Showing papers in "Physica A-statistical Mechanics and Its Applications in 2009"
TL;DR: This paper proposes an algorithm (EAGLE) to detect both the overlapping and hierarchical properties of complex community structure together and deals with the set of maximal cliques and adopts an agglomerative framework.
Abstract: Clustering and community structure is crucial for many network systems and the related dynamic processes. It has been shown that communities are usually overlapping and hierarchical. However, previous methods investigate these two properties of community structure separately. This paper proposes an algorithm (EAGLE) to detect both the overlapping and hierarchical properties of complex community structure together. This algorithm deals with the set of maximal cliques and adopts an agglomerative framework. The quality function of modularity is extended to evaluate the goodness of a cover. The examples of application to real world networks give excellent results.
679 citations
TL;DR: In this article, a classification of variable-order fractional diffusion models based on the possible physical origins which prompt the variable order is presented. But the characteristics of the new models change with time, space, concentration or other independent quantities.
Abstract: The purpose of this paper is to offer a unified discussion of variable-order differential operators in anomalous diffusion modeling. The characteristics of the new models, in contrast to constant-order fractional diffusion models, change with time, space, concentration or other independent quantities. We introduced a classification of variable-order fractional diffusion models based on the possible physical origins which prompt the variable-order. Some potential applications of the variable-order fractional diffusion models are also discussed.
479 citations
TL;DR: This paper uses a threshold method to construct China’s stock correlation network and then studies its structural properties and topological stability, finding that it displays a topological robustness against random vertex failures, but it is also fragile to intentional attacks.
Abstract: In many practical important cases, a massive dataset can be represented as a very large network with certain attributes associated with its vertices and edges. Stock markets generate huge amounts of data, which can be use for constructing the network reflecting the market’s behavior. In this paper, we use a threshold method to construct China’s stock correlation network and then study the network’s structural properties and topological stability. We conduct a statistical analysis of this network and show that it follows a power-law model. We also detect components, cliques and independent sets in this network. These analyses allows one to apply a new data mining technique of classifying financial instruments based on stock price data, which provides a deeper insight into the internal structure of the stock market. Moreover, we test the topological stability of this network and find that it displays a topological robustness against random vertex failures, but it is also fragile to intentional attacks. Such a network stability property would be also useful for portfolio investment and risk management.
289 citations
TL;DR: In this article, a leader-following consensus problem for a multi-agent system with a varying-velocity leader and time-varying delays is studied, where the interaction graph among the followers is switching and balanced.
Abstract: In this paper, we study a leader-following consensus problem for a multi-agent system with a varying-velocity leader and time-varying delays. Here, the interaction graph among the followers is switching and balanced. At first, we propose a neighbor-based rule for every agent to track a leader whose states may not be measured. In addition, we consider the convergence analysis of this multi-agent system under two different conditions: the connection between the followers and the leader is time-invariant and time-varying. For the first case, a novel decomposition method is introduced to facilitate the convergence analysis. By utilizing a Lyapunov–Krasovskii functional, we obtain sufficient conditions for uniformly ultimately boundedness of the tracking errors. Finally, two simulations are also presented to illustrate our theoretical results.
275 citations
TL;DR: In this article, the authors present an analysis of oil prices in USD and in other major currencies that diagnoses unsustainable faster-than-exponential behavior and supports the hypothesis that the recent oil price run-up was amplified by speculative behavior of the type found during a bubble-like expansion.
Abstract: We present an analysis of oil prices in USD and in other major currencies that diagnoses unsustainable faster-than-exponential behavior. This supports the hypothesis that the recent oil price run-up was amplified by speculative behavior of the type found during a bubble-like expansion. We also attempt to unravel the information hidden in the oil supply-demand data reported by two leading agencies, the US Energy Information Administration (EIA) and the International Energy Agency (IEA). We suggest that the found increasing discrepancy between the EIA and IEA figures provides a measure of the estimation errors. Rather than a clear transition to a supply restricted regime, we interpret the discrepancy between the IEA and EIA as a signature of uncertainty, and there is no better fuel than uncertainty to promote speculation! Our post-crash analysis confirms that the oil peak in July 2008 occurred within the expected 80% confidence interval predicted with data available in our pre-crash analysis.
241 citations
TL;DR: The Social Force Model presents some limitations when describing the experimental data of pedestrian flows in normal conditions — in particular the specific flow rates for different door widths and the fundamental diagram.
Abstract: The Social Force Model presents some limitations when describing the experimental data of pedestrian flows in normal conditions — in particular the specific flow rates for different door widths and the fundamental diagram. In the present work we propose a modification of this model that consists of a self-stopping mechanism to prevent a simulated pedestrian from continuously pushing over other pedestrians. With this simple change, the modified model is able to reproduce the specific flow rates and fundamental diagram of pedestrian flows for normal conditions, as reported in the literature.
232 citations
TL;DR: In this article, the authors introduce two new quantifiers for the stock market inefficiency: the number of forbidden patterns and the normalized permutation entropy, which are model-independent measures and have more general applicability.
Abstract: In this paper we introduce two new quantifiers for the stock market inefficiency: the number of forbidden patterns and the normalized permutation entropy. They are model-independent measures, thus they have more general applicability. We find robust evidence that degree of market inefficiency is positively correlated with the number of forbidden patterns and negatively correlated with the permutation entropy. Our empirical results suggest that these two physical tools are useful to discriminate the stage of stock market development and can be easily implemented.
224 citations
TL;DR: It is found that WMN is a small-world network with power law behavior, and the hierarchy structure and rich-club phenomenon in the network is revealed.
Abstract: 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.
203 citations
TL;DR: In this paper, the steady two-dimensional MHD stagnation point flow towards a stretching sheet with variable surface temperature is investigated and the effects of the governing parameters on the flow field and heat transfer characteristics are obtained and discussed.
Abstract: The steady two-dimensional MHD stagnation point flow towards a stretching sheet with variable surface temperature is investigated. The governing system of partial differential equations are transformed into ordinary differential equations, which are then solved numerically using a finite-difference scheme known as the Keller-box method. The effects of the governing parameters on the flow field and heat transfer characteristics are obtained and discussed. It is found that the heat transfer rate at the surface increases with the magnetic parameter when the free stream velocity exceeds the stretching velocity, i.e. e > 1 , and the opposite is observed when e 1 .
188 citations
TL;DR: Wang et al. as mentioned in this paper analyzed the Shanghai stock price index daily returns using MF-DFA method and found that there are two different sources for multifractality in time series, namely, fat-tailed probability distributions and non-linear temporal correlations.
Abstract: Analyzing the Shanghai stock price index daily returns using MF-DFA method, it is found that there are two different types of sources for multifractality in time series, namely, fat-tailed probability distributions and non-linear temporal correlations. Based on that, a sliding window of 240 frequency data in 5 trading days was used to study stock price index fluctuation. It is found that when the stock price index fluctuates sharply, a strong variability is clearly characterized by the generalized Hurst exponents h ( q ) . Therefore, two measures, Δ h and σ , based on generalized Hurst exponents were proposed to compare financial risks before and after Price Limits and Reform of Non-tradable Shares. The empirical results verify the validity of the measures, and this has led to a better understanding of complex stock markets.
178 citations
TL;DR: In this article, the microscopic characteristics of pedestrian dynamics, including velocity, density, and lateral oscillation, as well as their interrelations, were obtained and analyzed using a digital image processing method based on a mean shift algorithm.
Abstract: In this study, experiments of single-file pedestrian movement were conducted and the movement parameters of pedestrians were extracted with a digital image processing method based on a mean-shift algorithm The microscopic characteristics of pedestrian dynamics, including velocity, density, and lateral oscillation, as well as their interrelations, were obtained and analyzed Firstly, we studied the lateral oscillation phenomena of pedestrian movement The result indicates that the trajectory of pedestrians presents a wavy form and the amplitude of the oscillation remains about 55 cm when the pedestrians move with free walking velocity, which is the velocity when there is no obvious interaction between sequential pedestrians; but when the movement velocity decreases to 027 m/s, the amplitude of oscillation increases to 13 cm With increasing density, the velocity decreases and the amplitude of oscillation presents a linear increase trend The increasing oscillation amplitude widens the occupation area of a pedestrian with low velocity, so as to make the moving efficiency even worse Secondly, we studied the frequency of the oscillation; the result indicates that the frequency remains at 2 Hz when pedestrians move with a free walking velocity, but it presents a similar linear decrease trend when the velocity changes to a lower value The decrease of oscillation frequency is also a negative feedback to the moving efficiency Thirdly, it is found that with the increase of crowd density, the time interval between two sequential pedestrians increases, though the space gap between them decreases The quantitative relation between time interval and crowd density is obtained The study in this paper provides fundamental data and a basic method for understanding pedestrian dynamics, developing and validating evacuation models The results are also expected to be useful for evacuation design
TL;DR: In this article, a motility mechanism based on a simple exclusion process is considered, where the movement of discrete agents on a lattice is either unbiased (symmetric) or biased (asymmetric).
Abstract: A motility mechanism based on a simple exclusion process, where the movement of discrete agents on a lattice is either unbiased (symmetric) or biased (asymmetric) is considered. Estimates of diffusivities from tracking data do not describe the population-level response of the system. This mismatch between the individual-level and population-level behaviour can be resolved by averaging the individual-level mechanism in terms of an expected site occupancy. New insight into simple exclusion processes is obtained by representing the system as a series of interacting subpopulations. This formalism leads to a system of nonlinear advection–diffusion equations which can be interpreted in terms of the agent fluxes. These interactions have consequences for both agent-based modelling and continuum modelling in cell biology, such as tracking subpopulations of cells within a total cell population.
TL;DR: Comparison between the experimental and simulation results shows that the modified cellular automaton evacuation model can reproduce the experiment well, and the improvement of the CA model is useful for further study.
Abstract: An existing cellular automaton evacuation model is modified to simulate an evacuation experiment conducted in a classroom with obstacles. In the modified model, the impact of the occupant density around exits on human behavior in evacuation is considered. The simulation and experimental results prove that this improvement makes sense, because besides the spatial distance to exits, people may also choose the exit according to the occupant density around exits. The distribution of individual evacuation times as a function of initial positions and the dynamics of the evacuation process are studied. Comparison between the experimental and simulation results shows that the model can reproduce the experiment well. The improvement of the CA model is useful for further study.
TL;DR: In this paper, a visibility graph is used to obtain reliable values of the Hurst exponents of the series of the exchange rate of EURO to Japanese Yen, and it is found that the series convert into scale-free and hierarchically structured networks.
Abstract: By means of a visibility graph, we investigate six important exchange rate series. It is found that the series convert into scale-free and hierarchically structured networks. The relationship between the scaling exponents of the degree distributions and the Hurst exponents obeys the analytical prediction for fractal Brownian motions. The visibility graph can be used to obtain reliable values of Hurst exponents of the series. The characteristics are explained by using the multifractal structures of the series. The exchange rate of EURO to Japanese Yen is widely used to evaluate risk and to estimate trends in speculative investments. Interestingly, the hierarchies of the visibility graphs for the exchange rate series of these two currencies are significantly weak compared with that of the other series.
TL;DR: This work proposes a new communicability betweenness measure that allows information to pass through all possible routes, but introduces a scaling so that longer walks carry less importance, and shows that it recovers meaningful biological information from a protein–protein interaction network.
Abstract: Betweenness measures provide quantitative tools to pick out fine details from the massive amount of interaction data that is available from large complex networks. They allow us to study the extent to which a node takes part when information is passed around the network. Nodes with high betweenness may be regarded as key players that have a highly active role. At one extreme, betweenness has been defined by considering information passing only through the shortest paths between pairs of nodes. At the other extreme, an alternative type of betweenness has been defined by considering all possible walks of any length. In this work, we propose a betweenness measure that lies between these two opposing viewpoints. We allow information to pass through all possible routes, but introduce a scaling so that longer walks carry less importance. This new definition shares a similar philosophy to that of communicability for pairs of nodes in a network, which was introduced by Estrada and Hatano [E. Estrada, N. Hatano, Phys. Rev. E 77 (2008) 036111]. Having defined this new communicability betweenness measure, we show that it can be characterized neatly in terms of the exponential of the adjacency matrix. We also show that this measure is closely related to a Frechet derivative of the matrix exponential. This allows us to conclude that it also describes network sensitivity when the edges of a given node are subject to infinitesimally small perturbations. Using illustrative synthetic and real life networks, we show that the new betweenness measure behaves differently to existing versions, and in particular we show that it recovers meaningful biological information from a protein–protein interaction network.
TL;DR: In this paper, the authors proposed a new node centrality measure, the lobby index, inspired by Hirsch's h-index, which is shown to have power tail with exponent α (α + 1 ).
Abstract: We propose a new node centrality measure in networks, the lobby index, which is inspired by Hirsch’s h -index. It is shown that in scale-free networks with exponent α the distribution of the l -index has power tail with exponent α ( α + 1 ) . Properties of the l -index and extensions are discussed.
TL;DR: The results indicate that simple empirical equations, commonly used in practice, are unable to describe the permeability functionalities over a broad range of porous media configurations.
Abstract: A volume averaging approach is used to estimate the porous media permeability. Contrary to traditional methods that rely on solving the Navier–Stokes equations for laminar flow, this approach has the advantage that it does not require the specification of some physical conditions and parameters (pressure drop and viscosity). Numerical results on synthetic models of porous media showed that (i) the local porous medium configuration has an important effect on the permeability value, and (ii) the Carman–Kozeny equation cannot describe the permeability behavior as a function of porosity and characteristic lengths. In turn, our results indicate that simple empirical equations, commonly used in practice, are unable to describe the permeability functionalities over a broad range of porous media configurations.
TL;DR: In this article, the stability conditions of the disease-free equilibrium of the associated stochastic SIRS system with or without distributed time delay influenced by random perturbations are presented.
Abstract: Epidemiological models with bilinear incidence rate λ S I usually have an asymptotically stable trivial equilibrium corresponding to the disease-free state, or an asymptotically stable non-trivial equilibrium (i.e. interior equilibrium) corresponding to the endemic state. In this paper, we consider an epidemiological model, which is an SIRS model with or without distributed time delay influenced by random perturbations. We present the stability conditions of the disease-free equilibrium of the associated stochastic SIRS system.
TL;DR: It is found that the cooperator frequency is greatly influenced by the initial strategy of hub nodes when α>0.
Abstract: Considering the heterogeneity of individuals’ influence in the real world, we introduce a preferential selection mechanism to evolutionary games (the Prisoner’s Dilemma Game and the Snowdrift Game) on scale-free networks and focus on the cooperative behavior of the system. In every step, each agent chooses an individual from all its neighbors with a probability proportional to k α indicating the influence of the neighbor, where k is the degree. Simulation results show that the cooperation level has a non-trivial dependence on α . To understand the effect of preferential selection mechanism on the evolution of the system, we investigate the time series of the cooperator frequency in detail. It is found that the cooperator frequency is greatly influenced by the initial strategy of hub nodes when α > 0 . This observation is confirmed by investigating the system behavior when some hub nodes’ strategies are fixed.
TL;DR: In this paper, the authors investigated the properties of the networks formed by the cross-correlations of the daily and weekly index changes of 143 stock market indices from 59 different countries.
Abstract: We report the results of an investigation of the properties of the networks formed by the cross-correlations of the daily and weekly index changes of 143 stock market indices from 59 different countries. Analysis of the asset graphs, minimum spanning trees (MST) and planar maximally filtered graphs (PMFG) of the afermentioned networks confirms that globalization has been increasing in recent years. North American and European markets are observed to be much more strongly connected among themselves compared to the integration with the other geographical regions. Surprisingly, the integration of East Asian markets among themselves as well as to the Western markets is found to be rather weak. MST and PMFG of both daily and weekly return correlations indicates that the clustering of the indices is mostly geographical. The French fsbf250 index is found to be most important node of the MST and PMFG based on several graph centrality measures.
TL;DR: An unconditionally gradient stable scheme for solving the Allen–Cahn equation representing a model for anti-phase domain coarsening in a binary mixture and the pointwise boundedness of the numerical solution is shown.
Abstract: We consider an unconditionally gradient stable scheme for solving the Allen–Cahn equation representing a model for anti-phase domain coarsening in a binary mixture. The continuous problem has a decreasing total energy. We show the same property for the corresponding discrete problem by using eigenvalues of the Hessian matrix of the energy functional. We also show the pointwise boundedness of the numerical solution for the Allen–Cahn equation. We describe various numerical experiments we performed to study properties of the Allen–Cahn equation.
TL;DR: A typical power network is depicted as a weighted graph based on electrical topology by introducing its bus admittance matrix, which embodies the important characteristics of power networks in a much more realistic structure.
Abstract: Electric power networks have been studied as a typical example of real-world complex networks. Traditional models for structural vulnerability analysis appear to be all based on physical topological structure. In this paper, we depict a typical power network as a weighted graph based on electrical topology by introducing its bus admittance matrix, which embodies the important characteristics of power networks in a much more realistic structure. Furthermore, the numerical simulation for both the traditional dynamical model and the proposed electrical topological model are investigated based on the IEEE 300 bus system respectively. The comparison demonstrates that the improved model is more precise and highly efficient for the analysis of structural vulnerability of power networks.
TL;DR: In this paper, the authors analyzed dependencies in commodity markets, investigating correlations of future contracts for commodities over the period 1998-2007, and constructed a minimal spanning tree based on the correlation matrix, providing evidence for sector clusterization of investigated contracts.
Abstract: In this paper we analyzed dependencies in commodity markets, investigating correlations of future contracts for commodities over the period 1998.09.01–2007.12.14. We constructed a minimal spanning tree based on the correlation matrix. The tree provides evidence for sector clusterization of investigated contracts. We also studied dynamical properties of commodity dependencies. It turned out that the market was constantly getting more correlated within the investigated period, although the increase of correlation was distributed non-uniformly among all contracts, and depended on contracts branches.
TL;DR: This work analyzes and compares Wavelet Leaders with the well known Multifractal Detrended Fluctuation Analysis, a comprehensible and well adapted method for natural and weakly stationary signals.
Abstract: Wavelet Leaders is a novel alternative based on wavelet analysis for estimating the Multifractal Spectrum It was proposed by Jaffard and co-workers improving the usual wavelet methods In this work, we analyze and compare it with the well known Multifractal Detrended Fluctuation Analysis The latter is a comprehensible and well adapted method for natural and weakly stationary signals Alternatively, Wavelet Leaders exploits the wavelet self-similarity structures combined with the Multiresolution Analysis scheme We give a brief introduction on the multifractal formalism and the particular implementation of the above methods and we compare their effectiveness We expose several cases: Cantor measures, Binomial Multiplicative Cascades and also natural series from a tonic–clonic epileptic seizure We analyze the results and extract the conclusions
TL;DR: In this paper, the authors discuss the incorporation of dynamic subgrid scale (SGS) models in the lattice Boltzmann method (LBM) for large-eddy simulation (LES) of turbulent flows.
Abstract: In this paper, we discuss the incorporation of dynamic subgrid scale (SGS) models in the lattice-Boltzmann method (LBM) for large-eddy simulation (LES) of turbulent flows. The use of a dynamic procedure, which involves sampling or test-filtering of super-grid turbulence dynamics and subsequent use of scale-invariance for two levels, circumvents the need for empiricism in determining the magnitude of the model coefficient of the SGS models. We employ the multiple relaxation times (MRT) formulation of LBM with a forcing term, which has improved physical fidelity and numerical stability achieved by proper separation of relaxation time scales of hydrodynamic and non-hydrodynamic modes, for simulation of the grid-filtered dynamics of large-eddies. The dynamic procedure is illustrated for use with the common Smagorinsky eddy-viscosity SGS model, and incorporated in the LBM kinetic approach through effective relaxation time scales. The strain rate tensor in the SGS model is locally computed by means of non-equilibrium moments of the MRT-LBM. We also discuss proper sampling techniques or test-filters that facilitate implementation of dynamic models in the LBM. For accommodating variable resolutions, we employ conservative, locally refined grids in this framework. As examples, we consider the canonical anisotropic and inhomogeneous turbulent flow problem, i.e. fully-developed turbulent channel flow at two different shear Reynolds numbers R e ∗ of 180 and 395. The approach is able to automatically and self-consistently compute the values of the Smagorinsky coefficient, C S . In particular, the computed value in the outer or bulk flow region, where turbulence is generally more isotropic, is about 0.155 (or the model coefficient C = C S 2 = 0.024 ) which is in good agreement with prior data. It is also shown that the model coefficient becomes smaller and approaches towards zero near walls, reflecting the dampening of turbulent length scales near walls. The computed turbulence statistics at these Reynolds numbers are also in good agreement with prior data. The paper also discusses a procedure for incorporation of more general scale-similarity based SGS stress models.
TL;DR: In this article, a method based on detrended fluctuation analysis is proposed to investigate asymmetric correlations in nonstationary time series, and different scaling properties are found if signal trending is either positive or negative.
Abstract: Here we propose a method, based on detrended fluctuation analysis, to investigate asymmetric correlations in nonstationary time series. The aim is to show that, for a certain range of time scales, different scaling properties are found if signal trending is either positive and negative. We illustrate the method by selected examples from physics and finance.
TL;DR: In this paper, a lattice Boltzmann model with an amending function is proposed for the generalized Kuramoto-Sivashinsky equation that has the form u t + u u x + α u x x + β u xx x + γ u x X x x = 0.
Abstract: In this paper, a lattice Boltzmann model with an amending function is proposed for the generalized Kuramoto–Sivashinsky equation that has the form u t + u u x + α u x x + β u x x x + γ u x x x x = 0 With the Chapman–Enskog expansion, the governing evolution equation is recovered correctly from the continuous Boltzmann equation It is found that the numerical results agree well with the analytical solutions
TL;DR: In this article, the quantum potential is shown to result from the presence of a subtle thermal vacuum energy distributed across the whole domain of an experimental setup, and its form is demonstrated to be exactly identical to the heat distribution derived from the defining equation for classical diffusion wave fields.
Abstract: In a new thermodynamic interpretation, the quantum potential is shown to result from the presence of a subtle thermal vacuum energy distributed across the whole domain of an experimental setup. Explicitly, its form is demonstrated to be exactly identical to the heat distribution derived from the defining equation for classical diffusion wave fields. For a single free particle path, this thermal energy does not significantly affect particle motion. However, in between different paths, or at interfaces, the accumulation–depletion law for diffusion waves provides an immediate new understanding of the quantum potential’s main features.
TL;DR: The brain is probably the most interesting example of a complex network having 1 / f variability as determined through the analysis of EEG time series and magnetoencephalogram recordings as discussed by the authors.
Abstract: The brain is probably the most interesting example of a complex network having 1 / f variability as determined through the analysis of EEG time series and magnetoencephalogram recordings Herein we develop a theory of 1 / f noise of human cognition to explain the recent experimental observations that increasing the difficultly of cognitive tasks accelerates the transition from observed 1 / f noise to white noise in decision-making time series
TL;DR: In this paper, competition between languages or cultural traits diffusing in the same geographical area is studied combining the model of Abrams and Strogatz with a model of human dispersal on an inhomogeneous substrate.
Abstract: Competition between languages or cultural traits diffusing in the same geographical area is studied combining the model of Abrams and Strogatz with a model of human dispersal on an inhomogeneous substrate. Also, the effect of population growth is discussed. It is shown through numerical simulations that the final configuration of the languages can be strongly affected by geographical and historical factors. These factors are not related to the dynamics of culture transmission, but rather to initial population distributions as well as geographical boundaries and inhomogeneities, which modulate the diffusion process.