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

The research discusses the need to find the innovative structures and methodologies for developing Human Capital (HC) in Iraqi Universities. One of the most important of these structures is Communities of Practice (CoPs) which contributes to develop HC by using learning, teaching and training through the conversion speed of knowledge and creativity into practice. This research has been used the comparative approach through employing the methodology of Data Envelopment Analysis (DEA) by using (Excel 2010 - Solver) as a field evidence to prove the role of CoPs in developing HC. In light of the given information, a researcher adopted on an archived preliminary data about (23) colleges at Mosul University as a deliberate sample for t

Background: Generally, genetic disorders are a leading cause of spontaneous abortion, neonatal death, increased morbidity and mortality in children and adults as well. They a significant health care and psychosocial burden for the patient, the family, the healthcare system and the community as a whole. Chromosomal abnormalities occur much more frequently than is generally appreciated. It is estimated that approximately 1 of 200 newborn infants had some form of chromosomal abnormality. The figure is much higher in fetuses that do not survive to term. It is estimated that in 50% of first trimester abortions, the fetus has a chromosomal abnormality. Aim of the study: This study aims to shed some light on the results of chromosomal studies per

In the field of civil engineering, the adoption and use of Falling Weight Deflectometers (FWDs) is seen as a response to the ever changing and technology-driven world. Specifically, FWDs refer to devices that aid in evaluating the physical properties of a pavement. This paper has assessed the concepts of data processing, storage, and analysis via FWDs. The device has been found to play an important role in enabling the operators and field practitioners to understand vertical deflection responses upon subjecting pavements to impulse loads. In turn, the resultant data and its analysis outcomes lead to the backcalculation of the state of stiffness, with initial analyses of the deflection bowl occurring in conjunction with the measured or assum

In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.

The Atmospheric Infrared Sounder (AIRS) on EOS/Aqua satellite provides diverse measurements of Methane (CH₄) distribution at different pressure levels in the Earth's atmosphere. The focus of this research is to analyze the vertical variations of (CH₄) volume mixing ratio (VMR) time-series data at four Standard pressure levels SPL (925, 850, 600, and 300 hPa) in the troposphere above six cities in Iraq from January 2003 to September 2016. The analysis results of monthly average CH₄VMR time-series data show a significant increase between 2003 and 2016, especially from 2009 to 2016; the minimum values of CH₄ were in 2003 while the maximum values were in 2016. The vertical distribution of CH_4<