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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
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat

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Publication Date
Sun Mar 29 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Using Different Methods to Predict Oil in Place in Mishrif Formation / Amara Oil Field
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The reserve estimation process is continuous during the life of the field due to risk and inaccuracy that are considered an endemic problem thereby must be studied. Furthermore, the truth and properly defined hydrocarbon content can be identified just only at the field depletion. As a result, reserve estimation challenge is a function of time and available data. Reserve estimation can be divided into five types: analogy, volumetric, decline curve analysis, material balance and reservoir simulation, each of them differs from another to the kind of data required. The choice of the suitable and appropriate method relies on reservoir maturity, heterogeneity in the reservoir and data acquisition required. In this research, three types of rese

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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Green Innovation and its Impact in Reinforcing Sustainable Competitive Advantage: An Exploratory Study of Opinions of a Sample of Employees in the Karungi group in Kirkuk
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The development of the world, and in light of the intensity of competition highlighted the need to research and create a sustainable competitive advantage is sustained from an internal source in the company earned by the scarcity and difficulty of imitation by competitors, and this source is green innovation. In order to achieve the objective of the research, which is the diagnosis and analysis of the relationship between green innovation (in products, processes) and sustainable competitive advantage in the group of companies Kronji, was developed a default model of the research reflects the nature of the relationship and influence among its variables, the research adopted the questionnaire as a key tool for collecting data and i

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Publication Date
Tue Feb 28 2023
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Importance of Using Concentrator Solar Energy Technologies in Anbar Province
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The aim of the research is a techno-economic analysis of the use of concentrated solar energy technologies in the Iraqi city, considering the concentrated solar energy technology is a renewable energy technology that derives its resources from the sun and is replenished at a rate that exceeds its use. It is also inexhaustible and environmentally friendly energy from its environmental footprint, unlike traditional fossil energy which produces greenhouse gases and a major cause of global warming.

This research measures the costs of concentrated solar energy technology to Reduce the effects caused by other energies and work to fill part of the shortfall in the total electricity production, even at a specific percentage, in preparati

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Publication Date
Thu Dec 31 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Reducing of Corrosion Rate in Boiler Tubes by Using Oxygen Scavengers
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The corrosion behavior of carbon steel at different temperatures 100,120,140 and 160 Cͦ under different pressures 7,10 and 13 bar in pure distilled water and after adding three types of oxygen scavengers Hydroquinone, Ascorbic acid and Monoethanolamine in different concentrations 40,60 and 80 ppm has been investigated using weight loss method. The carbon steel specimens were immersed in water containing 8.2 ppm dissolved oxygen (DO) by using autoclave. It was found that corrosion behavior of carbon steel was greatly influenced by temperature with high pressure. The corrosion rate decreases, when adding any one of oxygen scavengers. The best results were obtained at a concentration of 80 ppm of each scavenger. It was observed that 

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Publication Date
Fri Sep 08 2006
Journal Name
Journal Of Engineering
INFLUENCE OF DEFECT IN THE CONCRETE PILES USING NON-DESTRUCTIVE TESTING
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This paper presents the results of experimental investigation carried out on concrete model piles to study the behaviour of defective piles. This was achieved by employing non-destructive tests using ultrasonic waves. It was found that the reduction in pile stiffness factor is found to be about (26%) when the defect ratio increased from (5%) to (15%). The modulus of elasticity reduction factor as well as the dynamic modulus of elasticity reduction factor increase with the defect ratio

Publication Date
Fri Jun 01 2018
Journal Name
International Journal Of Computer Science Trends And Technology
Secure Video Data Deduplication in the Cloud Storage Using Compressive Sensing
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Cloud storage provides scalable and low cost resources featuring economies of scale based on cross-user architecture. As the amount of data outsourced grows explosively, data deduplication, a technique that eliminates data redundancy, becomes essential. The most important cloud service is data storage. In order to protect the privacy of data owner, data are stored in cloud in an encrypted form. However, encrypted data introduce new challenges for cloud data deduplication, which becomes crucial for data storage. Traditional deduplication schemes cannot work on encrypted data. Existing solutions of encrypted data deduplication suffer from security weakness. This paper proposes a combined compressive sensing and video deduplication to maximize

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Publication Date
Wed Jun 24 2020
Journal Name
Journal Of Engineering
Using Steel Slag for Stabilizing Clayey Soil in Sulaimani City-Iraq
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The clayey soils have the capability to swell and shrink with the variation in moisture content. Soil stabilization is a well-known technique, which is implemented to improve the geotechnical properties of soils. The massive quantities of waste materials are resulting from modern industry methods create disposal hazards in addition to environmental problems. The steel industry has a waste that can be used with low strength and weak engineering properties soils. This study is carried out to evaluate the effect of steel slag (SS) as a by-product of the geotechnical properties of clayey soil. A series of laboratory tests were conducted on natural and stabilized soils. SS was added by 0, 2.5, 5, 10, 15, and 20% to the soil.

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Publication Date
Sun Jan 01 2023
Journal Name
International Conference Of Computational Methods In Sciences And Engineering Iccmse 2021
Penetration of charged particles in ZnO using energy loss function model
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In this paper, we propose an approach to estimate the induced potential, which is generated by swift heavy ions traversing a ZnO thin film, via an energy loss function (ELF). This induced potential is related to the projectile charge density, ρq(k) and is described by the extended Drude dielectric function. At zero momentum transfer, the resulting ELF exhibits good agreement with the previously reported results. The ELF, obtained by the extended Drude model, displays a realistic behavior over the Bethe ridge. It is observed that the induced potential relies on the heavy ion velocity and charge state q. Further, the numerical results show that the induced potential for neutral H, as projectile, dominates when the heavy ion velocity is less

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