142 resultados para linear rank regression model
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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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The purpose was to evaluate the reproductive performance of woolless ewes due to the feeding management of offsprings and weaning age in addition to measuring the effect of gender on weight gain of lambs. Sixty-four Santa Inês crossbred ewes were distributed in a completely randomized design in a factorial 4 x 2 x 2 - four weaning ages (56, 70, 84 and 98 days), sex and feeding management of the offspring, each treatment with four replications. The ewes were managed with the offsprings at the foot in 14 paddocks of 1,5 or 2,0 hectares, formed with Brachiaria humidícola. The offsprings were born by single birth, of Santa Inês pure of origin (PO). After the weaning of all groups, sixty-four lambs (32 males and 32 females) were randomly assigned in individual stalls and confined for 30 days. The comparison of the parameters was carried out by the adjustment of the simple linear regression model. It was verified over time addiction of the offspring feed management of + 3,7% (P<0,05) for the calving intervals and of + 1,4% (P<0,05) for the service period. There was increasing linear effect (P<0,05) of weaning age on calving intervals and service period. It was verified over time, addiction of the offspring sex of + 2,0% (P<0,05) for the calving intervals and + 0,8% (P<0,05) for the ewes service period. It was observed over time addiction of sex of + 35,2% and + 36,9% (P<0,05), respectively, for the daily weight gain of lambs from birth to weaning and post-weaning in feedlot. The supplementation of the offspring in private feeder and the anticipation of the weaning age reduce the calving intervals and the service period of woolless ewes in Brachiaria humidicula pasture. The offspring sex is the source of variation in the analysis of reproductive efficiency of ewe's mat rices and in the weight gain of Santa Inês crossbred lambs from birth to weaning, and after weaning.
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Leaf area estimate may contribute to understand the relationships of interference among weeds and crops. The objective of this research was to obtain a mathematical equation to estimate the leaf area of Euphorbia heterophylla based on linear measures of the leaf blade. Correlation studies were carried out using the real leaf area and leaf length (C) and the maximum leaf width (L) of 200 leaf blades which were collected from several agroecosystems at Universidade Estadual Paulista in Jaboticabal, SP, Brazil. The evaluated statistic models were: linear Y = a + bx; simple linear Y = bx; geometric Y = ax b; and exponential Y = ab x. All of the evaluated models can be used for E. heterophylla leaf area estimation. The simple linear regression model is suggested using C*L and taking the linear coefficient equal to zero. Thus, an estimate of the leaf area of E. heterophylla can be obtained using the equation Af' = 0.6816*(C*L).
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Data from reference stations are widely used in GNSS (Global Navigation Satellite System) positioning, and can be used in relative positioning or network-based positioning concept. Positioning accuracy will be directly influenced by errors in signals collected in these stations. In this paper, it is aimed at evaluating these data quality using temporal series of multipath index MP1 and MP2. A statistical study of temporal series with 7 years of daily observations related to 7 stations from RBMC (Rede Brasileira de Monitoramento Contínuo) was accomplished. In order to investigate trends and seasonality a linear regression model, correlograms, and Fourier periodograms were used. We also used a harmonic adjust to identify peaks on temporal series. At last, the possible causes of seasonality found in some stations were discussed. It was also possible to identify peaks in MP values of March and October months (mainly in stations located near geomagnetic equator).
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Pós-graduação em Engenharia Elétrica - FEIS
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Pós-graduação em Ciências Cartográficas - FCT
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In this work was developed a program capable of performing automatic counting of vehicles on roads. The problem of counting vehicles is using expensive techniques for its realization, techniques which often involve manual counting or degradation of the pavement. The main motivation for this work was the importance that the vehicle counting represents to the Traffic Engineer, being essential to analyze the performance of the roads, allowing to measure the need for installation of traffic lights, roundabouts, access ways, among other means capable of ensuring a continuous flow and safe for vehicles. The main objective of this work was to apply a statistical segmentation technique recently developed, based on a nonparametric linear regression model, to solve the segmentation problem of the program counter. The development program was based on the creation of three major modules, one for the segmentation, another for the tracking and another for the recognition. For the development of the segmentation module, it was applied a statistical technique combined with the segmentation by background difference, in order to optimize the process. The tracking module was developed based on the use of Kalman filters and application of simple concepts of analytical geometry. To develop the recognition module, it was used Fourier descriptors and a neural network multilayer perceptron, trained by backpropagation. Besides the development of the modules, it was also developed a control logic capable of performing the interconnection among the modules, mainly based on a data structure called state. The analysis of the results was applied to the program counter and its component modules, and the individual analysis served as a means to establish the par ameter values of techniques used. The find result was positive, since the statistical segmentation technique proved to be very useful and the developed program was able to count the vehicles belonging to the three goal..
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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A total of 3.035 lactations of Holstein cows from four farms in the Southeast, to check the influence of data structure of milk yield on the genetic parameters. Four dataset with different structures were tested, weekly controls (CW) with 122.842 controls, monthly controls (CM) 30.883, bimonthly controls (CB) with 15,837 and quarterly controls (CQ) with 12,702. The random regression model was used and was considered as random additive genetic and permanent environment effects, fixed effects of the contemporary groups (herd-year-month of test-day) and age of cow (linear and quadratic effects). Heritability estimates showed similar trends among the data files analyzed, with the greatest similarity between dataset CS, CM and CB. The dataset submitted all the CB estimates of genetic parameters analyzed with the same trend and similar magnitude to the CS and CM dataset, allowing the claim that there was no influence of the data structure on estimates of covariance components for the dataset CS, CM and CB. Thus, milk recording could be accomplished in a CB structure.
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A new mixed-integer linear programming (MILP) model is proposed to represent the plug-in electric vehicles (PEVs) charging coordination problem in electrical distribution systems. The proposed model defines the optimal charging schedule for each division of the considered period of time that minimizes the total energy costs. Moreover, priority charging criteria is taken into account. The steady-state operation of the electrical distribution system, as well as the PEV batteries charging is mathematically represented; furthermore, constraints related to limits of voltage, current and power generation are included. The proposed mathematical model was applied in an electrical distribution system used in the specialized literature and the results show that the model can be used in the solution of the PEVs charging problem.
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Pós-graduação em Fisiopatologia em Clínica Médica - FMB