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Surface Roughness Prediction for Steel 304 In Edm Using Response Graph Modeling
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Electrical Discharge Machining (EDM) is a non-traditional cutting technique for metals removing which is relied upon the basic fact that negligible tool force is produced during the machining process. Also, electrical discharge machining is used in manufacturing very hard materials that are electrically conductive. Regarding the electrical discharge machining procedure, the most significant factor of the cutting parameter is the surface roughness (Ra). Conventional try and error method is time consuming as well as high cost. The purpose of the present research is to develop a mathematical model using response graph modeling (RGM). The impact of various parameters such as (current, pulsation on time and pulsation off time) are studied on the surface roughness in the present research. 27 samples were run by using CNC-EDM machine which used for cutting steel 304 with dielectric solution of gas oil by supplied DC current values (10, 20, and 30A). Voltage of (140V) uses to cut 1.7mm thickness of the steel and use the copper electrode. The result from this work is useful to be implemented in industry to reduce the time and cost of Ra prediction. It is observed from response table and response graph that the applied current and pulse on time have the most influence parameters of surface roughness while pulse off time has less influence parameter on it. The supreme and least surface roughness, which is achieved from all the 27 experiments is (4.02 and 2.12µm), respectively. The qualitative assessment reveals that the surface roughness increases as the applied current and pulse on time increases

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Publication Date
Tue Jun 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Applications
A proposed method for cleaning data from outlier values using the robust rfch method in structural equation modeling
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Scopus (4)
Scopus
Publication Date
Wed Mar 01 2017
Journal Name
International Communications In Heat And Mass Transfer
Optimization, modeling and accurate prediction of thermal conductivity and dynamic viscosity of stabilized ethylene glycol and water mixture Al 2 O 3 nanofluids by NSGA-II using ANN
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In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

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Crossref
Publication Date
Sun Apr 06 2014
Journal Name
Journal Of Economics And Administrative Sciences
Modeling Absolute Deviations Method by using Numerical Methods to measure the dispersion of the proposal for error
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Is in this research review of the way minimum absolute deviations values ​​based on linear programming method to estimate the parameters of simple linear regression model and give an overview of this model. We were modeling method deviations of the absolute values ​​proposed using a scale of dispersion and composition of a simple linear regression model based on the proposed measure. Object of the work is to find the capabilities of not affected by abnormal values by using numerical method and at the lowest possible recurrence.

 

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Crossref
Publication Date
Mon Dec 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Material Requirements Planning (MRP) for Electric Geyser Product by Using Goal Programming\ applicative research in the general company of electrical industrialization
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Material Requirements Planning System (MRP) is considered as one of the planning and controlling of production and inventory systems which is used to prepare plan of the final production requirements and its parts of subcomponents raw materials and the time at which it was needed for the purpose of preparing orders of production and purchase.

The problem of the present work is represented in the general company of electrical industrialization adoption of traditional methods and personal experience of the process of the products and\or purchase quantity and inventory quantities and limiting the required time for acquiring the required quantities of the materials and parts used in the finish product of the

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Path Planning of an autonomous Mobile Robot using Swarm Based Optimization Techniques
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This paper presents a meta-heuristic swarm based optimization technique for solving robot path planning. The natural activities of actual ants inspire which named Ant Colony Optimization. (ACO) has been proposed in this work to find the shortest and safest path for a mobile robot in different static environments with different complexities. A nonzero size for the mobile robot has been considered in the project by taking a tolerance around the obstacle to account for the actual size of the mobile robot. A new concept was added to standard Ant Colony Optimization (ACO) for further modifications. Simulations results, which carried out using MATLAB 2015(a) environment, prove that the suggested algorithm outperforms the standard version of AC

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Crossref
Publication Date
Sat May 03 2025
Journal Name
Aip Conference Proceedings
On a graph associated to Ly group
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For the graph ⁠, the behavior associated with to the majority of the graphical properties of this graph is covered in this article. The reflection of the capabilities of on the Ly constructions is one of the key ideas addressed throughout this paper. For instance, by this technique we can comprehend the mechanism via which groups of relatively tiny structure are exist within Ly.

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Scopus Crossref
Publication Date
Thu Jan 01 2015
Journal Name
Algebra Letters
THE GRAPH OF A COMMUTATIVE KU-ALGEBRA
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In This paper, we introduce the associated graphs of commutative KU-algebra. Firstly, we define the KU-graph which is determined by all the elements of commutative KU-algebra as vertices. Secondly, the graph of equivalence classes of commutative KU-algebra is studied and several examples are presented. Also, by using the definition of graph folding, we prove that the graph of equivalence classes and the graph folding of commutative KU-algebra are the same, where the graph is complete bipartite graph.

Publication Date
Sat Mar 26 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Dual use of Altman financial failure prediction analysis and stress tests to achieve integration in banking risk management : Analytical study of the National Bank of Iraq
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The research aims to demonstrate the dual use of analysis to predict financial failure according to the Altman model and stress tests to achieve integration in banking risk management. On the bank’s ability to withstand crises, especially in light of its low rating according to the Altman model, and the possibility of its failure in the future, thus proving or denying the research hypothesis, the research reached a set of conclusions, the most important of which (the bank, according to the Altman model, is threatened with failure in the near future, as it is located within the red zone according to the model’s description, and will incur losses if it is exposed to crises in the future according to the analysis of stress tests

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Publication Date
Fri Oct 02 2020
Journal Name
International Journal Of Pharmaceutical Research
Corrosion Protection of Carbon Steel in Saline Solution Using Plant Extracts
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Publication Date
Sun Dec 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network
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In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

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