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Modeling the removal of Cadmium Ions from Aqueous Solutions onto Olive Pips Using Neural Network Technique
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The uptake of Cd(II) ions from simulated wastewater onto olive pips was modeled using artificial neural network (ANN) which consisted of three layers. Based on 112 batch experiments, the effect of contact time (10-240 min), initial pH (2-6), initial concentration (25-250 mg/l), biosorbent dosage (0.05-2 g/100 ml), agitation speed (0-250 rpm) and temperature (20-60ºC) were studied. The maximum uptake (=92 %) of Cd(II) was achieved at optimum parameters of 60 min, 6, 50 mg/l, 1 g/100 ml, 250 rpm and 25ºC respectively.

Tangent sigmoid and linear transfer functions of ANN for hidden and output layers respectively with 7 neurons were sufficient to present good predictions for cadmium removal efficiency with coefficient of correlation equal to 0.99798. The sensitivity analysis for outputs of ANN signified that the relative importance of initial pH equal to 38 % and it is the influential parameter in the treatment process, followed by initial concentration, agitation speed, biosorbent dosage, time and temperature

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Publication Date
Tue Mar 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Minimization of Toxic Ions in Waste Water Using Emulsion Liquid Membrane Technique
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In the present study, the removal of zinc from synthetic waste water using emulsion liquid membrane extraction technique was investigated. Synthetic surfactant solution is used as the emulsifying agent. Diphenylthiocarbazon (ditizone) was used as the extracting agent dissolved in carbon tetrachloride as the organic solvent and sulfuric acid is used as the stripping agent. The parameters that influence the extraction percentage of Zn+2 were studied. These are the ratio of volume of organic solvent to volume of aqueous feed (0.5-4), ratio of volume of surfactant solution to volume of aqueous feed (0.2-1.6), pH of the aqueous feed solution (5-10), mixing intensity (100-1000) rpm, concentration of extracting agent (20-400) ppm, surfactant co

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Publication Date
Fri Sep 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Green Fabrication and Characterization of Zinc Oxide Nanoparticles using Eucalyptus Leaves for Removing Acid Black 210 Dye from an Aqueous Medium
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This study uses an environmentally friendly and low-cost synthesis method to manufacture zinc oxide nanoparticles (ZnO NPs) by using zinc sulfate. Eucalyptus leaf extract is an effective chelating and capping agent for synthesizing ZnO NPs. The structure, morphology, thermal behavior, chemical composition, and optical properties of ZnO nanoparticles were studied utilizing FT-IR, FE-SEM, EDAX, AFM, and Zeta potential analysis. The FE-SEM pictures confirmed that the ZnO NPs with a size range of (22-37) nm were crystalline and spherical. Two methods were used to prepare ZnO NPs. The first method involved calcining the resulting ZnO NPs, while the second method did not. The prepared ZnO NPs were used as adsorbents for removing acid black 210

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Publication Date
Wed Apr 15 2020
Journal Name
Journal Of Engineering Science And Technology
INFLUENCE OF A RIVER WATER QUALITY ON THE EFFICIENCY OF WATER TREATMENT USING ARTIFICIAL NEURAL NETWORK
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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Crescent Moon Visibility: A New Criterion using Deep learned Artificial Neural-Network
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     Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai

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Publication Date
Wed Mar 01 2017
Journal Name
2017 Annual Conference On New Trends In Information & Communications Technology Applications (ntict)
Automatic Iraqi license plate recognition system using back propagation neural network (BPNN)
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Publication Date
Thu Feb 07 2019
Journal Name
Iraqi Journal Of Laser
Investigation of Size-dependent Nonlinearity of Ag Nano-Fluids using Self-defocusing Technique
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In this work, the effect of different particle size on the nonlinear optical properties of silver nanoparticles in de-ionized water was studied. The experimental observation of the far field diffraction patterns by CCD camera in two and three dimensions. The maximum change of nonlinear refractive index and the relative phase shift were calculated. The self-defocusing technique was used with a continuous-wave radiation from DPSS Blue laser .The wavelength is 473 nm with an output power of 270 mW. All the Ag colloids samples containing the sizes 15, 30, 50, and 70 nm of silver nanoparticles used in the study were chemically prepared. It was found that the nonlinear refractive index is a particle size dependent and of the order of 10-7 cm2/

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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Spatial Prediction of Monthly Precipitation in Sulaimani Governorate using Artificial Neural Network Models
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ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Intelligent Congestion Control of 5G Traffic in SDN using Dual-Spike Neural Network
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Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification. Different

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Scopus (10)
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Publication Date
Tue Sep 30 2025
Journal Name
Iraqi Journal Of Science
A Study on Using Molasses Production Waste Powder as a Green Adsorbent for Cu (II) Ions from its Aqueous Solution
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This study utilized low-cost agricultural waste (molasses production waste powder) to extract copper ions from aqueous solutions. The present investigation explored a range of factors that influence the adsorption process, including temperature, pH, ionic strength, contact time, quantity of adsorbent, and particle size. Spectrophotometric analysis was used to determine the solution's absorbance both before and after the adsorption procedure. The Langmuir and Freundlich adsorption models were used to match the equilibrium data. The Freundlich model was determined to be the best isotherm model using the linear regression coefficient R2=0.9868. Thermodynamic parameters, including enthalpy, entropy, and Gibbs free energy, were calculate

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Publication Date
Sun Jan 27 2019
Journal Name
Civil Engineering Journal
Prediction of Sediment Accumulation Model for Trunk Sewer Using Multiple Linear Regression and Neural Network Techniques
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Sewer sediment deposition is an important aspect as it relates to several operational and environmental problems. It concerns municipalities as it affects the sewer system and contributes to sewer failure which has a catastrophic effect if happened in trunks or interceptors. Sewer rehabilitation is a costly process and complex in terms of choosing the method of rehabilitation and individual sewers to be rehabilitated.  For such a complex process, inspection techniques assist in the decision-making process; though, it may add to the total expenditure of the project as it requires special tools and trained personnel. For developing countries, Inspection could prohibit the rehabilitation proceeds. In this study, the researchers propos

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