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High-accuracy models for iris recognition with merging features
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Due to advancements in computer science and technology, impersonation has become more common. Today, biometrics technology is widely used in various aspects of people's lives. Iris recognition, known for its high accuracy and speed, is a significant and challenging field of study. As a result, iris recognition technology and biometric systems are utilized for security in numerous applications, including human-computer interaction and surveillance systems. It is crucial to develop advanced models to combat impersonation crimes. This study proposes sophisticated artificial intelligence models with high accuracy and speed to eliminate these crimes. The models use linear discriminant analysis (LDA) for feature extraction and mutual information (MI), along with analysis of variance (ANOVA) for feature selection. Two iris classification systems were developed: one using LDA as an input for the OneR machine learning algorithm and another innovative hybrid model based on a One Dimensional Convolutional Neural Network (HM-1DCNN). The MMU database was employed, achieving a performance measure of 94.387% accuracy for the OneR model. Additionally, the HM-1DCNN model achieved 99.9% accuracy by integrating LDA with MI and ANOVA. Comparisons with previous studies show that the HM-1DCNN model performs exceptionally well, with at least 1.69% higher accuracy and lower processing time.

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Publication Date
Wed Apr 16 2025
Journal Name
International Journal Of Engineering Pedagogy (ijep)
Utilizing Machine Learning Techniques to Predict University Students' Digital Competence
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Given the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University

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Publication Date
Thu Sep 29 2022
Journal Name
Al–bahith Al–a'alami
Factors Affecting the Professional Performance of Editors of The News in Iraqi Satellite Channels - A research drawn from a Master Degree thesis
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Information pollution is regarded as a big problem facing journalists working in the editing section, whereby journalistic materials face such pollution through their way across the editing pyramid. This research is an attempt to define the concept of journalistic information pollution, and what are the causes and sources of this pollution. The research applied the descriptive research method to achieve its objectives. A questionnaire was used to collect data. The findings indicate that journalists are aware of the existence of information pollution in journalism, and this pollution has its causes and resources.

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Publication Date
Wed Nov 12 2025
Journal Name
Al–bahith Al–a'alami
Information Pollution in Iraqi Journalism…Study in Causes and Sources - A research drawn from a Master Degree thesis
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Information pollution is regarded as a big problem facing journalists working in the editing section, whereby journalistic materials face such pollution through their way across the editing pyramid. This research is an attempt to define the concept of journalistic information pollution, and what are the causes and sources of this pollution. The research applied the descriptive research method to achieve its objectives. A questionnaire was used to collect data. The findings indicate that journalists are aware of the existence of information pollution in journalism, and this pollution has its causes and resources.

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Publication Date
Thu Apr 01 2021
Journal Name
Chaos, Solitons & Fractals
Modeling and analysis of an <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si7.svg"><mml:mrow><mml:mi>S</mml:mi><mml:msub><mml:mi>I</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:msub><mml:mi>I</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mi>R</mml:mi></mml:mrow></mml:math> epidemic model with nonlinear incidence and general recovery functions of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si8.svg"><mml:msub><mml:mi>I</mml:mi><mml:mn>1</mml:mn></mml:msub></mml:math>
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Publication Date
Fri Jul 25 2025
Journal Name
Modern Sport
An Analytical Study on the Performance of the Video Assistant Referee (VAR) System in the Iraq Stars Football League
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The Video Assistant Referee (VAR) is a technology designed to review on- eld decisions through video footage in order to correct clear and critical refereeing errors. It enables the replay of key moments in slow motion to determine the correct naldecision,withcommunicationbetweenthevideoof cialsandtherefereeconductedviaheadset.Thesystem operates under the principle of "minimal interference, maximum bene t," intervening only in essential situations. This study aimedtoassessthecurrent implementationofVARintheIraqStarsFootballLeagueduringthe2023–2024season. To achieve this objective, the researchers employed a descriptive survey method involving a sample of 220 participants, including referees, coaches, players, assessors, academics, a

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
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
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Attention-Deficit Hyperactivity Disorder Prediction by Artificial Intelligence Techniques
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Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

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Publication Date
Sun Mar 30 2025
Journal Name
Mustansiriyah Journal Of Pure And Applied Sciences
Secure E-voting authentication system employing biometric technology, Crypto-Watermarking Approach and blockchain technology: A Review
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Moderately, advanced national election technologies have improved political systems. As electronic voting (e-voting) systems advance, security threats like impersonation, ballot tampering, and result manipulation increase. These challenges are addressed through a review covering biometric authentication, watermarking, and blockchain technologies, each of which plays a crucial role in improving the security of e-voting systems. More precisely, the biometric authentication is being examined due to its ability in identify the voters and reducing the risks of impersonation. The study also explores the blockchain technology to decentralize the elections, enhance the transparency and ensure the prevention of any unauthorized alteration or

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Publication Date
Thu Nov 08 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Effectiveness of osteoporosis prevention instruction program on nursing college students’ knowledge at Baghdad University
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Objective(s): Assess the effectiveness of osteoporosis prevention instruction program on nursing college students’
knowledge at Baghdad University.
Methodology: A quasi-experimental design was used to assess the effectiveness of osteoporosis prevention
instruction program on nursing college students at University of Baghdad from April 2011 to September 2011. A
random sample consisted of (40) females students from first year of Nursing College \ Baghdad University. The data
was collected by using constructed questionnaire, which consists of three parts. Part one: consists of demographic
information and health characteristics .Part two: consists of students’ daily life behaviors which include, dietary
behaviors, an

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Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Educational And Psychological Researches
Violence and sexual harassment against minors, causes, prevention strategies
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The aim of this study to investigate the sexual harassment, prevention strategies, and the appropriate ways that tackle this phenomena. The current research consisted of four chapter; the first chapter gave a general introduction about the targeted topic followed by the problem of statement, the significance of study, study’s aims, and end with the limitations of study. The second section of chapter one referred to the common concepts of study. Third section addressed the previous studies that related to the current one. Chapter two concerned with the sexual violence against minors. It has four section; first section addressed number of concepts which related to sexual violence. The second section focused on the implications of sexual

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