling techniques are also used to define safety parameters of existing timber structures, when subjected to dead and live loads, namely self-weight and wind actions. The parameters of the models have been defined as probabilistic variables, and safety of a selected case study was assessed using the Monte Carlo simulation technique. Assuming a target reliability index, a model was defined for both the residual cross section and the time dependent deterioration evolution. As a consequence, it was possible to compute probabilities of failure and reliability indices, as well as, time evolution deterioration curves for this structure. The results obtained provide a proposal for definition of the cross section geometric parameters of existing timber structures with different levels of decay, using a simplified probabilistic geometry model and considering a remaining capacity factor for the decayed areas. This model can be used for assessing the safety of the structure at present and for predicting future performance.

Framework development for providing accessibility to qualitative spatial calculi

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Stratigraphic interpretation of Well-Log data of the Athabasca Oil Sands of Alberta Canada through Pattern recognition and Artificial Intelligence

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Human activity recognition for an intelligent knee orthosis

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Developing Young Learners’ Logical/Deductive Thinking Skills and Second Language Skills through a CLIL approach

Trabalho de Projecto apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Teaching English as a Second / Foreign Language.

Intention recognition, commitment and their roles in the evolution of cooperation

Dissertação para obtenção do Grau de Doutor em Informática

Electron impact ionization cross sections and analysis of X-ray spectra

A thesis submitted for the degree of Ph. D. in Physics

Influenza A(H1N1)pdm09 Resistance and Cross-Decreased Susceptibility to Oseltamivir and Zanamivir Antiviral Drugs

Neuraminidase inhibitors (NAIs) oseltamivir and zanamivir are currently the only effective antiviral drugs available worldwide for the management of influenza. The potential development of resistance is continually threatening their use, rationalizing and highlighting the need for a close and sustained evaluation of virus susceptibility. This study aimed to analyze and characterize the phenotypic and genotypic NAIs susceptibility profiles of A(H1N1)pdm09 viruses circulating in Portugal from 2009 to 2010/2011. A total of 144 cases of A(H1N1)pdm09 virus infection from community and hospitalized patients were studied, including three suspected cases of clinical resistance to oseltamivir. Oseltamivir resistance was confirmed for two of the suspected cases. Neuraminidase (NA) H275Y resistant marker was found in viruses from both cases but for one it was only present in 26.2% of virus population, raising questions about the minimal percentage of resistant virus that should be considered relevant. Cross-decreased susceptibility to oseltamivir and zanamivir (2-4 IC50 fold-change) was detected on viruses from two potentially linked community patients from 2009. Both viruses harbored the NA I223V mutation. NA Y155H mutation was found in 18 statistical non-outlier viruses from 2009, having no impact on virus susceptibility. The mutations at NA N369K and V241I may have contributed to the significantly higher baseline IC50 value obtained to oseltamivir for 2010/2011 viruses, compared to viruses from the pandemic period. These results may contribute to a better understanding of the relationship between phenotype and genotype, which is currently challenging, and to the global assessment of A(H1N1)pdm09 virus susceptibility profile and baseline level to NAIs.

Determinants of venture capital and private equity investments in renewable energy: A cross-country study

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

A look into the cross-section of industry stock returns

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics