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ijcpe-317
Optimal Design of Cylinderical Ectrode Using Neural Network Modeling for Electrochemical Finishing
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The finishing operation of the electrochemical finishing technology (ECF) for tube of steel was investigated In this study. Experimental procedures included qualitative
and quantitative analyses for surface roughness and material removal. Qualitative analyses utilized finishing optimization of a specific specimen in various design and operating conditions; value of gap from 0.2 to 10mm, flow rate of electrolytes from 5 to 15liter/min, finishing time from 1 to 4min and the applied voltage from 6 to 12v, to find out the value of surface roughness and material removal at each electrochemical state. From the measured material removal for each process state was used to verify the relationship with finishing time of work piece. Electrochemical finishing proves an effective method to reduce the surface roughness (Ra) from 1.6μm to 0.1μm in 4 min. Finally, the observed relationships were used to predicate the diameter of blank, tool diameter and flow rate by neural network modeling ANN which has inputs defined by the finished hole diameter, surface roughness, and finishing time. Three of hidden layers and their neurons were found by an integration procedure. The design charts observed from this study utilize the designers in predication of diameter for blank and design of electrode.

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Publication Date
Fri Aug 02 2024
Journal Name
Journal Of Electrochemical Energy Conversion And Storage
Electrochemical Performance of Co1-xMnxFe2O4 Decorated Nanofiber Polyaniline Composites
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The current work is concerned with preparing cobalt manganese ferrite (Co1-xMnxFe2O4) with different concentrations of cobalt and manganese (x=0.2, 0.4, and 0.6) and decorating it with polyaniline (PAni) for use in supercapacitive applications. The results of the X-ray diffraction (XRD) manifested a broad peak of PAni and a cubic structure of cobalt manganese ferrite having crystal size between 60 nm and 138 nm, which decreases with increasing concentration of Mn. The field emission scanning electron microscopy (FESEM) images evidenced that the PAni has nanofiber (NF) structures, according to the method of preparation, where the hydrothermal method was used. The magnetic properties of the prepared ferrite, as well as the prepared PAni/Co1-x

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Publication Date
Fri Feb 27 2026
Journal Name
Sustainability
Recent Developments in Membrane, Adsorption, and Electrochemical Sustainable Approaches for Cadmium Removal from Contaminated Water
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The issue of cadmium (Cd(II)) contamination of the water is a serious concern of the environmental and health problem, and this requires effective technology to remove the problem of toxic element. It is the purpose of this review paper to give an overview of several techniques of cadmium removal, such as polymer membranes and composites, adsorption using green materials, and electrochemical methods. The important conclusions are presented regarding the effectiveness of the polymer and composite membranes; e.g., the efficacy of the PES/HPEI-SH membrane that reached 99% removal of Cd(II) in 20 min with adsorption capacity of 135.59 mg/cm2, and the PVA/IC/PANI/GO nanofiber composite that indicates high adsorption of the 459 mg/g. The

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Cadmium Removal Using Bio-Electrochemical Reactor with Packed Bed Rotating Cylindrical Cathode: A Kinetics Study
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   The kinetics of removing cadmium from aqueous solutions was studied using a bio-electrochemical reactor with a packed bed rotating cylindrical cathode. The effect of applied voltage, initial concentration of cadmium, cathode rotation speed, and pH on the reaction rate constant (k) was studied. The results showed that the cathodic deposition occurred under the control of mass transfer for all applied voltage values ​​used in this research. Accordingly, the relationship between logarithmic concentration gradient with time can be represented by a first-order kinetic rate equation. It was found that the rate constant (k) depends on the applied voltage, the initial cadmium concentration, the pH and the rotational speed of cathode. It

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Publication Date
Thu Oct 01 2020
Journal Name
Chemical Engineering And Processing - Process Intensification
Cobalt Removal from Simulated Wastewaters Using a Novel Flow-by Fixed Bed Bio-electrochemical Reactor
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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Solving Optimal Control Linear Systems by Using New Third kind Chebyshev Wavelets Operational Matrix of Derivative
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In this paper, a new third kind Chebyshev wavelets operational matrix of derivative is presented, then the operational matrix of derivative is applied for solving optimal control problems using, third kind Chebyshev wavelets expansions. The proposed method consists of reducing the linear system of optimal control problem into a system of algebraic equations, by expanding the state variables, as a series in terms of third kind Chebyshev wavelets with unknown coefficients. Example to illustrate the effectiveness of the method has been presented.

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Publication Date
Sun Dec 02 2012
Journal Name
Baghdad Science Journal
Stability of Back Propagation Training Algorithm for Neural Networks
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In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained

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Publication Date
Tue Jun 03 2025
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Comparison of some artificial neural networks for graduate students
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Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer

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Publication Date
Mon Apr 20 2026
Journal Name
International Journal Of Intelligent Engineering And Systems
A Robust Base-layer Design for Hierarchical IoT Intrusion Detection Using Hybrid Deep Learning
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The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines

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Scopus
Publication Date
Tue Dec 12 2017
Journal Name
Al-khwarizmi Engineering Journal
Design a Vegetative Filter Strips Length Using VFSMOD_W Model for Reducing Sediments and Pesticides
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 Abstract 

The vegetative filter strips (VFS) are a useful tool used for reducing the movement of sediment and pesticide in therivers. The filter strip’s soil can help in reducing the runoff volume by infiltration. However, the characteristics of VFS (i.e., length) are not recently identified depending on the estimation of VFS modeling performance. The aim of this research is to study these characteristics and determine acorrelation between filter strip length and percent reduction (trapping efficiency) for sediment, water, and pesticide. Two proposed pesticides(one has organic carbon sorption coefficient, Koc, of 147 L/kg which is more moveable than XXXX, and another one

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Publication Date
Mon Mar 18 2019
Journal Name
Al-khwarizmi Engineering Journal
Effect of optimal shot peening time on fatigue life for aluminum alloy 6061-T651
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The compressive residual stresses generated by shot peening, is increased in a direct proportional way with shot peening time (SPT). For each metal, there is an optimum shot peening time (O.S.T) which gives the optimum fatigue life. This paper experimentally studied to optimize shot peening time of aluminium alloy 6061-T651 as well as using of and analysis of variance (ANOVA).

Two types of fatigue test specimens’ configuration were used, one without notch (smooth) and the other with a notch radius (1,25mm), each type was shot peened at different time. The (O.S.T) was experimentally estimated  to be 8 minutes reaching the surface stresses at maximum peak of -184.94 MPa.

A response surface methodology (RSM) is presen

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