Complex network approach for recurrence analysis of time series

We propose a novel approach for analysing time series using complex network theory. We identify the recurrence matrix (calculated from time series) with the adjacency matrix of a complex network and apply measures for the characterisation of complex networks to this recurrence matrix. By using the logistic map, we illustrate the potential of these complex network measures for the detection of dynamical transitions. Finally, we apply the proposed approach to a marine palaeo-climate record and identify the subtle changes to the climate regime.     

Properties of wealth distribution in multi-agent systems of a complex network

We present a simple model for examining the wealth distribution with agents playing evolutionary games (the Prisoners’ Dilemma and the Snowdrift Game) on complex networks. Pareto’s power law distribution of wealth (from 1897) is reproduced on a scale-free network, and the Gibbs or log-normal distribution for a low income population is reproduced on a random graph. The Pareto exponents of a scale-free network are in agreement with empirical observations. The Gini coefficient of an ER random graph shows a sudden increment with game parameters. We suggest that the social network of a high income group is scale-free, whereas it is more like a random graph for a low income group.     

Characterization of water mobility and distribution in low- and intermediate-moisture food systems

The mechanism of water uptake in low moisture cereals and cookies has been studied by NMR relaxometry and solid imaging technology implemented on a low-resolution benchtop NMR spectrometer. A comparison between classical MRI and SPRITE imaging are also presented to highlight the benefits of each technology. The spin lattice (T(1)) and spin spin (T(2)) relaxation times, the 1D and 2D SPRITE imaging, were determined on Smacks, corn flakes, chocolate chips cookies, soft caramel candies with a chocolate crème filler, and corn starch/water systems. The Smacks and corn flakes were studied based on the soaking time in milk, and the results showed that T(1) and T(2) decreased in the first 20 sec of soaking and then increased with the soaking time. For Smacks stored at different relative humidity, T(1) decreased during the first day of storage and then was relatively constant over storage time indicating that the system reached an equilibrium. 1D SPRITE profiles indicated an increase in signal intensity over storage time for cookies in 58% RH. However, the moisture uptake was insignificant indicating that the water mobility (and not the amount of water) changed due to various chemical interactions in the system (hydrogen bonding, starch retrogradation, glassy/rubbery equilibrium). The T(1) and T(2) of corn starch/water systems decreased as the concentration in starch increased and temperature increased from 30 degrees C to 60 degrees C. However, for temperatures higher than 60 degrees C, the relaxation times increased showing more mobility and flexibility of the polymer chains during gelatinization.     

Acoustic attenuation analysis of network systems by using impedance matrix method

An impedance matrix method is proposed to predict the acoustic attenuation characteristics of network systems. The system may contain several silencer modules and each module may be composed of complex components such as multiply connected tubes, portions with any-shaped cross-section and dissipative parts. The technique of substructuring is adopted and the system is divided into several substructure modules. Three strategies: boundary element method (BEM), numerical point collocation approach and numerical mode matching technique are introduced and the impedance matrix of each module may be computed by a certain appropriate methodology according to the dimensions and geometry of the substructure. Impedance matrix synthesis is employed to obtain the resultant impedance matrix and then transmission loss may be calculated. All the calculation results are verified by experimental measurements and 3-D BEM predictions.     

An exponential distribution network

A complex network with an exponential distribution p(k)proptoe^{{-frac{k}{k_{c}}}}with k _c =3.50±0.02 is introduced and found to have assortative correlation k _i ⁿⁿ =B+qk _i (q>0) from numerical simulation.     

照明光学系统照度分布的计算机模拟分析

本文阐述了照明光学系统与传统成像光学系统的区别，提出了几种计算照明光学系统照度分布的原理和方法，并给出了一个具体的利用计算机对投影照明光学系统照度分布的模拟分析方法和运算结果。     

Complex stock trading network among investors

We provide an empirical investigation aimed at uncovering the statistical properties of intricate stock trading networks based on the order flow data of a highly liquid stock (Shenzhen Development Bank) listed on Shenzhen Stock Exchange during the whole year of 2003. By reconstructing the limit order book, we can extract detailed information of each executed order for each trading day and demonstrate that the trade size distributions for different trading days exhibit power-law tails and that most of the estimated power-law exponents are well within the Lévy stable regime. Based on the records of order matching among investors, we can construct a stock trading network for each trading day, in which the investors are mapped into nodes and each transaction is translated as a direct edge from the seller to the buyer with the trade size as its weight. We find that all the trading networks comprise a giant component and have power-law degree distributions and disassortative architectures. In particular, the degrees are correlated with order sizes by a power-law function. By regarding the size of executed order as its fitness, the fitness model can reproduce the empirical power-law degree distribution.     

Complex network study of Asian Go players

Tournaments of the game of Go can be represented as a directed network in which the vertices are players and a directed link is pointing from the winner to the loser for each game. In this article, we present some interesting results for the network of Asian Go players, which is composed of 756 Go players and 9473 tournaments. It is found that the topological structure of this network displays the small-world property and a significant rich-club phenomenon where high-degree nodes are tightly interconnected. In addition, we consider the weighted version of the network, and find the weights obey power-law distributions, while the strengths follow stretched exponential distributions. The time evolution of the network structure is studied and the corresponding results discussed. The analysis of this work provides a deeper understanding for the competition network structure of Asian Go players.     

Complex power distribution analysis in plates covered with passive constrained layer damping patches

The vibration of a plate partially covered with a passive constrained layer damping (PCLD) patch is studied from an energetic point of view. The damped plate is excited by an acoustic plane wave. The study is done with a numerical two-dimensional multilayer plate model. Results of the present model are compared to those obtained with three-dimensional finite element models. It is shown that the present model gives accurate results, even for the layer's inner behavior. It is less expansive in terms of computational cost; hence, it can simulate efficiently the structure for higher frequencies. Mathematical formulas for complex mechanical power are presented, and the link with strain and kinetic energies and dissipated power is detailed. Both local and global complex power balance are established, and corresponding expressions for the discretized problem are formulated. Conservative and dissipative powers are studied for the PCLD damped plate. After a global balance analysis versus frequency, a local study has been carried out in order to quantify the relative contribution of the components of strain and stress tensors to the total strain energy and dissipated power; the individual layer's contributions is also investigated. The in-plane distributions of powers are mapped, showing the location where dissipative phenomenon occurs and where strain energy is stored. Finally, three criteria based on the previous power quantities are proposed in order to quantify the mechanical damping efficiency of the patch.     

Complex dynamics in gelling systems

We study the viscoelastic properties and the relaxation process in a gelling system by means of a minimal statistical-mechanics model. The model is based on percolation and bond fluctuation dynamics. The values for the critical exponents of the viscosity and elasticity agree with a part of the experimental observations and of the theoretical predictions. The obtained relaxation patterns well reproduce the behaviour observed in different gelling systems. Received 10 March 2002 and Received in final form 30 April 2002     

Complex network perspective on structure and function of Staphylococcus aureus metabolic network

With remarkable advances in reconstruction of genome-scale metabolic networks, uncovering complex network structure and function from these networks is becoming one of the most important topics in system biology. This work aims at studying the structure and function of Staphylococcus aureus (S. aureus) metabolic network by complex network methods. We first generated a metabolite graph from the recently reconstructed high-quality S. aureus metabolic network model. Then, based on ‘bow tie’ structure character, we explain and discuss the global structure of S. aureus metabolic network. The functional significance, global structural properties, modularity and centrality analysis of giant strong component in S. aureus metabolic networks are studied.     

Complex networks and banking systems supervision

Comprehensive and thorough supervision of all banking institutions under a Central Bank’s regulatory control has become necessary as recent banking crises show. Promptly identifying bank distress and contagion issues is of great importance to the regulators. This paper proposes a methodology that can be used additionally to the standard methods of bank supervision or the new ones proposed to be implemented. By this, one can reveal the degree of banks’ connectedness and thus identify “core” instead of just “big” banks. Core banks are central in the network in the sense that they are shown to be crucial for network supervision. Core banks can be used as gauges of bank distress over a sub-network and promptly raise a red flag so that the central bank can effectively and swiftly focus on the corresponding neighborhood of financial institutions. In this paper we demonstrate the proposed scheme using as an example the asset returns variable. The method may and should be used with alternative variables as well.     

Complex systems analysis of series of blackouts: cascading failure, critical points, and self-organization

We give an overview of a complex systems approach to large blackouts of electric power transmission systems caused by cascading failure. Instead of looking at the details of particular blackouts, we study the statistics and dynamics of series of blackouts with approximate global models. Blackout data from several countries suggest that the frequency of large blackouts is governed by a power law. The power law makes the risk of large blackouts consequential and is consistent with the power system being a complex system designed and operated near a critical point. Power system overall loading or stress relative to operating limits is a key factor affecting the risk of cascading failure. Power system blackout models and abstract models of cascading failure show critical points with power law behavior as load is increased. To explain why the power system is operated near these critical points and inspired by concepts from self-organized criticality, we suggest that power system operating margins evolve slowly to near a critical point and confirm this idea using a power system model. The slow evolution of the power system is driven by a steady increase in electric loading, economic pressures to maximize the use of the grid, and the engineering responses to blackouts that upgrade the system. Mitigation of blackout risk should account for dynamical effects in complex self-organized critical systems. For example, some methods of suppressing small blackouts could ultimately increase the risk of large blackouts.     

Complex dynamics of blackouts in power transmission systems

In order to study the complex global dynamics of a series of blackouts in power transmission systems a dynamical model of such a system has been developed. This model includes a simple representation of the dynamical evolution by incorporating the growth of power demand, the engineering response to system failures, and the upgrade of generator capacity. Two types of blackouts have been identified, each having different dynamical properties. One type of blackout involves the loss of load due to transmission lines reaching their load limits but no line outages. The second type of blackout is associated with multiple line outages. The dominance of one type of blackout over the other depends on operational conditions and the proximity of the system to one of its two critical points. The model displays characteristics such as a probability distribution of blackout sizes with power tails similar to that observed in real blackout data from North America.     

Complex scaling behavior of nonconserved self-organized critical systems

The Olami-Feder-Christensen earthquake model is often considered the prototype dissipative self-organized critical model. It is shown that the size distribution of events in this model results from a complex interplay of several different phenomena, including limited floating-point precision. Parallels between the dynamics of synchronized regions and those of a system with periodic boundary conditions are pointed out, and the asymptotic avalanche size distribution is conjectured to be dominated by avalanches of size 1, with the weight of larger avalanches converging towards zero as the system size increases.     

Complex turing patterns in non-linearly coupled systems

Recently pattern formation in layered structures, showing complicated superimposed patterns, has been modeled by coupling two Turing systems linearly, i.e., passively, such that the characteristic length scales of the independent systems are well separated. Here we propose a model of two non-linearly coupled Turing systems to study pattern formation in layered membrane-like structures, where the coupling plays an active role and changes the kinetics of the uncoupled systems. Extensive numerical simulations show that non-linear coupling generates a number of new regular patterns different from the ones observed earlier with linearly coupled systems. Some of them turn out to be superimposed patterns with different length scales, but many are not. Also, contrary to the linear coupling case, the strength of the non-linear coupling is found to play an important role in the formation and selection of patterns.