Protesting or justifying? A latent class model for contingent valuation with attitudinal data

This article develops a latent class model for estimating willingness-to-pay for public goods using simultaneously contingent valuation (CV) and attitudinal data capturing protest attitudes related to the lack of trust in public institutions providing those goods. A measure of the social cost associated with protest responses and the consequent loss in potential contributions for providing the public good is proposed. The presence of potential justification biases is further considered, that is, the possibility that for psychological reasons the response to the CV question affects the answers to the attitudinal questions. The results from our empirical application suggest that psychological factors should not be ignored in CV estimation for policy purposes, allowing for a correct identification of protest responses.

Hub-and-spoke Interoperability: an out of the skies approach for large-scale data interoperability

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores

Corruption and Education: Empirical evidence from cross-country micro-data

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

Spatial Patterns and Irregularities of the electoral data: general elections in Canada

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

Vodafone - Kabel Deutschland Merger

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

Collecting data for indoor mapping of the university of Münster via a location based game

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

Multivariate analysis applied to clinical analysis data

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

Data fusion with computational intelligence techniques: a case study of fuzzy inference for terrain assessment

Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Evaluation and optimization of a session-based middleware for data management

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

A system’s approach to cache hierarchy-aware decomposition of data-parallel computations

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Combining WLAN fingerprint-based localization with sensor data for indoor navigation using mobile devices

This project proposes an approach for supporting Indoor Navigation Systems using Pedestrian Dead Reckoning-based methods and by analyzing motion sensor data available in most modern smartphones. Processes suggested in this investigation are able to calculate the distance traveled by a user while he or she is walking. WLAN fingerprint- based navigation systems benefit from the processes followed in this research and results achieved to reduce its workload and improve its positioning estimations.

Complex networks and data mining: toward a new perspective for the understanding of complex systems

Complex systems, i.e. systems composed of a large set of elements interacting in a non-linear way, are constantly found all around us. In the last decades, different approaches have been proposed toward their understanding, one of the most interesting being the Complex Network perspective. This legacy of the 18th century mathematical concepts proposed by Leonhard Euler is still current, and more and more relevant in real-world problems. In recent years, it has been demonstrated that network-based representations can yield relevant knowledge about complex systems. In spite of that, several problems have been detected, mainly related to the degree of subjectivity involved in the creation and evaluation of such network structures. In this Thesis, we propose addressing these problems by means of different data mining techniques, thus obtaining a novel hybrid approximation intermingling complex networks and data mining. Results indicate that such techniques can be effectively used to i) enable the creation of novel network representations, ii) reduce the dimensionality of analyzed systems by pre-selecting the most important elements, iii) describe complex networks, and iv) assist in the analysis of different network topologies. The soundness of such approach is validated through different validation cases drawn from actual biomedical problems, e.g. the diagnosis of cancer from tissue analysis, or the study of the dynamics of the brain under different neurological disorders.

A DSL for querying building data streams of energy, eeather and occupation data

The superfluous consumption of energy is faced by the modern society as a Socio-Economical and Environmental problem of the present days. This situation is worsening given that it is becoming clear that the tendency is to increase energy price every year. It is also noticeable that people, not necessarily proficient in technology, are not able to know where savings can be achieved, due to the absence of accessible awareness mechanisms. One of the home user concerns is to balance the need of reducing energy consumption, while producing the same activity with all the comfort and work efficiency. The common techniques to reduce the consumption are to use a less wasteful equipment, altering the equipment program to a more economical one or disconnecting appliances that are not necessary at the moment. However, there is no direct feedback from this performed actions, which leads to the situation where the user is not aware of the influence that these techniques have in the electrical bill. With the intension to give some control over the home consumption, Energy Management Systems (EMS) were developed. These systems allow the access to the consumption information and help understanding the energy waste. However, some studies have proven that these systems have a clear mismatch between the information that is presented and the one the user finds useful for his daily life, leading to demotivation of use. In order to create a solution more oriented towards the user’s demands, a specially tailored language (DSL) was implemented. This solution allows the user to acquire the information he considers useful, through the construction of questions about his energy consumption. The development of this language, following the Model Driven Development (MDD) approach, took into consideration the ideas of facility managers and home users in the phases of design and validation. These opinions were gathered through meetings with experts and a survey, which was conducted to the purpose of collecting statistics about what home users want to know.

Integrated data model and DSL modifications

Companies are increasingly more and more dependent on distributed web-based software systems to support their businesses. This increases the need to maintain and extend software systems with up-to-date new features. Thus, the development process to introduce new features usually needs to be swift and agile, and the supporting software evolution process needs to be safe, fast, and efficient. However, this is usually a difficult and challenging task for a developer due to the lack of support offered by programming environments, frameworks, and database management systems. Changes needed at the code level, database model, and the actual data contained in the database must be planned and developed together and executed in a synchronized way. Even under a careful development discipline, the impact of changing an application data model is hard to predict. The lifetime of an application comprises changes and updates designed and tested using data, which is usually far from the real, production, data. So, coding DDL and DML SQL scripts to update database schema and data, is the usual (and hard) approach taken by developers. Such manual approach is error prone and disconnected from the real data in production, because developers may not know the exact impact of their changes. This work aims to improve the maintenance process in the context of Agile Platform by Outsystems. Our goal is to design and implement new data-model evolution features that ensure a safe support for change and a sound migration process. Our solution includes impact analysis mechanisms targeting the data model and the data itself. This provides, to developers, a safe, simple, and guided evolution process.

Sistema de deteção de eventos adversos baseado num data warehouse

RESUMO - A Segurança do Doente tem assumido uma relevância crescente nas organizações de saúde, resultado da divulgação de diversos estudos que revelaram a magnitude deste problema e simultaneamente, de uma maior pressão por parte da opinião pública e da comunicação social. Este estudo pretende desenvolver e avaliar a performance de um sistema eletrónico de deteção de eventos adversos, baseado num Data Warehouse, por comparação com os resultados obtidos pela metodologia tradicional de revisão dos registos clínicos. O objetivo principal do trabalho consistiu em identificar um conjunto de triggers / indicadores de alerta que permitam detetar potenciais eventos adversos mais comuns. O sistema desenvolvido apresentou um Valor Preditivo Positivo de 18.2%, uma sensibilidade de 65.1% e uma especificidade de 68.6%, sendo constituído por nove indicadores baseados em informação clínica e 445 códigos do ICD-9-CM, relativos a diagnósticos e procedimentos. Apesar de terem algumas limitações, os sistemas eletrónicos de deteção de eventos adversos apresentam inúmeras potencialidades, nomeadamente a utilização em tempo real e em complemento a metodologias já existentes. Considerando a importância da problemática em análise e a necessidade de aprofundar os resultados obtidos neste trabalho de projeto, seria relevante a sua extensão a um universo mais alargado de instituições hospitalares, estando a sua replicabilidade facilitada, uma vez que o Data Warehouse tem por base um conjunto de aplicações disseminadas a nível nacional. O desenvolvimento e a consolidação dos sistemas eletrónicos de deteção de eventos adversos constitui inegavelmente uma área de futuro, com reflexos ao nível da melhoria da informação existente nas organizações e que contribuirá decisivamente para a melhoria dos cuidados de saúde prestados aos doentes.