225 resultados para Affective Computing


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Years after the introduction of computing in Australian schools, computer classrooms are still heavily dominated by male students studying subjects which have little appeal to female students, explains the author. This article looks at why girls are less likely to choose computing as a subject to study or to consider computing for a future career.

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The objective of our present paper is to derive a computationally efficient genetic pattern learning algorithm to evolutionarily derive the optimal rebalancing weights (i.e. dynamic hedge ratios) to engineer a structured financial product out of a multiasset, best-of option. The stochastic target function is formulated as an expected squared cost of hedging (tracking) error which is assumed to be partly dependent on the governing Markovian process underlying the individual asset returns and partly on
randomness i.e. pure white noise. A simple haploid genetic algorithm is advanced as an alternative numerical scheme, which is deemed to be
computationally more efficient than numerically deriving an explicit solution to the formulated optimization model. An extension to our proposed scheme is suggested by means of adapting the Genetic Algorithm parameters based on fuzzy logic controllers.

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In this paper, an example of pervasive computing in restaurant, a wireless web-based ordering system is presented. By using mobile devices such as Personal Digital Assistants (PDA) and WebPad, customers can get many benefits when making orders in restaurants. With this system, customers get faster and better services, restaurant staff cooperate more efficiently with less working mistakes, and enterprise owners thus receive more business profits. This system has multi-tiered web-based system architecture with good integration and scalability features, and is client device operating system fully independent. Details of design and implementation of this system are presented.