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 with accelerometry: novel time and frequency features

Human Activity Recognition systems require objective and reliable methods that can be used in the daily routine and must offer consistent results according with the performed activities. These systems are under development and offer objective and personalized support for several applications such as the healthcare area. This thesis aims to create a framework for human activities recognition based on accelerometry signals. Some new features and techniques inspired in the audio recognition methodology are introduced in this work, namely Log Scale Power Bandwidth and the Markov Models application. The Forward Feature Selection was adopted as the feature selection algorithm in order to improve the clustering performances and limit the computational demands. This method selects the most suitable set of features for activities recognition in accelerometry from a 423th dimensional feature vector. Several Machine Learning algorithms were applied to the used accelerometry databases – FCHA and PAMAP databases - and these showed promising results in activities recognition. The developed algorithm set constitutes a mighty contribution for the development of reliable evaluation methods of movement disorders for diagnosis and treatment applications.

Mathematical and numerical methods for inverse problems using fundamental solutions techniques

Fundação para a Ciência e a Tecnologia - SFRH/BD/27914/2006

Chaînes opératoires and resource-exploitation strategies in chimpanzee (Pan troglodytes) nut cracking

Journal of Human Evolution, V. 55, pp. 148-163

Extremum estimators and stochastic optimization methods

Submitted in partial fulfillment for the Requirements for the Degree of PhD in Mathematics, in the Speciality of Statistics in the Faculdade de Ciências e Tecnologia

Algorithms for information extraction and signal annotation on long-term biosignals using clustering techniques

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

What is the best accounting policy for gains and losses in pensions?

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

Time series morphological analysis applied to biomedical signals events detection

Dissertation submitted in the fufillment of the requirements for the Degree of Master in Biomedical Engineering

Introduction: digital methods and tools for historical research

As an introduction to a series of articles focused on the exploration of particular tools and/or methods to bring together digital technology and historical research, the aim of this paper is mainly to highlight and discuss in what measure those methodological approaches can contribute to improve analytical and interpretative capabilities available to historians. In a moment when the digital world present us with an ever-increasing variety of tools to perform extraction, analysis and visualization of large amounts of text, we thought it would be relevant to bring the digital closer to the vast historical academic community. More than repeating an idea of digital revolution introduced in the historical research, something recurring in the literature since the 1980s, the aim was to show the validity and usefulness of using digital tools and methods, as another set of highly relevant tools that the historians should consider. For this several case studies were used, combining the exploration of specific themes of historical knowledge and the development or discussion of digital methodologies, in order to highlight some changes and challenges that, in our opinion, are already affecting the historians' work, such as a greater focus given to interdisciplinarity and collaborative work, and a need for the form of communication of historical knowledge to become more interactive.