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.
This encapsulates the general relationship between plant and bacteria in the natural and agricultural ecosystem. It is based on the activities of useful bacteria, such as plant growth-promoting bacteria (PGPRs) and nitrogen-fixing bacteria, in promoting plant growth and plant tolerance to stressful situations regarding pollution, salinity, and drought. The article also mentions that the bacteria maintain plant health by secretion of phytohormones, nitrogen fixation, solubilization of phosphate, and production of antibiotics against pathogenic bacteria. The article also mentions the existing applications of the interaction in sustainable agriculture and bioremediation of contaminated soils.
A field Experiment was carried out in Baghdad for the purpose of compare five horticulture machines during used two types of fuel deffirance in octane number, normal and super fuel which produced in Iraqi and measuring the vibrations transmitted of the three axes are longitudinal X , lateral Y and vertical Z from handlebar in (Mowers) to the operator which walks behind the mower, and the determine of the productivity practical of cutting, productivity passing and fuel consumption. Experiment Factorial used with two factors, The first factor was Five Mowers vary in width , types, weight and company manufacturer, The Second factor was the types of fuel used internal combination engine horticulture mowers were Normal fuel with Octane Number 82
... Show MoreRotational Piezoelectric Energy Harvesting (RPZTEH) is widely used due to mechanical rotational input power availability in industrial and natural environments. This paper reviews the recent studies and research in RPZTEH based on its excitation elements and design and their influence on performance. It presents different groups for comparison according to their mechanical inputs and applications, such as fluid (air or water) movement, human motion, rotational vehicle tires, and other rotational operational principal including gears. The work emphasises the discussion of different types of excitations elements, such as mass weight, magnetic force, gravity force, centrifugal force, gears teeth, and impact force, to show their effect
... Show MoreA substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.
... Show MoreEarly detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med
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