934 resultados para Complex adaptive systems
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Power laws, also known as Pareto-like laws or Zipf-like laws, are commonly used to explain a variety of real world distinct phenomena, often described merely by the produced signals. In this paper, we study twelve cases, namely worldwide technological accidents, the annual revenue of America׳s largest private companies, the number of inhabitants in America׳s largest cities, the magnitude of earthquakes with minimum moment magnitude equal to 4, the total burned area in forest fires occurred in Portugal, the net worth of the richer people in America, the frequency of occurrence of words in the novel Ulysses, by James Joyce, the total number of deaths in worldwide terrorist attacks, the number of linking root domains of the top internet domains, the number of linking root domains of the top internet pages, the total number of human victims of tornadoes occurred in the U.S., and the number of inhabitants in the 60 most populated countries. The results demonstrate the emergence of statistical characteristics, very close to a power law behavior. Furthermore, the parametric characterization reveals complex relationships present at higher level of description.
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RTUWO Advances in Wireless and Optical Communications 2015 (RTUWO 2015). 5-6 Nov Riga, Latvia.
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A novel control technique is investigated in the adaptive control of a typical paradigm, an approximately and partially modeled cart plus double pendulum system. In contrast to the traditional approaches that try to build up ”complete” and ”permanent” system models it develops ”temporal” and ”partial” ones that are valid only in the actual dynamic environment of the system, that is only within some ”spatio-temporal vicinity” of the actual observations. This technique was investigated for various physical systems via ”preliminary” simulations integrating by the simplest 1st order finite element approach for the time domain. In 2004 INRIA issued its SCILAB 3.0 and its improved numerical simulation tool ”Scicos” making it possible to generate ”professional”, ”convenient”, and accurate simulations. The basic principles of the adaptive control, the typical tools available in Scicos, and others developed by the authors, as well as the improved simulation results and conclusions are presented in the contribution.
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Presented at SEMINAR "ACTION TEMPS RÉEL:INFRASTRUCTURES ET SERVICES SYSTÉMES". 10, Apr, 2015. Brussels, Belgium.
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It is imperative to accept that failures can and will occur, even in meticulously designed distributed systems, and design proper measures to counter those failures. Passive replication minimises resource consumption by only activating redundant replicas in case of failures, as typically providing and applying state updates is less resource demanding than requesting execution. However, most existing solutions for passive fault tolerance are usually designed and configured at design time, explicitly and statically identifying the most critical components and their number of replicas, lacking the needed flexibility to handle the runtime dynamics of distributed component-based embedded systems. This paper proposes a cost-effective adaptive fault tolerance solution with a significant lower overhead compared to a strict active redundancy-based approach, achieving a high error coverage with the minimum amount of redundancy. The activation of passive replicas is coordinated through a feedback-based coordination model that reduces the complexity of the needed interactions among components until a new collective global service solution is determined, improving the overall maintainability and robustness of the system.
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Presented at INForum - Simpósio de Informática (INFORUM 2015). 7 to 8, Sep, 2015. Covilhã, Portugal.
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Presented at INForum - Simpósio de Informática (INFORUM 2015). 7 to 8, Sep, 2015. Portugal.
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The electricity market restructuring, and its worldwide evolution into regional and even continental scales, along with the increasing necessity for an adequate integration of renewable energy sources, is resulting in a rising complexity in power systems operation. Several power system simulators have been developed in recent years with the purpose of helping operators, regulators, and involved players to understand and deal with this complex and constantly changing environment. The main contribution of this paper is given by the integration of several electricity market and power system models, respecting to the reality of different countries. This integration is done through the development of an upper ontology which integrates the essential concepts necessary to interpret all the available information. The continuous development of Multi-Agent System for Competitive Electricity Markets platform provides the means for the exemplification of the usefulness of this ontology. A case study using the proposed multi-agent platform is presented, considering a scenario based on real data that simulates the European Electricity Market environment, and comparing its performance using different market mechanisms. The main goal is to demonstrate the advantages that the integration of various market models and simulation platforms have for the study of the electricity markets’ evolution.
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This paper presents a decision support methodology for electricity market players’ bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method’s adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts’ negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems’ technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players’ decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator—MIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts’ negotiations.
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In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.
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In this paper, a rule-based automatic syllabifier for Danish is described using the Maximal Onset Principle. Prior success rates of rule-based methods applied to Portuguese and Catalan syllabification modules were on the basis of this work. The system was implemented and tested using a very small set of rules. The results gave rise to 96.9% and 98.7% of word accuracy rate, contrary to our initial expectations, being Danish a language with a complex syllabic structure and thus difficult to be rule-driven. Comparison with data-driven syllabification system using artificial neural networks showed a higher accuracy rate of the former system.
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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O ensino à distância cresceu consideravelmente nos últimos anos e a tendência é para que continue a crescer em anos vindouros. No entanto, enquanto que a maioria das plataformas de ensino à distância utilizam a mesma abordagem de ensino para todos os utilizadores, os estudantes que as usam são na realidade pessoas de diferentes culturas, locais, idades e géneros, e que possuem diferentes níveis de educação. Ao contrário do ensino à distância tradicional, os sistemas de hipermédia adaptativa educacional adaptam interface, apresentação de conteúdos e navegação, entre outros, às características, necessidades e interesses específicos de diferentes utilizadores. Apesar da investigação na área de sistemas de hipermédia adaptativa já estar bastante desenvolvida, é necessário efetuar mais desenvolvimento e experimentação de modo a determinar quais são os aspetos mais eficazes destes sistemas e avaliar o seu sucesso. A Plataforma de Aprendizagem Colaborativa da Matemática (PCMAT) é um sistema de hipermédia adaptativa educacional com uma abordagem construtivista, que foi desenvolvido com o objetivo de contribuir para a investigação na área de sistemas de hipermédia adaptativa. A plataforma avalia o conhecimento do utilizador e apresenta conteúdos e atividades adaptadas às características e estilo de aprendizagem dominante de estudantes de matemática do segundo ciclo. O desenvolvimento do PCMAT tem também o propósito de auxiliar os alunos Portugueses com a aprendizagem da matemática. De acordo com o estudo PISA 2012 da OCDE [OECD, 2014], o desempenho dos alunos Portugueses na área da matemática melhorou em relação à edição anterior do estudo, mas os resultados obtidos permanecem abaixo da média da OCDE. Por este motivo, uma das finalidades deste projeto é desenvolver um sistema de hipermédia adaptativa que, ao adequar o ensino da matemática às necessidades específicas de cada aluno, os assista com a aquisição de conhecimento. A adaptação é efetuada pelo sistema usando a informação constante no modelo do utilizador para definir um grafo de conceitos do domínio específico. Este grafo é adaptado do modelo do domínio e utilizado para dar resposta às necessidades particulares de cada aluno. Embora a trajetória inicial seja definida pelo professor, o percurso percorrido no grafo por cada aluno é determinado pela sua interação com o sistema, usando para o efeito a representação do conhecimento do aluno e outras características disponíveis no modelo do utilizador, assim como avaliação progressiva. A adaptação é conseguida através de alterações na apresentação de conteúdos e na estrutura e anotações das hiperligações. A apresentação de conteúdos é alterada mostrando ou ocultando cada um dos vários fragmentos que compõe as páginas dum curso. Estes fragmentos são compostos por diferentes objetos de aprendizagem, tais como exercícios, figuras, diagramas, etc. As mudanças efetuadas na estrutura e anotações das hiperligações têm o objetivo de guiar o estudante, apontando-o na direção do conhecimento mais relevante e mantendo-o afastado de informação inadequada. A escolha de objectos de aprendizagem adequados às características particulares de cada aluno é um aspecto essencial do modelo de adaptação do PCMAT. A plataforma inclui para esse propósito um módulo responsável pela recomendação de objectos de aprendizagem, e um módulo para a pesquisa e recuperação dos mesmos. O módulo de recomendação utiliza lógica Fuzzy para converter determinados atributos do aluno num conjunto de parâmetros que caracterizam o objecto de aprendizagem que idealmente deveria ser apresentado ao aluno. Uma vez que o objecto “ideal” poderá não existir no repositório de objectos de aprendizagem do sistema, esses parâmetros são utilizados pelo módulo de pesquisa e recuperação para procurar e devolver ao módulo de recomendação uma lista com os objectos que mais se assemelham ao objecto “ideal”. A pesquisa é feita numa árvore k-d usando o algoritmo k-vizinhos mais próximos. O modelo de recomendação utiliza a lista devolvida pelo módulo de pesquisa e recuperação para seleccionar o objecto de aprendizagem mais apropriado para o aluno e processa-o para inclusão numa das páginas Web do curso. O presente documento descreve o trabalho desenvolvido no âmbito do projeto PCMAT (PTDS/CED/108339/2008), dando relevância à adaptação de conteúdos.
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Manipulator systems are rather complex and highly nonlinear which makes difficult their analysis and control. Classic system theory is veil known, however it is inadequate in the presence of strong nonlinear dynamics. Nonlinear controllers produce good results [1] and work has been done e. g. relating the manipulator nonlinear dynamics with frequency response [2–5]. Nevertheless, given the complexity of the problem, systematic methods which permit to draw conclusions about stability, imperfect modelling effects, compensation requirements, etc. are still lacking. In section 2 we start by analysing the variation of the poles and zeros of the descriptive transfer functions of a robot manipulator in order to motivate the development of more robust (and computationally efficient) control algorithms. Based on this analysis a new multirate controller which is an improvement of the well known “computed torque controller” [6] is announced in section 3. Some research in this area was done by Neuman [7,8] showing tbat better robustness is possible if the basic controller structure is modified. The present study stems from those ideas, and attempts to give a systematic treatment, which results in easy to use standard engineering tools. Finally, in section 4 conclusions are presented.
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Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica