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Predicting the Sporting Achievement in the Pole Vault for Men Using Artificial Neural Networks

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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Publication Date
Wed Nov 20 2024
Journal Name
Journal Of Baghdad College Of Dentistry
The surface roughness of new fluoride releasing material after using three polishing protocols and storage in artificial saliva

Background: Prophylaxis methods are used to mechanically remove plaque and stain from tooth surfaces; such methods give rise to loss of superficial structure and roughen the surface of composites as a result of their abrasive action. This study was done to assess the effect of three polishing systems on surface texture of new anterior composites after storage in artificial saliva. Materials and methods: A total of 40 Giomer and Tetric®N-Ceram composite discs of 12 mm internal diameter and 3mm height were prepared using a specially designed cylindrical mold and were stored in artificial saliva for one month and then samples were divided into four groups according to surface treatment: Group A (control group):10 specimens received no surfa

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
An Improved Cuckoo Search Algorithm for Maximizing the Coverage Range of Wireless Sensor Networks

The issue of increasing the range covered by a wireless sensor network with restricted sensors is addressed utilizing improved CS employing the PSO algorithm and opposition-based learning (ICS-PSO-OBL). At first, the iteration is carried out by updating the old solution dimension by dimension to achieve independent updating across the dimensions in the high-dimensional optimization problem. The PSO operator is then incorporated to lessen the preference random walk stage's imbalance between exploration and exploitation ability. Exceptional individuals are selected from the population using OBL to boost the chance of finding the optimal solution based on the fitness value. The ICS-PSO-OBL is used to maximize coverage in WSN by converting r

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Publication Date
Tue Sep 25 2018
Journal Name
Iraqi Journal Of Science
Using Multiattribute Analysis to Predicting Effective Porosity of Yamama Formation in Nasriya Oilfield Southern Iraq

Emerge application was used in Hampsson-Russell programs and that uses a combination of multiple 3D or 2D seismic attributes to predict some reservoir parameter of interest. In this research used the seismic inversion technique was performed on post-stack three dimensions (3D) seismic data in Nasriya oilfield with five wells  and then used this results in  Emerge analysis (training and application) were used to estimate reservoir properties (effective porosity) with multiattribute analysis derive relations  between them at well locations. The horizon time slice of reservoir units of (Yb1, Yb3 and Yc) of Yamama Formation was made for property (effective porosity) to confirm match results and enhancement trends within these

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Publication Date
Mon Jan 01 2024
Journal Name
Explainable Artificial Intelligence In The Digital Sustainability Administration
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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Proposed Security Models for Node-level and Network-level Aspects of Wireless Sensor Networks Using Machine Learning Techniques

     As a result of the pandemic crisis and the shift to digitization, cyber-attacks are at an all-time high in the modern day despite good technological advancement. The use of wireless sensor networks (WSNs) is an indicator of technical advancement in most industries. For the safe transfer of data, security objectives such as confidentiality, integrity, and availability must be maintained. The security features of WSN are split into node level and network level. For the node level, a proactive strategy using deep learning /machine learning techniques is suggested. The primary benefit of this proactive approach is that it foresees the cyber-attack before it is launched, allowing for damage mitigation. A cryptography algorithm is put

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Publication Date
Fri Feb 04 2022
Journal Name
Iraqi Journal Of Science
AHeuristic Strategy for Improving the Performance of Evolutionary Based Complex Detection in Protein-Protein Interaction Networks

One of the most interested problems that recently attracts many research investigations in Protein-protein interactions (PPI) networks is complex detection problem. Detecting natural divisions in such complex networks is proved to be extremely NP-hard problem wherein, recently, the field of Evolutionary Algorithms (EAs) reveals positive results. The contribution of this work is to introduce a heuristic operator, called protein-complex attraction and repulsion, which is especially tailored for the complex detection problem and to enable the EA to improve its detection ability. The proposed heuristic operator is designed to fine-grain the structure of a complex by dividing it into two more complexes, each being distinguished with a core pr

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Publication Date
Mon Feb 13 2023
Journal Name
Journal Of Educational And Psychological Researches
Developing an Achievement Test in Light of the Specifications Table

Abstract

The research addresses the specification table and the extent of its use in developing achievement tests, as well as detects the obstacles to its use through a sample of (120) respondents from the faculty members in some Baghdad schools and colleges. After unpacking and processing the data statistically, the research reached several results: the study sample do not use the test map in the development of their tests, as their percentage reached (82%) and there are no statistically significant differences in the use of the specification table by the sample members according to their place of work or the number of years of experience. The results also revealed the most important reasons that prevent the use

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Publication Date
Sun Aug 01 2021
Journal Name
Telkomnika
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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Classification of Arabic Alphabets Using a Combination of a Convolutional Neural Network and the Morphological Gradient Method

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

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Publication Date
Tue Oct 01 2019
Journal Name
Karbala Journal Of Physical Education Sciences
Effect of use a designed device to develop some biochemical variables for rear vault dismount with one-half twist on parallel bars in gymnastics

The research included five sections containing the first section on the introduction o research and its importance and was addressed to the importance of the game of gymnastic and skilled parallel bars effectiveness and the importance of biochemical variables, either the research problem that there is a difference in learning this skill and difficulty in learning may be one of the most important reasons are falling and injury Has a negative impact on the performance and lack of sense of movement of is one of the obstacles in the completion of the skill and the goal of research to design a device that helps in the development of biochemical changes to skill of rear vault dismount with one-half twist on parallel bars in gymnastics . And the n

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