1000 resultados para Máquinas : Turing : Persistente : Paralela


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Ilustraciones de aplicaciones de fuerza mecánica a las máquinas.

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'Free will' and its corollary, the concept of individual responsibility are keystones of the justice system. This paper shows that if we accept a physics that disallows time reversal, the concept of 'free will' is undermined by an integrated understanding of the influence of genetics and environment on human behavioural responses. Analysis is undertaken by modelling life as a novel statistico-deterministic version of a Turing machine, i.e. as a series of transitions between states at successive instants of time. Using this model it is proven by induction that the entire course of life is independent of the action of free will. Although determined by prior state, the probability of transitions between states in response to a standard environmental stimulus is not equal to 1 and the transitions may differ quantitatively at the molecular level and qualitatively at the level of the whole organism. Transitions between states correspond to behaviours. It is shown that the behaviour of identical twins (or clones), although determined, would be incompletely predictable and non-identical, creating an illusion of the operation of 'free will'. 'Free will' is a convenient construct for current judicial systems and social control because it allows rationalization of punishment for those whose behaviour falls outside socially defined norms. Indeed, it is conceivable that maintenance of ideas of free will has co-evolved with community morality to reinforce its operation. If the concept is free will is to be maintained it would require revision of our current physical theories.

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O principal objetivo desta dissertação foi analisar por meio de estudo comparativo, o posicionamento competitivo de três máquinas ferramentas multitarefas. As hipóteses iniciais partiram das seguintes suposições: a) a indústria nacional de máquinas ferramentas esta sendo penalizada pela política industrial praticada pelo governo federal; e b) a importância relativa atribuída aos elementos multicriteriais das especificações das máquinas nacionais quando demonstram tendências elevadas, nem sempre alcançam as concorrentes importadas devido aos recursos tecnológicos agregados para se atingir a competitividade plena. Assim, indaga-se: até que ponto as máquinas ferramentas multitarefas selecionadas para o estudo, estão alinhadas com os critérios escolhidos e com suas importâncias relativas avaliadas por dois usuários desse equipamento. Como metodologia adotou-se estudo de caso múltiplo de duas empresas de médio porte do mesmo ramo. Utilizou-se o método multicritério de apoio à decisão por meio de Analytic Hierarchy Process (AHP), para a escolha da melhor alternativa entre máquinas ferramentas multitarefas similares, nacionais e importadas. Os resultados identificam que, para essas duas empresas usuárias pesquisadas, existe vantagem na aquisição da máquina importada, embora seja notório o avanço tecnológico da indústria nacional. Estas máquinas ainda carecem de algumas inovações, perdendo em competitividade, bem como em critérios importantes como versatilidade e rendimento. Com base nos trabalhos, conclui-se que, as máquinas ferramentas do tipo multitarefas nacionais das duas empresas fornecedoras analisadas não são competitivas em comparação as importadas.

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We present results concerning the application of the Good-Turing (GT) estimation method to the frequentist n-tuple system. We show that the Good-Turing method can, to a certain extent rectify the Zero Frequency Problem by providing, within a formal framework, improved estimates of small tallies. We also show that it leads to better tuple system performance than Maximum Likelihood estimation (MLE). However, preliminary experimental results suggest that replacing zero tallies with an arbitrary constant close to zero before MLE yields better performance than that of GT system.

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Computational Intelligence Methods have been expanding to industrial applications motivated by their ability to solve problems in engineering. Therefore, the embedded systems follow the same idea of using computational intelligence tools embedded on machines. There are several works in the area of embedded systems and intelligent systems. However, there are a few papers that have joined both areas. The aim of this study was to implement an adaptive fuzzy neural hardware with online training embedded on Field Programmable Gate Array – FPGA. The system adaptation can occur during the execution of a given application, aiming online performance improvement. The proposed system architecture is modular, allowing different configurations of fuzzy neural network topologies with online training. The proposed system was applied to: mathematical function interpolation, pattern classification and selfcompensation of industrial sensors. The proposed system achieves satisfactory performance in both tasks. The experiments results shows the advantages and disadvantages of online training in hardware when performed in parallel and sequentially ways. The sequentially training method provides economy in FPGA area, however, increases the complexity of architecture actions. The parallel training method achieves high performance and reduced processing time, the pipeline technique is used to increase the proposed architecture performance. The study development was based on available tools for FPGA circuits.