Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:GAYATHRI HARIHARA SUBRAMANIAN, P.S. KARTHIKA, ASHISH VERMA Abstract: Advances in Complex Systems, Volume 24, Issue 01, February 2021. Managing and monitoring large crowds pose a challenge to the crowd management authorities. Understanding the crowd dynamics in terms of its macroscopic parameters and its application to assess the maximum number of people likely to gather at a location or the number of people to be allowed to pass a point can go a long way in preventing situations of crowd risk. This paper presents a comparison of the fundamental diagrams of pedestrian flow at different locations of Kumbh mela and brings out differences in the flow patterns between a general crowd and a spiritually motivated crowd. The effect of spiritual motivation is reflected in terms of higher speeds of pedestrians at some locations and continuous flow despite higher densities. These results fill a significant research gap in the literature by highlighting the unique characteristics of spiritual crowd flows that must be incorporated for simulating a realistic crowd. Citation: Advances in Complex Systems PubDate: 2021-09-30T07:00:00Z DOI: 10.1142/S0219525921500028 Issue No:Vol. 24, No. 01 (2021)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:WILMER LEAL, GUILLERMO RESTREPO, PETER F. STADLER, JÜRGEN JOST Abstract: Advances in Complex Systems, Volume 24, Issue 01, February 2021. Hypergraphs serve as models of complex networks that capture more general structures than binary relations. For graphs, a wide array of statistics has been devised to gauge different aspects of their structures. Hypergraphs lack behind in this respect. The Forman–Ricci curvature is a statistics for graphs based on Riemannian geometry, which stresses the relational character of vertices in a network by focusing on the edges rather than on the vertices. Despite many successful applications of this measure to graphs, Forman–Ricci curvature has not been introduced for hypergraphs. Here, we define the Forman–Ricci curvature for directed and undirected hypergraphs such that the curvature for graphs is recovered as a special case. It quantifies the trade-off between hyperedge (arc) size and the degree of participation of hyperedge (arc) vertices in other hyperedges (arcs). Here, we determine upper and lower bounds for Forman–Ricci curvature both for hypergraphs in general and for graphs in particular. The measure is then applied to two large networks: the Wikipedia vote network and the metabolic network of the bacterium Escherichia coli. In the first case, the curvature is governed by the size of the hyperedges, while in the second example, it is dominated by the hyperedge degree. We found that the number of users involved in Wikipedia elections goes hand-in-hand with the participation of experienced users. The curvature values of the metabolic network allowed detecting redundant and bottle neck reactions. It is found that ADP phosphorylation is the metabolic bottle neck reaction but that the reverse reaction is not similarly central for the metabolism. Furthermore, we show the utility of the Forman–Ricci curvature for quantification of assortativity in hypergraphs and illustrate the idea by investigating three metabolic networks. Citation: Advances in Complex Systems PubDate: 2021-09-30T07:00:00Z DOI: 10.1142/S021952592150003X Issue No:Vol. 24, No. 01 (2021)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:S. EDET, P. PANZARASA, M. RICCABONI Abstract: Advances in Complex Systems, Ahead of Print. Recent studies on international networks have investigated the role of global cities as catalysts of knowledge flows. In this paper, we examine global cities in transnational networks of innovators. To assess the likelihood of scientists and inventors from different cities to take part in international teams, we propose a measure based on 3-hyperedges in the collaboration network constructed from scientific publications and patents. This measure is used to identify the most competitive global cities in the international network of innovators. To this end, we construct a null model based on the hypergeometric ensembles of random graphs. We find that five US cities play a leading role in transnational networks of innovators. Among them, San Francisco stands out as the most globalized city. Citation: Advances in Complex Systems PubDate: 2021-10-13T07:00:00Z DOI: 10.1142/S0219525921400026
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:SHAOPING XIAO, BAIKE SHE, SIDDHARTHA MEHTA, ZHEN KAN Abstract: Advances in Complex Systems, Ahead of Print. In many engineered and natural networked systems, there has been great interest in leader selection and/or edge assignment during the optimal design of controllable networks. In this paper, we present our pioneering work in leader–follower network design via memetic algorithms, which focuses on minimizing the number of leaders or the amount of control energy while ensuring network controllability. We consider three problems in this paper: (1) selecting the minimum number of leaders in a pre-defined network with guaranteed network controllability; (2) selecting the leaders in a pre-defined network with the minimum control energy; and (3) assigning edges (interactions) between nodes to form a controllable leader–follower network with the minimum control energy. The proposed framework can be applied in designing signed, unsigned, directed, or undirected networks. It should be noted that this work is the first to apply memetic algorithms in the design of controllable networks. We chose memetic algorithms because they have been shown to be more efficient and more effective than the standard genetic algorithms in solving some optimization problems. Our simulation results provide an additional demonstration of their efficiency and effectiveness. Citation: Advances in Complex Systems PubDate: 2021-09-25T07:00:00Z DOI: 10.1142/S0219525921500041
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:VASYL PALCHYKOV, MARIANA KRASNYTSKA, OLESYA MRYGLOD, YURIJ HOLOVATCH Abstract: Advances in Complex Systems, Ahead of Print. Concepts in a certain domain of science are linked via intrinsic connections reflecting the structure of knowledge. To get a qualitative insight and a quantitative description of this structure, we perform empirical analysis and modeling of the network of scientific concepts in the domain of physics. To this end, we use a collection of manuscripts submitted to the e-print repository arXiv and the vocabulary of scientific concepts collected via the ScienceWISE.info platform and construct a network of scientific concepts based on their co-occurrences in publications. The resulting complex network possesses a number of specific features (high node density, dissortativity, structural correlations, skewed node degree distribution) that cannot be understood as a result of simple growth by several commonly used network models. We show that the model based on a simultaneous account of two factors, growth by blocks and preferential selection, gives an explanation of empirically observed properties of the concepts network. Citation: Advances in Complex Systems PubDate: 2021-09-17T07:00:00Z DOI: 10.1142/S0219525921400014
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:WEN-JUAN XU, CHEN-YANG ZHONG, HUI-FEN YE, RONG-DA CHEN, TIAN QIU, FEI REN, LI-XIN ZHONG Abstract: Advances in Complex Systems, Ahead of Print. By incorporating delayed epidemic information and self-restricted travel behavior into the SIS model, we have investigated the coupled effects of timely and accurate epidemic information and people’s sensitivity to the epidemic information on contagion. In the population with only local random movement, whether the epidemic information is delayed or not has no effect on the spread of the epidemic. People’s high sensitivity to the epidemic information leads to their risk aversion behavior and the spread of the epidemic is suppressed. In the population with only global person-to-person movement, timely and accurate epidemic information helps an individual cut off the connections with the infected in time and the epidemic is brought under control in no time. A delay in the epidemic information leads to an individual’s misjudgment of who has been infected and who has not, which in turn leads to rapid progress and a higher peak of the epidemic. In the population with coexistence of local and global movement, timely and accurate epidemic information and people’s high sensitivity to the epidemic information play an important role in curbing the epidemic. A theoretical analysis indicates that people’s misjudgment caused by the delayed epidemic information leads to a higher encounter probability between the susceptible and the infected and people’s self-restricted travel behavior helps reduce such an encounter probability. A functional relation between the ratio of infected individuals and the susceptible-infected encounter probability has been found. Citation: Advances in Complex Systems PubDate: 2021-08-11T07:00:00Z DOI: 10.1142/S0219525921500016
Hybrid journal (It can contain Open Access articles)
[118 journals]
