In recent years,with the rapid growth of social network services(SNS),social networks pervade nearly every aspect of our daily lives.Social networks are influencing today’s societal and cultural issues,and changing t...In recent years,with the rapid growth of social network services(SNS),social networks pervade nearly every aspect of our daily lives.Social networks are influencing today’s societal and cultural issues,and changing the way of people seeing themselves.To fully understand the running mechanisms of social networks,in this paper,we aim at series of high knitted and important elements of online social networks.We mainly focus on 3 important but also open research problems,they are(1)structural properties and evolving laws,(2)social crowds and their interaction behaviors and(3)information and its diffusion.In this paper,we review the related work on the 3 problems.Then,we briefly introduce some interesting research directions and our progress on these research problems.展开更多
The ability to overcome the negative effects,induced by obstacles and turbulent atmosphere,is a core challenge of long-distance information transmission,and it is of great significance in free-space optical communicat...The ability to overcome the negative effects,induced by obstacles and turbulent atmosphere,is a core challenge of long-distance information transmission,and it is of great significance in free-space optical communication.The spatial-coherence structure,that characterizes partially coherent fields,provides a new degree of freedom for carrying information.However,due to the influence of the complex transmission environment,the spatial-coherence structure is severely damaged during the propagation path,which undoubtedly limits its ability to transmit information.Here,we realize the robust far-field orbital angular momentum(OAM)transmission and detection by modulating the spatial-coherence structure of a partially coherent vortex beam with the help of the cross-phase.The cross-phase enables the OAM information,quantified by the topological charge,hidden in the spatial-coherence structure can be stably transmitted to the far field and can resist the influence of obstructions and turbulence within the communication link.This is due to the self-reconstruction property of the spatial-coherence structure embedded with the cross-phase.We demonstrate experimentally that the topological charge information can be recognized well by measuring the spatial-coherence structure in the far field,exhibiting a set of distinct and separated dark rings even under amplitude and phase perturbations.Our findings open a door for robust optical signal transmission through the complex environment and may find application in optical communication through a turbulent atmosphere.展开更多
This paper presents a novel fault detection and identification method for low-voltage direct current(DC)microgrid with meshed configuration.The proposed method is based on graph convolutional network(GCN),which utiliz...This paper presents a novel fault detection and identification method for low-voltage direct current(DC)microgrid with meshed configuration.The proposed method is based on graph convolutional network(GCN),which utilizes the explicit spatial information and measurement data of the network topology to identify a fault.It has a more substantial feature extraction ability even in the presence of noise and bad data.The adjacency matrix for GCN is developed by considering the network topology as an inherent graph.The bus voltage and line current samples after faults are regarded as the node attributes.Moreover,the DC microgrid model is developed using PSCAD/EMTDC simulation,and fault simulation is carried out by considering different possible events that include environmental and physical conditions.The performance of the proposed method under different conditions is compared with those of different machine learning techniques such as convolutional neural network(CNN),support vector machine(SVM),and fully connected network(FCN).The results reveal that the proposed method is more effective than others at detecting and classifying faults.This method also possesses better robustness under the presence of noise and bad data.展开更多
基金supported by National BasicResearch Program of China(2013CB329601 and 2013CB329606)the National Natural Science Foundation of China(91124002,61372191,and 61303190)
文摘In recent years,with the rapid growth of social network services(SNS),social networks pervade nearly every aspect of our daily lives.Social networks are influencing today’s societal and cultural issues,and changing the way of people seeing themselves.To fully understand the running mechanisms of social networks,in this paper,we aim at series of high knitted and important elements of online social networks.We mainly focus on 3 important but also open research problems,they are(1)structural properties and evolving laws,(2)social crowds and their interaction behaviors and(3)information and its diffusion.In this paper,we review the related work on the 3 problems.Then,we briefly introduce some interesting research directions and our progress on these research problems.
基金National Key Research and Development Program of China (2022YFA1404800,2019YFA0705000)National Natural Science Foundation of China (12104264,12192254,92250304,and 12374311)+2 种基金China Postdoctoral Science Foundation (2022T150392)Natural Science Foundation of Shandong Province (ZR2021QA014 and ZR2023YQ006)Qingchuang Science and Technology Plan of Shandong Province (2022KJ246).
文摘The ability to overcome the negative effects,induced by obstacles and turbulent atmosphere,is a core challenge of long-distance information transmission,and it is of great significance in free-space optical communication.The spatial-coherence structure,that characterizes partially coherent fields,provides a new degree of freedom for carrying information.However,due to the influence of the complex transmission environment,the spatial-coherence structure is severely damaged during the propagation path,which undoubtedly limits its ability to transmit information.Here,we realize the robust far-field orbital angular momentum(OAM)transmission and detection by modulating the spatial-coherence structure of a partially coherent vortex beam with the help of the cross-phase.The cross-phase enables the OAM information,quantified by the topological charge,hidden in the spatial-coherence structure can be stably transmitted to the far field and can resist the influence of obstructions and turbulence within the communication link.This is due to the self-reconstruction property of the spatial-coherence structure embedded with the cross-phase.We demonstrate experimentally that the topological charge information can be recognized well by measuring the spatial-coherence structure in the far field,exhibiting a set of distinct and separated dark rings even under amplitude and phase perturbations.Our findings open a door for robust optical signal transmission through the complex environment and may find application in optical communication through a turbulent atmosphere.
文摘This paper presents a novel fault detection and identification method for low-voltage direct current(DC)microgrid with meshed configuration.The proposed method is based on graph convolutional network(GCN),which utilizes the explicit spatial information and measurement data of the network topology to identify a fault.It has a more substantial feature extraction ability even in the presence of noise and bad data.The adjacency matrix for GCN is developed by considering the network topology as an inherent graph.The bus voltage and line current samples after faults are regarded as the node attributes.Moreover,the DC microgrid model is developed using PSCAD/EMTDC simulation,and fault simulation is carried out by considering different possible events that include environmental and physical conditions.The performance of the proposed method under different conditions is compared with those of different machine learning techniques such as convolutional neural network(CNN),support vector machine(SVM),and fully connected network(FCN).The results reveal that the proposed method is more effective than others at detecting and classifying faults.This method also possesses better robustness under the presence of noise and bad data.
