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%.
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In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.
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The 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
Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
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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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Academic achievement is a professional standard for measuring student levels in the first stages. Therefore, any indication of the level of achievement makes us in an attempt to employ students in evening schools. The researcher has developed a closed questionnaire of (36) paragraphs. A total of (164) male and (24) female students were chosen from evening schools. The result of this research revealed that the number of students was a reason for the low level of their achievement, the lack of laboratories, educational methods, and techniques of the most prominent problems confirmed by students in these schools. In addition, to support educational institutions with their necessary needs. The most important conclusion in this research is th
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The research aims to examine the effect of Hawkins' strategy on students in the fourth grade of primary school in the General Directorate of Education in Baghdad / Karkh 3 for the academic year (2020-2021). The research was limited to the topics of the Arabic language grammar book for the fourth grade of primary school. The researcher developed the research hypothesis, which is: that there is no statistically significant difference at the significance level (0.05) between the average scores of the experimental group students who study using the Hawkins strategy and the average scores of the control group students who study in the traditional method in the achievement test. The researcher set a number of
... Show Moree current research aims to know the effect of fishbone strategy on achievement of chemistry and visual thinking among middle school students, the research sample consisted of 89 students divided into two experimental groups consisting of 44 students who studied fishbone strategy, and a control group that consisted of 45. A student studied in the usual way; the two groups were rewarded in a number of variables, and the researcher built two tools for the research: the first is an achievement test consisting in 30 paragraphs, and the second is a visual thinking test consisting in 18 paragraphs. Keywords: Chemistry, fishbone, seven grade, students, visual thinking..