Spatial data observed on a group of areal units is common in scientific applications. The usual hierarchical approach for modeling this kind of dataset is to introduce a spatial random effect with an autoregressive prior. However, the usual Markov chain Monte Carlo scheme for this hierarchical framework requires the spatial effects to be sampled from their full conditional posteriors one-by-one resulting in poor mixing. More importantly, it makes the model computationally inefficient for datasets with large number of units. In this article, we propose a Bayesian approach that uses the spectral structure of the adjacency to construct a low-rank expansion for modeling spatial dependence. We propose a pair of computationally efficient estimati

Deep drawing process to produce square cup is very complex process due to a lot of process parameters which control on this process, therefore associated with it many of defects such as earing, wrinkling and fracture. Study of the effect of some process parameters to determine the values of these parameters which give the best result, the distributions for the thickness and depths of the cup were used to estimate the effect of the parameters on the cup numerically, in addition to experimental verification just to the conditions which give the best numerical predictions in order to reduce the time, efforts and costs for producing square cup with less defects experimentally is the aim of this study. The numerical analysis is used to study

In this research was the study of a single method of estimation and testing parameters mediating variables (Mediation) in a specimen structural equations SEM a bootstrap method, for the purpose of application of the integrated survey of the situation Marital data and health mirror Iraqi (I-WISH) for the year 2011 from the Ministry of Planning - device Central Bureau of Statistics, and applied to the appropriate data from the terms of the data to a form of structural equation SEM using factor analysis affirmative (Confirmatory Factor analysis) CFA As a way to see the match variables that make up the model, and after confirming the model matching or suitability are having the effect of variables mediation in the model tested by the

This paper describes DC motor speed control based on optimal Linear Quadratic Regulator (LQR) technique. Controller's objective is to maintain the speed of rotation of the motor shaft with a particular step response.The controller is modeled in MATLAB environment, the simulation results show that the proposed controller gives better performance and less settling time when compared with the traditional PID controller.

The research objective was to study the amount of lost fluids, some blood components and mineral salts in volleyball players under hot weather conditions. The sample of the present study was composed of 12 volleyball players of Al-Sinaa Club (Baghdad, Iraq) in the 2022/2023 season. The variables analyzed in this study were: Heart rate before and after exercise, internal and external body temperature before and after exertion, potassium ion, sodium ion, calcium ion, and the amount of fluid lost (the player's weight) before and after the exercise. The tests were conducted at a temperature between 42-47 degrees Celsius. The maximum anaerobic exercise was performed with volleyball. The results showed that to play volleybal

The research objective was to study the amount of lost fluids, some blood components and mineral salts in volleyball players under hot weather conditions. The sample of the present study was composed of 12 volleyball players of Al-Sinaa Club (Baghdad, Iraq) in the 2022/2023 season. The variables analyzed in this study were: Heart rate before and after exercise, internal and external body temperature before and after exertion, potassium ion, sodium ion, calcium ion, and the amount of fluid lost (the player's weight) before and after the exercise. The tests were conducted at a temperature between 42-47 degrees Celsius. The maximum anaerobic exercise was performed with volleyball. The results showed that to play volleybal

Abstract:

The models of time series often suffer from the problem of the existence of outliers ​​that accompany the data collection process for many reasons, their existence may have a significant impact on the estimation of the parameters of the studied model. Access to highly efficient estimators  is one of the most important stages of statistical analysis, And it is therefore important to choose the appropriate methods to obtain good  estimators. The aim of this research is to compare the ordinary estimators and the robust estimators of the estimation of the parameters of

Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f