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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.

Crossref
Publication Date
Fri May 01 2020
Journal Name
Journal Of Engineering
Chemical and Thermal Investigation on Stability of Tanuma Formation Using Different Additives with Drilling Fluids
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Wellbore stability is considered as one of the most challenges during drilling wells due to the
reactivity of shale with drilling fluids. During drilling wells in North Rumaila, Tanuma shale is
represented as one of the most abnormal formations. Sloughing, caving, and cementing problems
as a result of the drilling fluid interaction with the formation are considered as the most important
problem during drilling wells. In this study, an attempt to solve this problem was done, by
improving the shale stability by adding additives to the drilling fluid. Water-based mud (WBM)
and polymer mud were used with different additives. Three concentrations 0.5, 1, 5 and 10 wt. %
for five types of additives (CaCl2, NaCl, Na2S

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Crossref
Publication Date
Tue May 28 2019
Journal Name
Al-khwarizmi Engineering Journal
Heuristic D* Algorithm Based on Particle Swarm Optimization for Path Planning of Two-Link Robot Arm in Dynamic Environment
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 Finding a path solution in a dynamic environment represents a challenge for the robotics researchers, furthermore, it is the main issue for autonomous robots and manipulators since nowadays the world is looking forward to this challenge. The collision free path for robot in an environment with moving obstacles such as different objects, humans, animals or other robots is considered as an actual problem that needs to be solved.  In addition, the local minima and sharp edges are the most common problems in all path planning algorithms. The main objective of this work is to overcome these problems by demonstrating the robot path planning and obstacle avoidance using D star (D*) algorithm based on Particle Swarm Optimization (PSO)

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Publication Date
Mon Apr 10 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fabrication of Photodetector and Study of Its Structural and Optical Properties of Cadmium Oxide Thin Films Prepared by Vacuum Thermal Evaporation Method
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     The fabricated Photodetector n-CdO /-Si factory thin films Altboukaraharara spatial silicon multi- crystallization of the type (n-Type) the deposition of a thin film of cadmium and at room temperature (300K) and thickness (300 ± 20nm) and the time of deposition (1.25sec) was antioxidant thin films cadmium (Cd) record temperature (673k) for one hour to the presence of air and calculated energy gap optical transitions electronic direct ( allowed ) a function of the absorption coefficient and permeability and reflectivity by recording the spectrum absorbance and permeability of the membrane record within the wavelengths (300 1100nm). was used several the bias ranged between 1-5 Volts. The results showed that this

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Publication Date
Wed Dec 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of the Point Efficiency of Sieve Tray Using Artificial Neural Network
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An application of neural network technique was introduced in modeling the point efficiency of sieve tray, based on a
data bank of around 33l data points collected from the open literature.Two models proposed,using back-propagation
algorithm, the first model network consists: volumetric liquid flow rate (QL), F foctor for gas (FS), liquid density (pL),
gas density (pg), liquid viscosity (pL), gas viscosity (pg), hole diameter (dH), weir height (hw), pressure (P) and surface
tension between liquid phase and gas phase (o). In the second network, there are six parameters as dimensionless
group: Flowfactor (F), Reynolds number for liquid (ReL), Reynolds number for gas through hole (Reg), ratio of weir
height to hole diqmeter

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Publication Date
Sat Sep 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Synthesis and Character ation of Novel (Co (II), Ni{11>, .cuM, Zn en>, and Cd(ll)) Binuclear Complexes of N, N- his [(2, 4, 6-trihydroxy metbyl)] Benzidine
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The Synthesis C!}f    a;  rw;v Schiff  base ligan-d .N  ' N  - bis(2> 4,6-

trjpr;diOXY meth)l) benz1dine l 6L] aAd its c.omplexes w.ith·  Co 1ll 1 , Ni('ll);

cu< I·>     Zn(ll) .and Cd(TJJ are  reported . The  ltgand   was  prepared  by  the

reaction           of          4,4-aniino-biphenyl            benzidine     with     2,4;6· tnliydro yace ophenon mQnohydmte ander  reflux in m tbaool as solvent and a few d

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Electrical, thermal and optical characteristics of plasma torch
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Non thermal argon plasma needle at atmospheric pressure was constructed. The experimental set up was based on simple and low cost electric components that generate electrical field sufficiently high at the electrodes to ionize various gases which flow at atmospheric pressure. A high AC power supply was used with 9.6kV peak to peak and 33kHz frequency. The plasma was generated using two electrodes. The voltage and current discharge waveform were measured. The temperature of Ar gas plasma jet at different gas flow rate and distances from the plasma electrode was also recorded. It was found that the temperature increased with increasing frequency to reach the maximum value at 15 kHz, and that the current leading the voltage, which demonstra

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Crossref
Publication Date
Thu Dec 23 2010
Journal Name
Arabian Journal Of Geosciences
Climatic prediction of the terrestrial and coastal areas of Iraq
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Publication Date
Sun Mar 13 2011
Journal Name
Baghdad Science Journal
Impact of Rhizobial strains Mixture, Phosphorus and Zinc Applications in Nodulation and Yield of Bean(Phaseolus vulgaris L.)
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Pot experiment was carried out at the College of Agriculture – Baghdad University during autumn season, 2007. Thirteen treatments were formulated to evaluate the effectiveness of four applications of Phosphorus (0, 60, 60×2 and 120 Kg P. h-1) and three applications of Zinc (0, 25×2 mg Zn. L-1 and 50 mg Zn. Kg soil-1) along with inoculating seeds of bean with strains mixture 889 and 1865 and non-inoculated treatment, on nodulation, yield and protein content in seeds (N%). The results showed that inoculated plants exceeded on non-inoculated one in all the studied characteristics. While, P and Zn, applications at the rate of 60×2 kg/ha and 25×2 mg/L respectively, significantly, increased, nodulation, yield, protein content in se

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Crossref
Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Structure for Modeling and Controlling Nonlinear Systems
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This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

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Crossref
Publication Date
Wed Sep 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Application
Suggested methods for prediction using semiparametric regression function
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Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m

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