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Optimization, modeling and accurate prediction of thermal conductivity and dynamic viscosity of stabilized ethylene glycol and water mixture Al 2 O 3 nanofluids by NSGA-II using ANN
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In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and introduced. Optimal results showed that the optimum viscosity and thermal conductivity occurs at maximum temperature.

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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Numerical Modeling of Renal Ionic Equilibrium for Implantable Kidney Applications
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The human kidney is one of the most important organs in the human body; it performs many functions
and has a great impact on the work of the rest of the organs. Among the most important possible treatments is
dialysis, which works as an external artificial kidney, and several studies have worked to enhance the
mechanism of dialysate flow and improve the permeability of its membrane. This study introduces a new
numerical model based on previous research discussing the variations in the concentrations of sodium,
potassium, and urea in the extracellular area in the blood during hemodialysis. We simulated the differential
equations related to mass transfer diffusion and we developed the model in MATLAB Simu

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
MODELING DEATH RATE OF THE COVID-19 PANDEMIC IN IRAQ
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Scopus
Publication Date
Tue Oct 01 2019
Journal Name
2019 12th International Conference On Developments In Esystems Engineering (dese)
Structural Modeling of Cross-Frame Behavior in Steel Girder Bridges
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Publication Date
Tue Mar 16 2021
Journal Name
2021 4th International Conference On Energy Conservation And Efficiency (icece)
Finite Element Modeling Of Finned Double-Pass Solar Air Heaters
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Publication Date
Tue Dec 01 2009
Journal Name
Iraqi Journal Of Physics
Analytical Performance Modeling of InP-InGaAs Hetero-junction Avalanche Photodiode
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In this study, an analytical model depending on experimental results for InPInGaAs
avalanche photodiode at low bias was presented and the characteristics of
gain for this photodiode were determined directly by the impulse response. The
model have considered the most important mechanisms contributing the
photocurrent, they are trapping, photogeneration in the undepleted region and
charge-carriers velocity due to the built-in electrical field. Also, the bandwidth
was determined as a function to the total gain of photodiode and it was mainly
determined by diffusion and trapping processes at low gain regarding to the multilayer
structure considered in this study

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Publication Date
Sun Oct 02 2022
Journal Name
Engineering, Technology & Applied Science Research
Statistical Modeling for Traffic Noise: The Case of Kirkuk City
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The auditory system can suffer from exposure to loud noise and human health can be affected. Traffic noise is a primary contributor to noise pollution. To measure the noise levels, 3 variables were examined at 25 locations. It was found that the main factors that determine the increase in noise level are traffic volume, vehicle speed, and road functional class. The data have been taken during three different periods per day so that they represent and cover the traffic noise of the city during heavy traffic flow conditions. Analysis of traffic noise prediction was conducted using a simple linear regression model to accurately predict the equivalent continuous sound level. The difference between the predicted and the measured noise shows that

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Publication Date
Mon Dec 02 2024
Journal Name
Engineering, Technology & Applied Science Research
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. Temperatur

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Publication Date
Wed Mar 04 2026
Journal Name
Journal Of Engineering
Drag Reduction by using Anionic Surfactants
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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Image Steganography by Using Multiwavelet Transform
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Steganography is the art of secret communication. Its purpose is to hide the presence of information, using, for example, images as covers. The frequency domain is well suited for embedding in image, since hiding in this frequency domain coefficients is robust to many attacks. This paper proposed hiding a secret image of size equal to quarter of the cover one. Set Partitioning in Hierarchal Trees (SPIHT) codec is used to code the secret image to achieve security. The proposed method applies Discrete Multiwavelet Transform (DMWT) for cover image. The coded bit stream of the secret image is embedded in the high frequency subbands of the transformed cover one. A scaling factors ? and ? in frequency domain control the quality of the stego

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Publication Date
Thu Sep 01 2022
Journal Name
Iop Conference Series: Earth And Environmental Science
Non-Diatomic Diversity and Community Structure in Hoor-Al- Azime Marshes, Iran
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Abstract<p>This study was conducted to delineate diversity and species composition of non-diatoms planktonic algae in Hoor- Al- Azime marshes, Iran. The samples were collected from four sites at monthly basis from April 2011 to March 2012. A total 88 taxa were identified, out of which (40 taxa, 45.45%) belonging to Cyanophyta followed by Chlorophyta (29 taxa, 32.96%), Euglenophyta (18 taxa, 20.45%) and (1 taxa, 1.14%) of Dinophyta recorded. Comparing species richness (65 taxa, 34.76%) at Shat- Ali (St4) was the highest and the lowest (34 taxa, 18.18%) was observed at Rafi (St2). Species occurrence was associated with temperature where in summer (66 taxa) and (25 taxa) encountered winter. The phy</p> ... Show More
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