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.

Felski’s Literary Sociological Thought From the Perspective of Actor-Network Theory

The relationship between literature and society has been a subject of continuous exploration since the inception of literature itself.On the one hand,from Plato’s theory of mimesis onward,literature has consistently been viewed as a representation of social reality,positioning literature as subordinate to society.On the other hand,with the rise of structuralism and the New Criticism,certain schools of thought have focused exclusively on literature itself,deliberately overlooking the complex connections between literature and society.The growing tension between these two perspectives has increasingly placed contemporary literary studies in a polarized state,leading to a crisis in the legitimacy of literary scholarship.In response to this,Rita Felski’s exploration of the uses of literature embodies a new literary sociology that offers a way out of the current impasse in literary studies.

Venture Capital Syndication under Social Network Theory:Literature Review and Prospect

As an important channel for start-ups to obtain R&D funds and external knowledge and information resources,and as one of the key methods for investment institutions to leverage scale and synergy effects to enhance investment returns,venture capital syndication holds significant research value in the field of venture capital.This paper reviews the literature,summarizing the motivations behind the formation of joint investment networks,the conceptual characteristics of the three core theories of social network theory,and the empirical research on venture capital syndication within the framework of social network theory.It also highlights the existing research results,identifies gaps,and anticipates future research directions.

Aviation Accident Causation Analysis Based on Complex Network Theory

Accident causation analysis is of great importance for accident prevention.In order to improve the aviation safety,a new analysis method of aviation accident causation based on complex network theory is proposed in this paper.Through selecting 257 accident investigation reports,45 causative factors and nine accident types are obtained by the three-level coding process of the grounded theory,and the interaction of these factors is analyzed based on the“2-4”model.Accordingly,the aviation accident causation network is constructed based on complex network theory which has scale-free characteristics and small-world properties,the characteristics of causative factors are analyzed by the topology of the network,and the key causative factors of the accidents are identified by the technique for order of preference by similarity to ideal solution(TOPSIS)method.The comparison results show that the method proposed in this paper has the advantages of independent of expert experience,quantitative analysis of accident causative factors and statistical analysis of a lot of accident data,and it has better applicability and advancement.

Dependency-based importance measures of components in mechatronic systems with complex network theory

To compensate for the limitations of previous studies,a complex network-based method is developed for determining importance measures,which combines the functional roles of the components of a mechatronic system and their topological positions.First,the dependencies among the components are well-represented and well-calculated.Second,a mechatronic system is modeled as a weighted and directional functional dependency network(FDN),in which the node weights are determined by the functional roles of components in the system and their topological positions in the complex network whereas the edge weights are represented by dependency strengths.Third,given that the PageRank algorithm cannot calculate the dependency strengths among components,an improved PageRank importance measure(IPIM)algorithm is proposed,which combines the node weights and edge weights of complex networks.IPIM also considers the importance of neighboring components.Finally,a case study is conducted to investigate the accuracy of the proposed method.Results show that the method can effectively determine the importance measures of components.

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.

The Evaluation of the Integrated Risk for the South-to-North Water Transfer Project Using the Bayesian Network Theory

南水北调工程是目前我国最大的调水工程。随着工程的建设和运行,由不确定性问题引起的风险问题越来越受到关注,工程运行的风险分析也摆在管理者的面前,如何识别、评估、降低和控制风险的发生成为南水北调工程运行中的一个重要问题。本文首次将贝叶斯网络理论引入到南水北调综合风险分析中,选取东线工程宝应抽水泵站为研究对象,利用贝叶斯网络推理功能得出宝应站运行综合风险发生的概率为0.025%,风险发生的等级为"较低"。利用情景分析的方法,得出在影响综合风险的因素中,泵站的管理维护状况条件改变时,综合风险变化最大,因此需要予以重点关注。

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.

A unified dynamic scaling property for the unified hybrid network theory framework

In this article, we present a new type of unified dynamic scaling property for synchronizability, which can describe the scaling relationship between dynamic synehronizability and four hybrid ratios under the unified hybrid network theory framework （UHNTF）. Our theory results can not only be applied to judge and analyze dynamic synehronizability for most of complex networks associated with the UHNTF, but also we can flexibly adjust and design different hybrid ratios and sealing exponent to meet actual requirement for the dynanfic characteristics of the UHNTF.

Criterion of Quantum Entanglement and the Covariance Correlation Tensor in the Theory of Quantum Network

This article discusses the covariance correlation tensor (CCT) in quantum network theory for four Bell bases in detail. Furthermore, it gives the expression of the density operator in terms of CCT for a quantum network of three nodes, thus gives the criterion of entanglement for this case, i.e. the conditions of complete separability and partial separability for a given quantum state of three bodies. Finally it discusses the general case for the quantum network of nodes.

A Digital Evidence Fusion Method in Network Forensics Systems with Dempster-Shafer Theory

Network intrusion forensics is an important extension to present security infrastructure,and is becoming the focus of forensics research field.However,comparison with sophisticated multi-stage attacks and volume of sensor data,current practices in network forensic analysis are to manually examine,an error prone,labor-intensive and time consuming process.To solve these problems,in this paper we propose a digital evidence fusion method for network forensics with Dempster-Shafer theory that can detect efficiently computer crime in networked environments,and fuse digital evidence from different sources such as hosts and sub-networks automatically.In the end,we evaluate the method on well-known KDD Cup1999 dataset.The results prove our method is very effective for real-time network forensics,and can provide comprehensible messages for a forensic investigators.

Fault diagnosis method of hydraulic system based on fusion of neural network and D-S evidence theory

According to fault type diversity and fault information uncertainty problem of the hydraulic driven rocket launcher servo system（HDRLSS） , the fault diagnosis method based on the evidence theory and neural network ensemble is proposed. In order to overcome the shortcomings of the single neural network, two improved neural network models are set up at the com-mon nodes to simplify the network structure. The initial fault diagnosis is based on the iron spectrum data and the pressure, flow and temperature（PFT） characteristic parameters as the input vectors of the two improved neural network models, and the diagnosis result is taken as the basic probability distribution of the evidence theory. Then the objectivity of assignment is real-ized. The initial diagnosis results of two improved neural networks are fused by D-S evidence theory. The experimental results show that this method can avoid the misdiagnosis of neural network recognition and improve the accuracy of the fault diagnosis of HDRLSS.

Efficient Virtual Network Embedding Algorithm Based on Restrictive Selection and Optimization Theory Approach

Network virtualization(NV) is widely considered as a key component of the future network and promises to allow multiple virtual networks(VNs) with different protocols to coexist on a shared substrate network(SN). One main challenge in NV is virtual network embedding(VNE). VNE is a NPhard problem. Previous VNE algorithms in the literature are mostly heuristic, while the remaining algorithms are exact. Heuristic algorithms aim to find a feasible embedding of each VN, not optimal or sub-optimal, in polynomial time. Though presenting the optimal or sub-optimal embedding per VN, exact algorithms are too time-consuming in smallscaled networks, not to mention moderately sized networks. To make a trade-off between the heuristic and the exact, this paper presents an effective algorithm, labeled as VNE-RSOT(Restrictive Selection and Optimization Theory), to solve the VNE problem. The VNERSOT can embed virtual nodes and links per VN simultaneously. The restrictive selection contributes to selecting candidate substrate nodes and paths and largely cuts down on the number of integer variables, used in the following optimization theory approach. The VNE-RSOT fights to minimize substrate resource consumption and accommodates more VNs. To highlight the efficiency of VNERSOT, a simulation against typical and stateof-art heuristic algorithms and a pure exact algorithm is made. Numerical results reveal that virtual network request(VNR) acceptance ratio of VNE-RSOT is, at least, 10% higher than the best-behaved heuristic. Other metrics, such as the execution time, are also plotted to emphasize and highlight the efficiency of VNE-RSOT.

Full Diversity Reception Based on Dempster-Shafer Theory for Network Coding with Multiple-Antennas Relay

In this paper,a two-way relay system which achieves bi-directional communication via a multiple-antenna relay in two time slots is studied.In the multiple access(MA) phase,the novel receive schemes based on Dempster-Shafer(D-S) evidence theory are proposed at the relay node.Instead of traditional linear detection,the first proposed MIMO-DS NC scheme adopts D-S evidence theory to detect the signals of each source node before mapping them into network-coded signal.Moreover,different from traditional physical-layer network coding(PNC) based on virtual MIMO model,the further proposed MIMO-DS PNC comes from the vector space perspective and combines PNC mapping with D-S theory to obtain network-coded signal without estimating each source node signal.D-S theory can appropriately characterize uncertainty and make full use of multiple evidence source information by Dempster's combination rule to obtain reliable decisions.In the broadcast(BC) phase,the space-time coding(STC) and antenna selection(AS) schemes are adopted to achieve transmit diversity.Simulation results reveal that the STC and AS schemes both achieve full transmit diversity in the BC phase and the proposed MIMO-DS NC/PNC schemes obtain better end-to-end BER performance and throughputs compared with traditional schemes with a little complexity increasing and no matter which scheme is adopted in the BC phase,MIMO-DS PNC always achieves full end-to-end diversity gain as MIMO-ML NC but with a lower complexity and its throughput approaches the throughput of MIMO-ML NC in high SNR regime.

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,

Assessment of challenges and strategies for driving energy transitions in emerging markets:A socio-technological systems perspective

The pursuit of improved quality of life standards has significantly influenced the contemporary mining model in the 21st century.This era is witnessing an unprecedented transformation driven by pressing concerns related to sustainability,climate change,the just energy transition,dynamic operating environments,and complex social challenges.Such transitions present both opportunities and obstacles.The aim of this study is to provide an extensive literature review on energy transition to identify the challenges and strategies associated with navigating transformations in energy systems.Understanding these transformations is particularly critical in the face of the severe consequences of global warming,where an accelerated energy transition is viewed as a universal remedy.Adopting a socio-technological systems perspective,specifically through the application of Actor Network Theory(ANT),this research provides a theoretical foundation while categorising challenges into five distinct domains and outlining strategies across these different dimensions.These insights are specifically tailored for emerging market countries to effectively navigate energy transition while fostering the development of resilient societies.Furthermore,our findings highlight that energy transition encompasses more than a mere technological shift;it entails fundamental changes in various systemic socio-economic imperatives.Through focusing on the role of social structures in transitions,this study makes a significant and innovative contribution to ANT,which has historically been criticised for its limited acknowledgement of social structures.Consequently,we propose an emerging market energy transition framework,which not only addresses technological aspects,but also integrates social considerations.This framework paves the way for future research and exploration of energy transition dynamics.The outcomes of this study offer valuable insights to policymakers,researchers,and practitioners engaged in the mining industry,enabling them to comprehend the multifaceted challenges involved and providing practical strategies for effective resolution.Through incorporating the social dimension into the analysis,we enhance the understanding of the complex nature of energy system transformations,facilitating a more holistic approach towards achieving sustainable and resilient energy transitions in emerging markets and beyond.

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.

Separability of Pure States and Mixed States of the Quantum Network of Two Nodes

This article discusses the separability of the pure states and mixed states of the quantum network of two nodes by means of the criterion of no entanglement in terms of the covariance correlation tensor in quantum network theory, i.e. for a composite system consisting of two nodes. The covariance correlation tensor is equal to zero for all possible and .