New Rural Community Construction or Retention Development:A Comparative Analysis of Rural Settlement Transition Mechanism in Plain Agriculture Area of China Based on Actor Network Theory

It is an important way to realize rural revitalization and sustainable development to guide rural settlement transition(RST)in an appropriate way.This paper uses actor network theory(ANT)to construct a theoretical framework for the study of RST.Taking two typical villages with different transition paths in rural areas of North China Plain as examples,this paper reveals the mechanism of RST and makes a comparative analysis.The results show that:1)after identifying problems and obligatory passage point,key actors recruit heterogeneous actors into the actor network by entrusting them with common interests,and realize RST under the system operation.2)Rural settlements under different transition paths have similarities in the problems to be solved,collective actions and policy factors,but there are differences in the transition process,mechanism and effect.The actor network and mechanism of RST through the path of new rural community construction are more complex and the transition effect is more thorough.In contrast,the degree of RST of retention development path is limited if there is no resource and location advantage.3)Based on the applicable conditions of different paths,this paper designs a logical framework of‘Situation-Structure-Behavior-Result’to scientifically guide the identification of RST paths under the background of rural revitalization.

RESEARCH ON KEY NODES OF WIRELESS SENSOR NETWORK BASED ON COMPLEX NETWORK THEORY

On the basis of complex network theory, the issues of key nodes in Wireless Sensor Networks (WSN) are discussed. A model expression of sub-network fault in WSN is given at first; subsequently, the concepts of average path length and clustering coefficient are introduced. Based on the two concepts, a novel attribute description of key nodes related to sub-networks is proposed. Moreover, in terms of node deployment density and transmission range, the concept of single-point key nodes and generalized key nodes of WSN are defined, and their decision theorems are investigated.

Cascading failure analysis of power flow on wind power based on complex network theory

Cascading failure is a potential threat in power systems with the scale development of wind power,especially for the large-scale grid-connected and long distance transmission wind power base in China.This introduces a complex network theory(CNT)for cascading failure analysis considering wind farm integration.A cascading failure power flow analysis model for complex power networks is established with improved network topology principles and methods.The network load and boundary conditions are determined to reflect the operational states of power systems.Three typical network evaluation indicators are used to evaluate the topology characteristics of power network before and after malfunction including connectivity level,global effective performance and percentage of load loss(PLL).The impacts of node removal,grid current tolerance capability,wind power instantaneous penetrations,and wind farm coupling points on the power grid are analyzed based on the IEEE 30 bus system.Through the simulation analysis,the occurrence mechanism and main influence factors of cascading failure are determined.Finally,corresponding defense strategies are proposed to reduce the hazards of cascading failure in power systems.

Multiple scenario simulation and optimization of an urban green infrastructure network based on complex network theory:a case study in Harbin City,China

Background:Urban green infrastructure(GI)networks play a significant role in ensuring regional ecological security;however,they are highly vulnerable to the influence of urban development,and the optimization of GI networks with better connectivity and resilience under different development scenarios has become a practical problem that urgently needs to be solved.Taking Harbin,a megacity in Northeast China,as the case study,we set five simulation scenarios by adjusting the economic growth rate and extracted the GI network in multiple scenarios by integrating the minimal cumulative resistance model and the gravity model.The low‑degree‑first(LDF)strategy of complex network theory was introduced to optimize the GI network,and the optimization effect was verified by robustness analysis.Results:The results showed that in the 5%economic growth scenario,the GI network structure was more complex,and the connectivity of the network was better,while in the other scenarios,the network structure gradually degraded with economic growth.After optimization by the LDF strategy,the average degree of the GI network in multiple scenarios increased from 2.368,2.651,2.189,1.972,and 1.847 to 2.783,3.125,2.643,2.414,and 2.322,respectively,and the GI network structure connectivity and resilience were significantly enhanced in all scenarios.Conclusions:Economic growth did not necessarily lead to degradation of the GI network;there was still room for economic development in the study area,but it was limited under existing GI conditions,and the LDF strategy was an effective method to optimize the GI network.The research results provide a new perspective for the study of GI network protection with urban economic growth and serve as a methodological reference for urban GI network optimization.

Reform of the Course System of Network Security Theory and Technology for Foreign Students in China

Theory and technology of network security is the core course of information security major,however,it still faces many challenges in the education of foreign graduate students studying in China.This paper analyzes the status quo and existing problems in the course of theory and technology of network security for foreign graduate students studying in China,the most fundamental of which is that the existing teaching materials are difficult to meet the needs of foreign graduate students.In view of the problem,this paper discusses how to improve the existing teaching materials to adapt to the teaching needs for foreign students and puts forward some new ideas and reform measures.

Call for papers Journal of Control Theory and Applications Special issue on Wireless sensor networks:from theory to practices and applications

Wireless Sensor Network （WSN） is characterized by the dense deployment of sensor nodes that continuously observe physical phenomenon. The main advantages of WSN include its low cost, rapid deployment, self-organization, and fault tolerance. WSN has received tremendous interests of various research communities,

Contextualized Analysis of Social Networks:Collaboration in Scientific Communities

Currently, the collaboration in scientific communities has been studied in order to explain, among other things, the knowledge diffusion. The quality of Graduate Programmes is often associated with the scientific collaboration. This paper discusses how scientific collaboration processes can be identified and characterized through social and complex networks. For this purpose, collaboration networks of bibliographic production, research projects, and committees of PhD theses and Masters’ dissertations by researchers from a graduate program in computational modeling were studied. The data were obtained from CAPES’ reports of the period from 2001 to 2009. Among the studied indices, centrality indices indicate the presence of prominent researchers who influence others and promptly interact with other researchers in the network. The indices of complex networks reveal the presence of the small-world (i.e. these networks are favorable to increase coordination between researchers) phenomenon and indicate a behavior of scale-free degree distribution (i.e. some researchers promote clustering more than others) for one of the studied networks.

Scale-Free Behavior in Weighted Stock Network

A weighted stock network model of stock market is presented based on the complex network theory. The model is a weighted random network, in which each vertex denotes a stock, and the weight assigned to each edge is the cross-correlation coefficient of returns. Analysis of A shares listed at Shanghai Stock Exchange finds that the influence-strength （IS） follows a power-law distribution with the exponent of 2.58. The empirical analysis results show that there are a few stocks whose price fluctuations can powerfully influence the price dynamics of other stocks in the same market. Further econometric analysis reveals that there are significant differences between the positive IS and the negative IS.

Structural and robustness properties of smart-city transportation networks

The concept of smart city gives an excellent resolution to construct and develop modern cities, and also demands infrastructure construction. How to build a safe, stable, and highly efficient public transportation system becomes an important topic in the process of city construction. In this work, we study the structural and robustness properties of transportation networks and their sub-networks. We introduce a complementary network model to study the relevance and complementarity between bus network and subway network. Our numerical results show that the mutual supplement of networks can improve the network robustness. This conclusion provides a theoretical basis for the construction of public traffic networks, and it also supports reasonable operation of managing smart cities.

Network Security Situation Evaluation Based on Modified D-S Evidence Theory

With the rapid development of global information and the increasing dependence on network for people, network security problems are becoming more and more serious. By analyzing the existing security assessment methods, we propose a network security situation evaluation system based on modified D-S evidence theory is proposed. Firstly, we give a modified D-S evidence theory to improve the reliability and rationality of the fusion result and apply the theory to correlation analysis. Secondly, the attack successful support is accurately calculated by matching internal factors with external threats. Multi-module evaluation is established to comprehensively evaluate the situation of network security. Finally we use an example of actual network datasets to validate the network security situation evaluation system. The simulation result shows that the system can not only reduce the rate of false positives and false alarms, but also effectively help analysts comprehensively to understand the situation of network security.

Influence of Coordinate Field Index on Upconversion Luminescence in Er ^(3+) Doped Tellurite Glasses

The upconversion luminescence in Er 3+ doped tellurite glasses (MKT: TeO_2-MgO-K_2O) were performed. Two green emission bands at 521 and 550 nm, corresponding to the 2H_ 11/2→4I_ 15/2 and 4S_ 3/2→4I_ 15/2 transitions, respectively, were observed. Coordinate field index, which was proposed by deducing from Pauling′s rules on the basis of Zachariasen′s random network theory, can be used to rationalize the remarkable variation in the intensity of upconversion luminescence.

The partial side information problem with additional reconstructions

We consider a quadratic Gaussian distributed lossy source coding setup with an additional constraint of identical reconstructions between the encoder and the decoder.The setup consists of two correlated Gaussian sources,wherein one of them has to be reconstructed to be within some distortion constraint and match with a corresponding reconstruction at the encoder,while the other source acts as coded side information.We study the tradeoff between the rates of two encoders for a given distortion constraint on the reconstruction.An explicit characterization of this trade-off is the main result of the paper.We also give close inner and outer bounds for the discrete memoryless version of the problem.

GGC:Gray-Granger Causality Method for Sensor Correlation Network Structure Mining on High-Speed Train

Vehicle information on high-speed trains can not only determine whether the various parts of the train are working normally,but also predict the train’s future operating status.How to obtain valuable information from massive vehicle data is a difficult point.First,we divide the vehicle data of a high-speed train into 13 subsystem datasets,according to the functions of the collection components.Then,according to the gray theory and the Granger causality test,we propose the Gray-Granger Causality(GGC)model,which can construct a vehicle information network on the basis of the correlation between the collection components.By using the complex network theory to mine vehicle information and its subsystem networks,we find that the vehicle information network and its subsystem networks have the characteristics of a scale-free network.In addition,the vehicle information network is weak against attacks,but the subsystem network is closely connected and strong against attacks.

ECOLOGICAL NETWORKS IN AGROECOSYSTEMS: APPROACHES AND APPLICATIONS

Complex network theory has been increasingly used in various research areas,including agroecosystems.This paper summarizes the basic concepts and approaches commonly used in complex network theory,and then reviews recent studies on the applications in agroecosystems of three types of common ecological networks,i.e.,food webs,pollination networks and microbial co-occurrence networks.In general,agricultural intensification is considered to be a key driver of the change of agroecosystems.It causes the simplification of landscape,leads to the loss of biocontrol through cascading effect in food webs,and also reduces the complexity and connectance of soil food webs.For pollination networks,agricultural intensification impaired the robustness by reducing specialization and enhancing generality.The microbial co-occurrence networks with high connectance and low modularity generally corresponded to high efficiency in utilization of nutrients,and high resistance to crop pathogens.This review aims to show the readers the advances of ecological networks in agroecosystems and inspire the researchers to conduct their studies in a new network perspective.

Pinning Control and Controllability of Complex Dynamical Networks

In this article, the notion of pinning control for directed networks of dynamical systems is introduced, where the nodes could be either single-input single-output （SISO） or multi-input multi-output （MIMO） dynamical systems, and could be non-identical and nonlinear in general but will be specified to be identical linear time-invariant （LTI） systems here in the study of network controllability. Both state and structural controllability problems will be discussed, illustrating how the network topology, node-system dynamics, external control inputs and inner dynamical interactions altogether affect the controllability of a general complex network of LTI systems, with necessary and sufficient conditions presented for both SISO and MIMO settings. To that end, the controllability of a special temporally switching directed network of linear time-varying （LTV） node systems will be addressed, leaving some more general networks and challenging issues to the end for research outlook.

Geodesic Vulnerability Approach for Identification of Critical Buses in Power Systems

One of the most critical issues in the evaluation of power systems is the identification of critical buses. For this purpose, this paper proposes a new methodology that evaluates the substitution of the power flow technique by the geodesic vulnerability index to identify critical nodes in power systems.Both methods are applied comparatively to demonstrate the scope of the proposed approach. The applicability of the methodology is illustrated using the IEEE 118-bus test system as a case study. To identify the critical components, a node is initially disconnected, and the performance of the resulting topology is evaluated in the face of simulations for multiple cascading faults. Cascading events are simulated by randomly removing assets on a system that continually changes its structure with the elimination of each component. Thus, the classification of the critical nodes is determined by evaluating the resulting performance of 118 different topologies and calculating the damaged area for each of the disintegration curves of cascading failures. In summary, the feasibility and suitability of complex network theory are justified to identify critical nodes in power systems.

A New Algorithm of Harmonious Decompositionof Linear Graph

This paper gives a new algorithm of harmonious decomposition of linear graph. It bases onthe degree of cconected linear graph. Comparing with the other existed algorithms, it can save twothirds of computation time. And it is more direct and zntuitive thon the other algorithms. It is more con-venient and quick to get the topofogical degrees of freedonz of linear graph- So it will have wide use inthe hybrid analyszs of electrical circuits. In the end of this paper we discuss an appltcalion example ofthe algorithm.

Extract Rules by Using Rough Set and Knowledge-Based NN

In this paper, rough set theory is used to extract roughly-correct inference rules from information systems. Based on this idea, the learning algorithm ERCR is presented. In order to refine the learned roughly-correct inference rules, the knowledge-based neural network is used. The method presented here sufficiently combines the advanages of rough set theory and neural network.