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.
This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that
Signal denoising is directly related to sample estimation of received signals, either by estimating the equation parameters for the target reflections or the surrounding noise and clutter accompanying the data of interest. Radar signals recorded using analogue or digital devices are not immune to noise. Random or white noise with no coherency is mainly produced in the form of random electrons, and caused by heat, environment, and stray circuitry loses. These factors influence the output signal voltage, thus creating detectable noise. Differential Evolution (DE) is an effectual, competent, and robust optimisation method used to solve different problems in the engineering and scientific domains, such as in signal processing. This paper looks
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In this study, He's parallel numerical algorithm by neural network is applied to type of integration of fractional equations is Abel’s integral equations of the 1st and 2nd kinds. Using a Levenberge – Marquaradt training algorithm as a tool to train the network. To show the efficiency of the method, some type of Abel’s integral equations is solved as numerical examples. Numerical results show that the new method is very efficient problems with high accuracy.
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This study proposes a mathematical approach and numerical experiment for a simple solution of cardiac blood flow to the heart's blood vessels. A mathematical model of human blood flow through arterial branches was studied and calculated using the Navier-Stokes partial differential equation with finite element analysis (FEA) approach. Furthermore, FEA is applied to the steady flow of two-dimensional viscous liquids through different geometries. The validity of the computational method is determined by comparing numerical experiments with the results of the analysis of different functions. Numerical analysis showed that the highest blood flow velocity of 1.22 cm/s occurred in the center of the vessel which tends to be laminar and is influe
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The study includes the relationship between the ecologia and Abbaside's community in the middle ages, and the role of Baghdad capital city to increasing the sensibility of the people to the outwardly peripheral.
The study explains the efforts between the people and Abbaside's government to cure the knowledge of ecologia, to prevent the separation of diseases and pollutions of the community.
Keywords: Ecologia, Abbasid's, diseases, pollutions.
The world went through turmoil before the sixth century AD, and human societies were in conflict and rivalry, each strong state is a weak state-dependent, but the dominant societies made the slave societies to them .. And thus made many societies or civilizations system of classes, and differentiation between members of one community, Weakened its strength and go alone. As the Islamic society in the present weak and weak and falling to the lowest levels of civilizational underdevelopment in the organization of society and social security contrary to what it was Islamic civilization, because of our distance from the heavenly instructions, and this prompted many to walk behind Western ideas aimed at the demolition of Islamic civilization,
... Show MorePraise be to God, Lord of the worlds, and prayers and peace be upon our master Muhammad and upon his family and companions.
We see human societies differ from one society to another in organizing social life, and each according to the foundations and rules prepared by the main thing in the welfare and prosperity.
That is why we see eastern societies differ from western societies in many patterns and various ways of reaching that sophistication, until Islam came and gave the proper model in raising society at that time to the best and highest social levels, because it is based on heavenly rules and foundations and not status as in previous civilizations.
And when the Islamic community has