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.
The necessities of steganography methods for hiding secret message into images have been ascend. Thereby, this study is to generate a practical steganography procedure to hide text into image. This operation allows the user to provide the system with both text and cover image, and to find a resulting image that comprises the hidden text inside. The suggested technique is to hide a text inside the header formats of a digital image. Least Significant Bit (LSB) method to hide the message or text, in order to keep the features and characteristics of the original image are used. A new method is applied via using the whole image (header formats) to hide the image. From the experimental results, suggested technique that gives a higher embe
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback
... Show More:Electron transfer (El) through molecular frameworks is. ce.ntral
to a wide range of chemical, physical , an biological processes. Atheoretical calculation ·investigation of (ED between dihydroxy antimony (V) tetraP.henylporphine cation (Sb''(TP.P)(04)2] and halid cr,Br·,r ,and SCN- is presented . These Calculations &re is fiting on experrnental studies Showing that the rate of Electron Transfer. The theoretical Calculation are based ·an a eontinm: m theory. The tran:sferr ng  
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The application of low order panel method with the Dirichlet boundary condition on complex aircraft configuration have been studied in high subsonic and transonic speeds. Low order panel method has been used to solve the case of the steady, inviscid and compressible flow on a forward swept wing – canard configuration with cylindrical fuselage and a vertical stabilizer with symmetrical cross section. The aerodynamic coefficients for the forward swept wing aircraft were calculated using measured wake shape from an experimental work on same model configuration. The study showed that the application of low order panel method can be used with acceptable results
In this work, novel copolymers of poly(adipic anhydride-co-mannitol) were synthesized by melting condensation polymerization of poly(adipic anhydride) with five percentages of mannitol sugar, 1 to 5 Wt.%. These copolymers were purified and then, characterized by FT-IR, which was proved that the cross-linking reaction was caused by nucleophilic attack of mannitol hydroxyl group to acidic anhydride groups of poly(adipic anhydride) backbone and new ester groups were formed and appeared. Also, modified organic-soluble chitosan, N-maleoyl-chitosan, were synthesized by grafting reaction of chitosan with maleic anhydride in DMF as solvent, and it was also purified and characterized by FT-IR. Biodegradation in vitro of the IPNs of poly(adipic anhyd
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The human perception of science and knowledge is affected by the personal point of view, thus giving it its religious, mental and emotional dimensions to make that perception an effective tool for realizing the truth comprehensively in the delivery of knowledge to the depths of the human soul. The later is composed of multiple factors, which contributes to the human self-development with dimensions beyond the limits of mental logic and the perception of material and emotional situations. That knowledge in the perception of Islamic virtue, which must characterize each Muslim.
Human beings have been striving for knowledge and the understanding of the universe in which they live. For centuries, mankind has acquired knowledge directly an
Background: In recent years, the prevalence of obesity has climbed sharply. Still, only a few safe and effective medications are approved as weight-loss drugs. Objective: This study aims to assess the knowledge and practice of community pharmacists in Iraq regarding the use of Liraglutide and Semaglutide as weight-loss medications. Method: A cross-sectional survey was implemented using a validated questionnaire and a convenient sample of Iraqi community pharmacists from different governorates. The questionnaire was created after conducting a literature review of the most important articles about liraglutide and semaglutide. The questionnaire consists of three sections. The first part was used to collect demographic information. The second a
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