Preferred Language
Articles
/
Uhe7l5MBVTCNdQwCTdbp
An Artificial Neural Network Prediction Model of GFRP Residual Tensile Strength
...Show More Authors

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%.

Scopus Crossref
View Publication
Publication Date
Sun Dec 10 2023
Journal Name
Journal Of Applied Engineering And Technological Science (jaets)
The Role of Artificial Intelligence in Diagnosing Heart Disease in Humans: A Review
...Show More Authors

The electrical activity of the heart and the electrocardiogram (ECG) signal are fundamentally related. In the study that has been published, the ECG signal has been examined and used for a number of applications. The monitoring of heart rate and the analysis of heart rhythm patterns, the detection and diagnosis of cardiac diseases, the identification of emotional states, and the use of biometric identification methods are a few examples of applications in the field. Several various phases may be involved in the analysis of electrocardiogram (ECG) data, depending on the type of study being done. Preprocessing, feature extraction, feature selection, feature modification, and classification are frequently included in these stages. Ever

... Show More
View Publication
Scopus (3)
Crossref (3)
Scopus Crossref
Publication Date
Fri Jul 19 2019
Journal Name
Communications Chemistry
Positive functional synergy of structurally integrated artificial protein dimers assembled by Click chemistry
...Show More Authors
Abstract<p>Construction of artificial higher order protein complexes allows sampling of structural architectures and functional features not accessible by classical monomeric proteins. Here, we combine in silico modelling with expanded genetic code facilitated strain promoted azide-alkyne cycloaddition to construct artificial complexes that are structurally integrated protein dimers and demonstrate functional synergy. Using fluorescent proteins sfGFP and Venus as models, homodimers and heterodimers are constructed that switched ON once assembled and display enhanced spectral properties. Symmetrical crosslinks are found to be important for functional enhancement. The determined molecular structure of one artific</p> ... Show More
View Publication
Scopus (19)
Crossref (21)
Scopus Clarivate Crossref
Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Swab – Surge Pressure Investigation, and the Influence Factors, Prediction and Calculation (Review)
...Show More Authors

Surge pressure is supplemental pressure because of the movement of the pipes downward and the swab pressure is the pressure reduction as a result of the drill string's upward movement. Bottom hole pressure is reduced because of swabbing influence. An Investigation showed that the surge pressure has great importance for the circulation loss problem produced by unstable processes in the management pressure drilling (MPD) actions. Through Trip Margin there is an increase in the hydrostatic pressure of mud that compensates for the reduction of bottom pressure due to stop pumping and/or swabbing effect while pulling the pipe out of the hole. This overview shows suggested mathematical/numerical models for simulating surge pressure problems ins

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Thu Nov 29 2018
Journal Name
Al-khwarizmi Engineering Journal
Surface Roughness Prediction for Steel 304 In Edm Using Response Graph Modeling
...Show More Authors

Electrical Discharge Machining (EDM) is a non-traditional cutting technique for metals removing which is relied upon the basic fact that negligible tool force is produced during the machining process. Also, electrical discharge machining is used in manufacturing very hard materials that are electrically conductive. Regarding the electrical discharge machining procedure, the most significant factor of the cutting parameter is the surface roughness (Ra). Conventional try and error method is time consuming as well as high cost. The purpose of the present research is to develop a mathematical model using response graph modeling (RGM). The impact of various parameters such as (current, pulsation on time and pulsation off time) are studied on

... Show More
View Publication
Crossref (1)
Crossref
Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Permeability Prediction for Nahr-Umr Reservoir / Subba field by Using FZI Method
...Show More Authors

 The permeability determination in the reservoirs that are anisotropic and heterogeneous is a complicated problem due to the limited number of wells that contain core samples and well test data. This paper presents hydraulic flow units and flow zone indicator for predicting permeability of rock mass from core for Nahr-Umr reservoir/ Subba field. The Permeability measurement is better found in the laboratory work on the cored rock that taken from the formation. Nahr-Umr Formation is the main lower cretaceous sandstone reservoir in southern of Iraq. This formation is made up mainly of sandstone. Nahr-Umr formation was deposited on a gradually rising basin floor. The digenesis of Nahr-Umr sediments is very important du

... Show More
View Publication Preview PDF
Publication Date
Mon Mar 31 2025
Journal Name
International Journal Of Advanced Technology And Engineering Exploration
Breast cancer survival rate prediction using multimodal deep learning with multigenetic features
...Show More Authors

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

... Show More
View Publication Preview PDF
Scopus Crossref
Publication Date
Thu Jun 01 2017
Journal Name
Iosr Journal Of Computer Engineering
Lossy Image Compression Using Wavelet Transform, Polynomial Prediction And Block Truncation Coding
...Show More Authors

View Publication
Crossref
Publication Date
Thu Aug 02 2012
Journal Name
International Journal Of Advanced Research In Computer Science
User Authentication based on Keystroke Dynamics Using Backpropagation Network
...Show More Authors

Computer systems and networks are being used in almost every aspect of our daily life; as a result the security threats to computers and networks have also increased significantly. Traditionally, password-based user authentication is widely used to authenticate legitimate user in the current system0T but0T this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary attack, guessing, phishing and many more. The aim of this paper is to enhance the password authentication method by presenting a keystroke dynamics with back propagation neural network as a transparent layer of user authentication. Keystroke Dynamics is one of the famous and inexpensive behavioral biometric technologies, which identi

... Show More
Publication Date
Sat Jun 01 2024
Journal Name
Civil And Environmental Engineering
Constructing a Corrected Stations Network Using Some Geomatic Techniques
...Show More Authors
Abstract<p>The major objective of this study is to establish a network of Ground Control Points-GCPs which can use it as a reference for any engineering project. Total Station (type: Nikon Nivo 5.C), Optical Level and Garmin Navigator GPS were used to perform traversing. Traversing measurement was achieved by using nine points covered the selected area irregularly. Near Civil Engineering Department at Baghdad University Al-jadiriya, an attempt has been made to assess the accuracy of GPS by comparing the data obtained from the Total Station. The average error of this method is 3.326 m with the highest coefficient of determination (R<sup>2</sup>) is 0.077 m observed in Northing. While in</p> ... Show More
View Publication Preview PDF
Scopus (2)
Crossref (2)
Scopus Clarivate Crossref
Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Generative Adversarial Network for Imitation Learning from Single Demonstration
...Show More Authors

Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

... Show More
View Publication Preview PDF
Scopus Clarivate Crossref