48 resultados para programming Task


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Background: The time synchronization is a very important ability for the acquisition and performance of motor skills that generate the need to adapt the actions of body segments to external events of the environment that are changing their position in space. Down Syndrome (DS) individuals may present some deficits to perform tasks with synchronization demand. We aimed to investigate the performance of individuals with DS in a simple Coincident Timing task. Method. 32 individuals were divided into 2 groups: the Down syndrome group (DSG) comprised of 16 individuals with average age of 20 (+/- 5 years old), and a control group (CG) comprised of 16 individuals of the same age. All individuals performed the Simple Timing (ST) task and their performance was measured in milliseconds. The study was conducted in a single phase with the execution of 20 consecutive trials for each participant. Results: There was a significant difference in the intergroup analysis for the accuracy adjustment - Absolute Error (Z = 3.656, p = 0.001); and for the performance consistence - Variable Error (Z = 2.939, p = 0.003). Conclusion: DS individuals have more difficulty in integrating the motor action to an external stimulus and they also present more inconsistence in performance. Both groups presented the same tendency to delay their motor responses. © 2013 Torriani-Pasin et al.; licensee BioMed Central Ltd.

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Goal Programming (GP) is an important analytical approach devised to solve many realworld problems. The first GP model is known as Weighted Goal Programming (WGP). However, Multi-Choice Aspirations Level (MCAL) problems cannot be solved by current GP techniques. In this paper, we propose a Multi-Choice Mixed Integer Goal Programming model (MCMI-GP) for the aggregate production planning of a Brazilian sugar and ethanol milling company. The MC-MIGP model was based on traditional selection and process methods for the design of lots, representing the production system of sugar, alcohol, molasses and derivatives. The research covers decisions on the agricultural and cutting stages, sugarcane loading and transportation by suppliers and, especially, energy cogeneration decisions; that is, the choice of production process, including storage stages and distribution. The MCMIGP allows decision-makers to set multiple aspiration levels for their problems in which the more/higher, the better and the less/lower, the better in the aspiration levels are addressed. An application of the proposed model for real problems in a Brazilian sugar and ethanol mill was conducted; producing interesting results that are herein reported and commented upon. Also, it was made a comparison between MCMI GP and WGP models using these real cases. © 2013 Elsevier Inc.

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In this study, a novel approach for the optimal location and contract pricing of distributed generation (DG) is presented. Such an approach is designed for a market environment in which the distribution company (DisCo) can buy energy either from the wholesale energy market or from the DG units within its network. The location and contract pricing of DG is determined by the interaction between the DisCo and the owner of the distributed generators. The DisCo intends to minimise the payments incurred in meeting the expected demand, whereas the owner of the DG intends to maximise the profits obtained from the energy sold to the DisCo. This two-agent relationship is modelled in a bilevel scheme. The upper-level optimisation is for determining the allocation and contract prices of the DG units, whereas the lower-level optimisation is for modelling the reaction of the DisCo. The bilevel programming problem is turned into an equivalent single-level mixed-integer linear optimisation problem using duality properties, which is then solved using commercially available software. Results show the robustness and efficiency of the proposed model compared with other existing models. As regards to contract pricing, the proposed approach allowed to find better solutions than those reported in previous works. © The Institution of Engineering and Technology 2013.