Jinghua Xiao

Evidence for a bimodal distribution in human communication

Interacting human activities underlie the patterns of many social, technological, and economic phenomena. Here we present clear empirical evidence from Short Message correspondence that observed human actions are the result of the interplay of three basic ingredients: Poisson initiation of tasks and decision making for task execution in individual humans as well as interaction among individuals. This interplay leads to new types of interevent time distribution, neither completely Poisson nor power-law, but a bimodal combination of them. We show that the events can be separated into independent bursts which are generated by frequent mutual interactions in short times following random initiations of communications in longer times by the individuals. We introduce a minimal model of two interacting priority queues incorporating the three basic ingredients which fits well the distributions using the parameters extracted from the empirical data. The model can also embrace a range of realistic social interacting systems such as e-mail and letter communications when taking the time scale of processing into account. Our findings provide insight into various human activities both at the individual and network level. Our analysis and modeling of bimodal activity in human communication from the viewpoint of the interplay between processes of different time scales is likely to shed light on bimodal phenomena in other complex systems, such as interevent times in earthquakes, rainfall, forest fire, and economic systems, etc.

Synchronization control of memristor-based recurrent neural networks with perturbations.

In this paper, the synchronization control of memristor-based recurrent neural networks with impulsive perturbations or boundary perturbations is studied. We find that the memristive connection weights have a certain relationship with the stability of the system. Some criteria are obtained to guarantee that memristive neural networks have strong noise tolerance capability. Two kinds of controllers are designed so that the memristive neural networks with perturbations can converge to the equilibrium points, which evoke humans memory patterns. The analysis in this paper employs the differential inclusions theory and the Lyapunov functional method. Numerical examples are given to show the effectiveness of our results.

Data clustering using bacterial foraging optimization

Clustering divides data into meaningful or useful groups (clusters) without any prior knowledge. It is a key technique in data mining and has become an important issue in many fields. This article presents a new clustering algorithm based on the mechanism analysis of Bacterial Foraging (BF). It is an optimization methodology for clustering problem in which a group of bacteria forage to converge to certain positions as final cluster centers by minimizing the fitness function. The quality of this approach is evaluated on several well-known benchmark data sets. Compared with the popular clustering method named k-means algorithm, ACO-based algorithm and the PSO-based clustering technique, experimental results show that the proposed algorithm is an effective clustering technique and can be used to handle data sets with various cluster sizes, densities and multiple dimensions.

The robustness of interdependent transportation networks under targeted attack

The modern world is built on the robustness of interdependent infrastructures, which can be characterized as complex networks. Recently, a framework for the analysis of interdependent networks has been developed to explain the mechanism of robustness in interdependent networks. Here, we extend this interdependent network model by considering flows in the networks, and we study the systems robustness under different attack strategies. In our model, nodes may fail because of either overload or loss of interdependency. Considering the interaction between these two failure mechanisms, it is shown that interdependent scale-free networks show extreme vulnerability. The robustness of interdependent scale-free networks is found in our simulations to be much smaller than that of the single scale-free networks or the interdependent scale-free networks without flows.

Applying Semigroup Property of Enhanced Chebyshev Polynomials to Anonymous Authentication Protocol

We apply semigroup property of enhanced Chebyshev polynomials to present an anonymous authentication protocol. This paper aims at improving security and reducing computational and storage overhead. The proposed scheme not only has much lower computational complexity and cost in the initialization phase but also allows the users to choose their passwords freely. Moreover, it can provide revocation of lost or stolen smart card, which can resist man-in-the-middle attack and off-line dictionary attack together with various known attacks.

Robustness of Interrelated Traffic Networks to Cascading Failures

The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks S and B composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (BA) and Erdős-Rényi graphs (ER) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network αS > α0.

Effects of frequency-degree correlation on synchronization transition in scale-free networks

Explosive synchronization in the scale-free network with a positive frequency-degree correlation has been reported recently (GOMEZ G. J. et al., Phys. Rev. Lett., 106 (2011) 128701). In this article, we generalize this study and find that the explosive synchronization is replaced by a kind of hierarchical synchronization if the microscopic correlation between the frequency and the interacting topology of the network becomes negative. A star network model is set to prove this novel behavior. We also find that the degree assortativity has significant influence on the explosive synchronization but slight impact on the hierarchical synchronization. These findings are meaningful for revealing unusual effects of correlations between dynamics and structure of complex networks. Copyright (c) EPLA, 2013

Anti-synchronization Control of Memristive Neural Networks with Multiple Proportional Delays

This paper investigates anti-synchronization control of memristive neural networks with multiple proportional delays. Here, we first study the proportional delay, which is a kind of unbounded time-varying delay in the memristive neural networks, by using the differential inclusion theory to handle the memristive neural networks with discontinuous right-hand side. In particular, several new criteria ensuring anti-synchronization of memristive neural networks with multiple proportional delays are presented. In addition, the new proposed criteria are easy to verify and less conservative than earlier publications about anti-synchronization control of memristive neural networks. Finally, two numerical examples are given to show the effectiveness of our results.

Anti-phase synchronization of two coupled mechanical metronomes

This paper mainly investigates the anti-phase synchronization of two coupled mechanical metronomes not only by means of numerical simulations, but also by experimental tests. It is found that the attractor basin of anti-phase synchronization enlarges as the rolling friction increases. Furthermore, this paper studies the relationship between different initial conditions and synchronization types. The impacts of rolling friction on in-phase and anti-phase synchronization times are also discovered. Finally, in-phase and anti-phase synchronization conditions of non-identical metronomes are discussed. These results indicate the potential complexity of the dynamics of coupled metronomes.

Finite-Time Function Projective Synchronization in Complex Multi-links Networks with Time-Varying Delay

This paper investigates the problem of finite-time function projective synchronization in complex multi-links networks with time-varying delay. A nonlinear feedback controller is designed to achieve finite-time function projective synchronization. Some novel and useful finite-time function projective synchronization criteria are derived based on finite-time stability theory. And another controller is designed to ensure function projective synchronization of complex multi-links networks with time-varying delay. Finally, illustrative examples are given to show the feasibility of the proposed method.