The accelerated growth of the worldwide air transportation network

Mobility by means of air transportation has a critical impact on the global economy. Especially against the backdrop of further growth and an aggravation of the energy crisis, it is crucial to design a sustainable air transportation system. Current approaches focus on air traffic management. Nevertheless, also the historically evolved network offers great potential for an optimized redesign. But the understanding of its complex structure and development is limited, although modern network science supplies a great set of new methods and tools. So far studies analyzing air transportation as a complex network are based on divers and poor data, which are either merely regional or strongly bounded time-wise. As a result, the current state of research is rather inconsistent regarding topological coefficients and incomplete regarding network evolution. Therefore, we use the historical, worldwide OAG flight schedules data between 1979 and 2007 for our study. Through analyzing by far the most comprehensive data base so far, a better understanding of the network, its evolution and further implications is being provided. To our knowledge we present the first study to determine that the degree distribution of the worldwide air transportation network is non-stationary and is subject to densification and accelerated growth, respectively.     

Weighted complex network analysis of travel routes on the Singapore public transportation system

The structure and properties of public transportation networks have great implications for urban planning, public policies and infectious disease control. We contribute a complex weighted network analysis of travel routes on the Singapore rail and bus transportation systems. We study the two networks using both topological and dynamical analyses. Our results provide additional evidence that a dynamical study adds to the information gained by traditional topological analysis, providing a richer view of complex weighted networks. For example, while initial topological measures showed that the rail network is almost fully connected, dynamical measures highlighted hub nodes that experience disproportionately large traffic. The dynamical assortativity of the bus networks also differed from its topological counterpart. In addition, inspection of the weighted eigenvector centralities highlighted a significant difference in traffic flows for both networks during weekdays and weekends, suggesting the importance of adding a temporal perspective missing from many previous studies.     

Jamming transition in air transportation networks

In this work we present a model of an air transportation traffic system from the complex network modelling viewpoint. In the network, every node corresponds to a given airport, and two nodes are connected by means of flight routes. Each node is weighted according to its load capacity, and links are weighted according to the Euclidean distance that separates each pair of nodes. Local rules describing the behaviour of individual nodes in terms of the surrounding flow have been also modelled, and a random network topology has been chosen in a baseline approach. Numerical simulations describing the diffusion of a given number of agents (aircraft) in this network show the onset of a jamming transition that distinguishes an efficient regime with null amount of airport queues and high diffusivity (free phase) and a regime where bottlenecks suddenly take place, leading to a poor aircraft diffusion (congested phase). Fluctuations are maximal around the congestion threshold, suggesting that the transition is critical. We then proceed by exploring the robustness of our results in neutral random topologies by embedding the model in heterogeneous networks. Specifically, we make use of the European air transportation network formed by 858 airports and 11 170 flight routes connecting them, which we show to be scale-free. The jamming transition is also observed in this case. These results and methodologies may introduce relevant decision-making procedures in order to optimize the air transportation traffic.     

Topology of the fittest transportation network

The presence or absence of loops in the emergent transportation networks, that are characterized by a minimum overall cost, is shown to depend on the convexity of the cost function for the local transportation of material. Our results are directly applicable to a variety of situations across disciplines.     

Synchronization in a multiplex network of gene oscillators

Study of the synchronization in the network of gene oscillator network has vital importance in understanding of rhythmicity of molecular and cellular activities. In this paper, we analyze a network of linearly coupled genetic oscillators in a multiplex structure. The coupling strength values are changed and the coupling range is considered to be fixed, but different in the two layers. The analyses are done in two cases of periodic and chaotic oscillations. By computing the statistical measures, the interlayer and intralayer synchronization states are studied. The results show that the layer with higher coupling range has more enhanced synchrony and is less affected by the turbulent behavior of the other layer. On the other hand, the layer with lower coupling range approaches synchronization by strengthening the interlayer and intralayer couplings. The interlayer synchronization is also achieved in high coupling strength values.     

Empirical analysis of the worldwide maritime transportation network

In this paper we present an empirical study of the worldwide maritime transportation network (WMN) in which the nodes are ports and links are container liners connecting the ports. Using the different representations of network topology — the spaces L and P, we study the statistical properties of WMN including degree distribution, degree correlations, weight distribution, strength distribution, average shortest path length, line length distribution and centrality measures. We find that WMN is a small-world network with power law behavior. Important nodes are identified based on different centrality measures. Through analyzing weighted clustering coefficient and weighted average nearest neighbors degree, we reveal the hierarchy structure and rich-club phenomenon in the network.     

Weighted and unweighted network of amino acids within protein

The information regarding the structure of a single protein is encoded in the network of interacting amino acids considered as nodes. If any two atoms from two different amino acids (nodes) are within higher cut-off distance of London-van der Waals forces, the amino acids are considered to be linked or connected. Several atoms of any amino acids in a protein may be within the above prescribed distance of several atoms of another amino acid resulting in possible multiple links between them. These multiple links are the basis of the weight of the connectivity in a protein network. Each protein has been considered as a weighted and an unweighted network of amino acids. A total of forty nine protein structures that covers the three branches of life on earth has been analyzed and several network properties have been studied. The probability degree and strength distributions of network connectivity have been obtained. It has been observed that the average strength of amino acid node depends on its degree. The results show that the average clustering coefficient of weighted network is less than that of unweighted network. It implies that the topological clustering is generated by edges with low weights. The power-law behavior of clustering coefficients of weighted and unweighted networks as a function of degree indicates that they have signatures of hierarchy. It has also been observed that the network is of assortative type.     

Complexity in human transportation networks: a comparative analysis of worldwide air transportation and global cargo-ship movements

We present a comparative network-theoretic analysis of the two largest global transportation networks: the worldwide air-transportation network (WAN) and the global cargo-ship network (GCSN). We show that both networks exhibit surprising statistical similarities despite significant differences in topology and connectivity. Both networks exhibit a discontinuity in node and link betweenness distributions which implies that these networks naturally segregate into two different classes of nodes and links. We introduce a technique based on effective distances, shortest paths and shortest path trees for strongly weighted symmetric networks and show that in a shortest path tree representation the most significant features of both networks can be readily seen. We show that effective shortest path distance, unlike conventional geographic distance measures, strongly correlates with node centrality measures. Using the new technique we show that network resilience can be investigated more precisely than with contemporary techniques that are based on percolation theory. We extract a functional relationship between node characteristics and resilience to network disruption. Finally we discuss the results, their implications and conclude that dynamic processes that evolve on both networks are expected to share universal dynamic characteristics.     

Analysis of identification methods of key nodes in transportation network

The identification of key nodes plays an important role in improving the robustness of the transportation network. For different types of transportation networks, the effect of the same identification method may be different. It is of practical significance to study the key nodes identification methods corresponding to various types of transportation networks. Based on the knowledge of complex networks, the metro networks and the bus networks are selected as the objects, and the key nodes are identified by the node degree identification method, the neighbor node degree identification method, the weighted k-shell degree neighborhood identification method (KSD), the degree k-shell identification method (DKS), and the degree k-shell neighborhood identification method (DKSN). Take the network efficiency and the largest connected subgraph as the effective indicators. The results show that the KSD identification method that comprehensively considers the elements has the best recognition effect and has certain practical significance.     

Analysis of the Chinese air route network as a complex network

The air route network, which supports all the flight activities of the civil aviation, is the most fundamental infrastructure of air traffic management system. In this paper, we study the Chinese air route network (CARN) within the framework of complex networks. We find that CARN is a geographical network possessing exponential degree distribution, low clustering coefficient, large shortest path length and exponential spatial distance distribution that is obviously different from that of the Chinese airport network (CAN). Besides, via investigating the flight data from 2002 to 2010, we demonstrate that the topology structure of CARN is homogeneous, howbeit the distribution of flight flow on CARN is rather heterogeneous. In addition, the traffic on CARN keeps growing in an exponential form and the increasing speed of west China is remarkably larger than that of east China. Our work will be helpful to better understand Chinese air traffic systems.     

基于多路可视图的健康与心梗患者心电图信号复杂网络识别

可视图(visibility graph, VG)算法已被证明是将时间序列转换为复杂网络的简单且高效的方法,其构成的复杂网络在拓扑结构中继承了原始时间序列的动力学特性.目前,单维时间序列的可视图分析已趋于成熟,但应用于复杂系统时,单变量往往无法描述系统的全局特征.本文提出一种新的多元时间序列分析方法,将心梗和健康人的12导联心电图(electrocardiograph, ECG)信号转换为多路可视图,以每个导联为一个节点,两个导联构成可视图的层间互信息为连边权重,将其映射到复杂网络.由于不同人群的全连通网络表现为完全相同的拓扑结构,无法唯一表征不同个体的动力学特征,根据层间互信息大小重构网络,提取权重度和加权聚类系数,实现对不同人群12导联ECG信号的识别.为判断序列长度对识别效果的影响,引入多尺度权重度分布熵.由于健康受试者拥有更高的平均权重度和平均加权聚类系数,其映射网络表现为更加规则的结构、更高的复杂性和连接性,可以与心梗患者进行区分,两个参数的识别准确率均达到93.3%.     

基于复杂网络理论的多元混合空管技术保障系统网络特征分析

为提高空管技术保障系统应对突发事件的能力,本文以空管技术保障系统导航、通信、监视设备覆盖的航路结构为基础,构建系统对应的空间网络模型.提出从灵活性、鲁棒性、高效性三个方面度量空管技术保障系统网络特性,对北京、上海、广州、昆明、沈阳、兰州飞行情报区的空管技术保障系统网络的平均度、度分布、度-度相关性、聚集系数、平均路径长度、直径等进行分析.分析结果显示,各飞行情报区空管技术保障系统的平均聚集系数在0.25—0.39之间,网络聚集程度偏低;网络平均路径长度为3.4,表现出小世界网络特征;度值3时服从幂律分布,度-度分布不表现出正相关或负相关.对网络进行基于度优先的和随机的抗毁性测度,空管技术保障系统网络抗毁性较差,网络的可靠性由少数核心节点决定,应对核心节点进行目标免疫,提高网络的抗毁性.这些规律为空管技术保障系统能力提升、新建扩建提供理论依据,对降低突发事件对空管系统保障能力的影响,保障空中交通持续安全具有现实意义.     

基于STM32的多网络人防警报终端设计

传统人防警报系统一般采用单一途径触发方式,实时性和可靠性易受限制,据此设计了多种远程方式控制警报的终端,采用STM32作为主控芯片,外围集成包括移动通讯、固话、有线以太网络三种技术途径触发多种警报,三种途径的仲裁采用先到先触发的兼容方式,并给出了终端的架构及内部设计运行原理,充分发挥了不同网络在不同环境下的优势,保障了不期灾害发生时警报的实时快速预警,同时对状态信息进行反馈,经实际使用测试,系统稳定,实时,可靠性强,为破坏性灾害发生时的成功预警提供了一种可靠方法。     

A mathematical expression for air ESD current waveform using BP neural network

A curve-fitting method based on backpropagation (BP) neural network (NN) is proposed for fitting electrostatic discharge (ESD) current waveforms and giving the corresponding expressions in order to analyze the characteristics of ESD and calculate the ESD electromagnetic pulse radiation field. According to IEC61000-4-2, this method is used to fit the ideal contact current waveform of human-metal ESD to obtain the mathematical expression. The waveform parameters of the fitting curve meet the requirements of the IEC61000-4-2. By fitting the measured air ESD current waveform at 4 kV discharge, the mathematical expression is obtained. This paper proposes the mathematical expression for arbitrary curves and analyzes the factors affecting the effects of curve-fitting.     

Weighted Information and Weighted Entropic Inequalities for Qutrit States

We review the notion of weighted quantum entropy and consider the weighted quantum entropy for bipartite and noncomposite quantum systems. We extend the subadditivity condition, the inequality known for the weighted entropy information, to the case of indivisible qudit system, such as a qutrit. We discuss the new inequality for the qutrit density matrix for different weights and states, as well as the role of weighted entropy with respect to nonlinear quantum channels.     

一种简易的多重全息术

在全息照相实验光路的基础上,通过调换扩束镜与反射镜的位置,改变反射镜角度可以得到多重全息图. 实验结果与理论分析基本吻合.     

旋转光楔多重全息术

本文提出一种新颖的多重全息术,它是利用旋转光楔调制平面参考波的传播方向,实现编码参考光记录获得多重全息图.该全息图经球面波再现,获得位于同一平面内的再现多重象.文中给出了这种方法的理论分析和实验结果,两者是吻合的.     

Identifying influential waypoints in air route networks based on network agglomeration relative entropy

Air route network (ARN) is one of the most important transportation networks and the key waypoints (nodes) have significant influence on the stability and robustness of the ARN. In this paper, a network agglomeration relative entropy centrality (NAREC) method to identify influential nodes in ARNs is proposed, based on the network agglomeration and relative entropy theory. The basic topological features of the regional ARNs in Beijing, Shanghai and Guangzhou are analyzed and then the proposed method is applied to identifying influential nodes in the three networks. At last, the effectiveness of the NAREC method is demonstrated by the susceptible-infected-removed (SIR) model and the Kendall's tau coefficient. Results show that the proposed method is applicable and effective.     

Weighted Graph Colorings

We study two weighted graph coloring problems, in which one assigns q colors to the vertices of a graph such that adjacent vertices have different colors, with a vertex weighting w that either disfavors or favors a given color. We exhibit a weighted chromatic polynomial Ph(G,q,w) associated with this problem that generalizes the chromatic polynomial P(G,q). General properties of this polynomial are proved, and illustrative calculations for various families of graphs are presented. We show that the weighted chromatic polynomial is able to distinguish between certain graphs that yield the same chromatic polynomial. We give a general structural formula for Ph(G,q,w) for lattice strip graphs G with periodic longitudinal boundary conditions. The zeros of Ph(G,q,w) in the q and w planes and their accumulation sets in the limit of infinitely many vertices of G are analyzed. Finally, some related weighted graph coloring problems are mentioned.