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.
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
... 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
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This paper studies the effect of contact areas on the transient response of mechanical structures. Precisely, it investigates replacing the ordinary beam of a structure by two beams of half the thickness, which are joined by bolts. The response of these beams is controlled by adjusting the tightening of the connecting bolts and hence changing the magnitude of the induced frictional force between the two beams which affect the beams damping capacity. A cantilever of two beams joined together by bolts has been investigated numerically and experimentally. The numerical analysis was performed using ANSYS-Workbench version 17.2. A good agreement between the numerical and experimental results has been obtained. In general, results s
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Phosphorus (P) is an element that is potatoes require in large amounts. Soil pH is a crucial factor impacting phosphorus availability in potato production. This study was conducted to evaluate the influence of P application rates on the P efficiency for tuber yield, specific gravity, and P uptake. Additionally, the relationship between soil pH and total potato tuber yield was determined. Six rates of P fertilization (0–280 kg P ha−1) were applied at twelve different sites across Northern Maine. Yield parameters were not responsive to P application rates. However, regression analysis showed that soil pH was significantly correlated with total potato tuber yield(R2 = 0.38). Sites with soil pH values < 6 had total tuber yields,
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Physical measurements are one of the basic factors that affect the performance of the goalkeeper, especially when confronting fixed kicks that require special skills such as the reaction and accuracy in concentration, and with technological development artificial intelligence has become an effective tool for analyzing mathematical data that is difficult to discover in traditional methods The study aims to employ techniques Artificial intelligence to study the relationship between physical measurements and the accuracy of confronting the fixed kicks of goalkeepers in football. This study will contribute to providing a deeper understanding of physical factors that affect the performance of goalkeepers, in addition to designing dedicat
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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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Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,
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