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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
Sun Aug 16 2026
Journal Name
Journal Of Esthetic And Restorative Dentistry
Effectiveness of Cellulose Nanofibers Addition to Soft Denture Lining Material on Candida albicans Adherence and Physical and Mechanical Properties
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Purpose: Current denture liner materials suffer from low tear strength, poor abrasion resistance, weak bond strength to denture material, and increasing risk of denture stomatitis due to adherence. The aim of this study was to evaluate the effects of the addition of cellulose nanofibers (CNFs) to commercial soft denture liner material on the adherence of and physical and mechanical properties. Materials and Methods: CNFs at concentrations of 0.0, 0.5, and 1.0 wt.% were incorporated into a soft liner material. Antifungal effects were assessed by quantifying the adherence of . The Shore A hardness, tensile strength, peel bond strength, and surface roughness tests were employed to assess the properties of the denture liner materials. Chemica

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Thu Jul 17 2025
Journal Name
International Journal Of Environmental Sciences
Inverse Kinematic Analysis For A 5 DOF Robotic Arm Using Deep Neural Network
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In this study, the kinematic analysis including the forward and inverse kinematic developed for a 5 degree of freedom robotic arm. The forward kinematic is elaborated using Denavit-Hartenberg (DH) convention. Inverse Kinematic is established using Deep Neural Network (DNN) model with five hidden layer each contain 50 neurons fully connected using ReLu activation. A data of inputs and outputs are created and trained. The inputs are the end-effector position and orientation. The outputs are the joint angles of the manipulator. The data is generated by the forward kinematics, where a set of joint angles that limited by their corresponding ranges are inserted to the forward kinematic equations to result the end-effector positions and or

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Intelligent Congestion Control of 5G Traffic in SDN using Dual-Spike Neural Network
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Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification. Different

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Publication Date
Fri Dec 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Experimental investigation and modelling of residual stresses in face milling of Al-6061-T3 using neural network
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Milling process is a common machining operation that is used in the manufacturing of complex surfaces. Machining-induced residual stresses (RS) have a great impact on the performance of machined components and the surface quality in face milling operations with parameter cutting. The properties of engineering material as well as structural components, specifically fatigue life, deformation, impact resistance, corrosion resistance, and brittle fracture, can all be significantly influenced by residual stresses. Accordingly, controlling the distribution of residual stresses is indeed important to protect the piece and avoid failure. Most of the previous works inspected the material properties, tool parameters, or cutting parameters, bu

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Using Genetic Algorithm to Estimate the Parameters of the Gumbel Distribution Function by Simulation
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In this research, the focus was on estimating the parameters on (min- Gumbel distribution), using the maximum likelihood method and the Bayes method. The genetic algorithmmethod was employed in estimating the parameters of the maximum likelihood method as well as  the Bayes method. The comparison was made using the mean error squares (MSE), where the best  estimator  is the one who has the least mean squared error. It was noted that the best estimator was (BLG_GE).

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Publication Date
Tue Nov 03 2020
Journal Name
Modern Sport
Effect of using flat hierarchical method on some aspects of muscular strength and straight serve skill for nascent tennis players
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The researcher focused on the importance of the physical abilities of the tennis game, as this game is one of the games that are characterized by its specificity in performance as this game is characterized by continuous movement and dealing with different elements, so this game requires the development of muscle strength, which plays an important role in Performance skills in the game of tennis. There are several methods to develop strength, including flat hierarchical technique, which is one of the most common forms of training in the development of muscle strength.     As for the research problem, the researcher found a method that has an effect on the development of force. Therefore, the researcher tried to diversify a

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Publication Date
Tue Nov 03 2020
Journal Name
Modern Sport
Effect of using flat hierarchical method on some aspects of muscular strength and straight serve skill for nascent tennis players
...Show More Authors

The researcher focused on the importance of the physical abilities of the tennis game, as this game is one of the games that are characterized by its specificity in performance as this game is characterized by continuous movement and dealing with different elements, so this game requires the development of muscle strength, which plays an important role in Performance skills in the game of tennis. There are several methods to develop strength, including flat hierarchical technique, which is one of the most common forms of training in the development of muscle strength.     As for the research problem, the researcher found a method that has an effect on the development of force. Therefore, the researcher tried to diversify a

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Publication Date
Sat Dec 31 2016
Journal Name
مجلة جامعة االنبار للعلوم البدنية والرياضية
The effects of Pilates exercises while using the ladder barrel device on fitness and coordinatedin performance for motor formations in artistic gymnastics for students
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The aim of the research was to prepare Pilates exercises using the barrel ladder apparatus and to identify the effect of Pilates exercises on agility, coordination, and motor sequences of third-year female students in artistic gymnastics. The researcher adopted the experimental method to achieve the objectives of the study and to verify its hypotheses, as it is suitable for the nature and problem of the research. In selecting the research population, the researcher carefully chose the sample using a purposive method, clarifying its elements and constituent units. The research population consisted of third-year female students at the College of Physical Education and Sports Sciences for Women / University of Baghdad, with a total of 20 stud

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Publication Date
Mon May 01 2023
Journal Name
Ain Shams Engineering Journal
Neural network modeling of rutting performance for sustainable asphalt mixtures modified by industrial waste alumina
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