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EVALUATE THE RATE OF CONTAMINATION SOILS BY COPPER USING NEURAL NETWORK TECHNIQUE
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The aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to evaluate concentration of Copper in contaminated soils. First, sixteen (4x4) soil samples were harvested from a phytoremediated contaminated site located in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Copper. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this study show that the ANN technique trained on experimental measurements can be successfully applied to the rapid estimation of Copper.

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Publication Date
Fri Dec 01 2023
Journal Name
Case Studies In Chemical And Environmental Engineering
Removal of copper from a simulated wastewater by electromembrane extraction technique using a novel electrolytic cell provided with a flat polypropylene membrane infused with 1-octanol and DEHP as a carrier
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Publication Date
Sun Feb 10 2019
Journal Name
Iraqi Journal Of Physics
Copper nanoparticles prepared by pulsed exploding wire
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In this work copper nanopowder was created at different liquid
medias like DDDW, ethylene glycol and Polyvinylpyrrolidone
(PVP). Copper nanopowder prepared using explosion wire process
and investigated the effects of the exploding energy, wire diameter,
the type of liquid on the particle size, and the particles size
distribution. The nanoparticles are characterized by x-ray diffraction,
UV-visible absorption spectroscopy and transmission electron
microscopy (TEM). The x-ray diffraction results reveal that the
nanoparticles continue to routine lattice periodicity at reduced
particle size. The UV-Visible absorption spectrum of liquid solution
for copper nanoparticles shows sharp and single surface Plasmon
r

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Publication Date
Tue Oct 04 2022
Journal Name
Caspian Journal Of Environmental Sciences
Detecting genetics of several isolated bacterial species from soils by hydrocarbons
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The presence of hydrocarbons in the soil is considered one of the main problems of pollution. In our current study, eight samples isolated from soil saturated with hydrocarbons were taken from different areas of Baghdad, Iraq. In this study, 5 isolates belonging to Pseudomonas aeruginosa by 99%, 4 isolates to Klebsiella pneumoniae by 98%, and 3 isolates to Enterobacter hormaechei by 97% were diagnosed in different ways. A molecular examination was also conducted by 16sRNA. We recorded P. aeruginosa, K. Pneumoniae and E. hormaechei as new local isolates in NCBI. In addition, a comparison was made between our isolates and the global isolates to determine the degree of convergence in the evolutionary line. The genes alkB and nahAc7 were diagno

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Scopus (4)
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Publication Date
Tue Sep 01 2020
Journal Name
Iraqi Journal Of Physics
Enhancment of the corrosion resistance of copper metal by laser surface treatment
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In this work, the copper metal was treated using Nd:YAG laser with energy 1Joul to enhance corrosion resistance and improve surface properties. The copper metal has many applications in industry as well as water, oil and gas pipes. The same conditions, (laser power density, scan speed, distance between paths, medium gas-air) were applied in the laser surface treatment, After laser treatment, the samples microstructures were investigated using optical microscope (OM) to examine micro structural changes due to laser irradiation. Specimen surfaces were investigated using atomic force microscopy (AFM), X-ray diffraction (XRD), macro hardness, and corrosion test before and after laser treatment to

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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Application of Artificial Neural Network for Predicting Iron Concentration in the Location of Al-Wahda Water Treatment Plant in Baghdad City
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Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul

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Publication Date
Mon Jul 22 2019
Journal Name
Innovations In Pharmacy
Evaluate Factors Influencing Depression in Baghdad: Using Deck-Depression Inventory
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Objective: This study goal was to screen participants from different settings in Baghdad for depression using Beck Depression Inventory (BDI) scale and identify factors influencing the levels of depression. Methods: This cross-sectional study included a convenience sample of 313 people from four settings (teaching hospital, college of medicine, college of pharmacy, and high school) in Baghdad, Iraq. The participants were screened using paper survey relying on the BDI scale during spring 2018. Using multiple linear regression analysis, we measured the association between depression scores and six participant factors. Results: The overall prevalence of depression in our sample was 57.2%. Female participants had higher BDI

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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Engineering
Compensation of the Nonlinear Power Amplifier by Using SCPWL Predistorter with Genetic Algorithm in OFDM technique
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The High Power Amplifiers (HPAs), which are used in wireless communication, are distinctly characterized by nonlinear properties. The linearity of the HPA can be accomplished by retreating an HPA to put it in a linear region on account of power performance loss. Meanwhile the Orthogonal Frequency Division Multiplex signal is very rough. Therefore, it will be required a large undo to the linear action area that leads to a vital loss in power efficiency. Thereby, back-off is not a positive solution. A Simplicial Canonical Piecewise-Linear (SCPWL) model based digital predistorters are widely employed to compensating the nonlinear distortion that introduced by a HPA component in OFDM technology. In this paper, the genetic al

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

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Publication Date
Sun Nov 01 2015
Journal Name
Journal Of Engineering
A Spike Neural Controller for Traffic Load Parameter with Priority-Based Rate in Wireless Multimedia Sensor Networks
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Wireless Multimedia Sensor Networks (WMSNs) are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to   produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC). The Modify Spike Neural Network controller (MSNC) can calculate the appropriate traffi

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
Development and Assessment of Feed Forward Back Propagation Neural Network Models to Predict Sunshine Duration
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         The duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmosp

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