Azorean Agriculture Efficiency by PAR

Copyright © 2013 Springer Netherlands.

Gestão e monitorização de uma rede departamental: um caso de estudo

Mestrado em Engenharia Electrotécnica e de Computadores

Aplicação web para tratamento estatístico de dados de teste

Mestrado em Engenharia Electrotécnica e de Computadores

Eficiência energética e a queima de combustíveis limpos

Mestrado em Engenharia Química

Recuperação do isopentano da gasolina leve

Mestrado em Engenharia Química

Open-source software in operations research in engineering teaching

ENEGI 2013: Atas do 2º Encontro Nacional de Engenharia e Gestão Industrial, Universidade de Aveiro, 17 e 18 de maio de 2013, Aveiro, Portugal.

Towards an Academic Social Network for Bologna Process

The Bologna Process aimed to build a European Higher Education Area promoting student's mobility. The adoption of Bologna Declaration directives requires a self management distributed approach to deal with student's mobility, allowing frequent updates in institutions rules or legislation. This paper suggests a computational system architecture, which follows a social network design. A set of structured annotations is proposed in order to organize the user's information. For instance, when the user is a student its annotations are organized into an academic record. The academic record data is used to discover interests, namely mobility interests, among students that belongs the academic network. These ideas have been applied into a demonstrator that includes a mobility simulator to compare and show the student's academic evolution.

A student personal system for Bologna process mobility

The Bologna Process aimed to build a European Higher Education Area with the objective of promoting students mobility. The adoption of Bologna Declaration directives requires a decentralized approach that accelerates student's mobility, based on frequently updated legislation. This paper proposes a student personal system to manage student's academic information. This system is supported by a flexible model that integrates, for instance, knowledge about the student attended courses or about a course that the student wishes to apply. Essentially, this model holds a (i) Student's Academic Record with skills acquired in academic course units, professional experience or training and an (ii) Individual Studies Plan, which places the student in a particular (iii) Course Plan setting the curricular structure that the student wishes to apply.

Preparatory and field work phases in the qualitative empirical research process in management: the case studies approach

Purpose: The aim of this paper is to promote qualitative methodology within the scientific community of management. The specific objective is oriented to propose an empirical research process based on case study method. This is to ensure rigor in the empirical research process, that future research may follow a similar procedure to that is proposed. Design/methodology/approach: Following a qualitative methodological approach, we propose a research process that develops according to four phases, each with several stages. This study analyses the preparatory and field work phases and their stages. Findings: The paper shows the influence that case studies have on qualitative empirical research process in management. Originality/value:. Case study method assumes an important role within qualitative research by allowing for the study and analysis of certain types of phenomena that occur inside organisations, and in respect of which quantitative studies cannot provide an answer.

Estudo e análise de soluções de acessos Wimax partilhados em cenários residenciais

Mestrado em Engenharia Electrotécnica e de Computadores

Aplicação de algoritmos genéticos para sintonia de controladores

Mestrado em Engenharia Electrotécnica e de Computadores

Distributed process execution in collaborative networks

Processes are a central entity in enterprise collaboration. Collaborative processes need to be executed and coordinated in a distributed Computational platform where computers are connected through heterogeneous networks and systems. Life cycle management of such collaborative processes requires a framework able to handle their diversity based on different computational and communication requirements. This paper proposes a rational for such framework, points out key requirements and proposes it strategy for a supporting technological infrastructure. Beyond the portability of collaborative process definitions among different technological bindings, a framework to handle different life cycle phases of those definitions is presented and discussed. (c) 2007 Elsevier Ltd. All rights reserved.

Mapping multi-species habitat use for marine conservation planning

Tese de Doutoramento, Ciências do Mar (Biologia Marinha)

Machine Learning Algorithms at Myocardial Perfusion Imaging - a Preliminary Study

Introduction: A major focus of data mining process - especially machine learning researches - is to automatically learn to recognize complex patterns and help to take the adequate decisions strictly based on the acquired data. Since imaging techniques like MPI – Myocardial Perfusion Imaging on Nuclear Cardiology, can implicate a huge part of the daily workflow and generate gigabytes of data, there could be advantages on Computerized Analysis of data over Human Analysis: shorter time, homogeneity and consistency, automatic recording of analysis results, relatively inexpensive, etc.Objectives: The aim of this study relates with the evaluation of the efficacy of this methodology on the evaluation of MPI Stress studies and the process of decision taking concerning the continuation – or not – of the evaluation of each patient. It has been pursued has an objective to automatically classify a patient test in one of three groups: “Positive”, “Negative” and “Indeterminate”. “Positive” would directly follow to the Rest test part of the exam, the “Negative” would be directly exempted from continuation and only the “Indeterminate” group would deserve the clinician analysis, so allowing economy of clinician’s effort, increasing workflow fluidity at the technologist’s level and probably sparing time to patients. Methods: WEKA v3.6.2 open source software was used to make a comparative analysis of three WEKA algorithms (“OneR”, “J48” and “Naïve Bayes”) - on a retrospective study using the comparison with correspondent clinical results as reference, signed by nuclear cardiologist experts - on “SPECT Heart Dataset”, available on University of California – Irvine, at the Machine Learning Repository. For evaluation purposes, criteria as “Precision”, “Incorrectly Classified Instances” and “Receiver Operating Characteristics (ROC) Areas” were considered. Results: The interpretation of the data suggests that the Naïve Bayes algorithm has the best performance among the three previously selected algorithms. Conclusions: It is believed - and apparently supported by the findings - that machine learning algorithms could significantly assist, at an intermediary level, on the analysis of scintigraphic data obtained on MPI, namely after Stress acquisition, so eventually increasing efficiency of the entire system and potentially easing both roles of Technologists and Nuclear Cardiologists. In the actual continuation of this study, it is planned to use more patient information and significantly increase the population under study, in order to allow improving system accuracy.

Estudo da eficiência de sistemas fotovoltaicos

Mestrado em Engenharia Química. Ramo optimização energética na indústria química