24 resultados para COGNITIVE FUNCTION


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Recently simple limiting functions establishing upper and lower bounds on the Mittag-Leffler function were found. This paper follows those expressions to design an efficient algorithm for the approximate calculation of expressions usual in fractional-order control systems. The numerical experiments demonstrate the superior efficiency of the proposed method.

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Technology is present in almost every simple aspect of the people’s daily life. As an instance, let us refer to the smartphone. This device is usually equipped with a GPS modulewhich may be used as an orientation system, if it carries the right functionalities. The problem is that these applications may be complex to operate and may not be within the bounds of everybody. Therefore, the main goal here is to develop an orientation system that may help people with cognitive disabilities in their day-to-day journeys, when the caregivers are absent. On the other hand, to keep paid helpers aware of the current location of the disable people, it will be also considered a localization system. Knowing their current locations, caregiversmay engage in others activities without neglecting their prime work, and, at the same time, turning people with cognitive disabilities more independent.

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4th International Conference on Future Generation Communication Technologies (FGCT 2015), Luton, United Kingdom.

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Recently simple limiting functions establishing upper and lower bounds on the Mittag-Leffler function were found. This paper follows those expressions to design an efficient algorithm for the approximate calculation of expressions usual in fractional-order control systems. The numerical experiments demonstrate the superior efficiency of the proposed method.

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This paper analyses the dynamical properties of systems with backlash and impact phenomena based on the describing function method. The dynamics is illustrated using the Nyquist and Bode plots and the results are compared with those of standard models.

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Recent advances in psychosocial treatments for schizophrenia have targeted social cognitive deficits. A critical literature review and effect-size (ES) analysis was conducted to investigate the efficacy of comprehensive programs of social cognitive training in schizophrenia. Results revealed 16 controlled studies consisting of seven models of comprehensive treatment with only three of these treatment models investigated in more than one study. The effects of social cognitive training were reported in 11/15 studies that included facial affect recognition skills (ES=.84) and 10/13 studies that included theory-of-mind (ES=.70) as outcomes. Less than half (4/9) of studies that measured attributional style as an outcome reported effects of treatment, but effect sizes across studies were significant (ESs=.30-.52). The effect sizes for symptoms were modest, but, with the exception of positive symptoms, significant (ESs=.32-.40). The majority of trials were randomized (13/16), selected active control conditions (11/16) and included at least 30 participants (12/16). Concerns for this area of research include the absence of blinded outcome raters in more than 50% of trials and low rates of utilization of procedures for maintaining treatment fidelity. These findings provide preliminary support for the broader use of comprehensive social cognitive training procedures as a psychosocial intervention for schizophrenia.

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Optimization methods have been used in many areas of knowledge, such as Engineering, Statistics, Chemistry, among others, to solve optimization problems. In many cases it is not possible to use derivative methods, due to the characteristics of the problem to be solved and/or its constraints, for example if the involved functions are non-smooth and/or their derivatives are not know. To solve this type of problems a Java based API has been implemented, which includes only derivative-free optimization methods, and that can be used to solve both constrained and unconstrained problems. For solving constrained problems, the classic Penalty and Barrier functions were included in the API. In this paper a new approach to Penalty and Barrier functions, based on Fuzzy Logic, is proposed. Two penalty functions, that impose a progressive penalization to solutions that violate the constraints, are discussed. The implemented functions impose a low penalization when the violation of the constraints is low and a heavy penalty when the violation is high. Numerical results, obtained using twenty-eight test problems, comparing the proposed Fuzzy Logic based functions to six of the classic Penalty and Barrier functions are presented. Considering the achieved results, it can be concluded that the proposed penalty functions besides being very robust also have a very good performance.