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An Artificial Neural Network Prediction Model of GFRP Residual Tensile Strength
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This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperature exerted the most significant influence at 100%, while sample dimensions had a minimal impact at 17.9%. In addition, the mathematical model closest to the proposed was the Bazli model, because the latter depends on two variables (thickness and temperature). The ANN accurately predicted the residual tensile strength of GFRP at elevated temperatures, achieving a correlation coefficient of 97.3% and a determination coefficient of 94.3%.

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Publication Date
Wed Jul 31 2019
Journal Name
Journal Of Engineering
A Comparative Study of Various Intelligent Optimization Algorithms Based on Path Planning and Neural Controller for Mobile Robot
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In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Calculating the Transport Density Index from Some of the Productivity Indicators for Railway Lines by Using Neural Networks
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The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
The Effect Of Optimizers On The Generalizability Additive Neural Attention For Customer Support Twitter Dataset In Chatbot Application
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When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

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Publication Date
Thu Nov 19 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Enhanced Multistage RSA Encryption Model
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Publication Date
Sun Dec 10 2017
Journal Name
Al-academy
Technical Variation in Scientific Model
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The present study tackles the scientific model and the mechanisms of operating in the formation of the image of the artistic work to create a scene that cares for the aesthetic decoration through raw and techniques and employing them to express the aesthetic values that care for what is not familiar and deviation from the familiar in the visual exhibition and the care for the employment of the technical abilities, lighting, and sound as well as the employment of multiple materials. The research presents the objectives of his study in the exhibition hall of Natural History Museum (University of Baghdad) to create an aesthetic and expressive state at the same time. Then, in the theoretical framework the researcher traces the experiments of

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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Engineering
ESTIMATION THE 7 AND 28- DAY NORMAL COMPRESSIVE STRENGTH BY ACCELERATED TEST METHODS IN CONCRETE
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Curing of concrete is the maintenance of a satisfactory moisture content and temperature for a
period of time immediately following placing so the desired properties are developed. Accelerated
curing is advantages where early strength gain in concrete is important. The expose of concrete
specimens to the accelerated curing conditions which permit the specimens to develop a significant
portion of their ultimate strength within a period of time (1-2 days), depends on the method of the
curing cycle.Three accelerated curing test methods are adopted in this study. These are warm water,
autogenous and proposed test methods. The results of this study has shown good correlation
between the accelerated strength especially for

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Publication Date
Wed Nov 27 2024
Journal Name
Frontiers In Education
The impact of using artificial intelligence techniques in improving the quality of educational services/case study at the University of Baghdad
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The utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional quality.

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Publication Date
Mon Jan 01 2024
Journal Name
International Journal Of Literacy And Education
The availability of concepts and applications of artificial intelligence in the content of the chemistry textbook for the fourth scientific grade
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Publication Date
Wed Nov 27 2024
Journal Name
Frontiers In Education
The impact of using artificial intelligence techniques in improving the quality of educational services/case study at the University of Baghdad
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The utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional

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Publication Date
Sat Sep 30 2023
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The effect of operational efficiency on some financial indicators according to the CAMEL model of banking financial stability: An applied research on a sample of Iraqi private banks for the period 2010-2020
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Abstract

          The research aims to determine the nature of the Iraqi market in terms of banking financial stability and the extent impact of the operational efficiency on it, Accordingly, chosen 15 relational banks were chosen as an intentional sample that could represent the Iraqi banking system for the period 2010-2020. The operational efficiency variable was measured according to the data envelope model, and banking financial stability used  CAMELS model which includes five indicators (capital adequacy, asset quality, management quality, profitability, and liquidity), so for testing the research hypotheses used the random regression model by adopting the S

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