The research aims to demonstrate the dual use of analysis to predict financial failure according to the Altman model and stress tests to achieve integration in banking risk management. On the bank’s ability to withstand crises, especially in light of its low rating according to the Altman model, and the possibility of its failure in the future, thus proving or denying the research hypothesis, the research reached a set of conclusions, the most important of which (the bank, according to the Altman model, is threatened with failure in the near future, as it is located within the red zone according to the model’s description, and will incur losses if it is exposed to crises in the future according to the analysis of stress tests

The purpose of this paper is to preparing preventive exercises supported by collagen supplements and vitamin D for handball players, and identify the effect of preventive physical exercises supported by collagen supplements and vitamin D on some physical and skill abilities of handball players. The researchers used the experimental method and designed two groups, one experimental and the other control, with both pre- and post-tests, to suit the nature of the research. The research community was selected from handball players (specialized school players), numbering (14), and they were divided into two groups, each group numbering (7) players. One of the most important results reached by the researcher is that: The exercises prepared by the r

         The aims of the present study are to evaluate the levels of CA19-9 in sera and tissues' homogenate of breast and thyroid benign patients in order to assess its use as an early diagnostic parameter in differentiation between malignant and benign cases. The study was conducted on 8 patients with breast benign tumor and 8 patients with thyroid benign tumor, by the enzyme linked immunosorbent assay (ELISA) technique. The results of CA19-9 levels in sera were (15 ±1.58 and 10.67 ±2.08)U/ml respectively compared with serum CA19-9 levels of control group which was 7.74 ±4.92 U/ml, the results were found to be highly significantly in breast tumor patients and non significantly in thyroid

This study was aimed to use plant tissue culture technique to induce callus formation of Aloe vera on MS. Medium supplied with 10 mg/l NAA and 5 mg/l BA that exhibit the best results even with subculturing. As the method of [1] 1g. dru weight of callus induced from A. vera crown and in vivo crown were extracted then injected in HPLC using the standards of Ascorbic acid (vit. C), Salysilic acid and Nicotenic acid (vit. B5) to compare with the plant extracts. Results showed high potential of increasing some secondary products using the crown callus culture of A. vera as compared with in vivo crown, Ascorbic acid was 1.829 ?g/l in in vivo crown and increased to 3.905 ?g/l crown callus culture . Salysilic acid raised from 3.54 ?g/l in in vivo c

Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi