The production mode of manufacturing industry presents characteristics of multiple varieties,small-batch and personalization,leading to frequent disturbances in workshop.Traditional centralized scheduling methods are ...The production mode of manufacturing industry presents characteristics of multiple varieties,small-batch and personalization,leading to frequent disturbances in workshop.Traditional centralized scheduling methods are difficult to achieve efficient and real-time production management under dynamic disturbance.In order to improve the intelligence and adaptability of production scheduler,a novel distributed scheduling architecture is proposed,which has the ability to autonomously allocate tasks and handle disturbances.All production tasks are scheduled through autonomous collaboration and decision-making between intelligent machines.Firstly,the multi-agent technology is applied to build a self-organizing manufacturing system,enabling each machine to be equipped with the ability of active information interaction and joint-action execution.Secondly,various self-organizing collaboration strategies are designed to effectively facilitate cooperation and competition among multiple agents,thereby flexibly achieving global perception of environmental state.To ensure the adaptability and superiority of production decisions in dynamic environment,deep reinforcement learning is applied to build a smart production scheduler:Based on the perceived environment state,the scheduler intelligently generates the optimal production strategy to guide the task allocation and resource configuration.The feasibility and effectiveness of the proposed method are verified through three experimental scenarios using a discrete manufacturing workshop as the test bed.Compared to heuristic dispatching rules,the proposed method achieves an average performance improvement of 34.0%in three scenarios in terms of order tardiness.The proposed system can provide a new reference for the design of smart manufacturing systems.展开更多
In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to ...In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.展开更多
In this paper,a novel method for investigating the particle-crushing behavior of breeding particles in a fusion blanket is proposed.The fractal theory and Weibull distribution are combined to establish a theoretical m...In this paper,a novel method for investigating the particle-crushing behavior of breeding particles in a fusion blanket is proposed.The fractal theory and Weibull distribution are combined to establish a theoretical model,and its validity was verified using a simple impact test.A crushable discrete element method(DEM)framework is built based on the previously established theoretical model.The tensile strength,which considers the fractal theory,size effect,and Weibull variation,was assigned to each generated particle.The assigned strength is then used for crush detection by comparing it with its maximum tensile stress.Mass conservation is ensured by inserting a series of sub-particles whose total mass was equal to the quality loss.Based on the crushable DEM framework,a numerical simulation of the crushing behavior of a pebble bed with hollow cylindrical geometry under a uniaxial compression test was performed.The results of this investigation showed that the particle withstands the external load by contact and sliding at the beginning of the compression process,and the results confirmed that crushing can be considered an important method of resisting the increasing external load.A relatively regular particle arrangement aids in resisting the load and reduces the occurrence of particle crushing.However,a limit exists to the promotion of resistance.When the strain increases beyond this limit,the distribution of the crushing position tends to be isotropic over the entire pebble bed.The theoretical model and crushable DEM framework provide a new method for exploring the pebble bed in a fusion reactor,considering particle crushing.展开更多
Effective partitioning is crucial for enabling parallel restoration of power systems after blackouts.This paper proposes a novel partitioning method based on deep reinforcement learning.First,the partitioning decision...Effective partitioning is crucial for enabling parallel restoration of power systems after blackouts.This paper proposes a novel partitioning method based on deep reinforcement learning.First,the partitioning decision process is formulated as a Markov decision process(MDP)model to maximize the modularity.Corresponding key partitioning constraints on parallel restoration are considered.Second,based on the partitioning objective and constraints,the reward function of the partitioning MDP model is set by adopting a relative deviation normalization scheme to reduce mutual interference between the reward and penalty in the reward function.The soft bonus scaling mechanism is introduced to mitigate overestimation caused by abrupt jumps in the reward.Then,the deep Q network method is applied to solve the partitioning MDP model and generate partitioning schemes.Two experience replay buffers are employed to speed up the training process of the method.Finally,case studies on the IEEE 39-bus test system demonstrate that the proposed method can generate a high-modularity partitioning result that meets all key partitioning constraints,thereby improving the parallelism and reliability of the restoration process.Moreover,simulation results demonstrate that an appropriate discount factor is crucial for ensuring both the convergence speed and the stability of the partitioning training.展开更多
The application of nitrogen fertilizers in agricultural fields can lead to the release of nitrogen-containing gases(NCGs),such as NO_(x),NH_(3) and N_(2)O,which can significantly impact regional atmospheric environmen...The application of nitrogen fertilizers in agricultural fields can lead to the release of nitrogen-containing gases(NCGs),such as NO_(x),NH_(3) and N_(2)O,which can significantly impact regional atmospheric environment and con-tribute to global climate change.However,there remain considerable research gaps in the accurate measurement of NCGs emissions from agricultural fields,hindering the development of effective emission reduction strategies.We improved an open-top dynamic chambers(OTDCs)system and evaluated the performance by comparing the measured and given fluxes of the NCGs.The results showed that the measured fluxes of NO,N_(2)O and NH_(3)were 1%,2%and 7%lower than the given fluxes,respectively.For the determination of NH_(3) concentration,we employed a stripping coil-ion chromatograph(SC-IC)analytical technique,which demonstrated an absorption efficiency for atmospheric NH_(3) exceeding 96.1%across sampling durations of 6 to 60 min.In the summer maize season,we utilized the OTDCs system to measure the exchange fluxes of NO,NH_(3),and N_(2)O from the soil in the North China Plain.Substantial emissions of NO,NH_(3) and N_(2)O were recorded following fertilization,with peaks of 107,309,1239 ng N/(m^(2)·s),respectively.Notably,significant NCGs emissions were observed following sus-tained heavy rainfall one month after fertilization,particularly with NH_(3) peak being 4.5 times higher than that observed immediately after fertilization.Our results demonstrate that the OTDCs system accurately reflects the emission characteristics of soil NCGs and meets the requirements for long-term and continuous flux observation.展开更多
Marine thin plates are susceptible to welding deformation owing to their low structural stiffness.Therefore,the efficient and accurate prediction of welding deformation is essential for improving welding quality.The t...Marine thin plates are susceptible to welding deformation owing to their low structural stiffness.Therefore,the efficient and accurate prediction of welding deformation is essential for improving welding quality.The traditional thermal elastic-plastic finite element method(TEP-FEM)can accurately predict welding deformation.However,its efficiency is low because of the complex nonlinear transient computation,making it difficult to meet the needs of rapid engineering evaluation.To address this challenge,this study proposes an efficient prediction method for welding deformation in marine thin plate butt welds.This method is based on the coupled temperature gradient-thermal strain method(TG-TSM)that integrates inherent strain theory with a shell element finite element model.The proposed method first extracts the distribution pattern and characteristic value of welding-induced inherent strain through TEP-FEM analysis.This strain is then converted into the equivalent thermal load applied to the shell element model for rapid computation.The proposed method-particularly,the gradual temperature gradient-thermal strain method(GTG-TSM)-achieved improved computational efficiency and consistent precision.Furthermore,the proposed method required much less computation time than the traditional TEP-FEM.Thus,this study lays the foundation for future prediction of welding deformation in more complex marine thin plates.展开更多
At present,there is currently a lack of unified standard methods for the determination of antimony content in groundwater in China.The precision and trueness of related detection technologies have not yet been systema...At present,there is currently a lack of unified standard methods for the determination of antimony content in groundwater in China.The precision and trueness of related detection technologies have not yet been systematically and quantitatively evaluated,which limits the effective implementation of environmental monitoring.In response to this key technical gap,this study aimed to establish a standardized method for determining antimony in groundwater using Hydride Generation–Atomic Fluorescence Spectrometry(HG-AFS).Ten laboratories participated in inter-laboratory collaborative tests,and the statistical analysis of the test data was carried out in strict accordance with the technical specifications of GB/T 6379.2—2004 and GB/T 6379.4—2006.The consistency and outliers of the data were tested by Mandel's h and k statistics,the Grubbs test and the Cochran test,and the outliers were removed to optimize the data,thereby significantly improving the reliability and accuracy.Based on the optimized data,parameters such as the repeatability limit(r),reproducibility limit(R),and method bias value(δ)were determined,and the trueness of the method was statistically evaluated.At the same time,precision-function relationships were established,and all results met the requirements.The results show that the lower the antimony content,the lower the repeatability limit(r)and reproducibility limit(R),indicating that the measurement error mainly originates from the detection limit of the method and instrument sensitivity.Therefore,improving the instrument sensitivity and reducing the detection limit are the keys to controlling the analytical error and improving precision.This study provides reliable data support and a solid technical foundation for the establishment and evaluation of standardized methods for the determination of antimony content in groundwater.展开更多
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 the...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.展开更多
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...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.展开更多
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,c...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.展开更多
Considering that growing hierarchical self-organizing map(GHSOM) ignores the influence of individual component in sample vector analysis, and its accurate rate in detecting unknown network attacks is relatively lower,...Considering that growing hierarchical self-organizing map(GHSOM) ignores the influence of individual component in sample vector analysis, and its accurate rate in detecting unknown network attacks is relatively lower, an improved GHSOM method combined with mutual information is proposed. After theoretical analysis, experiments are conducted to illustrate the effectiveness of the proposed method by accurately clustering the input data. Based on different clusters, the complex relationship within the data can be revealed effectively.展开更多
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 com...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.展开更多
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 compres...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.展开更多
To solve the mapping problem for the mobile robots in the unknown environment, a dynamic growing self-organizing map with growing-threshold tuning automatically algorithm (DGSOMGT) based on Self-organizing Map is prop...To solve the mapping problem for the mobile robots in the unknown environment, a dynamic growing self-organizing map with growing-threshold tuning automatically algorithm (DGSOMGT) based on Self-organizing Map is proposed. It introduces a value of spread factor to describe the changing process of the growing threshold dynamically. The method realizes the network structure growing by training through mobile robot movement constantly in the unknown environment. The proposed algorithm is based on self-organizing map and can adjust the growing-threshold value by the number of network neurons increasing. It avoids tuning the parameters repeatedly by human. The experimental results show that the proposed method detects the complex environment quickly, effectively and correctly. The robot can realize environment mapping automatically. Compared with the other methods the proposed mapping strategy has better topological properties and time property.展开更多
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 ...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.展开更多
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 struct...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.展开更多
This paper describes the evaluation method of the gait motion in walk rehabilitation. We assume that the evaluation consists of the classification of the measured data and the prediction of the feature of the gait mot...This paper describes the evaluation method of the gait motion in walk rehabilitation. We assume that the evaluation consists of the classification of the measured data and the prediction of the feature of the gait motion. The method may enable a doctor and a physical therapist to recognize the condition of the patients more easily, and increase the motivation of patient further for rehabilitation. However, it is difficult to divide the gait motion into discrete categories, since the gait motion continuously changes and does not have the clear boundaries. Therefore, the self-organizing map （SOM） that is able to arrange the continuous data on the almost continuous map is employed in order to classify them. And, the feature of the gait motion is predicted by the classification. In this study, we adopt the gravity-center fluctuation （GCF） on the sole as the measured data. First, it is shown that the pattern of the CCF that is obtained by our developed measurement system includes the feature of the gait motion. Secondly, the relation between the pattern of the GCF and the feature of the gait motion that the doctor and the physical therapist evaluate by visual inspection is considered using the SOM. Next, we describe the prediction of following features measured by numerical values： the length of stride, the velocity of walk and the difference of steps that are important for the doctor and the physical therapist to make a diagnosis of the condition of the gait motion in walk rehabilitation. Finally, it is investigated that the position of a new test data that is arranged on the map accords with the prediction. As a consequence, we confirm that the method using the SOM is often useful to classify and predict the condition of the patient.展开更多
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 wi...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,展开更多
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 Ele...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).展开更多
基金supported by the Scientific Research Foundation of Nanjing Institute of Technology(No.YKJ202425)the National Natural Science Foundation of China(No.72301130).
文摘The production mode of manufacturing industry presents characteristics of multiple varieties,small-batch and personalization,leading to frequent disturbances in workshop.Traditional centralized scheduling methods are difficult to achieve efficient and real-time production management under dynamic disturbance.In order to improve the intelligence and adaptability of production scheduler,a novel distributed scheduling architecture is proposed,which has the ability to autonomously allocate tasks and handle disturbances.All production tasks are scheduled through autonomous collaboration and decision-making between intelligent machines.Firstly,the multi-agent technology is applied to build a self-organizing manufacturing system,enabling each machine to be equipped with the ability of active information interaction and joint-action execution.Secondly,various self-organizing collaboration strategies are designed to effectively facilitate cooperation and competition among multiple agents,thereby flexibly achieving global perception of environmental state.To ensure the adaptability and superiority of production decisions in dynamic environment,deep reinforcement learning is applied to build a smart production scheduler:Based on the perceived environment state,the scheduler intelligently generates the optimal production strategy to guide the task allocation and resource configuration.The feasibility and effectiveness of the proposed method are verified through three experimental scenarios using a discrete manufacturing workshop as the test bed.Compared to heuristic dispatching rules,the proposed method achieves an average performance improvement of 34.0%in three scenarios in terms of order tardiness.The proposed system can provide a new reference for the design of smart manufacturing systems.
基金Supported in part by Natural Science Foundation of Guangxi(2023GXNSFAA026246)in part by the Central Government's Guide to Local Science and Technology Development Fund(GuikeZY23055044)in part by the National Natural Science Foundation of China(62363003)。
文摘In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.
基金supported by Anhui Provincial Natural Science Foundation(2408085QA030)Natural Science Research Project of Anhui Educational Committee,China(2022AH050825)+3 种基金Medical Special Cultivation Project of Anhui University of Science and Technology(YZ2023H2C008)the Excellent Research and Innovation Team of Anhui Province,China(2022AH010052)the Scientific Research Foundation for High-level Talents of Anhui University of Science and Technology,China(2021yjrc51)Collaborative Innovation Program of Hefei Science Center,CAS,China(2019HSC-CIP006).
文摘In this paper,a novel method for investigating the particle-crushing behavior of breeding particles in a fusion blanket is proposed.The fractal theory and Weibull distribution are combined to establish a theoretical model,and its validity was verified using a simple impact test.A crushable discrete element method(DEM)framework is built based on the previously established theoretical model.The tensile strength,which considers the fractal theory,size effect,and Weibull variation,was assigned to each generated particle.The assigned strength is then used for crush detection by comparing it with its maximum tensile stress.Mass conservation is ensured by inserting a series of sub-particles whose total mass was equal to the quality loss.Based on the crushable DEM framework,a numerical simulation of the crushing behavior of a pebble bed with hollow cylindrical geometry under a uniaxial compression test was performed.The results of this investigation showed that the particle withstands the external load by contact and sliding at the beginning of the compression process,and the results confirmed that crushing can be considered an important method of resisting the increasing external load.A relatively regular particle arrangement aids in resisting the load and reduces the occurrence of particle crushing.However,a limit exists to the promotion of resistance.When the strain increases beyond this limit,the distribution of the crushing position tends to be isotropic over the entire pebble bed.The theoretical model and crushable DEM framework provide a new method for exploring the pebble bed in a fusion reactor,considering particle crushing.
基金funded by the Beijing Engineering Research Center of Electric Rail Transportation.
文摘Effective partitioning is crucial for enabling parallel restoration of power systems after blackouts.This paper proposes a novel partitioning method based on deep reinforcement learning.First,the partitioning decision process is formulated as a Markov decision process(MDP)model to maximize the modularity.Corresponding key partitioning constraints on parallel restoration are considered.Second,based on the partitioning objective and constraints,the reward function of the partitioning MDP model is set by adopting a relative deviation normalization scheme to reduce mutual interference between the reward and penalty in the reward function.The soft bonus scaling mechanism is introduced to mitigate overestimation caused by abrupt jumps in the reward.Then,the deep Q network method is applied to solve the partitioning MDP model and generate partitioning schemes.Two experience replay buffers are employed to speed up the training process of the method.Finally,case studies on the IEEE 39-bus test system demonstrate that the proposed method can generate a high-modularity partitioning result that meets all key partitioning constraints,thereby improving the parallelism and reliability of the restoration process.Moreover,simulation results demonstrate that an appropriate discount factor is crucial for ensuring both the convergence speed and the stability of the partitioning training.
基金supported by the National Key Research and Develop-ment Program(No.2022YFC3701103)the National Natural Science Foundation of China(Nos.42130714 and 41931287).
文摘The application of nitrogen fertilizers in agricultural fields can lead to the release of nitrogen-containing gases(NCGs),such as NO_(x),NH_(3) and N_(2)O,which can significantly impact regional atmospheric environment and con-tribute to global climate change.However,there remain considerable research gaps in the accurate measurement of NCGs emissions from agricultural fields,hindering the development of effective emission reduction strategies.We improved an open-top dynamic chambers(OTDCs)system and evaluated the performance by comparing the measured and given fluxes of the NCGs.The results showed that the measured fluxes of NO,N_(2)O and NH_(3)were 1%,2%and 7%lower than the given fluxes,respectively.For the determination of NH_(3) concentration,we employed a stripping coil-ion chromatograph(SC-IC)analytical technique,which demonstrated an absorption efficiency for atmospheric NH_(3) exceeding 96.1%across sampling durations of 6 to 60 min.In the summer maize season,we utilized the OTDCs system to measure the exchange fluxes of NO,NH_(3),and N_(2)O from the soil in the North China Plain.Substantial emissions of NO,NH_(3) and N_(2)O were recorded following fertilization,with peaks of 107,309,1239 ng N/(m^(2)·s),respectively.Notably,significant NCGs emissions were observed following sus-tained heavy rainfall one month after fertilization,particularly with NH_(3) peak being 4.5 times higher than that observed immediately after fertilization.Our results demonstrate that the OTDCs system accurately reflects the emission characteristics of soil NCGs and meets the requirements for long-term and continuous flux observation.
基金Supported by the National Natural Science Foundation of China under Grant No.51975138the High-Tech Ship Scientific Research Project from the Ministry of Industry and Information Technology under Grant No.CJ05N20the National Defense Basic Research Project under Grant No.JCKY2023604C006.
文摘Marine thin plates are susceptible to welding deformation owing to their low structural stiffness.Therefore,the efficient and accurate prediction of welding deformation is essential for improving welding quality.The traditional thermal elastic-plastic finite element method(TEP-FEM)can accurately predict welding deformation.However,its efficiency is low because of the complex nonlinear transient computation,making it difficult to meet the needs of rapid engineering evaluation.To address this challenge,this study proposes an efficient prediction method for welding deformation in marine thin plate butt welds.This method is based on the coupled temperature gradient-thermal strain method(TG-TSM)that integrates inherent strain theory with a shell element finite element model.The proposed method first extracts the distribution pattern and characteristic value of welding-induced inherent strain through TEP-FEM analysis.This strain is then converted into the equivalent thermal load applied to the shell element model for rapid computation.The proposed method-particularly,the gradual temperature gradient-thermal strain method(GTG-TSM)-achieved improved computational efficiency and consistent precision.Furthermore,the proposed method required much less computation time than the traditional TEP-FEM.Thus,this study lays the foundation for future prediction of welding deformation in more complex marine thin plates.
基金supported by the National Natural Science Foundation of China(Project No.42307555).
文摘At present,there is currently a lack of unified standard methods for the determination of antimony content in groundwater in China.The precision and trueness of related detection technologies have not yet been systematically and quantitatively evaluated,which limits the effective implementation of environmental monitoring.In response to this key technical gap,this study aimed to establish a standardized method for determining antimony in groundwater using Hydride Generation–Atomic Fluorescence Spectrometry(HG-AFS).Ten laboratories participated in inter-laboratory collaborative tests,and the statistical analysis of the test data was carried out in strict accordance with the technical specifications of GB/T 6379.2—2004 and GB/T 6379.4—2006.The consistency and outliers of the data were tested by Mandel's h and k statistics,the Grubbs test and the Cochran test,and the outliers were removed to optimize the data,thereby significantly improving the reliability and accuracy.Based on the optimized data,parameters such as the repeatability limit(r),reproducibility limit(R),and method bias value(δ)were determined,and the trueness of the method was statistically evaluated.At the same time,precision-function relationships were established,and all results met the requirements.The results show that the lower the antimony content,the lower the repeatability limit(r)and reproducibility limit(R),indicating that the measurement error mainly originates from the detection limit of the method and instrument sensitivity.Therefore,improving the instrument sensitivity and reducing the detection limit are the keys to controlling the analytical error and improving precision.This study provides reliable data support and a solid technical foundation for the establishment and evaluation of standardized methods for the determination of antimony content in groundwater.
基金Supported by the Science Foundation of the Ministry of Education of China for the Returned Overseas Chinese Scholars
文摘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.
基金supported by the National Natural Science Foundation of China(72072047)the Humanities and Social Sciences Project of Ministry of Education(20YJC630090)+1 种基金Heilongjiang Philosophy and Social Science Research Project(19GLB087)the Science and Technology Program of Hebei Province(20557688D)。
文摘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.
基金ACKNOWLEDGEMENT This work was supported by National Natural Science Foundation of China （No. 61172050）, Program for New Century Excellent Talents in University （NECT-12-0774）, the open research fund of National Mobile Communications Research Laboratory, Southeast University （No.2013D12）, the Foundation of Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services. The corresponding author is Dr. Zhongshan Zhang.
文摘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.
基金Supported by the Natural Science Foundation of Tianjin(No.15JCQNJC00200)
文摘Considering that growing hierarchical self-organizing map(GHSOM) ignores the influence of individual component in sample vector analysis, and its accurate rate in detecting unknown network attacks is relatively lower, an improved GHSOM method combined with mutual information is proposed. After theoretical analysis, experiments are conducted to illustrate the effectiveness of the proposed method by accurately clustering the input data. Based on different clusters, the complex relationship within the data can be revealed effectively.
基金supported by National Natural Science Foundation of China(No.60674081,No.60834002,No.61074145)
文摘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.
文摘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.
文摘To solve the mapping problem for the mobile robots in the unknown environment, a dynamic growing self-organizing map with growing-threshold tuning automatically algorithm (DGSOMGT) based on Self-organizing Map is proposed. It introduces a value of spread factor to describe the changing process of the growing threshold dynamically. The method realizes the network structure growing by training through mobile robot movement constantly in the unknown environment. The proposed algorithm is based on self-organizing map and can adjust the growing-threshold value by the number of network neurons increasing. It avoids tuning the parameters repeatedly by human. The experimental results show that the proposed method detects the complex environment quickly, effectively and correctly. The robot can realize environment mapping automatically. Compared with the other methods the proposed mapping strategy has better topological properties and time property.
基金Supported by the Natural Science Foundation of Zhejiang Province under Grant No LY15A050001the National Natural Science Foundation of China under Grant Nos 11247007 and 11374262the Open Fund of the State Key Laboratory of High-Field Laser Physics at SIOM
文摘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.
文摘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.
基金supported by JSPS KAKENHI(Nos.JP26730118 and JP16K12486)
文摘This paper describes the evaluation method of the gait motion in walk rehabilitation. We assume that the evaluation consists of the classification of the measured data and the prediction of the feature of the gait motion. The method may enable a doctor and a physical therapist to recognize the condition of the patients more easily, and increase the motivation of patient further for rehabilitation. However, it is difficult to divide the gait motion into discrete categories, since the gait motion continuously changes and does not have the clear boundaries. Therefore, the self-organizing map （SOM） that is able to arrange the continuous data on the almost continuous map is employed in order to classify them. And, the feature of the gait motion is predicted by the classification. In this study, we adopt the gravity-center fluctuation （GCF） on the sole as the measured data. First, it is shown that the pattern of the CCF that is obtained by our developed measurement system includes the feature of the gait motion. Secondly, the relation between the pattern of the GCF and the feature of the gait motion that the doctor and the physical therapist evaluate by visual inspection is considered using the SOM. Next, we describe the prediction of following features measured by numerical values： the length of stride, the velocity of walk and the difference of steps that are important for the doctor and the physical therapist to make a diagnosis of the condition of the gait motion in walk rehabilitation. Finally, it is investigated that the position of a new test data that is arranged on the map accords with the prediction. As a consequence, we confirm that the method using the SOM is often useful to classify and predict the condition of the patient.
基金Project supported by the National Natural Science Foundation of China （Grant Nos 60374037 and 60574036）, the Program for New Century Excellent Talents of High Education of China（Grant No NCET 2005-290）, The Special Research Fund for the Doctoral Program of High Education of China （Grant No 20050055013）.Acknowledgments The authors would like to thank Réka Albert for useful discussion and are grateful to the anonymous referees for their valuable suggestions and comments, which have made this paper improved.
文摘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,
文摘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).
