Background. Handball is a team sport that demands quick reflexes and precise motor skills, particularly in shooting. Players' ability to shoot accurately and swiftly while stationary makes upper limb reaction time crucial for success. Objectives. The research objective is to study the relationship between the motor time of the muscles of the arms and the index of accuracy of shooting from constancy in fourth-stage students in handball. Methods. The researchers used the descriptive method because it is one of the methods used in the research on a sample of students of the fourth stage of the college of Physical Education and Sports Sciences, where the sample consisted of 29 male students from the community of origin, 43 students. Results. The results showed that the variables under study have significant direct correlations with the accuracy variable of shooting from stability, where the correlation of the motor response time was r=0.73 (p=0.047), the speed of movement of the arm r=0.87 (p=0.380), the maximum decrease in the knee angle variable r=0.77 (p=0.360) and the maximum decrease in the center of mass of the body was r=0.79 (p=0.380). In contrast, the degree of elbow angle during the ball's exit was variable, r=0.62 (p=0.560), and the degree of wrist angle during the ball's exit was variable, r=0.79 (p=0.380). Conclusion. The study found that motor response speed, knee angle, and body center of mass significantly impact skill accuracy. These factors balance the player and maintain the movement path, resulting in an integrated skill. The accuracy of shooting from consistency in handball is primarily determined by the angle taken at each stage, particularly during the exit phase of the ball. This study stands out with novelty for its focus on university handball players, providing an accurate biomechanical analysis of this category of students, which has not been studied. The analyzed variables included elbow angle, wrist angle, knee flexion, and center of body mass during different shooting phases. In addition, using a non-random sample is a limitation that may affect the generalizability of the results.
Forecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti
... Show MoreThe study aims to measure the level of academic stress in the e-learning environment in three areas, students and their dealing with classmates, dealing with the professor and technical skills, and the nature and content of the curriculum among graduate students in the College of Education at King Khalid University during COVID-19 pandemic. This study was descriptive in nature (survey, comparative). The sample consisted of (512) male and female graduate students in the master's and doctoral programs. The Academic Stress Scale in the E-learning Environment designed by Amer (2021) was used. The results indicated a high level of academic stress among graduate students in the e-learning environment. The study also found that there were stati
... Show MoreThe importance of forecasting has emerged in the economic field in order to achieve economic growth, as forecasting is one of the important topics in the analysis of time series, and accurate forecasting of time series is one of the most important challenges in which we seek to make the best decision. The aim of the research is to suggest the use of hybrid models for forecasting the daily crude oil prices as the hybrid model consists of integrating the linear component, which represents Box Jenkins models and the non-linear component, which represents one of the methods of artificial intelligence, which is long short term memory (LSTM) and the gated recurrent unit (GRU) which represents deep learning models. It was found that the proposed h
... Show MoreHydrate dissociation equilibrium conditions for carbon dioxide + methane with water, nitrogen + methane with water and carbon dioxide + nitrogen with water were measured using cryogenic sapphire cell. Measurements were performed in the temperature range of 275.75 K–293.95 K and for pressures ranging from 5 MPa to 25 MPa. The resulting data indicate that as the carbon dioxide concentration is increased in the gas mixture, the gas hydrate equilibrium temperature increases. In contrast, by increasing the nitrogen concentration in the gas mixtures containing methane or carbon dioxide decreased the gas hydrate equilibrium temperatures. Furthermore, the cage occupancies for the carbon dioxide + methane system were evaluated using the Van der Wa
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An experiment was carried out to study the effects of Time Factor, potassium and Molybdenum on Rhizobium growth. The objective of the experiment, which conducted under laboratory conditions, was to investigate the interaction effects of using three levels of Molybdenum (0, 0.25, 2.50 mg Mo . Kg-1 sterile soil) and four levels of potassium (0, 25, 50, 100 mg K . Kg-1 sterile soil) on the viable counts of Rhizobium growth in the sterile soil after 3, 9, 15 and 21 days of incubation at 28°C. The results indicated that Molybdenum level 2.50 mg Mo . Kg-1 sterile soil and potassium level 50 mg K . Kg-1 sterile soil recorded the biggest significant increase in the viable counts of Rhizobium growth in the sterile soil especially after 15 da
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The purpose of this study is to investigate the research on artificial intelligence algorithms in football, specifically in relation to player performance prediction and injury prevention. To accomplish this goal, scholarly resources including Google Scholar, ResearchGate, Springer, and Scopus were used to provide a systematic examination of research done during the last ten years (2015–2025). Through a systematic procedure that included data collection, study selection based on predetermined criteria, categorisation based on AI applications in football, and assessment of major research problems, trends, and prospects, almost fifty papers were found and analysed. Summarising AI applications in football for performance and injury p
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The paper uses the Direct Synthesis (DS) method for tuning the Proportional Integral Derivative (PID) controller for controlling the DC servo motor. Two algorithms are presented for enhancing the performance of the suggested PID controller. These algorithms are Back-Propagation Neural Network and Particle Swarm Optimization (PSO). The performance and characteristics of DC servo motor are explained. The simulation results that obtained by using Matlab program show that the steady state error is eliminated with shorter adjusted time when using these algorithms with PID controller. A comparative between the two algorithms are described in this paper to show their effectiveness, which is found that the PSO algorithm gives be
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