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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
Mon Oct 30 2023
Journal Name
Traitement Du Signal
A Comprehensive Review on Machine Learning Approaches for Enhancing Human Speech Recognition
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Publication Date
Fri Aug 27 2021
Journal Name
Human Interaction, Emerging Technologies And Future Systems V: Proceedings Of The 5th International Virtual Conference On Human Interaction And Emerging Technologies, Ihiet 2021, August 27-29, 2021 And The 6th Ihiet: Future Systems (ihiet-fs 2021), October 28-30, 2021, France
Electricity Consumption Forecasting in Iraq with Artificial Neural Network
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Scopus (8)
Scopus
Publication Date
Thu Apr 28 2022
Journal Name
Iraqi Journal Of Science
Natural Attenuation Modelling of Heavy-Metal in Groundwater of Kirkuk City, Iraq
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This study deals with the shallow alluvial aquifer situated beneath the urban area of kirkuk city. The ancient part of the city (Shorja) is affected by seepage from local agricultural areas causing relatively high heavy metals concentration in groundwater. The selection of polluted site depended on the highest TDS value (3856 mg/L) associated with the highest heavy metal concentrations (Pb, Ni, Co and Zn) in groundwater. This study focuses on the evaluation of natural attenuation effectivity for long-term protection of groundwater quality using realistic three-dimensional reactive-transport groundwater model. The requirements of 3-dimensional reactive transport model were obtained from field observation and laboratory works, in addition

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Publication Date
Sun Jun 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Micro-Bubble Flotation for Removing Cadmium Ions from Aqueous Solution: Artificial Neural Network Modeling and Kinetic of Flotation
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In this work, microbubble dispersed air flotation technique was applied for cadmium ions removal from wastewater aqueous solution. Experiments parameters such as pH (3, 4, 5, and 6), initial Cd(II) ions concentration (40, 80, and 120 mg/l)  contact time( 2, 5, 10 , 15, and 20min), and surfactant (10, 20and 40mg/l) were studied in order to optimize the best conditions .The experimental results indicate that microbubbles were quite effective in removing cadmium ions and the anionic surfactant SDS was found to be more efficient than cationic CTAB in flotation process. 92.3% maximum removal efficiency achieved through 15min at pH 5, SDS surfactant concentration 20mg/l, flow rate250 cm3/min and at 40mg/l Cd(II) ions initial co

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Crossref (3)
Crossref
Publication Date
Fri Jan 01 2021
Journal Name
Environmental Pollution
Prediction of sediment heavy metal at the Australian Bays using newly developed hybrid artificial intelligence models
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Crossref (89)
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Publication Date
Sat Dec 01 2018
Journal Name
Indian Journal Of Ecology
Classification of al-hammar marshes satellite images in Iraq using artificial neural network based on coding representation
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Scopus (1)
Scopus
Publication Date
Wed Jan 01 2020
Journal Name
Solid State Technology
Image Fusion Using A Convolutional Neural Network
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Image Fusion Using A Convolutional Neural Network

Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Demulsification of Remaining Waste (Water In Oil Emulsions) After Removal Of Phenol In Emulsion Liquid Membrane Process
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The aim of present work is to study the removal of phenol present in aqueous feed solution by the emulsion liquid membrane technique using kerosene as a diluent, sodium hydroxide as a stripping agent, and sorbitan monooleate (Span 80) as a surfactant. The parameters studied were: surfactant concentration, volume ratio of membrane phase to internal phase, and stirring speed. It was found that more than 98% of phenol can be removed at the conditions were surfactant concentration 2% (v/v), volume ratio of membrane phase to internal phase 5:1 and stirring speed 400 rpm. Maximum phenol extraction efficiency at 7 minutes of process time was observed. It was found that there was a good agreement between the standard kerosene an

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Publication Date
Tue Jun 30 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Furfural Degradation in Waste Water by Advanced Oxidation Process Using UV/H2O2
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Furfural is one of the one of pollutants in refinery industrial wastewaters. In this study advanced oxidation process using UV/H2O2 was investigated for furfural degradation in synthetic wastewater. The results from the experimental work showed that the degradation of furfural decreases as its concentration increases, reaching 100% at 50mg/l furfural concentration and increasing the concentration of H2O2 from 250 to 500 mg/l increased furfural removal from 40 to 60%.The degradation of furfural reached 100% after 90 min exposure time using two UV lamps, where it reached 60% using one lamp after 240 min exposure time. The rate of furfural degradation k increased at the pH and initial concentratio

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Publication Date
Fri Dec 06 2019
Journal Name
Ssociation Of Arab Universities Journal Of Engineering Sciences
Application of Artificial Neural Network and GeographicalInformation System Models to Predict and Evaluate the Quality ofDiyala River Water, Iraq
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This research discusses application Artificial Neural Network (ANN) and Geographical InformationSystem (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameterswere used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium,Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity.These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala provincewhile it is poor to very polluted at the south of Baghdad City. The selected parameters wer

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