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.
Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre
... Show MoreFractal image compression depends on representing an image using affine transformations. The main concern for researches in the discipline of fractal image compression (FIC) algorithm is to decrease encoding time needed to compress image data. The basic technique is that each portion of the image is similar to other portions of the same image. In this process, there are many models that were developed. The presence of fractals was initially noticed and handled using Iterated Function System (IFS); that is used for encoding images. In this paper, a review of fractal image compression is discussed with its variants along with other techniques. A summarized review of contributions is achieved to determine the fulfillment of fractal ima
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The study aims to build a water quality index that fits the Iraqi aquatic systems and reflects the environmental reality of Iraqi water. The developed Iraqi Water Quality Index (IQWQI) includes physical and chemical components. To build the IQWQI, Delphi method was used to communicate with local and global experts in water quality indices for their opinion regarding the best and most important parameter we can use in building the index and the established weight of each parameter. From the data obtained in this study, 70% were used for building the model and 30% for evaluating the model. Multiple scenarios were applied to the model inputs to study the effects of increasing parameters. The model was built 4 by 4 until it reached 17 parame
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Abstract: Residual ridge resorption is chronic, progressive, irreversible and cumulative condition associated with teeth loss. Management of a residual ridge with severe resorption to fulfill the patient’s esthetic and functional requirements is quite difficult for the practitioner and also in the construction of an acceptable appliance. As the height of the edentulous ridge reduces the mandibular denture will be improperly function. Severe resorption of the mandibular alveolar ridge may cause instability and discomfort of the convention acrylic resin denture. Dealing with this condition requires clinical skills and knowledge. Treating the severely resorbed mandibular ridge is a challenging effort for prosthodontics. This research present
... Show MoreKE Sharquie, AA Noaimi, WK Al-Janabi, Journal of Cosmetics, Dermatological Sciences and Applications, 2013
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci
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In this paper two ranking functions are employed to treat the fuzzy multiple objective (FMO) programming model, then using two kinds of membership function, the first one is trapezoidal fuzzy (TF) ordinary membership function, the second one is trapezoidal fuzzy weighted membership function. When the objective function is fuzzy, then should transform and shrinkage the fuzzy model to traditional model, finally solving these models to know which one is better
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With the recent developments of technology and the advances in artificial intelligent and machine learning techniques, it becomes possible for the robot to acquire and show the emotions as a part of Human-Robot Interaction (HRI). An emotional robot can recognize the emotional states of humans so that it will be able to interact more naturally with its human counterpart in different environments. In this article, a survey on emotion recognition for HRI systems has been presented. The survey aims to achieve two objectives. Firstly, it aims to discuss the main challenges that face researchers when building emotional HRI systems. Secondly, it seeks to identify sensing channels that can be used to detect emotions and provides a literature review
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In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from
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