We have found through research , that administrative institutions on the outskirts of Kufa and their management is not as important as administrative institution in place that were associated with it and subject to its control ,as it often was express power , or poor ( if true ) expression , directors of the center for the suburbs , as it became clear to our diversity of those administrative institutions and prominent role in the interest of the affairs of the people and society in all aspects of life , and are the functions and different staff from the highest authority the suburbs represented by house of representatives ( the workers ) ,then workers abscess and Al-dhaqan and not to mention for other jobs came the actions of Bhaltsier and monitoring economic and social aspects in people s lives ,such as publicans and workers charity and Mahtsiaun , also found through research that social status ,cultural , scientific and managerial expertise have been instrumental in the appointment of staff to assume managerial positions and work assignments on the outskirts of kufa , usually what are the persons and individuals with prestige and efficiency , competence , which helped to stabilize and population growth is evident in the outskirts of Kufa , and because the system of government in Kufa and its suburbs was centrally however the governors of Kufa who met their hand s the powers set representatives and staff profiles administrative components of the outskirts of Kufa ,has undergone these control that power and accountability , which contributed to the provisions of the control center to the suburbs and administrative subordination of the center .
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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Abstract: Urinary Tract Infections (UTIs) are the most common bacterial infection in humans and a major cause of morbidity and they are the most common cause of hospital visits worldwide. Proper knowledge in identifying factors associated with urinary tract infection may allow the intervention to easily control of the disease in a timely manner. Therefore, the purpose of the study is determining the prevalence of UTI, diagnosis of causative bacterial agents and identifying the factors associated to the urinary tract infection among patients attending Medical City Hospital in Baghdad, Iraq. A total of 237, morning mid-stream urine samples were collected aseptically and the samples were diagnosed according to the standard methods. I
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In the present paper, chitosan Schiff base has been synthesized from chitosan’s reaction with the salicyldehyde. The AuNPs was manufacture by extract of onion peels as a reducing agent. The Au NPs that have been prepared were characterized through the UV-vis spectroscopy, XRD analyses and SEM microscopy. The polymer blends of the chitosan Schiff base / PVP has been prepared through using the approach of solution casting. Chitosan Schiff base / PVP Au nano-composites was prepared. Nano composites and polymer blends have been characterized by FTIR which confirm the formation of Schiff base by revealing a new band of absorption at 1651cm-1 as a result of the (C=N) imine group. SEM, DSC and TGA confirms the thermal stability of
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