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An Improved Cuckoo Search Algorithm for Maximizing the Coverage Range of Wireless Sensor Networks
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The issue of increasing the range covered by a wireless sensor network with restricted sensors is addressed utilizing improved CS employing the PSO algorithm and opposition-based learning (ICS-PSO-OBL). At first, the iteration is carried out by updating the old solution dimension by dimension to achieve independent updating across the dimensions in the high-dimensional optimization problem. The PSO operator is then incorporated to lessen the preference random walk stage's imbalance between exploration and exploitation ability. Exceptional individuals are selected from the population using OBL to boost the chance of finding the optimal solution based on the fitness value. The ICS-PSO-OBL is used to maximize coverage in WSN by converting regional monitoring into point monitoring utilizing the discretization method in WSN. In the experiments, the ICS-PSO-OBL with the standard CS and three CS variants (MACS, ICS-2, and ICS) are utilized to execute the simulation experiment under different numbers of nodes (20 and 30, respectively). The experimental results reveal that the optimized coverage of ICS-PSO-OBL is 18.36%, 7.894%, 15%, and 9.02% higher than that of standard CS, MACS, ICS-2, and ICS when the number of nodes is 20. Moreover, it is 16.94%, 9.61%, 12.27%, and 7.75% higher when the quantity of nodes is 30, the convergence speed of ICS-PSO-OBL, and the distribution of nodes is superior to others.

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Publication Date
Wed Jan 01 2014
Journal Name
Scienceasia
A combined compact genetic algorithm and local search method for optimizing the ARMA(1,1) model of a likelihood estimator
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In this paper, a compact genetic algorithm (CGA) is enhanced by integrating its selection strategy with a steepest descent algorithm (SDA) as a local search method to give I-CGA-SDA. This system is an attempt to avoid the large CPU time and computational complexity of the standard genetic algorithm. Here, CGA dramatically reduces the number of bits required to store the population and has a faster convergence. Consequently, this integrated system is used to optimize the maximum likelihood function lnL(φ1, θ1) of the mixed model. Simulation results based on MSE were compared with those obtained from the SDA and showed that the hybrid genetic algorithm (HGA) and I-CGA-SDA can give a good estimator of (φ1, θ1) for the ARMA(1,1) model. Anot

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Publication Date
Wed Dec 01 2010
Journal Name
Iraqi Journal Of Physics
An Improved Method for the Determination of Airplane Radial Velocity Using Doppler Shift
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In this research velocity of moving airplane from its recorded digital sound is introduced. The data of sound file is sliced into several frames using overlapping partitions. Then the array of each frame is transformed from time domain to frequency domain using Fourier Transform (FT). To determine the characteristic frequency of the sound, a moving window mechanics is used, the size of that window is made linearly proportional with the value of the tracked frequency. This proportionality is due to the existing linear relationship between the frequency and its Doppler shift. An algorithm was introduced to select the characteristic frequencies, this algorithm allocates the frequencies which satisfy the Doppler relation, beside that the tra

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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
A Cognitive Hybrid Tuning Control Algorithm Design for Nonlinear Path-Tracking Controller for Wheeled Mobile Robot
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This research presents a on-line cognitive tuning control algorithm for the nonlinear controller of path-tracking for dynamic wheeled mobile robot to stabilize and follow a continuous reference path with minimum tracking pose error. The goal of the proposed structure of a hybrid (Bees-PSO) algorithm is to find and tune the values of the control gains of the nonlinear (neural and back-stepping method) controllers as a simple on-line with fast tuning techniques in order to obtain the best torques actions of the wheels for the cart mobile robot from the proposed two controllers. Simulation results (Matlab Package 2012a) show that the nonlinear neural controller with hybrid Bees-PSO cognitive algorithm is m

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Publication Date
Mon Jun 29 2026
Journal Name
Al–bahith Al–a'alami
Frameworks for international press coverage of external interference in the formation of the Iraqi government Analytical study for the Saudi Al-Sharq Al-Awsat and Kayhan Al-Arabi-Iranian newspapers for the period (1/1/2018 - 31/12/2018)
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This research deals with the frameworks and mechanisms of international press coverage of the issue of foreign interference in the formation of the Iraqi government in the Saudi newspapers Asharq Al-Awsat and Kayhan Al-Arabi Iran and how this topic was addressed in the two newspapers. The frameworks for international press coverage of external interference in the formation of the Iraqi government. ”This research is one of the descriptive research that adopted the survey method، which made it possible to use the content analysis tool to analyze
the content of the two newspapers، whose numbers are (624) from the
newspapers (Al-Sharq Al-Awsat Al-Saudi Arabia and Kayhan Al-Arabi Iran) from (1/1/2018 to 31/12/2018)، and the researc

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Delivery Route Management based on Dijkstra Algorithm
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For businesses that provide delivery services, the efficiency of the delivery process in terms of punctuality is very important. In addition to increasing customer trust, efficient route management, and selection are required to reduce vehicle fuel costs and expedite delivery. Some small and medium businesses still use conventional methods to manage delivery routes. Decisions to manage delivery schedules and routes do not use any specific methods to expedite the delivery settlement process. This process is inefficient, takes a long time, increases costs and is prone to errors. Therefore, the Dijkstra algorithm has been used to improve the delivery management process. A delivery management system was developed to help managers and drivers

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Publication Date
Wed Apr 24 2019
Journal Name
Annals Of Telecommunications
Traveling distance estimation to mitigate unnecessary handoff in mobile wireless networks
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Publication Date
Sat Oct 20 2018
Journal Name
Journal Of Economics And Administrative Sciences
The effect of The Organizational Agility On High Performance ( Applied Search )
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Abstract

The current research aims to know  the  reality of the  research's coefficients, to know  correlation and effectiveness  between  the  organizational  Agility  and high performance . The current research  has been applied on  the official banks , including  a sample of  senior administration  members  (120) ; besides , the research has used questionnaire  that being considered as the main tool for gathering  information  and data . It includes  59 questions  in addition to  the personal interviews  program  as to support  the questionnaire and to fulfill a great deal of reality. It has been anal

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Publication Date
Tue Jan 30 2024
Journal Name
Iraqi Journal Of Science
Parallel Particle Swarm Optimization Algorithm for Identifying Complex Communities in Biological Networks
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    Identification of complex communities in biological networks is a critical and ongoing challenge since lots of network-related problems correspond to the subgraph isomorphism problem known in the literature as NP-hard. Several optimization algorithms have been dedicated and applied to solve this problem. The main challenge regarding the application of optimization algorithms, specifically to handle large-scale complex networks, is their relatively long execution time. Thus, this paper proposes a parallel extension of the PSO algorithm to detect communities in complex biological networks. The main contribution of this study is summarized in three- fold; Firstly, a modified PSO algorithm with a local search operator is proposed

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Publication Date
Sun Jul 01 2018
Journal Name
Ieee Transactions On Intelligent Transportation Systems
Real-Time Intersection-Based Segment Aware Routing Algorithm for Urban Vehicular Networks
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High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Optimum Median Filter Based on Crow Optimization Algorithm
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          A novel median filter based on crow optimization algorithms (OMF) is suggested to reduce the random salt and pepper noise and improve the quality of the RGB-colored and gray images. The fundamental idea of the approach is that first, the crow optimization algorithm detects noise pixels, and that replacing them with an optimum median value depending on a criterion of maximization fitness function. Finally, the standard measure peak signal-to-noise ratio (PSNR), Structural Similarity, absolute square error and mean square error have been used to test the performance of suggested filters (original and improved median filter) used to removed noise from images. It achieves the simulation based on MATLAB R2019b and the resul

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