Dynamic power- and failure-aware cloud resources allocation for Sets of independent tasks

Cloud computing is increasingly being adopted in different scenarios, like social networking, business applications, scientific experiments, etc. Relying in virtualization technology, the construction of these computing environments targets improvements in the infrastructure, such as power-efficiency and fulfillment of users’ SLA specifications. The methodology usually applied is packing all the virtual machines on the proper physical servers. However, failure occurrences in these networked computing systems can induce substantial negative impact on system performance, deviating the system from ours initial objectives. In this work, we propose adapted algorithms to dynamically map virtual machines to physical hosts, in order to improve cloud infrastructure power-efficiency, with low impact on users’ required performance. Our decision making algorithms leverage proactive fault-tolerance techniques to deal with systems failures, allied with virtual machine technology to share nodes resources in an accurately and controlled manner. The results indicate that our algorithms perform better targeting power-efficiency and SLA fulfillment, in face of cloud infrastructure failures.

Adaptive learning in agents behaviour: a framework for electricity markets simulation

Electricity markets are complex environments with very particular characteristics. A critical issue regarding these specific characteristics concerns the constant changes they are subject to. This is a result of the electricity markets’ restructuring, which was performed so that the competitiveness could be increased, but it also had exponential implications in the increase of the complexity and unpredictability in those markets scope. The constant growth in markets unpredictability resulted in an amplified need for market intervenient entities in foreseeing market behaviour. The need for understanding the market mechanisms and how the involved players’ interaction affects the outcomes of the markets, contributed to the growth of usage of simulation tools. Multi-agent based software is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This dissertation presents ALBidS – Adaptive Learning strategic Bidding System, a multiagent system created to provide decision support to market negotiating players. This system is integrated with the MASCEM electricity market simulator, so that its advantage in supporting a market player can be tested using cases based on real markets’ data. ALBidS considers several different methodologies based on very distinct approaches, to provide alternative suggestions of which are the best actions for the supported player to perform. The approach chosen as the players’ actual action is selected by the employment of reinforcement learning algorithms, which for each different situation, simulation circumstances and context, decides which proposed action is the one with higher possibility of achieving the most success. Some of the considered approaches are supported by a mechanism that creates profiles of competitor players. These profiles are built accordingly to their observed past actions and reactions when faced with specific situations, such as success and failure. The system’s context awareness and simulation circumstances analysis, both in terms of results performance and execution time adaptation, are complementary mechanisms, which endow ALBidS with further adaptation and learning capabilities.

O Combate à fraude e evasão fiscais: a atuação da administração tributária e a avaliação dos resultados obtidos

Dissertação para obtenção do Grau de Mestre em Auditoria Orientação científica do Professor Coordenador Rodrigo Mário Oliveira Carvalho

A relação terapeuta-cliente: na perspectiva do cliente

O presente estudo resulta de uma crescente preocupação e percepção da importância da relação terapeuta-cliente e procura compreender a perspectiva do cliente e a forma como este sente e vive essa relação ao longo de todo o seu processo terapêutico. O estudo realizado, de natureza qualitativa e de carácter exploratório, visa sobretudo analisar a influência da relação terapeuta-cliente na perspectiva do cliente, identificar e descrever os fatores que a influenciam e perceber a mais-valia desta relação ao longo do processo terapêutico. Para tal, foram entrevistadas dezanove pessoas que estão a receber tratamento de terapia ocupacional. Para a recolha dos dados foi aplicada a entrevista semi-estruturada por se pretender um contributo mais envolvente, particularizado e subjetivo dos clientes. Através da realização do estudo e de acordo com a perspetiva dos clientes entrevistados, concluiu-se que a capacidade do terapeuta em construir e estabelecer um vínculo com o cliente ditará grande parte do sucesso ou insucesso do processo terapêutico. Porém, tão importante como formar e estabelecer um vínculo terapeuta-cliente é preciso ter a preocupação contínua de o manter sempre vivo e fortalecido. Para que tal aconteça, o terapeuta não pode menosprezar a experiência de vida e expectativas do cliente e deve assumir um papel de permanente preocupação e atenção a todas as transformações quotidianas pois estas influenciam o envolvimento do cliente nas suas atividades/ocupações e afetam a sua saúde e desempenho. O novo milénio requer dos profissionais de saúde em geral e dos terapeutas ocupacionais em particular, novas habilidades e competências. É fundamental adquirir a consciência de que os clientes são o centro de todo o processo terapêutico. É necessário ter uma visão holística e não fragmentada do cliente. É importante interagir com os clientes e permitir uma troca de conhecimento, entre o saber do cliente e o saber do terapeuta. Essa troca gera convergências, fortalece laços e o processo terapêutico avança. Nesse relacionamento, ambos aprendem, progridem e crescem.

Strap repairs using embedded patches: numerical analysis and experimental results

Adhesively bonded repairs offer an attractive option for repair of aluminium structures, compared to more traditional methods such as fastening or welding. The single-strap (SS) and double-strap (DS) repairs are very straightforward to execute but stresses in the adhesive layer peak at the overlap ends. The DS repair requires both sides of the damaged structures to be reachable for repair, which is often not possible. In strap repairs, with the patches bonded at the outer surfaces, some limitations emerge such as the weight, aerodynamics and aesthetics. To minimize these effects, SS and DS repairs with embedded patches were evaluated in this work, such that the patches are flush with the adherends. For this purpose, in this work standard SS and DS repairs, and also with the patches embedded in the adherends, were tested under tension to allow the optimization of some repair variables such as the overlap length (LO) and type of adhesive, thus allowing the maximization of the repair strength. The effect of embedding the patch/patches on the fracture modes and failure loads was compared with finite elements (FE) analysis. The FE analysis was performed in ABAQUS® and cohesive zone modelling was used for the simulation of damage onset and growth in the adhesive layer. The comparison with the test data revealed an accurate prediction for all kinds of joints and provided some principles regarding this technique.