Comportamento de consumo, elites sociais e moda : contributo para a consolidação disciplinar dos estudos de tendências

Tese de doutoramento, Estudos de Literatura e de Cultura (Cultura e Comunicação), Universidade de Lisboa, Faculdade de Letras, 2015

Effectiveness of resilience assessment tools in different case studies

Tese de doutoramento, Biologia (Biologia Marinha e Aquacultura), Universidade de Lisboa, Faculdade de Ciências, 2015

A review of dynamic Bayesian network techniques with applications in healthcare risk modelling

Coping with an ageing population is a major concern for healthcare organisations around the world. The average cost of hospital care is higher than social care for older and terminally ill patients. Moreover, the average cost of social care increases with the age of the patient. Therefore, it is important to make efficient and fair capacity planning which also incorporates patient centred outcomes. Predictive models can provide predictions which their accuracy can be understood and quantified. Predictive modelling can help patients and carers to get the appropriate support services, and allow clinical decision-makers to improve care quality and reduce the cost of inappropriate hospital and Accident and Emergency admissions. The aim of this study is to provide a review of modelling techniques and frameworks for predictive risk modelling of patients in hospital, based on routinely collected data such as the Hospital Episode Statistics database. A number of sub-problems can be considered such as Length-of-Stay and End-of-Life predictive modelling. The methodologies in the literature are mainly focused on addressing the problems using regression methods and Markov models, and the majority lack generalisability. In some cases, the robustness, accuracy and re-usability of predictive risk models have been shown to be improved using Machine Learning methods. Dynamic Bayesian Network techniques can represent complex correlations models and include small probabilities into the solution. The main focus of this study is to provide a review of major time-varying Dynamic Bayesian Network techniques with applications in healthcare predictive risk modelling.

Self-optimization module for scheduling using case-based reasoning

Metaheuristics performance is highly dependent of the respective parameters which need to be tuned. Parameter tuning may allow a larger flexibility and robustness but requires a careful initialization. The process of defining which parameters setting should be used is not obvious. The values for parameters depend mainly on the problem, the instance to be solved, the search time available to spend in solving the problem, and the required quality of solution. This paper presents a learning module proposal for an autonomous parameterization of Metaheuristics, integrated on a Multi-Agent System for the resolution of Dynamic Scheduling problems. The proposed learning module is inspired on Autonomic Computing Self-Optimization concept, defining that systems must continuously and proactively improve their performance. For the learning implementation it is used Case-based Reasoning, which uses previous similar data to solve new cases. In the use of Case-based Reasoning it is assumed that similar cases have similar solutions. After a literature review on topics used, both AutoDynAgents system and Self-Optimization module are described. Finally, a computational study is presented where the proposed module is evaluated, obtained results are compared with previous ones, some conclusions are reached, and some future work is referred. It is expected that this proposal can be a great contribution for the self-parameterization of Metaheuristics and for the resolution of scheduling problems on dynamic environments.

Transient analysis of variable-speed wind turbines at wind speed disturbances and a pitch control malfunction

As wind power generation undergoes rapid growth, new technical challenges emerge: dynamic stability and power quality. The influence of wind speed disturbances and a pitch control malfunction on the quality of the energy injected into the electric grid is studied for variable-speed wind turbines with different power-electronic converter topologies. Additionally, a new control strategy is proposed for the variable-speed operation of wind turbines with permanent magnet synchronous generators. The performance of disturbance attenuation and system robustness is ascertained. Simulation results are presented and conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

GuideMe: service for consulting, publication and recommendation of touristic locations

Trabalho de Projeto realizado para obtenção do grau de Mestre em Engenharia Informática e de Computadores

Diagnóstico de avarias em motores elétricos

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Development of triplet repeat primed PCR (TP-PCR) technique as a support of molecular test in Machado-Joseph disease

Dissertação de Mestrado, Ciências Biomédicas, 3 de Fevereiro de 2016, Universidade dos Açores.

O impacto da implementação do Basel III no capital dos bancos portugueses

Este trabalho é uma análise dos efeitos da implementação das últimas recomendações do Basel Committee on Banking Supervision (BCBS) também conhecidas como o Basel III de 2010 que deverão ser faseadamente implementadas desde 1 de Janeiro de 2013 até 1 de Janeiro de 2019, no capital próprio dos bancos Portugueses. Neste trabalho assume-se que os ativos pesados pelo risco de 2012 mantêm-se constantes e o capital terá de ser aumentado segundo as recomendações ano após ano até ao fim de 2018. Com esta análise, pretende-se entender o nível de robustez do capital próprio dos bancos Portugueses e se os mesmos têm capital e reservas suficientes para satisfazer as recomendações de capital mínimo sugeridas pelo BCBS ou caso contrário, se necessitarão de novas injeções de capital ou terão de reduzir a sua atividade económica. O Basel III ainda não foi implementado em Portugal, pois a União Europeia está no processo de desenvolvimento e implementação do Credit Requirement Directive IV (CRD IV) que é uma recomendação que todos os bancos centrais dos países da zona Euro deverão impor aos respetivos bancos. Esta diretiva da União Europeia é baseada totalmente nas recomendações do Basel III e deverá ser implementada em 2014 ou nos anos seguintes. Até agora, os bancos Portugueses seguem um sistema com base no aviso 6/2010 do Banco de Portugal que recomenda o cálculo dos rácios core tier 1, tier 1 e tier 2 usando o método notações internas (IRB) de avaliação da exposição do banco aos riscos de crédito, operacional, etc. e onde os ativos ponderados pelo risco são calculados como 12,5 vezes o valor dos requisitos totais de fundos calculados pelo banco. Este método é baseado nas recomendações do Basel II que serão substituídas pelo Basel III. Dado que um dos principais motivos para a crise económica e financeira que assolou o mundo em 2007 foi a acumulação de alavancagem excessiva e gradual erosão da qualidade da base do capital próprio dos bancos, é importante analisar a posição dos bancos Portugueses, que embora não sejam muito grandes a nível global, controlam a economia do país. Espera-se que com a implementação das recomendações do Basel III não haja no futuro uma repetição dos choques sistémicos de 2007. Os resultados deste estudo usando o método padrão recomendado pelo BCBS mostram que de catorze bancos Portugueses incluídos neste estudo, apenas seis (BES, Montepio, Finantia, BIG, Invest e BIC) conseguem enquadrar nas recomendações mínimas do Basel III até 1-1- 2019 e alguns outros estão marginalmente abaixo dos rácios mínimos (CGD, Itaú e Crédito Agrícola).

A literature review on the optimization of legged robots

Over the last two decades the research and development of legged locomotion robots has grown steadily. Legged systems present major advantages when compared with ‘traditional’ vehicles, because they allow locomotion in inaccessible terrain to vehicles with wheels and tracks. However, the robustness of legged robots, and especially their energy consumption, among other aspects, still lag behind mechanisms that use wheels and tracks. Therefore, in the present state of development, there are several aspects that need to be improved and optimized. Keeping these ideas in mind, this paper presents the review of the literature of different methods adopted for the optimization of the structure and locomotion gaits of walking robots. Among the distinct possible strategies often used for these tasks are referred approaches such as the mimicking of biological animals, the use of evolutionary schemes to find the optimal parameters and structures, the adoption of sound mechanical design rules, and the optimization of power-based indexes.

Economic, environmental and mixed objective functions in non-linear process optimization using simulated annealing and tabu search

Screening of topologies developed by hierarchical heuristic procedures can be carried out by comparing their optimal performance. In this work we will be exploiting mono-objective process optimization using two algorithms, simulated annealing and tabu search, and four different objective functions: two of the net present value type, one of them including environmental costs and two of the global potential impact type. The hydrodealkylation of toluene to produce benzene was used as case study, considering five topologies with different complexities mainly obtained by including or not liquid recycling and heat integration. The performance of the algorithms together with the objective functions was observed, analyzed and discussed from various perspectives: average deviation of results for each algorithm, capacity for producing high purity product, screening of topologies, objective functions robustness in screening of topologies, trade-offs between economic and environmental type objective functions and variability of optimum solutions.

Application-specific modified particle swarm optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

Despacho económico de unidades com funções de custo não convexas usando enxames

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

Hybrid adaptive control of a dragonfly model

Dragonflies show unique and superior flight performances than most of other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, it is presented an adaptive scheme controlling a nonlinear model inspired in a dragonfly-like robot. It is proposed a hybrid adaptive (HA) law for adjusting the parameters analyzing the tracking error. At the current stage of the project it is considered essential the development of computational simulation models based in the dynamics to test whether strategies or algorithms of control, parts of the system (such as different wing configurations, tail) as well as the complete system. The performance analysis proves the superiority of the HA law over the direct adaptive (DA) method in terms of faster and improved tracking and parameter convergence.

An approach for reliability-based robust design optimisation of angle-ply composites

Variations of manufacturing process parameters and environmental aspects may affect the quality and performance of composite materials, which consequently affects their structural behaviour. Reliability-based design optimisation (RBDO) and robust design optimisation (RDO) searches for safe structural systems with minimal variability of response when subjected to uncertainties in material design parameters. An approach that simultaneously considers reliability and robustness is proposed in this paper. Depending on a given reliability index imposed on composite structures, a trade-off is established between the performance targets and robustness. Robustness is expressed in terms of the coefficient of variation of the constrained structural response weighted by its nominal value. The Pareto normed front is built and the nearest point to the origin is estimated as the best solution of the bi-objective optimisation problem.