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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
Sun Mar 01 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Effectiveness of Quantitative Instruments in Controlling Money Supply: An Applied Research in the Central Bank of Iraq
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This research deals with the role of quantitative (indirect) tools of monetary policy that used by the Central Bank of Iraq in order to control and manage the size of the money supply that intermediate goal through which monetary policy is able to achieve its final goals, foremost among which is to reduce inflation and raise the value of the local currency in front of foreign currency rates. The research is based on a major hypothesis stating that quantitative tools have a direct and strong influence on the money supply, especially under the circumstances of the shift towards a market economy. There has been a branching relationship with this statistically significant relationship between the money supply and the quantitative tools used

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Publication Date
Mon Jan 01 2018
Journal Name
The Journal Of Contemporary Dental Practice
Assessment of Ions released from Three Types of Orthodontic Brackets immersed in Different Mouthwashes: An in vitro Study
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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Some of Behaviorism Choices that is Availability of Managerial Leaderships an affect of job frustration Management An Opinion Study of Heads Units and Departments In Modern Badoosh Cement Factory
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 Represent choices Behaviorism available to the Managerial leaders one of the prerequisites to run any beginnings of a psychological or dilemmas Managerial barriers to working in the field of work has been varied these options until it had taken several kinds of which contributed to the left different impacts on the alleviation of these problems, which prompted the researcher to raising the problem of study within the framework of questionable content how to contribute to that shown by Choices Behaviorism accredited to the Managerial leaders in the management of frustration

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Publication Date
Sun Sep 01 2019
Journal Name
Diabetes & Metabolic Syndrome: Clinical Research & Reviews
Rhabdomyolysis; is it an overlooked DKA complication
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Publication Date
Thu May 05 2022
Journal Name
Karbala International Journal Of Modern Science
An economical source for peroxidase: maize cobs
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According to the current situation of peroxidase (POD), the relevant studies on this enzyme indicated its importance as a tool in clinical biochemistry and different industrial fields. Most of these studies used the fruits and vegetables as source of this enzyme. So that in order to couple the growing requirements for POD with the recent demands for reduc-ing disposal volume by recycling the plant waste, the aim of the present study was to extract POD through management of municipal bio-waste of Iraqi maize species. A simple, green and economical method was used to extract this enzyme. Our results revealed that maize cobs are rich sources of POD, where the activity of this enzyme was found to be 7035.54 U/g of cobs. In pilot experiments thi

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Publication Date
Tue Dec 30 2014
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Electrofacies Characterization of an Iraqi Carbonate Reservoir
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Predicting peterophysical parameters and doing accurate geological modeling which are an active research area in petroleum industry cannot be done accurately unless the reservoir formations are classified into sub-groups. Also, getting core samples from all wells and characterize them by geologists are very expensive way; therefore, we used the Electro-Facies characterization which is a simple and cost-effective approach to classify one of Iraqi heterogeneous carbonate reservoirs using commonly available well logs.

The main goal of this work is to identify the optimum E-Facies units based on principal components analysis (PCA) and model based cluster analysis(MC

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Publication Date
Thu Sep 16 2021
Journal Name
International Journal Of Clinical Practice
An overview of post‐COVID‐19 complications
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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
An overview of machine learning classification techniques
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Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

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Publication Date
Sun Mar 04 2018
Journal Name
Baghdad Science Journal
CVOTING: An Anonymous Ballot E-Voting System
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One of the concerns of adopting an e-voting systems in the pooling place of any critical elections is the possibility of compromising the voting machine by a malicious piece of code, which could change the votes cast systematically. To address this issue, different techniques have been proposed such as the use of vote verification techniques and the anonymous ballot techniques, e.g., Code Voting. Verifiability may help to detect such attack, while the Code Voting assists to reduce the possibility of attack occurrence. In this paper, a new code voting technique is proposed, implemented and tested, with the aid of an open source voting. The anonymous ballot improved accordingly the paper audit trail used in this machine. The developed system,

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Publication Date
Tue Sep 14 2021
Journal Name
Nature Reviews Microbiology
Towards an integrative view of virus phenotypes
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