This study aims to examine the sources of organizational power prevailing among the academic leaders at the University of Tabuk from the faculty members’ viewpoint. The purposes behind such an aim are: to reveal the level of administrative and technical institutional creativity, the nature of the relationship between the reality of organizational power and the level of institutional creativity, and to disclose statistically the significant differences between the averages of faculty members’ responses attributed to the demographic variables (gender,  years of experience, academic degree). The study used the descriptive approach, both survey and correlational. A questionnaire was used to collect data from a simple random sample o

The Frankfurt School most prominent school of philosophical and social cash Contemporary directed cash centrally according to the cons of social and intellectual known to communities of European contemporary criticism of radical and profound concepts and values that founded this community (k rationality, liberty, scientific and technical progress), as was most of the thinkers seeking to one common goal is to work to change the reality to become more humane and find a picture of the mind that are commensurate with the human mind .as Although extinguished spark most of the patrons adults, but the ideas of philosophical and social cash continue to be under live and this is evidence of the vitality and strength of the impact and effe

Aim: The purpose of this study was to analyze the patterns of facial fractures in children and to compare them between preschool- and school-aged children. Materials and methods: This retrospective observational study included 57 children with facial fractures. The variables analyzed were the age of the patients—divided into a preschool-aged group (0–5 years) and a school-aged group (6–12 years)—gender, cause of trauma, the facial bones involved, the pattern of fracture, the modality of treatment used, the time between injury and treatment, and the postoperative complications. Results: The incidence of facial fractures in children ≤12 years was 30.2%. The patients consisted of 40 (70.2%) males and 17 (29.8%) females, and most pati

Research aims to know the impact beyond the defined in the collection. The research community is the second school students at Baghdad University and a research sample (63) students, the number of experimental group (27) students and a control group (30) students.  The researcher was rewarded in variable lifetime for students and educational attainment and educational level of the parents and the educational level of mothers. The researcher has developed a test took the number of paragraphs (20).  A test was true after it has been submitted to the Group of arbitrators. The test was consistent with test method used and the reliability coefficient (0, 88). Either the statistical methods used by the researcher are: Pearson correla

Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

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