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Comparison of some artificial neural networks for graduate students
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Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, University of Baghdad for the period from 2014-2015 to The academic year 2017-2018. The variables are use in the research is (student’s success, age, gender, job, type of study (higher diploma, master’s, doctorate), specialization (statistics, economics, accounting, industry management, administrative management, and public administration) and channel acceptance). It became clear that the best variables that affect the success of graduate students are the type of study, age and job.                                                                                     

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Publication Date
Tue Apr 01 2025
Journal Name
Natural And Engineering Sciences
Comparison of Some Soil Mineral’s Ability to Adsorb and Release Lead and Rates of its Removal From its Aqueous Solutions
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To study the comparative use of some soil minerals (zeolite, bentonite, phosphate rock, and limestone) in the adsorption and release of lead and its removal rates from its aqueous solutions using adsorption equations. Two laboratory experiments were carried out for the adsorption and release of lead. The adsorption experiment took 0.5 g of some of the above soil minerals. Lead was added as Pb (NO3)2 at levels of 3.0, 2.0, 1.5, 1.0, 0.5, and 0.0 mmol L-1 containing a concentration of 0.01M of calcium chloride. The experimental unit’s number was 72, the concentration of dissolved lead in the equilibrium solution was estimated and the amount of lead adsorbed was calculated. As for the lead release experiment, samples fo

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Publication Date
Tue Apr 02 2024
Journal Name
Engineering, Technology & Applied Science Research
Two Proposed Models for Face Recognition: Achieving High Accuracy and Speed with Artificial Intelligence
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In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

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Publication Date
Sun Jan 04 2026
Journal Name
Steam-h: Science, Technology, Engineering, Agriculture, Mathematics; Health
Artificial Intelligence Applications for Achieving Economic Stability and Sustainable Growth in the Modern Era
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In recent years, the steady stream of artificial intelligence into economic systems has become a torrent. It is changing how we generate wealth and grow anew. Manufacturing, finance, health care energy, agriculture and education are just a few of the areas where AI may result in dramatic increases in productivity as well as innovation and sustainability. Predictive analytics, AI, robotics and natural language processing have significantly contributed in the improvement of resource allocation mechanisms and decision making as well as reaching SDGs. The concept of Artificial Humanity is also introduced in the paper. It shows how AI could become a global cognitive network to foster knowledge. By comparison and references of the literature, thi

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Publication Date
Sun Jun 30 2024
Journal Name
Modern Sport
The effect of an educational curriculum using virtual reality glasses in improving some kinetic abilities and learning freestyle swimming for first-year primary school students
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هدفت الدراسة الى الاهتمام واستغلال ماهو جديد من تقنيات واجهزة حديثة في تعليم السباحة الحرة عن طريق توجيه الاطفال على تطوير مداركهم واستيعابهم بالتطور التكنولوجي الذي يتناوله العالم ،قامت الباحثتان باعداد منهج تعليمي باستخدام نظارة الواقع الافتراضي وذالك بتوفير بيئة مشابهة للبيئة الحقيقية تحاكي مدارك عقول الاطفال في عالم افتراضي لتتكون صورة كاملة عن مهارات السباحة الحرة ،ومن هنا اتت المشكلة نتيجة تعل

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Publication Date
Tue Apr 30 2024
Journal Name
Modern Sport
Decision-making and its relationship to some basic offensive skills in female students’ basketball
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هدفت الدراسة الى التعرف على درجة اتخاذ القرار وعلاقتها ببعض المهارات  الأساسية الهجومية بكرة السلة للطالبات ، اذ يعد اتخاذ القرار قدرة الفرد على التوصل لحل مشكلة اعتراضية أو موقف محير، وذلك باختيار حل من البدائل الموجودة أو المبتكرة، وهذا الاختيار يعتمد على المعلومات التي جمعها الفرد حول المشكلة وعلى القيم والعادات والخبرة والتعليم والمهارات الفردية وتمتاز لعبة كرة السلة بوجود الكثير من المواقف المتغ

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Publication Date
Fri Jul 19 2024
Journal Name
An International Journal Of Optimization And Control: Theories & Applications (ijocta)
Design optimal neural network based on new LM training algorithm for solving 3D - PDEs
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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Automatic Spike Neural Technique for Slicing Bandwidth Estimated Virtual Buffer-Size in Network Environment
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The Next-generation networks, such as 5G and 6G, need capacity and requirements for low latency, and high dependability. According to experts, one of the most important features of (5 and 6) G networks is network slicing. To enhance the Quality of Service (QoS), network operators may now operate many instances on the same infrastructure due to configuring able slicing QoS. Each virtualized network resource, such as connection bandwidth, buffer size, and computing functions, may have a varied number of virtualized network resources. Because network resources are limited, virtual resources of the slices must be carefully coordinated to meet the different QoS requirements of users and services. These networks may be modifie

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Publication Date
Wed Jan 01 2014
Journal Name
International Journal Of Computer Applications
Enhancing the Delta Training Rule for a Single Layer Feedforward Heteroassociative Memory Neural Network
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In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Measuring the Use of Social Media Networks (SMNs) in Knowledge Sharing, by Using Social Cognitive Theory (SCT) A Study Conducted in Some of Iraqi Universities
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   SMNs like Facebook, YouTube, Twitter, WhatsApp,..etc. are among the most popular sites on the Internet. These sites can provide a powerful means of sharing, organizing, finding information and knowledge. The popularity of these sites provides an opportunity to measure the use them in knowledge sharing, which needs a special scale, but unfortunately, there is no special scale for that. Thus, this study supposes to use SCT as a scale to measure the use of SMNs in electronic knowledge sharing due to it has been used to measure knowledge sharing with its traditional form. This study can help the decision-makers to use these SMNs to share the academics’ knowledge in educational institutes to the communi

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Publication Date
Mon Dec 25 2017
Journal Name
Biomedical And Pharmacology Journal
Effect of the Addition of Polyamide (Nylon 6) Micro-Particles on Some Mechanical Properties of RTV Maxillofacial Silicone Elastomer Before and After Artificial Aging
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