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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
Thu Jan 29 2026
Journal Name
Journal Of Interdisciplinary Mathematics
Efficient design of neural network based on modified LM training algorithm for solving nonlinear 4th order 3D-PDEs 
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Authors in this work design efficient neural networks, which are based on the modified Levenberg - Marquardt (LM) training algorithms to solve non-linear fourth - order three -dimensional partial differential equations in the two kinds in the periodic and in the non-periodic - Periodic. Software reliability growth models are essential tools for monitoring and evaluating the evolution of software reliability. Software defect detection events that occur during testing and operation are often treated as counting processes in many current models. However, when working with large software systems, the error detection process should be viewed as a random process with a continuous state space, since the number of faults found during testin

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Publication Date
Tue Aug 27 2024
Journal Name
Tem Journal
Preparing the Electrical Signal Data of the Heart by Performing Segmentation Based on the Neural Network U-Net
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Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files tha

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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Use Of Artificial Neural Networks In Developing The Role Of Auditor In Discovering Fundamental Errors: An Applied Research In General Company for Electrical Industries and Nasr General Company for Mechanical Industries
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Artificial neural networks usage, as a developed technique, increased in many fields such as Auditing business. Contemporary auditor should cope with the challenges of the technology evolution in the business environment by using computerized techniques such as Artificial neural networks, This research is the first work made in the field of modern techniques of the artificial neural networks in the field of auditing; it is made by using thesample of neural networks as a sample of the artificial multi-layer Back Propagation neural networks in the field of detecting fundamental mistakes of the financial statements when making auditing. The research objectives at offering a methodology for the application of theartificial neural networks wi

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Publication Date
Tue Jun 30 2015
Journal Name
Al-khwarizmi Engineering Journal
Tensile and Compressive Properties of Kaolin Rienforced Epoxy
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Abstract

The toughening of epoxy resins with the addition of organic or inorganic compounds is of great interest nowadays, considering their large scale of applications. In the present work, composites of epoxy are synthesized with kaolin particles having different particle sizes as reinforcement. Composites of epoxy with varying concentration (0 to 40 weight %) of kaolin was prepared by using hand lay method. The variation of mechanical properties such as modulus of elasticity, yield, tensile, and compressive strength with filler content was evaluated. The composite showed improved modulus of elasticity and compressive properties on addition of filler. In contrast, the tensile and yield strength of the composite

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Publication Date
Thu Mar 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
An Artificial Intelligence Algorithm to Optimize the Classification of the Hepatitis Type
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Hepatitis is one of the diseases that has become more developed in recent years in terms of the high number of infections. Hepatitis causes inflammation that destroys liver cells, and it occurs as a result of viruses, bacteria, blood transfusions, and others. There are five types of hepatitis viruses, which are (A, B, C, D, E) according to their severity. The disease varies by type. Accurate and early diagnosis is the best way to prevent disease, as it allows infected people to take preventive steps so that they do not transmit the difference to other people, and diagnosis using artificial intelligence gives an accurate and rapid diagnostic result. Where the analytical method of the data relied on the radial basis network to diagnose the

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Publication Date
Thu Sep 01 2011
Journal Name
Journal Of Baghdad College Of Dentistry
Push out bond strength of different obturation systems (An in vitro study)
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Background: The bond strength of the root canal sealers to dentin seems to be a very important property for maintaining the integrity and the seal of root canal filling. The aim of this study was to evaluate the shear bond strength of four different obturation systems using push-out test. Materials and methods: Forty straight palatal roots of the maxillary first molars teeth were used in this study, these roots were instrumented using crown down technique and ProTaper system, instrumentation were done with copious irrigation of 2.5% sodium hypochlorite and 17% buffered solution of EDTA was used as final irrigant followed by distilled water, roots were randomly divided into four groups according to the obturation system (ten teeth for each g

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of The Mechanical Behavior Of Materials
Structural behavior of one-way slabs reinforced by a combination of GFRP and steel bars: An experimental and numerical investigation
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Abstract<p>Glass- fiber-reinforced polymer (GFRP) offers a significant alternative to steel in reinforced concrete, with superior corrosion and fire resistance. Though less ductile and more brittle in stress–strain behavior than steel, it is very helpful to combine GFRP with steel reinforcement that improves the structural behavior. This research investigates the flexural characteristics of a one-way slab reinforced by a combination of GFRP and steel reinforcement. Three identical concrete slabs ((1500 × 550 × 120) mm and 43 MPa) were tested under static load with GFRP replacement ratios of (0, 20, and 40)%. The experimental data were utilized to verify a numerical model. The experimen</p> ... Show More
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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Research In Medical And Dental Science
Evaluation of Bond Strength of Acrylic Artificial Teeth with Unreinforced and Nano Silica Reinforced Denture Base Material after Chemical Disinfection
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Soaking dentures with disinfection solutions is an effective way of keeping dentures in a healthy status; however, immersions in these solutions have a negative effect on the bond strength of denture base and denture teeth. The aim of this study was to evaluate the bond strength between denture acrylic teeth and heat-cured Poly (methyl methacrylate) denture base material (with and without nano silica) after disinfection with different chemical disinfectants for a simulated period of six months. One hundred specimens of maxillary central incisors attached to PMMA were divided into two groups; 50 specimens of PMMA without nano silica and 50 specimens of PMMA reinforced with 5 wt% of nano silica. Specimens of each group were immersed in five i

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Publication Date
Fri Mar 01 2024
Journal Name
International Journal Of Medical Informatics
An artificial intelligence approach to predict infants’ health status at birth
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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Fractographic Analysis of Tensile Failures of Zirconia Epoxy Nanocomposites
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This work characterizes the fractographic features of the neat epoxy and ZrO2 epoxy nanocomposites. All samples were subjected to a tensile test to determine the tensile strength and tensile modulus. SEM images were used to study the morphology of the fractured surface. The fractographic of the fracture surfaces were studied by microstructure analysis program (j-images) to specify the effect of ZrO2 nanoparticles on tensile performance and failure mechanism for ZrO2 epoxy nanocomposites. The tensile test results show that the addition of ZrO2 nanoparticles (2, 4, 6, 8, and 10 vol.%) to the epoxy matrix leads to increase the tensile strength about 40% for optimal content of ZrO2 nanop

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