A Reconfigurable Intelligent Surface(RIS)can relay signals from the transmitter to the receiver.In this regard,RISs operate similarly to traditional relays.We design a Multiple-Input-Multiple-Output(MIMO)system with a...A Reconfigurable Intelligent Surface(RIS)can relay signals from the transmitter to the receiver.In this regard,RISs operate similarly to traditional relays.We design a Multiple-Input-Multiple-Output(MIMO)system with a hybrid network of RIS and Half-Duplex(HD)Amplify-and-Forward(AF)relay.We model the system’s signal propagation and propose a new algorithm to get the system’s Achievable Rate(AR)value.We complete simulations to evaluate the performance of the RIS and HD-AF relay hybrid network system compared to the system assisted by either the RIS or HD-AF relay.The simulations indicate that many factors can considerably influence the system performance.Selecting an optimal placement for the RIS and relay can result in the best performance for the RIS and HD-AF relay hybrid network system in situations where the direct link between the receiver and transmitter is absent.展开更多
The off situ accurate reconstruction of the core neutron field is an important step in realizing real-time reactor monitoring.The existing off situ reconstruction method of the neutron field is only applicable to case...The off situ accurate reconstruction of the core neutron field is an important step in realizing real-time reactor monitoring.The existing off situ reconstruction method of the neutron field is only applicable to cases wherein a single region changes at a specified location of the core.However,when the neutron field changes are complex,the accurate identification of the individual changed regions becomes challenging,which seriously affects the accuracy and stability of the neutron field recon-struction.Therefore,this study proposed a dual-task hybrid network architecture(DTHNet)for off situ reconstruction of the core neutron field,which trained the outermost assembly reconstruction task and the core reconstruction task jointly such that the former could assist the latter in the reconstruction of the core neutron field under core complex changes.Furthermore,to exploit the characteristics of the ex-core detection signals,this study designed a global-local feature upsampling module that efficiently distributed the ex-core detection signals to each reconstruction unit to improve the accuracy and stability of reconstruction.Reconstruction experiments were performed on the simulation datasets of the CLEAR-I reactor to verify the accuracy and stability of the proposed method.The results showed that when the location uncertainty of a single region did not exceed nine and the number of multiple changed regions did not exceed five.Further,the reconstructed ARD was within 2%,RD_(max)was maintained within 17.5%,and the number of RD≥10%was maintained within 10.Furthermore,when the noise interference of the ex-core detection signals was within±2%,although the average number of RD≥10%increased to 16,the average ARD was still within in 2%,and the average RD_(max)was within 22%.Collectively,these results show that,theoretically,the DTHNet can accurately and stably reconstruct most of the neutron field under certain complex core changes.展开更多
This paper presents a new HMM/MLP hybrid network for speech recognition. By taking advantage of the discriminative training of MLP, the unreasonable model correctness assumption on the model correctness of the ML trai...This paper presents a new HMM/MLP hybrid network for speech recognition. By taking advantage of the discriminative training of MLP, the unreasonable model correctness assumption on the model correctness of the ML training in basic HMM can be overcome, and its discriminative ability and recognition performance can be improved. Experimental results demonstrate that the discriminative ability and recognition performance of HMM/MLP is apparently better than normal HMM.展开更多
The demand for wireless data has been driving network capacity to double about every two years for the past 50 years, if not 100 years, and this has come to be known as Cooper＇s Law. In recent years, this trend has a...The demand for wireless data has been driving network capacity to double about every two years for the past 50 years, if not 100 years, and this has come to be known as Cooper＇s Law. In recent years, this trend has accelerated as a greater proportion of the population adopts wireless devices with ever greater capabilities, including tablets that support HD video and other advanced capabilities.展开更多
The mobile ad hoc network (MANET) with infrastructure networks (hybrid networks) has several practical uses. The utility of hybrid network is increased in real time applications by providing some suitable quality of s...The mobile ad hoc network (MANET) with infrastructure networks (hybrid networks) has several practical uses. The utility of hybrid network is increased in real time applications by providing some suitable quality of service. The quality thresholds are imposed on parameters like end-to-end delay (EED), jitter, packet delivery ratio (PDR) and throughput. This paper utilizes the extended ad hoc on-demand distance vector (AODV) routing protocol for communication between ad hoc network and fixed wired network. This paper also uses the IEEE 802.11e medium access control (MAC) function HCF Controlled Channel Access (HCCA) to support quality of service (QoS) in hybrid network. In this paper two simulation scenarios are analyzed for hybrid networks. The nodes in wireless ad hoc networks are mobile in one scenario and static in the other scenario. Both simulation scenarios are used to compare the performance of extended AODV with HCCA (IEEE 802.11e) and without HCCA (IEEE802.11) for real time voice over IP (VoIP) traffic. The extensive set of simulations results show that the performance of extended AODV with HCCA (IEEE 802.11e) improves QoS in hybrid network and it is unaffected whether the nodes in wireless ad hoc networks are mobile or static.展开更多
The deepwater subsea wellhead(SW)system is the foundation for the construction of oil and gas wells and the crucial channel for operation.During riser connection operation,the SW system is subjected to cyclic dynamic ...The deepwater subsea wellhead(SW)system is the foundation for the construction of oil and gas wells and the crucial channel for operation.During riser connection operation,the SW system is subjected to cyclic dynamic loads which cause fatigue damage to the SW system,and continuously accumulated fatigue damage leads to fatigue failure of the SW system,rupture,and even blowout accidents.This paper proposes a hybrid Bayesian network(HBN)-based dynamic reliability assessment approach for deepwater SW systems during their service life.In the proposed approach,the relationship between the accumulation of fatigue damage and the fatigue failure probability of the SW system is predicted,only considering normal conditions.The HBN model,which includes the accumulation of fatigue damage under normal conditions and the other factors affecting the fatigue of the SW system,is subsequently developed.When predictive and diagnostic analysis techniques are adopted,the dynamic reliability of the SW system is achieved,and the most influential factors are determined.Finally,corresponding safety control measures are proposed to improve the reliability of the SW system effectively.The results illustrate that the fatigue failure speed increases rapidly when the accumulation fatigue damage is larger than 0.45 under normal conditions and that the reliability of the SW system is larger than 94%within the design life.展开更多
Satellite and terrestrial cellular networks can be integrated together to achieve extended broad-band coverage for,e.g.,maritime communication sce-narios,in the upcoming sixth-generation(6G)era.To counter spectrum sca...Satellite and terrestrial cellular networks can be integrated together to achieve extended broad-band coverage for,e.g.,maritime communication sce-narios,in the upcoming sixth-generation(6G)era.To counter spectrum scarcity,collaborative spectrum sharing is considered for hybrid satellite-terrestrial networks(HSTNs)in this paper.With only slowly-varying large-scale channel state information(CSI),joint power and channel allocation is implemented for terrestrial mobile terminals(MTs)which share the same frequency band with the satellite MTs oppor-tunistically.Specially,strict quality service assurance is adopted for terrestrial MTs under the constraint of leakage interference to satellite MTs.With the tar-get of maximizing both the number of served terres-trial MTs and the average sum transmission rate,a double-target spectrum sharing problem is formulated.To solve the complicated mixed integer programming(MIP)problem efficiently,user-centric channel pools are introduced.Simulations demonstrate that the proposed spectrum sharing scheme could achieve a significant performance gain for the HSTN.展开更多
Blockchain platform swith the unique characteristics of anonymity,decentralization,and transparency of their transactions,which are faced with abnormal activities such as money laundering,phishing scams,and fraudulent...Blockchain platform swith the unique characteristics of anonymity,decentralization,and transparency of their transactions,which are faced with abnormal activities such as money laundering,phishing scams,and fraudulent behavior,posing a serious threat to account asset security.For these potential security risks,this paper proposes a hybrid neural network detection method(HNND)that learns multiple types of account features and enhances fusion information among them to effectively detect abnormal transaction behaviors in the blockchain.In HNND,the Temporal Transaction Graph Attention Network(T2GAT)is first designed to learn biased aggregation representation of multi-attribute transactions among nodes,which can capture key temporal information from node neighborhood transactions.Then,the Graph Convolutional Network(GCN)is adopted which captures abstract structural features of the transaction network.Further,the Stacked Denoising Autoencode(SDA)is developed to achieve adaptive fusion of thses features from different modules.Moreover,the SDA enhances robustness and generalization ability of node representation,leading to higher binary classification accuracy in detecting abnormal behaviors of blockchain accounts.Evaluations on a real-world abnormal transaction dataset demonstrate great advantages of the proposed HNND method over other compared methods.展开更多
Network virtualization is the development trend and inevitable requirement of hybrid wireless sensor networks(HWSNs).Low mapping efficiency and service interruption caused by mobility seriously affect the reliability ...Network virtualization is the development trend and inevitable requirement of hybrid wireless sensor networks(HWSNs).Low mapping efficiency and service interruption caused by mobility seriously affect the reliability of sensing tasks and ultimately affect the long-term revenue of the infrastructure providers.In response to these problems,this paper proposes an efficient virtual network embedding algorithm with a reliable service guarantee.Based on the topological attributes of nodes,a method for evaluating the physical network resource importance degree is proposed,and the nodes with rich resources are selected to improve embedding efficiency.Then,a method for evaluating the physical network reliability degree is proposed to predict the probability of mobile sensors providing uninterrupted services.The simulation results show that the proposed algorithm improves the acceptance rate of virtual sensor networks(VSN)embedding requests and the long-term revenue of the infrastructure providers.展开更多
Accurate forecasting of electricity spot prices is crucial for market participants in formulating bidding strategies.However,the extreme volatility of electricity spot prices,influenced by various factors,poses signif...Accurate forecasting of electricity spot prices is crucial for market participants in formulating bidding strategies.However,the extreme volatility of electricity spot prices,influenced by various factors,poses significant challenges for forecasting.To address the data uncertainty of electricity prices and effectively mitigate gradient issues,overfitting,and computational challenges associated with using a single model during forecasting,this paper proposes a framework for forecasting spot market electricity prices by integrating wavelet packet decomposition(WPD)with a hybrid deep neural network.By ensuring accurate data decomposition,the WPD algorithm aids in detecting fluctuating patterns and isolating random noise.The hybrid model integrates temporal convolutional networks(TCN)and long short-term memory(LSTM)networks to enhance feature extraction and improve forecasting performance.Compared to other techniques,it significantly reduces average errors,decreasing mean absolute error(MAE)by 27.3%,root mean square error(RMSE)by 66.9%,and mean absolute percentage error(MAPE)by 22.8%.This framework effectively captures the intricate fluctuations present in the time series,resulting in more accurate and reliable predictions.展开更多
With limited number of labeled samples,hyperspectral image(HSI)classification is a difficult Problem in current research.The graph neural network(GNN)has emerged as an approach to semi-supervised classification,and th...With limited number of labeled samples,hyperspectral image(HSI)classification is a difficult Problem in current research.The graph neural network(GNN)has emerged as an approach to semi-supervised classification,and the application of GNN to hyperspectral images has attracted much attention.However,in the existing GNN-based methods a single graph neural network or graph filter is mainly used to extract HSI features,which does not take full advantage of various graph neural networks(graph filters).Moreover,the traditional GNNs have the problem of oversmoothing.To alleviate these shortcomings,we introduce a deep hybrid multi-graph neural network(DHMG),where two different graph filters,i.e.,the spectral filter and the autoregressive moving average(ARMA)filter,are utilized in two branches.The former can well extract the spectral features of the nodes,and the latter has a good suppression effect on graph noise.The network realizes information interaction between the two branches and takes good advantage of different graph filters.In addition,to address the problem of oversmoothing,a dense network is proposed,where the local graph features are preserved.The dense structure satisfies the needs of different classification targets presenting different features.Finally,we introduce a GraphSAGEbased network to refine the graph features produced by the deep hybrid network.Extensive experiments on three public HSI datasets strongly demonstrate that the DHMG dramatically outperforms the state-ofthe-art models.展开更多
In this article, we present a new type of unified dynamic scaling property for synchronizability, which can describe the scaling relationship between dynamic synehronizability and four hybrid ratios under the unified ...In this article, we present a new type of unified dynamic scaling property for synchronizability, which can describe the scaling relationship between dynamic synehronizability and four hybrid ratios under the unified hybrid network theory framework （UHNTF）. Our theory results can not only be applied to judge and analyze dynamic synehronizability for most of complex networks associated with the UHNTF, but also we can flexibly adjust and design different hybrid ratios and sealing exponent to meet actual requirement for the dynanfic characteristics of the UHNTF.展开更多
Indoor wireless communication networking has received significant attention along with the growth of indoor data traffic.VLC(Visible Light Communication)as a novel wireless communication technology with the advantages...Indoor wireless communication networking has received significant attention along with the growth of indoor data traffic.VLC(Visible Light Communication)as a novel wireless communication technology with the advantages of a high data rate,license-free spectrum and safety provides a practical solution for the indoor high-speed transmission of large data traffic.However,limited coverage is an inherent feature of VLC.In this paper,we propose a novel hybrid VLC-Wi-Fi system that integrates multiple links to achieve an indoor high-speed wide-coverage network combined with multiple access,a multi-path transmission control protocol,mobility management and cell handover.Furthermore,we develop a hybrid network experiment platform,the experimental results of which show that the hybrid VLC-Wi-Fi network outperforms both single VLC and Wi-Fi networks with better coverage and greater network capacity.展开更多
The benefit of a two-layer hybrid IP/MPLS （multi-protocol label switching） over a wavelength division multiplexing network has been analyzed considering both the cost and different grooming policies. A detailed cost...The benefit of a two-layer hybrid IP/MPLS （multi-protocol label switching） over a wavelength division multiplexing network has been analyzed considering both the cost and different grooming policies. A detailed cost and performance analysis of hybrid networks is done for three different grooming policies. The hybrid network cost is compared with that of an opaque network for equal traffic demand and equal blocking probability of dynamic requests of label switched paths. An algorithm is given to design optimum hybrid nodes for different grooming policies to provide the desired blocking probability for a given number of dynamic connection requests. The results show that all three applied grooming policies （IP layer first, optical layer first, and one hop first） result in lower costs of the hybrid network architecture than for the opaque network. In addition, an adaptive one hop first method is given to improve the best of the applied grooming policies, which limits grooming in heavily loaded hybrid nodes to achieve load balancing. The simulation resuits show that the new policy significantly reduces the overall blocking probability.展开更多
Most of studies on network capacity are based on the assumption that all the nodes are uniformly distributed, which means that the networks are characterized by homogeneity. However, many realistic networks exhibit in...Most of studies on network capacity are based on the assumption that all the nodes are uniformly distributed, which means that the networks are characterized by homogeneity. However, many realistic networks exhibit inhomogeneity due to natural and man-made reasons. In this work, the capacity of inhomogeneous hybrid networks with directional antennas for the first time is studied. By setting different node distribution probabilities, the whole network can be devided into dense cells and sparse cells. On this basis, an inhomogeneous hybrid network model is proposed. The network can exhibit significant inhomogeneity due to the coexistence of two types of cells. Then, we derive the network capacity and maximize the capacity under different channel allocation schemes. Finally, how the network parameters influence the network capacity is analyzed. It is found that if there are plenty of base stations, the per-node throughput can achieve constant order, and if the beamwidth of directional antenna is small enough, the network capacity can scale.展开更多
Network virtualization provides a powerful way of sharing substrate networks. Efficient allocation of network resources for multiple virtual networks( VNs) has always been a challenging task. Especially under the ever...Network virtualization provides a powerful way of sharing substrate networks. Efficient allocation of network resources for multiple virtual networks( VNs) has always been a challenging task. Especially under the everincreasing demand of customized VN requests,many problems arise as network conditions change constantly.Particularly with the emergance of resource conflict alongside the development of VNs,service provider( SP) needs to provide a faster and more effective solution. Recently,software defined network( SDN) has emerged as a new networking paradigm,SDN’s centralized control and customizable routing features present new opportunities for convenient and flexible embedding VNs in the network. However,due to the limitations of SDN,replacing all legacy devices in current operational networks by SDN-enabled switches in a short span of time is impractical.Thus,in our study,we focus on the scenario of VN embedding( VNE) in software-defined hybrid networks. In this work,first of all,we propose partially deploying SDN nodes; and then,we use the characteristics of SDN to allocate resources for VN requests,and redirect the path for requests conflict in hybrid SDN network. We formulate the problems and provide simple algorithms to solve them. Simulation results show that our scheme has high ratio in responsiveness and acceptance.展开更多
Because of its high theoretical capacity,transition metal sulfides have always been regarded as promising anode materials for potas-slum-ion batteries.However,It is difficult for us to make use of transition metal sul...Because of its high theoretical capacity,transition metal sulfides have always been regarded as promising anode materials for potas-slum-ion batteries.However,It is difficult for us to make use of transition metal sulfides due to their low conductivity,poor ionic dif-fusivity,sluggish reaction kinetics and severe volume expansion.Here,we developed a novel carbon-coated CoSx@CNT material with carbon nanotubes inter-connected(CCS@CNT),which shows an excellent potassium storage performance with a specific capacity of 550 mA·h·g^(-1) under the current of 50 mA·g^(-1) and 296 mA·hg^(-1) at 1000 mA·g-1.The carbon layer can effectively alleviate volume ex-pansion during charging and discharging process.And this special structure of inter-connected hybrid networks with CNTs greatly improves the electron transport,ion diffusion coefficient and reaction kinetics of the material.展开更多
Advances in mobile technology make most people have their own mobile devices which contain various sensors such as a smartphone.People produce their own personal data or collect surrounding environment data with their...Advances in mobile technology make most people have their own mobile devices which contain various sensors such as a smartphone.People produce their own personal data or collect surrounding environment data with their mobile devices at every moment.Recently,a broad spectrum of studies on Participatory Sensing,the concept of extracting new knowledge from a mass of data sent by participants,are conducted.Data collection method is one of the base technologies for Participatory Sensing,so networking and data filtering techniques for collecting a large number of data are the most interested research area.In this paper,we propose a data collection model in hybrid network for participatory sensing.The proposed model classifies data into two types and decides networking form and data filtering method based on the data type to decrease loads on data center and improve transmission speed.展开更多
With the rapid development of related computer vision algorithms,the large-scale use of video surveillance systems has not only improved traffic safety,but also promoted the development of intelligent high-speed.Howev...With the rapid development of related computer vision algorithms,the large-scale use of video surveillance systems has not only improved traffic safety,but also promoted the development of intelligent high-speed.However,due to the complexity of the application scene,especially in the face of complex scene occlusion factors,the noise generated by the occlusion inevitably leads to the loss of the feature information of the identified person or object,which poses a great challenge to the existing pedestrian re-recognition algorithms.Therefore,this paper proposes a novel pedestrian re-recognition based on hybrid network.Feature extraction is carried out on four cooperative branches:local branch,global branch,global contrast pool branch and associated branch,and powerful diversity pedestrian feature expression ability is obtained.The network in this paper can be applied to different backbone networks.Through experimental comparison,the proposed algorithm has certain advantages compared with the latest methods,and the ablation experimental analysis further proves the effectiveness of the proposed network structure.展开更多
Natural disaster or large-scale unexpected events easily make the terrestrial network overloaded,paralyzed, or totally destroyed. It is highly demanded to build an emergency network which can be deployed rapidly, offe...Natural disaster or large-scale unexpected events easily make the terrestrial network overloaded,paralyzed, or totally destroyed. It is highly demanded to build an emergency network which can be deployed rapidly, offer high data rate and wide coverage. The emergence of aerial platforms especially the low altitude platforms(LAPs) indicates a stable and reliable direction for the development of emergency network. Hybrid satellite-aerial-terrestrial(HSAT) networks have the ability to provide effective services rather than traditional infrastructures during the emergency situation. In this paper, the aerial platforms and the HSAT networks are surveyed and the key technologies are discussed from several aspects. The challenges of the HSAT networks are also outlined finally.展开更多
文摘A Reconfigurable Intelligent Surface(RIS)can relay signals from the transmitter to the receiver.In this regard,RISs operate similarly to traditional relays.We design a Multiple-Input-Multiple-Output(MIMO)system with a hybrid network of RIS and Half-Duplex(HD)Amplify-and-Forward(AF)relay.We model the system’s signal propagation and propose a new algorithm to get the system’s Achievable Rate(AR)value.We complete simulations to evaluate the performance of the RIS and HD-AF relay hybrid network system compared to the system assisted by either the RIS or HD-AF relay.The simulations indicate that many factors can considerably influence the system performance.Selecting an optimal placement for the RIS and relay can result in the best performance for the RIS and HD-AF relay hybrid network system in situations where the direct link between the receiver and transmitter is absent.
基金supported by the National Natural Science Foundation of China(No.12305344)the 2023 Anhui university research project of China(No.2023AH052179).
文摘The off situ accurate reconstruction of the core neutron field is an important step in realizing real-time reactor monitoring.The existing off situ reconstruction method of the neutron field is only applicable to cases wherein a single region changes at a specified location of the core.However,when the neutron field changes are complex,the accurate identification of the individual changed regions becomes challenging,which seriously affects the accuracy and stability of the neutron field recon-struction.Therefore,this study proposed a dual-task hybrid network architecture(DTHNet)for off situ reconstruction of the core neutron field,which trained the outermost assembly reconstruction task and the core reconstruction task jointly such that the former could assist the latter in the reconstruction of the core neutron field under core complex changes.Furthermore,to exploit the characteristics of the ex-core detection signals,this study designed a global-local feature upsampling module that efficiently distributed the ex-core detection signals to each reconstruction unit to improve the accuracy and stability of reconstruction.Reconstruction experiments were performed on the simulation datasets of the CLEAR-I reactor to verify the accuracy and stability of the proposed method.The results showed that when the location uncertainty of a single region did not exceed nine and the number of multiple changed regions did not exceed five.Further,the reconstructed ARD was within 2%,RD_(max)was maintained within 17.5%,and the number of RD≥10%was maintained within 10.Furthermore,when the noise interference of the ex-core detection signals was within±2%,although the average number of RD≥10%increased to 16,the average ARD was still within in 2%,and the average RD_(max)was within 22%.Collectively,these results show that,theoretically,the DTHNet can accurately and stably reconstruct most of the neutron field under certain complex core changes.
文摘This paper presents a new HMM/MLP hybrid network for speech recognition. By taking advantage of the discriminative training of MLP, the unreasonable model correctness assumption on the model correctness of the ML training in basic HMM can be overcome, and its discriminative ability and recognition performance can be improved. Experimental results demonstrate that the discriminative ability and recognition performance of HMM/MLP is apparently better than normal HMM.
文摘The demand for wireless data has been driving network capacity to double about every two years for the past 50 years, if not 100 years, and this has come to be known as Cooper＇s Law. In recent years, this trend has accelerated as a greater proportion of the population adopts wireless devices with ever greater capabilities, including tablets that support HD video and other advanced capabilities.
文摘The mobile ad hoc network (MANET) with infrastructure networks (hybrid networks) has several practical uses. The utility of hybrid network is increased in real time applications by providing some suitable quality of service. The quality thresholds are imposed on parameters like end-to-end delay (EED), jitter, packet delivery ratio (PDR) and throughput. This paper utilizes the extended ad hoc on-demand distance vector (AODV) routing protocol for communication between ad hoc network and fixed wired network. This paper also uses the IEEE 802.11e medium access control (MAC) function HCF Controlled Channel Access (HCCA) to support quality of service (QoS) in hybrid network. In this paper two simulation scenarios are analyzed for hybrid networks. The nodes in wireless ad hoc networks are mobile in one scenario and static in the other scenario. Both simulation scenarios are used to compare the performance of extended AODV with HCCA (IEEE 802.11e) and without HCCA (IEEE802.11) for real time voice over IP (VoIP) traffic. The extensive set of simulations results show that the performance of extended AODV with HCCA (IEEE 802.11e) improves QoS in hybrid network and it is unaffected whether the nodes in wireless ad hoc networks are mobile or static.
基金financially supported by the National Natural Science Foundation of China(Grant No.52071337)the Research Initiation Funds of Zhejiang University of Science and Technology(Grant No.F701102N06)+2 种基金the High-tech Ship Research Projects Sponsored by MIIT(Grant No.CBG2N21-4-2-5)the National Key Research and Development Program of China(Grant No.2022YFC2806300)the Marine Economy Development(Six Marine Industries)Special Foundation of the Department of Natural Resources of Guangdong Province(Grant No.GDNRC[2023]50).
文摘The deepwater subsea wellhead(SW)system is the foundation for the construction of oil and gas wells and the crucial channel for operation.During riser connection operation,the SW system is subjected to cyclic dynamic loads which cause fatigue damage to the SW system,and continuously accumulated fatigue damage leads to fatigue failure of the SW system,rupture,and even blowout accidents.This paper proposes a hybrid Bayesian network(HBN)-based dynamic reliability assessment approach for deepwater SW systems during their service life.In the proposed approach,the relationship between the accumulation of fatigue damage and the fatigue failure probability of the SW system is predicted,only considering normal conditions.The HBN model,which includes the accumulation of fatigue damage under normal conditions and the other factors affecting the fatigue of the SW system,is subsequently developed.When predictive and diagnostic analysis techniques are adopted,the dynamic reliability of the SW system is achieved,and the most influential factors are determined.Finally,corresponding safety control measures are proposed to improve the reliability of the SW system effectively.The results illustrate that the fatigue failure speed increases rapidly when the accumulation fatigue damage is larger than 0.45 under normal conditions and that the reliability of the SW system is larger than 94%within the design life.
基金supported in part by the National Natural Science Foundation of China under Grant 62425110 and Grant U22A2002in part by the National Key Research and Development Program of China under Grant 2020YFA0711301+2 种基金in part by the Leading Project of Minzu University of China under Grant 2023QNYL23in part by the Key Research and Development Project of Nantong(Special Project for Prospective Technology Innovation)under Grant GZ2024002in part by the Suzhou Science and Technology Project,and in part by the FAW Jiefang Automotive Co.,Ltd.
文摘Satellite and terrestrial cellular networks can be integrated together to achieve extended broad-band coverage for,e.g.,maritime communication sce-narios,in the upcoming sixth-generation(6G)era.To counter spectrum scarcity,collaborative spectrum sharing is considered for hybrid satellite-terrestrial networks(HSTNs)in this paper.With only slowly-varying large-scale channel state information(CSI),joint power and channel allocation is implemented for terrestrial mobile terminals(MTs)which share the same frequency band with the satellite MTs oppor-tunistically.Specially,strict quality service assurance is adopted for terrestrial MTs under the constraint of leakage interference to satellite MTs.With the tar-get of maximizing both the number of served terres-trial MTs and the average sum transmission rate,a double-target spectrum sharing problem is formulated.To solve the complicated mixed integer programming(MIP)problem efficiently,user-centric channel pools are introduced.Simulations demonstrate that the proposed spectrum sharing scheme could achieve a significant performance gain for the HSTN.
文摘Blockchain platform swith the unique characteristics of anonymity,decentralization,and transparency of their transactions,which are faced with abnormal activities such as money laundering,phishing scams,and fraudulent behavior,posing a serious threat to account asset security.For these potential security risks,this paper proposes a hybrid neural network detection method(HNND)that learns multiple types of account features and enhances fusion information among them to effectively detect abnormal transaction behaviors in the blockchain.In HNND,the Temporal Transaction Graph Attention Network(T2GAT)is first designed to learn biased aggregation representation of multi-attribute transactions among nodes,which can capture key temporal information from node neighborhood transactions.Then,the Graph Convolutional Network(GCN)is adopted which captures abstract structural features of the transaction network.Further,the Stacked Denoising Autoencode(SDA)is developed to achieve adaptive fusion of thses features from different modules.Moreover,the SDA enhances robustness and generalization ability of node representation,leading to higher binary classification accuracy in detecting abnormal behaviors of blockchain accounts.Evaluations on a real-world abnormal transaction dataset demonstrate great advantages of the proposed HNND method over other compared methods.
基金supported by National Natural Science Foundation of China(61901071,61871062,61771082,U20A20157)Science and Natural Science Foundation of Chongqing,China(cstc2020jcyjzdxmX0024)+1 种基金University Innovation Research Group of Chongqing(CXQT20017)Scientific and Technological Research Program of Chongqing Municipal Education Commission(No.KJZD-K201901301).
文摘Network virtualization is the development trend and inevitable requirement of hybrid wireless sensor networks(HWSNs).Low mapping efficiency and service interruption caused by mobility seriously affect the reliability of sensing tasks and ultimately affect the long-term revenue of the infrastructure providers.In response to these problems,this paper proposes an efficient virtual network embedding algorithm with a reliable service guarantee.Based on the topological attributes of nodes,a method for evaluating the physical network resource importance degree is proposed,and the nodes with rich resources are selected to improve embedding efficiency.Then,a method for evaluating the physical network reliability degree is proposed to predict the probability of mobile sensors providing uninterrupted services.The simulation results show that the proposed algorithm improves the acceptance rate of virtual sensor networks(VSN)embedding requests and the long-term revenue of the infrastructure providers.
基金partially supported by projects funded by the National Key R&D Program of China(2022YFB2403000)the State Grid Corporation of China Science and Technology Project(522722230034).
文摘Accurate forecasting of electricity spot prices is crucial for market participants in formulating bidding strategies.However,the extreme volatility of electricity spot prices,influenced by various factors,poses significant challenges for forecasting.To address the data uncertainty of electricity prices and effectively mitigate gradient issues,overfitting,and computational challenges associated with using a single model during forecasting,this paper proposes a framework for forecasting spot market electricity prices by integrating wavelet packet decomposition(WPD)with a hybrid deep neural network.By ensuring accurate data decomposition,the WPD algorithm aids in detecting fluctuating patterns and isolating random noise.The hybrid model integrates temporal convolutional networks(TCN)and long short-term memory(LSTM)networks to enhance feature extraction and improve forecasting performance.Compared to other techniques,it significantly reduces average errors,decreasing mean absolute error(MAE)by 27.3%,root mean square error(RMSE)by 66.9%,and mean absolute percentage error(MAPE)by 22.8%.This framework effectively captures the intricate fluctuations present in the time series,resulting in more accurate and reliable predictions.
文摘With limited number of labeled samples,hyperspectral image(HSI)classification is a difficult Problem in current research.The graph neural network(GNN)has emerged as an approach to semi-supervised classification,and the application of GNN to hyperspectral images has attracted much attention.However,in the existing GNN-based methods a single graph neural network or graph filter is mainly used to extract HSI features,which does not take full advantage of various graph neural networks(graph filters).Moreover,the traditional GNNs have the problem of oversmoothing.To alleviate these shortcomings,we introduce a deep hybrid multi-graph neural network(DHMG),where two different graph filters,i.e.,the spectral filter and the autoregressive moving average(ARMA)filter,are utilized in two branches.The former can well extract the spectral features of the nodes,and the latter has a good suppression effect on graph noise.The network realizes information interaction between the two branches and takes good advantage of different graph filters.In addition,to address the problem of oversmoothing,a dense network is proposed,where the local graph features are preserved.The dense structure satisfies the needs of different classification targets presenting different features.Finally,we introduce a GraphSAGEbased network to refine the graph features produced by the deep hybrid network.Extensive experiments on three public HSI datasets strongly demonstrate that the DHMG dramatically outperforms the state-ofthe-art models.
基金The work was supported by the National Natural Science Foundation of China （Grant Nos. 60874087 and 61174151）.
文摘In this article, we present a new type of unified dynamic scaling property for synchronizability, which can describe the scaling relationship between dynamic synehronizability and four hybrid ratios under the unified hybrid network theory framework （UHNTF）. Our theory results can not only be applied to judge and analyze dynamic synehronizability for most of complex networks associated with the UHNTF, but also we can flexibly adjust and design different hybrid ratios and sealing exponent to meet actual requirement for the dynanfic characteristics of the UHNTF.
基金supported by National Program on Key Basic Research Project of China(No.2013CB329205)National Natural Science Foundation of China(No.61601432)and Fundamental Research Funds for the Central Universities.
文摘Indoor wireless communication networking has received significant attention along with the growth of indoor data traffic.VLC(Visible Light Communication)as a novel wireless communication technology with the advantages of a high data rate,license-free spectrum and safety provides a practical solution for the indoor high-speed transmission of large data traffic.However,limited coverage is an inherent feature of VLC.In this paper,we propose a novel hybrid VLC-Wi-Fi system that integrates multiple links to achieve an indoor high-speed wide-coverage network combined with multiple access,a multi-path transmission control protocol,mobility management and cell handover.Furthermore,we develop a hybrid network experiment platform,the experimental results of which show that the hybrid VLC-Wi-Fi network outperforms both single VLC and Wi-Fi networks with better coverage and greater network capacity.
基金Supported in part by the National High-Tech Research and Development (863) Program of China (Nos.2008AA01A327 and 2008AA01A329)
文摘The benefit of a two-layer hybrid IP/MPLS （multi-protocol label switching） over a wavelength division multiplexing network has been analyzed considering both the cost and different grooming policies. A detailed cost and performance analysis of hybrid networks is done for three different grooming policies. The hybrid network cost is compared with that of an opaque network for equal traffic demand and equal blocking probability of dynamic requests of label switched paths. An algorithm is given to design optimum hybrid nodes for different grooming policies to provide the desired blocking probability for a given number of dynamic connection requests. The results show that all three applied grooming policies （IP layer first, optical layer first, and one hop first） result in lower costs of the hybrid network architecture than for the opaque network. In addition, an adaptive one hop first method is given to improve the best of the applied grooming policies, which limits grooming in heavily loaded hybrid nodes to achieve load balancing. The simulation resuits show that the new policy significantly reduces the overall blocking probability.
基金Projects(61401476,61201166)supported by the National Natural Science Foundation of China
文摘Most of studies on network capacity are based on the assumption that all the nodes are uniformly distributed, which means that the networks are characterized by homogeneity. However, many realistic networks exhibit inhomogeneity due to natural and man-made reasons. In this work, the capacity of inhomogeneous hybrid networks with directional antennas for the first time is studied. By setting different node distribution probabilities, the whole network can be devided into dense cells and sparse cells. On this basis, an inhomogeneous hybrid network model is proposed. The network can exhibit significant inhomogeneity due to the coexistence of two types of cells. Then, we derive the network capacity and maximize the capacity under different channel allocation schemes. Finally, how the network parameters influence the network capacity is analyzed. It is found that if there are plenty of base stations, the per-node throughput can achieve constant order, and if the beamwidth of directional antenna is small enough, the network capacity can scale.
基金supported by the National Natural Science Foundation of China ( 61602051)the Fundamental Research Funds for the Central Universities ( 2017RC11)
文摘Network virtualization provides a powerful way of sharing substrate networks. Efficient allocation of network resources for multiple virtual networks( VNs) has always been a challenging task. Especially under the everincreasing demand of customized VN requests,many problems arise as network conditions change constantly.Particularly with the emergance of resource conflict alongside the development of VNs,service provider( SP) needs to provide a faster and more effective solution. Recently,software defined network( SDN) has emerged as a new networking paradigm,SDN’s centralized control and customizable routing features present new opportunities for convenient and flexible embedding VNs in the network. However,due to the limitations of SDN,replacing all legacy devices in current operational networks by SDN-enabled switches in a short span of time is impractical.Thus,in our study,we focus on the scenario of VN embedding( VNE) in software-defined hybrid networks. In this work,first of all,we propose partially deploying SDN nodes; and then,we use the characteristics of SDN to allocate resources for VN requests,and redirect the path for requests conflict in hybrid SDN network. We formulate the problems and provide simple algorithms to solve them. Simulation results show that our scheme has high ratio in responsiveness and acceptance.
基金This study was supported by the National Natural Science Foundation of China(51772283,22072140)the Fundamental Research Funds for the Central Universities(WK2060000032).
文摘Because of its high theoretical capacity,transition metal sulfides have always been regarded as promising anode materials for potas-slum-ion batteries.However,It is difficult for us to make use of transition metal sulfides due to their low conductivity,poor ionic dif-fusivity,sluggish reaction kinetics and severe volume expansion.Here,we developed a novel carbon-coated CoSx@CNT material with carbon nanotubes inter-connected(CCS@CNT),which shows an excellent potassium storage performance with a specific capacity of 550 mA·h·g^(-1) under the current of 50 mA·g^(-1) and 296 mA·hg^(-1) at 1000 mA·g-1.The carbon layer can effectively alleviate volume ex-pansion during charging and discharging process.And this special structure of inter-connected hybrid networks with CNTs greatly improves the electron transport,ion diffusion coefficient and reaction kinetics of the material.
基金supported by Defense Acquisition Program Administration and Agency for Defense Development under the contract UD140022PD,Koreafunded by the Ministry of Science,ICT and Future Planning(NRF-2015R1C1A2A01051452).
文摘Advances in mobile technology make most people have their own mobile devices which contain various sensors such as a smartphone.People produce their own personal data or collect surrounding environment data with their mobile devices at every moment.Recently,a broad spectrum of studies on Participatory Sensing,the concept of extracting new knowledge from a mass of data sent by participants,are conducted.Data collection method is one of the base technologies for Participatory Sensing,so networking and data filtering techniques for collecting a large number of data are the most interested research area.In this paper,we propose a data collection model in hybrid network for participatory sensing.The proposed model classifies data into two types and decides networking form and data filtering method based on the data type to decrease loads on data center and improve transmission speed.
文摘With the rapid development of related computer vision algorithms,the large-scale use of video surveillance systems has not only improved traffic safety,but also promoted the development of intelligent high-speed.However,due to the complexity of the application scene,especially in the face of complex scene occlusion factors,the noise generated by the occlusion inevitably leads to the loss of the feature information of the identified person or object,which poses a great challenge to the existing pedestrian re-recognition algorithms.Therefore,this paper proposes a novel pedestrian re-recognition based on hybrid network.Feature extraction is carried out on four cooperative branches:local branch,global branch,global contrast pool branch and associated branch,and powerful diversity pedestrian feature expression ability is obtained.The network in this paper can be applied to different backbone networks.Through experimental comparison,the proposed algorithm has certain advantages compared with the latest methods,and the ablation experimental analysis further proves the effectiveness of the proposed network structure.
基金supported by the National 863 Project under Grant No.2015AA015701National Nature Science Foundation of China under Grant No. 61421061
文摘Natural disaster or large-scale unexpected events easily make the terrestrial network overloaded,paralyzed, or totally destroyed. It is highly demanded to build an emergency network which can be deployed rapidly, offer high data rate and wide coverage. The emergence of aerial platforms especially the low altitude platforms(LAPs) indicates a stable and reliable direction for the development of emergency network. Hybrid satellite-aerial-terrestrial(HSAT) networks have the ability to provide effective services rather than traditional infrastructures during the emergency situation. In this paper, the aerial platforms and the HSAT networks are surveyed and the key technologies are discussed from several aspects. The challenges of the HSAT networks are also outlined finally.
