945 resultados para MULTIVARIATE DISTRIBUTIONS


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Soft tissue damage has been observed in hip joints with pathological geometries. Our primary goal was to study the relationship between morphological variations of the bony components of the hip and resultant stresses within the soft tissues of the joint during routine daily activities. The secondary goal was to find the range of morphological parameters in which stresses are minimized. Computational models of normal and pathological joints were developed based on variations of morphological parameters of the femoral head (Alpha angle) and acetabulum (CE angle). The Alpha angle was varied between 40 degrees (normal joint) and 80 degrees (cam joint). The CE angle was varied between 0 degrees (dysplastic joint) and 40 degrees (pincer joint). Dynamic loads and motions for walking and standing to sitting were applied to all joint configurations. Contact pressures and stresses were calculated and crosscompared to evaluate the influence of morphology. The stresses in the soft tissues depended strongly on the head and acetabular geometry. For the dysplastic joint, walking produced high acetabular rim stresses. Conversely, for impinging joints, standing-to-sitting activities that involved extensive motion were critical, inducing excessive distortion and shearing of the tissue-bone interface. Zones with high von Mises stresses corresponded with clinically observed damage zones in the acetabular cartilage and labrum. Hip joint morphological parameters that minimized were 20 degrees

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Inventory policies provide instructions on how to calculate stock levels and order quantities. This paper examines the effect of the demand distribution on the performance of several well-known policies. Their performance is compared in terms of achieved service levels. As a conclusion from these comparisons, a nonparametric demand model is proposed to be used in inventory policies.

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Truncated distributions of the exponential family have great influence in the simulation models. This paper discusses the truncated Weibull distribution specifically. The truncation of the distribution is achieved by the Maximum Likelihood Estimation method or combined with the expectation and variance expressions. After the fitting of distribution, the goodness-of-fit tests (the Chi-Square test and the Kolmogorov-Smirnov test) are executed to rule out the rejected hypotheses. Finally the distributions are integrated in various simulation models, e. g. shipment consolidation model, to compare the influence of truncated and original versions of Weibull distribution on the model.