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 main work of this paper is devoted to a new technique of constructing approximated solutions for linear delay differential equations using the basis functions power series functions with the aid of Weighted residual methods (collocations method, Galerkin’s method and least square method).

Environmental pollution is experiencing an alarming surge within the global ecosystem, warranting urgent attention. Among the significant challenges that demand immediate resolution, effective treatment of industrial pollutants stands out prominently, which for decades has been the focus of most researchers for sustainable industrial development aiming to remove those pollutants and recover some of them. The liquid membrane (LM) method, specifically electromembrane extraction (EME), offers promise. EME deploys an electric field, reducing extraction time and energy use while staying eco-friendly. However, there's a crucial knowledge gap. Despite strides in understanding and applying EME, optimizing it for diverse industrial pollutant

Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener

Abstract

The multiple linear regression model of the important regression models used in the analysis for different fields of science Such as business, economics, medicine and social sciences high in data has undesirable effects on analysis results . The multicollinearity is a major problem in multiple linear regression. In its simplest state, it leads to the departure of the model parameter that is capable of its scientific properties, Also there is an important problem in regression analysis is the presence of high leverage points in the data have undesirable effects on the results of the analysis , In this research , we present some of

The research study includes shedding light on the sas dance in Iraq, as it is one of the popular legacies that are rich in the Mesopotamian civilization and because of the different practices it has in the different occasions on which these dances are held. Which is one of the kinetic arts widespread among the classes of Iraqi society. The researcher explained its features and artistic content that characterizes Iraqi music. The (methodological framework) reviewed the justification, importance and purpose of the research, and the limits of the research that included the (National Troupe of Folk Art) as a human limit to discover the artistic methods of the Sas dance and then define the terms of the search. The "theoretical framework" cont

We propose two simple, rapid, and convenient spectrophotometric methods which are described for the determination of cephalexin in bulk and its pharmaceutical preparations. They are based on the measurement of the flame atomic emission of potassium ion (in the first method) and colorimetric determination of the green colored solution at 610 nm formed after the reaction of cephalexin with potassium permanganate as an oxidant agent (in the second method) in basic medium. The working conditions of the methods are investigated and optimized. Beer's law plot shows a good correlation in the concentration range of 5-40?g ml-1. The detection limits are 2.573,2.814 ?g ml-1 for the flame emission photometric method and 1.844,2.016 ?g ml-1 for colo

Chromatographic and spectrophotometric methods for the estimation of mebendazole in
pharmaceutical products were developed. The flow injection method was based on the oxidation of
mebendazole by a known excess of sodium hypochlorite at pH=9.5. The excess sodium hypochlorite is then
reacted with chloranilic acid (CAA) to bleach out its color. The absorbance of the excess CAA was recorded
at 530 nm. The method is fast, simple, selective, and sensitive. The chromatographic method was carried out
on a Varian C18 column. The mobile phase was a mixture of acetonitrile (ACN), methanol (MeOH), water
and triethylamine (TEA), (56% ACN, 20% MeOH, 23.5% H2O, 0.5% TEA, v/v), adjusted to pH = 3.0 with
1.0 M hy

The main focus of research is on how to achieve the internal and external dimensions of corporate social responsibility through human resources management strategies, which is a major of research aimed. The main problem of this research was confirmed, which confirms that there is an unclear role for social responsibility, lack of human resources management strategies, and ambiguity of roles in the municipality under study. The diagnose of the problem and determining the gap between the internal and external dimensions of social responsibility and human resources management was identified, which attacked the researcher's attention to navigate in this subject, look for the reasons for the gaps and try to reduce them. The case study