The linear multiregression dynamic model (LMDM) is a Bayesian dynamic model which preserves any conditional independence and causal structure across a multivariate time series. The conditional independence structure is used to model the multivariate series by separate (conditional) univariate dynamic linear models, where each series has contemporaneous variables as regressors in its model. Calc...

this paper presents a control model of the hydroforming and the dual hydroforming process of atube. the theoretical part includes calculations to measure the change in tube thickness through thedeveloped process. the hydroforming and the dual hydroforming processes are simulated in thesolidsimulation software and the static and the dynamic simulations are modeled. theobtained results for the t-...

The choice network revenue management model incorporates customer purchase behavior as a function of the offered products, and is the appropriate model for airline and hotel network revenue management, dynamic sales of bundles, and dynamic assortment optimization. The optimization problem is a stochastic dynamic program and is intractable. A certainty-equivalence relaxation of the dynamic progr...

Generalized linear mixed models (GLMM) are useful in a variety of applications. With surrogate covariate data, existing methods of inference for GLMM are usually computationally intensive. We propose a two-step inference procedure for GLMM with missing covariate data. It is shown that the proposed estimator is consistent and asymptotically normal with covariance matrix that can be easily estima...

State-of-the-art video deblurring methods cannot handle blurry videos recorded in dynamic scenes, since they are built under a strong assumption that the captured scenes are static. Contrary to the existing methods, we propose a video deblurring algorithm that can deal with general blurs inherent in dynamic scenes. To handle general and locally varying blurs caused by various sources, such as m...

In this paper the dynamic behavior of linear induction motor is described by a mathematical model taking into account the end effects and the core losses. The need for such a model rises due to the complexity of linear induction motors electromagnetic field theory. The end affects by introducing speed dependent scale factor to the magnetizing inductance and series resistance in the d-axis equiv...

Various linear models may be specified when attempting to estimate an apparent linear trend in real data sets, based on assumptions about the possibly unknown mechanism for generating the data. However, in many cases the best-fit line obtained from implementation of the specified model does not agree at all with the apparent trend in a scatterplot of the data, based on the evident geometric str...

We study the market partition between two distinct firms that deliver services to waiting-time sensitive customers. In our model, the incoming customers select a firm on the basis of its posted price, the expected waiting time and its brand. More specifically, we quantify by a cost any departure from the ideal brand expected by each incoming customer. Considering that the two underlying queuein...