scholarly journals SDG interlinkage networks: Analysis, robustness, sensitivities, and hierarchies

2022 ◽  
Vol 149 ◽  
pp. 105693
Author(s):  
J.H.P. Dawes
Keyword(s):  
Networks Analysis

Social Networks Analysis in Accounting and Finance

2019 ◽  
Author(s):  
Pietro A. Bianchi ◽  
Monika Causholli ◽  
Miguel Minutti-Meza ◽  
Raul Villamil-Otero
Keyword(s):  
Social Networks ◽  
Social Networks Analysis ◽  
Networks Analysis

scholarly journals Approaching the Optimal Solution of the Maximal α-quasi-clique Local Community Problem

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1438
Author(s):  
Patricia Conde-Cespedes
Keyword(s):  
Graph Theory ◽  
Community Detection ◽  
Local Community ◽  
Optimal Solution ◽  
Local Communities ◽  
Optimal Value ◽  
Interesting Task ◽  
Local Community Detection ◽  
Networks Analysis ◽  
Node Problem

Complex networks analysis (CNA) has attracted so much attention in the last few years. An interesting task in CNA complex network analysis is community detection. In this paper, we focus on Local Community Detection, which is the problem of detecting the community of a given node of interest in the whole network. Moreover, we study the problem of finding local communities of high density, known as α-quasi-cliques in graph theory (for high values of α in the interval ]0,1[). Unfortunately, the higher α is, the smaller the communities become. This led to the maximal α-quasi-clique community of a given node problem, which is, the problem of finding local communities that are α-quasi-cliques of maximal size. This problem is NP-hard, then, to approach the optimal solution, some heuristics exist. When α is high (>0.5) the diameter of a maximal α-quasi-clique is at most 2. Based on this property, we propose an algorithm to calculate an upper bound to approach the optimal solution. We evaluate our method in real networks and conclude that, in most cases, the bound is very accurate. Furthermore, for a real small network, the optimal value is exactly achieved in more than 80% of cases.

scholarly journals A Middleware-Based Approach for Multi-Scale Mobility Simulation

2021 ◽  
Vol 13 (2) ◽  
pp. 22
Author(s):  
Xavier Boulet ◽  
Mahdi Zargayouna ◽  
Gérard Scemama ◽  
Fabien Leurent
Keyword(s):  
Modeling And Simulation ◽  
Transportation Networks ◽  
External Control ◽  
Independent Mobility ◽  
Time Step ◽  
Time Representation ◽  
Multi Scale ◽  
Networks Analysis ◽  
Maximal Benefit ◽  
Do So

Modeling and simulation play an important role in transportation networks analysis. In the literature, authors have proposed many traffic and mobility simulations, with different features and corresponding to different contexts and objectives. They notably consider different scales of simulations. The scales refer to the represented entities, as well as to the space and the time representation of the transportation environment. However, we often need to represent different scales in the same simulation, for instance to represent a neighborhood interacting with a wider region. In this paper, we advocate for the reuse of existing simulations to build a new multi-scale simulation. To do so, we propose a middleware model to couple independent mobility simulations, working at different scales. We consider all the necessary processing and workflow to allow for a coherent orchestration of these simulations. We also propose a prototype implementation of the middleware. The results show that such a middleware is capable of creating a new multi-scale mobility simulation from existing ones, while minimizing the incoherence between them. They also suggest that, to have a maximal benefit from the middleware, existing mobility simulation platforms should allow for an external control of the simulations, allowing for executing a time step several times if necessary.

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