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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
Mon Dec 24 2018
Journal Name
Civil Engineering Journal
Artificial Neural Network Model for the Prediction of Groundwater Quality
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The present article delves into the examination of groundwater quality, based on WQI, for drinking purposes in Baghdad City. Further, for carrying out the investigation, the data was collected from the Ministry of Water Resources of Baghdad, which represents water samples drawn from 114 wells in Al-Karkh and Al-Rusafa sides of Baghdad city. With the aim of further determining WQI, four water parameters such as (i) pH, (ii) Chloride (Cl), (iii) Sulfate (SO4), and (iv) Total dissolved solids (TDS), were taken into consideration. According to the computed WQI, the distribution of the groundwater samples, with respect to their quality classes such as excellent, good, poor, very poor and unfit for human drinking purpose, was found to be

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Publication Date
Sun Dec 09 2018
Journal Name
Baghdad Science Journal
A Comparative Efficiency Study of Two Adsorbent Materials to Remove Eosin Y Dye from Aqueous Solutions
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This study was done to find a cheap, available and ecofriendly materials that can remove eosin y dye from aqueous solutions by adsorption in this study, two adsorbent materials were used, the shells of fresh water clam (Cabicula fluminea) and walnut shells. To make a comparison between the two adsorbents, five experiments were conducted. First, the effects of the contact time, here the nut shell removed the dye quickly, while the C. flumina need more contact time to remove the dye. Second, the effects of adsorbent weight were examined. The nut shell was very promising and for all used adsorbent weight, the R% ranged from 94.87 to 99.29. However C. fluminea was less effective in removing the dye with R% ranged from 47.59 to 55.39. The thi

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Publication Date
Sun Dec 05 2010
Journal Name
Baghdad Science Journal
Effect of aqueous extract of olive (Olea europaea) fruit on lipid profile in female rabbits
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The activity of the aqueous extract of Olea europaea was tested at concentrations of 8, 15 or 20 mg/kg of body weight on lipid profile in twenty female local rabbits. These animals were randomly divided into four groups (five animals in each group). Three groups were dosed orally with the concentrations mentioned above, while the last was administered with distilled water and considered as a control group. These animals were orally dosed by aqueous extract using a micropipette for 30 days. The results showed that there was a significant (P<0.05) decrease in cholesterol, triglycerides, low density lipoprotein (LDL-cholesterol), very low density lipoprotein (VLDL-cholesterol) concentrations and atherosclerosis index means for the three trea

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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Numerical solution for Wiener-Hopf integral equation using artificial neural network
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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
Mobile position estimation using artificial neural network in CDMA cellular systems
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Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

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Publication Date
Wed Aug 03 2022
Journal Name
Egyptian Journal Of Chemistry
A Novel Bio-electrochemical Cell with Rotating Cylinder Cathode for Cadmium Removal from Simulated Wastewater
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Publication Date
Thu Jan 27 2022
Journal Name
Eurasian Chemical Communications
Equilibrium and kinetic modeling studies for the adsorption-desorption of methyl violet 10B onto leather waste
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In this study, vegetable tanned leather waste of cow (VTLW-C) is used as adsorbent for removing methyl violet 10B dye from aqueous solution. The VTLW-C adsorbent was characterized by FTIR and SEM in order to evaluate its surface properties before using in adsorption experiments. Batch adsorption method was applied to study the effect of different factors such as weight of leather waste, time of shaking, and starting concentration of methyl violet 10B dye. Different isothermal models such as Langmuir, Freundlich, Temkin and Dubinin-Radushkevich (D–R) were used to analyze the experimental data. Kinetic study proceeds using (PFO) kinetic model and (PSO) kinetic model. The results showed better agreement with the Freundlich model; this means

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Publication Date
Sat Aug 03 2024
Journal Name
Proceedings Of Ninth International Congress On Information And Communication Technology
Offline Signature Verification Based on Neural Network
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The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

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Publication Date
Sun Sep 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development of PVT Correlation for Iraqi Crude Oils Using Artificial Neural Network
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Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

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Publication Date
Thu Mar 06 2025
Journal Name
Aip Conference Proceedings
Solving 5th order nonlinear 4D-PDEs using efficient design of neural network
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