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A comprehensive review on modelling the adsorption process for heavy metal removal from waste water using artificial neural network technique
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Publication Date
Fri Sep 30 2016
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Experimental Study and Mathematical Modelling of Zinc Removal by Reverse Osmosis Membranes
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In this study, aromatic polyamide reverse osmosis membranes were used to remove zinc ions from electroplating wastewater. Influence of different operating conditions such as time, zinc concentration and pressure on reverse osmosis process efficiency was studied. The experimental results showed, concentration of zinc in permeate increase with increases of time from 0 to 70 min, and flux of water through membrane decline with time. While, the concentrations of zinc in permeate increase with the increase in feed zinc concentration (10–300 mg/l), flux decrease with the increment of feed concentration. The raise of pressure from 1 to 4 bar, the zinc concentration decreases and the flux increase. The highest recovery percentage was found is 54.

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Publication Date
Fri Sep 30 2016
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Experimental Study and Mathematical Modelling of Zinc Removal by Reverse Osmosis Membranes
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In this study, aromatic polyamide reverse osmosis membranes were used to remove zinc ions from electroplating wastewater. Influence of different operating conditions such as time, zinc concentration and pressure on reverse osmosis process efficiency was studied.  The experimental results showed, concentration of zinc in permeate increase with increases of time from 0 to 70 min, and flux of water through membrane decline with time. While, the concentrations of zinc in permeate increase with the increase in feed zinc concentration (10–300 mg/l), flux decrease with the increment of feed concentration. The raise of pressure from 1 to 4 bar, the zinc concentration decreases and the flux increase. The highest recovery percentage was fou

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Publication Date
Sat Jun 01 2024
Journal Name
Case Studies In Chemical And Environmental Engineering
Optimization of photocatalytic process with SnO2 catalyst for COD reduction from petroleum refinery wastewater using a slurry bubble photoreactor
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Publication Date
Tue Nov 01 2022
Journal Name
Inorganic Chemistry Communications
Sustainable adsorptive removal of high concentration organic contaminants from water using biodegradable Gum-Acacia integrated magnetite nanoparticles hydrogel adsorbent
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Release of industrial effluents comprising dyes in water bodies is one of the foremost causes of water pollution. Therefore, the proper and proficient treatment of these dyes contaminated left-over material before their release is crucial. Herein, an eco-friendly biological macromolecule Gum-Acacia (GA) integrated Fe3O4 nanoparticles composite hydrogel was manufactured via co-precipitation technique for effective adsorption of Congo red (CR) dye existing in water bodies. The as-prepared magnetic GA/Fe3O4 composite hydrogel was characterized by FTIR, XRD, EDX, VSM, SEM, and BET techniques. These studies discovered the fruitful fabrication of biodegradable magnetic GA/Fe3O4 composite hydrogel possessing porous structure with large surface are

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Publication Date
Mon Feb 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Comparative study of logistic regression and artificial neural networks on predicting breast cancer cytology
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<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

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Publication Date
Tue Sep 01 2020
Journal Name
Journal Of Engineering
Review on Heat Transfer Process Inside Open and Closed Porous Cavity
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Many researchers used different methods in their investigations to enhance the heat transfer coefficient, one of these methods is using porous medium. Heat transfer process inside closed and open cavities filled with a fluid-saturated porous media has a considerable importance in different engineering applications, such as compact heat exchangers, nuclear reactors and solar collectors. So, the present paper comprises a review on natural, forced, and combined convection heat transfer inside a porous cavity with and without driven lid. Most of the researchers on this specific subject studied the effect of many parameters on the heat transfer and fluid field inside a porous cavity, like the angle of inclination, the presenc

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Robotics And Control (jrc)
Automated Stand-alone Surgical Safety Evaluation for Laparoscopic Cholecystectomy (LC) using Convolutional Neural Network and Constrained Local Models (CNN-CLM)
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In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of University Of Anbar For Pure Science
A Short Review: Chemistry of Curcumin and Its Metal Complex Derivatives
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This review covers recent progress in the synthesis of curcumin and the bioactivity of semisynthetic and synthetic analogs of curcumin. The review also shows how curcumin is a useful intermediate for the synthesis of more complex organic molecules; historical perspective; the process of preparing the metal complexes and characterization the produced complexes using various spectral and other techniques; shows the importance of curcumin and its derivatives for their potential applications in medical devices and broad-spectrum of medical application such as antibiotic ointment, alternative therapeutics, antifungal, and antibacterial activities

Publication Date
Mon Sep 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Adsorption of Methyl Orange from Wastewater by using Biochar
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The biochar prepared from sawdust raw material was applied in this study for the treatment of wastewater polluted with methyl orange dye. The effect of pH (2-11), initial concertation (50-250 mg/L) and time were studied. The isotherm of Langmuir, Frendluch and temkin models studied. The Langmuir model was the best to explain the adsorption process, maximum uptake was 136.67 mg/g at 25Co of methyl orange dye. Equilibrium reached after four hours of contact for most adsorbents.The values of thermodynamic parameters ∆G were negative at various temperatures, so the process spontaneous, while ∆H values were 16683 j/mol and ∆S values was 60.82 j/mol.k.

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Publication Date
Wed Mar 24 2021
Journal Name
Ieee Access
Smart IoT Network Based Convolutional Recurrent Neural Network With Element-Wise Prediction System
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An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

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