Abstract The Object of the study aims to identify the effectiveness of using the 7E’s learning cycle to learn movement chains on uneven bars, for this purpose, we used the method SPSS. On a sample composed (20) students on collage of physical education at the university of Baghdad Chosen as two groups experimental and control group (10) student for each group, and for data collection, we used SPSS After collecting the results and having treated them statistically, we conclude the use 7E’s learning cycle has achieved remarkable positive progress, but it has diverged between to methods, On this basis, the study recommended the necessity of applying 7E’s learning cycle strategy in learning the movement chain on uneven bar

This paper offers a systemic review of the deep learning methods to detect violence on campus, which is a critical issue in intelligent surveillance to improve the student safety and prompt cut off of violent accidents. The review reviews studies published 2018-2025, concentrating on model structure to detect fights, bullying, vandalism, and aggressive behavior on problematic campuses due to occlusion and light variations and complicated human interactions. The research design includes a comparative study of different deep learning networks, such as CNNs, RNNs, 3D CNNs, attention-based networks, transformers, graph neural networks, neuro-fuzzy, and multimodal systems and federated learning methods. The paper also assesses benchmark

In recent years, literary studies have witnessed a remarkable shift towards employing digital technologies, particularly artificial intelligence tools, in analyzing literary texts and exploring their linguistic and semantic structures. This trend has provided researchers with new possibilities for understanding texts in quantitative and qualitative ways that transcend traditional methods based solely on critical reading. The current research aims to introduce professors and students of Arabic to artificial intelligence tools that contribute to the analysis of literary texts, focusing on exploring their mechanisms for studying style, meaning, structure, and emotion. It also seeks to highlight the most prominent challenges facing researchers

Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregati

               The research aimed at designing a teaching aid for learning backswing into handstand as well as identifying its effect on learning skill performance. The researchers hypothesized statistical differences between pre and post-tests in favor of the research group. They used the experimental method on six (13 – 16) year–old Baghdad club gymnasts. The researchers used the one group design in which all players perform pretests followed by special tests on the teaching aid than are tested posttests. The researchers conclude that the teaching aid positively affected learning the skill as well as the teaching aid was very good and endured the performance of all gymnasts. The researcher recommended making simi

CNC machine is used to machine complex or simple shapes at higher speed with maximum accuracy and minimum error. In this paper a previously designed CNC control system is used to machine ellipses and polylines. The sample needs to be machined is drawn by using one of the drawing software like AUTOCAD® or 3D MAX and is saved in a well-known file format (DXF) then that file is fed to the CNC machine controller by the CNC operator then that part will be machined by the CNC machine. The CNC controller using developed algorithms that reads the DXF file feeds to the machine, extracts the shapes from the file and generates commands to move the CNC machine axes so that these shapes can be machined.

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne