This paper examines the effect of the observation time on source identification of a discrete-time susceptible-infectedrecovered diffusion process in a network with snapshot of partial nodes.We formulate the source id...This paper examines the effect of the observation time on source identification of a discrete-time susceptible-infectedrecovered diffusion process in a network with snapshot of partial nodes.We formulate the source identification problem as a maximum likelihood(ML)estimator and develop a statistical inference method based on Monte Carlo simulation(MCS)to estimate the source location and the initial time of diffusion.Experimental results in synthetic networks and real-world networks demonstrate evident impact of the observation time as well as the fraction of the observers on the concerned problem.展开更多
The dissemination of information across various locations is an ubiquitous occurrence,however,prevalent methodologies for multi-source identification frequently overlook the fact that sources may initiate disseminatio...The dissemination of information across various locations is an ubiquitous occurrence,however,prevalent methodologies for multi-source identification frequently overlook the fact that sources may initiate dissemination at distinct initial moments.Although there are many research results of multi-source identification,the challenge of locating sources with varying initiation times using a limited subset of observational nodes remains unresolved.In this study,we provide the backward spread tree theorem and source centrality theorem,and develop a backward spread centrality algorithm to identify all the information sources that trigger the spread at different start times.The proposed algorithm does not require prior knowledge of the number of sources,however,it can estimate both the initial spread moment and the spread duration.The core concept of this algorithm involves inferring suspected sources through source centrality theorem and locating the source from the suspected sources with linear programming.Extensive experiments from synthetic and real network simulation corroborate the superiority of our method in terms of both efficacy and efficiency.Furthermore,we find that our method maintains robustness irrespective of the number of sources and the average degree of network.Compared with classical and state-of-the art source identification methods,our method generally improves the AUROC value by 0.1 to 0.2.展开更多
Passengers’demands for riding comfort have been getting higher and higher as the high-speed railway develops.Scientific methods to analyze the interior noise of the high-speed train are needed and the operational tra...Passengers’demands for riding comfort have been getting higher and higher as the high-speed railway develops.Scientific methods to analyze the interior noise of the high-speed train are needed and the operational transfer path analysis(OTPA)method provides a theoretical basis and guidance for the noise control of the train and overcomes the shortcomings of the traditional method,which has high test efficiency and can be carried out during the working state of the targeted machine.The OTPA model is established from the aspects of“path reference point-target point”and“sound source reference point-target point”.As for the mechanism of the noise transmission path,an assumption is made that the direct sound propagation is ignored,and the symmetric sound source and the symmetric path are merged.Using the operational test data and the OTPA method,combined with the results of spherical array sound source identification,the path contribution and sound source contribution of the interior noise are analyzed,respectively,from aspects of the total value and spectrum.The results show that the OTPA conforms to the calculation results of the spherical array sound source identification.At low speed,the contribution of the floor path and the contribution of the bogie sources are dominant.When the speed is greater than 300 km/h,the contribution of the roof path is dominant.Moreover,for the carriage with a pantograph,the lifted pantograph is an obvious source.The noise from the exterior sources of the train transfer into the interior mainly through the form of structural excitation,and the contribution of air excitation is non-significant.Certain analyses of train parts provide guides for the interior noise control.展开更多
基金the National Natural Science Foundation of China(Grant Nos.61673027 and 62106047)the Beijing Social Science Foundation(Grant No.21GLC042)the Humanity and Social Science Youth foundation of Ministry of Education,China(Grant No.20YJCZH228)。
文摘This paper examines the effect of the observation time on source identification of a discrete-time susceptible-infectedrecovered diffusion process in a network with snapshot of partial nodes.We formulate the source identification problem as a maximum likelihood(ML)estimator and develop a statistical inference method based on Monte Carlo simulation(MCS)to estimate the source location and the initial time of diffusion.Experimental results in synthetic networks and real-world networks demonstrate evident impact of the observation time as well as the fraction of the observers on the concerned problem.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.62103375,62006106,61877055,and 62171413)the Philosophy and Social Science Planning Project of Zhejinag Province,China(Grant No.22NDJC009Z)+1 种基金the Education Ministry Humanities and Social Science Foundation of China(Grant No.19YJCZH056)the Natural Science Foundation of Zhejiang Province,China(Grant Nos.LY23F030003,LY22F030006,and LQ21F020005).
文摘The dissemination of information across various locations is an ubiquitous occurrence,however,prevalent methodologies for multi-source identification frequently overlook the fact that sources may initiate dissemination at distinct initial moments.Although there are many research results of multi-source identification,the challenge of locating sources with varying initiation times using a limited subset of observational nodes remains unresolved.In this study,we provide the backward spread tree theorem and source centrality theorem,and develop a backward spread centrality algorithm to identify all the information sources that trigger the spread at different start times.The proposed algorithm does not require prior knowledge of the number of sources,however,it can estimate both the initial spread moment and the spread duration.The core concept of this algorithm involves inferring suspected sources through source centrality theorem and locating the source from the suspected sources with linear programming.Extensive experiments from synthetic and real network simulation corroborate the superiority of our method in terms of both efficacy and efficiency.Furthermore,we find that our method maintains robustness irrespective of the number of sources and the average degree of network.Compared with classical and state-of-the art source identification methods,our method generally improves the AUROC value by 0.1 to 0.2.
文摘Passengers’demands for riding comfort have been getting higher and higher as the high-speed railway develops.Scientific methods to analyze the interior noise of the high-speed train are needed and the operational transfer path analysis(OTPA)method provides a theoretical basis and guidance for the noise control of the train and overcomes the shortcomings of the traditional method,which has high test efficiency and can be carried out during the working state of the targeted machine.The OTPA model is established from the aspects of“path reference point-target point”and“sound source reference point-target point”.As for the mechanism of the noise transmission path,an assumption is made that the direct sound propagation is ignored,and the symmetric sound source and the symmetric path are merged.Using the operational test data and the OTPA method,combined with the results of spherical array sound source identification,the path contribution and sound source contribution of the interior noise are analyzed,respectively,from aspects of the total value and spectrum.The results show that the OTPA conforms to the calculation results of the spherical array sound source identification.At low speed,the contribution of the floor path and the contribution of the bogie sources are dominant.When the speed is greater than 300 km/h,the contribution of the roof path is dominant.Moreover,for the carriage with a pantograph,the lifted pantograph is an obvious source.The noise from the exterior sources of the train transfer into the interior mainly through the form of structural excitation,and the contribution of air excitation is non-significant.Certain analyses of train parts provide guides for the interior noise control.
