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.
The present work is an attempt to develop design data for an Iraqi roof and wall constructions using the latest ASHRAE Radiant Time Series (RTS) cooling load calculation method. The work involves calculation of cooling load theoretically by introducing the design data for Iraq, and verifies the results experimentally by field measurements. Technical specifications of Iraqi construction materials are used to derive the conduction time factors that needed in RTS method calculations. Special software published by Oklahoma state university is used to extract the conduction factors according to the technical specifications of Iraqi construction materials. Good agreement between the average theoretical and measured cooli
... Show MoreEfficient operations and output of outstanding quality distinguish superior manufacturing sectors. The manufacturing process production of bending sheet metal is a form of fabrication in the industry of manufacture in which the plate is bent using punches and dies to the angle of the work design. Product quality is influenced by plate material selection, which includes thickness, type, dimensions, and material. Because no prior research has concentrated on this methodology, this research aims to determine V-bending capacity limits utilizing the press bending method. The inquiry employed finite element analysis (FEA), along with Solidworks was the tool of choice to develop drawings of design and simulations. The ASTM E290
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The risk of significant concern is resistance to antibiotics for public health. The alternative treatment of metallic nanoparticles (NPs), such as heavy metals, effects on antibiotic resistance bacteria with different types of antibiotics of - impossible to treat using noval eco-friendly synthesis technique nanoparticles copper oxide (CuO NPs) preparation from S. epidermidis showed remarkable antimicrobial activity against S.aureus Minimum inhibitory concentra range (16,32,64,256,512) µg/ml via well diffusion method in vitro, discover those concentrations effected in those bacteria and the best concentration is 64 µg/ml, characterization CuO NPs to prove this included atomic force microscope, UV, X-ray Diffraction and TEM, and ant
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature
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In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen
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Citric acid is an essential ingredient for the manufacture of (12) key industrial chemicals. Citric acid use is increasing steadily with a high annual growth rate as a result of the development of ever more sophisticated applications. Citric acid is widely utilized in the food and pharmaceutical industries due to its low toxicity when compared to other acidulous. Other uses for citric acid can be found in cleaning supplies and detergents. Based on information from a review of the literature, Citric acid production substrates and methods for surface fermentation, submerged fermentation, solid-state fermentation, and international market expansion are all covered in the current review study. Finally, there is still much to learn about the
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This work presents a canned-food defect-detection method using the EfficientDet model with four backbones (MobileNet, EfficientNet, Swin-T, and ConvNeXt). The dataset included 8046 images with a resolution of 512 × 512 pixels. The performance criteria in this study accuracy “mAP”, computational cost “FLOPs”, and Frames Per Second “FPS”. The lightweight backbone with EfficientDet achieves a mean Average Precision (mAP) of 90% with MobileNet, while EfficientNet achieves mAP accuracy of 92% and 94%. The heavy backbone for EfficientDet (Swin-T, and ConvNeXt) achieves mAP accuracy of 96% and 98%. The main contribution of this study is to optimize the speed of conveyor belts in industrial production lines to considers the
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