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jih-3033
Constructing RKM-Method for Solving Fractional Ordinary Differential Equations of Fifth-Order with Applications
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This paper sheds the light on the vital role that fractional ordinary differential equations(FrODEs) play in the mathematical modeling and in real life, particularly in the physical conditions. Furthermore, if the problem is handled directly by using numerical method, it is a far more powerful and efficient numerical method in terms of computational time, number of function evaluations, and precision. In this paper, we concentrate on the derivation of the direct numerical methods for solving fifth-order FrODEs  in one, two, and three stages. Additionally, it is important to note that the RKM-numerical methods with two- and three-stages for solving fifth-order ODEs are convenient, for solving class's fifth-order FrODEs. Numerical examples have been analyzed to demonstrate the efficacy of the new methods in comparison to the analytical method. Therefore, the numerical compression is carried out to confirm the efficiency and precision of the modified numerical methods. Significantly, the study demonstrates that the numerical outcomes of the proposed derived and modified numerical applied methods proved to be brilliant. Finally, based on the findings of the study, it could be said that the numerical outcomes of the test-problems using proposed and modified methods agree well with the analytical solutions. Hence, we can conclude that the proposed numerical methods that are derived or modified in the analytic study of this paper are quite efficient.

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Publication Date
Fri Jan 31 2020
Journal Name
Iraqi Geological Journal
Manufacturing Perforated and Ordinary Bricks Using Injana Claystone Exposed in The Middle of Iraq
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This study aims to use claystone beds exposed in the Injana Formation (Late Miocene) at Karbala-Najaf plateau, middle of Iraq for the manufacturing of perforated and ordinary bricks. The claystone samples were assessed as an alternative material of the recent sediments, which are preferred to remain as agricultural land. The claystones are sandy mud composing of 29.1 - 39.1% clay, 37.2 - 54.8% silt and 14.1-26.8% sand. They consist of kaolinite, illite, chlorite, palygorskite, and montmorillonite with a lot of quartz, calcite, dolomite, gypsum and feldspar. Claystone samples were characterized by linear shrinkage 0.01 - 0.1%, volume shrinkage 0.1 - 0.9%, bulk density 1.2 - 2.11gm/cm3 (1.68 g / cm3 average), and the efflorescence is

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Logical thinking and its relation with problem Solving among female instructors in the university
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problems with its unobvious effect on scientific creativity and information. Problem solving is one of main goals of researchers because it develops their right logical thinking methods. The present study aims at measuring logical thinking among female it structures in the university mea swing problem solving among them ,identifying statically differences significance in logical thinking among female instructors in the university according to (Specialization Variable), identifying differences significance in problem Solving among female instructions in the university according to ( Specialization Variable) and identifying the Correlation between logical thinking and problem solving among female instructors in the university. The sample c

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Solving B- spline functions
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In this paper, we proposed to zoom Volterra equations system Altfazlah linear complementarity of the first type in this approximation were first forming functions notch Baschtdam matrix and then we discussed the approach and stability, to notch functions

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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Tue Oct 30 2018
Journal Name
Iraqi Journal Of Physics
N3, N749 dyes effect on the TiO2 for optoelectronic applications
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The present work aimed to study effect of (N749 & N3) dyes on TiO2 optical and electrical properties for optoelectronic application. The TiO2 paste prepared by using a doctor blade method. The samples were UV-VIS specterophometricall analyzes of TiO2 before and after immersed in dyes (N749 & N3). The results showed absorption spectra shift toward the visible region due to the adsorption of dye molecules on the surface of oxide nanoparticles. It is seen that the Eg determined to give a value of 3.3eV for TiO2 before immersing in dyes, and immersing in dyes (N749 & N3) are (1.4 &1.6 eV) respectively. The structural properties (XRD), (FTIR) and (SEM) for the sample prepared were investigated and (J-V) characteristics was stu

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Publication Date
Wed May 01 2024
Journal Name
Scientific Visualization
Shadow Detection and Elimination for Robot and Machine Vision Applications
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Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit

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Publication Date
Sat Jul 01 2017
Journal Name
Energy Procedia
Epoxy/Silicone Rubber Blends for Voltage Insulators and Capacitors Applications
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Publication Date
Fri Feb 18 2022
Journal Name
Coatings
Non-Polar Gallium Nitride for Photodetection Applications: A Systematic Review
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Ultraviolet photodetectors have been widely utilized in several applications, such as advanced communication, ozone sensing, air purification, flame detection, etc. Gallium nitride and its compound semiconductors have been promising candidates in photodetection applications. Unlike polar gallium nitride-based optoelectronics, non-polar gallium nitride-based optoelectronics have gained huge attention due to the piezoelectric and spontaneous polarization effect–induced quantum confined-stark effect being eliminated. In turn, non-polar gallium nitride-based photodetectors portray higher efficiency and faster response compared to the polar growth direction. To date, however, a systematic literature review of non-polar gallium nitride-

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Publication Date
Thu May 11 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Solution of Some Application of System of Ordinary Initial Value Problems Using Osculatory Interpolation Technique
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 The aim of this paper is to find a new method for solving a system of linear initial value problems of ordinary differential equation using approximation technique by two-point osculatory  interpolation with the fit equal numbers of derivatives at the end points of an interval [0, 1] and compared the results with conventional methods and is shown to be that seems to converge faster and more accurately than the conventional methods.

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Publication Date
Sun Jan 01 2017
Journal Name
Lecture Notes In Computer Science
Constrained Differential Evolution for Cost and Energy Efficiency Optimization in 5G Wireless Networks
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The majority of real-world problems involve not only finding the optimal solution, but also this solution must satisfy one or more constraints. Differential evolution (DE) algorithm with constraints handling has been proposed to solve one of the most fundamental problems in cellular network design. This proposed method has been applied to solve the radio network planning (RNP) in the forthcoming 5G Long Term Evolution (5G LTE) wireless cellular network, that satisfies both deployment cost and energy savings by reducing the number of deployed micro base stations (BSs) in an area of interest. Practically, this has been implemented using constrained strategy that must guarantee good coverage for the users as well. Three differential evolution

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