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The effect of the activation functions on the classification accuracy of satellite image by artificial neural network
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Publication Date
Mon Oct 13 2025
Journal Name
Mesopotamian Journal Of Cybersecurity
Improvement of the Face Recognition Systems Security Against Morph Attacks using the Developed Siamese Neural Network
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Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

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Publication Date
Fri Jan 15 2021
Journal Name
Journal Of Mechanical Engineering Research And Developments
Comparison of the Effect Using Color Sensor and Pixy2 Camer on the Classification of Pepper Crop
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Image processing applications are currently spreading rapidly in industrial agriculture. The process of sorting agricultural fruits according to their color comes first among many studies conducted in industrial agriculture. Therefore, it is necessary to conduct a study by developing an agricultural crop separator with a low economic cost, however automatically works to increase the effectiveness and efficiency in sorting agricultural crops. In this study, colored pepper fruits were sorted using a Pixy2 camera on the basis of algorithm image analysis, and by using a TCS3200 color sensor on the basis of analyzing the outer surface of the pepper fruits, thus This separation process is done by specifying the pepper according to the color of it

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Publication Date
Fri Jan 02 2026
Journal Name
Al–bahith Al–a'alami
Adopting the public on satellite channels
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The importance of television has emerged as an effective and influential force in the lives of societies and peoples, And not just a professional media since the fifties of the twentieth century, It was used as a platform to achieve the goals and objectives of the media and politics for governments, agencies and individuals in different countries of the world, Using many methods, methods and techniques that later became important major subjects and curricula and a scientific specialization that was founded for him to study and teach in most international universities, The media, especially television and satellite channels, play an active and significant role in managing crises and conflicts and directing them through the methods of deal

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network
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       In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.

         

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Tuning PID Controller by Neural Network for Robot Manipulator Trajectory Tracking
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Ziegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller. This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions. In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities. The proportional, integral and derivative (KP, KI, KD) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control. The conventio

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
Water Quality Assessment and Total Dissolved Solids Prediction using Artificial Neural Network in Al-Hawizeh Marsh South of Iraq
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The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The develope

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Engineering/
Water quality assessment and total dissolved solids prediction using artificial neural network in Al-Hawizeh marsh south of Iraq
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The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The

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Publication Date
Sun Dec 17 2017
Journal Name
Al-khwarizmi Engineering Journal
Experimental and Prediction Using Artificial Neural Network of Bed Porosity and Solid Holdup in Viscous 3-Phase Inverse Fluidization
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In the present investigation, bed porosity and solid holdup in viscous three-phase inverse fluidized bed (TPIFB) are determined for aqueous solutions of carboxy methyl cellulose (CMC) system using polyethylene and polypropylene as  a particles with low-density and diameter (5 mm) in a (9.2 cm) inner diameter with height (200 cm) of vertical perspex column. The effectiveness of gas velocity Ug , liquid velocity UL, liquid viscosity μL, and particle density ρs on bed porosity BP and solid holdups εg were determined. The bed porosity increases with "increasing gas velocity", "liquid velocity", and "liquid viscosity". Solid holdup decreases with increasing gas, liquid

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Publication Date
Sun Mar 27 2022
Journal Name
Sport Tk-revista Euroamericana De Ciencias Del Deporte
Effect of resistance training on the biomechanics and accuracy of serve receiving skills in volleyball
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This study aimed to identify the effect of resistance training on the biomechanics and accuracy of serve receiving skills in volleyball. The research community was composed of 26 young volleyball players of Baghdad volleyball clubs. A total of 4 players were selected for the preliminary experiment, while 14 participants were recruited as the main sample for the study. In the present study, a set of resistance exercises were designed by the researchers for the volleyball players of the sample. Exercises were performed by the sample participants during the course of study. The biomechanical variables considered in the present study were: Preparation moment (shoulder joint angle, hip angle, knee joint angle), moment of pr

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Publication Date
Thu Dec 25 2025
Journal Name
Retos
The effect of neurofeedback on free throw accuracy in female basketball players of Baghdad University
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Background: Female basketball players often face difficulties in maintaining free throw accuracy, particularly under psychological and neural pressure. Traditional training emphasizes physical skills, often neglecting cognitive and neurophysiological factors essential for precision performance. Objective: This study examined the effect of neurofeedback training on free throw accuracy in female basketball players at the University of Baghdad, comparing outcomes between an experimental group and a control group, and assessing associated neural changes. Methods: A quasi-experimental design involved two groups: an experimental group receiving neurofeedback to regulate brainwave activity, and a control group undergoing traditional traini

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