48 resultados para Goodness


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A utilização de funções matemáticas para descrever o crescimento animal é antiga. Elas permitem resumir informações em alguns pontos estratégicos do desenvolvimento ponderal e descrever a evolução do peso em função da idade do animal. Também é possível comparar taxas de crescimento de diferentes indivíduos em estados fisiológicos equivalentes. Os modelos de curvas de crescimento mais utilizados na avicultura são os derivados da função Richards, pois apresentam parâmetros que possibilitam interpretação biológica e portanto podem fornecer subsídios para seleção de uma determinada forma da curva de crescimento em aves. Também pode-se utilizar polinômios segmentados para descrever as mudanças de tendência da curva de crescimento animal. Entretanto, existem importantes fatores de variação para os parâmetros das curvas, como a espécie, o sistema de criação, o sexo e suas interações. A adequação dos modelos pode ser verificada pelos valores do coeficiente de determinação (R2), do quadrado médio do resíduo (QM res), do erro de predição médio (EPm), da facilidade de convergência dos dados e pela possibilidade de interpretação biológica dos parâmetros. Estudos envolvendo modelagem e descrição da curva de crescimento e seus componentes são amplamente discutidos na literatura. Porém, programas de seleção que visem a progressos genéticos para a forma da curva não são mencionados. A importância da avaliação dos parâmetros dos modelos de curvas de crescimento é ainda mais relevante já que os maiores ganhos genéticos para peso estão relacionados com seleção para pesos em idades próximas ao ponto de inflexão. A seleção para precocidade pode ser auxiliada com base nos parâmetros do modelo associados à variáveis que descrevem esta característica genética dos animais. Esses parâmetros estão relacionados a importantes características produtivas e reprodutivas e apresentam magnitudes diferentes, de acordo com a espécie, o sexo e o modelo utilizados na avaliação. Outra metodologia utilizada são os modelos de regressão aleatória, permitindo mudanças graduais nas covariâncias entre idades ao longo do tempo e predizendo variâncias e covariâncias em pontos contidos ao longo da trajetória estudada. A utilização de modelos de regressões aleatórias traz como vantagem a separação da variação da curva de crescimento fenotípica em seus diferentes efeitos genético aditivo e de ambiente permanente individual, mediante a determinação dos coeficientes de regressão aleatórios para esses diferentes efeitos. Além disto, não há necessidade de utilizar fatores de ajuste para a idade. Esta revisão teve por objetivos levantar os principais modelos matemáticos frequentistas utilizados no estudo de curvas de crescimento de aves, com maior ênfase nos empregados com a finalidade de estimar parâmetros genéticos e fenotípicos.

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A body of research has developed within the context of nonlinear signal and image processing that deals with the automatic, statistical design of digital window-based filters. Based on pairs of ideal and observed signals, a filter is designed in an effort to minimize the error between the ideal and filtered signals. The goodness of an optimal filter depends on the relation between the ideal and observed signals, but the goodness of a designed filter also depends on the amount of sample data from which it is designed. In order to lessen the design cost, a filter is often chosen from a given class of filters, thereby constraining the optimization and increasing the error of the optimal filter. To a great extent, the problem of filter design concerns striking the correct balance between the degree of constraint and the design cost. From a different perspective and in a different context, the problem of constraint versus sample size has been a major focus of study within the theory of pattern recognition. This paper discusses the design problem for nonlinear signal processing, shows how the issue naturally transitions into pattern recognition, and then provides a review of salient related pattern-recognition theory. In particular, it discusses classification rules, constrained classification, the Vapnik-Chervonenkis theory, and implications of that theory for morphological classifiers and neural networks. The paper closes by discussing some design approaches developed for nonlinear signal processing, and how the nature of these naturally lead to a decomposition of the error of a designed filter into a sum of the following components: the Bayes error of the unconstrained optimal filter, the cost of constraint, the cost of reducing complexity by compressing the original signal distribution, the design cost, and the contribution of prior knowledge to a decrease in the error. The main purpose of the paper is to present fundamental principles of pattern recognition theory within the framework of active research in nonlinear signal processing.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Sorption isotherms were determined for salted alligator's meat at four different temperatures (10degreesC, 15degreesC, 25degreesC and 35degreesC), using a standard gravimetric method. The goodness of fit of five sorption models to experimental data was determined. Five models, namely the GAB, the BET, the Halsey, the Henderson and the Hailwood and Horrobin, were evaluated to determine the best fit for the experimental data. The GAB was the best fitted model for the data of salted alligator's meat with an average error less than 10% for temperature of 10degreesC and less than 5% for the others temperatures. The coefficients of determination (r(2)) were 0.99 for all temperatures considered. The monolayer values decreased as temperature increased. The other four models were not appropriated to fit the data because of the high error values, although the r(2) were also similar to the GAB model. The net isosteric heat of sorption was estimated from equilibrium sorption data, using the Clausis-Clapeyron equation. Isosteric heats of sorption were found to increase with increasing temperature and could be well adjusted by an exponential relationship. (C) 2002 Elsevier B.V. Ltd. All rights reserved.

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Aerodynamic balances are employed in wind tunnels to estimate the forces and moments acting on the model under test. This paper proposes a methodology for the assessment of uncertainty in the calibration of an internal multi-component aerodynamic balance. In order to obtain a suitable model to provide aerodynamic loads from the balance sensor responses, a calibration is performed prior to the tests by applying known weights to the balance. A multivariate polynomial fitting by the least squares method is used to interpolate the calibration data points. The uncertainties of both the applied loads and the readings of the sensors are considered in the regression. The data reduction includes the estimation of the calibration coefficients, the predicted values of the load components and their corresponding uncertainties, as well as the goodness of fit.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Our aim was to investigate the population fluctuation and the damage caused by the phytophagous mites Calacarus heveae Feres, Tenuipalpus heveae Baker, and Eutetranychus banksi (McGregor) on clones FX 2784, FX 3864, and MDF 180 in rubber tree crops from southeastern Bahia, Brazil. Moreover, we tested for the influence of climatic variables on occurrence patterns of these species throughout weekly samples performed from October to April. The infestation peaks was between mid-January and late February. The clones FX 2784 and FX 3864 had the highest infestations and more severe damage possibly caused by C. heveae, which was the most frequent and abundant species in all clones. We found that sunlight duration and rainfall were the most important factors for C. heveae while T. heveae was affected by rainfall and temperature. Eutetranychus banksi was only affected by sunlight duration. However, the best models had low goodness of fit. We concluded that the clones FX 2784 and FX 3864 had a higher susceptibility to mite attack, and the association between climatic variables and favorable physiological conditions were determinant for the population increase of the species from January to April. © 2012 Sociedade Entomológica do Brasil.

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A total of 61,528 weight records from 22,246 Nellore animals born between 1984 and 2002 were used to compare different multiple-trait analysis methods for birth to mature weights. The following models were used: standard multivarite model (MV), five reduced-rank models fitting the first 1, 2, 3, 4 and 5 genetic principal components, and five models using factor analysis with 1, 2, 3, 4 and 5 factors. Direct additive genetic random effects and residual effects were included in all models. In addition, maternal genetic and maternal permanent environmental effects were included as random effects for birth and weaning weight. The models included contemporary group as fixed effect and age of animal at recording (except for birth weight) and age of dam at calving as linear and quadratic effects (for birth weight and weaning weight). The maternal genetic, maternal permanent environmental and residual (co)variance matrices were assumed to be full rank. According to model selection criteria, the model fitting the three first principal components (PC3) provided the best fit, without the need for factor analysis models. Similar estimates of phenotypic, direct additive and maternal genetic, maternal permanent environmental and residual (co)variances were obtained with models MV and PC3. Direct heritability ranged from 0.21 (birth weight) to 0.45 (weight at 6 years of age). The genetic and phenotypic correlations obtained with model PC3 were slightly higher than those estimated with model MV. In general, the reduced-rank model substantially decreased the number of parameters in the analyses without reducing the goodness-of-fit. © 2013 Elsevier B.V.

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Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross-bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations (MLOG); a linear model without transformation of the observations (MLIN); and a generalized linear Poisson model with residual term (MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 ± 0.02, 0.10 ± 0.02 and 0.14 ± 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion (DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick-resistant animals. © 2013 Blackwell Verlag GmbH.

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The main objective of this study is to verify the influence of Environmental Management (EM) on Operational Performance (OP) in Brazilian automotive companies, analyzing whether Lean Manufacturing (LM) and Human Resources (HR) interfere in the greening of these companies. Therefore, a conceptual framework listing these concepts was proposed, and three research hypotheses were presented. A questionnaire was elaborated based on this theoretical background and sent to respondents occupying the highest positions in the production/operations areas of Brazilian automotive companies. The data, collected from 75 companies, were analyzed using structural equation modeling. The main results are as follows: (a) the model tested revealed an adequate goodness of fit, showing that overall, the relations proposed between EM and OP and between HR, LM and EM tend to be statistically valid; (b) EM tends to influence OP in a positive and statistically weak manner; (c) LM has a greater influence on EM when compared to the influence HR has over EM; (d) HR has a positive relationship over EM, but the statistical significance of this relationship is less than that of the other evaluated relationships. The originality of this paper lies in its gathering the concepts of EM, LM, HR and OP in a single study, as they generally tend not to be treated jointly. This paper also provided valid empirical evidence for a littlestudied context: the Brazilian automotive sector. © 2012 Elsevier Ltd. All rights reserved.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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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)