Spatial Protection and Development of Traditional Mountain Settlements from the Perspective of Self-organization : A Case Study of Anju Ancient Town in Tongliang District, Chongqing

Through literature research, field research and urban design analysis methods, based on the self-organization theory, the evolution characteristics of the settlement space of Anju Ancient Town with significant characteristics of traditional mountain settlements were analyzed, and then its internal and external influencing factors were summarized. Finally, appropriate protection and development strategies were proposed, such as reasonably planning functional zones, breaking through the single structure, and creating a good living cultural environment. The innovation of this study is that it integrates the self-organization theory into the cognition of traditional mountain settlement space, and discusses the connection between the mountain settlement space and the traditional regional context under the modern development concept, so as to seek the benign protection and reasonable development of traditional mountain settlement space.

Multi-UAV Collaborative Mission Planning Method for Self-Organized Sensor Data Acquisition

In recent years,sensor technology has been widely used in the defense and control of sensitive areas in cities,or in various scenarios such as early warning of forest fires,monitoring of forest pests and diseases,and protection of endangered animals.Deploying sensors to collect data and then utilizing unmanned aerial vehicle(UAV)to collect the data stored in the sensors has replaced traditional manual data collection as the dominant method.The current strategies for efficient data collection in above scenarios are still imperfect,and the low quality of the collected data and the excessive energy consumed by UAV flights are still the main problems faced in data collection.With regards this,this paper proposes a multi-UAV mission planning method for self-organized sensor data acquisition by comprehensively utilizing the techniques of self-organized sensor clustering,multi-UAV mission area allocation,and sub-area data acquisition scheme optimization.The improvedα-hop clustering method utilizes the average transmission distance to reduce the size of the collection sensors,and the K-Dimensional method is used to form a multi-UAV cooperative workspace,and then,the genetic algorithm is used to trade-off the speed with the age of information(AoI)of the collected information and the energy consumption to form the multi-UAV data collection operation scheme.The combined optimization scheme in paper improves the performance by 95.56%and 58.21%,respectively,compared to the traditional baseline model.In order to verify the excellent generalization and applicability of the proposed method in real scenarios,the simulation test is conducted by introducing the digital elevation model data of the real terrain,and the results show that the relative error values of the proposed method and the performance test of the actual flight of the UAV are within the error interval of±10%.Then,the advantages and disadvantages of the present method with the existing mainstream schemes are tested,and the results show that the present method has a huge advantage in terms of space and time complexity,and at the same time,the accuracy for data extraction is relatively improved by 10.46%and 12.71%.Finally,by eliminating the clustering process and the subtask assignment process,the AoI performance decreases by 3.46×and 4.45×,and the energy performance decreases by 3.52×and 4.47×.This paper presents a comprehensive and detailed proactive optimization of the existing challenges faced in the field of data acquisition by means of a series of combinatorial optimizations.

Equilibrium reconstruction method for self-organized plasmas on reversed field pinches with polarimeter-interferometer

In the reversed field pinch(RFP),plasmas exhibit various self-organized states.Among these,the three-dimensional(3D)helical state known as the“quasi-single-helical”(QSH)state enhances RFP confinement.However,accurately describing the equilibrium is challenging due to the presence of 3D structures,magnetic islands,and chaotic regions.It is difficult to obtain a balance between the available diagnostic and the real equilibrium structure.To address this issue,we introduce KTX3DFit,a new 3D equilibrium reconstruction code specifically designed for the Keda Torus eXperiment(KTX)RFP.KTX3DFit utilizes the stepped-pressure equilibrium code(SPEC)to compute 3D equilibria and uses polarimetric interferometer signals from experiments.KTX3DFit is able to reconstruct equilibria in various states,including axisymmetric,doubleaxis helical(DAx),and single-helical-axis(SHAx)states.Notably,this study marks the first integration of the SPEC code with internal magnetic field data for equilibrium reconstruction and could be used for other 3D configurations.

Hierarchical Self-organization of Complex Systems

Researches on organization and structure in complex systems are academic and industrial fronts in modern sciences. Though many theories are tentatively proposed to analyze complex systems, we still lack a rigorous theory on them. Complex systems possess various degrees of freedom, which means that they should exhibit all kinds of structures. However, complex systems often show similar patterns and structures. Then the question arises why such similar structures appear in all kinds of complex systems. The paper outlines a theory on freedom degree compression and the existence of hierarchical self-organization for all complex systems is found. It is freedom degree compression and hierarchical self-organization that are responsible for the existence of these similar patterns or structures observed in the complex systems.

Self-Organization Approaches for Optimization in Cognitive Radio Networks

Cognitive radio(CR) is regarded as a promising technology for providing a high spectral efficiency to mobile users by using heterogeneous wireless network architectures and dynamic spectrum access techniques.However,cognitive radio networks(CRNs)may also impose some challenges due to the ever increasing complexity of network architecture,the increasing complexity with configuration and management of large-scale networks,fluctuating nature of the available spectrum,diverse Quality-of-Service(QoS)requirements of various applications,and the intensifying difficulties of centralized control,etc.Spectrum management functions with self-organization features can be used to address these challenges and realize this new network paradigm.In this paper,fundamentals of CR,including spectrum sensing,spectrum management,spectrum mobility and spectrum sharing,have been surveyed,with their paradigms of self-organization being emphasized.Variant aspects of selforganization paradigms in CRNs,including critical functionalities of Media Access Control(MAC)- and network-layer operations,are surveyed and compared.Furthermore,new directions and open problems in CRNs are also identified in this survey.

Self-organization of Reconfigurable Protocol Stack for Networked Control Systems

In networked control systems （NCS）,the control performance depends on not only the control algorithm but also the communication protocol stack.The performance degradation introduced by the heterogeneous and dynamic communication environment has intensified the need for the reconfigurable protocol stack.In this paper,a novel architecture for the reconfigurable protocol stack is proposed,which is a unified specification of the protocol components and service interfaces supporting both static and dynamic reconfiguration for existing industrial communication standards.Within the architecture,a triple-level self-organization structure is designed to manage the dynamic reconfiguration procedure based on information exchanges inside and outside the protocol stack.Especially,the protocol stack can be self-adaptive to various environment and system requirements through the reconfiguration of working mode,routing and scheduling table.Finally,the study on the protocol of dynamic address management is conducted for the system of controller area network （CAN）.The results show the efficiency of our self-organizing architecture for the implementation of a reconfigurable protocol stack.

Evolution of technology management system based on self-organization theory

Industrial and academic interest in how to effectively manage technology resources is increasing as it becomes more and more important.Effective managing of technology resources depends on technology management system,and thus understanding how such system evolves becomes an ongoing research topic.Based on the self-organization theory,this paper constructs an evolution model of technology management system.The simulation results show that the evolution of each of the technology management subsystem is affected by the knowledge growth rate of its own,and it is also affected by the coupling and synergy relationship with other subsystems.Moreover,the coupling and synergy relationship can make the speed of evolution higher than the knowledge growth rate of the subsystem itself.

Improve Fractal Compression Encoding Speed Using Feature Extraction and Self-organization Network

Image compression consists of two main parts: encoding and decoding. One of the important problems of the fractal theory is the long encoding implementation time, which hindered the acceptance of fractal image compression as a practical method. The long encoding time results from the need to perform a large number of domain-range matches, the total encoding time is the product of the number of matches and the time to perform each match. In order to improve encoding speed, a hybrid method combining features extraction and self-organization network has been provided, which is based on the feature extraction approach the comparison pixels by pixels between the feature of range blocks and domains blocks. The efficiency of the new method was been proved by examples.

Self-Organization of Charged Particulates in the Presence of External Force

Evolution of spatial distribution of charged particulates under the action of an external force is investigated. It is found that starting from a homogeneous Maxwellian distribution of particulates, clusters can form and aggregate. The evolution process, as well as the asymptotic number and configuration of the clusters formed, depends strongly on the strength of the external force. The particulates in most of the final clusters are in the crystal state, as can also be deduced from the corresponding velocity and auto-correlation functions.

On the Mechanism of Evolution for Enterprise＇s Sustainable Growth Based on the Theory of Self-organization

The capabilities of industry, technology, institution and market power form the model of four-capability structure for enterprise＇s sustainable growth. The firm＇s system has the characteristics of dissipative structure. The process of the formation for the sustainable growth capability is one of self-organization operations. The evolution and development of sustainable growth capability is the result of inter-functions and inter-operations among all the sub-systems. On the whole, the current level of sustainable growth capability, the four-capability structure and the random rise-and-fall elements of the external environment determine the direction, speed and level of transition of sustainable growth capability. The self-organization mechanism of the enterprise＇s sustainable growth can be illustrated by the instability of system evolution, the sequence parameter, the potential function and the nonequilibrium phase transition. Chinese firms must pay attention to industry selecting and positioning, technology innovation, institution reform and cultivation of market power, and accelerate the formation of self-organization and effective operation through the dynamic integration and inter-operation of industry, technology, institution and market power. Only in this way can firms cultivate and develop their sustainable growth capability and realize enterprises＇ sustainable growth finally.

Analysis of morphological characteristics of gravels based on digital image processing technology and self-organizing map

A comprehensive understanding of spatial distribution and clustering patterns of gravels is of great significance for ecological restoration and monitoring.However,traditional methods for studying gravels are low-efficiency and have many errors.This study researched the spatial distribution and cluster characteristics of gravels based on digital image processing technology combined with a self-organizing map(SOM)and multivariate statistical methods in the grassland of northern Tibetan Plateau.Moreover,the correlation of morphological parameters of gravels between different cluster groups and the environmental factors affecting gravel distribution were analyzed.The results showed that the morphological characteristics of gravels in northern region(cluster C)and southern region(cluster B)of the Tibetan Plateau were similar,with a low gravel coverage,small gravel diameter,and elongated shape.These regions were mainly distributed in high mountainous areas with large topographic relief.The central region(cluster A)has high coverage of gravels with a larger diameter,mainly distributed in high-altitude plains with smaller undulation.Principal component analysis(PCA)results showed that the gravel distribution of cluster A may be mainly affected by vegetation,while those in clusters B and C could be mainly affected by topography,climate,and soil.The study confirmed that the combination of digital image processing technology and SOM could effectively analyzed the spatial distribution characteristics of gravels,providing a new mode for gravel research.

A realistic model for complex networks with local interaction, self-organization and order

In this paper, a new mechanism for the emergence of scale-free distribution is proposed. It is more realistic than the existing mechanism. Based on our mechanism, a model responsible for the scale-free distribution with an exponent in a range of 3-to-5 is given. Moreover, this model could also reproduce the exponential distribution that is discovered in some real networks. Finally, the analytical result of the model is given and the simulation shows the validity of our result,

Self-Organization of PbS into Quantum Dots Superlattices

Self-organization of PbS into quantum dots superlattices is demonstrated for the first lime, and hexaplanar colloidal crystals 1-10 mu m in size made from PbS quantum dots 4nm in diameter are shown in Transmission Electron Microscope (TEM) micrograph, and the inner structures of the superlattices can be seen from the High Resolution Transmission Electron Microscope (HRTEM).

Ore Zoning as Self-Organization of Geochemical Dynamic Systems

Zoning in ore bodies, ore deposits and ore regions are recognized as temporal-spatial structures generated by the dynamics of ore- forming processes. Viewed from the theory of dissipative structures, ore zoning is a kind of self-organization phenomenon occurring in far from-equilibrium geochemical dynamic systems. Therefore,kinetic and dynamic approaches must be taken to reveal the mechanisms of ore zoning. Two dominant coupling processes leading to ore zoning——reaction-transport feedbacks and double-diffusive convection——are discussed.

PRELIMINARY STUDY ON RELATIONSHIP BETWEEN DOUBLE VORTICES SELF-ORGANIZATION AND TYPHOON FORMATION IN BAROCLINIC ENVIRONMENT

The relationship between the self-organization of double vortices （SODVs） and the formation of typhoons was discussed based on six numerical experiments with the Fifth-Generation National Center for Atmospheric Research/Penn State Mesoscale Model （MM5） and further discussion was made with a real typhoon case. The results showed that there is a critical distance dc for SODVs in baroclinic atmosphere. When the distance between separated vortices is smaller than or equal to d~, the double vortices self-organize into a typhoon-like vortex with two spiral bands. But the double vortices cannot have such organization if the distance between them is larger than de. The value of dc is about 380 km in the context of ideal conditions in this paper, larger than that achieved in a barotropic model. A typical typhoon case in 2005 （Haitang） was selected to verify the above-mentioned conclusions. It was found that the SODV is one of the important and typical ways for the formation of typhoons.

Conditions,Mechanisms and Process within Self-organization Evolution

Business growth and development are similar to a selforganization evolution system. This paper intends to explore the context, drive and process within enterprise self-organization evolution from a conceptual perspective. And an enterprise evolution model can be applied on the basis of ecological logistic equations to approach the elementary process and the growth stage of organization. Moreover,the influence of diverse variable on the evolution of enterprise growth is discussed. At last, the study concludes that new structures and functions can emerge within organizations and enterprises,which contribute to transformation and upgrade during their self-organization evolution.

A LOCAL DYNAMIC CLUSTER SELF-ORGANIZATION ALGORITHM IN WIRELESS SENSOR NETWORKS FOR RAINFALL MONITORING

Wireless Sensor Networks for Rainfall Monitoring (RM-WSNs) is a sensor network for the large-scale regional and moving rainfall monitoring,which could be controlled deployment. Delivery delay and cross-cluster calculation leads to information inaccuracy by the existing dynamic collabo-rative self-organization algorithm in WSNs. In this letter,a Local Dynamic Cluster Self-organization algorithm (LDCS) is proposed for the large-scale regional and moving target monitoring in RM-WSNs. The algorithm utilizes the resource-rich node in WSNs as the cluster head,which processes target information obtained by sensor nodes in cluster. The cluster head shifts with the target moving in chance and re-groups a new cluster. The target information acquisition is limited in the dynamic cluster,which can reduce information across-clusters transfer delay and improve the real-time of information acquisition. The simulation results show that,LDCS can not only relieve the problem of "too frequent leader switches" in IDSQ,also make full use of the history monitoring information of target and con-tinuous monitoring of sensor nodes that failed in DCS.

Electrical Tree Simulation Based on the Self-Organization Criticality

So far much effort has been made to understand the development of electrical treeing. For the simulation based study of electrical treeing, the most common method is to apply DBM stochastic model to simulate the growing of electrical treeing patterns. Previous simulation results showed that this stochastic model is capable of simulating the real electrical treeing patterns in a point-to-plane electrode system. However, this model only allows the tree channels to propagate on equipotential lines proportional to local electrical field. Therefore, it is necessary to develop a novel stochastic model to simulate the electrical patterns in order to get a good agreement with experimental results.

Self-organization: the governance of CAO fisheries from perspective of the global commons

The Central Arctic Ocean （CAO） is a global commons, and fishes in the CAO are common property resources. If humanity does not manage this region well, then this will lead to a ＂Tragedy of the Commons,＂ an old problem in human society. However, the two existing means of commons governance, privatization and government control, are not appropriate for the CAO. This study＇s findings indicate that CAO fisheries management will most likely result from a process of self-organization. The openness of the CAO and the imbalance of powers, interests and responsibilities among the states that are involved will lead to a process of self-organized governance of CAO fisheries. There are four stages in this process： competition, synergy, establishment of governing principles and mechanisms, and expansion and evolution of influence. The outcome of CAO fisheries governance will be the result of compromise among the parties as no one actor is in a dominant position.

Innovative Mechanism of Rural Organization Based on Self-Organization

The paper analyzes the basic situation of the formation of innovative rural organizations with the form of self-organization;reveals the features of self-organization,including the four aspects of openness of rural organization,innovation of rural organization far away from equilibrium,the non-linear response mechanism of rural organization innovation and the random rise and fall of rural organization innovation.The evolution mechanism of rural organization innovation is revealed according to the growth stage,the ideal stage,the decline and the fall stage.The paper probes into the basic restriction mechanism of the self-organization evaluation of rural organization from three aspects,including target recognition,path dependence and knowledge sharing.The basic measures on cultivating the innovative mechanism of rural organization are put forward.Firstly,constructing the dissipative structure of rural organization innovation;secondly,cultivating the dynamic study capability of rural organization innovation system;thirdly,selecting the step-by-step evolution strategy of rural organization innovation system.