Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

The present study aims to identify wisdom-based thinking and its relationship to psychological capital. It further aims to find out the differences in the level of wisdom-based thinking and psychological capital according to the variables of gender and specialization (scientific, humanities). To achieve this, the study has been conducted on a sample of (380) male and female students. The two scales, wisdom-based thinking and psychological capital are implemented to the sample after being constructed by the researcher and after ensuring their psychometric characteristics' suitability for the study's aims. Results concerning the first aim have shown that there is a significant relationship among students. The second aim has revealed that t

Objective of this work is the mixing between human biometric characteristics and unique attributes of the computer in order to protect computer networks and resources environments through the development of authentication and authorization techniques. In human biometric side has been studying the best methods and algorithms used, and the conclusion is that the fingerprint is the best, but it has some flaws. Fingerprint algorithm has been improved so that their performance can be adapted to enhance the clarity of the edge of the gully structures of pictures fingerprint, taking into account the evaluation of the direction of the nearby edges and repeat. In the side of the computer features, computer and its components like human have uniqu

One of the most important , compound which have active hydrogen is the compound possessing (thiol group) Biphenyl-4,4-dithiol is agood example utilized in a wide field for preparation mannich bases , avariety of new acetylenic mannich bases have been Synthesized and all proposed structure were Supported by FTIR , 1H – NMR, 13C-NMR , Elemental analysis and microbial study .

This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to

The rapid development of telemedicine services and the requirements for exchanging medical information between physicians, consultants, and health institutions have made the protection of patients’ information an important priority for any future e-health system. The protection of medical information, including the cover (i.e. medical image), has a specificity that slightly differs from the requirements for protecting other information. It is necessary to preserve the cover greatly due to its importance on the reception side as medical staff use this information to provide a diagnosis to save a patient's life. If the cover is tampered with, this leads to failure in achieving the goal of telemedicine. Therefore, this work provides an in

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

The aim of this research is to identify the strengths and weaknesses of organizational health in the Iraqi Central Handball Federation from the point of view of those who manage the implementation of the annual curriculum, and adopt a descriptive approach in the method of studying the case. This is based on a sample of administrators of the Iraqi Handball Federation curriculum [trainers, governors, members, president, the 138 members of the Central Federation's Administrative Authority, the President, members of the sub-federations of the sports market (2021/2022) selected deliberately by 100% and then divided into statistical analysis sample (30), reconnaissance sample (10), and application sample (98)]. The regulatory health questionnaire