The outbreak of corona virus disease 2019 has profoundly affected people’s way of life.It is increasingly necessary to investigate epidemics over social networks.This paper studies susceptible-infected-removed(SIR)ep...The outbreak of corona virus disease 2019 has profoundly affected people’s way of life.It is increasingly necessary to investigate epidemics over social networks.This paper studies susceptible-infected-removed(SIR)epidemics via the semi-tensor product.First,a formal susceptible-infected-removed epidemic dynamic model over probabilistic dynamic networks(SIRED-PDN)is given.Based on an evolutionary rule,the algebraic form for the dynamics of individual states and network topologies is given,respectively.Second,the SIRED-PDN can be described by a probabilistic mix-valued logical network.After providing an algorithm,all possible final spreading equilibria can be obtained for any given initial epidemic state and network topology by seeking attractors of the network.And the shortest time for all possible initial epidemic state and network topology profiles to evolve to the final spreading equilibria can be obtained by seeking the transient time of the network.Finally,an illustrative example is given to show the effectiveness of our model.展开更多
The mobility of service providers brings new features into the research of dynamic network based service composition.From an optimistic perspective,the mobility of services could benefit the optimization of service co...The mobility of service providers brings new features into the research of dynamic network based service composition.From an optimistic perspective,the mobility of services could benefit the optimization of service composition,if properly handled.Therefore,the impacts of node mobility on the dynamic network based service composition are investigated.Then,a movement-assisted optimization method,namely MASCO,is proposed to improve the performance of the composited services by minimizing the length of data stream and the hop-counts of the service routes in the underlying networks.The correctness and efficiency of the proposed method are then verified through theoretical analysis and computer simulations.展开更多
This paper investigates epidemic dynamics over dynamic networks via the approach of semi-tensor product of matrices. First, a formal susceptible-infected-susceptible epidemic dynamic model over dynamic networks （SISE...This paper investigates epidemic dynamics over dynamic networks via the approach of semi-tensor product of matrices. First, a formal susceptible-infected-susceptible epidemic dynamic model over dynamic networks （SISED-DN） is given. Second, based on a class of determinate co-evolutionary rule, the matrix expressions are established for the dynamics of individual states and network topologies, respectively. Then, all possible final spreading equilibria are obtained for any given initial epidemic state and network topology by the matrix expression. Third, a sufficient and necessary condition of the existence of state feedback vaccination control is presented to make every individual susceptible. The study of illustrative examples shows the effectiveness of our new results.展开更多
We investigate the similarities and differences among three queue rules,the first-in-first-out(FIFO)rule,last-in-firstout(LIFO)rule and random-in-random-out(RIRO)rule,on dynamical networks with limited buffer size.In ...We investigate the similarities and differences among three queue rules,the first-in-first-out(FIFO)rule,last-in-firstout(LIFO)rule and random-in-random-out(RIRO)rule,on dynamical networks with limited buffer size.In our network model,nodes move at each time step.Packets are transmitted by an adaptive routing strategy,combining Euclidean distance and node load by a tunable parameter.Because of this routing strategy,at the initial stage of increasing buffer size,the network density will increase,and the packet loss rate will decrease.Packet loss and traffic congestion occur by these three rules,but nodes keep unblocked and lose no packet in a larger buffer size range on the RIRO rule networks.If packets are lost and traffic congestion occurs,different dynamic characteristics are shown by these three queue rules.Moreover,a phenomenon similar to Braess’paradox is also found by the LIFO rule and the RIRO rule.展开更多
The increasing popularity of the Internet and the widespread use of information technology have led to a rise in the number and sophistication of network attacks and security threats.Intrusion detection systems are cr...The increasing popularity of the Internet and the widespread use of information technology have led to a rise in the number and sophistication of network attacks and security threats.Intrusion detection systems are crucial to network security,playing a pivotal role in safeguarding networks from potential threats.However,in the context of an evolving landscape of sophisticated and elusive attacks,existing intrusion detection methodologies often overlook critical aspects such as changes in network topology over time and interactions between hosts.To address these issues,this paper proposes a real-time network intrusion detection method based on graph neural networks.The proposedmethod leverages the advantages of graph neural networks and employs a straightforward graph construction method to represent network traffic as dynamic graph-structured data.Additionally,a graph convolution operation with a multi-head attention mechanism is utilized to enhance the model’s ability to capture the intricate relationships within the graph structure comprehensively.Furthermore,it uses an integrated graph neural network to address dynamic graphs’structural and topological changes at different time points and the challenges of edge embedding in intrusion detection data.The edge classification problem is effectively transformed into node classification by employing a line graph data representation,which facilitates fine-grained intrusion detection tasks on dynamic graph node feature representations.The efficacy of the proposed method is evaluated using two commonly used intrusion detection datasets,UNSW-NB15 and NF-ToN-IoT-v2,and results are compared with previous studies in this field.The experimental results demonstrate that our proposed method achieves 99.3%and 99.96%accuracy on the two datasets,respectively,and outperforms the benchmark model in several evaluation metrics.展开更多
Social interaction with peer pressure is widely studied in social network analysis.Game theory can be utilized to model dynamic social interaction,and one class of game network models assumes that people’s decision p...Social interaction with peer pressure is widely studied in social network analysis.Game theory can be utilized to model dynamic social interaction,and one class of game network models assumes that people’s decision payoff functions hinge on individual covariates and the choices of their friends.However,peer pressure would be misidentified and induce a non-negligible bias when incomplete covariates are involved in the game model.For this reason,we develop a generalized constant peer effects model based on homogeneity structure in dynamic social networks.The new model can effectively avoid bias through homogeneity pursuit and can be applied to a wider range of scenarios.To estimate peer pressure in the model,we first present two algorithms based on the initialize expand merge method and the polynomial-time twostage method to estimate homogeneity parameters.Then we apply the nested pseudo-likelihood method and obtain consistent estimators of peer pressure.Simulation evaluations show that our proposed methodology can achieve desirable and effective results in terms of the community misclassification rate and parameter estimation error.We also illustrate the advantages of our model in the empirical analysis when compared with a benchmark model.展开更多
For emerging respiratory infectious diseases like COVID-19,non-pharmaceutical interventions such as isolation are crucial for controlling the spread.From the perspective of network transmission,non-pharmaceutical inte...For emerging respiratory infectious diseases like COVID-19,non-pharmaceutical interventions such as isolation are crucial for controlling the spread.From the perspective of network transmission,non-pharmaceutical interventions like isolation alter the degree distribution and other topological structures of the network,thereby controlling the spread of the infectious disease.In this paper,we establish a SEIR mean-field propagation dynamics model for the synchronous evolution of dynamic networks caused by propagation and tracing isolation.We employ the reducing-dimension method to convert the mean-field model in networks into an equivalent and simpler low-dimension model,and then calculate the exact expression of the final size.In addition,we get the differential equations of the degree distribution over time in dynamic networks under tracing isolation and the relationships between the first and second moment of the dynamic network.While the degree of a node remains constant regardless of its state in many previous studies,this paper takes into account that the degree of each node changes over time whatever its state under the disease spread and intervention measures.展开更多
Delay aware routing is now widely used to provide efficient network transmission. However, for newly developing or developed mobile communication networks(MCN), only limited delay data can be obtained. In such a netwo...Delay aware routing is now widely used to provide efficient network transmission. However, for newly developing or developed mobile communication networks(MCN), only limited delay data can be obtained. In such a network, the delay is with epistemic uncertainty, which makes the traditional routing scheme based on deterministic theory or probability theory not applicable. Motivated by this problem, the MCN with epistemic uncertainty is first summarized as a dynamic uncertain network based on uncertainty theory, which is widely applied to model epistemic uncertainties. Then by modeling the uncertain end-toend delay, a new delay bounded routing scheme is proposed to find the path with the maximum belief degree that satisfies the delay threshold for the dynamic uncertain network. Finally, a lowEarth-orbit satellite communication network(LEO-SCN) is used as a case to verify the effectiveness of our routing scheme. It is first modeled as a dynamic uncertain network, and then the delay bounded paths with the maximum belief degree are computed and compared under different delay thresholds.展开更多
Aqueous Zn-metal batteries(AZMBs)performance is hampered by freezing water at low temperatures,which hampers their multi-scenario application.Hydrogen bonds(HBs)play a pivotal role in water freezing,and proton transpo...Aqueous Zn-metal batteries(AZMBs)performance is hampered by freezing water at low temperatures,which hampers their multi-scenario application.Hydrogen bonds(HBs)play a pivotal role in water freezing,and proton transport is indispensable for the establishment of HBs.Here,the accelerated proton transport modulates the dynamic hydrogen bonding network of a Zn(BF4)2/EMIMBF4impregnated polyacrylamide/poly(vinyl alcohol)/xanthan gum dual network eutectic gel electrolyte(PPX-ILZSE)for lowtemperature AZMBs.The PPX-ILZSE forms more HBs,shorter HBs lifetimes,higher tetrahedral entropy,and faster desolvation processes,as demonstrated by experimental and theoretical calculations.This enhanced dynamic proton transport promotes rapid cycling of HBs formation-failure,and for polyaniline cathode(PANI)abundant redox sites of proton,confers excellent low temperature electrochemical performance to the Zn//PANI full cell.Specific capacities for 1000 and 5000 cycles at 1 and 5 A g^(-1)were149.8 and 128.4 m A h g^(-1)at room temperature,respectively.Furthermore,specific capacities of 131.1 mA hg^(-1)(92.4%capacity retention)and 0.0066%capacity decay per lap were achieved for 3000and 3500 laps at-30 and 40℃,respectively,at 0.5 A g^(-1).Furthermore,in-situ protective layer of ZnOHF nano-arrays on the Zn anode surface to eliminate dendrite growth and accelerate Zn-ions adsorption and charge transfer.展开更多
This paper proposes second-order consensus protocols with time-delays and gives the measure of the robustness of the protocols to the time-delay existing in the network of agents with second-order dynamics. By employi...This paper proposes second-order consensus protocols with time-delays and gives the measure of the robustness of the protocols to the time-delay existing in the network of agents with second-order dynamics. By employing a frequency domain method, it is proven that the information states and their time derivatives of all the agents in the network achieve consensus asymptotically, respectively, for appropriate communication timedelay if the topology of weighted network is connected. Particularly, a tight upper bound on the communication time-delay that can be tolerated in the dynamic network is found. The consensus protocols are distributed in the sense that each agent only needs information from its neighboring agents, which reduces the complexity of connections between neighboring agents significantly. Numerical simulation results are provided to demonstrate the effectiveness and the sharpness of the theoretical results for second-order consensus in networks in the presence of communication time-delays.展开更多
Multivariate dynamic networks indicate networks whose topology structure and vertex attributes are evolving along time.They are common in multimedia applications.Anomaly detection is one of the essential tasks in anal...Multivariate dynamic networks indicate networks whose topology structure and vertex attributes are evolving along time.They are common in multimedia applications.Anomaly detection is one of the essential tasks in analyzing these networks though it is not well addressed.In this paper,we combine a rare category detection method and visualization techniques to help users to identify and analyze anomalies in multivariate dynamic networks.We conclude features of rare categories and two types of anomalies of rare categories.Then we present a novel rare category detection method,called DIRAD,to detect rare category candidates with anomalies.We develop a prototype system called iNet,which integrates two major visualization components,including a glyph-based rare category identifier,which helps users to identify rare categories among detected substructures,a major view,which assists users to analyze and interpret the anomalies of rare categories in network topology and vertex attributes.Evaluations,including an algorithm performance evaluation,a case study,and a user study,are conducted to test the effectiveness of proposed methods.展开更多
This paper proposes second-order consensus protocols and gives a measure of the robustness of the protocols to the time-delays existing in the dynamics of agents with second-order dynamics. By employing a frequency do...This paper proposes second-order consensus protocols and gives a measure of the robustness of the protocols to the time-delays existing in the dynamics of agents with second-order dynamics. By employing a frequency domain method, it is proven that the information states achieve second-order consensus asymptotically for appropriate time-delay if the topology of the network is connected. Particularly, a nonconservative upper bound on the fixed time-delay that can be tolerated is found. The consensus protocols are distributed in the sense that each agent only needs information from its neighboring agents, which makes the proposed protocols scalable. It reduces the complexity of connections among agents significantly. Simulation results are provided to verify the effectiveness of the theoretical results for second-order consensus in networks in the presence of time-delays existing in the dynamics of agents.展开更多
Air transport systems are highly dynamic at temporal scales from minutes to years.This dynamic behavior not only characterizes the evolution of the system but also affect the system＇s functioning.Understanding the ev...Air transport systems are highly dynamic at temporal scales from minutes to years.This dynamic behavior not only characterizes the evolution of the system but also affect the system＇s functioning.Understanding the evolutionary mechanisms is thus fundamental in order to better design optimal air transport networks that benefits companies,passengers and the environment.In this review,we briefly present and discuss the state-of-the-art on time-evolving air transport networks.We distinguish the structural analysis of sequences of network snapshots,ideal for long-term network evolution（e.g.annual evolution）,and temporal paths,preferred for short-term dynamics（e.g.hourly evolution）.We emphasize that most previous research focused on the first modeling approach（i.e.long-term） whereas only a few studies look at high-resolution temporal paths.We conclude the review highlighting that much research remains to be done,both to apply already available methods and to develop new measures for temporal paths on air transport networks.In particular,we identify that the study of delays,network resilience and optimization of resources（aircraft and crew） are critical topics.展开更多
One of the major factors inhibiting the construction of deep underground projects is the risk posed by rockbursts.A study was conducted on the access tunnel of the Shuangjiangkou hydropower station to determine the ev...One of the major factors inhibiting the construction of deep underground projects is the risk posed by rockbursts.A study was conducted on the access tunnel of the Shuangjiangkou hydropower station to determine the evolutionary mechanism of microfractures within the surrounding rock mass during rockburst development and develop a rockburst warning model.The study area was chosen through the combination of field studies with an analysis of the spatial and temporal distribution of microseismic(MS)events.The moment tensor inversion method was adopted to study rockburst mechanism,and a dynamic Bayesian network(DBN)was applied to investigating the sensitivity of MS source parameters for rockburst warnings.A MS multivariable rockburst warning model was proposed and validated using two case studies.The results indicate that fractures in the surrounding rock mass during the development of strain-structure rockbursts initially show shear failure and are then followed by tensile failure.The effectiveness of the DBN-based rockburst warning model was demonstrated using self-validation and K-fold cross-validation.Moment magnitude and source radius are the most sensitive factors based on an investigation of the influence on the parent and child nodes in the model,which can serve as important standards for rockburst warnings.The proposed rockburst warning model was found to be effective when applied to two actual projects.展开更多
This paper studies local exponential synchronization of complex delayed networks with switching topology via switched system stability theory. First, by a common unitary matrix, the problem of synchronization is trans...This paper studies local exponential synchronization of complex delayed networks with switching topology via switched system stability theory. First, by a common unitary matrix, the problem of synchronization is transformed into the stability analysis of some linear switched delay systems. Then, when all subnetworks are synchronizable, a delay-dependent sufficient condition is given in terms of linear matrix inequalities （LMIs） which guarantees the solvability of the synchronization problem under an average dwell time scheme. We extend this result to the case that not all subnetworks are synchronizable. It is shown that in addition to average dwell time, if the ratio of the total activation time of synchronizable and non-synchronizable subnetworks satisfy an extra condition, then the problem is also solvable. Two numerical examples of delayed dynamical networks with switching topology are given, which demonstrate the effectiveness of obtained results.展开更多
In this article, a synchronization problem for master-slave Markovian switching complex dynamical networks with time-varying delays in nonlinear function via sliding mode control is investigated. On the basis of the a...In this article, a synchronization problem for master-slave Markovian switching complex dynamical networks with time-varying delays in nonlinear function via sliding mode control is investigated. On the basis of the appropriate Lyapunov-Krasovskii functional, introducing some free weighting matrices, new synchronization criteria are derived in terms of linear matrix inequalities （LMIs）. Then, an integral sliding surface is designed to guarantee synchronization of master-slave Markovian switching complex dynamical networks, and the suitable controller is synthesized to ensure that the trajectory of the closed-loop error system can be driven onto the prescribed sliding mode surface. By using Dynkin＇s formula, we established the stochastic stablity of master-slave system. Finally, numerical example is provided to demonstrate the effectiveness of the obtained theoretical results.展开更多
A problem of topology identification for complex dynamical networks is investigated in this paper. An adaptive observer is proposed to identify the topology of a complex dynamical networks based on the Lyapunov stabil...A problem of topology identification for complex dynamical networks is investigated in this paper. An adaptive observer is proposed to identify the topology of a complex dynamical networks based on the Lyapunov stability theory. Here the output of the network and the states of the observer are used to construct the updating law of the topology such that the communication resources from the network to its observer are saved. Some convergent criteria of the adaptive observer are derived in the form of linear inequality matrices. Several numerical examples are shown to demonstrate the effectiveness of the proposed observer.展开更多
Under unanticipated natural disasters, any failure of structure components may cause the crash of an entire structure system. Resilience is an important metric for the structure system. Although many resilience metric...Under unanticipated natural disasters, any failure of structure components may cause the crash of an entire structure system. Resilience is an important metric for the structure system. Although many resilience metrics and assessment approaches are proposed for engineering system, they are not suitable for complex structure systems, since the failure mechanisms of them are different under the influences of natural disasters. This paper proposes a novel resilience assessment metric for structure system from a macroscopic perspective, named structure resilience, and develops a corresponding assessment approach based on remaining useful life of key components. Dynamic Bayesian networks(DBNs) and Markov are applied to establish the resilience assessment model. In the degradation process, natural degradation and accelerated degradation are modelled by using Bayesian networks, and then coupled by using DBNs. In the recovery process, the model is established by combining Markov and DBNs. Subsea oil and gas pipelines are adopted to demonstrate the application of the proposed structure metric and assessment approach.展开更多
In this paper, successive lag synchronization （SLS） on a dynamical network with communication delay is investigated. In order to achieve SLS on the dynamical network with communication delay, we design linear feedba...In this paper, successive lag synchronization （SLS） on a dynamical network with communication delay is investigated. In order to achieve SLS on the dynamical network with communication delay, we design linear feedback control and adaptive control, respectively. By using the Lyapunov function method, we obtain some sufficient conditions for global stability of SLS. To verify these results, some numerical examples are further presented. This work may find potential applications in consensus of multi-agent systems.展开更多
An adaptive multi-QoS routing algorithm called AMQRA is proposed for dynamic topology networks, such as satellite networks and Ad-hoc networks. The AMQRA is a distributed and mobile-agents-based routing algorithm, whi...An adaptive multi-QoS routing algorithm called AMQRA is proposed for dynamic topology networks, such as satellite networks and Ad-hoc networks. The AMQRA is a distributed and mobile-agents-based routing algorithm, which combines ant quantity system （AQS） with ant colony optimization （ACO） that is used in AntNet routing algorithm. In dynamic topology networks, the AMQRA achieves timely optimization for concave metric QoS constraint and fast convergence. The proposed routing algorithm is simulated in Iridium satellite constellation on OPNET. The results show that AMQRA not only outperforms the AntNet in convergence rate in dynamic topology networks but also can optimize concave metric QoS constraint and reasonably allot bandwidth to the load to avoid networks congestion.展开更多
基金supported by the National Natural Science Foundation of China(Nos.61973175,62203328)the Tianjin Natural Science Foundation(Nos.20JCYBJC01060,21JCQNJC00840)the General Terminal IC Interdisciplinary Science Center of Nankai University.
文摘The outbreak of corona virus disease 2019 has profoundly affected people’s way of life.It is increasingly necessary to investigate epidemics over social networks.This paper studies susceptible-infected-removed(SIR)epidemics via the semi-tensor product.First,a formal susceptible-infected-removed epidemic dynamic model over probabilistic dynamic networks(SIRED-PDN)is given.Based on an evolutionary rule,the algebraic form for the dynamics of individual states and network topologies is given,respectively.Second,the SIRED-PDN can be described by a probabilistic mix-valued logical network.After providing an algorithm,all possible final spreading equilibria can be obtained for any given initial epidemic state and network topology by seeking attractors of the network.And the shortest time for all possible initial epidemic state and network topology profiles to evolve to the final spreading equilibria can be obtained by seeking the transient time of the network.Finally,an illustrative example is given to show the effectiveness of our model.
基金Supported by the National Natural Science Foundation of China(No.61070182,60873192)
文摘The mobility of service providers brings new features into the research of dynamic network based service composition.From an optimistic perspective,the mobility of services could benefit the optimization of service composition,if properly handled.Therefore,the impacts of node mobility on the dynamic network based service composition are investigated.Then,a movement-assisted optimization method,namely MASCO,is proposed to improve the performance of the composited services by minimizing the length of data stream and the hop-counts of the service routes in the underlying networks.The correctness and efficiency of the proposed method are then verified through theoretical analysis and computer simulations.
基金This work was supported by the National Natural Science Foundation of China （Nos. 61374065, 61503225）, the Research Fund for the Taishan Scholar Project of Shandong Province, and the Natural Science Foundation of Shandong Province （No. ZR2015FQ003）.
文摘This paper investigates epidemic dynamics over dynamic networks via the approach of semi-tensor product of matrices. First, a formal susceptible-infected-susceptible epidemic dynamic model over dynamic networks （SISED-DN） is given. Second, based on a class of determinate co-evolutionary rule, the matrix expressions are established for the dynamics of individual states and network topologies, respectively. Then, all possible final spreading equilibria are obtained for any given initial epidemic state and network topology by the matrix expression. Third, a sufficient and necessary condition of the existence of state feedback vaccination control is presented to make every individual susceptible. The study of illustrative examples shows the effectiveness of our new results.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.71801066 and 71431003)the Fundamental Research Funds for the Central Universities of China(Grant Nos.PA2019GDQT0020 and JZ2017HGTB0186)
文摘We investigate the similarities and differences among three queue rules,the first-in-first-out(FIFO)rule,last-in-firstout(LIFO)rule and random-in-random-out(RIRO)rule,on dynamical networks with limited buffer size.In our network model,nodes move at each time step.Packets are transmitted by an adaptive routing strategy,combining Euclidean distance and node load by a tunable parameter.Because of this routing strategy,at the initial stage of increasing buffer size,the network density will increase,and the packet loss rate will decrease.Packet loss and traffic congestion occur by these three rules,but nodes keep unblocked and lose no packet in a larger buffer size range on the RIRO rule networks.If packets are lost and traffic congestion occurs,different dynamic characteristics are shown by these three queue rules.Moreover,a phenomenon similar to Braess’paradox is also found by the LIFO rule and the RIRO rule.
文摘The increasing popularity of the Internet and the widespread use of information technology have led to a rise in the number and sophistication of network attacks and security threats.Intrusion detection systems are crucial to network security,playing a pivotal role in safeguarding networks from potential threats.However,in the context of an evolving landscape of sophisticated and elusive attacks,existing intrusion detection methodologies often overlook critical aspects such as changes in network topology over time and interactions between hosts.To address these issues,this paper proposes a real-time network intrusion detection method based on graph neural networks.The proposedmethod leverages the advantages of graph neural networks and employs a straightforward graph construction method to represent network traffic as dynamic graph-structured data.Additionally,a graph convolution operation with a multi-head attention mechanism is utilized to enhance the model’s ability to capture the intricate relationships within the graph structure comprehensively.Furthermore,it uses an integrated graph neural network to address dynamic graphs’structural and topological changes at different time points and the challenges of edge embedding in intrusion detection data.The edge classification problem is effectively transformed into node classification by employing a line graph data representation,which facilitates fine-grained intrusion detection tasks on dynamic graph node feature representations.The efficacy of the proposed method is evaluated using two commonly used intrusion detection datasets,UNSW-NB15 and NF-ToN-IoT-v2,and results are compared with previous studies in this field.The experimental results demonstrate that our proposed method achieves 99.3%and 99.96%accuracy on the two datasets,respectively,and outperforms the benchmark model in several evaluation metrics.
基金supported by the National Nature Science Foundation of China(71771201,72531009,71973001)the USTC Research Funds of the Double First-Class Initiative(FSSF-A-240202).
文摘Social interaction with peer pressure is widely studied in social network analysis.Game theory can be utilized to model dynamic social interaction,and one class of game network models assumes that people’s decision payoff functions hinge on individual covariates and the choices of their friends.However,peer pressure would be misidentified and induce a non-negligible bias when incomplete covariates are involved in the game model.For this reason,we develop a generalized constant peer effects model based on homogeneity structure in dynamic social networks.The new model can effectively avoid bias through homogeneity pursuit and can be applied to a wider range of scenarios.To estimate peer pressure in the model,we first present two algorithms based on the initialize expand merge method and the polynomial-time twostage method to estimate homogeneity parameters.Then we apply the nested pseudo-likelihood method and obtain consistent estimators of peer pressure.Simulation evaluations show that our proposed methodology can achieve desirable and effective results in terms of the community misclassification rate and parameter estimation error.We also illustrate the advantages of our model in the empirical analysis when compared with a benchmark model.
基金supported by the National Natural Science Foundation of China(Grant No.12231012,No.U23A20331)Key Research and Development Project in Shanxi Province,China(Grant No.202003D31011/GZ).
文摘For emerging respiratory infectious diseases like COVID-19,non-pharmaceutical interventions such as isolation are crucial for controlling the spread.From the perspective of network transmission,non-pharmaceutical interventions like isolation alter the degree distribution and other topological structures of the network,thereby controlling the spread of the infectious disease.In this paper,we establish a SEIR mean-field propagation dynamics model for the synchronous evolution of dynamic networks caused by propagation and tracing isolation.We employ the reducing-dimension method to convert the mean-field model in networks into an equivalent and simpler low-dimension model,and then calculate the exact expression of the final size.In addition,we get the differential equations of the degree distribution over time in dynamic networks under tracing isolation and the relationships between the first and second moment of the dynamic network.While the degree of a node remains constant regardless of its state in many previous studies,this paper takes into account that the degree of each node changes over time whatever its state under the disease spread and intervention measures.
基金National Natural Science Foundation of China (61773044,62073009)National key Laboratory of Science and Technology on Reliability and Environmental Engineering(WDZC2019601A301)。
文摘Delay aware routing is now widely used to provide efficient network transmission. However, for newly developing or developed mobile communication networks(MCN), only limited delay data can be obtained. In such a network, the delay is with epistemic uncertainty, which makes the traditional routing scheme based on deterministic theory or probability theory not applicable. Motivated by this problem, the MCN with epistemic uncertainty is first summarized as a dynamic uncertain network based on uncertainty theory, which is widely applied to model epistemic uncertainties. Then by modeling the uncertain end-toend delay, a new delay bounded routing scheme is proposed to find the path with the maximum belief degree that satisfies the delay threshold for the dynamic uncertain network. Finally, a lowEarth-orbit satellite communication network(LEO-SCN) is used as a case to verify the effectiveness of our routing scheme. It is first modeled as a dynamic uncertain network, and then the delay bounded paths with the maximum belief degree are computed and compared under different delay thresholds.
基金supported by the National Natural Science Foundation of China(NSFC 52432002,52372041,and 52302087)China Postdoctoral Science Foundation(Grant No.2023 M740895)+1 种基金Heilongjiang Touyan Team Programthe Fundamental Research Funds for the Central Universities(Grant No.HIT.OCEF.2021003 and HIT.DZJJ.2025002)。
文摘Aqueous Zn-metal batteries(AZMBs)performance is hampered by freezing water at low temperatures,which hampers their multi-scenario application.Hydrogen bonds(HBs)play a pivotal role in water freezing,and proton transport is indispensable for the establishment of HBs.Here,the accelerated proton transport modulates the dynamic hydrogen bonding network of a Zn(BF4)2/EMIMBF4impregnated polyacrylamide/poly(vinyl alcohol)/xanthan gum dual network eutectic gel electrolyte(PPX-ILZSE)for lowtemperature AZMBs.The PPX-ILZSE forms more HBs,shorter HBs lifetimes,higher tetrahedral entropy,and faster desolvation processes,as demonstrated by experimental and theoretical calculations.This enhanced dynamic proton transport promotes rapid cycling of HBs formation-failure,and for polyaniline cathode(PANI)abundant redox sites of proton,confers excellent low temperature electrochemical performance to the Zn//PANI full cell.Specific capacities for 1000 and 5000 cycles at 1 and 5 A g^(-1)were149.8 and 128.4 m A h g^(-1)at room temperature,respectively.Furthermore,specific capacities of 131.1 mA hg^(-1)(92.4%capacity retention)and 0.0066%capacity decay per lap were achieved for 3000and 3500 laps at-30 and 40℃,respectively,at 0.5 A g^(-1).Furthermore,in-situ protective layer of ZnOHF nano-arrays on the Zn anode surface to eliminate dendrite growth and accelerate Zn-ions adsorption and charge transfer.
基金supported by the National Natural Science Foundation of China (6057408860274014)
文摘This paper proposes second-order consensus protocols with time-delays and gives the measure of the robustness of the protocols to the time-delay existing in the network of agents with second-order dynamics. By employing a frequency domain method, it is proven that the information states and their time derivatives of all the agents in the network achieve consensus asymptotically, respectively, for appropriate communication timedelay if the topology of weighted network is connected. Particularly, a tight upper bound on the communication time-delay that can be tolerated in the dynamic network is found. The consensus protocols are distributed in the sense that each agent only needs information from its neighboring agents, which reduces the complexity of connections between neighboring agents significantly. Numerical simulation results are provided to demonstrate the effectiveness and the sharpness of the theoretical results for second-order consensus in networks in the presence of communication time-delays.
基金This work was supported by National Key Research and Development Program(2018YFB0904503)the National Natural Science Foundation of China(Grant Nos.61772456,U1866602,61761136020,U1736109).
文摘Multivariate dynamic networks indicate networks whose topology structure and vertex attributes are evolving along time.They are common in multimedia applications.Anomaly detection is one of the essential tasks in analyzing these networks though it is not well addressed.In this paper,we combine a rare category detection method and visualization techniques to help users to identify and analyze anomalies in multivariate dynamic networks.We conclude features of rare categories and two types of anomalies of rare categories.Then we present a novel rare category detection method,called DIRAD,to detect rare category candidates with anomalies.We develop a prototype system called iNet,which integrates two major visualization components,including a glyph-based rare category identifier,which helps users to identify rare categories among detected substructures,a major view,which assists users to analyze and interpret the anomalies of rare categories in network topology and vertex attributes.Evaluations,including an algorithm performance evaluation,a case study,and a user study,are conducted to test the effectiveness of proposed methods.
基金Supported by the National Natural Science Foundation of China (60574088, 60274014)
文摘This paper proposes second-order consensus protocols and gives a measure of the robustness of the protocols to the time-delays existing in the dynamics of agents with second-order dynamics. By employing a frequency domain method, it is proven that the information states achieve second-order consensus asymptotically for appropriate time-delay if the topology of the network is connected. Particularly, a nonconservative upper bound on the fixed time-delay that can be tolerated is found. The consensus protocols are distributed in the sense that each agent only needs information from its neighboring agents, which makes the proposed protocols scalable. It reduces the complexity of connections among agents significantly. Simulation results are provided to verify the effectiveness of the theoretical results for second-order consensus in networks in the presence of time-delays existing in the dynamics of agents.
基金supported by the Fonds De La Recherche Scientifique-FNRS
文摘Air transport systems are highly dynamic at temporal scales from minutes to years.This dynamic behavior not only characterizes the evolution of the system but also affect the system＇s functioning.Understanding the evolutionary mechanisms is thus fundamental in order to better design optimal air transport networks that benefits companies,passengers and the environment.In this review,we briefly present and discuss the state-of-the-art on time-evolving air transport networks.We distinguish the structural analysis of sequences of network snapshots,ideal for long-term network evolution（e.g.annual evolution）,and temporal paths,preferred for short-term dynamics（e.g.hourly evolution）.We emphasize that most previous research focused on the first modeling approach（i.e.long-term） whereas only a few studies look at high-resolution temporal paths.We conclude the review highlighting that much research remains to be done,both to apply already available methods and to develop new measures for temporal paths on air transport networks.In particular,we identify that the study of delays,network resilience and optimization of resources（aircraft and crew） are critical topics.
基金funding support from the National Natural Science Foundation of China(Grant No.42177143 and 51809221)the Science Foundation for Distinguished Young Scholars of Sichuan Province,China(Grant No.2020JDJQ0011).
文摘One of the major factors inhibiting the construction of deep underground projects is the risk posed by rockbursts.A study was conducted on the access tunnel of the Shuangjiangkou hydropower station to determine the evolutionary mechanism of microfractures within the surrounding rock mass during rockburst development and develop a rockburst warning model.The study area was chosen through the combination of field studies with an analysis of the spatial and temporal distribution of microseismic(MS)events.The moment tensor inversion method was adopted to study rockburst mechanism,and a dynamic Bayesian network(DBN)was applied to investigating the sensitivity of MS source parameters for rockburst warnings.A MS multivariable rockburst warning model was proposed and validated using two case studies.The results indicate that fractures in the surrounding rock mass during the development of strain-structure rockbursts initially show shear failure and are then followed by tensile failure.The effectiveness of the DBN-based rockburst warning model was demonstrated using self-validation and K-fold cross-validation.Moment magnitude and source radius are the most sensitive factors based on an investigation of the influence on the parent and child nodes in the model,which can serve as important standards for rockburst warnings.The proposed rockburst warning model was found to be effective when applied to two actual projects.
基金the National Natural Science Foundation of China (No.60874024, 60574013).
文摘This paper studies local exponential synchronization of complex delayed networks with switching topology via switched system stability theory. First, by a common unitary matrix, the problem of synchronization is transformed into the stability analysis of some linear switched delay systems. Then, when all subnetworks are synchronizable, a delay-dependent sufficient condition is given in terms of linear matrix inequalities （LMIs） which guarantees the solvability of the synchronization problem under an average dwell time scheme. We extend this result to the case that not all subnetworks are synchronizable. It is shown that in addition to average dwell time, if the ratio of the total activation time of synchronizable and non-synchronizable subnetworks satisfy an extra condition, then the problem is also solvable. Two numerical examples of delayed dynamical networks with switching topology are given, which demonstrate the effectiveness of obtained results.
文摘In this article, a synchronization problem for master-slave Markovian switching complex dynamical networks with time-varying delays in nonlinear function via sliding mode control is investigated. On the basis of the appropriate Lyapunov-Krasovskii functional, introducing some free weighting matrices, new synchronization criteria are derived in terms of linear matrix inequalities （LMIs）. Then, an integral sliding surface is designed to guarantee synchronization of master-slave Markovian switching complex dynamical networks, and the suitable controller is synthesized to ensure that the trajectory of the closed-loop error system can be driven onto the prescribed sliding mode surface. By using Dynkin＇s formula, we established the stochastic stablity of master-slave system. Finally, numerical example is provided to demonstrate the effectiveness of the obtained theoretical results.
基金supported in part by the National Natural Science Foundation of China (Grant Nos.60874091 and 61104103)the Natural Science Fund for Colleges and Universities in Jiangsu Province,China (Grant No.10KJB120001)the Climbing Program of Nanjing University of Posts & Telecommunications,China (Grant Nos.NY210013 and NY210014)
文摘A problem of topology identification for complex dynamical networks is investigated in this paper. An adaptive observer is proposed to identify the topology of a complex dynamical networks based on the Lyapunov stability theory. Here the output of the network and the states of the observer are used to construct the updating law of the topology such that the communication resources from the network to its observer are saved. Some convergent criteria of the adaptive observer are derived in the form of linear inequality matrices. Several numerical examples are shown to demonstrate the effectiveness of the proposed observer.
基金financially supported by the National Natural Science Foundation of China (Grant No. 51779267)the Taishan Scholars Project (Grant No. tsqn201909063)+3 种基金the Science and Technology Support Plan for Youth Innovation of Universities in Shandong Province (Grant No.2019KJB016)the National Key Research and Development Program of China (Grant No. 2019YFE0105100)the Fundamental Research Funds for the Central Universitiesthe Opening Fund of National Engineering Laboratory of Offshore Geophysical and Exploration Equipment (Grant No.20CX02301A)。
文摘Under unanticipated natural disasters, any failure of structure components may cause the crash of an entire structure system. Resilience is an important metric for the structure system. Although many resilience metrics and assessment approaches are proposed for engineering system, they are not suitable for complex structure systems, since the failure mechanisms of them are different under the influences of natural disasters. This paper proposes a novel resilience assessment metric for structure system from a macroscopic perspective, named structure resilience, and develops a corresponding assessment approach based on remaining useful life of key components. Dynamic Bayesian networks(DBNs) and Markov are applied to establish the resilience assessment model. In the degradation process, natural degradation and accelerated degradation are modelled by using Bayesian networks, and then coupled by using DBNs. In the recovery process, the model is established by combining Markov and DBNs. Subsea oil and gas pipelines are adopted to demonstrate the application of the proposed structure metric and assessment approach.
基金Project supported by the National Natural Science Foundation of China(Grant No.61004101)the Natural Science Foundation Program of Guangxi Province,China(Grant No.2015GXNSFBB139002)+1 种基金the Graduate Innovation Project of Guilin University of Electronic Technology,China(Grant No.GDYCSZ201472)the Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation,Guilin University of Electronic Technology,China
文摘In this paper, successive lag synchronization （SLS） on a dynamical network with communication delay is investigated. In order to achieve SLS on the dynamical network with communication delay, we design linear feedback control and adaptive control, respectively. By using the Lyapunov function method, we obtain some sufficient conditions for global stability of SLS. To verify these results, some numerical examples are further presented. This work may find potential applications in consensus of multi-agent systems.
基金the National Natural Science Foundation of China (60532030)
文摘An adaptive multi-QoS routing algorithm called AMQRA is proposed for dynamic topology networks, such as satellite networks and Ad-hoc networks. The AMQRA is a distributed and mobile-agents-based routing algorithm, which combines ant quantity system （AQS） with ant colony optimization （ACO） that is used in AntNet routing algorithm. In dynamic topology networks, the AMQRA achieves timely optimization for concave metric QoS constraint and fast convergence. The proposed routing algorithm is simulated in Iridium satellite constellation on OPNET. The results show that AMQRA not only outperforms the AntNet in convergence rate in dynamic topology networks but also can optimize concave metric QoS constraint and reasonably allot bandwidth to the load to avoid networks congestion.
