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Community Detection in Modular Complex Networks Using an Improved Particle Swarm Optimization Algorithm
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     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a local improvement operator to effectively discover community structure in the modular complex networks when employing the modularity density metric as a single-objective function. The framework of the proposed algorithm consists of three main steps: an initialization strategy, a movement strategy based on perturbation genetic operators, and an improvement operator. The key idea behind the improvement operator is to determine and reassign the complex network nodes that are located in the wrong communities if the majority of their topological links do not belong to their current communities, making it appear that these nodes belong to another community. The performance of the proposed algorithm has been tested and evaluated when applied to publicly-available modular complex networks generated using a flexible and simple benchmark generator. The experimental results showed the effectiveness of the suggested method in discovering community structure over modular networks of different complexities and sizes.

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Publication Date
Sat Jan 01 2022
Journal Name
Desalination And Water Treatment
Optimization and kinetic evaluation of reactive yellow dye degradation by solar photocatalytic process
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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Ant Colony Optimization Based Force-Position Control for Human Lower Limb Rehabilitation Robot
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The aim of human lower limb rehabilitation robot is to regain the ability of motion and to strengthen the weak muscles. This paper proposes the design of a force-position control for a four Degree Of Freedom (4-DOF) lower limb wearable rehabilitation robot. This robot consists of a hip, knee and ankle joints to enable the patient for motion and turn in both directions. The joints are actuated by Pneumatic Muscles Actuators (PMAs). The PMAs have very great potential in medical applications because the similarity to biological muscles. Force-Position control incorporating a Takagi-Sugeno-Kang- three- Proportional-Derivative like Fuzzy Logic (TSK-3-PD) Controllers for position control and three-Proportional (3-P) controllers for force contr

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Publication Date
Wed Jul 05 2023
Journal Name
Chalcogenide Letters
Optimization physical properties of CdTe /Si solar cell devices fabricated by vacuum evaporation
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We investigated at the optical properties, structural makeup, and morphology of thin films of cadmium telluride (CdTe) with a thickness of 150 nm produced by thermal evaporation over glass. The X-ray diffraction study showed that the films had a crystalline composition, a cubic structure, and a preference for grain formation along the (111) crystallographic direction. The outcomes of the inquiry were used to determine these traits. With the use of thin films of CdTe that were doped with Ag at a concentration of 0.5%, the crystallization orientations of pure CdTe (23.58, 39.02, and 46.22) and CdTe:Ag were both determined by X-ray diffraction. orientations (23.72, 39.21, 46.40) For samples that were pure and those that were doped with

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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology & Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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Publication Date
Mon Jan 01 2018
Journal Name
Al–bahith Al–a'alami
The Role of TV Programs in Spreading the Culture of Community for Peace: Studying the Attitudes of the Publics towards a Program entitled Mosamih Kareem on YouTube
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The fundamental problem in determining the role of television programs in broadcasting the culture of community for peace through studying almosamig kareem program by studying the topics addressed in this program. It is a descriptive study and it follows the approach survey method.  In this study, the spatial framework is limited to the program of almosamih kareem on YouTube, while the temporal framework is concerned with the episodes that are raised on YouTube from the second half of 2014 to 2015 of almosamih kareem program. The fundamental problem in determining the role of television programs in broadcasting the culture of community for peace through studying almosamig kareem program by studying the topics addressed in this

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Publication Date
Tue Jun 30 2015
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
Consumer protection in e-marketing contracts An analytical study.: Consumer protection in e-marketing contracts An analytical study.
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Marketing plays a role in the transfer of consumer desires through research, studies and satisfy the needs process, and with the technical development has evolved and marketing departments in the world of commerce has made great strides since the expansion of the trade deal, especially in light of spread of the Internet and the culture of use where he became a lot as individuals or institutions are dealings via electronic shopping . In all cases, we find that the consumer is important party, and that the legal rules did not leave the shopping process or contracting E without protection and I've dealt with so many studies through the civil protection for the consumer in electronic contracts legally with an analytical study of the

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Measuring Positive and Negative Association of Apriori Algorithm with Cosine Correlation Analysis
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This work aims to see the positive association rules and negative association rules in the Apriori algorithm by using cosine correlation analysis. The default and the modified Association Rule Mining algorithm are implemented against the mushroom database to find out the difference of the results. The experimental results showed that the modified Association Rule Mining algorithm could generate negative association rules. The addition of cosine correlation analysis returns a smaller amount of association rules than the amounts of the default Association Rule Mining algorithm. From the top ten association rules, it can be seen that there are different rules between the default and the modified Apriori algorithm. The difference of the obta

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Publication Date
Mon Sep 25 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Algorithm to Solve Linear Volterra Fractional Integro-Differential Equation via Elzaki Transform
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       In this work, Elzaki transform (ET) introduced by Tarig Elzaki is applied to solve linear Volterra fractional integro-differential equations (LVFIDE). The fractional derivative is considered in the Riemman-Liouville sense. The procedure is based on the application of (ET) to (LVFIDE) and using properties of (ET) and its inverse. Finally, some examples are solved to show that this is computationally efficient and accurate.

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Publication Date
Sun Oct 10 2021
Journal Name
Journal Of Physics
A novel kite cross hexagonal search algorithm for fast block motion estimation
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The performance quality and searching speed of Block Matching (BM) algorithm are affected by shapes and sizes of the search patterns used in the algorithm. In this paper, Kite Cross Hexagonal Search (KCHS) is proposed. This algorithm uses different search patterns (kite, cross, and hexagonal) to search for the best Motion Vector (MV). In first step, KCHS uses cross search pattern. In second step, it uses one of kite search patterns (up, down, left, or right depending on the first step). In subsequent steps, it uses large/small Hexagonal Search (HS) patterns. This new algorithm is compared with several known fast block matching algorithms. Comparisons are based on search points and Peak Signal to Noise Ratio (PSNR). According to resul

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Publication Date
Mon Feb 20 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Text Encryption Algorithm Based on Chaotic Neural Network and Random Key Generator
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This work presents a symmetric cryptography coupled with Chaotic NN , the encryption algorithm process the data as a blocks and it consists of multilevel( coding of character, generates array of keys (weights),coding of text and chaotic NN ) , also the decryption process consists of multilevel (generates array of keys (weights),chaotic NN, decoding of text and decoding of character).Chaotic neural network is used as a part of the proposed system with modifying on it ,the keys that are used in chaotic sequence are formed by proposed key generation algorithm .The proposed algorithm appears efficiency during the execution time where it can encryption and decryption long messages by short time and small memory (chaotic NN offer capacity of m

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