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THE EFFECT OF A PROPOSED TRAINING PROGRAM USING INTERMITTENT TRAINING TO DEVELOP SOME PHYSICAL AND BIO-KINEMATIC VARIABLES AND ACCURACY OF THE JUMP SPIKE SERVE SKILL IN VOLLEYBALL
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The purpose of this paper is to identifying the values of some physical and Bio- Kinematic variables during the performance of the jump spike serve skill, and identifying the effect of the proposed training program using intermittent training to develop some physical and Bio- Kinematic variables and accuracy of the jump spike serve skill among the research sample. The experimental method was used and the research was conducted on a deliberately chosen sample of the players of the Army Club, who were primarily advanced in volleyball, and the number of the sample was (10) players. The conclusions were reached that the proposed training program using intermittent training has a positive effect on some of the physical and Bio- Kinematic variables of the advanced volleyball players and that this program has made an improvement in accuracy of the skill, Therefore some recommendations were given, including the use of the intermittent training program to develop some physical and Bio- Kinematic variables because of its positive impact on volleyball players, and the use of intermittent training activities mainly in the special preparation period and the transitional period because of its importance in improving the physical and skill condition of volleyball players Providing sports equipment and tools used in intermittent training in sports clubs to serve the training process for volleyball players.

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Publication Date
Mon Mar 23 2020
Journal Name
Journal Of Engineering
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Constructed Wetland Units Filled with Waterworks Sludge for Remediating of Wastewater Contaminated with Congo Red Dye
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The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

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