876 resultados para Modeling Rapport Using Hidden Markov Models


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The purpose of this study was to evaluate the effect of using different mathematical models to describe the relationship between treadmill running speed and time to exhaustion. All models generated a value for an aerobic parameter (critical speed; S(critical)). 35 university students performed 5-7 constant-speed 0%-slope treadmill tests at speeds that elicited exhaustion in similar to 3 min to similar to 10 min. Speed and time data were fitted using 3 models: (1) a 2-parameter hyperbolic model; (2) a 3-parameter hyperbolic model; and (3) a hybrid 3-parameter hyperbolic + exponential model. The 2-parameter model generated values for S(critical) (mean (+/- SD): 186 +/- 33 m.min(-1)) and anaerobic distance capacity (ADC; 251 +/- 122 m) with a high level of statistical certainty (i.e., with small SEEs). The 3-parameter models generated parameter estimates that were unrealistic in magnitude and/or associated with large SEEs and little statistical certainty. Therefore, it was concluded that, for the range of exercise durations used in the present study, the 2-parameter model is preferred because it provides a parsimonious description of the relationship between velocity and time to fatigue, and it produces parameters of known physiological significance, with excellent confidence.

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Weight records of Brazilian Nelore cattle, from birth to 630 d of age, recorded every 3 mo, were analyzed using random regression models. Independent variables were Legendre polynomials of age at recording. The model of analysis included contemporary groups as fixed effects and age of dam as a linear and quadratic covariable. Mean trends were modeled through a cubic regression on orthogonal polynomials of age. Up to four sets of random regression coefficients were fitted for animals' direct and maternal, additive genetic, and permanent environmental effects. Changes in measurement error variances with age were modeled through a variance function. Orders of polyno-mial fit from three to six were considered, resulting in up to 77 parameters to be estimated. Models fitting random regressions modeled the pattern of variances in the data adequately, with estimates similar to those from corresponding univariate analysis. Direct heritability estimates decreased after birth and tended to be lowest at ages at which maternal effect estimates tended to be highest. Maternal heritability estimates increased after birth to a peak around 110 to 120 d of age and decreased thereafter. Additive genetic direct correlation estimates between weights at standard ages (birth, weaning, yearling, and final weight) were moderate to high and maternal genetic and environmental correlations were consistently high. © 2001 American Society of Animal Science. All rights reserved.

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Purpose - The aim of this paper is to present a synthetic chart based on the non-central chi-square statistic that is operationally simpler and more effective than the joint X̄ and R chart in detecting assignable cause(s). This chart will assist in identifying which (mean or variance) changed due to the occurrence of the assignable causes. Design/methodology/approach - The approach used is based on the non-central chi-square statistic and the steady-state average run length (ARL) of the developed chart is evaluated using a Markov chain model. Findings - The proposed chart always detects process disturbances faster than the joint X̄ and R charts. The developed chart can monitor the process instead of looking at two charts separately. Originality/value - The most important advantage of using the proposed chart is that practitioners can monitor the process by looking at only one chart instead of looking at two charts separately. © Emerald Group Publishing Limted.

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In this paper is presented a region-based methodology for Digital Elevation Model segmentation obtained from laser scanning data. The methodology is based on two sequential techniques, i.e., a recursive splitting technique using the quad tree structure followed by a region merging technique using the Markov Random Field model. The recursive splitting technique starts splitting the Digital Elevation Model into homogeneous regions. However, due to slight height differences in the Digital Elevation Model, region fragmentation can be relatively high. In order to minimize the fragmentation, a region merging technique based on the Markov Random Field model is applied to the previously segmented data. The resulting regions are firstly structured by using the so-called Region Adjacency Graph. Each node of the Region Adjacency Graph represents a region of the Digital Elevation Model segmented and two nodes have connectivity between them if corresponding regions share a common boundary. Next it is assumed that the random variable related to each node, follows the Markov Random Field model. This hypothesis allows the derivation of the posteriori probability distribution function whose solution is obtained by the Maximum a Posteriori estimation. Regions presenting high probability of similarity are merged. Experiments carried out with laser scanning data showed that the methodology allows to separate the objects in the Digital Elevation Model with a low amount of fragmentation.

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Discriminative training of Gaussian Mixture Models (GMMs) for speech or speaker recognition purposes is usually based on the gradient descent method, in which the iteration step-size, ε, uses to be defined experimentally. In this letter, we derive an equation to adaptively determine ε, by showing that the second-order Newton-Raphson iterative method to find roots of equations is equivalent to the gradient descent algorithm. © 2010 IEEE.

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Carpolobia lutea leaves (CLL) (Polygalaceae) were earlier screened and the antiulcer ethnomedicinal claim established. This article seeks to quantitatively isolate, elucidate the active compounds from most active CLL fraction. Fractionation was by semi-preparative HPLC; the active fraction was subjected to radical scavenging assays (RSA) and quantification of the total phenolic content (TPC) were also executed. Results: Ethyl acetate fraction (EAF) was observed to be the most pharmacologically active antiulcer fraction when screened using acute ulcer models induced in rodents. The EAF demonstrated significant (p < 0.05-0.001) antiulcer activity in various in vivo induced ulceration models by reducing the ulcer index and increasing the preventive ratio. The EAF demonstrated > 70% in TPC and < 20 % in RSA. Cinnamic and coumaric acids derivatives were isolated from EAF. Cinnamic acids have been implicated and patented as antiulcer agent. Isolated compounds could in part mediate the observed pharmacological activities which lend credence to its ethnobotanical uses.

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Includes bibliography

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

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Engenharia e Ciência de Alimentos - IBILCE

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Zootecnia - FCAV

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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)