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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
Fri Mar 31 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Micro encapsulation of Naproxen By Complex Coacervation and Aqueous Colloid Dispersion Part ( 1 )
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Naproxen is a non steroidal anti inflammatory and antipyretic drug which has local irritation effect  on  the  stomach, and  unpleasant taste,  besides bad   flowability and light sensitivity .The drug was prepared as microcapsules by complex coacervation method using acacia-gelatin coating materials , and aqueous colloid polymer dispersion method ( ACPD ), using ethyl cellulose and sodium alginate coating materials . The results indicated that microcapsules prepared by 2:1  core:wall ratio is the best for both methods, with an average encapsulation efficiency (75%) and avarege yield (90%) .

Moreover the drug release was affected mainly by core : ratio ,pH enviroment and method of microenca

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Publication Date
Wed Feb 15 2023
Journal Name
Environmental Technology
Bio-synthesis of TiO<sub>2</sub> using grape leaves extract and its application for photocatalytic degradation of ibuprofen from aqueous solution
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Publication Date
Sat Jun 27 2020
Journal Name
Iraqi Journal Of Science
The Performance Differences between Using Recurrent Neural Networks and Feedforward Neural Network in Sentiment Analysis Problem
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 With the spread use of internet, especially the web of social media, an unusual quantity of information is found that includes a number of study fields such as psychology, entertainment, sociology, business, news, politics, and other cultural fields of nations. Data mining methodologies that deal with social media allows producing enjoyable scene on the human behaviour and interaction. This paper demonstrates the application and precision of sentiment analysis using traditional feedforward and two of recurrent neural networks (gated recurrent unit (GRU) and long short term memory (LSTM)) to find the differences between them. In order to test the system’s performance, a set of tests is applied on two public datasets. The firs

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Publication Date
Fri Feb 17 2023
Journal Name
Biomass Conversion And Biorefinery
Effect of green synthesis of Fe3O4 nanomaterial on the removal of cefixime from aqueous solution
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In this paper, two types of iron oxide nanomaterial (Fe3O4) and nanocomposite (T-Fe3O4) were created from the bio-waste mass of tangerine peel. These two materials were utilized for adsorption tests to remove cefixime (CFX) from an aqueous solution. Before the adsorption application, both adsorbents have been characterized by various characterizations such as XRD, FTIR, VSM, TEM, and FESEM. The mesoporous nano-crystalline structure of Fe3O4 and T-Fe3O4 nanocomposite with less than 100-nm diameter is confirmed. The adsorption of the obtained adsorbents was evaluated for CFX removal by adjusting several operation parameters to optimize the removal. The optimal conditions for CFX removal were found to be an initial concentration of 40 and 50 m

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Synthesis of Multifunctional Polymers Based on Tert-Butyl Acrylamide/Octyl Acrylate as Lubricant Additives and Adsorbents for Copper Ion from Aqueous Solution
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Two homopolymeric and three copolymeric additives for base oil were synthesized using octyl acrylate (OA) and tert-butyl acrylamide (TBA) monomers. The two additives named P1 and P2 are the homopolymers of TBA and OA, respectively, whereas copolymeric additives named Co1, Co2, and Co3 were synthesized by varying the ratios of TBA:OA as 1:3, 3:1 and 1:1, respectively. The prepared polymers were characterized by Fourier Transform Infrared (FTIR). Based on the solubility of synthesized polymers in base oil and reactivity ratios of TBA/OA copolymer (0.222, 0.434) calculated by Fineman-Ross method, P2, Co1, Co2 and Co3 were selected to evaluate their performance as pour point depressant (PPD), viscosity improver (VII), and anticorrosion addit

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Publication Date
Sat Jan 01 2022
Journal Name
Computers, Materials &amp; Continua
An Optimal Method for Supply Chain Logistics Management Based on Neural Network
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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Convolutional Multi-Spike Neural Network as Intelligent System Prediction for Control Systems
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The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
PDCNN: FRAMEWORK for Potato Diseases Classification Based on Feed Foreword Neural Network
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         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

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Publication Date
Mon Sep 16 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Adsorption of Methyl Violet Dye from Aqueous Solution by Iraqi Bentonite and Surfactant – Modified Iraqi Bentonite
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Natural bentonite (B) mineral clay was modified by anionic surfactant sodium dodecyl sulfate (SDS) and characterized using different techniques such as: FTIR spectroscopy, scanning electron microscopy (SEM) and X-Ray diffraction (XRD). The bentonite and modified bentonite were used as adsorbents for the adsorption of methyl violet (MV) from aqueous solutions. The adsorption study was carried out at different conditions such as: contact time, pH value and adsorbent weight. The adsorption kinetic described by pseudo– first order and pseudo – second order equilibrium experimental data described by Langmuir, Freundlich and Temkin isotherm models. The thermodynamic parameters standard free energy ( ), standard entropy ( ) standa

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Publication Date
Sun Jun 01 2008
Journal Name
2008 Ieee International Joint Conference On Neural Networks (ieee World Congress On Computational Intelligence)
Linear block code decoder using neural network
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