MASDScheGATS: a prototype system for dynamic scheduling

A manufacturing system has a natural dynamic nature observed through several kinds of random occurrences and perturbations on working conditions and requirements over time. For this kind of environment it is important the ability to efficient and effectively adapt, on a continuous basis, existing schedules according to the referred disturbances, keeping performance levels. The application of Meta-Heuristics and Multi-Agent Systems to the resolution of this class of real world scheduling problems seems really promising. This paper presents a prototype for MASDScheGATS (Multi-Agent System for Distributed Manufacturing Scheduling with Genetic Algorithms and Tabu Search).

Multi-agent electricity market simulation with dynamic strategies & virtual power producers

Distributed energy resources will provide a significant amount of the electricity generation and will be a normal profitable business. In the new decentralized grid, customers will be among the many decentralized players and may even help to co-produce the required energy services such as demand-side management and load shedding. So, they will gain the opportunity to be more active market players. The aggregation of DG plants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets. In this paper we propose the improvement of MASCEM, a multi-agent simulation tool to study negotiations in electricity spot markets based on different market mechanisms and behavior strategies, in order to take account of decentralized players such as VPP.

Predicted VO2 on 6 minutes walk test for FAP liver transplanted patients

Physical function is limited post-liver transplantation and exercise training can improve exercise capacity following transplantation but previously assessment of functional capacity is necessary. The 6 minute walk test (6MWT) is routinely used for studying patient’s exercise capacity and is less expensive and time consuming than a Cardiopulmonary Exercise Test (CPXT). There have been some studies looking at the relationship between 6MWT and peak VO2 in patients but few presented an adequate equation for predicted peak VO2 from 6MWT to transplanted patients and none for Familial Amyloidotic Polyneuropathy (FAP) liver transplanted patients (FAPTx). The aim of this study was to compare the validity of 6 equations as predictors of VO2 from the 6MWT and compare it with directly measured VO2 in patients FAPTx.

Collective intelligence on dynamic manufacturing scheduling optimization

Swarm Intelligence (SI) is a growing research field of Artificial Intelligence (AI). SI is the general term for several computational techniques which use ideas and get inspiration from the social behaviours of insects and of other animals. This paper presents hybridization and combination of different AI approaches, like Bio-Inspired Techniques (BIT), Multi-Agent systems (MAS) and Machine Learning Techniques (ML T). The resulting system is applied to the problem of jobs scheduling to machines on dynamic manufacturing environments.

Meta-heuristics tunning using CBR for dynamic scheduling

This paper addresses the problem of Biological Inspired Optimization Techniques (BIT) parameterization, considering the importance of this issue in the design of BIT especially when considering real world situations, subject to external perturbations. A learning module with the objective to permit a Multi-Agent Scheduling System to automatically select a Meta-heuristic and its parameterization to use in the optimization process is proposed. For the learning process, Casebased Reasoning was used, allowing the system to learn from experience, in the resolution of similar problems. Analyzing the obtained results we conclude about the advantages of its use.

Self-optimization aspects for dynamic scheduling

Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. At this scenario, self-optimizing arise as the ability of the agent to monitor its state and performance and proactively tune itself to respond to environmental stimuli.

Self-managing agents for dynamic scheduling in manufacturing

The main purpose of this paper is to propose a Multi-Agent Autonomic and Bio-Inspired based framework with selfmanaging capabilities to solve complex scheduling problems using cooperative negotiation. Scheduling resolution requires the intervention of highly skilled human problem-solvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing (AC) evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference.

The darmstadt challenge (the turing test revisited)

Significant work has been done in the areas of Pervcomp/Ubicomp Smart Environments with advances on making proactive systems, but those advances have not made these type of systems accurately proactive. On the other hand a great deal is needed to make systems more sensible/sensitive and trustable (both in terms of reliability and privacy). We put forward the thesis that a more integral and social-aware sort of intelligence is needed to effectively interact, decide and act on behalf of people’s interest and that a way to test how effective systems are achieving these desirable behaviour is needed as a consequence. We support our thesis by providing examples on how to measure effectiveness in variety of different environments.

Cooperation mechanism for team-work based multi-agent system in dynamic scheduling through meta-heuristics

This paper describes a Multi-agent Scheduling System that assumes the existence of several Machines Agents (which are decision-making entities) distributed inside the Manufacturing System that interact and cooperate with other agents in order to obtain optimal or near-optimal global performances. Agents have to manage their internal behaviors and their relationships with other agents via cooperative negotiation in accordance with business policies defined by the user manager. Some Multi Agent Systems (MAS) organizational aspects are considered. An original Cooperation Mechanism for a Team-work based Architecture is proposed to address dynamic scheduling using Meta-Heuristics.

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.

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

Mestrado em Engenharia Electrotécnica e de Computadores

Análise da resistência à fadiga de tubos de aço API 5CT N80 Tipo Q soldados via processo de indução magnética de alta frequência (HFIW)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

An application of structural equation modeling of test dispositional optimism as mediator or moderator in quality of life in patients with chronic disease

The aim of the present study was to test a hypothetical model to examine if dispositional optimism exerts a moderating or a mediating effect between personality traits and quality of life, in Portuguese patients with chronic diseases. A sample of 540 patients was recruited from central hospitals in various districts of Portugal. All patients completed self-reported questionnaires assessing socio-demographic and clinical variables, personality, dispositional optimism, and quality of life. Structural equation modeling (SEM) was used to analyze the moderating and mediating effects. Results suggest that dispositional optimism exerts a mediator rather than a moderator role between personality traits and quality of life, suggesting that “the expectation that good things will happen” contributes to a better general well-being and better mental functioning.

Comportamento motor do tronco e membro superior, num sistema de posicionamento rígido e dinâmico, durante atividade

A funcionalidade dos indivíduos com Paralisia Cerebral está muitas vezes comprometida devido às alterações do movimento e do controlo postural. Dadas estas alterações, a posição de sentado oferece uma maior estabilidade sendo muitas das atividades de vida diária desempenhadas nesta posição. O objetivo mais importante de intervenção é obter o máximo de funcionalidade na posição de sentado, particularmente do membro superior. Este objectivo, na maioria das vezes, só pode ser atingido com o uso de sistemas de posicionamento que tentam colmatar as alterações posturais e do movimento. Assim, o objetivo deste estudo de caso é verificar se existem diferenças no comportamento motor do tronco e do membro superior, com um sistema de posicionamento rígido e com um sistema de posicionamento dinâmico, numa jovem com Paralisia Cerebral, aquando da ativação manual de um switch. Foi realizado um estudo de caso único em que foi feita uma análise cinemática do movimento do tronco e membro superior na ativação de um switch BigMack, em três posições de teste com distâncias diferentes. Simultaneamente mediu-se a distribuição do peso durante o movimento, através do mapa de pressão e foi registada, bilateralmente a atividade dos músculos trapézio (porção média), longuíssimo, recto abdominal e oblíquo externo. Os resultados obtidos apontam, neste caso em particular, para uma melhoria na qualidade do movimento e da distribuição de peso, com o sistema de posicionamento dinâmico, sem diferenças entre os dois sistemas relativamente à ativação muscular.

Harvesting dynamic aspects from a real rational map : the bulb of period 5

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