Intelligent behavior in a Cyber-Ambient training system for control center operators

This paper deals with the application of an intelligent tutoring approach to delivery training in diagnosis procedures of a Power System. In particular, the mechanisms implemented by the training tool to support the trainees are detailed. This tool is part of an architecture conceived to integrate Power Systems tools in a Power System Control Centre, based on an Ambient Intelligent paradigm. The present work is integrated in the CITOPSY project which main goal is to achieve a better integration between operators and control room applications, considering the needs of people, customizing requirements and forecasting behaviors.

Negotiation mechanism for self-organized scheduling system

This paper presents a negotiation mechanism for Dynamic Scheduling based on Swarm Intelligence (SI). Under the new negotiation mechanism, agents must compete to obtain a global schedule. SI is the general term for several computational techniques which use ideas and get inspiration from the social behaviors of insects and other animals. This work is concerned with negotiation, the process through which multiple selfinterested agents can reach agreement over the exchange of operations on competitive resources.

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.

Negotiation mechanism for self-organized scheduling system with collective intelligence

Current Manufacturing Systems challenges due to international economic crisis, market globalization and e-business trends, incites the development of intelligent systems to support decision making, which allows managers to concentrate on high-level tasks management while improving decision response and effectiveness towards manufacturing agility. This paper presents a novel negotiation mechanism for dynamic scheduling based on social and collective intelligence. Under the proposed negotiation mechanism, agents must interact and collaborate in order to improve the global schedule. Swarm Intelligence (SI) is considered a general aggregation term for several computational techniques, which use ideas and inspiration from the social behaviors of insects and other biological systems. This work is primarily concerned with negotiation, where multiple self-interested agents can reach agreement over the exchange of operations on competitive resources. Experimental analysis was performed in order to validate the influence of negotiation mechanism in the system performance and the SI technique. Empirical results and statistical evidence illustrate that the negotiation mechanism influence significantly the overall system performance and the effectiveness of Artificial Bee Colony for makespan minimization and on the machine occupation maximization.

Web survey system to discover the actual role of experience in learning in higher education: a case study

March 19 - 22, 2006, São Paulo, BRAZIL World Congress on Computer Science, Engineering and Technology Education

Assessment of guanylin peptides system in type 2 diabetes

Os doentes com diabetes mellitus tipo 2 apresentam predisposição para a retenção de sódio e são frequentemente hipertensos. No entanto, os mecanismos implicados na dificuldade do rim diabético em mobilizar o sódio são, ainda, pouco compreendidos. Os peptídeos da família das guanilinas estão envolvidos na regulação do transporte de electrólitos e água nos epitélios intestinal e renal, através da activação do receptor guanilato ciclase-C (GC-C) e subsequente libertação intracelular de GMPc. O objectivo do presente estudo foi a avaliação da actividade do sistema dos peptídeos das guanilinas (SPG) e do seu papel na regulação do balanço de sódio num modelo animal de diabetes tipo 2. Ratinhos machos C57BL/6 foram submetidos a uma dieta com alto teor de gordura e rica em hidratos de carbono simples (ratinhos diabéticos) ou a uma dieta normal (ratinhos controlo). A expressão renal e intestinal da guanilina (GN), uroguanilina (UGN) e do receptor GC-C assim como os níveis de GMPc na urina e plasma foram avaliados nos ratinhos controlo e diabéticos, durante a ingestão de dietas normo (NS) e hiper-salina (HS). Nos ratinhos diabéticos, durante a dieta NS verificou-se um aumento significativo da pressão arterial que foi acompanhado de redução da expressão do ARNm da GN, UGN e do GC-C no intestino e de aumento da expressão de ARNm da UGN no rim. A dieta HS induziu um aumento da expressão do ARNm da UGN no jejuno dos ratinhos controlo mas não nos diabéticos. Os ratinhos diabéticos apresentaram níveis urinários de GMPc inferiores aos controlos, em condições de dieta NS. Em conclusão, os nossos resultados sugerem que na diabetes tipo 2 ocorre uma redução da actividade intestinal do SPG que é acompanhada por um aumento compensatório da actividade renal do SPG. A diminuição da actividade do SPG intestinal na diabetes tipo 2 deve-se não só a uma redução da expressão dos peptídeos GN e UGN, mas também a uma redução da expressão do seu receptor, GC-C. Estes resultados sugerem que o SPG pode contribuir para a sensibilidade ao sódio na diabetes.

Gestão de dados pessoais em saúde

Na presente dissertação pretendemos averiguar da pertinência prática do actual modelo de protecção de dados clínicos, ou seja, se nele está devidamente consagrada a autonomia e a individualidade do utente; pretendemos ainda perceber a tendência evolutiva do sistema português de protecção de dados clínicos, nomeadamente a sua capacidade de inovação e adaptação aos sistemas internacionais, respeitando o nosso ordenamento jurídico. Concretamente, pretendemos perceber de que forma esta informação estará protegida, bem como até onde os utentes estarão consciencializados dos perigos que enfrentam. Embora este seja um problema mundial, o facto é que a Gestão do Sistema de Protecção de Dados Pessoais e Clínicos suscita polémica e interpretações diferentes, dada a sensibilidade ética do tema, a integridade humana. Além deste facto, estamos perante uma problemática que irá sempre envolver vários interesses e consequentemente um confronto de posições. Este trabalho procura ilustrar de que forma se lida com a gestão de dados pessoais no nosso país, de que modo se harmonizam os diferentes interesses e perspectivas, que prioridades se encontram na orientação governamental nesta matéria, quais as penalizações para os eventuais incumpridores e qual o futuro possível dos dados pessoais em saúde, tendo como objectivo comum uma eficácia e sustentabilidade dos mecanismos utilizados. Vamos encontrar interesses divergentes, compromissos permissivos ou restritivos de tratamento de dados, tendências que suportam interesses privados e públicos que se vão concretizar em escolhas eficientes de gestão de dados. Esta diversidade de comportamentos vai ser objecto de estudo e análise neste trabalho, procurando aferir das vantagens e desvantagens de um sistema de informação em saúde: universal com a população coberta, e integrado a fim de compartilhar informações de todos os pacientes, de todas as unidades de prestação de cuidados de saúde.

An heuristic approach for optimal location of gas supply units in transportation system

The best places to locate the Gas Supply Units (GSUs) on a natural gas systems and their optimal allocation to loads are the key factors to organize an efficient upstream gas infrastructure. The number of GSUs and their optimal location in a gas network is a decision problem that can be formulated as a linear programming problem. Our emphasis is on the formulation and use of a suitable location model, reflecting real-world operations and constraints of a natural gas system. This paper presents a heuristic model, based on lagrangean approach, developed for finding the optimal GSUs location on a natural gas network, minimizing expenses and maximizing throughput and security of supply.The location model is applied to the Iberian high pressure natural gas network, a system modelised with 65 demand nodes. These nodes are linked by physical and virtual pipelines – road trucks with gas in liquefied form. The location model result shows the best places to locate, with the optimal demand allocation and the most economical gas transport mode: by pipeline or by road truck.

Learning business strategies for competitive electronic marketplaces

This paper presents a Multi-Agent Market simulator designed for developing new agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. This tool studies negotiations based on different market mechanisms and, time and behavior dependent strategies. The results of the negotiations between agents are analyzed by data mining algorithms in order to extract rules that give agents feedback to improve their strategies. The system also includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agent reactions.

DITRANS - a multi-agent system for integrated diagnosis of power transformers

This paper describes the development and the implementation of a multi-agent system for integrated diagnosis of power transformers. The system is divided in layers which contain a number of agents performing different functions. The social ability and cooperation between the agents lead to the final diagnosis and to other relevant conclusions through integrating various monitoring technologies, diagnostic methods and data sources, such as the dissolved gas analysis.

TINSEL – a web-based intelligent tutoring system on electrical installation design

This paper presents a project consisting on the development of an Intelligent Tutoring System, for training and support concerning the development of electrical installation projects to be used by electrical engineers, technicians and students. One of the major goals of this project is to devise a teaching model based on Intelligent Tutoring techniques, considering not only academic knowledge but also other types of more empirical knowledge, able to achieve successfully the training of electrical installation design.

Study of distribution network demand response events in the Portuguese system

In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. Grid operators and utilities are taking new initiatives, recognizing the value of demand response for grid reliability and for the enhancement of organized spot markets’ efficiency. This paper proposes a methodology for the selection of the consumers that participate in an event, which is the responsibility of the Portuguese transmission network operator. The proposed method is intended to be applied in the interruptibility service implemented in Portugal, in convergence with Spain, in the context of the Iberian electricity market. This method is based on the calculation of locational marginal prices (LMP) which are used to support the decision concerning the consumers to be schedule for participation. The proposed method has been computationally implemented and its application is illustrated in this paper using a 937 bus distribution network with more than 20,000 consumers.

Intelligent management of end consumers loads including electric vehicles through a SCADA system

The large penetration of intermittent resources, such as solar and wind generation, involves the use of storage systems in order to improve power system operation. Electric Vehicles (EVs) with gridable capability (V2G) can operate as a means for storing energy. This paper proposes an algorithm to be included in a SCADA (Supervisory Control and Data Acquisition) system, which performs an intelligent management of three types of consumers: domestic, commercial and industrial, that includes the joint management of loads and the charge/discharge of EVs batteries. The proposed methodology has been implemented in a SCADA system developed by the authors of this paper – the SCADA House Intelligent Management (SHIM). Any event in the system, such as a Demand Response (DR) event, triggers the use of an optimization algorithm that performs the optimal energy resources scheduling (including loads and EVs), taking into account the priorities of each load defined by the installation users. A case study considering a specific consumer with several loads and EVs is presented in this paper.

Residential energy resources management by a SCADA system in case of excess wind generation

The end consumers in a smart grid context are seen as active players. The distributed generation resources applied in smart home system as a micro and small-scale systems can be wind generation, photovoltaic and combine heat and power facility. The paper addresses the management of domestic consumer resources, i.e. wind generation, solar photovoltaic, combined heat and power, electric vehicle with gridable capability and loads, in a SCADA system with intelligent methodology to support the user decision in real time. The main goal is to obtain the better management of excess wind generation that may arise in consumer’s distributed generation resources. The optimization methodology is performed in a SCADA House Intelligent Management context and the results are analyzed to validate the SCADA system.

Cooperative scheduling system with emergent swarm based behavior

This paper presents a Swarm based Cooperation Mechanism for scheduling optimization. We intend to conceptualize real manufacturing systems as interacting autonomous entities in order to support decision making in agile manufacturing environments. Agents coordinate their actions automatically without human supervision considering a common objective – global scheduling solution taking advantages from collective behavior of species through implicit and explicit cooperation. The performance of the cooperation mechanism will be evaluated consider implicit cooperation at first stage through ACS, PSO and ABC algorithms and explicit through cooperation mechanism application.