927 resultados para Algorithmic Complexity


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Agility refers to the manufacturing system ability to rapidly adapt to market and environmental changes in efficient and cost-effective ways. This paper addresses the development of self-organization methods to enhance the operations of a scheduling system, by integrating scheduling system, configuration and optimization into a single autonomic process requiring minimal manual intervention to increase productivity and effectiveness while minimizing complexity for users. We intend to conceptualize real manufacturing systems as interacting autonomous entities in order to build future Decision Support Systems (DSS) for Scheduling in agile manufacturing environments.

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In this paper, we foresee the use of Multi-Agent Systems for supporting dynamic and distributed scheduling in Manufacturing Systems. We also envisage the use of Autonomic properties in order to reduce the complexity of managing systems and human interference. By combining Multi-Agent Systems, Autonomic Computing, and Nature Inspired Techniques we propose an approach for the resolution of dynamic scheduling problem, with Case-based Reasoning Learning capabilities. The objective is to permit a system to be able to automatically adopt/select a Meta-heuristic and respective parameterization considering scheduling characteristics. From the comparison of the obtained results with previous results, we conclude about the benefits of its use.

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We describe a novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS) and Nature Inspired Optimization Techniques (NIT). Autonomic Computing has emerged as paradigm aiming at embedding applications with a management structure similar to a central nervous system. A natural Autonomic Computing evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference. In this paper we envisage the use of Multi-Agent Systems paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with Autonomic properties, in order to reduce the complexity of managing systems and human interference. Additionally, we consider the resolution of realistic problems. The scheduling of a Cutting and Treatment Stainless Steel Sheet Line will be evaluated. Results show that proposed approach has advantages when compared with other scheduling systems.

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A existência de estações de tratamentos de águas residuais (ETAR) é, nos dias de hoje, fundamental na medida em que permite, reduzir a poluição ambiental associada às águas e, também, a reutilização da água tratada para diversos fins. A constante necessidade de cumprir os limites de descargas nos meios recetores conduziu a um melhoramento nas técnicas e processos de tratamento de efluentes, nomeadamente, nos processos biológicos. O processo por lamas ativadas é um processo amplamente utilizado para a remoção de poluentes orgânicos presentes nas águas residuais, pelo que um estudo mais intensivo sobre estes tratamentos resultou na publicação de uma série de conceitos e pressupostos, através de modelos numéricos. A modelação numérica de processos de tratamento de águas residuais e a utilização de ferramentas de simulação numérica têm sido largamente utilizadas, a nível mundial, por exemplo em investigação, desenvolvimento de processos, atividade de consultoria e igualmente por entidades reguladoras, na medida em que os auxiliam no planeamento, dimensionamento e análise do comportamento de infraestruturas de tratamento. No presente trabalho, recorreu-se ao software de simulação GPS-X (versão 6.0) para implementar o esquema de tratamento da ETAR de Beirolas. O objetivo deste trabalho é verificar a aplicabilidade de modelos numéricos na simulação de unidades de tratamento de efluentes e avaliar a resposta dos diferentes modelos, assim como a influência na alteração de características das águas afluentes no comportamento dos modelos. Os resultados obtidos permitiram concluir que os modelos numéricos podem ser utilizados para prever a resposta dos sistemas biológicos e as suas perturbações. Conclui-se ainda que o comportamento, dos modelos estudados (ASM1, ASM2d, ASM3 e mantis), é semelhante, contudo deve-se referir que devido à complexidade do modelo e a falta de informação experimental sobre as características do efluente, não permitiram efetuar uma completa caracterização e calibração do caso de estudo, e toda a informação disponível sobre as características físico-químicas da água foram baseadas em estimativas de concentrações de carências de oxigénio e sólidos suspensos.

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In a world increasingly conscientious about environmental effects, power and energy systems are undergoing huge transformations. Electric energy produced from power plants is transmitted and distributed to end users through a power grid. The power industry performs the engineering design, installation, operation, and maintenance tasks to provide a high-quality, secure energy supply while accounting for its systems’ abilities to withstand uncertain events, such as weather-related outages. Competitive, deregulated electricity markets and new renewable energy sources, however, have further complicated this already complex infrastructure.Sustainable development has also been a challenge for power systems. Recently, there has been a signifi cant increase in the installation of distributed generations, mainly based on renewable resources such as wind and solar. Integrating these new generation systems leads to more complexity. Indeed, the number of generation sources greatly increases as the grid embraces numerous smaller and distributed resources. In addition, the inherent uncertainties of wind and solar energy lead to technical challenges such as forecasting, scheduling, operation, control, and risk management. In this special issue introductory article, we analyze the key areas in this field that can benefi t most from AI and intelligent systems now and in the future.We also identify new opportunities for cross-fertilization between power systems and energy markets and intelligent systems researchers.

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The public sector is facing turbulent times and this also challenges the health professions who are expected to serve both the interests of the citizens and the cost-containment and austerity policies of governments. This article seeks to explore the changing role of the health professions. I introduce an approach on ‘citizen professionals’ as active players in the policy process and mediators between the state/policymakers and the citizens/patients. The aim is to highlight a transformative potential of professionalism and the connectedness with other sets of governance, like management. Empirical material from a German case study and a comparative European study serve to illustrate the arguments, drawing on policy analysis and secondary sources. The results bring the complexity of transformations and new emergent forms of professionalism into view that cannot be understood in traditional categories of conflict, exclusion and jurisdiction. Exploring the potential of the health professions to creatively respond to new challenges may reveal new opportunities for innovating healthcare policy beyond market and management.

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Neste trabalho defendo que as narrativas podem ser instrumentos para avaliar a competência linguística e comunicativa de crianças na escola por serem bons indicadores da complexidade sintáctico-semântica, darem informação preciosa sobre competências discursivas, particularmente construção da referência (nominal e temporal), continuidade tópica, frases complexas. Por ser o primeiro tipo de texto que as crianças adquirem, deve ser encarado como um meio importante para desenvolver a consciência meta-textual.

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Tese de Doutoramento, Física, 27 de Novembro de 2013, Universidade dos Açores.

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There is a general consensus that in a competitive business environment, firms’ performance will depend on their capacity to innovate. To clarifying how, when and to what extent innovation affects the market and financial performance of firms, the authors deploy seemingly unrelated regression equation model to examine innovation in over 500 Portuguese firms from 1998 to 2004. The results confirm, as theorists have frequently assumed, that innovation positively affects firms’ performance; but they also suggest that the reverse is true, a result that is less intuitively obvious, given the complexity of the innovation process and local, national and global competitive environments.

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Mestrado em Engenharia Electrotécnica e de Computadores

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Dissertação de 2º Ciclo conducente ao grau de Mestre em Ciências da Educação, especialização em Intervenção Precoce.

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In this work a new probabilistic and dynamical approach to an extension of the Gompertz law is proposed. A generalized family of probability density functions, designated by Beta* (p, q), which is proportional to the right hand side of the Tsoularis-Wallace model, is studied. In particular, for p = 2, the investigation is extended to the extreme value models of Weibull and Frechet type. These models, described by differential equations, are proportional to the hyper-Gompertz growth model. It is proved that the Beta* (2, q) densities are a power of betas mixture, and that its dynamics are determined by a non-linear coupling of probabilities. The dynamical analysis is performed using techniques of symbolic dynamics and the system complexity is measured using topological entropy. Generally, the natural history of a malignant tumour is reflected through bifurcation diagrams, in which are identified regions of regression, stability, bifurcation, chaos and terminus.

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Dissertação de Mestrado, Sociologia, 24 de Março de 2014, Universidade dos Açores.

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Video coding technologies have played a major role in the explosion of large market digital video applications and services. In this context, the very popular MPEG-x and H-26x video coding standards adopted a predictive coding paradigm, where complex encoders exploit the data redundancy and irrelevancy to 'control' much simpler decoders. This codec paradigm fits well applications and services such as digital television and video storage where the decoder complexity is critical, but does not match well the requirements of emerging applications such as visual sensor networks where the encoder complexity is more critical. The Slepian Wolf and Wyner-Ziv theorems brought the possibility to develop the so-called Wyner-Ziv video codecs, following a different coding paradigm where it is the task of the decoder, and not anymore of the encoder, to (fully or partly) exploit the video redundancy. Theoretically, Wyner-Ziv video coding does not incur in any compression performance penalty regarding the more traditional predictive coding paradigm (at least for certain conditions). In the context of Wyner-Ziv video codecs, the so-called side information, which is a decoder estimate of the original frame to code, plays a critical role in the overall compression performance. For this reason, much research effort has been invested in the past decade to develop increasingly more efficient side information creation methods. This paper has the main objective to review and evaluate the available side information methods after proposing a classification taxonomy to guide this review, allowing to achieve more solid conclusions and better identify the next relevant research challenges. After classifying the side information creation methods into four classes, notably guess, try, hint and learn, the review of the most important techniques in each class and the evaluation of some of them leads to the important conclusion that the side information creation methods provide better rate-distortion (RD) performance depending on the amount of temporal correlation in each video sequence. It became also clear that the best available Wyner-Ziv video coding solutions are almost systematically based on the learn approach. The best solutions are already able to systematically outperform the H.264/AVC Intra, and also the H.264/AVC zero-motion standard solutions for specific types of content. (C) 2013 Elsevier B.V. All rights reserved.