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Improvement of the Accuracy of the Perturbed Orbital Elements for LEO Satellite by Improving 4th Order Runge–Kutta’s Method
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Background/objectives: To study the motion equation under all perturbations effect for Low Earth Orbit (LEO) satellite. Predicting a satellite’s orbit is an important part of mission exploration. Methodology: Using 4th order Runge–Kutta’s method this equation was integrated numerically. In this study, the accurate perturbed value of orbital elements was calculated by using sub-steps number m during one revolution, also different step numbers nnn during 400 revolutions. The predication algorithm was applied and orbital elements changing were analyzed. The satellite in LEO influences by drag more than other perturbations regardless nnn through semi-major axis and eccentricity reducing. Findings and novelty/improvement: The results demonstrated that when m for Runge–Kutta’s method is large; the perturbed value for orbital element considers more acceptable. Furthermore, as nnn increases the step will reduce.

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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Development of Pavement Maintenance Management System for Baghdad Urban Roadway Network
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The road transportation system is considered as major component of the infrastructure in any country, it affects the developments in economy and social activities. The Asphalt Concrete which is considered as the major pavement material for the road transportation system in Baghdad is subjected to continuous deterioration with time due to traffic loading and environmental conditions, it was felt that implementing a comprehensive pavement maintenance management system (PMMS), which should be capable for preserving the functional and structural conditions of pavement layers, is essential. This work presents the development of PMMS with Visual inspection technique for evaluating the Asphalt Concrete pavement surface condition; common types o

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Iron Permeable Reactive Barrier for Removal of Lead from Contaminated Groundwater
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The possibility of using zero-valent iron as permeable reactive barrier in removing lead from a contaminated groundwater was investigated. In the batch tests, the effects of many parameters such as contact time between adsorbate and adsorbent (0-240 min), initial pH of the solution (4-8), sorbent dosage (1-12 g/100 mL), initial metal concentration (50-250 mg/L), and agitation speed
(0-250 rpm) were studied. The results proved that the best values of these parameters achieve the maximum removal efficiency of Pb+2 (=97%) were 2 hr, 5, 5 g/100 mL, 50 mg/L and 200 rpm respectively. The sorption data of Pb+2 ions on the zero-valent iron have been performed well by Langmuir isotherm model in compared with Freundlich model under the studied

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Publication Date
Mon Dec 03 2018
Journal Name
Journal Of Engineering
Comparative Analysis of Various Multicarrier Modulation Techniques for Different Multilevel Converters
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The applications of Multilevel Converter (MLC) are increased because of the huge demand for clean power; especially these types of converters are compatible with the renewable energy sources. In addition, these new types of converters have the capability of high voltage and high power operation. A Nine-level converter in three modes of implementation; Diode Clamped-MLC (DC-MLC), Capacitor Clamped-MLC (CC-MLC), and the Modular Structured-MLC (MS-MLC) are analyzed and simulated in this paper. Various types of Multicarrier Modulation Techniques (MMTs) (Level shifted (LS), and Phase shifted (PS)) are used for operating the proposed Nine level - MLCs. Matlab/Simulink environment is used for the simulation, extracting, and ana

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Publication Date
Thu Dec 01 2011
Journal Name
Iraqi Journal Of Physics
vStudy of Linear Shrinkage for Siliceous Materials to Meet Insulating Requirements
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Iraqi siliceous rocks were chosen to be used as raw materials in this study which is concern with the linear shrinkage and their related parameters. They are porcelinite from Safra area (western desert) and Kaolin Duekla, their powders were mixed in certain percentage, to shape compacts and sintered. The study followed with thermal and chemical treatments, which are calcination and acid washing. The effects on final compact properties such as linear shrinkage were studied. Linear shrinkage was calculated for sintered compacts to study the effects of calcination processes, chemical washing, weight percentage, sintering processes, loading moment were studied on this property where the compacts for groups is insulating materials.
Linear

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
IMPLEMENTATION OF GYPSEOUS SOIL-ASPHALT STABILIZATION TECHNIQUE FOR BASE COURSE CONSTRUCTION
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The aim of this research work is to study the effect of stabilizing gypseous soil, which covers
vast areas in the middle, west and south parts of Iraq, using liquid asphalt on its strength properties
to be used as a base course layer replacing the traditional materials of coarse aggregate and broken
stones which are scarce at economical prices and hauling distances.
Gypseous soil brought from Al-Ramadi City, west of Iraq, with gypsum content of 66.65%,
medium curing cutback asphalt (MC-30), and hydrated lime are used in this study.
The conducted tests on untreated and treated gypseous soil with different percentages of medium
curing cutback asphalt (MC-30), water, and lime were: unconfined compression strength, and o

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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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Publication Date
Mon Oct 09 2023
Journal Name
2023 Ieee 34th International Symposium On Software Reliability Engineering Workshops (issrew)
Semantics-Based, Automated Preparation of Exploratory Data Analysis for Complex Systems
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Publication Date
Sat Jan 13 2018
Journal Name
Journal Of Engineering
Performance Evaluation of RIPng, EIGRPv6 and OSPFv3 for Real Time Applications
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In this modern Internet era and the transition to IPv6, routing protocols must adjust to assist this transformation. RIPng, EIGRPv6 and OSPFv3 are the dominant IPv6 IGRP (Interior Gateway Routing Protocols). Selecting the best routing protocol among the available is a critical task, which depends upon the network requirement and performance parameters of different real time applications. The primary motivation of this paper is to estimate the performance of these protocols in real time applications. The evaluation is based on a number of criteria including:  network convergence duration, Http Page Response Time, DB Query Response Time, IPv6 traffic dropped, video packet delay variation and video packet end to end de

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Publication Date
Mon Feb 27 2023
Journal Name
Applied Sciences
Comparison of ML/DL Approaches for Detecting DDoS Attacks in SDN
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Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

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Publication Date
Sun Jan 01 2023
Journal Name
Computational Thermal Sciences: An International Journal
EXPERIMENTAL AND NUMERICAL ANALYSIS FOR THERMAL PROBLEM OF FRICTIONAL BRAKE SYSTEM
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The present work aims to validate the experimental results of a new test rig built from scratch to evaluate the thermal behavior of the brake system with the numerical results of the transient thermal problem. The work was divided into two parts; in the first part, a three-dimensional finite-element solution of the transient thermal problem using a new developed 3D model of the brake system for the selected vehicle is SAIPA 131, while in the second part, the experimental test rig was built to achieve the necessary tests to find the temperature distribution during the braking process of the brake system. We obtained high agreement between the results of the new test rig with the numerical results based on the developed model of the brake

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