981 resultados para Auto-identidade
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The 1988 constitution makes an life is a supreme good when increased health as the fundamental condition requiring that all ill patient has the right to be treated in a public hospital (CF, art. 196). In this sense, the goal of this work is to generate a weekly forecast of hospital care by means of an advanced prediction model. It is expected that the model of self-regressivas seasonal moving averages SARIMA generate reliable and adherent to issue forecasts analyzed, thus enabling better resource allocation and more efficient hospital management
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This research aims to investigate the consequences of a possible change caused by the social context in the life and behavior of the main characters in the novel Blindness, [by José Saramago]. Starting by that there is an allegorical correlation between the blindness white, discussed by Saramago in his novel and the construction of the Plato's Cave Myth, and taking as theoretical basis the reflections of some thinkers such as Stuart Hall (1992), Goffman (2002) and Antonio da Costa Ciampa (2005) it be sought to describe the occurrence of the phenomenon the social role change in the characters and its consequences to the identity deconstruction of fictional subjects
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The national truck fleet has expanded strongly in recent decades. However, due to fluctuations in the demand that the market is exposed, it needed up making more effective strategic decisions of automakers. These decisions are made after an evaluation of guaranteed sales forecasts. This work aims to generate an annual forecast of truck production by Box and Jenkins methodology. They used annual data for referring forecast modeling from the year 1957 to 2014, which were obtained by the National Association of Motor Vehicle Manufacturers (Anfavea). The model used was Autoregressive Integrated Moving Average (ARIMA) and can choose the best model for the series under study, and the ARIMA (2,1,3) as representative for conducting truck production forecast
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Considering the high competitiveness in the industrial chemical sector, demand forecast is a relevant factor for decision-making. There is a need for tools capable of assisting in the analysis and definition of the forecast. In that sense, the objective is to generate the chemical industry forecast using an advanced forecasting model and thus verify the accuracy of the method. Because it is time series with seasonality, the model of seasonal autoregressive integrated moving average - SARIMA generated reliable forecasts and acceding to the problem analyzed, thus enabling, through validation with real data improvements in the management and decision making of supply chain
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The automobile industry shows relevance inside the Brazilian industrial scenario since it contributes with the development of a significant chain of supply, distributors, workshops, publicity agencies and insurance companies in the internal market, aside from being one of the five biggest worldwide market. Thereby, the federal government decreed in Dec, 17th 2012 by Law nº 12.715 the Inovar-Auto Program. As the Adjusted Present Value (APV) is highly recommended, although not yet widespread to public politics of tax reduction, this work intends to apply the APV method on the cash flow analysis of an automobile sector's company, which has recently installed in national territory and wants to rely with governmental incentives proposed by Inovar-Auto Program. The developed work evaluates the company's current cash flow stochastically from mathematical modeling of variables such as price, demand and interest rate through probability distributions with the assist of Crystal Ball software, a Microsoft Excel Add-in, generating different scenarios from Monte Carlo Simulation. As results probabilities situations have been evaluated until the end of the Inovar-Auto's conducted period, in 2017. Beside APV others indicator such as Internal Rate of Return (IRR) and payback period were estimated for the investment project. For APV a sampling distribution with only 0.057% of risk, IRR of 29% were obtained and estimated project payback period was 4.13 years