Many countries are very important in their interest not only in diversifying foreign reserves, but in determining and planning their volume in accordance with the goals set, namely facing potential external shocks, as the research aims to determine the extent of the strength of foreign reserves in the possession of the Central Bank in relation to every influential variable in the Iraqi economy. , in order to determine the minimum level of reserves that requires reconsideration of the exchange rate, as the research adopted the inductive analytical method in analyzing real (Quantitative data) for the research variables in the years of study, as the research adopted a set of analytical indicators approved by the International Moneta

              governance Is considered as one approach that gained the attention of many researchers in Management and politics field as one of the dominant philosophies and desired in the current period, became seen as a panacea for all diseases afflicting in particular public administrative organs in General ,This concept has been associated with concepts of reorganization Reforme besidc the administrative directed to improve the efficiency and effectiveness of the performance of such devices as reflected on the totality of features and characteristics that relate to service fulfillment needs of beneficiaries and underlying phenomenon, there was also a constituent charact

تعد الحوكمة من المداخل التي نالت اهتمام العديد من الباحثين والدارسين في مجال الإدارة والسياسة بوصفها إحدى الفلسفات السائدة والمرغوبة في الفترة الحالية , وأصبح ينظر إليها دواء لجميع الامراض التي تعاني منها الأجهزة الإدارية عموماً بالأخص العامة منها . وقد ارتبط هذا المفهوم بمفاهيم إعادة التنظيم Reforme والاصلاح الإداري المجه لتحسين كفاءة وفاعلية أداء تلك الاجهزة وبما ينعكس على مجمل السمات والمميزات التي تتعلق ب

ABSTRACT

The research aims to study the effect of the commodity dumping phenomenon that Iraq suffered after 2003 on the consumption pattern of individuals, towards the acquisition of non-essential goods (luxury). To achieve our goal we relied on the questionnaire as a main tool for obtaining information related to the research, and it was distributed on a random sample of consumers in the city of Baghdad with 250 questionnaires. The answers of the research sample were analyzed using the statistical program (SPSS). The percentage weights and the factorial analysis method were used also to arrange the variables that affected on changing consumption patterns. The research reached a set of conclusions:

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

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

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

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