Based on the theoretical review of researches and studies concerned with virtual teams in organizations, it was found that the role of virtual teams varies from case to another, and it may be positive or opposite. The purpose of the current research is to examine the role of virtual teams in the impact of cultural intelligence on the strategic excellence of Zain worldwide Group. An electronic questionnaire was designed through the (Google) and (Microsoft) forms, and distributed then on a sample of (146) participants with a high organizational level of the HRM departments within the group. The results showed that there was a positive moderator role of virtual teams in the relationship of cultural intelligence and strategic excellence

The current research aimed to identify psychological stability and its relationship to university integration and spiritual intelligence among university students. The research sample consisted of (158) students from the College of Education - Al-Mustansiriya University.

A scale was applied: psychological stability, university integration, and spiritual intelligence,   and by using the (Pearson) correlation coefficient, and the t-test, the results showed: the sample members enjoy psychological stability, university integration, and spiritual intelligence, and there is a positive, statistically significant correlation between the research variables, and the results resulted in some recommendations and proposals.

The emphasis of Master Production Scheduling (MPS) or tactic planning is on time and spatial disintegration of the cumulative planning targets and forecasts, along with the provision and forecast of the required resources. This procedure eventually becomes considerably difficult and slow as the number of resources, products and periods considered increases. A number of studies have been carried out to understand these impediments and formulate algorithms to optimise the production planning problem, or more specifically the master production scheduling (MPS) problem. These algorithms include an Evolutionary Algorithm called Genetic Algorithm, a Swarm Intelligence methodology called Gravitational Search Algorithm (GSA), Bat Algorithm (BAT), T

This research aims to find out the relationship of risk behavior & job satisfaction for workers in the emergency program in the international relief agency (UNRWA) in the Gaza Strip and the level of each of them, and to achieve that we have been conducting research on the strength of "210" sample employees of the emergency program staff in the international relief agency in Gaza governorates, and try to answer the research questions the researcher through the use of measurements of risk behavior and job satisfaction are two of the researcher, The researcher has used several statistical methods to identify the validity and reliability of scales and access to research and interpretations of the results, and these methods: the m

The research aimed to prepare a measure of job stressors affecting the quality of teaching performance in the College of Physical Education and Sports Sciences at the University of Baghdad, to identify their levels, if any, and the most influential dimensions on the quality of teaching performance within the college’s work environment, as well as the deanship’s ability to help prevent and Alleviating its severity through logical administrative methods, on a scale that includes four dimensions that include (the administrative and financial environment, the organizational environment, the social and humanitarian environment, and the scientific and research environment). The descriptive approach was adopted using the case study met

Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial