The research aims at showing the media awareness for Students, especially for the students of the preparatory schools through their following the mass media in forming the cultural, educational and political database. It also aims at building a content and prospectives that make them a wide awake stratum that safeguard the society which has faced huge effects of terrorist actions.

                 Furthermore, it aims at knowing to what extent that students have been acquainted with the printed and electronic newspapers. Finally, it aims at knowing to what extent that they are content with the mass media in covering and

Student performance may influence by several factors in all his study levels such as primary school, intermediate school and even in his college; some of these factors are psychological factors, social factors, and the factors which correlate with student environment.

In this paper we study some of these factors to discover their influence by using canonical correlation analysis to analyze the data. Many conclusions are discovered to help who focuses student performance or to make it pest in future.

The impact of applying the K-W-L self-scheduling technique on first-year intermediate students' learning of basic volleyball skills, Ayad Ali Hussein*, Israa Fouad Salih

The exercise of activities and sports are of great importance to public health and to maintain the ideal health weight as well as the psychological and mental comfort of humans. The aim of this study is to determine the contribution and participation of educated females in physical activities at the University of Baghdad hall for the years 2011-2016, and to show the factors that influence women's contribution to physical activities at the university by selecting 100 students of males and 100 females' students randomly. During the questioning questions and statistical analysis of the questioning to find out the reasons for the discouraging contribution of the women to the various physical activities and try to find solutions and r

Numerous research studies have been conducted on why some learners acquire a second language more easily and quickly than others. Most of these studies have demonstrated that acquiring a second language does not depend only on learners’ cognitive ability or professional teaching strategies. The learning language process is more complicated than that. It is affected by crucial factors that are beyond the control of learners and teachers. These factors are known as sociolinguistic factors. These factors include culture, age, motivation, socio-economic status, and gender. This research paper mainly concentrates on the role of motivation in second language acquisition.

One study whose importance has significantly grown in recent years is lip-reading, particularly with the widespread of using deep learning techniques. Lip reading is essential for speech recognition in noisy environments or for those with hearing impairments. It refers to recognizing spoken sentences using visual information acquired from lip movements. Also, the lip area, especially for males, suffers from several problems, such as the mouth area containing the mustache and beard, which may cover the lip area. This paper proposes an automatic lip-reading system to recognize and classify short English sentences spoken by speakers using deep learning networks. The input video extracts frames and each frame is passed to the Viola-Jone

With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve