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System identification and control of robot manipulator based on fuzzy adaptive differential evolution algorithm
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Publication Date
Tue Jun 20 2023
Journal Name
Bulletin Of The Iraq Natural History Museum
IDENTIFICATION OF HARD TICKS FROM BUFFALO BUBALUS BUBALIS (LINNAEUS, 1758) IN IRAQ
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Ticks (Acari: Ixodidae) are ectoparasites that infest livestock in every geographic region of the world and are vectors of several viral, bacterial, and protozoan pathogens to both animals and humans. There is little information is available is about tick presence in Buffalo Bubalus bubalis (Linnaeus, 1758) (Artiodactyla, Bovidae) in Iraq. The current study determined the species of ticks parasitizing Buffalo in some central and southern regions included: Baghdad (Al Fathelia), Karbala (Al-Hussainia), Wasit (Kut and Al-Suwairah), Al-Qadisia (Al- Diwaniyah, Al- Saniya, Al-Mihnawea, and Afak), Thi Qar (Al-Nasiriyah and Al-chibayish), Missan (Amara and Qalaat Salih) and Basrah (Al-Haretha, Al-Madena and Al-Deer). A total of 150 Buffal

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Publication Date
Thu Feb 01 2024
Journal Name
Ain Shams Engineering Journal
Performance enhancement of high degree Charlier polynomials using multithreaded algorithm
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Publication Date
Wed Jun 01 2022
Journal Name
Journal Of King Saud University - Computer And Information Sciences
Heuristic initialization of PSO task scheduling algorithm in cloud computing
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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Selection of variables Affecting Red Blood Cell by Firefly Algorithm
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Some maps of the chaotic firefly algorithm were selected to select variables for data on blood diseases and blood vessels obtained from Nasiriyah General Hospital where the data were tested and tracking the distribution of Gamma and it was concluded that a Chebyshevmap method is more efficient than a Sinusoidal map method through mean square error criterion.

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Publication Date
Fri Sep 03 2021
Journal Name
Entropy
Reliable Recurrence Algorithm for High-Order Krawtchouk Polynomials
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Krawtchouk polynomials (KPs) and their moments are promising techniques for applications of information theory, coding theory, and signal processing. This is due to the special capabilities of KPs in feature extraction and classification processes. The main challenge in existing KPs recurrence algorithms is that of numerical errors, which occur during the computation of the coefficients in large polynomial sizes, particularly when the KP parameter (p) values deviate away from 0.5 to 0 and 1. To this end, this paper proposes a new recurrence relation in order to compute the coefficients of KPs in high orders. In particular, this paper discusses the development of a new algorithm and presents a new mathematical model for computing the

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Publication Date
Sun Dec 01 2002
Journal Name
Iraqi Journal Of Physics
An edge detection algorithm matching visual contour perception
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For several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.

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Publication Date
Fri Apr 20 2012
Journal Name
International Journal Of Computer And Information Engineering
An Optimal Algorithm for HTML Page Building Process
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An Optimal Algorithm for HTML Page Building Process

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Publication Date
Thu Dec 01 2011
Journal Name
2011 Developments In E-systems Engineering
Enhanced Computation Time for Fast Block Matching Algorithm
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Publication Date
Thu Sep 26 2019
Journal Name
Processes
Fine-Tuning Meta-Heuristic Algorithm for Global Optimization
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This paper proposes a novel meta-heuristic optimization algorithm called the fine-tuning meta-heuristic algorithm (FTMA) for solving global optimization problems. In this algorithm, the solutions are fine-tuned using the fundamental steps in meta-heuristic optimization, namely, exploration, exploitation, and randomization, in such a way that if one step improves the solution, then it is unnecessary to execute the remaining steps. The performance of the proposed FTMA has been compared with that of five other optimization algorithms over ten benchmark test functions. Nine of them are well-known and already exist in the literature, while the tenth one is proposed by the authors and introduced in this article. One test trial was shown t

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Nurse Scheduling Problem Using Hybrid Simulated Annealing Algorithm
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Nurse scheduling problem is one of combinatorial optimization problems and it is one of NP-Hard problems which is difficult to be solved as optimal solution. In this paper, we had created an proposed algorithm which it is hybrid simulated annealing algorithm to solve nurse scheduling problem, developed the simulated annealing algorithm and Genetic algorithm. We can note that the proposed algorithm (Hybrid simulated Annealing Algorithm(GS-h)) is the best method among other methods which it is used in this paper because it satisfied minimum average of the total cost and maximum number of Solved , Best and Optimal problems. So we can note that the ratios of the optimal solution are 77% for the proposed algorithm(GS-h), 28.75% for Si

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