scholarly journals A Method of Node Layout of a Complex Network Based on Community Compression

2019 ◽  
Vol 11 (12) ◽  
pp. 250 ◽  
Author(s):  
Chengxiang Liu ◽  
Wei Xiong ◽  
Xitao Zhang ◽  
Zheng Liu
Keyword(s):  
Community Structure ◽  
Complex Network ◽  
Network Node ◽  
Single Node ◽  
Structure Characteristics ◽  
Mesoscale Structure ◽  
The Status ◽  
Importance Analysis ◽  
And Function ◽  
Important Nodes

As the theory of complex networks is further studied, the scale of nodes in the network is increasing, which makes it difficult to find useful patterns from only the analysis of nodes. Therefore, this paper proposes a complex network node layout method based on community compression, which can effectively display the mesoscale structure characteristics of the network, making it more convenient for users to analyze the status and function of a single node or a class of nodes in the whole complex network. To begin with, the whole network is divided into communities with different granularity by the Louvain algorithm. Secondly, the method of nodes importance analysis based on topological potential theory is extended from the network to the community structure, and the internal nodes of the community are classified into three types, namely important nodes, relatively important nodes, and fringe nodes. Furthermore, a compression algorithm for the community structure is designed to realize the compression of the network by retaining important nodes and merging fringe nodes. Finally, the compression network is laid out by the traditional force-directed layout method. Experimental results show that, compared with the compression layout methods of a complex network based on degree or PageRank, the method in this paper can retain the integrated community composition and its internal structure, which is convenient for users to effectively analyze the topology structure of a complex network.

scholarly journals Benefiting from the community structure in opportunistic forwarding

2013 ◽  
Vol 10 (2) ◽  
pp. 865-876
Author(s):  
Bing Bai ◽  
Zhenqian Feng ◽  
Baokang Zhao ◽  
Jinshu Su
Keyword(s):  
Community Structure ◽  
Complex Network ◽  
Single Copy ◽  
Routing Algorithms ◽  
Node Mobility ◽  
Challenging Problem ◽  
Community Based ◽  
Single Node ◽  
Inherent Structure ◽  
Delay Tolerant

In Delay Tolerant Networks (DTNs), an end-to-end connectivity cannot be assumed for node mobility and lack of infrastructure. Due to the uncertainty in nodal mobility, routing in DTNs becomes a challenging problem. To cope with this, many researchers proposed opportunistic routing algorithms based on some utilities. However, these simple metrics may only capture one facet of the single node?s mobility process, which cannot reflect the inherent structure of the networks well. Recently, some researchers introduce the Complex network analysis (CNA) to formulate and predict the future contact in DTNs. The community structure is one of the most important properties of CNA. And it reveals the inherent structure of the complex network. In this paper, we present a community-based single-copy forwarding protocol for DTNs routing, which efficiently utilizes the community structure to improve the forwarding efficiency. Simulation results are presented to support the effectiveness of our scheme.

Current situation and development direction of sports industry in colleges and universities based on euclidean algorithm

2021 ◽  
pp. 1-7
Author(s):  
Shunjiang Ma ◽  
Gaicheng Liu ◽  
Zhiwu Huang
Keyword(s):  
Computer Technology ◽  
Colleges And Universities ◽  
Status Quo ◽  
Euclidean Algorithm ◽  
Test Results ◽  
Sports Industry ◽  
Development Direction ◽  
The Status ◽  
Traditional Sports ◽  
And Function

With the development of sports in colleges and universities, the research on innovation reform of sports industry has been deepened. Therefore, based on the above situation, a study of the status quo and development direction of sports industry in colleges and universities based on the Euclid algorithm is proposed. In the research here, according to the traditional sports industry concept to sum up, and then according to the advantages of computer technology to deal with the relevant data. In order to realize good overlap between data, an application of Euclidean algorithm is proposed. In the test of Euclidean algorithm, the efficiency and function of the algorithm are tested comprehensively, and the test results show that the research is feasible.

Concession Agreements and Nationalization

1958 ◽  
Vol 52 (2) ◽  
pp. 260-279 ◽  
Author(s):  
Kenneth S. Carlston
Keyword(s):  
International Law ◽  
Clear Understanding ◽  
Legal Rules ◽  
Social Facts ◽  
The Social ◽  
The Status ◽  
And Function ◽  
International Economies

It is the purpose of this article to investigate the status of concession agreements in the light of the rules of international law bearing on the power of a state to nationalize property. It is a continuation of an earlier article which explored the nature and function of the concession agreement in the national and international economies. The first article rested on the assumption that legal rules could not be fully understood or evaluated without a fairly clear understanding of the social facts which they were designed to regulate.

AUTOMATIC DEVELOPMENT OF FUZZY MEMBERSHIP FUNCTIONS ON HEPATITIS PATIENTS DATA USING PARTICLE SWARM OPTIMIZATION (PSO)

2015 ◽  
Vol 77 (22) ◽  
Author(s):  
Candra Dewi ◽  
Ratna Putri P.S ◽  
Indriati Indriati
Keyword(s):  
Particle Swarm Optimization ◽  
Membership Function ◽  
Fuzzy System ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Membership Functions ◽  
Swarm Optimization ◽  
Global Weight ◽  
The Status ◽  
And Function

Information about the status of disease (prognosis) for patients with hepatitis is important to determine the type of action to stabilize and cure this disease. Among some system, fuzzy system is one of the methods that can be used to obtain this prognosis. In the fuzzification process, the determination of the exact range of membership function will influence the calculation of membership degree and of course will affect the final value of fuzzy system. This range and function can usually be formed using intuition or by using an algorithm. In this paper, Particle Swarm Optimization (PSO) algorithm is implemented to form the triangular membership functions in the case of patients with hepatitis. For testing process, this paper conducts four scenarios to find the best combination of PSO parameter values . Based on the testing it was found that the best parameters to form a membership function range for the hepatitis data is about 0.9, 0.1, 2, 2, 100, 500 for inertia max, inertia min, local ballast constant, global weight constant, the number of particles, and maximum iterations respectively.  

Community Structure Detection Using Firefly Algorithm

2018 ◽  
Vol 9 (4) ◽  
pp. 52-70 ◽  
Author(s):  
Ameera Saleh Jaradat ◽  
Safa'a Bani Hamad
Keyword(s):  
Community Structure ◽  
Community Detection ◽  
Graph Partitioning ◽  
Firefly Algorithm ◽  
Real Life ◽  
People Detection ◽  
Continuous Growth ◽  
Structure Detection ◽  
Partitioning Problem ◽  
And Function

This article describes how parallel to the continuous growth of the Internet, which allows people to share and collaborate more, social networks have become more attractive as a research topic in many different disciplines. Community structures are established upon interactions between people. Detection of these communities has become a popular topic in computer science. How to detect the communities is of great importance for understanding the organization and function of networks. Community detection is considered a variant of the graph partitioning problem which is NP-hard. In this article, the Firefly algorithm is used as an optimization algorithm to solve the community detection problem by maximizing the modularity measure. Firefly algorithm is a new Nature-inspired heuristic algorithm that proved its good performance in a variety of applications. Experimental results obtained from tests on real-life networks demonstrate that the authors' algorithm successfully detects the community structure.

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