Estudo e desenvolvimento de uma solução de monitorização estrutural em túneis baseada na tecnologia de redes de Bragg em fibra ótica

Ao longo dos últimos anos, vários esforços e estudos foram feitos com o objetivo de colocar a fibra ótica no mercado, como um sistema preferencial de monitorização das mais diversas obras de Engenharia. Os sensores baseados na tecnologia em fibra ótica apresentam vantagens reconhecidas pelos mais diversos especialistas, sendo atualmente reconhecida como uma das soluções mais eficazes. Na engenharia Civil, a monitorização das grandes obras tem ganho uma importância crescente. Neste contexto, a monitorização de convergências em túneis visa o controlo da respectiva integridade estrutural ao longo da construção e a exploração da obra. Atualmente a solução de monitorização estrutural de túneis utilizada pela FiberSensing é uma solução desenhada em conjunto com a EPOS e o Cegeo (IST), baseada em sensores de Bragg em Fibra Ótica: o SysTunnel. O objetivo do estudo de uma solução alternativa encontra-se no facto do SysTunnel apresentar algumas debilidades no algoritmo de cálculo, sendo para o seu cálculo necessário a introdução de um parâmetro relacionado com o solo envolvente do túnel, facto que introduz incertezas no cálculo das convergências. O presente relatório tem como finalidade documentar o estágio curricular realizado na FiberSensing, entre 01/02/2014 a 31/07/2014. Este estágio teve como objetivo o desenvolvimento de uma solução alternativa de monitorização estrutural baseada na tecnologia das redes de Bragg para a monitorização das convergências em túneis.

Estimation Models for the adoption and use of information technology: internet-related technologies at firm level in the Portuguese and European context

Dissertação apresentada como requisito parcial para obtenção do grau de Doutor em Gestão de Informação

A framework for robustness assessment in the context of corroded RC structures

Structural robustness is an emergent concept related to the structural response to damage. At the present time, robustness is not well defined and much controversy still remains around this subject. Even if robustness has seen growing interest as a consequence of catastrophic consequences due to extreme events, the fact is that the concept can also be very useful when considered on more probable exposure scenarios such as deterioration, among others. This paper intends to be a contribution to the definition of structural robustness, especially in the analysis of reinforced concrete structures subjected to corrosion. To achieve this, first of all, several proposed robustness definitions and indicators and misunderstood concepts will be analyzed and compared. From this point and regarding a concept that could be applied to most type of structures and dam-age scenarios, a robustness definition is proposed. To illustrate the proposed concept, an example of corroded reinforced concrete structures will be analyzed using nonlinear analysis numerical methods based on a contin-uum strong discontinuities approach and isotropic damage models for concrete. Finally the robustness of the presented example will be assessed.

Geodupa - a geography-driven partial membership algorithm

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

Efficient Legendre spectral tau algorithm for solving two-sided space-time Caputo fractional advection-dispersion equation

In this paper we present the operational matrices of the left Caputo fractional derivative, right Caputo fractional derivative and Riemann–Liouville fractional integral for shifted Legendre polynomials. We develop an accurate numerical algorithm to solve the two-sided space–time fractional advection–dispersion equation (FADE) based on a spectral shifted Legendre tau (SLT) method in combination with the derived shifted Legendre operational matrices. The fractional derivatives are described in the Caputo sense. We propose a spectral SLT method, both in temporal and spatial discretizations for the two-sided space–time FADE. This technique reduces the two-sided space–time FADE to a system of algebraic equations that simplifies the problem. Numerical results carried out to confirm the spectral accuracy and efficiency of the proposed algorithm. By selecting relatively few Legendre polynomial degrees, we are able to get very accurate approximations, demonstrating the utility of the new approach over other numerical methods.

Bringing Context Awareness to IoT-Based Wireless Sensor Networks

IEEE International Conference on Pervasive Computing and Communications (PerCom). 23 to 26, Mar, 2015, PhD Forum. Saint Louis, U.S.A..

Students’ reading behavior: digital vs. print preferences in portuguese context

The aim of this paper is to present the main Portuguese results from a multi-national study on reading format preferences and behaviors from undergraduate students from Polytechnic Institute of Porto (Portugal). For this purpose we apply an adaptation of the Academic Reading Questionnaire previously created by Mizrachi (2014). This survey instrument has 14 Likert-style statements regarding the format influence in the students reading behavior, including aspects such as ability to remember, feelings about access convenience, active engagement with the text by highlighting and annotating, and ability to review and concentrate on the text. The importance of the language and dimension of the text to determine the preference format is also inquired. Students are also asked about the electronic device they use to read digital documents. Finally, some demographic and academic data were gathered. The analysis of the results will be contextualized on a review of the literature concerning youngsters reading format preferences. The format (digital or print) in which a text is displayed and read can impact comprehension, which is an important information literacy skill. This is a quite relevant issue for class readings in academic context because it impacts learning. On the other hand, students preferences on reading formats will influence the use of library services. However, literature is not unanimous on this subject. Woody, Daniel and Baker (2010) concluded that the experience of reading is not the same in electronic or print context and that students prefer print books than e-books. This thesis is reinforced by Ji, Michaels and Waterman (2014) which report that among 101 undergraduates the large majority self-reported to read and learn more when they use printed format despite the fact that they prefer electronically supplied readings instead of those supplied in printed form. On the other side, Rockinson-Szapkiw, et al (2013) conducted a study were they demonstrate that e-textbook is as effective for learning as the traditional textbook and that students who choose e-textbook had significantly higher perceived learning than students who chose to use print textbooks.

Information professionals in business context: new professionals, old skills

This communication aims to present some reflections regarding the importance of information in organizational context, especially in business context. The ability to produce and to share expertise and knowledge among its employees is now a key factor in the success of any organization. However, it’s also true that workers are increasingly feeling that too much information can hurt their performance. The existence of skilled professionals able to organize, evaluate, select and disseminate information in organizations appears to be a prerequisite for success. The skills necessary for the formation of a professional devoted to the management of information and knowledge in the context of business organizations will be analysed. Then data collected in two focus group discussion with students from a graduate course in Business Information, from Polytechnic Institute of Porto, Portugal, a will be examined.

A Clinical Support System Based on Quality of Life Estimation

Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual's daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt's sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.

Negotiation context analysis in electricity markets

Contextualization is critical in every decision making process. Adequate responses to problems depend not only on the variables with direct influence on the outcomes, but also on a correct contextualization of the problem regarding the surrounding environment. Electricity markets are dynamic environments with increasing complexity, potentiated by the last decades' restructuring process. Dealing with the growing complexity and competitiveness in this sector brought the need for using decision support tools. A solid example is MASCEM (Multi-Agent Simulator of Competitive Electricity Markets), whose players' decisions are supported by another multiagent system – ALBidS (Adaptive Learning strategic Bidding System). ALBidS uses artificial intelligence techniques to endow market players with adaptive learning capabilities that allow them to achieve the best possible results in market negotiations. This paper studies the influence of context awareness in the decision making process of agents acting in electricity markets. A context analysis mechanism is proposed, considering important characteristics of each negotiation period, so that negotiating agents can adapt their acting strategies to different contexts. The main conclusion is that context-dependant responses improve the decision making process. Suiting actions to different contexts allows adapting the behaviour of negotiating entities to different circumstances, resulting in profitable outcomes.

A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context

In the traditional paradigm, the large power plants supply the reactive power required at a transmission level and the capacitors and transformer tap changer were also used at a distribution level. However, in a near future will be necessary to schedule both active and reactive power at a distribution level, due to the high number of resources connected in distribution levels. This paper proposes a new multi-objective methodology to deal with the optimal resource scheduling considering the distributed generation, electric vehicles and capacitor banks for the joint active and reactive power scheduling. The proposed methodology considers the minimization of the cost (economic perspective) of all distributed resources, and the minimization of the voltage magnitude difference (technical perspective) in all buses. The Pareto front is determined and a fuzzy-based mechanism is applied to present the best compromise solution. The proposed methodology has been tested in the 33-bus distribution network. The case study shows the results of three different scenarios for the economic, technical, and multi-objective perspectives, and the results demonstrated the importance of incorporating the reactive scheduling in the distribution network using the multi-objective perspective to obtain the best compromise solution for the economic and technical perspectives.

Six thinking hats: A novel metalearner for intelligent decision support in electricity markets

The energy sector has suffered a significant restructuring that has increased the complexity in electricity market players' interactions. The complexity that these changes brought requires the creation of decision support tools to facilitate the study and understanding of these markets. The Multiagent Simulator of Competitive Electricity Markets (MASCEM) arose in this context, providing a simulation framework for deregulated electricity markets. The Adaptive Learning strategic Bidding System (ALBidS) is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM, ALBidS considers several different strategic methodologies based on highly distinct approaches. Six Thinking Hats (STH) is a powerful technique used to look at decisions from different perspectives, forcing the thinker to move outside its usual way of thinking. This paper aims to complement the ALBidS strategies by combining them and taking advantage of their different perspectives through the use of the STH group decision technique. The combination of ALBidS' strategies is performed through the application of a genetic algorithm, resulting in an evolutionary learning approach.

Question order and context effects on multi-items scales questions

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Cutting path as a rural postman problem

The Rural Postman Problem (RPP) is a particular Arc Routing Problem (ARP) which consists of determining a minimum cost circuit on a graph so that a given subset of required edges is traversed. The RPP is an NP-hard problem with significant real-life applications. This paper introduces an original approach based on Memetic Algorithms - the MARP algorithm - to solve the RPP and, also deals with an interesting Industrial Application, which focuses on the path optimization for component cutting operations. Memetic Algorithms are a class of Metaheuristics which may be seen as a population strategy that involves cooperation and competition processes between population elements and integrates “social knowledge”, using a local search procedure. The MARP algorithm is tested with different groups of instances and the results are compared with those gathered from other publications. MARP is also used in the context of various real-life applications.

Decision-making process in radiology: the magnetic resonance example in the TA context

Based on the report for “Project IV” unit of the PhD programme on Technology Assessment (Doctoral Conference) at Universidade Nova de Lisboa (December 2011). This thesis research has the supervision of António Moniz (FCT-UNL and ITAS-KIT) and Michael Decker (Karlsruhe Institute of Technology-ITAS). Other members of the thesis committee are Carlos Alberto da Silva (University of Évora), José Maria de Albuquerque (Institute of Welding and Quality), Lotte Steuten (University of Twente), Mário Forjaz Secca (FCT-UNL) and Nelson Chibeles Martins (FCT-UNL).