This paper aims to explain the effect of workplace respect on employee performance at Abu Ghraib Dairy Factory (AGDF). For achieving the research aim, the analytical and descriptive approach was chosen using a questionnaire tool for collecting data.  It covers 22 items; ten of them for the workplace respect variable and twelve items for the employee performance variable. The research population involved human resources who work at AGDF in Baghdad within two administrative levels (top and middle). We conducted a purposive stratified sample approach. It was distributed 70 questionnaire forms, and 65 forms were received. However, six of them had missing data and did not include in the final data analysis. The main results are t

 This paper is concerned with preliminary test single stage shrinkage estimators for the mean (q) of normal distribution with known variance s2 when a prior estimate (q0) of the actule value (q) is available, using specifying shrinkage weight factor y( ) as well as pre-test region (R).         Expressions for the Bias, Mean Squared Error [MSE( )] and Relative Efficiency [R.Eff.( )] of proposed estimators are derived. Numerical results and conclusions are drawn about selection different constants including in these expressions. Comparisons between suggested estimators with respect to usual estimators in the sense of Relative Efficiency are given. Furthermore, comparisons with the earlier existi

Throughout this paper R represents a commutative ring with identity and all R-modules M are unitary left R-modules. In this work we introduce the notion of S-maximal submodules as a generalization of the class of maximal submodules, where a proper submodule N of an R-module M is called S-maximal, if whenever W is a semi essential submodule of M with N ? W ? M, implies that W = M. Various properties of an S-maximal submodule are considered, and we investigate some relationships between S-maximal submodules and some others related concepts such as almost maximal submodules and semimaximal submodules. Also, we study the behavior of S-maximal submodules in the class of multiplication modules. Farther more we give S-Jacobson radical of ri

A laboratory experiment was carried out in the laboratories of College of Agricultural Engineering Sciences, University of Baghdad in 2017. Three factors were studied; Sorghum bicolor L. cultivars (Inqath, Rabeh and Buhoth70), primed and unprimed seed, and salt stress (0, 6, 9 and 12 dS.m−1). The aim was to improve germination and seedling growth under salt stress. The results showed significant superiority of Buhoth70 cultivar compared to others, significantly superiority of primed seed compared to the unprimed and significant negative impact as long as increasing levels of salt stress at germination ratio, plumule length, dry seedling weight and seedling vigor index. The interaction between cultivars, priming and salt stress showed that

In this research, the covariance estimates were used to estimate the population mean in the stratified random sampling and combined regression estimates. were compared by employing the robust variance-covariance matrices estimates with combined regression estimates by employing the traditional variance-covariance matrices estimates when estimating the regression parameter, through the two efficiency criteria (RE) and mean squared error (MSE). We found that robust estimates significantly improved the quality of combined regression estimates by reducing the effect of outliers using robust covariance and covariance matrices estimates (MCD, MVE) when estimating the regression parameter. In addition, the results of the simulation study proved

Five samples of the ternary alloy Ge-S-Cd were created using the melting point method, and the effects of partially substituting cadmium for germanium were determined. and partial substitution of germanium by cadmium was used to study the change in electrical conductivity. Electrical experiments were performed on Ge_35-xS₆₅Cd_xternary alloy with x = 0, 5, 10, 15, and 20. It was discovered that the conductivity (σ_dc) rises with rising temperature in all samples under experiment. This confirms that the samples have semiconductor behavior. It has been observed that there are three regions of electrical conductivity in the electrical conductivity curve at low, moderate, and high temperatures. The pr

Throughout this paper R represents commutative ring with identity and M is a unitary left R-module. The purpose of this paper is to investigate some new results (up to our knowledge) on the concept of weak essential submodules which introduced by Muna A. Ahmed, where a submodule N of an R-module M is called weak essential, if N ? P ? (0) for each nonzero semiprime submodule P of M. In this paper we rewrite this definition in another formula. Some new definitions are introduced and various properties of weak essential submodules are considered.

The concept of the Extend Nearly Pseudo Quasi-2-Absorbing submodules was recently introduced by Omar A. Abdullah and Haibat K. Mohammadali in 2022, where he studies this concept and it is relationship to previous generalizationsm especially  2-Absorbing submodule and Quasi-2-Absorbing submodule, in addition to studying the most important Propositions, charactarizations and Examples. Now in this research, which is considered a continuation of the definition that was presented earlier, which is the Extend Nearly Pseudo Quasi-2-Absorbing submodules, we have completed the study of this concept in multiplication modules. And the relationship between the Extend Nearly Pseudo Quasi-2-Absorbing submodule and Extend Nearly Pseudo Quasi-2-Abs

     Coronavirus disease (COVID-19), which is caused by SARS-CoV-2, has been announced as a global pandemic by the World Health Organization (WHO), which results in the collapsing of the healthcare systems in several countries around the globe. Machine learning (ML) methods are one of the most utilized approaches in artificial intelligence (AI) to classify COVID-19 images. However, there are many machine-learning methods used to classify COVID-19. The question is: which machine learning method is best over multi-criteria evaluation? Therefore, this research presents benchmarking of COVID-19 machine learning methods, which is recognized as a multi-criteria decision-making (MCDM) problem. In the recent century, the trend of developing