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An Evolutionary Bi-clustering Algorithm for Community Mining in Complex Networks
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A network (or formally a graph) can be described by a set of nodes and a set of edges connecting these nodes. Networks model many real-world phenomena in various research domains, such as biology, engineering and sociology. Community mining is discovering the groups in a network where individuals group of membership are not explicitly given. Detecting natural divisions in such complex networks is proved to be extremely NP-hard problem that recently enjoyed a considerable interest. Among the proposed methods, the field of evolutionary algorithms (EAs) takes a remarkable interest. To this end, the aim of this paper is to present the general statement of community detection problem in social networks. Then, it visits the problem as an optimization problem where a modularity-based ( ) and normalized mutual information ( ) metrics are formulated to describe the problem. An evolutionary algorithm is then expressed in the light of its characteristic components to tackle the problem. The presentation will highlight the possible alternative that can be adopted in this study for individual representation, fitness evaluations, and crossover and mutation operators. The results point out that adopting as a fitness function carries out more correct solutions than adopting the modularity function . Moreover, the strength of mutation has a background role. When coupled with non elite selection, increasing mutation probability could results in better solutions. However, when elitism is used, increasing mutation probability could bewilder the behavior of EA.
A network (or formally a graph) can be described by a set of nodes and a set of edges connecting these nodes. Networks model many real-world phenomena in various research domains, such as biology, engineering and sociology. Community mining is discovering the groups in a network where individuals group of membership are not explicitly given. Detecting natural divisions in such complex networks is proved to be extremely NP-hard problem that recently enjoyed a considerable interest. Among the proposed methods, the field of evolutionary algorithms (EAs) takes a remarkable interest. To this end, the aim of this paper is to present the general statement of community detection problem in social networks. Then, it visits the problem as an optimization problem where a modularity-based ( ) and normalized mutual information ( ) metrics are formulated to describe the problem. An evolutionary algorithm is then expressed in the light of its characteristic components to tackle the problem. The presentation will highlight the possible alternative that can be adopted in this study for individual representation, fitness evaluations, and crossover and mutation operators. The results point out that adopting as a fitness function carries out more correct solutions than adopting the modularity function . Moreover, the strength of mutation has a background role. When coupled with non elite selection, increasing mutation probability could results in better solutions. However, when elitism is used, increasing mutation probability could bewilder the behavior of EA.

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Development of an Integrated Construction Management System for Building Estimation
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Project management are still depending on manual exchange of information based on paper documents. Where design drawings drafting by computer-aided design (CAD), but the data needed by project management software can not be extracted directly from CAD, and must be manually entered by the user. The process of calculation and collection of information from drawings and enter in the project management software needs effort and time with the possibility of errors in the transfer and enter of information. This research presents an integrated computer system for building projects where the extraction and import quantities, through the interpretation of AutoCAD drawing with MS Access database of unit costs and productivities for the pricing and

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Publication Date
Sun May 17 2020
Journal Name
Iraqi Journal Of Science
Bayesian Adaptive Bridge Regression for Ordinal Models with an Application
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In this article, we propose a Bayesian Adaptive bridge regression for ordinal model. We developed a new hierarchical model for ordinal regression in the Bayesian adaptive bridge. We consider a fully Bayesian approach that yields a new algorithm with tractable full conditional posteriors. All of the results in real data and simulation application indicate that our method is effective and performs very good compared to other methods. We can also observe that the estimator parameters in our proposed method, compared with other methods, are very close to the true parameter values.

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Publication Date
Fri Apr 01 2022
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
An adaptive neural control methodology design for dynamics mobile robot
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Publication Date
Thu Aug 01 2024
Journal Name
Smart Agricultural Technology
Smart fertilizer technologies: An environmental impact assessment for sustainable agriculture
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The global food supply heavily depends on utilizing fertilizers to meet production goals. The adverse impacts of traditional fertilization practices on the environment have necessitated the exploration of new alternatives in the form of smart fertilizer technologies (SFTs). This review seeks to categorize SFTs, which are slow and controlled-release Fertilizers (SCRFs), nano fertilizers, and biological fertilizers, and describes their operational principles. It examines the environmental implications of conventional fertilizers and outlines the attributes of SFTs that effectively address these concerns. The findings demonstrate a pronounced environmental advantage of SFTs, including enhanced crop yields, minimized nutrient loss, improved nut

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Publication Date
Wed Mar 16 2022
Journal Name
Journal Of Educational And Psychological Researches
Cognitive Distortions and Time Management as Predictors of Academic Procrastination among Students from Al Aqsa Community College
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The study aimed to reveal the possibility of predicting academic procrastination through both Cognitive distortions and time management among students of Al-Aqsa Community College, as well as to reveal the level of both cognitive distortions, time management, and academic procrastination. Additionally, it aimed to identify the size of the correlation between cognitive distortions, time management, and academic procrastination. The study sample consisted of (250) students from Al-Aqsa community college students. The results of the study concluded that the mean for each level of cognitive distortions and academic procrastination is average. The mean level of time management is high. There is a statistically significant positive relationshi

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Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Science
Impact of Hindiya Dam on Rotifera Community of Euphrates River on the Northern of Babil Governorate, Iraq
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     This study was the first of its kind on the Hindiya Dam, which is considered one of the important dams in Euphrates River. Five sites were chosen on the north of Babil Governorate in   order to know the rotifers biodiversity features and the impact of the Hindiya Dam on it's during the 2019. Site2(S2) was located near the dam to reflect the rotifers diversity of this site, whereas , S1 was located at the upstream of the dam as a control site, and  S3, S4 and S5 were located down the dam.  Rotifers  showed higher density average at Hindiya Dam site compared with sites downstream the dam which was 9164 Ind./m3, whereas density average at the site downstream the dam

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Planner And Development
Analysis and evaluation of related factors affecting community Participation as a policy to upgrade residential slums area
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have suffered from deteriorating residential neighborhoods, poor economic, social and urban living conditions of the population and deteriorating the infrastructural and superior services. These problems were the secretions of these cities' rapid urbanization. Based on the principles of sustainable urban planning and in order to achieve adequate opportunities for the lives of the population and provide them with sustainable livelihoods, policies have emerged to upgrade along the lines of community participation and programmes to reform and develop those neighbourhoods, raise their efficiency and make them livable. Thus, the problem of research was identified "The absence of a comprehensive cognitive perception of the most prominent facto

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Publication Date
Thu Sep 02 2021
Journal Name
Solid State Technology
Spectroscopic Investigation of Charge Transfer Complex And Adsorption of Nitrondye with Curcumin(1) Onmodified Attapulgiteclay
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A charge transfer complex formed by interaction between nitron as electron donor with curcumin(1 ) as electron acceptor in ethanol at the temperature of theroom to form a colored complex. The optimum conditions of complex formation were investigated by Univariate method. The linearity range of complex was (3.124– 53.11) μg.mL-1 at 442 nm with molar absorptivity (1858.33) L.mol-1.cm-1, Sandell's sensitivity (0.1681μg.cm-2), and with a correlation coefficient (0.9935). Both modified attapulgite and modified attapulgite – complex have been characterized by using , FTIR, SEM, AFM, and XRD. Theadsorption behaviourof complex onto the modified attapulgite has been researchedthrough the variation of the parameters like the adsorbent weight, p

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Publication Date
Mon Oct 05 2020
Journal Name
International Journal Of Advanced Science And Technology
Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval
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Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval

Publication Date
Wed May 24 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
On Comparison between Radial Basis Function and Wavelet Basis Functions Neural Networks
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      In this paper we study and design two feed forward neural networks. The first approach uses radial basis function network and second approach uses wavelet basis function network to approximate the mapping from the input to the output space. The trained networks are then used in an conjugate gradient algorithm to estimate the output. These neural networks are then applied to solve differential equation. Results of applying these algorithms to several examples are presented

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