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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 concentration. The removal efficiency of cadmium ion was predicted through 11 neurons hidden layer, with a correlation coefficient of 0.9997 between ANN outputs and the experimental data and through sensitivity analysis, pH was found to be most significant parameter (25.13 %).The kinetic flotation order for cadmium ions almost first order and the removal rate constant (k) increases with decreasing the initial metal concentration.

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Compared with Genetic Algorithm Fast – MCD – Nested Extension and Neural Network Multilayer Back propagation
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The study using Nonparametric methods for roubust to estimate a location and scatter it is depending  minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .       

It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu

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Publication Date
Thu Oct 30 2025
Journal Name
Iraqi Journal Of Science
Postmortem Panoramic Dental Radiography: Human Identification Based on Convolution Neural Network and Contourlet Transform
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Human identification is crucial in forensics for the investigation of large-scale disasters such as fires, epidemics, earthquakes, and tsunamis. Even though biometric identification using panoramic dental radiography (PDR) has been the subject of several studies in the literature, further study remains a necessary and challenging issue. In this research, a human identification system was developed based on a convolutional neural network (CNN) and contour transform (CT). The proposed system was implemented on a total of 1540 PDR from 302 individuals. The preprocessing applied to PDRs for enhancing and taking the Region of Interest (ROI). The features were extracted using CT transform. These features were fused with features extracted

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Publication Date
Mon Oct 20 2025
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
<b>Commercial Graphite Flakes as an Adsorbent of Janus Green Dye from Aqueous Solution: Adsorption Kinetics and Isotherms Study</b>
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Commercial graphite (CGT) powder was used as an adsorbent surface for cationic dye, Janus green (JG), from aqueous solutions. This study aims to highlight the practical significance of using inexpensive CGT as an efficient adsorbent for the removal of JG dye from industrial wastewater. CGT was characterized by Fourier transform infrared spectroscopy, scanning electron microscopy, and X-ray diffraction. The adsorption process was investigated by examining parameters like the weight of the adsorbent, contact time, and temperature. Pseudo-second-order kinetic (PSO), pseudo-first-order, and intraparticle diffusion were used for analyzing the kinetic data. JG dye's adsorption kinetics fit the PSO kinetic model well (R2= 0.999). Furthermo

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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
Thu May 18 2023
Journal Name
Journal Of Engineering
Competitive Stripping of Multi-Organic Pollutants from Contaminated Water in Bubble Column Semi-Batch
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Air  stripping  for  removal  of  Trichloroethylene  (TCE),  Chloroform  (CF)  and  Dichloromethane (DCM) from water were studied in a bubble column (0.073 m inside dia. and 1.08 m height with several sampling ports). The contaminated water was prepared from deionized water and VOCs. The presence of VOCs in feed solution was single, binary or ternary components. They were diluted to the concentrations ranged between 50 mg/l to 250 mg/l. The experiments were carried out in batch experiments which regard the bubble column as stirred tank and only gas was bubbled through stationary liquid. In this case transient measurements of VOC concentration in the liquid phase and the measured concentra

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Publication Date
Sat Jun 01 2024
Journal Name
Case Studies In Chemical And Environmental Engineering
Congo red removal from aqueous solution by electrocoagulation- electro-oxidation combined system with Al and Cu–Mn–Ni nano composite as efficient electrodes
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Removing Congo red (CR) is critical in wastewater treatment. We introduce a combination of electrocoagulation (EC) and electro-oxidation (EO) to address the elimination of CR. We also discuss the deposition of triple oxides (Cu–Mn–Ni) simultaneously on both anodic and cathodic graphite electrodes at constant current density. These electrodes efficiently worked as anodes in the EC-EO system. The EC-CO combination eliminated around 98 % of the CR dye and about 95 % of the Chemical Oxygen demand (COD), and similar results were obtained with the absence of NaCl. Thus, EC-EO is a promising technique to remove CR in an environmentally friendly pathway.

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Publication Date
Thu Sep 13 2012
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Density and Viscosity of Amino Acid Serine in aqueous dimethyl sulfoxide solution at deferent temperatures
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Publication Date
Fri Feb 03 2012
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Viscosity and Density of Chrom Alum in Aqueous Poly (Ethylene Glycol) Solution at Different Temperature
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Density data of alum chrom in water and in aqueous solution of poly (ethylene glycol) (1500) at different temperatures (288.15, 293.15, 298.15) k have been used to estimate the apparent molar volume (Vθ), limiting apparent molar volume (Vθ˚) experimental slope (Sv) and the second derivative of limiting partial molar volume [δ2 θ v° /δ T2] p .The viscosity data have been analyzed by means of Jones –Dole equation to obtain coefficient A, and Jones –Dole coefficient B, Free activation energy of activation per mole of solvent, Δμ10* solute, Δμ20* the activation enthalpy ΔH*,and entropy, ΔS*of activation of viscous flow. These results have been discussed in terms of solute –solvent interaction and making/breaking ability of so

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Estimating Pitting Corrosion Depth and Density on Carbon Steel (C-4130) using Artificial Neural Networks
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The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Active Carbon from Date Stones for Phenol Oxidation in Trickle Bed Reactor, Experimental and Kinetic Study
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The catalytic wet air oxidation (CWAO) of phenol has been studied in a trickle bed reactor

using  active  carbon  prepared  from  date  stones  as  catalyst  by  ferric  and  zinc  chloride activation (FAC and ZAC). The activated carbons were characterized by measuring their surface area and adsorption capacity besides conventional properties, and then checked for CWAO using a trickle bed reactor operating at different conditions (i.e. pH, gas flow rate, LHSV, temperature and oxygen partial pressure). The results showed that the active carbon (FAC and ZAC), without any active metal supported, gives the highest phenol conversion. The reaction network proposed account

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