7 resultados para Computer input-output equipment.

em Scielo Saúde Pública - SP


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This paper examines the post-War industrialization process in the Brazilian State of Minas Gerais, focusing on one of its desirable outcomes, namely the capacity to generate growth through the impact of strong input-output linkages. This process is placed into historical perspective considering the ideas that permeate the economic development debate throughout the period of analysis. Changes in the regional economic structure are assessed through the use of three input-output tables for the years of 1953, 1980 and 1995. By adopting the fields of influence methodology as the analytical core, it is shown that the efforts towards the creation of a more integrated regional economy have generated stronger influence of the targeted sectors (metal products, transportation equipment, chemical, and services). However, structural changes also contributed to strengthen leakage in the system originated in traditional economic activities.

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Em média, os salários no Brasil são onerados em 42,5% do seu valor bruto, somando-se a parte que é descontada do salário do trabalhador com a que incide sobre a folha de pagamentos das empresas. Isso torna o país uma das economias que mais tributam rendimentos do trabalho assalariado no mundo. O maior ônus sobre os salários recai sobre as empresas, estimulando práticas como a contratação de empregados sem carteira de trabalho assinada e a terceirização, fazendo da informalidade um dos elementos determinantes dos crescentes déficits do INSS. A folha de pagamentos é tributada em média em 35%, sendo a contribuição previdenciária o tributo de maior peso. Após diagnosticar o problema, este texto discute aspectos relacionados aos regimes previdenciários e as bases de incidência adequadas a cada um deles. Mostra ainda que o regime geral da previdência no Brasil assumiu conotação de política pública de renda complementar. Nesse sentido, propõe-se a substituição do INSS patronal, uma base restrita, por uma contribuição de 0,61% sobre as movimentações nas contas-correntes bancárias, uma base universal, e compara os efeitos sobre a economia de um tributo cumulativo com os produzidos por um imposto sobre o valor agregado. Utilizando o modelo de input-output de Leontief como mecanismo de análise, o trabalho revela que uma contribuição sobre as transações bancárias implica menor carga tributária sobre os preços setoriais e menor distorção alocativa que os 20% cobrados sobre a folha de salários das empresas para o INSS. Por fim, o texto procura desmistificar a crítica envolvendo a cumulatividade tributária.

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Non-linear functional representation of the aerodynamic response provides a convenient mathematical model for motion-induced unsteady transonic aerodynamic loads response, that accounts for both complex non-linearities and time-history effects. A recent development, based on functional approximation theory, has established a novel functional form; namely, the multi-layer functional. For a large class of non-linear dynamic systems, such multi-layer functional representations can be realised via finite impulse response (FIR) neural networks. Identification of an appropriate FIR neural network model is facilitated by means of a supervised training process in which a limited sample of system input-output data sets is presented to the temporal neural network. The present work describes a procedure for the systematic identification of parameterised neural network models of motion-induced unsteady transonic aerodynamic loads response. The training process is based on a conventional genetic algorithm to optimise the network architecture, combined with a simplified random search algorithm to update weight and bias values. Application of the scheme to representative transonic aerodynamic loads response data for a bidimensional airfoil executing finite-amplitude motion in transonic flow is used to demonstrate the feasibility of the approach. The approach is shown to furnish a satisfactory generalisation property to different motion histories over a range of Mach numbers in the transonic regime.

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The formal calibration procedure of a phase fraction meter is based on registering the outputs resulting from imposed phase fractions at known flow regimes. This can be straightforwardly done in laboratory conditions, but is rarely the case in industrial conditions, and particularly for on-site applications. Thus, there is a clear need for less restrictive calibration methods regarding to the prior knowledge of the complete set of inlet conditions. A new procedure is proposed in this work for the on-site construction of the calibration curve from total flown mass values of the homogeneous dispersed phase. The solution is obtained by minimizing a convenient error functional, assembled with data from redundant tests to handle the intrinsic ill-conditioned nature of the problem. Numerical simulations performed for increasing error levels demonstrate that acceptable calibration curves can be reconstructed, even from total mass measured within a precision of up to 2%. Consequently, the method can readily be applied, especially in on-site calibration problems in which classical procedures fail due to the impossibility of having a strict control of all the input/output parameters.

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The present study aimed at evaluating the use of Artificial Neural Network to correlate the values resulting from chemical analyses of samples of coffee with the values of their sensory analyses. The coffee samples used were from the Coffea arabica L., cultivars Acaiá do Cerrado, Topázio, Acaiá 474-19 and Bourbon, collected in the southern region of the state of Minas Gerais. The chemical analyses were carried out for reducing and non-reducing sugars. The quality of the beverage was evaluated by sensory analysis. The Artificial Neural Network method used values from chemical analyses as input variables and values from sensory analysis as output values. The multiple linear regression of sensory analysis values, according to the values from chemical analyses, presented a determination coefficient of 0.3106, while the Artificial Neural Network achieved a level of 80.00% of success in the classification of values from the sensory analysis.

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The aim of this work was to evaluate the energy flows of a commercial production system of swine deep bed in its finishing phase, located in Juiz de Fora, in the State of Minas Gerais, Brazil. Thus, an energy efficiency study was carried out by monitoring a lot of animals, during a 94-day period. The energy rate of each compound involved in the production process was quantified and the matrixes of energy consumption were determined in the form of animal feeding, electrical energy, piglets, material used as deep bed, human labor, equipment, swine buildings, production of alive swine for slaughter, organic fertilizer production (swine deep bed or swine deep litter). From the direct input energy, 80.57% correspond to animal feeding, 11.90% to pigs for slaughter and 6.76% to piglets, while from the energy output 53.45% correspond to the terminating swine and 46.55% to organic fertilizer (swine deep bed). By the results obtained, we can conclude that such production system has corresponded to an industrial and highly specialized agro ecosystem, importing a great part of the energy consumed in the production process, with 41% of energy efficiency.

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The present study shows the development, simulation and actual implementation of a closed-loop controller based on fuzzy logic that is able to regulate and standardize the mass flow of a helical fertilizer applicator. The control algorithm was developed using MATLAB's Fuzzy Logic Toolbox. Both open and closed-loop simulations of the controller were performed in MATLAB's Simulink environment. The instantaneous deviation of the mass flow from the set point (SP), its derivative, the equipment´s translation velocity and acceleration were all used as input signals for the controller, whereas the voltage of the applicator's DC electric motor (DCEM) was driven by the controller as output signal. Calibration and validation of the rules and membership functions of the fuzzy logic were accomplished in the computer simulation phase, taking into account the system's response to SP changes. The mass flow variation coefficient, measured in experimental tests, ranged from 6.32 to 13.18%. The steady state error fell between -0.72 and 0.13g s-1 and the recorded average rise time of the system was 0.38 s. The implemented controller was able to both damp the oscillations in mass flow that are characteristic of helical fertilizer applicators, and to effectively respond to SP variations.