844 resultados para Global Knowledge Base


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In this paper, an expert and interactive system for developing protection system for overhead and radial distribution feeders is proposed. In this system the protective devices can be allocated through heuristic and an optimized way. In the latter one, the placement problem is modeled as a mixed integer non-linear programming, which is solved by genetic algorithm (GA). Using information stored in a database as well as a knowledge base, the computational system is able to obtain excellent conditions of selectivity and coordination for improving the feeder reliability indices. Tests for assessment of the algorithm efficiency were carried out using a real-life 660-nodes feeder. © 2006 IEEE.

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The need for the representation of both semantics and common sense and its organization in a lexical database or knowledge base has motivated the development of large projects, such as Wordnets, CYC and Mikrokosmos. Besides the generic bases, another approach is the construction of ontologies for specific domains. Among the advantages of such approach there is the possibility of a greater and more detailed coverage of a specific domain and its terminology. Domain ontologies are important resources in several tasks related to the language processing, especially in those related to information retrieval and extraction in textual bases. Information retrieval or even question and answer systems can benefit from the domain knowledge represented in an ontology. Besides embracing the terminology of the field, the ontology makes the relationships among the terms explicit. Copyright 2007 ACM.

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Purpose: This paper describes proposed health care services innovations, provided by a system called CAALYX (Complete Ambient Assisted Living eXperiment). CAALYX aimed to provide healthcare innovation by extending the state-of-the-art in tele-healthcare, by focusing on increasing the confidence of elderly people living autonomously, by building on the knowledge base of the most common disorders and respective characteristic vital sign changes for this age group. Methods: A review of the state-of-the-art on health care services was carried out. Then, extensive research was conducted on the particular needs of the elderly in relation to home health services that, if offered to them, could improve their day life by giving them greater confidence and autonomy. To achieve this, we addressed issues associated with the gathering of clinical data and interpretation of these data, as well as possibilities of automatically triggering appropriate clinical measures. Considering this initial work we started the identification of initiatives, ongoing works and technologies that could be used for the development of the system. After that, the implementation of CAALYX was done. Findings: The innovation in CAALYX system considers three main areas of contribution: (i) The Roaming Monitoring System that is used to collect information on the well-being of the elderly users; (ii) The Home Monitoring System that is aimed at helping the elders independently living at home being implemented by a device (a personal computer or a set top box) that supports the connection of sensors and video cameras that may be used for monitoring and for interaction with the elder; (iii) The Central Care Service and Monitoring System that is implemented by a Caretaker System where attention and care services are provided to elders, where actors as Caretakers, Doctors and Relatives are logically linked to elders. Innovations in each of these areas are presented here. Conclusions: The ageing European society is placing an added burden on future generations, as the 'elderly-to-working-age-people' ratio is set to steadily increase in the future. Nowadays, quality of life and fitness allows for most older persons to have an active life well into their eighties. Furthermore, many older persons prefer to live in their own house and choose their own lifestyle. The CAALYX system can have a clear impact in increasing older persons' autonomy, by ensuring that they do not need to leave their preferred environment in order to be properly monitored and taken care of. © 2011 Elsevier B.V. All rights reserved.

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Includes bibliography

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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A automação na gestão e análise de dados tem sido um fator crucial para as empresas que necessitam de soluções eficientes em um mundo corporativo cada vez mais competitivo. A explosão do volume de informações, que vem se mantendo crescente nos últimos anos, tem exigido cada vez mais empenho em buscar estratégias para gerenciar e, principalmente, extrair informações estratégicas valiosas a partir do uso de algoritmos de Mineração de Dados, que comumente necessitam realizar buscas exaustivas na base de dados a fim de obter estatísticas que solucionem ou otimizem os parâmetros do modelo de extração do conhecimento utilizado; processo que requer computação intensiva para a execução de cálculos e acesso frequente à base de dados. Dada a eficiência no tratamento de incerteza, Redes Bayesianas têm sido amplamente utilizadas neste processo, entretanto, à medida que o volume de dados (registros e/ou atributos) aumenta, torna-se ainda mais custoso e demorado extrair informações relevantes em uma base de conhecimento. O foco deste trabalho é propor uma nova abordagem para otimização do aprendizado da estrutura da Rede Bayesiana no contexto de BigData, por meio do uso do processo de MapReduce, com vista na melhora do tempo de processamento. Para tanto, foi gerada uma nova metodologia que inclui a criação de uma Base de Dados Intermediária contendo todas as probabilidades necessárias para a realização dos cálculos da estrutura da rede. Por meio das análises apresentadas neste estudo, mostra-se que a combinação da metodologia proposta com o processo de MapReduce é uma boa alternativa para resolver o problema de escalabilidade nas etapas de busca em frequência do algoritmo K2 e, consequentemente, reduzir o tempo de resposta na geração da rede.

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Pós-graduação em Engenharia de Produção - FEB

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This is a preliminary theoretical discussion on the computational requirements of the state of the art smoothed particle hydrodynamics (SPH) from the optics of pattern recognition and artificial intelligence. It is pointed out in the present paper that, when including anisotropy detection to improve resolution on shock layer, SPH is a very peculiar case of unsupervised machine learning. On the other hand, the free particle nature of SPH opens an opportunity for artificial intelligence to study particles as agents acting in a collaborative framework in which the timed outcomes of a fluid simulation forms a large knowledge base, which might be very attractive in computational astrophysics phenomenological problems like self-propagating star formation.

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Discusses the concepts occupational knowledge and scientific knowledge, taking into account the existence of the field of Information Science formed by sub-professional and scientific fields. Displays incursions in profession sociology and systems theory of profession, in order to expand the vision of the knowledge base among information professionals.

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In the current context of Metalexicography several types of studies have been conducted in order to better understand the organization of existing dictionaries and, thus, constitute a knowledge base that would support the development of new works. Regarding specifically the dictionaries of Phraseology, although there are many researchers who engage in this domain, there is still much to study in order to optimize and boost production as much monolingual as bilingual works. The aim of this paper is to present a brief discursive analysis of three phraseological dictionaries considering the pedagogical aspect.

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Wetland ecology is a relatively new field that developed from an initial interest in a few direct benefits that wetlands provide to society. Consequently, much early scientific work was stimulated by economic returns from specific wetland services, such as production of peat and provision of habitat for economically valuable wildlife (e.g., waterfowl and furbearers). Over time, societal interest in wetlands broadened, and these unique habitats are now valued for many additional services, including some that bear non market value. Common examples include carbon sequestration, flood reduction, water purification, and aesthetics. The increased recognition of the importance of wetlands has generated a diversity of job opportunities in wetland ecology and management. Despite the increased knowledge base and enhanced job market, I am not aware of any institutions that offer specialty degrees in this new discipline. Indeed, relatively few institutions offer specific wetland ecology classes, with Arnold G. van der Valk and a few of his peers at other universities being notable exceptions.

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Product miniaturization for applications in fields such as biotechnology, medical devices, aerospace, optics and communications has made the advancement of micromachining techniques essential. Machining of hard and brittle materials such as ceramics, glass and silicon is a formidable task. Rotary ultrasonic machining (RUM) is capable of machining these materials. RUM is a hybrid machining process which combines the mechanism of material removal of conventional grinding and ultrasonic machining. Downscaling of RUM for micro scale machining is essential to generate miniature features or parts from hard and brittle materials. The goal of this thesis is to conduct a feasibility study and to develop a knowledge base for micro rotary ultrasonic machining (MRUM). Positive outcome of the feasibility study led to a comprehensive investigation on the effect of process parameters. The effect of spindle speed, grit size, vibration amplitude, tool geometry, static load and coolant on the material removal rate (MRR) of MRUM was studied. In general, MRR was found to increase with increase in spindle speed, vibration amplitude and static load. MRR was also noted to depend upon the abrasive grit size and tool geometry. The behavior of the cutting forces was modeled using time series analysis. Being a vibration assisted machining process, heat generation in MRUM is low which is essential for bone machining. Capability of MRUM process for machining bone tissue was investigated. Finally, to estimate the MRR a predictive model was proposed. The experimental and the theoretical results exhibited a matching trend.