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Using artificial neural networks to assign soccer players by physical and motor abilities
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Introduction: The introduction of analytics tools in sports indicates that artificial neural networks can be one of the intelligent approaches to process complex data and identify patterns that help players move according to their most suitable positions. Objective: The purpose of this research is to investigate the possibility of using artificial neural networks to determine the physical and motor abilities of football players and determine their suitable playing positions based on exact quantitative indicators. Method: The study sample consists of 45 youth players aged (15–16) years from the Espanyol Football Academy in Baghdad. The results are analyzed using a multilayer perceptron (MLP) artificial neural network model to identify the relationships between physical variables and playing positions. Results: The Pearson correlation analysis reveals statistically significant relationships between physical and motor abilities and the players’ actual playing positions (p < 0.05). In addition, the artificial neural network (MLP) model demonstrated the ability to assign players to different playing positions based on the relative weights of the variables. Speed, endurance, and explosive power were identified as the most influential factors in determining offensive positions, whereas flexibility and visual–motor coordination played a significant role in determining defensive positions and goalkeeping. The model achieved a classification accuracy exceeding 85%. Discussion: The artificial neural network model demonstrates a high capacity to exploit correlational relationships and transform them from conventional statistical associations into accurate predictive patterns. This enables the model to guide players toward the most suitable playing positions based on their physical and motor characteristics. Conclusions: The findings of the study confirm the feasibility of adopting artificial neural networks as an intelligent tool for sports performance analysis and for guiding youth players toward the playing positions most suited to their physical and motor abilities.

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
Estimation and Improvement of Routing Protocol Mobile Ad-Hoc Network Using Fuzzy Neural Network
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Ad-Hoc Networks are a generation of networks that are truly wireless, and can be easily constructed without any operator. There are protocols for management of these networks, in which the effectiveness and the important elements in these networks are the Quality of Service (QoS). In this work the evaluation of QoS performance of MANETs is done by comparing the results of using AODV, DSR, OLSR and TORA routing protocols using the Op-Net Modeler, then conduct an extensive set of performance experiments for these protocols with a wide variety of settings. The results show that the best protocol depends on QoS using two types of applications (+ve and –ve QoS in the FIS evaluation). QoS of the protocol varies from one prot

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Publication Date
Sun Apr 02 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Traffic Classification of IoT Devices by Utilizing Spike Neural Network Learning Approach
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Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field
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In this paper, an enhanced artificial potential field (EAPF) planner is introduced. This planner is proposed to rapidly find online solutions for the mobile robot path planning problems, when the underlying environment contains obstacles with unknown locations and sizes. The classical artificial potential field represents both the repulsive force due to the detected obstacle and the attractive force due to the target. These forces can be considered as the primary directional indicator for the mobile robot. However, the classical artificial potential field has many drawbacks. So, we suggest two secondary forces which are called the midpoint

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Publication Date
Wed Aug 31 2022
Journal Name
Ieee Access
SHE Networks: Security, Health, and Emergency Networks Traffic Priority Management Based on ML and SDN
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Recently, the increasing demand to transfer data through the Internet has pushed the Internet infrastructure to the nal edge of the ability of these networks. This high demand causes a deciency of rapid response to emergencies and disasters to control or reduce the devastating effects of these disasters. As one of the main cornerstones to address the data trafc forwarding issue, the Internet networks need to impose the highest priority on the special networks: Security, Health, and Emergency (SHE) data trafc. These networks work in closed and private domains to serve a group of users for specic tasks. Our novel proposed network ow priority management based on ML and SDN fullls high control to give the required ow priority to SHE dat

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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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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Scopus (38)
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Publication Date
Fri Jul 25 2014
Journal Name
Modern Sport
Analyze study for some biomechanics variables to jump shoot skill from different spots with and without defense to basketball youth players in 3x3
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The research to knows some biomechanics variables in different spots with and without players in basketball youth players and analysis by using destructive method in surfing study and the research were applied for jump shoot from one of basketball players in ( middle , left , right ) in side zone and out of zone also from three point shoot with and without defense and we depend on successful shoot on analyze .The results and conclusions that center of weight of the player on standby on high and knee angel and hips were more wide also the two angle of wrist , elbow on start of shooting be more wide with defender more than without defender .the maximum high center of weight and shooting angle and ball entrance being less degree with defender

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Publication Date
Wed May 12 2021
Journal Name
Indian Journal Of Forensic Medicine &amp; Toxicology
The Relationship of Healthy Rationalist Pundit Thinking to the Spiking and Block Performance of Volleyball For Junior Players
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Publication Date
Sat Oct 03 2026
Journal Name
Revista Iberoamericana De Psicología Del Ejercicio Y El Deporte, Issn 1886-8576, Vol. 17, Nº. 6, 2022, Págs. 399-401
Aggressive Behavior And Its Relationship To The Phenomenon Of Bullying Among Young Football Players Aged (17-19) Years
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Autorías: Muwafaq Obayes Khudhair, Hayder Talib Jasim, Ahmed Thare Hani. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 6, 2022. Artículo de Revista en Dialnet.

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Publication Date
Thu Sep 11 2025
Journal Name
Sulaimani Journal For Humanities
Psychological hesitation and its relationship to the accuracy of serving reception skills among Baghdad University volleyball team players
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This study aims to determine the relationship between psychological frequency and the accuracy of receiving a serve in volleyball. The researchers used a descriptive approach, which is best suited to the research problem. The study sample consisted of 12 players from the University of Baghdad volleyball team. Ten players were selected purposively, and two were excluded from the research sample for use in a pilot study, as well as players who participate in volleyball at sports clubs. The sample size represented 83% of the original population. The researchers used the Psychological Frequency Scale developed by Firas Abdul Hussein (1999) for sports-related applications, which consists of 51 positive and negative items. The SPSS version 26 sof

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Publication Date
Wed Nov 28 2018
Journal Name
International Journal Of Engineering &amp; Technology
Improvement of Gypsum Soil by Using Polyurethane to Reduce Erosion and Solubility of Irrigation Canals
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The reducing of erosion and the solubility of irrigation canals soils which constructed on gypsum soil is important in civil and water resources engineering. The main problem of gypsum soils is the presence of gypsum which represents one of most complex engineering problems, especially when accompanied by the moving of water which represent dynamic load along the canal. There are several solutions to this problem, in this research “Poly urethane” is used to give the gypsum soil sufficient hardness to reduce the solubility and erosion, after compacting the soil in the canal, percentages of Poly urethane was used to making cover to the soil by mixing percent of soil with Poly urethane, and the ratio was as follows: (5 and 10) % an

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