Power Line Communications-Artificial Intelligence of Things(PLC-AIo T)combines the low cost and high coverage of PLC with the learning ability of Artificial Intelligence(AI)to provide data collection and transmission ...Power Line Communications-Artificial Intelligence of Things(PLC-AIo T)combines the low cost and high coverage of PLC with the learning ability of Artificial Intelligence(AI)to provide data collection and transmission capabilities for PLC-AIo T devices in smart parks.With the development of smart parks,their emerging services require secure and accurate time synchronization of PLC-AIo T devices.However,the impact of attackers on the accuracy of time synchronization cannot be ignored.To solve the aforementioned problems,we propose a tampering attack-aware Deep Q-Network(DQN)-based time synchronization algorithm.First,we construct an abnormal clock source detection model.Then,the abnormal clock source is detected and excluded by comparing the time synchronization information between the device and the gateway.Finally,the proposed algorithm realizes the joint guarantee of high accuracy and low delay for PLC-AIo T in smart parks by intelligently selecting the multi-clock source cooperation strategy and timing weights.Simulation results show that the proposed algorithm has better time synchronization delay and accuracy performance.展开更多
The detection of software vulnerabilities written in C and C++languages takes a lot of attention and interest today.This paper proposes a new framework called DrCSE to improve software vulnerability detection.It uses ...The detection of software vulnerabilities written in C and C++languages takes a lot of attention and interest today.This paper proposes a new framework called DrCSE to improve software vulnerability detection.It uses an intelligent computation technique based on the combination of two methods:Rebalancing data and representation learning to analyze and evaluate the code property graph(CPG)of the source code for detecting abnormal behavior of software vulnerabilities.To do that,DrCSE performs a combination of 3 main processing techniques:(i)building the source code feature profiles,(ii)rebalancing data,and(iii)contrastive learning.In which,the method(i)extracts the source code’s features based on the vertices and edges of the CPG.The method of rebalancing data has the function of supporting the training process by balancing the experimental dataset.Finally,contrastive learning techniques learn the important features of the source code by finding and pulling similar ones together while pushing the outliers away.The experiment part of this paper demonstrates the superiority of the DrCSE Framework for detecting source code security vulnerabilities using the Verum dataset.As a result,the method proposed in the article has brought a pretty good performance in all metrics,especially the Precision and Recall scores of 39.35%and 69.07%,respectively,proving the efficiency of the DrCSE Framework.It performs better than other approaches,with a 5%boost in Precision and a 5%boost in Recall.Overall,this is considered the best research result for the software vulnerability detection problem using the Verum dataset according to our survey to date.展开更多
A room-temperature broadly tunable mid-infrared difference frequency laser source for highly sensitive trace gas detection has been developed recently in our laboratory. The mid-infrared laser system is based on quasi...A room-temperature broadly tunable mid-infrared difference frequency laser source for highly sensitive trace gas detection has been developed recently in our laboratory. The mid-infrared laser system is based on quasi-phase-matched （QPM） difference frequency generation （DFG） in a multigrating, temperature-controlled periodically poled LiNbO3 （PPLN） crystal and employs two near-infrared diode lasers as pump sources. The mid-infrared coherent radiation generated is tunable from 3.2 μm to 3.7μm with an output power of about 100 μW. By changing one of the pump laser head with another wavelength range, we can readily obtain other needed mid-infrared wavelength range cover. The performance of the mid-infrared laser system and its application to highly sensitive spectroscopic detection of CH4, HCl, CH2O, and NO2 has been carried out. A multi-reflection White cell was used in the experiment gaining ppb-level sensitivity. The DFG laser system has the features of compact, room-temperature operation, narrow line-width, and broadly continuous tunable range for potential applications in industry and environmental monitoring.展开更多
This study focuses on the detection of infection sources in dynamic networks,which is very important for network analysis,cybersecurity,and public health.We aim to improve source detection in complex networks using da...This study focuses on the detection of infection sources in dynamic networks,which is very important for network analysis,cybersecurity,and public health.We aim to improve source detection in complex networks using data,computational advances,and machine learning to improve epidemic response and public health protection.We explore dynamic network analysis and recent algorithms for infection source detection,emphasizing data integration and machine learning.Our approach involves reviewing existing research,identifying gaps,and proposing dynamic network-based infectious disease source detection strategies.Our study highlights evolving infection source detection methods and underscores the potential of machine learning and artificial intelligence.We acknowledge ongoing challenges due to network complexity and outline promising research directions.Detecting infection sources in dynamic networks is vital.This study emphasizes the need for improved techniques and technology integration to address complexities effectively.Advancements will empower us to identify and mitigate epidemics,reducing their societal and public health impacts.展开更多
Purpose The Einstein Probe(EP)is a space X-ray mission dedicated to the time-domain astrophysics,aiming to discover high-energy transients and monitor variable objects.As a principal scientific payload onboard EP,the ...Purpose The Einstein Probe(EP)is a space X-ray mission dedicated to the time-domain astrophysics,aiming to discover high-energy transients and monitor variable objects.As a principal scientific payload onboard EP,the Follow-up X-ray Telescope(FXT)mainly responses for prompt and deep follow-up observations of the triggered targets by EP-WXT and discovers and characterizes X-ray transients,particularly faint or distant X-ray transients.Since these transient signals fade rapidly or evolve dramatically,a fast and reliable analysis of the FXT data is essential to discover them and trigger timely and efficient follow-up observations,which is important to identify the nature of these sources.Methods To address this issue,we develop a real-time source search toolkit to automatically process EP-FXT observations in real time,detecting all the sources in the field of view of FXT,extracting their scientific information,and searching for transients and bursts.Accordingly,the toolkit consists of three modules:source detection,source information extraction,and source identification.Results The toolkit outcomes a quick-look database:1)a series of high-level scientific products for every observed source,such as the position,count rate,flux,variability amplitude,hardness,light curve,an absorbed powerlaw or blackbody model fitted spectrum,and the power density spectrum;2)transients and bursts;3)source list;4)sky map.As the software is automatically running,this quick-look database is continuously updated.Conclusion The real-time source search toolkit can process all the observed data and effectively meets the fast source search requirements of FXT.展开更多
Due to the prevalence of social network services, more and more attentions are paid to explore how information diffuses and users affect each other in these networks, which has a wide range of applications, such as vi...Due to the prevalence of social network services, more and more attentions are paid to explore how information diffuses and users affect each other in these networks, which has a wide range of applications, such as viral marketing, reposting prediction and social recommendation. Therefore, in this paper, we review the recent advances on information diffusion analysis in social networks and its applications. Specifically, we first shed light on several popular models to describe the information diffusion process in social networks, which enables three practical applications, i.e., influence evaluation, influence maximization and information source detection. Then, we discuss how to evaluate the authority and influence based on network structures. After that, current solutions to influence maximiza- tion and information source detection are discussed in detail, respectively. Finally, some possible research directions of information diffu- sion analysis are listed for further study.展开更多
A new short-term optimal control of air quality in an industrial region during atmospheric inversions is proposed.lts goal is to prevent violation of health standard of air quality in a few monitored zones.The control...A new short-term optimal control of air quality in an industrial region during atmospheric inversions is proposed.lts goal is to prevent violation of health standard of air quality in a few monitored zones.The control establishes restrictions on the emission rates of industrial sources and includes the identification of the industrial sources violating(exceeding)the emission rates set by the control.Both control and identification are based on using solutions to an adjoint dispersion model.Conditions that show the convergence of the emission rates,prescribed by the control,to the original emission rates of the industrial sources are given(Theorems 4 and 5).These results ensure that the new emission rates of industrial sources(established by the control)will be as close as possible to the original emission rates throughout the entire period of application of the control.This creates the minimum possible restrictions on the functioning of industrial enterprises.The highlight of the new control is the possibility of selecting special weights for each pollution source in the goal function that is minimized.These weights are mainly aimed at reducing the intensity of emissions of the main sources of pollution.An example demonstrates the ability of the new method.A similar approach can also be used to develop methods for cleaning water zones polluted by oil(the problem of bioremediation),and to prevent excessive pollution of urban areas with automobile emissions.展开更多
Based on advantages of technology of distributive fiber-optic temperature sensing and specific to its applications in monitoring mine conflagration, the corresponding Processes such as connection arrangement, signal t...Based on advantages of technology of distributive fiber-optic temperature sensing and specific to its applications in monitoring mine conflagration, the corresponding Processes such as connection arrangement, signal transmission and monitoring were illustrated. As applied in Sitai Coal Mine of Datong Coal Mine Group Co., this method is effective and accurate and could provide reliable gist for monitoring spontaneous combustion in gob area of mines.展开更多
In this paper,a low complexity ESPRIT algorithm based on power method and Orthogo- nal-triangular (QR) decomposition is presented for direction finding,which does not require a priori knowledge of source number and th...In this paper,a low complexity ESPRIT algorithm based on power method and Orthogo- nal-triangular (QR) decomposition is presented for direction finding,which does not require a priori knowledge of source number and the predetermined threshold (separates the signal and noise ei- gen-values).Firstly,according to the estimation of noise subspace obtained by the power method,a novel source number detection method without eigen-decomposition is proposed based on QR de- composition.Furthermore,the eigenvectors of signal subspace can be determined according to Q matrix and then the directions of signals could be computed by the ESPRIT algorithm.To determine the source number and subspace,the computation complexity of the proposed algorithm is approximated as (2log_2 n+2.67)M^3,where n is the power of covariance matrix and M is the number of array ele- ments.Compared with the Single Vector Decomposition (SVD) based algorithm,it has a substantial computational saving with the approximation performance.The simulation results demonstrate its effectiveness and robustness.展开更多
The safety of rail is very important for the development of high speed railway, and it is necessary to investigate the features of inner cracks in rail. In order to obtain the features of Acoustic Emission （AE） sour...The safety of rail is very important for the development of high speed railway, and it is necessary to investigate the features of inner cracks in rail. In order to obtain the features of Acoustic Emission （AE） sources of inner cracks in rail, AE sources with different types, depths and propagation distances are examined for crack in rail. The finite element method is utilized to model the rail with cracks and the results of experiment demonstrate the effectiveness of this model. Wavelet transform and Rayleigh-Lamb equations are utilized to extract the features of crack AE sources. The results illustrate that the intensity ratio among AE modes can identify the AE source types and the AE sources with different frequencies in rail. There are uniform AE mode features existing in the AE signals from AE sources in rail web, however AE signals from AE sources in rail head and rail base have the complex and unstable AE modes. Different AE source types have the different propagation features in rail. It is helpful to understand the rail cracks and detect the rail cracks based on the AE technique.展开更多
Aiming to the estimation of source numbers, mixing matrix and separation of mixing signals under underdetermined case, the article puts forward a method of underdetermined blind source separation （UBSS） with an appl...Aiming to the estimation of source numbers, mixing matrix and separation of mixing signals under underdetermined case, the article puts forward a method of underdetermined blind source separation （UBSS） with an application in ultra-wideband （UWB） communication signals. The method is based on the sparse characteristic of UWB communication signals in the time domain. Firstly, finding the single source area by calculating the ratio of observed sampling points. Then an algorithm called hough-windowed method was introduced to estimate the number of sources and mixing matrix. Finally the separation of mixing signals using a method based on amended subspace projection. The simulation results indicate that the proposed method can separate UWB communication signals successfully, estimate the mixing matrix with higher accuracy and separate the mixing signals with higher gain compared with other conventional algorithms. At the same time, the method reflects the higher stability and the better noise immunity.展开更多
基金supported by the Science and Technology Project of the State Grid Corporation of China under Grant Number 5400202199541A-0-5-ZN。
文摘Power Line Communications-Artificial Intelligence of Things(PLC-AIo T)combines the low cost and high coverage of PLC with the learning ability of Artificial Intelligence(AI)to provide data collection and transmission capabilities for PLC-AIo T devices in smart parks.With the development of smart parks,their emerging services require secure and accurate time synchronization of PLC-AIo T devices.However,the impact of attackers on the accuracy of time synchronization cannot be ignored.To solve the aforementioned problems,we propose a tampering attack-aware Deep Q-Network(DQN)-based time synchronization algorithm.First,we construct an abnormal clock source detection model.Then,the abnormal clock source is detected and excluded by comparing the time synchronization information between the device and the gateway.Finally,the proposed algorithm realizes the joint guarantee of high accuracy and low delay for PLC-AIo T in smart parks by intelligently selecting the multi-clock source cooperation strategy and timing weights.Simulation results show that the proposed algorithm has better time synchronization delay and accuracy performance.
文摘The detection of software vulnerabilities written in C and C++languages takes a lot of attention and interest today.This paper proposes a new framework called DrCSE to improve software vulnerability detection.It uses an intelligent computation technique based on the combination of two methods:Rebalancing data and representation learning to analyze and evaluate the code property graph(CPG)of the source code for detecting abnormal behavior of software vulnerabilities.To do that,DrCSE performs a combination of 3 main processing techniques:(i)building the source code feature profiles,(ii)rebalancing data,and(iii)contrastive learning.In which,the method(i)extracts the source code’s features based on the vertices and edges of the CPG.The method of rebalancing data has the function of supporting the training process by balancing the experimental dataset.Finally,contrastive learning techniques learn the important features of the source code by finding and pulling similar ones together while pushing the outliers away.The experiment part of this paper demonstrates the superiority of the DrCSE Framework for detecting source code security vulnerabilities using the Verum dataset.As a result,the method proposed in the article has brought a pretty good performance in all metrics,especially the Precision and Recall scores of 39.35%and 69.07%,respectively,proving the efficiency of the DrCSE Framework.It performs better than other approaches,with a 5%boost in Precision and a 5%boost in Recall.Overall,this is considered the best research result for the software vulnerability detection problem using the Verum dataset according to our survey to date.
基金supported by National Natural Science Foundation of China under Grant No. 50534050the Key Project of the Chinese Academy of Sciences under Grant No. KJCX2-SW-W27.
文摘A room-temperature broadly tunable mid-infrared difference frequency laser source for highly sensitive trace gas detection has been developed recently in our laboratory. The mid-infrared laser system is based on quasi-phase-matched （QPM） difference frequency generation （DFG） in a multigrating, temperature-controlled periodically poled LiNbO3 （PPLN） crystal and employs two near-infrared diode lasers as pump sources. The mid-infrared coherent radiation generated is tunable from 3.2 μm to 3.7μm with an output power of about 100 μW. By changing one of the pump laser head with another wavelength range, we can readily obtain other needed mid-infrared wavelength range cover. The performance of the mid-infrared laser system and its application to highly sensitive spectroscopic detection of CH4, HCl, CH2O, and NO2 has been carried out. A multi-reflection White cell was used in the experiment gaining ppb-level sensitivity. The DFG laser system has the features of compact, room-temperature operation, narrow line-width, and broadly continuous tunable range for potential applications in industry and environmental monitoring.
文摘This study focuses on the detection of infection sources in dynamic networks,which is very important for network analysis,cybersecurity,and public health.We aim to improve source detection in complex networks using data,computational advances,and machine learning to improve epidemic response and public health protection.We explore dynamic network analysis and recent algorithms for infection source detection,emphasizing data integration and machine learning.Our approach involves reviewing existing research,identifying gaps,and proposing dynamic network-based infectious disease source detection strategies.Our study highlights evolving infection source detection methods and underscores the potential of machine learning and artificial intelligence.We acknowledge ongoing challenges due to network complexity and outline promising research directions.Detecting infection sources in dynamic networks is vital.This study emphasizes the need for improved techniques and technology integration to address complexities effectively.Advancements will empower us to identify and mitigate epidemics,reducing their societal and public health impacts.
基金supported by the Einstein Probe(EP)Program which is funded by the Strategic Priority Research Program of the Chinese Academy of Sciences Grant No.XDA15310303the National Natural Science Foundation of China under Grant No.U2038102,U1938102.
文摘Purpose The Einstein Probe(EP)is a space X-ray mission dedicated to the time-domain astrophysics,aiming to discover high-energy transients and monitor variable objects.As a principal scientific payload onboard EP,the Follow-up X-ray Telescope(FXT)mainly responses for prompt and deep follow-up observations of the triggered targets by EP-WXT and discovers and characterizes X-ray transients,particularly faint or distant X-ray transients.Since these transient signals fade rapidly or evolve dramatically,a fast and reliable analysis of the FXT data is essential to discover them and trigger timely and efficient follow-up observations,which is important to identify the nature of these sources.Methods To address this issue,we develop a real-time source search toolkit to automatically process EP-FXT observations in real time,detecting all the sources in the field of view of FXT,extracting their scientific information,and searching for transients and bursts.Accordingly,the toolkit consists of three modules:source detection,source information extraction,and source identification.Results The toolkit outcomes a quick-look database:1)a series of high-level scientific products for every observed source,such as the position,count rate,flux,variability amplitude,hardness,light curve,an absorbed powerlaw or blackbody model fitted spectrum,and the power density spectrum;2)transients and bursts;3)source list;4)sky map.As the software is automatically running,this quick-look database is continuously updated.Conclusion The real-time source search toolkit can process all the observed data and effectively meets the fast source search requirements of FXT.
基金supported by National Natural Science Foundation of China(Nos.61703386,U1605251 and91546103)the Anhui Provincial Natural Science Foundation(No.1708085QF140)+1 种基金the Fundamental Research Funds for the Central Universities(No.WK2150110006)the Youth Innovation Promotion Association of Chinese Academy of Sciences(No.2014299)
文摘Due to the prevalence of social network services, more and more attentions are paid to explore how information diffuses and users affect each other in these networks, which has a wide range of applications, such as viral marketing, reposting prediction and social recommendation. Therefore, in this paper, we review the recent advances on information diffusion analysis in social networks and its applications. Specifically, we first shed light on several popular models to describe the information diffusion process in social networks, which enables three practical applications, i.e., influence evaluation, influence maximization and information source detection. Then, we discuss how to evaluate the authority and influence based on network structures. After that, current solutions to influence maximiza- tion and information source detection are discussed in detail, respectively. Finally, some possible research directions of information diffu- sion analysis are listed for further study.
基金This work was supported by the National System of Researcher of Mexico(SNI,CONACyT)(Nos.14539,25170).
文摘A new short-term optimal control of air quality in an industrial region during atmospheric inversions is proposed.lts goal is to prevent violation of health standard of air quality in a few monitored zones.The control establishes restrictions on the emission rates of industrial sources and includes the identification of the industrial sources violating(exceeding)the emission rates set by the control.Both control and identification are based on using solutions to an adjoint dispersion model.Conditions that show the convergence of the emission rates,prescribed by the control,to the original emission rates of the industrial sources are given(Theorems 4 and 5).These results ensure that the new emission rates of industrial sources(established by the control)will be as close as possible to the original emission rates throughout the entire period of application of the control.This creates the minimum possible restrictions on the functioning of industrial enterprises.The highlight of the new control is the possibility of selecting special weights for each pollution source in the goal function that is minimized.These weights are mainly aimed at reducing the intensity of emissions of the main sources of pollution.An example demonstrates the ability of the new method.A similar approach can also be used to develop methods for cleaning water zones polluted by oil(the problem of bioremediation),and to prevent excessive pollution of urban areas with automobile emissions.
基金Supported by the National Natural Science Foundation of China （50375026,50375028）
文摘Based on advantages of technology of distributive fiber-optic temperature sensing and specific to its applications in monitoring mine conflagration, the corresponding Processes such as connection arrangement, signal transmission and monitoring were illustrated. As applied in Sitai Coal Mine of Datong Coal Mine Group Co., this method is effective and accurate and could provide reliable gist for monitoring spontaneous combustion in gob area of mines.
基金Supported by the National Natural Science Foundation of China (No.60102005).
文摘In this paper,a low complexity ESPRIT algorithm based on power method and Orthogo- nal-triangular (QR) decomposition is presented for direction finding,which does not require a priori knowledge of source number and the predetermined threshold (separates the signal and noise ei- gen-values).Firstly,according to the estimation of noise subspace obtained by the power method,a novel source number detection method without eigen-decomposition is proposed based on QR de- composition.Furthermore,the eigenvectors of signal subspace can be determined according to Q matrix and then the directions of signals could be computed by the ESPRIT algorithm.To determine the source number and subspace,the computation complexity of the proposed algorithm is approximated as (2log_2 n+2.67)M^3,where n is the power of covariance matrix and M is the number of array ele- ments.Compared with the Single Vector Decomposition (SVD) based algorithm,it has a substantial computational saving with the approximation performance.The simulation results demonstrate its effectiveness and robustness.
基金supported by the China Scholarship Council,the National Natural Science Foundation of China(61171197,61201307,61371045)the Innovation Funds of Harbin Institute of Technology(Grant IDGA18102011)the Promotive Research Fund for Excellent Young and Middle-Aged Scientisits of Shandong Province(BS2010DX001)
文摘The safety of rail is very important for the development of high speed railway, and it is necessary to investigate the features of inner cracks in rail. In order to obtain the features of Acoustic Emission （AE） sources of inner cracks in rail, AE sources with different types, depths and propagation distances are examined for crack in rail. The finite element method is utilized to model the rail with cracks and the results of experiment demonstrate the effectiveness of this model. Wavelet transform and Rayleigh-Lamb equations are utilized to extract the features of crack AE sources. The results illustrate that the intensity ratio among AE modes can identify the AE source types and the AE sources with different frequencies in rail. There are uniform AE mode features existing in the AE signals from AE sources in rail web, however AE signals from AE sources in rail head and rail base have the complex and unstable AE modes. Different AE source types have the different propagation features in rail. It is helpful to understand the rail cracks and detect the rail cracks based on the AE technique.
基金supported by the National Natural Science Foundation of China (61172038, 60831001)
文摘Aiming to the estimation of source numbers, mixing matrix and separation of mixing signals under underdetermined case, the article puts forward a method of underdetermined blind source separation （UBSS） with an application in ultra-wideband （UWB） communication signals. The method is based on the sparse characteristic of UWB communication signals in the time domain. Firstly, finding the single source area by calculating the ratio of observed sampling points. Then an algorithm called hough-windowed method was introduced to estimate the number of sources and mixing matrix. Finally the separation of mixing signals using a method based on amended subspace projection. The simulation results indicate that the proposed method can separate UWB communication signals successfully, estimate the mixing matrix with higher accuracy and separate the mixing signals with higher gain compared with other conventional algorithms. At the same time, the method reflects the higher stability and the better noise immunity.
