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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
Wed Jul 01 2015
Journal Name
Journal Of Engineering
Spiking Neural Network in Precision Agriculture
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In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p

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Publication Date
Sat Feb 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Using GIS Technique for evaluating water quality of Abu Zarag marsh during the flood season
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Abstract<p>This research deals with the most important heritage in Iraq, which are the Iraqi marshes, especially Abu Zarag marsh in Al-Nasiriyah city south of Iraq. The research is divided into two parts. The first part deals with evaluating the water quality parameters of Abu Zarag marsh for the period from December 2018 to April 2019 which is the flooding season. The parameters are Temperature, pH, Electrical Conductivity, Total Dissolved Solids, Alkalinity, Total Hardness, Turbidity, Dissolved Oxygen, Sulfate, Nitrate. The second part is a comparison between the water quality parameters during the recent period with the same period during the previous years from 2014 to 2019. The results are </p> ... Show More
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Publication Date
Fri Jul 19 2024
Journal Name
Applied Science And Engineering Progress
Multicomponent Equilibrium Isotherms and Kinetics Study of Heavy Metals Removal from Aqueous Solutions Using Electrocoagulation Combined with Mordenite Zeolite and Ultrasonication
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Combining different treatment strategies successively or simultaneously has become recommended to achieve high purification standards for the treated discharged water. The current work focused on combining electrocoagulation, ion-exchange, and ultrasonication treatment approaches for the simultaneous removal of copper, nickel, and zinc ions from water. The removal of the three studied ions was significantly enhanced by increasing the power density (4–10 mA/cm2) and NaCl salt concentration (0.5–1.5 g/L) at a natural solution pH. The simultaneous removal of these metal ions at 4 mA/cm2 and 1 g NaCl/L was highly improved by introducing 1 g/L of mordenite zeolite as an ion-exchanger. A remarkable removal of heavy metals was reported

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Publication Date
Wed Mar 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Application of Finite Element Technique: A Review Study
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The finite element approach is used to solve a variety of difficulties, including well bore stability, fluid flow production and injection wells, mechanical issues and others. Geomechanics is a term that includes a number of important aspects in the petroleum industry, such as studying the changes that can be occur in oil reservoirs and geological structures, and providing a picture of oil well stability during drilling. The current review study concerned about the advancements in the application of the finite element method (FEM) in the geomechanical field over a course of century.

Firstly, the study presented the early advancements of this method by development the structural framework of stress, make numerical computer solution

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Publication Date
Mon Oct 25 2021
Journal Name
Iraqi Journal Of Science
Synthesis, Characterization and Kinetic Studies of Chelate Polymer Derived from 3-Nonyl Benzene and its Use for the Removal of Some Heavy Metals from Aqueous Solutions
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    A new chelate polymer (2-5-hydroxy-3-methyl-2- (3-nonyl benzene) imino) methyl) benzyl) 4-6-dimethyphenol] (K4) was prepared by using the condensation reaction method and identified by several techniques, including FT-IR, NMR, and atomic absorption spectroscopy, as well as TG-DTA thermal analysis. The kinetic equilibrium for the sorption of lead and cadmium ions on the chelate polymer surface was also investigated. The results showed that the sorption of both ions followed the pseudo-first-order and pseudo-second-order kinetic equilibrium. The rate constant values of pseudo-first-order reaction  were equal to 0.062 and 0.057 min-1  , while the values of pseudo-second-order were 0.0103 and 0.053 L.m

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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
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Tuning PID Controller by Neural Network for Robot Manipulator Trajectory Tracking
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Ziegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller. This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions. In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities. The proportional, integral and derivative (KP, KI, KD) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control. The conventio

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Publication Date
Wed May 03 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Designing Feed Forward Neural Network for Solving Linear VolterraIntegro-Differential Equations
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The aim of this paper, is to design multilayer Feed Forward Neural Network(FFNN)to find the approximate solution of the second order linear Volterraintegro-differential equations with boundary conditions. The designer utilized to reduce the computation of solution, computationally attractive, and the applications are demonstrated through illustrative examples.

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Thu Dec 01 2022
Journal Name
Iaes International Journal Of Artificial Intelligence
Reduced hardware requirements of deep neural network for breast cancer diagnosis
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

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