Networked analysis of the Shanghai subway network,in China

Recently, cities have become larger and larger, and more and more people are living in large cities. This phenomenon has caused serious traffic congestion which is very detrimental to the development of large cities. In this context, the subway has become the most effective solution for relieving traffic congestion and subways have been constructed in many cities, so the reliability and robustness of subways should be guaranteed. In this paper, Shanghai subway network, in China, will be analyzed and investigated; the topological characteristics and functional properties can be studied in order to assess the reliability and robustness. The topological characteristics can be measured using several parameters; meanwhile the fraction of removed nodes of Shanghai subway network is discussed and compared against that for a random network, and the critical threshold of this fraction is obtained. Two novel parameters called the functionality loss and connectivity of subway lines are proposed for measuring the transport functionality and the connectivity of subway lines. Subway lines 4 and 7 are selected as examples for evaluating the connectivity of lines subjected to different attack protocols. This study indicates that the subway network is robust against random attacks but fragile for malicious attacks, and the highest betweenness node-based attacks can cause the most serious damage to subway networks among the different attack protocols.     

Efficiency of star-like graphs and the Atlanta subway network

The distance d(i,j)$d(i,j)$ between any two vertices i$i$ and j$j$ in a graph is the number of edges in a shortest path between i$i$ and j$j$. If there is no path connecting i$i$ and j$j$, then d(i,j)=∞$d(i,j)=\infty$. In 2001, Latora and Marchiori introduced the measure of efficiency between vertices in a graph (Latora and Marchiori, 2001) [1]. The efficiency between two vertices i$i$ and j$j$ is defined to be _∈i,j=j${\in }_{i,j}=j$. In this paper, we investigate the efficiency of star-like networks, and show that networks of this type have a high level of efficiency. We apply these ideas to an analysis of the Metropolitan Atlanta Rapid Transit Authority (MARTA) Subway system, and show this network is 82% as efficient as a network where there is a direct line between every pair of stations.     

Skeleton of weighted social network

In the literature of social networks, understanding topological structure is an important scientific issue. In this paper, we construct a network from mobile phone call records and use the cumulative number of calls as a measure of the weight of a social tie. We extract skeletons from the weighted social network on the basis of the weights of ties, and we study their properties. We find that strong ties can support the skeleton in the network by studying the percolation characters. We explore the centrality of w$w$-skeletons based on the correlation between some centrality measures and the skeleton index w$w$ of a vertex, and we find that the average centrality of a w$w$-skeleton increases as w$w$ increases. We also study the cumulative degree distribution of the successive w$w$-skeletons and find that as w$w$ increases, the w$w$-skeleton tends to become more self-similar. Furthermore, fractal characteristics appear in higher w$w$-skeletons. We also explore the global information diffusion efficiency of w$w$-skeletons using simulations, from which we can see that the ties in the high w$w$-skeletons play important roles in information diffusion. Identifying such a simple structure of a w$w$-skeleton is a step forward toward understanding and representing the topological structure of weighted social networks.     

Scale-invariant statistics of period in directed earthquake network

The seismic data taken in California is mapped to a growing directed network. Then, statistics of period in the network, which implies that after how many earthquakes an event returns to the initial location, is studied. It is found that the period distribution obeys a power law, showing the fundamental difficulty of statistical estimate of period.     

Analysis of the airport network of India as a complex weighted network

Transportation infrastructure of a country is one of the most important indicators of its economic growth. Here we study the Airport Network of India (ANI) which represents India’s domestic civil aviation infrastructure as a complex network. We find that ANI, a network of domestic airports connected by air links, is a small-world network characterized by a truncated power-law degree distribution and has a signature of hierarchy. We investigate ANI as a weighted network to explore its various properties and compare them with their topological counterparts. The traffic in ANI, as in the World-wide Airport Network (WAN), is found to be accumulated on interconnected groups of airports and is concentrated between large airports. In contrast to WAN, ANI is found to be having disassortative mixing which is offset by the traffic dynamics. The analysis indicates possible mechanism of formation of a national transportation network, which is different from that on a global scale.     

Properties of a growing random directed network

We study a number of properties of a simple random growing directed network which can be used to model real directed networks such as the world-wide web and call graphs. We confirm numerically that the distributions of in- and out-degree are consistent with a power law, in agreement with previous analytical results and with empirical measurements from real graphs. We study the distribution and mean of the minimum path length, the high degree nodes, the appearance and size of the giant component and the topology of the nodes outside the giant component. These properties are compared with empirical studies of the world-wide web. Received 15 June 2001 and Received in final form 12 July 2001     

基于社团结构的城市地铁网络模型研究

本文运用复杂网络理论, 对我国北京、上海、广州和深圳等城市的地铁网络进行了实证研究. 分别研究了地铁网络的度分布、聚类系数和平均路径长度. 研究表明, 该网络具有高的聚类系数和短的平均路径长度, 显示小世界网络的特征, 其度分布并不严格服从幂律分布或指数分布, 而是呈多段的分布, 显示层次网络的特征. 此外, 它还具有重叠的社团结构特征. 基于实证研究的结果, 提出一种基于社团结构的交通网络模型, 并对该模型进行了模拟分析, 模拟结果表明, 该模型的模拟结果与实证研究结果相符. 此外, 该模型还能解释其他类型的复杂网络(如城市公共汽车交通网络)的网络特性. 关键词： 复杂网络 地铁网络 小世界 社团     

A directed network of Greek and Roman mythology

We construct a directed network using a dictionary of Greek and Roman mythology in which the nodes represent the entries listed in the dictionary and we make directional links from an entry to other entries that appear in its explanatory part. We find that this network is clearly not a random network but a directed scale-free network in which the distributions of out-degree and in-degree follow a power-law with exponents γ_out≈3.0 and γ_in≈2.5, respectively. Also we measure several quantities which describe the topological properties of the network and compare it to that of other real networks.     

Road traffic: A case study of flow and path-dependency in weighted directed networks

How much can we tell about flows through networks just from their topological properties? Whereas flow distributions of river basins, trees or cardiovascular systems come naturally to mind, more complex topologies are not so immediate, especially if the network is large and heterogeneously directed. Our study is motivated by the question of how the distribution of path-dependent trails in directed networks is correlated to the distribution of network flows. As an example we have studied the path-dependencies in closed trails in four metropolitan areas in England and the USA and computed their global and spatial correlations with measured traffic flows. We have found that the heterogeneous distribution of traffic intensity is mirrored by the distribution of agglomerate path-dependency and that high traffic roads are packed along corridors at short-to-medium trail lengths from the ensemble of nodes.     

Exploring new insights in BAlN from evolutionary algorithms ab initio computations

BN-AlN alloys are potential candidates to achieve wide band gap material for ultraviolet device applications. By combing density functional theory and evolutionary structure predictions, we systematically explore the thermodynamic, mechanical, dynamical and optical properties of ${\mathrm{B}}_x{\mathrm{Al}}_{1?x}\mathrm{N}$ alloys. Through structure search, three compounds (cubic ($\mathrm{B}{\mathrm{Al}}_3{\mathrm{N}}_4$, and ${\mathrm{B}}_3\mathrm{Al}{\mathrm{N}}_4$, space group P-43m), and tetragonal ($\mathrm{B}\mathrm{Al}{\mathrm{N}}_2$, space group P-42m)) have been predicted. The calculated relative large formation enthalpies suggest that large miscibility gap exists in BAlN alloys. In addition, computed elastic constants and phonon show that these structures are mechanically and dynamically stable. From the state of the art LDA-1/2 we show that the direct band gap of BN-AlN evinces strong deviation from a linear dependence on B composition. We found -in particular- giant direct band gap bowing parameter of $b～11.6$ eV for the entire range of composition, where b parameter is found to be sensitive to composition x. From a detailed analysis of the physical origin of the optical gap bowing b, we found that structural and chemical contributions play the most significant effects behind the huge optical band gap bowing parameter of BAlN alloys.     

A centrality measure for communication ability in weighted network

This paper proposes a new node centrality measurement in a weighted network, the communication centrality, which is inspired by Hirsch’s h$h$-index. We investigated the properties of the communication centrality, and proved that the distribution of the communication centrality has the power-law upper tail in weighted scale-free networks. Relevant measures for node and network are discussed as extensions. A case study of a scientific collaboration network indicates that the communication centrality is different from other common centrality measures and other h$h$-type indexes. Communication centrality displays moderate correlation with other indexes, and contains a well-balanced mix of other centrality measures and cannot be replaced by any of them.     

Projective synchronization of spatiotemporal chaos in a weighted complex network

<正>Projective synchronization of a weighted complex network is studied in which nodes are spatiotemporal chaos systems and all nodes are coupled not with the nonlinear terms of the system but through a weighted connection.The range of the linear coefficient matrix of separated configuration,when the synchronization is implemented,is determined according to Lyapunov stability theory.It is found that projective synchronization can be realized for unidirectional star-connection even if the coupling strength between the nodes is a given arbitrary weight value.The Gray-Scott models having spatiotemporal chaos behaviours are taken as nodes in the weighted complex network,and simulation results of spatiotemporal synchronization show the effectiveness of the method.     

Synchronization transition of identical phase oscillators in a directed small-world network

We numerically study a directed small-world network consisting of attractively coupled, identical phase oscillators. While complete synchronization is always stable, it is not always reachable from random initial conditions. Depending on the shortcut density and on the asymmetry of the phase coupling function, there exists a regime of persistent chaotic dynamics. By increasing the density of shortcuts or decreasing the asymmetry of the phase coupling function, we observe a discontinuous transition in the ability of the system to synchronize. Using a control technique, we identify the bifurcation scenario of the order parameter. We also discuss the relation between dynamics and topology and remark on the similarity of the synchronization transition to directed percolation.     

Stability of weighted spectral distribution in a pseudo tree-like network model

The comparison of networks with different orders strongly depends on the stability analysis of graph features in evolving systems. In this paper, we rigorously investigate the stability of the weighted spectral distribution(i.e., a spectral graph feature) as the network order increases. First, we use deterministic scale-free networks generated by a pseudo treelike model to derive the precise formula of the spectral feature, and then analyze the stability of the spectral feature based on the precise formula. Except for the scale-free feature, the pseudo tree-like model exhibits the hierarchical and small-world structures of complex networks. The stability analysis is useful for the classification of networks with different orders and the similarity analysis of networks that may belong to the same evolving system.     

Applications of Markov spectra for the weighted partition network by the substitution rule

The weighted self-similar network is introduced in an iterative way. In order to understand the topological properties of the self-similar network, we have done a lot of research in this field.Firstly, according to the symmetry feature of the self-similar network, we deduce the recursive relationship of its eigenvalues at two successive generations of the transition-weighted matrix.Then, we obtain eigenvalues of the Laplacian matrix from these two successive generations.Finally, we calculate an accurate expression for the eigentime identity and Kirchhoff index from the spectrum of the Laplacian matrix.     

Exploring the relationship between fractal features and bacterial essential genes

Essential genes are indispensable for the survival of an organism in optimal conditions.Rapid and accurate identifications of new essential genes are of great theoretical and practical significance.Exploring features with predictive power is fundamental for this.Here,we calculate six fractal features from primary gene and protein sequences and then explore their relationship with gene essentiality by statistical analysis and machine learning-based methods.The models are applied to all the currently available identified genes in 27 bacteria from the database of essential genes(DEG).It is found that the fractal features of essential genes generally differ from those of non-essential genes.The fractal features are used to ascertain the parameters of two machine learning classifiers:Na¨?ve Bayes and Random Forest.The area under the curve(AUC) of both classifiers show that each fractal feature is satisfactorily discriminative between essential genes and non-essential genes individually.And,although significant correlations exist among fractal features,gene essentiality can also be reliably predicted by various combinations of them.Thus,the fractal features analyzed in our study can be used not only to construct a good essentiality classifier alone,but also to be significant contributors for computational tools identifying essential genes.     

环形加权网络的时空混沌延迟同步

研究了环形加权网络的时空混沌延迟同步问题.以随时间和空间演化均呈现混沌行为的时空混沌系统作为网络的节点,通过环形加权连接使所有节点建立关联.基于线性稳定性定理,通过确定网络的最大Lyapunov指数,得到了实现网络延迟同步的条件.在最大Lyapunov指数小于零的区域内,任取节点之间耦合强度的权重值,均可以使整个网络实现延迟同步.采用具有时空混沌行为的自催化反应扩散系统作为网络节点,仿真模拟验证了该方法的有效性. 关键词： 延迟同步 加权网络 时空混沌 Lyapunov指数     

激光时空混沌模型的加权网络投影同步

提出了一种实现加权网络时空混沌投影同步的方法.通过构造合适的Lyapunov函数,确定了加权网络中连接节点之间耦合函数的结构以及网络节点状态方程中分离配置的线性项的系数矩阵的取值范围.以Bragg声光双稳系统作为局域函数,单向耦合映像格子作为空间扩展系统构成激光时空混沌模型.通过仿真模拟检验了采用激光时空混沌模型作为网络节点的加权网络的投影同步效果.结果显示,对于任意的节点之间耦合强度的权重值,加权网络的投影同步均可以实现. 关键词： 投影同步 加权网络 时空混沌 Bragg声光双稳系统     

能量异构的无线传感器网络加权无标度拓扑研究

针对无线传感器网络节点能耗不均和如何高效获得节点和边的负载问题,提出一种局域范围内能量异构的加权无标度拓扑演化模型.通过对节点能量与负载、能耗的关系建模,建立节点能量与点权和边权的联系,进而结合点权和加权模型给出网络的演化方式,推出点权、度和边权的幂率分布规律,最终根据网络获得的点权和边权来分析负载和能耗.仿真结果表明,提出的模型不仅能够准确计算点边的负载,而且缓解了无标度网络的节点能耗不均衡问题.