952 resultados para Legendre polynomial


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Um total de 19.770 pesos corporais de bovinos Guzerá, do nascimento aos 365 dias de idade, pertencentes ao banco de dados da Associação Brasileira dos Criadores de Zebu (ABCZ) foi analisado com os objetivos de comparar diferentes estruturas de variâncias residuais, considerando 1, 18, 28 e 53 classes residuais e funções de variância de ordens quadrática a quíntica; e estimar funções de co-variância de diferentes ordens para os efeitos genético aditivo direto, genético materno, de ambiente permanente de animal e de mãe e parâmetros genéticos para os pesos corporais usando modelos de regressão aleatória. Os efeitos aleatórios foram modelados por regressões polinomiais em escala de Legendre com ordens variando de linear a quártica. Os modelos foram comparados pelo teste de razão de verossimilhança e pelos critérios de Informação de Akaike e de Informação Bayesiano de Schwarz. O modelo com 18 classes heterogêneas foi o que melhor se ajustou às variâncias residuais, de acordo com os testes estatísticos, porém, o modelo com função de variância de quinta ordem também mostrou-se apropriado. Os valores de herdabilidade direta estimados foram maiores que os encontrados na literatura, variando de 0,04 a 0,53, mas seguiram a mesma tendência dos estimados pelas análises unicaracterísticas. A seleção para peso em qualquer idade melhoraria o peso em todas as idades no intervalo estudado.

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The objective of this study was to evaluate animal performance and carcass characteristics of 64 Nellore young bulls at 22 months of age finished in a feedlot and slaughtered at five body weights (350; 455; 485; 555 and 580 kg) fed diets containing coated or uncoated urea. The experimental design adopted was completely randomized, set in a 4 × 2 factorial arrangement, and for the variables assessed in the control animals, it was 5 × 2. No effect of interaction between slaughter weights and diets were observed, so the variables were analyzed separately, compared by polynomial contrasts and by the F test, respectively. The time animals remained in the feedlot to reach slaughter weights was 66, 88, 145 and 194 days. Average daily gain (ADG) showed quadratic behavior, with a maximum of 1.44 kg/day with animals of 491.7 kg. Dry matter intake (DMI) (kg/day) was similar in all the treatments, but it decreased linearly as body weight increased. The bionutritional efficiency worsened linearly as body weight rose. The elevation in slaughter weight resulted in linear decrease in the percentage of beef round and increase in forequarter. Backfat thickness and rib eye area of the longissimus increased linearly and the percentages of muscle and protein in the carcass reduced and those of fat and ether extract increased linearly as body weight increased. Average daily gain, DMI, feed efficiency and carcass characteristics were not affected by diets containing coated or uncoated urea. However, animals fed coated urea presenter better crude fiber and neutral detergent fiber intake.

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

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The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

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O trabalho teve como objetivo verificar a influência da adubação orgânica em 6 épocas de crescimento na produção de β-ecdisona por plantas de Pfaffia glomerata. O experimento foi conduzido na Fazenda Santo Antonio do Araquá, distrito de Catâneo Ângelo, município de São Manuel, São Paulo, Brasil. Utilizou-se o delineamento de blocos ao acaso, num esquema fatorial 5x6, com quatro repetições, considerando-se 8 plantas úteis por parcela. Os blocos foram constituídos de 6 épocas de crescimento (60, 120, 180, 240, 300 e 360 dias após a germinação) e de 5 doses de esterco de galinha curtido [testemunha (sem adubação), 15, 30, 45 e 60 t ha-1]. Após cada colheita, as raízes das plantas foram secas em estufa com circulação de ar forçada a 40ºC e pesadas para posterior extração do β-ecdisona, seguindo metodologia desenvolvida por Magalhães (2000). Os resultados foram submetidos à análise de variância e ao teste de separação de médias de Scott Knott, todos a 5% de probabilidade. Quando ocorreu interação os resultados foram avaliados usando-se análise de regressão polinominal. O teor de β-ecdisona não foi influenciado pelas doses de adubo e nem pela época do crescimento das plantas. Porém a quantidade total de β-ecdisona por raiz foi influenciada pela época de crescimento, sendo que aos 360 dias após a emergência ocorreu uma maior quantidade do princípio ativo em todos os tratamentos. Apesar de não diferir estatisticamente dos demais tratamentos, aos 360 dias após a emergência das plantas, o tratamento 30 t ha-1 foi o que proporcionou maior quantidade de β-ecdisona.

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This work presents a modelling and identification method for a wheeled mobile robot, including the actuator dynamics. Instead of the classic modelling approach, where the robot position coordinates (x,y) are utilized as state variables (resulting in a non linear model), the proposed discrete model is based on the travelled distance increment Delta_l. Thus, the resulting model is linear and time invariant and it can be identified through classical methods such as Recursive Least Mean Squares. This approach has a problem: Delta_l can not be directly measured. In this paper, this problem is solved using an estimate of Delta_l based on a second order polynomial approximation. Experimental data were colected and the proposed method was used to identify the model of a real robot

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This paper presents an evaluative study about the effects of using a machine learning technique on the main features of a self-organizing and multiobjective genetic algorithm (GA). A typical GA can be seen as a search technique which is usually applied in problems involving no polynomial complexity. Originally, these algorithms were designed to create methods that seek acceptable solutions to problems where the global optimum is inaccessible or difficult to obtain. At first, the GAs considered only one evaluation function and a single objective optimization. Today, however, implementations that consider several optimization objectives simultaneously (multiobjective algorithms) are common, besides allowing the change of many components of the algorithm dynamically (self-organizing algorithms). At the same time, they are also common combinations of GAs with machine learning techniques to improve some of its characteristics of performance and use. In this work, a GA with a machine learning technique was analyzed and applied in a antenna design. We used a variant of bicubic interpolation technique, called 2D Spline, as machine learning technique to estimate the behavior of a dynamic fitness function, based on the knowledge obtained from a set of laboratory experiments. This fitness function is also called evaluation function and, it is responsible for determining the fitness degree of a candidate solution (individual), in relation to others in the same population. The algorithm can be applied in many areas, including in the field of telecommunications, as projects of antennas and frequency selective surfaces. In this particular work, the presented algorithm was developed to optimize the design of a microstrip antenna, usually used in wireless communication systems for application in Ultra-Wideband (UWB). The algorithm allowed the optimization of two variables of geometry antenna - the length (Ls) and width (Ws) a slit in the ground plane with respect to three objectives: radiated signal bandwidth, return loss and central frequency deviation. These two dimensions (Ws and Ls) are used as variables in three different interpolation functions, one Spline for each optimization objective, to compose a multiobjective and aggregate fitness function. The final result proposed by the algorithm was compared with the simulation program result and the measured result of a physical prototype of the antenna built in the laboratory. In the present study, the algorithm was analyzed with respect to their success degree in relation to four important characteristics of a self-organizing multiobjective GA: performance, flexibility, scalability and accuracy. At the end of the study, it was observed a time increase in algorithm execution in comparison to a common GA, due to the time required for the machine learning process. On the plus side, we notice a sensitive gain with respect to flexibility and accuracy of results, and a prosperous path that indicates directions to the algorithm to allow the optimization problems with "η" variables

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A modelagem de processos industriais tem auxiliado na produção e minimização de custos, permitindo a previsão dos comportamentos futuros do sistema, supervisão de processos e projeto de controladores. Ao observar os benefícios proporcionados pela modelagem, objetiva-se primeiramente, nesta dissertação, apresentar uma metodologia de identificação de modelos não-lineares com estrutura NARX, a partir da implementação de algoritmos combinados de detecção de estrutura e estimação de parâmetros. Inicialmente, será ressaltada a importância da identificação de sistemas na otimização de processos industriais, especificamente a escolha do modelo para representar adequadamente as dinâmicas do sistema. Em seguida, será apresentada uma breve revisão das etapas que compõem a identificação de sistemas. Na sequência, serão apresentados os métodos fundamentais para detecção de estrutura (Modificado Gram- Schmidt) e estimação de parâmetros (Método dos Mínimos Quadrados e Método dos Mínimos Quadrados Estendido) de modelos. No trabalho será também realizada, através dos algoritmos implementados, a identificação de dois processos industriais distintos representados por uma planta de nível didática, que possibilita o controle de nível e vazão, e uma planta de processamento primário de petróleo simulada, que tem como objetivo representar um tratamento primário do petróleo que ocorre em plataformas petrolíferas. A dissertação é finalizada com uma avaliação dos desempenhos dos modelos obtidos, quando comparados com o sistema. A partir desta avaliação, será possível observar se os modelos identificados são capazes de representar as características estáticas e dinâmicas dos sistemas apresentados nesta dissertação

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Information retrieval is of paramount importance in all areas of knowledge. Regarding the temperatures of Natal, they were simulated and analyzed. Thus, it was possible to recover, with some accuracy, the temperatures of days they were not collected. For this we constructed a software that displays the temperature value at each moment in the city. The program was developed in Delphi using interpolated polynomial function of third degree. The equations were obtained in Excel and data were collected at the Instituto Nacional de Pesquisas Espaciais (INPE). These functions were changed from a correction factor in order to provide values to temperatures between those who were not collected. Armed with this program you can build tables and charts to analyze the temperatures for certain periods of time. The same analysis was done by developing mathematical functions that describes the temperatures. With the data provided by this software is possible to say which are the hours of highest and lowest temperatures in the city, as the months have indexes with the highest and lowest temperatures.

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

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The present study investigates how the inter-relationship of the content of polynomial equations works with structured activities and with the history of mathematics through a sequence of activities presented in an e-book, so that the result of this research will proceed will result in a didactic and pedagogic proposal for the teaching of polynomial equations in a historical approach via the reported e-book. Therefore, we have considered in theoretical and methodological assumptions of the History of Mathematics, in structured activities and new technologies with an emphasis on e-book tool. We used as a methodological approach the qualitative research, as our research object adjusts to the objectives of this research mode. As methodological instruments, we used the e-book as a synthesis tool of the sequence of activities to be evaluated, while the questionnaires, semi-structured interviews and participant observation were designed to register and analyze the evaluation made by the research, participants in the structured activities. The processing and analysis of data collected though the questionnaires were organized, classified and quantified in summary tables to facilitate visualization, interpretation, understanding, and analysis of these data. As for participant observation was used to contribute to the qualitative analysis of the quantified data. The interviews were synthetically transcribed and qualitatively analyzed. The analysis ratified our research objectives and contributed to improve, approve and indicate the use of e-book for the teaching of polynomial equations. Thus, we consider that this educational product will bring significant contributions to the teaching of mathematical content, in Basic Education

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The stability of multistep second derivative methods for integro-differential equations is examined through a test equation which allows for the construction of the associated characteristic polynomial and its region of stability (roots in the unit circle) at a proper parameter space. (c) 2004 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.