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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-dimensional Convolutional Neural Network Hybrid Model (1D-CNNHM). The MUCT database was considered for training and evaluation. The performance, in terms of classification, of the J48 model reached 96.01% accuracy whereas the DL model that merged LDA with MI and ANOVA reached 100% accuracy. Comparing the proposed models with other works reflects that they are performing very well, with high accuracy and low processing time.

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Publication Date
Fri Mar 06 2026
Journal Name
Modern Sport
Comparison of the speed of hospitalization according to the training load of some physiological and biochemical variables of badminton players and runner800 m youth
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It is necessary to use the means of recovery and other means that help to get rid of the effects of fatigue, as the game of badminton and the effectiveness of running 800 meters fall within the mixed system with the superiority of the anaerobic system by more than the air system, so requires the development of energy systems In proportion to the time of the match for badminton players and their travels and high performance and ability to tolerate the high level of lactic acid in the muscles and blood and increase the pain associated with the fatigue that occurs during the performance. In light of the physical and physiological processes of these actions N it should seek through training programs to develop your endurance and wind energy sys

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Publication Date
Tue Apr 16 2024
Journal Name
International Development Planning Review
RESISTANCE TRAINING IN THE WEIGHT OF DIFFERENT BODY PARTS AND THEIR EFFECT ON SOME MECHANICAL BIO VARIABLES AND THE ACHIEVEMENT OF THE HIGH JUMP FOR YOUNG PEOPLE
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The study aims to identify the effect of training with weight added to different parts of the body in improving the biomechanical variables of the last step and upgrading the high jump for young people, the research was applied to one of the elite high jumpers for young people, and video imaging and kinetic analysis were conducted to extract the variables under study, and then the jumper underwent For the proposed exercises by 3 training units per week for a period of (8) weeks, in which emphasis was placed on improving the rotational forces (moments) of these parts, and then the post-tests were conducted, and the researcher concluded that the exercises applied and the added weights for all parts of the body (leg, thigh, trunk, and arms) le

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Publication Date
Sun May 01 2022
Journal Name
International Journal Of Multiphase Flow
Application of artificial neural network to predict slug liquid holdup
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Publication Date
Tue Jan 01 2013
Journal Name
Thesis
User Authentication Based on Keystroke Dynamics Using Artificial Neural Networks
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Computer systems and networks are being used in almost every aspect of our daily life, the security threats to computers and networks have increased significantly. Usually, password-based user authentication is used to authenticate the legitimate user. However, this method has many gaps such as password sharing, brute force attack, dictionary attack and guessing. Keystroke dynamics is one of the famous and inexpensive behavioral biometric technologies, which authenticate a user based on the analysis of his/her typing rhythm. In this way, intrusion becomes more difficult because the password as well as the typing speed must match with the correct keystroke patterns. This thesis considers static keystroke dynamics as a transparent layer of t

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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Application of Artificial Neural Network for Predicting Iron Concentration in the Location of Al-Wahda Water Treatment Plant in Baghdad City
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Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul

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Publication Date
Sun Jun 09 2019
Journal Name
Al-kindy College Medical Journal
Early Detection of Left Ventricular Systolic Dysfunction in Asymptomatic Patients with Chronic Aortic Regurgitation by two Dimensional Speckle Tracking Echocardiography
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Background: Early detection of subclinical left ventricular (LV) systolic dysfunction is crucial and could influence patients' prognosis by aiding the clinician to candidate patients for better management.

Objective: To detect early LV systolic dysfunction in asymptomatic patient with chronic aortic regurgitation by two dimensional speckle tracking echocardiography.

 Methods:  Sixty one asymptomatic patients with chronic aortic regurgitation, with no ischemic heart diseases (by coronary angiography) or conductive heart diseases, no diabetes mellitus, no hypertension, and no other valvular heart diseases (group 1) and fifty age and sex-matched healthy subjects (

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Publication Date
Fri Jun 30 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Enhanced Prosthesis Control Through Improved Shoulder Girdle Motion Recognition Using Time-Dependent Power Spectrum Descriptors and Long Short-Term Memory
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Surface electromyography (sEMG) and accelerometer (Acc) signals play crucial roles in controlling prosthetic and upper limb orthotic devices, as well as in assessing electrical muscle activity for various biomedical engineering and rehabilitation applications. In this study, an advanced discrimination system is proposed for the identification of seven distinct shoulder girdle motions, aimed at improving prosthesis control. Feature extraction from Time-Dependent Power Spectrum Descriptors (TDPSD) is employed to enhance motion recognition. Subsequently, the Spectral Regression (SR) method is utilized to reduce the dimensionality of the extracted features. A comparative analysis is conducted between the Linear Discriminant Analysis (LDA) class

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Publication Date
Tue May 10 2022
Journal Name
Himalayan Journal Of Economics And Business Management
Information Systems Ethics and Its Role in Achieving Banking Discrimination Analytical Research in a Sample of Private Banks
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The research aims to shed light on the ethics of information systems and their role in achieving banking excellence for a sample of private banks in the province of Baghdad. It is important to focus on studying the ethics of banking information systems, which has become one of the most important basic and strategic resources that banks rely on to achieve outstanding performance. Achieving banking leadership in the Iraqi banking market. The researchers adopted the descriptive analytical approach to the research, and the questionnaire was considered as a main tool for collecting information in addition to personal interviews. The research reached the most important results that there is an acceptable correlation relationship between the ethic

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Publication Date
Fri Jan 26 2024
Journal Name
Journal Of Information Systems Engineering And Management
Application of Material Flow Cost Accounting Technology to Support Green Productivity and Its Reflection in Achieving Sustainable Development
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As material flow cost accounting technology focuses on the most efficient use of resources like energy and materials while minimizing negative environmental effects, the research aims to show how this technology can be applied to promote green productivity and its reflection in attaining sustainable development. In addition to studying sustainability, which helps to reduce environmental impacts and increase green productivity, the research aims to demonstrate the knowledge bases for accounting for the costs of material flow and green productivity. It also studies the technology of accounting for the costs of material flow in achieving sustainable development and the role of green productivity in achieving sustainable development. According

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
The impact of managing organizational diversity in achieving success Exploratory study in the Ministry of Industry and Minerals
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The aim of the research is to demonstrate the impact of organizational diversity management on achieving success, The problem of research is to create an appropriate work environment that stimulates everyone regardless of each dimension of diversity, So as to reach the best levels of success, The importance of research is to identify how the organization in question can manage organizational diversity effectively and contribute to its success, The research started from two main hypotheses which were derived from sub-hypotheses to identify the correlation and influence between the search variables by analyzing the answers of the research sample which included (81)

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