The educational service industry is one of the most negatively affected industries by the spread of the COVID-19 pandemic. Government agencies have taken many measures to slow its spread, and then restrict movement and gatherings and stop recreational activities. Furthermore, the repercussions of the curfew had a significant impact due to the interruption in actual attendance for students and employees, and the severity of the Covid-19 crisis and its (economic, social, security, humanitarian and behavioral) effects on all societies and work sectors is no secret to anyone. Iraq, like other countries, was also affected by the negative impact of Covid-19 pandemic in all fields of institutional work, especially public fields, and specifically the field of education, given that It is based on the necessity for the administration to maintain the continuity of workers’ commitment to perform their duties, which raised the possibility of them being exposed to greater levels of pressure and workload due to the requirements to adhere to the new work procedures as specified by the crisis cell, such as full curfew and social distancing measures to preserve health, and since workers represent the lifeline of any an organization, managing and dealing with them was considered to be highly important because despite the lack of material and financial resources in business, employees remain one of the key assets that administrations of organizations must take care of and ensure the quality of their practical life and careers, not only during crises but at all times, by striving to satisfy them in order to maintain their organizational loyalty. These changes in work methods and procedures have likely had an impact on the performance and commitment of employees. Therefore, employee satisfaction has become one of the important topics that need examination and testing in light of crises in general and the COVID-19 crisis in particular. The global health crisis forced institutions to expedite the formulation of plans and a response strategy with little guidance as a result of the unprecedented nature of the epidemic, and then there was an impact on the predetermined factors that might have affected the satisfaction of employees in various institutions, especially service institutions whose work required them to continue providing services and complete work. In addition, the previously less relevant factors have become prevalent due to the nature of the pandemic; for example, the topics of job insecurity, unemployment and health risks have been identified as the most serious consequences of the epidemic globally. This research came to examine the level of job satisfaction of employees working in the educational institution (the University of Baghdad as a model) and its relationship to the degree of their organizational loyalty in light of the COVID 19 pandemic based on the knowledge generated by reviewing the literature that was used to identify the key factors that affect employee’s satisfaction and hence the degree of loyalty to his\her organization, and the foundational idea that employee’s satisfaction affects the overall performance level of the organization is based on several factors, including the degree of employee loyalty and devotion to work, thus, maintaining an adequate level of job satisfaction for employees is one of the key factors in maintaining effective organizational performance for any organization. In light of the changes that took place in the methods and procedures of institutional work in light of the COVID-19 pandemic, it became important to unveil the positive and negative factors that affected the job satisfaction of employees and then their organizational loyalty to achieve further organizational progress and improvement and then improve the overall performance of the organization. thus came this research to focus on analyzing the relationship between employee satisfaction and organizational loyalty during the COVID-19 pandemic, and for that reason, we developed questionnaires to identify job satisfaction and organizational loyalty at the job level for employees of the educational institution, the University of Baghdad (Colleges of Education for Girls and Science for Girls) in light of the COVID-19 pandemic. The study included (279) employees from the Colleges of Education for Girls and the College of Science for Girls, with a rate of (135) (144) employees, respectively. Employee satisfaction was considered an independent variable, and organizational loyalty was considered a dependent variable. Reliability tests, correlation analysis and regression were conducted to prove the research hypotheses, and the results of the research showed that satisfied employees tend to be more loyal and devoted to the organization and contribute positively to improving organizational performance. Furthermore, at the time of the outbreak of the COVID-19 pandemic, employees in the field of educational services at the University of Baghdad.
Transient drop in the heart beat or transient heart block (AVB) may be consider the main cause of syncope or presyncope inpatients with bifascicular block and syncope According to the Guidelines for cardiac pacing pacemaker consider part of treatment. Aims of our study were to evaluate whether there is role for EPS in patients BFB and to evaluate the symptoms after pacing. 42 patients were enrolled in this study, with mean age value (63.4± 12.2years), suffer from interventricular conductive defect and syncope; patients underwent EPS on admission time, and pacemaker implantation accordingly and programmed follow up for the device in the last four years. Our patients were 25 (59.5%) male and 17 (40.5%)female, all of them with syncope o
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This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conc
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In the present study, activated carbon supported metal oxides was prepared for thiophene removal from model fuel (Thiophene in n-hexane) using adsorptive desulfurization technique. Commercial activated carbon was loaded individually with copper oxide in the form of Cu2O/AC. A comparison of the kinetic and isotherm models of the sorption of thiophene from model fuel was made at different operating conditions including adsorbent dose, initial thiophene concentration and contact time. Various adsorption rate constants and isotherm parameters were calculated. Results indicated that the desulfurization was enhanced when copper was loaded onto activated carbon surface. The highest desulfurization percent for Cu2O/AC and o
... Show MoreThe hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s
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<p>In combinatorial testing development, the fabrication of covering arrays is the key challenge by the multiple aspects that influence it. A wide range of combinatorial problems can be solved using metaheuristic and greedy techniques. Combining the greedy technique utilizing a metaheuristic search technique like hill climbing (HC), can produce feasible results for combinatorial tests. Methods based on metaheuristics are used to deal with tuples that may be left after redundancy using greedy strategies; then the result utilization is assured to be near-optimal using a metaheuristic algorithm. As a result, the use of both greedy and HC algorithms in a single test generation system is a good candidate if constructed correctly. T
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This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.
Two-dimensional unsteady mixed convection in a porous cavity with heated bottom wall is numerically studied in the present paper. The forced flow conditions are imposed by providing a hydrostatic pressure head at the inlet port that is located at the bottom of one of the vertical side walls and an open vent at the top of the other vertical side wall. The Darcy model is adopted to model the fluid flow in the porous medium and the combination effects of hydrostatic pressure head and the heat flux quantity parameters are carefully investigated. These governing parameters are varied over wide ranges and their effect on the heat transfer characteristics is studied in detail. It is found that the time required to reach a desired temperature at th
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