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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
Tue May 30 2023
Journal Name
Iraqi Journal Of Science
Algorithm Development for Full Gaps of Landsat 7 Images
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      Landsat7 of Enhanced thematic mapper plus (ETM+) was launched on April 15,  1999. Four years later, images start degrading due to the scan line corrector (SLC). SLC is a malfunction that results in pixel gaps in images captured by the sensor of Landsat7. The pixel gap regions extend from about one pixel near the image center and reach up to about 14 pixels in width near the image edge. The shape of this loss is like a zigzag line; however, there are different studies about repairing these gaps. The challenge of all studies depends on retrieving inhomogeneous areas because the homogenous area can be retrieved quickly depending on the surrounding area. This research focuses on filling these gaps by utilizing pixels around them

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Publication Date
Sun Sep 01 2019
Journal Name
Baghdad Science Journal
PWRR Algorithm for Video Streaming Process Using Fog Computing
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       The most popular medium that being used by people on the internet nowadays is video streaming.  Nevertheless, streaming a video consumes much of the internet traffics. The massive quantity of internet usage goes for video streaming that disburses nearly 70% of the internet. Some constraints of interactive media might be detached; such as augmented bandwidth usage and lateness. The need for real-time transmission of video streaming while live leads to employing of Fog computing technologies which is an intermediary layer between the cloud and end user. The latter technology has been introduced to alleviate those problems by providing high real-time response and computational resources near to the

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Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
Determination Optimum Inventory Level for Material Using Genetic Algorithm
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The integration of decision-making will lead to the robust of its decisions, and then determination optimum inventory level to the required materials to produce and reduce the total cost by the cooperation of purchasing department with inventory department and also with other company,s departments. Two models are suggested to determine Optimum Inventory Level (OIL), the first model (OIL-model 1) assumed that the inventory level for materials quantities equal to the required materials, while the second model (OIL-model 2) assumed that the inventory level for materials quantities more than the required materials for the next period.             &nb

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Publication Date
Sat Jul 31 2021
Journal Name
Iraqi Journal Of Science
A Decision Tree-Aware Genetic Algorithm for Botnet Detection
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     In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant

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Publication Date
Tue Aug 31 2021
Journal Name
Iraqi Journal Of Science
A lightweight AES Algorithm Implementation for Secure IoT Environment
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In recent years, the rapid development in the field of wireless technologies led to the appearance of a new topic, known as the Internet of things (IoT). The IoT applications can be found in various fields of our life, such as smart home, health care, smart building, and etc. In all these applications, the data collected from the real world are transmitted through the Internet; therefore, these data have become a target of many attacks and hackers. Hence, a secure communication must be provided to protect the transmitted data from unauthorized access. This paper focuses on designing a secure IoT system to protect the sensing data. In this system, the security is provided by the use of Lightweight AES encryption algorithm to encrypt the d

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Publication Date
Sun Oct 30 2022
Journal Name
Iraqi Journal Of Science
Pairwise Regularity and Normality Separation Axioms in C ̌ech Fuzzy Soft Bi-Closure Spaces
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    In this paper, some new types of regularity axioms, namely pairwise quasi-regular, pairwise semi-regular, pairwise pseudo regular and pairwise regular are defined and studied in both ech fuzzy soft bi-closure spaces (  bicsp’s) and their induced fuzzy soft bitopological spaces. We also study the relationships between them. We show that in all these types of axioms, the hereditary property is satisfied under closed fs bi-csubsp of . Furthermore, we define some normality axioms, namely pairwise semi-normal, pairwise pseudo normal, pairwise normal and pairwise completely normal in both  bicsp’s and their induced fuzzy soft bitopological spaces, as well as their basic properties and the relationships between them are studied.

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Publication Date
Thu Apr 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Phytoplankton community within Al-Auda marsh in maysan province southern Iraq
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Abstract<p>Phytoplankton assemblage in relation to physical and chemical characteristics of water in Al-Auda marsh of Maysan province southern Iraq was assessed from November 2012 to July 2013. Six sampling sites were chosen to examine all phytoplankton species in the study area. A total of 246 species and seventy-five genera have been recognized belonging to twelve phytoplankton classes as follows: Bacillariophyceae (106 taxa), Chlorophyceae (34 taxa), Euglenophyceae (29 taxa), Cyanophyceae (29 taxa), Conjugatophyceae (19 taxa), Mediophyceae (10 taxa), Cryptophyceas (5 taxa), Coscinodiscophyceae (4 taxa), Chrysophyceae (4 taxa), Dinophyceae (3 taxa), Trebouxiophyceae (2 taxa) whereas Compsopogonophyceae record</p> ... Show More
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Publication Date
Fri Sep 20 2019
Journal Name
Journal Of The College Of Education For Women
Community Innovation and Its Role in Gender Mainstreaming and Development Issues
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Gender mainstreaming is a goal for building a society characterized by justice and equality. Gender mainstreaming requires a clear understanding of the concept. Therefore, the research focuses on the concept of gender and how it was addressed in the literature through which the concepts related to gender were extracted which is represented by the role and social status through which the relationship of gender can be measured. In order to find out the basis for the different status and roles of both sexes in societies, the interpreted theories of gender were addressed, through which the most important factors affecting gender relations, such as biological, social and economic factors, as well as political systems, were discussed. Due to t

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Publication Date
Sat Dec 11 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Community Pharmacists' Attitudes and Practice in the Management of Minor Ailments
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This study aimed to know the attitudes and practice of pharmacists regarding the management of minor ailments in Iraqi community pharmacies. A cross-sectional study for 320 community pharmacists was conducted during February 2020 using a newly developed and validated questionnaire. Only 4.4% of pharmacists prefer not to deal with minor ailment cases. Minority (15.6%) of participated pharmacists refer more than half of minor ailment cases they face to the physician. Regarding the assessment of minor ailments using WWHAM technique, what are the symptoms are the most commonly asked questions by pharmacists. Only 49.1% mentioned that they ask all WWHAM questions. On the other hand, most pharmacists (90%) educate their patients about the dosi

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Publication Date
Sun Oct 22 2023
Journal Name
Iraqi Journal Of Science
Brain Tumor Detection of Skull Stripped MR Images Utilizing Clustering and Region Growing
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Brain tissues segmentation is usually concerned with the delineation of three types of brain matters Grey Matter (GM), White Matter (WM) and Cerebrospinal Fluid (CSF). Because most brain structures are anatomically defined by boundaries of these tissue classes, accurate segmentation of brain tissues into one of these categories is an important step in quantitative morphological study of the brain. As well as the abnormalities regions like tumors are needed to be delineated. The extra-cortical voxels in MR brain images are often removed in order to facilitate accurate analysis of cortical structures. Brain extraction is necessary to avoid the misclassifications of surrounding tissues, skull and scalp as WM, GM or tumor when implementing s

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