Intrusion detection system is an imperative role in increasing security and decreasing the harm of the computer security system and information system when using of network. It observes different events in a network or system to decide occurring an intrusion or not and it is used to make strategic decision, security purposes and analyzing directions. This paper describes host based intrusion detection system architecture for DDoS attack, which intelligently detects the intrusion periodically and dynamically by evaluating the intruder group respective to the present node with its neighbors. We analyze a dependable dataset named CICIDS 2017 that contains benign and DDoS attack network flows, which meets certifiable criteria and is ope

 The study aims to identify the relationship between Dogmatism and the behavioral problems among preparatory school students. To do this, the researcher adopted Rokeach’s scale of dogmatism, which was modified to be more appropriate of the Iraqi context. A sample of (300) students was chosen randomly to collect the needed data for the current study. To process the data, the researcher employed T-test, Pearson correlation coefficient, and Weighted Mean. The finding revealed that the study sample experience too many behavioral problems, as well as there is a positive strong relationship between Dogmatism and behavioral problems. To conclude, the researcher recommended holding counseling sessions targeting school students to mitigate

Given the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University

Writing in English is one of the essential factors for successful                      EFL learning .Iraqi students at the preparatory schools encounter problems when using their background knowledge in handling subskills                                  of writing(Burhan,2013:164).Therefore, this study aims to investigate the 4^thyear preparatory school students’ problems in English composition writing, and find solutions to these pro

Irrigation scheduling techniques is one of the suggested solutions for water scarcity problem. The study aims to show the possibility of using practical and applicable irrigation scheduling program which was designed by Water Resources Department at the University of Baghdad by using Spreadsheet Formulas for Microsoft Excel program, version 2007, with some modification to generalize it and made it applicable to various climatic zone and different soil types, as a salvation for the shortage of irrigation water inside the irrigation projects. Irrigation projects which incidence of Tigris River basin will be taken as an applicable example. This program was based on water budgeting and programmed depending on scientific concepts which facili

Face recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recogni

In this paper, a new class of nonconvex sets and functions called strongly -convex sets and strongly -convex functions are introduced. This class is considered as a natural extension of strongly -convex sets and functions introduced in the literature. Some basic and differentiability properties related to strongly -convex functions are discussed. As an application to optimization problems, some optimality properties of constrained optimization problems are proved. In these optimization problems, either the objective function or the inequality constraints functions are strongly -convex. 

Background: Polycystic ovary syndrome (PCOS) is the most common endocrinopathy affecting women, at reproductive age. PCOS is a chronic hyperandrogenic state that has many significant short-term and long-term implications for patients such as oligomenorrhea, amenorrhea, infertility, diabetes mellitus, cardiovascular disease, increased risk of endometrial cancer, and hirsutism. Objectives: To evaluate the obesity and glycemic criteria among women with polycystic ovary syndrome. Method: A case control designed study was carried out at the National Diabetes Center (NDC) / Al-Mustansiryia University; on 50 participants formed the PCOS group and 50 healthy control participants. Data collected about age, age at menarche and BMI. Also, blood sam