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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
Mon Apr 21 2025
Journal Name
Structural Concrete
On the effectiveness of shear reinforcement type in <scp>GFRP</scp>‐reinforced concrete beams: Experimental study
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Abstract<p>This study investigated the shear performance of concrete beams with GFRP stirrups vs. traditional steel stirrups. Longitudinal glass fiber‐reinforced polymer (GFRP) bars were used to doubly reinforce the tested beams at both the top and bottom of their cross sections. To accomplish this, several stirrup spacings were provided. Eight beam specimens, measuring 300 × 250 × 2400 mm, were used in an experimental program to test under a two‐point concentrated load with an equal span‐to‐depth ratio until failure. Four beams in Group I have standard mild steel stirrups of 8 mm diameter, while four beams in Group II have GFRP stirrups with the same adopted diameter. The difference betwe</p> ... Show More
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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of International Society Of Preventive And Community Dentistry
Investigating tensile bonding and other properties of yttrium oxide nanoparticles impregnated heat-cured soft-denture lining composite in vitro
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Aims: This study was conducted to assess the effect of the addition of yttrium oxide (Y2O3) nanoparticles on the tensile bond strength, tear strength, shore A hardness, and surface roughness of soft-denture lining material. Materials and Methods: Y2O3 NPs with 1.5 and 2 wt.% were added into acrylic-based heat-cured soft-denture liner. A total of 120 specimens were prepared and divided into four groups according to the test to be performed (tensile bond strength, tear strength, surface hardness, and surface roughness). Results: There was a highly significant increase in tensile bond strength between the soft liner and the acrylic denture base, tear strength, and hardness at both concentrations as compared to the control group, whereas ther

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

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Publication Date
Sun Dec 16 2018
Journal Name
Al-academy
An Educational Model in Journalistic Production Course to Develop the Creative Thinking Skills of Printing Design Students
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The printing designer's creative thinking is a deliberate  mental process based on specific skills that stimulate the motivation of  the student to learn and call for  new information for the investigation and research to discover the problems and attitudes and through reformulating the experience in new patterns depending on the active imagination and the flexible scientific thinking through providing the largest number possible  of various unfamiliar  printing design models, and testing their suitability and then readjusting the results with the availability of  suitable educational, learning and academic atmosphere.

The designer's creative thinking depends on main skills. Fluency skill is to put t

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Publication Date
Sat Jan 01 2022
Journal Name
1st Samarra International Conference For Pure And Applied Sciences (sicps2021): Sicps2021
The persistence and bifurcation analysis of an ecological model with fear effect involving prey refuge and harvesting
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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

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Publication Date
Mon Feb 21 2022
Journal Name
Applied Sciences
The Behavior of Hybrid Fiber-Reinforced Concrete Elements: A New Stress-Strain Model Using an Evolutionary Approach
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Several stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of concrete. For this reason, the researchers conducted an experimental program to determine the stress-strain relationship of 30 concrete samples reinforced with two distinct fibers (a hybrid of polyvinyl alcohol and steel fibers), with compressive strengths ranging from 40 to 120 MPa. A total of 80% of the experimental results were used to develop a new empirical stress-strain model, which was accomplished through the application of the parti

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Publication Date
Mon Dec 01 2008
Journal Name
Journal Of Economics And Administrative Sciences
Neural Networks as a Discriminant Purposes
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Discriminant between groups is one of the common procedures because of its ability to analyze many practical phenomena, and there are several methods can be used for this purpose, such as linear and quadratic discriminant functions. recently, neural networks is used as a tool to distinguish between groups.

In this paper the simulation is used to compare neural networks and classical method for classify observations to group that is belong to, in case of some variables that don’t follow the normal distribution. we use the proportion of number of misclassification observations to the all observations as a criterion of comparison.  

 

 

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Direction Finding Using GHA Neural Networks
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 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

 

 

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Publication Date
Sun Jan 15 2023
Journal Name
Dental Hypotheses
Effect of addition of polymerized polymethyl methacrylate (PMMA) and zirconia particles on impact strength, surface hardness, and roughness of heat cure PMMA: An in vitro study
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Introduction: This study was designed to examine the effects of addition of the combination of polymerized polymethyl methacrylate (PMMA) and zirconia (ZrO2) particles to heat cure PMMA resin on impact strength, surface hardness, and roughness. Methods: The 70% (w/w) of polymerized PMMA powder (particle size: 0.70mm) was mixed with 30% (w/w) of zirconia powder (ZrO2) (1mm) to produce PMMA-ZrO2 filler. Ninety acrylic specimens created were divided into three groups containing 0% wt (Control group), 2% wt, and 4% wt, PMMA-ZrO2 filler. Ten specimens were used for impact strength, surface hardness and roughness test, blindly. Data were analyzed via oneway ANOVA and the Tukey post hoc test using R 3.6.3. Results: There was statistically signific

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