The physical sports sector in Iraq suffers from the problem of achieving sports achievements in individual and team games in various Asian and international competitions, for many reasons, including the lack of exploitation of modern, accurate and flexible technologies and means, especially in the field of information technology, especially the technology of artificial neural networks. The main goal of this study is to build an intelligent mathematical model to predict sport achievement in pole vaulting for men, the methodology of the research included the use of five variables as inputs to the neural network, which are Avarage of Speed (m/sec in Before distance 05 meters latest and Distance 05 meters latest, The maximum speed achieved in the last 5 meters from the total approach distance of 30 meters, The ratio of the conversion coefficient of horizontal velocity to vertical velocity, The ratio of the conversion coefficient of horizontal velocity to vertical velocity, The height of the fist is over the full length of the pole's stick) and these are considered independent variables, while the dependent variable was the prediction of achievement (Final height achieved by the jumper) as an output. The neural network architecture was represented by three layers, the first layer is the input layer with the five variables, and one layer is hidden and contains one node, while the last layer is the output layer that represents the outcome of the sport achievement prediction of male weight jumping. The momentum term and learning rate were chosen by 0.95 and 0.4 respectively, and the transfer function in the hidden layer was the sigmoid function and in the last layer was the sigmoid function, the historical data used in this model represent the Olympic achievements of a number of world champions, the results of this study were that the artificial neural network has the ability to prediction of sport achievement for determine the height of the jump of the pole player with a degree of accuracy of 90.10%, correlation coefficient and 95.60%.
Abstract
The aim of the current research is to identify the effect of the effective reading strategy on the achievement of second-middle students in biology, as well as the imaginative thinking skills of students. The researcher adopted the experimental design with partial control to achieve the goal of the research. The current research community identified the second-middle students in the government schools of the Baghdad Education Directorate / Rusafa I for the academic year (2021-2022 AD). The Safina Intermediate School for Girls was chosen to be the research sample in the form of intentionally, two classes were randomly selected from a total of four classes, one of them is experimental and the other is con
... Show MoreThe current research aims to identify the effect of the Bransford and Stein model on the achievement of fifth-grade literary students for geography and their reflective thinking. To achieve the objective of the research, the following two null hypotheses were formulated:
- There is no statistically significant difference at the significance level (0.05) between the average scores of the experimental group students who studied geography using the Bransford and Stein model and the average scores of the control group students who studied the same subject in the usual way in the achievement test. 2- There is no statistically significant difference at the significance level (0.05) between the average scores of the experimental gr
To determine the abilities of salivary E‐cadherin to differentiate between periodontal health and periodontitis and to discriminate grades of periodontitis.
E‐cadherin is the main protein responsible for maintaining the integrity of epithelial‐barrier function. Disintegration of this protein is one of the events associated with the destructive forms of periodontal disease leading to increase concentration of E‐cadherin in the oral biofluids.
A total of 63 patients with periodontitis (case) and 35
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Identification of complex communities in biological networks is a critical and ongoing challenge since lots of network-related problems correspond to the subgraph isomorphism problem known in the literature as NP-hard. Several optimization algorithms have been dedicated and applied to solve this problem. The main challenge regarding the application of optimization algorithms, specifically to handle large-scale complex networks, is their relatively long execution time. Thus, this paper proposes a parallel extension of the PSO algorithm to detect communities in complex biological networks. The main contribution of this study is summarized in three- fold; Firstly, a modified PSO algorithm with a local search operator is proposed
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Mobile Ad hoc Networks (MANETs) is a wireless technology that plays an important role in several modern applications which include military, civil, health and real-time applications. Providing Quality of Service (QoS) for this application with network characterized by node mobility, infrastructure-less, limitation resource is a critical issue and takes greater attention. However, transport protocols effected influential on the performance of MANET application. This study provides an analysis and evaluation of the performance for TFRC, UDP and TCP transport protocols in MANET environment. In order to achieve high accuracy results, the three transport protocols are implemented and simulated with four different network topology which are 5, 10
... Show MoreAn adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th
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