External and internal dynamics in the EU's counter-terrorism policy: a political and legal analysis

Tese de Doutoramento em Ciência Política e Relações Internacionais

Development of an intelligent earthwork optimization system

Tese de Doutoramento em Engenharia Civil.

Estimativa dos parâmetros de compactação de solos usando técnicas de data mining

Dissertação de mestrado integrado em Engenharia Civil

Using mouse dynamics to assess stress during online exams

"Lecture notes in computer science series", ISSN 0302-9743, vol. 9121

Fundamental concepts in multibody dynamics

In this chapter, the fundamental ingredients related to formulation of the equations of motion for multibody systems are described. In particular, aspects such as degrees of freedom, types of coordinates, basic kinematics joints and types of analysis in multibody systems are briefly characterized. Illustrative examples of application are also presented to better clarify the fundamental issues for spatial rigid multibody systems, which are of crucial importance in the formulation development of mathematical models of mechanical systems, as well as its computational implementation.

Introduction [to Contact force models for multibody dynamics]

"Series: Solid mechanics and its applications, vol. 226"

Numerical methods in multibody system dynamics

"Series: Solid mechanics and its applications, vol. 226"

Contact force models for multibody dynamics

"Series: Solid mechanics and its applications, vol. 226"

On the frictional contacts in multibody system dynamics

"Series title: Computational methods in applied sciences, ISSN1871-3033, vol. 42"

The electoral dynamics of human development

This paper analyses the impact of elections on the dynamics of human development in a panel of 82 countries over the period 1980-2013. The incidence of partisan and political support effects is also taken into account. A GMM estimator is employed in the empirical analysis and the results point out to the presence of an electoral cycle in the growth rate of human development. Majority governments also influence it, but no clear evidence is found regarding partisan effects. The electoral cycles have proved to be stronger in non-OECD countries, in countries with less frequent elections, with lower levels of income and human development, in presidential and non-plurality systems and in proportional representation regimes. They have also become more intense in this millennium.

Role of sirtuin 3 on mitochondrial dynamics in Huntington's disease striatal cells

Dissertação de mestrado em Genética Molecular

Pervasive decision support to predict football corners and goals by means of data mining

Football is considered nowadays one of the most popular sports. In the betting world, it has acquired an outstanding position, which moves millions of euros during the period of a single football match. The lack of profitability of football betting users has been stressed as a problem. This lack gave origin to this research proposal, which it is going to analyse the possibility of existing a way to support the users to increase their profits on their bets. Data mining models were induced with the purpose of supporting the gamblers to increase their profits in the medium/long term. Being conscience that the models can fail, the results achieved by four of the seven targets in the models are encouraging and suggest that the system can help to increase the profits. All defined targets have two possible classes to predict, for example, if there are more or less than 7.5 corners in a single game. The data mining models of the targets, more or less than 7.5 corners, 8.5 corners, 1.5 goals and 3.5 goals achieved the pre-defined thresholds. The models were implemented in a prototype, which it is a pervasive decision support system. This system was developed with the purpose to be an interface for any user, both for an expert user as to a user who has no knowledge in football games.

Towards a pervasive data mining engine: architecture overview

Current data mining engines are difficult to use, requiring optimizations by data mining experts in order to provide optimal results. To solve this problem a new concept was devised, by maintaining the functionality of current data mining tools and adding pervasive characteristics such as invisibility and ubiquity which focus on their users, providing better ease of use and usefulness, by providing autonomous and intelligent data mining processes. This article introduces an architecture to implement a data mining engine, composed by four major components: database; Middleware (control); Middleware (processing); and interface. These components are interlinked but provide independent scaling, allowing for a system that adapts to the user’s needs. A prototype has been developed in order to test the architecture. The results are very promising and showed their functionality and the need for further improvements.

Predicting triage waiting time in maternity emergency care by means of data mining

Healthcare organizations often benefit from information technologies as well as embedded decision support systems, which improve the quality of services and help preventing complications and adverse events. In Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto (CHP), an intelligent pre-triage system is implemented, aiming to prioritize patients in need of gynaecology and obstetrics care in two classes: urgent and consultation. The system is designed to evade emergency problems such as incorrect triage outcomes and extensive triage waiting times. The current study intends to improve the triage system, and therefore, optimize the patient workflow through the emergency room, by predicting the triage waiting time comprised between the patient triage and their medical admission. For this purpose, data mining (DM) techniques are induced in selected information provided by the information technologies implemented in CMIN. The DM models achieved accuracy values of approximately 94% with a five range target distribution, which not only allow obtaining confident prediction models, but also identify the variables that stand as direct inducers to the triage waiting times.