This study was conducted to determine the relationship between test anxiety and cognitive representation among university students. To this end, 152 student (male, female) were chosen randomly from scientific and social departments to fill out the questionnaires of test anxiety and cognitive representation. The researcher utilized Independent Samples T-Test, Pearson product-moment correlation coefficient, Cronbach's alpha and T-Test in his study. The result revealed that there were negative and a weak correlation between test anxiety and cognitive representation among university students.

The research aims at identifying the level of imaginative thinking skills in mathematics among fourth scientific grade students.For this purpose, the researcher adopted the descriptive (survey) approach, as an imaginative thinking test was built and applied to the research sample that consists of (301) students from fourth scientific grade students who are distributed to secondary and Preparatory schools,they are Al-Furat Preparatory, Al-Hindiya Preparatory school and Al-Rajiba Preparatory school , who are affiliated to the Al-Hindiya Education Department of the General Directorate in the Holy Karbala Governorate for the academic year (2021-2022). The imaginative thinking test consisted of (36) items of four alternatives multiple-choice obj

This study seeks to answer urgent questions about the role of new media that have emerged recently, such as the Internet and social networking sites and information services through mobile and others to increase awareness among young people, especially university students. during a field study that took place on a sample of students in the Department of Media at the University of Petra Kingdom of Jordan during the second semester in 2013 in the study the researcher finds increased attention and follow-up by young people for many of the world events and regional and local communities through exposure to a number of new media; in the forefront of the Internet and increase the level of awareness and interests young people do many of the eve

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the