911 resultados para MINIMIZING EARLINESS
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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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Pós-graduação em Biopatologia Bucal - ICT
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Engenharia Elétrica - FEIS
Modelo de mensuração orçamentária dos custos de produção para uma indústria de manufatura de madeira
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The companies who produce goods and services taking of the demanding of the customers correctly use the management of the production. The verification of the costs decisive becomes. This article presents a model of measurement of the results of production for the elaborated budgetary planning for an industry of wooden manufacture. This research intends to evidence the importance of the planning and the budget. It presents main given the necessary ones to the budgetary methods, which are used by the company as instruments of control of the planning, providing the concentration of the efforts of the managers in the point-key, minimizing the tension in the process of decision taking.
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Pós-graduação em Agronomia (Horticultura) - FCA
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Pós-graduação em Matematica Aplicada e Computacional - FCT
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According to current legislation, is part of the Target of Special Education, students with high abilities/giftedness (HA/G). However, it appears that there are few studies on efficiency and effectiveness of diverse pedagogical practice for students with these characteristics. With increasing globalization, are multiplied opportunities for transnational education programs and educational services, particularly through the Internet, increasing the need for information services and accreditation of institutions and educational programs. This study aims to: a) develop a website containing information on high abilities/giftedness; b) evaluate the design of teachers on applicability of the site; c) analyze the contributions posted on the site. Therefore, it was available to the participants of this research produced site. Consisted on the site, among other information, those relating to HA/G indicators. Was sent a questionnaire via the Internet, with nine closed questions and two open, to 2000 teachers, registered in the database Improvement Course in Educational Practices Inclusive conducted by UNESP, under the coordination of Prof. Dr. Vera Lucia Messias Fialho Capellini. Data were considering frequency responses. For the treatment we used the Google Docs. As result Program Observed how teachers are lacking this subject deserves further Top depth. Concerning the site he was Considered by the participants as a support tool to the teacher, Which helps to identify and recognition of Individuals with HA/G and contributes to information, training and practical pedagogical way. This, is expected to Contribute to the dissemination of this issue in society as well as the Possibility of Minimizing the myths about this population, since such myths exist due to the lack of information
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Pós-graduação em Engenharia Elétrica - FEIS
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Pós-graduação em Direito - FCHS
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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The grinding operation gives workpieces their final finish, minimizing surface roughness through the interaction between the abrasive grains of a tool (grinding wheel) and the workpiece. However, excessive grinding wheel wear due to friction renders the tool unsuitable for further use, thus requiring the dressing operation to remove and/or sharpen the cutting edges of the worn grains to render them reusable. The purpose of this study was to monitor the dressing operation using the acoustic emission (AE) signal and statistics derived from this signal, classifying the grinding wheel as sharp or dull by means of artificial neural networks. An aluminum oxide wheel installed on a surface grinding machine, a signal acquisition system, and a single-point dresser were used in the experiments. Tests were performed varying overlap ratios and dressing depths. The root mean square values and two additional statistics were calculated based on the raw AE data. A multilayer perceptron neural network was used with the Levenberg-Marquardt learning algorithm, whose inputs were the aforementioned statistics. The results indicate that this method was successful in classifying the conditions of the grinding wheel in the dressing process, identifying the tool as "sharp''(with cutting capacity) or "dull''(with loss of cutting capacity), thus reducing the time and cost of the operation and minimizing excessive removal of abrasive material from the grinding wheel.