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Development of Hybrid Intelligent Models for Prediction Machining Performance Measure in End Milling of Ti6Al4V Alloy with PVD Coated Tool under Dry Cutting Conditions
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Ti6Al4V alloy is widely used in aerospace and medical applications. It is classified as a difficult to machine material due to its low thermal conductivity and high chemical reactivity. In this study, hybrid intelligent models have been developed to predict surface roughness when end milling Ti6Al4V alloy with a Physical Vapor Deposition PVD coated tool under dry cutting conditions. Back propagation neural network (BPNN) has been hybridized with two heuristic optimization techniques, namely: gravitational search algorithm (GSA) and genetic algorithm (GA). Taguchi method was used with an L27 orthogonal array to generate 27 experiment runs. Design expert software was used to do analysis of variances (ANOVA). The experimental data were divided randomly into three subsets for training, validation, and testing the developed hybrid intelligent model. ANOVA results revealed that feed rate is highly affected by the surface roughness followed by the depth of cut. One-way ANOVA, including a Post-Hoc test, was used to evaluate the performance of three developed models. The hybrid model of Artificial Neural Network-Gravitational Search Algorithm (ANN-GSA) has outperformed Artificial Neural Network (ANN) and Artificial Neural Network-Genetic Algorithm (ANN-GA) models. ANN-GSA achieved minimum testing mean square error of 7.41 × 10−13 and a maximum R-value of 1. Further, its convergence speed was faster than ANN-GA. GSA proved its ability to improve the performance of BPNN, which suffers from local minima problems.

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Publication Date
Sat Jul 25 2026
Journal Name
Modern Sport
Impact style of the changeable resistance in the development some of physical & functional changes for the National team for the badminton
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Publication Date
Thu Jun 29 2023
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
Recognition of Upper Limb Movements Based on Hybrid EEG and EMG Signals for Human-Robot Interaction
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Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that usin

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Publication Date
Thu Nov 08 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Suggested Technique for Creating Physical Growth Curves Charts for Anthropometric Measurements in Admixed form in a sample of children under two years of age In Diyala Governorate
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Objective: This study aimed to assessing new suggested technique of Physical Growth Curves (PGC) charts in
children under two years old of a non-probability sample.
Methodology: A non-probability sample of size (420) children under two years selected from 12 Primary
Health Care Centers in Diyala governorate during the period from 15th Nov. 2010 to 13th Mar. 2011
according to admix of a different properties together in one chart/or growth curve chart included in at least
weight, Height, and Head circumference.
Results: the results showed different properties that can be admix together in one chart/or growth curve
chart included in at least weight, Height, and Head circumference. And to overtake the problem of the norm

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Publication Date
Thu Dec 01 2011
Journal Name
Iraqi Journal Of Physics
Surface Modification of Ti-6Al-4V Alloy by Glow Discharge-Plasma Nitriding
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Titanium alloy (Ti-6Al-4V) samples were nitrided in low pressure (1.3, 3 mbar) dc-glow discharge plasmas of nitrogen. The treating time was 5, 10 and 15 hour and the temperatures range of the samples during the nitriding process was close to 800oC. The obtained microstructures of the nitride layers were studied by x-ray diffraction and optical microscopy. The ε –Ti2N, ζ-Ti3N3-x and η-Ti3N2-x.phases were formed and addition to the solid solution of nitrogen in titanium, α (Ti,N). Micro hardness measurements exhibit an increment for the Ti-alloy specimens which nitrided at 800oC for 10 and 15h.Corrosion measurements were obtained for the Ti-6Al-4V alloy in Ringer solution after plasma nitriding. The clear improving in the corrosion r

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Shot Peening Time Effect on Corrosion Behaviors of Al Alloy 2024-T3
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In this study many specimen s were prepared from 2024-T3 Aluminum alloy for corrosion test by the dimensions of (15*15*3) mm according to ASTM G71-31 and then subjected to shot peening process at different time (15, 30, 45) minutes using steel ball having a diameter of 2.75 mm and Rockwell Hardness of 55RC to induce compressive residual stress which were measured using X-Ray diffraction method, surface roughness and   hardness were tested before and after peening. Electrochemical corrosion test by Tafel extrapolation method was carried out in an environment of 3 .5% NaCl solutions (sea water) where Corrosion rate calculated using Tafle equation.

The obtained results show a favorable influence of SP treatment

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Improvement the Mechanical Characteristics of Alloy Steel DIN 41Cr4 by Shot Peening
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The effects of shot peening treatment (SPT) were studied at (10,20, and 30) minutes on the rotating bending fatigue behavior and the behavior of the alloy steel DIN 41Cr4 vibrations. The hardness test, tensile test, constant amplitude fatigue tests, and the vibration measurements were performed on samples with and without cracks at room temperature (RT), also, the fracture surface was examined and analyzed by a Scanning Electron Microscope (SEM). The results of the investigations, for example, Stress to Number of cycles to failure (S-N) curves, fatigue strength improvement factor of 5% to 10%, the decreasing percentage of maximum Fast Fourier Transform (FFT) acceleration of the shot-peened condition were compared to untr

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Publication Date
Tue Mar 03 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
Administrative performance and its relationship with the cognitive style (rigidity - flexibility) for management body members of the sport clubs
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Publication Date
Sun Apr 12 2026
Journal Name
Experimental Heat Transfer
Thermal performance of open-cell copper metal foam heat sinks with different configurations and pore densities for electronics cooling
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Publication Date
Fri Jan 01 2021
Journal Name
Int. J. Nonlinear Anal. Appl.
Analysis of a harvested discrete-time biological models
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This work aims to analyze a three-dimensional discrete-time biological system, a prey-predator model with a constant harvesting amount. The stage structure lies in the predator species. This analysis is done by finding all possible equilibria and investigating their stability. In order to get an optimal harvesting strategy, we suppose that harvesting is to be a non-constant rate. Finally, numerical simulations are given to confirm the outcome of mathematical analysis.

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Scopus
Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of Models (NAGARCH & APGARCH) by Using Simulations
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Simulation experiments are a means of solving in many fields, and it is the process of designing a model of the real system in order to follow it and identify its behavior through certain models and formulas written according to a repeating software style with a number of iterations. The aim of this study is to build a model  that deals with the behavior suffering from the state of (heteroskedasticity) by studying the models (APGARCH & NAGARCH) using (Gaussian) and (Non-Gaussian) distributions for different sample sizes (500,1000,1500,2000) through the stage of time series analysis (identification , estimation, diagnostic checking and prediction). The data was generated using the estimations of the parameters resulting f

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