Purpose: the purpose of this study is to investigate how managers working for the General Authority for Irrigation and Reclamation Projects react to the impact of Emotional Intelligence (EI) on their performance.   Theoretical framework: The current study includes an intellectual framework on two variables, namely EI and Manager Performance (MP), because it is essential to investigate the relationship between these two variables and the impact of EI on MP.   Design/methodology/approach: The research problem is that a manager's capacity to make wise decisions about their work or interactions with subordinates is diminished when they have inadequate EI. The questionnaire is used as a tool for gathering data for the study, and the st

The financial crises that occurred in South East Asia and America, and the discovery of the financial and administrative corruption that affected these companies, which led to the crisis. Since then, organizations and institutions interested in accounting have begun new ways to further rationalize the management of these companies. Hence the concept of governance, which means good governance. Al-Susiya confirmed its adoption of the financial reporting standards and adopted internal and external auditing for the purpose of increasing the reliability and credibility of the financial and reports that increase the confidence of investors in making their investment decisions in the financial markets The study dealt with the contributi

The estimation of the parameters of Two Parameters Gamma Distribution in case of missing data has been made by using two important methods: the Maximum Likelihood Method and the Shrinkage Method. The former one consists of three methods to solve the MLE non-linear equation by which the estimators of the maximum likelihood can be obtained: Newton-Raphson, Thom and Sinha methods. Thom and Sinha methods are developed by the researcher to be suitable in case of missing data. Furthermore, the Bowman, Shenton and Lam Method, which depends on the Three Parameters Gamma Distribution to get the maximum likelihood estimators, has been developed. A comparison has been made between the methods in the experimental aspect to find the best meth

In this paper we suggest new method to estimate the missing data  in bivariate normal distribution and compare it with Single Imputation  method (Unconditional mean and Conditional mean) by using simulation. 

مشكلة البحث واهميته:

نتيجة لما يشهده قطاع التربية من تغير كبير وتطور سريع, فقد اتجه تخطيط السياسة التعليمية في القطر نحو تحديد كفاءة النظام التعليمي بمختلف مراحله كونها اجزاء متداخلة في تركيب تنظيمي واحد(9: 3 ) . وذلك من اجل استمرار تطويره, وتوجيهه بما يتفق واحداث المرحلة ومتطلباتها, على اساس ان مخرجات كل مرحلة تعليمية من مراحله المتتابعة تمثل المدخلات الجديدة لمرحلة تعليمية لاحقة.

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Multiple sclerosis (MS) is a chronic, inflammatory demyelinating disease of central nervous system with complex etiopathogenesis that impacts young adults (Lee et al., 2015), and MS impacts younger and middle aged character and leads to a range of disabilities that can alter their daily routines (Yara et al, 2010). Although, the exact cause of MS is still undetermined, the disease is mediated by adaptive immunity through the infiltration of T cells into the central nervous system (Bjelobaba et al, 2017). MS causes the Focal neurological symptomsand biochemical changes in the molecular level and the variation of neural cells such as loss or alteration of sensation, motor function, visible signs such as blurred vision or transient blindness,

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial