The research aims to identify banking stress tests, which is one of the modern and important tools in managing banking risks by applying the equations of that tool to the sample. The banking sector considered one of the most vulnerable to sudden and rapid changes in an unstable economic environment, making it more vulnerable. Therefore, it is necessary to establish a special risk management section to reduce the banking risks of the banking business that negatively affect its performance.

The research concluded that there is a direct relationship between stress tests and risk management, as stress tests are an essential tool in risk management. They also considered a unified approach in managing bank risks that helps the bank to

The purpose of this research is defining the main factors influencing on decision of management system on sensitive data in cloud. The framework is proposed to enhance management information systems decision on sensitive information in cloud environment. The structured interview with several security experts working on cloud computing security to investigate the main objective of framework and suitability of instrument, a pilot study conducts to test the instrument. The validity and reliability test results expose that study can be expanded and lead to final framework validation. This framework using multilevel related to Authorization, Authentication, Classification and identity anonymity, and save and verify, to enhance management

     Methotrexate (MTX) is still one of the gold standard treatments for rheumatoid arthritis (RA). It shows diverse outcomes in blood level and clinical response, this was demonstrated by its relation to the genetic polymorphism in the pharmacogenetic study. This study aimed to investigate the role of methylenetetrahydrofolate reductase (MTHFR) gene polymorphisms in relation to MTX efficacy and toxicity in Iraqi Kurdish RA patients. Sixty-four RA patients were involved in this study with an average age of 47.78 ±14.08 and female to male ratio of (8.1). Diagnosis and disease activity were confirmed. Blood analyses, including those of laboratory markers of disease activity, were done. The 28 joint disease activity score (DAS28-CRP) w

  The study aimed to estimate  the role of glucagon-like peptide-1 (GLP-1)  and visfatin as a novel  pro inflammatory marker in Rheumatoid Arthritis (RA ) according to the activity scores of disease to assess the possibility of introducing glucagon-like peptide-1 and visfatin in the diagnosis and monitoring of RA patients and to found the correlation  of visfatin level with GLP-1 and AIP in patients prone to atherosclerosis ,fifty  healthy individuals as control group (G1) and fifty rheumatoid arthritis (RA) patients (G2) were enrolled in this study with middle age  ranged (30 – 40) years and BMI ≥24 kg/m2. ESR ,RF, lipid profile, CRP,insulin, visfatin and GLP-1were determined. Results in t

The study aimed to assess the frequency of invasive fungal infection in patients with respiratory diseases by conventional and molecular methods. This study included 117 Broncho alveolar lavage (BAL) samples were collected from patients with respiratory disease (79 male and 38 female) with ages ranged between (20-80) years, who attended Medicine Baghdad Teaching hospital and AL-Emamain AL-Khadhymian Medical City, during the period from September 2019 to April 2020. The results in PCR versus culture methods in this study showed that out of 117 samples of fungal infections 30(25.6 %) were detected by culture method, while the 24(20.5%) samples were detected by PCR technique, the most commonly diagnosed pathogenic fungi is Candida spp.

Abstract
  financial market occupy very important place in the economic activity all over the world countris, and its importance increased with considerable technological progress in the world of transportation ,communications and information where its impact have spread over the whole world, which led to link the international economy in a kind of international relations so that the open policy became the prevailing trend in national and regional economies within the framework of the new world order.

the international economy has faced the financial crisis, global, that hit all world economies although the United States is the center of the crisis and the starting spark for it w

Cloud computing provides huge amount of area for storage of the data, but with an increase of number of users and size of their data, cloud storage environment faces earnest problem such as saving storage space, managing this large data, security and privacy of data. To save space in cloud storage one of the important methods is data deduplication, it is one of the compression technique that allows only one copy of the data to be saved and eliminate the extra copies. To offer security and privacy of the sensitive data while supporting the deduplication, In this work attacks that exploit the hybrid cloud deduplication have been identified, allowing an attacker to gain access to the files of other users based on very small hash signatures of

In this study asparaginase was extracted from fruit part of Capiscum annum then Asparaginase activity was detected and optimised. Optimum conditions for the activity of crude asparaginase were studied. Results showed maximum activity of asparaginase was achieved 140 u/ml when the enzyme was incubated with 200 mM of asparagines at 35 °C for 30 minutes in the presence of 0.05 M of potassium phosphate buffer solution at pH 8.

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an