With technological advancements,high-speed rail has emerged as a prevalent mode of transportation.During travel,passengers exhibit a growing demand for streaming media services.However,the high-speed mobile networks e...With technological advancements,high-speed rail has emerged as a prevalent mode of transportation.During travel,passengers exhibit a growing demand for streaming media services.However,the high-speed mobile networks environment poses challenges,including frequent base station handoffs,which significantly degrade wireless network transmission performance.Improving transmission efficiency in high-speed mobile networks and optimizing spatiotemporal wireless resource allocation to enhance passengers’media experiences are key research priorities.To address these issues,we propose an Adaptive Cross-Layer Optimization Transmission Method with Environment Awareness(ACOTM-EA)tailored for high-speed rail streaming media.Within this framework,we develop a channel quality prediction model utilizing Kalman filtering and an algorithm to identify packet loss causes.Additionally,we introduce a proactive base station handoffstrategy to minimize handoffrelated disruptions and optimize resource distribution across adjacent base stations.Moreover,this study presents a wireless resource allocation approach based on an enhanced genetic algorithm,coupled with an adaptive bitrate selection mechanism,to maximize passenger Quality of Experience(QoE).To evaluate the proposed method,we designed a simulation experiment and compared ACOTM-EA with established algorithms.Results indicate that ACOTM-EA improves throughput by 11%and enhances passengers’media experience by 5%.展开更多
The integration of high-speed railway communication systems with 5G technology is widely recognized as a significant development.Due to the considerable mobility of trains and the complex nature of the environment,the...The integration of high-speed railway communication systems with 5G technology is widely recognized as a significant development.Due to the considerable mobility of trains and the complex nature of the environment,the wireless channel exhibits non-stationary characteristics and fast time-varying characteristics,which presents significant hurdles in terms of channel estimation.In addition,the use of massive MIMO technology in the context of 5G networks also leads to an increase in the complexity of estimation.To address the aforementioned issues,this paper presents a novel approach for channel estimation in high mobility scenarios using a reconstruction and recovery network.In this method,the time-frequency response of the channel is considered as a two-dimensional image.The Fast Super-Resolution Convolution Neural Network(FSRCNN)is used to first reconstruct channel images.Next,the Denoising Convolution Neural Network(DnCNN)is applied to reduce the channel noise and improve the accuracy of channel estimation.Simulation results show that the accuracy of the channel estimation model surpasses that of the standard channel estimation method,while also exhibiting reduced algorithmic complexity.展开更多
Traffic is an indispensable prerequisite for a tourism system. The ＂four vertical and four horizontal＂ HSR network represents an important milestone of the ＂traffic revolution＂ in China. It will affect the spatial...Traffic is an indispensable prerequisite for a tourism system. The ＂four vertical and four horizontal＂ HSR network represents an important milestone of the ＂traffic revolution＂ in China. It will affect the spatial pattern of tourism accessibility in Chinese cities, thus substan- tially increasing their power to attract tourists and their radiation force. This paper examines the evolution and spatial characteristics of the power to attract tourism of cities linked by China＇s HSR network by measuring the influence of accessibility of 338 HSR-linked cities using GIS analysis. The results show the following. （1） The accessibility of Chinese cities is optimized by the HSR network, whose spatial pattern of accessibility exhibits an obvious traf- fic direction and causes a high-speed rail-corridor effect. （2） The spatial pattern of tourism field strength in Chinese cities exhibits the dual characteristics of multi-center annular diver- gence and dendritic diffusion. Dendritic diffusion is particularly more obvious along the HSR line. The change rate of urban tourism field strength forms a high-value corridor along the HSR line and exhibits a spatial pattern of decreasing area from the center to the outer limit along the HSR line. （3） The influence of the higher and highest tourism field strength areas along the HSR line is most significant, and the number of cities that distribute into these two types of tourism field strengths significantly increases： their area expands by more than 100% HSR enhances the tourism field strength value of regional central cities, and the radiation range of tourism attraction extends along the HSR line.展开更多
High-speed trains often use temperature sensors to monitor the motion state of bearings.However,the temperature of bearings can be affected by factors such as weather and faults.Therefore,it is necessary to analyze in...High-speed trains often use temperature sensors to monitor the motion state of bearings.However,the temperature of bearings can be affected by factors such as weather and faults.Therefore,it is necessary to analyze in detail the relationship between the bearing temperature and influencing factors.In this study,a dynamics model of the axle box bearing of high-speed trains is established.The model can obtain the contact force between the rollers and raceway and its change law when the bearing contains outer-ring,inner-ring,and rolling-element faults.Based on the model,a thermal network method is introduced to study the temperature field distribution of the axle box bearings of high-speed trains.In this model,the heat generation,conduction,and dispersion of the isothermal nodes can be solved.The results show that the temperature of the contact point between the outer-ring raceway and rolling-elements is the highest.The relationships between the node temperature and the speed,fault type,and fault size are analyzed,finding that the higher the speed,the higher the node temperature.Under different fault types,the node temperature first increases and then decreases as the fault size increases.The effectiveness of the model is demonstrated using the actual temperature data of a high-speed train.This study proposes a thermal network model that can predict the temperature of each component of the bearings on a high-speed train under various speed and fault conditions.展开更多
To predict the temperature of a motorized spindle more accurately,a novel temperature prediction model based on the back-propagation neural network optimized by adaptive particle swarm optimization(APSO-BPNN)is propos...To predict the temperature of a motorized spindle more accurately,a novel temperature prediction model based on the back-propagation neural network optimized by adaptive particle swarm optimization(APSO-BPNN)is proposed.First,on the basis of the PSO-BPNN algorithm,the adaptive inertia weight is introduced to make the weight change with the fitness of the particle,the adaptive learning factor is used to obtain different search abilities in the early and later stages of the algorithm,the mutation operator is incorporated to increase the diversity of the population and avoid premature convergence,and the APSO-BPNN model is constructed.Then,the temperature of different measurement points of the motorized spindle is forecasted by the BPNN,PSO-BPNN,and APSO-BPNN models.The experimental results demonstrate that the APSO-BPNN model has a significant advantage over the other two methods regarding prediction precision and robustness.The presented algorithm can provide a theoretical basis for intelligently controlling temperature and developing an early warning system for high-speed motorized spindles and machine tools.展开更多
In metal cutting industry it is a common practice to search for optimal combination of cutting parameters in order to maximize the tool life for a fixed minimum value of material removal rate(MRR).After the advent of ...In metal cutting industry it is a common practice to search for optimal combination of cutting parameters in order to maximize the tool life for a fixed minimum value of material removal rate(MRR).After the advent of high-speed milling(HSM)pro cess,lots of experimental and theoretical researches have been done for this purpose which mainly emphasized on the optimization of the cutting parameters.It is highly beneficial to convert raw data into a comprehensive knowledge-based expert system using fuzzy logic as the reasoning mechanism.In this paper an attempt has been presented for the extraction of the rules from fuzzy neural network(FNN)so as to have the most effective knowledge-base for given set of data.Experiments were conducted to determine the best values of cutting speeds that can maximize tool life for different combinations of input parameters.A fuzzy neural network was constructed based on the fuzzification of input parameters and the cutting speed.After training process,raw rule sets were extracted and a rule pruning approach was proposed to obtain concise linguistic rules.The estimation process with fuzzy inference showed that the optimized combination of fuzzy rules provided the estimation error of only 6.34 m/min as compared to 314 m/min of that of randomized combination of rule s.展开更多
With the increasing enlargement of network scale and the rapid development of network techniques, large numbers of the network applications begin to appear. Packet capture plays an important role as one basic techniqu...With the increasing enlargement of network scale and the rapid development of network techniques, large numbers of the network applications begin to appear. Packet capture plays an important role as one basic technique used in each field of the network applications. In a high-speed network, the heavy traffic of network transmission challenges the packet capture techniques. This paper does an in-depth analysis on the traditional packet capture mechanisms in Linux, and then measures the performance bottleneck in the process of packet capture. The methods for improving the packet capture performance are presented and an optimized packet capture scheme is also designed and implemented. The test demonstrates that the new packet capture mechanism (Libpacket) can greatly improve the packet capture performance of the network application systems in a high-speed network.展开更多
With the continual growth of the variety and complexity of network crime means, the traditional packet feature matching cannot detect all kinds of intrusion behaviors completely. It is urgent to reassemble network str...With the continual growth of the variety and complexity of network crime means, the traditional packet feature matching cannot detect all kinds of intrusion behaviors completely. It is urgent to reassemble network stream to perform packet processing at a semantic level above the network layer. This paper presents an efficient TCP stream reassembly mechanism for real-time processing of high-speed network traffic. By analyzing the characteristics of network stream in high-speed network and TCP connection establishment process, several polices for designing the reassembly mechanism are built. Then, the reassembly implementation is elaborated in accordance with the policies. Finally, the reassembly mechanism is compared with the traditional reassembly mechanism by the network traffic captured in a typical gigabit gateway. Experiment results illustrate that the reassembly mechanism is efficient and can satisfy the real-time property requirement of traffic analysis system in high-speed network.展开更多
The interfacial oxidation behavior of Cr_(4)Mo_(4) V high-speed steel(HSS)joints undergoing hot-compression bonding was investigated by using optical microscopy(OM),scanning electron microscopy(SEM),and transmission e...The interfacial oxidation behavior of Cr_(4)Mo_(4) V high-speed steel(HSS)joints undergoing hot-compression bonding was investigated by using optical microscopy(OM),scanning electron microscopy(SEM),and transmission electron microscopy(TEM).In the heating and holding processes,dispersed rod-like and granularδ-Al_(2)O_(3) oxides were formed at the interface and in the matrix near the interface due to the selective oxidation and internal oxidation of Al,while irregular Si-Al-O compounds and spheroidal SiO_(2) particles were formed at the interface.After the post-holding treatment,SiO_(2) oxides and Si-Al-O compounds were dissolved into the matrix,andδ-Al_(2)O_(3) oxides were transformed into nanoscaleα-Al_(2)O_(3) particles,which did not deteriorate the mechanical properties of the joints.The formation and migration of newly-formed grain boundaries by plastic deformation and post-holding treatment were the main mechanism for interface healing.The tensile test results showed that the strength of the healed joints was comparable to that of the base material,and the in-situ tensile observations proved that the fracture was initiated at the grain boundary of the matrix rather than at the interface.The clarification of interfacial oxides and microstructure is essential for the application of hot-compression bonding of HSSs.展开更多
The congestion control mechanisms of the current standard TCP constrain the congestion windows that can be achieved by TCP in high-speed networks, which leads to low link utilization. HSTCP is one solution to solve th...The congestion control mechanisms of the current standard TCP constrain the congestion windows that can be achieved by TCP in high-speed networks, which leads to low link utilization. HSTCP is one solution to solve this problem by modifying the congestion control mechanism to have the characteristics of TCP friendliness in high loss rate environment and high scalability in low loss rate environment. However, experiments revealed that HSTCP has severe RTT unfairness. After analyzing the RTT unfairness in HSTCP with a model, we proposed CW-HSTCP, which added a fair factor to decrease the difference of congestion window caused by different RTT. Fair factor of long RTT flows can cause a sharp window increment that is easy to cause a bursty traffic, so a method called block-pacing was adopted. Simulation results showed that our new proposal could alleviate the RTT unfairness while keeping advantages of HSTCP.展开更多
China has the largest high-speed railway(HSR) system in the world, and it has gradually reshaped the urban network.The HSR system can be represented as different types of networks in terms of the nodes and various rel...China has the largest high-speed railway(HSR) system in the world, and it has gradually reshaped the urban network.The HSR system can be represented as different types of networks in terms of the nodes and various relationships(i.e.,linkages) between them. In this paper, we first introduce a general dual network model, including a physical network(PN)and a logical network(LN) to provide a comparative analysis for China’s high-speed rail network via complex network theory. The PN represents a layout of stations and rail tracks, and forms the basis for operating all trains. The LN is a network composed of the origin and destination stations of each high-speed train and the train flows between them. China’s high-speed railway(CHSR) has different topological structures and link strengths for PN in comparison with the LN. In the study, the community detection is used to analyze China’s high-speed rail networks and several communities are found to be similar to the layout of planned urban agglomerations in China. Furthermore, the hierarchies of urban agglomerations are different from each other according to the strength of inter-regional interaction and intra-regional interaction, which are respectively related to location and spatial development strategies. Moreover, a case study of the Yangtze River Delta shows that the hub stations have different resource divisions and are major contributors to the gap between train departure and arrival flows.展开更多
The hot deformation behavior of TI (18W-4Cr-1V) high-speed steel was investigated by means of continuous compression tests performed on Gleeble 1500 thermomechan- ical simulator in a wide range of tempemtures (950℃...The hot deformation behavior of TI (18W-4Cr-1V) high-speed steel was investigated by means of continuous compression tests performed on Gleeble 1500 thermomechan- ical simulator in a wide range of tempemtures (950℃-1150℃) with strain rotes of 0.001s-1-10s-1 and true strains of 0-0. 7. The flow stress at the above hot defor- mation conditions is predicted by using BP artificial neural network. The architecture of network includes there are three input parameters:strain rate,temperature T and true strain , and just one output parameter, the flow stress ,2 hidden layers are adopted, the first hidden layer includes 9 neurons and second 10 negroes. It has been verified that BP artificial neural network with 3-9-10-1 architecture can predict flow stress of high-speed steel during hot deformation very well. Compared with the prediction method of flow stress by using Zaped-Holloman parumeter and hyperbolic sine stress function, the prediction method by using BP artificial neurul network has higher efficiency and accuracy.展开更多
For the congestion problems in high-speed networks, a genetic based fuzzy Q-learning flow controller is proposed. Because of the uncertainties and highly time-varying, it is not easy to accurately obtain the complete ...For the congestion problems in high-speed networks, a genetic based fuzzy Q-learning flow controller is proposed. Because of the uncertainties and highly time-varying, it is not easy to accurately obtain the complete information for high-speed networks. In this case, the Q-learning, which is independent of mathematic model, and prior-knowledge, has good performance. The fuzzy inference is introduced in order to facilitate generalization in large state space, and the genetic operators are used to obtain the consequent parts of fuzzy rules. Simulation results show that the proposed controller can learn to take the best action to regulate source flow with the features of high throughput and low packet loss ratio, and can avoid the occurrence of congestion effectively.展开更多
High-speed train communication system is a typical high-mobility wireless communication network. Resource allocation problem has a great impact on the system performance. However, conventional resource allocation appr...High-speed train communication system is a typical high-mobility wireless communication network. Resource allocation problem has a great impact on the system performance. However, conventional resource allocation approaches in cellular network cannot be directly applied to this kind of special communication environment. A multidomain resource allocation strategy was proposed in the orthogonal frequency-division multiple access(OFDMA) of high-speed. By analyzing the effect of Doppler shift, sub-channels, antennas, time slots and power were jointly considered to maximize the energy efficiency under the constraint of total transmission power. For the purpose of reducing the computational complexity, noisy chaotic neural network algorithm was used to solve the above optimization problem. Simulation results showed that the proposed resource allocation method had a better performance than the traditional strategy.展开更多
The construction of high-speed rail(HSR)network has promoted the social-economic ties of cities,accelerated the compression of time and space,and changed the pattern of regional development.In this paper,with the adop...The construction of high-speed rail(HSR)network has promoted the social-economic ties of cities,accelerated the compression of time and space,and changed the pattern of regional development.In this paper,with the adoption of the operation frequency data of HSR from 12306 website,and based on the HSR connection strength model and social network analysis model,as well as according to the HSR connection strength,HSR network density,centrality,agglomeration subgroup,and other indicators,we analyzed the characteristics of HSR network structure in Northeast China.Results show that the number of HSR cities in Northeast China is small,cities in HSR network generally exhibit weak connectivity,and the existence of HSR network marginalizes cities such as Ulanhot,Baicheng,and Songyuan,which significantly reduce the overall network connectivity of Northeast China.The overall centrality of HSR network in Northeast China is characterized by“one axis,four edges”;specifically,the one axis is located in Harbin-Dalian transportation line and the four edges are located on both sides of the main axis of Harbin-Dalian transportation line.Eight agglomeration subgroups(four double city subgroups and four multi city subgroups)have formed in Northeast China.The core status of Shenyang in HSR network is improved significantly,and“one axis and two wings”HSR network in Liaoning Province is improved significantly.With the gradual expansion of Chaoyang-Fuxin,Dandong-Benxi,and Jilin-Yanji branch networks,the“point axis”HSR network mode in Northeast China has gradually developed and matured.In the future,it is recommended to rely on eight agglomerating subgroups to encrypt HSR network structure,create secondary node central cities,and gradually build a new pattern of opening up in Northeast China.展开更多
Nowadays,high mobility scenarios have become increasingly common.The widespread adoption of High-speed Rail(HSR)in China exemplifies this trend,while more promising use cases,such as vehicle-to-everything,continue to ...Nowadays,high mobility scenarios have become increasingly common.The widespread adoption of High-speed Rail(HSR)in China exemplifies this trend,while more promising use cases,such as vehicle-to-everything,continue to emerge.However,the Internet access provided in high mobility environments stllstruggles to achieve seamless connectivity.The next generation of wireless cellular technology 5 G further poses more requirements on the endto-end evolution to fully utilize its ultra-high band-width,while existing network diagnostic tools focus on above-IP layers or below-IP layers only.We then propose HiMoDiag,which enables flexible online analysis of the network performance in a cross-layer manner,i.e.,from the top(application layer)to the bottom(physical layer).We believe HiMoDiag could greatly simplify the process of pinpointing the deficiencies of the Internet access delivery on HSR,lead to more timely optimization and ultimately help to improve the network performance.展开更多
The rapid advancement of high-speed electronic devices has driven the need for new materials that can meet the demands for higher performance,miniaturization,and energy efficiency.Among these materials,graphene has ga...The rapid advancement of high-speed electronic devices has driven the need for new materials that can meet the demands for higher performance,miniaturization,and energy efficiency.Among these materials,graphene has garnered significant attention due to its exceptional electrical,thermal,and mechanical properties.This paper reviews the research progress on graphene-based composites and their application in high-speed electronics,focusing on the material's unique characteristics and its potential to enhance the performance of electronic devices.The paper examines various graphene-based composite materials,including graphene/polymer,graphene/metal,and graphene/ceramic composites,highlighting their fabrication methods,functionalization strategies,and integration with other materials.Moreover,the paper explores the critical challenges related to scalability,interface compatibility,and integration with existing semiconductor processes.In addition,performance evaluation methodologies and reliability assessments are discussed in the context of electrical,thermal,and mechanical properties.Despite the promising potential of graphene-based composites,challenges such as cost-effective large-scale production,material dispersion,and interface engineering remain.The review concludes by offering insights into future directions for graphene-based materials in high-speed electronic devices,emphasizing the need for further research into scalable manufacturing techniques and functionalization strategies to overcome these challenges.展开更多
Currently,most trains are equipped with dedicated cameras for capturing pantograph videos.Pantographs are core to the high-speed-railway pantograph-catenary system,and their failure directly affects the normal operati...Currently,most trains are equipped with dedicated cameras for capturing pantograph videos.Pantographs are core to the high-speed-railway pantograph-catenary system,and their failure directly affects the normal operation of high-speed trains.However,given the complex and variable real-world operational conditions of high-speed railways,there is no real-time and robust pantograph fault-detection method capable of handling large volumes of surveillance video.Hence,it is of paramount importance to maintain real-time monitoring and analysis of pantographs.Our study presents a real-time intelligent detection technology for identifying faults in high-speed railway pantographs,utilizing a fusion of self-attention and convolution features.We delved into lightweight multi-scale feature-extraction and fault-detection models based on deep learning to detect pantograph anomalies.Compared with traditional methods,this approach achieves high recall and accuracy in pantograph recognition,accurately pinpointing issues like discharge sparks,pantograph horns,and carbon pantograph-slide malfunctions.After experimentation and validation with actual surveillance videos of electric multiple-unit train,our algorithmic model demonstrates real-time,high-accuracy performance even under complex operational conditions.展开更多
In order to ensure the uninterrupted communication between high-speed train and base station,driving safety and satisfying online experience of passengers,a dual-link switching algorithm based on CNN-WaveNet decision ...In order to ensure the uninterrupted communication between high-speed train and base station,driving safety and satisfying online experience of passengers,a dual-link switching algorithm based on CNN-WaveNet decision parameter multi-step prediction model is proposed to establish a two-hop relay communication system model between the high-speed train and the base station.Firstly,the switching algorithm uses convolution neural network(CNN)to extract the time sequence characteristics of decision parameters.Then,it learns the mapping relationship between feature information and decision parameters based on WaveNet and combining with rolling prediction method to realize multi-step prediction of decision parameters.Finally,dual-antenna communication mode is adopted to realize dual-link communication.The simulation results show that the proposed handover algorithm can improve handover trigger rate and handover success rate.展开更多
Intelligent polymers have garnered significant attention for enhancing component safety,but there are still obstacles to achieving rapid self-healing at room temperature.Here,inspired by the microscopic layered struct...Intelligent polymers have garnered significant attention for enhancing component safety,but there are still obstacles to achieving rapid self-healing at room temperature.Here,inspired by the microscopic layered structure of mother-of-pearl,we have developed a biomimetic composite with high strength and self-repairing capabilities,achieved by the ordered arrangement of pearl-like structures within a flexible polyurethane matrix and GO nanosheets functionalized by in situ polymerization of carbon dots(CDs),this biomimetic interface design approach results in a material strength of 8 MPa and toughness(162 MJ m^(-3)),exceptional ductile properties(2697%elongation at break),and a world-record the fast and high-efficient self-healing ability at room temperature(96%at 25℃for 60 min).Thereby these composites overcome the limitations of dynamic composite networks of graphene that struggle to balance repair capability and robustness,and the CDs in situ loaded in the interfacial layer inhibit corrosion and prevent damage to the metal substrate during the repair process.(TheƵ_(f=0.01Hz)was 1.81×10^(9)Ωcm^(2)after 2 h of healing).Besides,the material can be intelligently actuated and shape memory repaired,which provides reliable protection for developments in smart and flexible devices such as robots and electronic skins.展开更多
基金substantially supported by the National Natural Science Foundation of China under Grant No.62002263in part by Tianjin Municipal Education Commission Research Program Project under 2022KJ012Tianjin Science and Technology Program Projects:24YDTPJC00630.
文摘With technological advancements,high-speed rail has emerged as a prevalent mode of transportation.During travel,passengers exhibit a growing demand for streaming media services.However,the high-speed mobile networks environment poses challenges,including frequent base station handoffs,which significantly degrade wireless network transmission performance.Improving transmission efficiency in high-speed mobile networks and optimizing spatiotemporal wireless resource allocation to enhance passengers’media experiences are key research priorities.To address these issues,we propose an Adaptive Cross-Layer Optimization Transmission Method with Environment Awareness(ACOTM-EA)tailored for high-speed rail streaming media.Within this framework,we develop a channel quality prediction model utilizing Kalman filtering and an algorithm to identify packet loss causes.Additionally,we introduce a proactive base station handoffstrategy to minimize handoffrelated disruptions and optimize resource distribution across adjacent base stations.Moreover,this study presents a wireless resource allocation approach based on an enhanced genetic algorithm,coupled with an adaptive bitrate selection mechanism,to maximize passenger Quality of Experience(QoE).To evaluate the proposed method,we designed a simulation experiment and compared ACOTM-EA with established algorithms.Results indicate that ACOTM-EA improves throughput by 11%and enhances passengers’media experience by 5%.
基金funded in part by the National Natural Science Foundation of China(62261024 and U2001213)in part by National Key Research and Development Project(2020YFB1807204)+2 种基金in part by Science and Technology Project of Education Department of Jiangxi Province(GJJ214606 and GJJ2205201)in part by Key Laboratory of Universal Wireless Communications(BUPT),Ministry of Education,P.R.China(KFKT-2022101)in part by the Jiangxi Provincial Natural Science Foundation(20212BAB212001)。
文摘The integration of high-speed railway communication systems with 5G technology is widely recognized as a significant development.Due to the considerable mobility of trains and the complex nature of the environment,the wireless channel exhibits non-stationary characteristics and fast time-varying characteristics,which presents significant hurdles in terms of channel estimation.In addition,the use of massive MIMO technology in the context of 5G networks also leads to an increase in the complexity of estimation.To address the aforementioned issues,this paper presents a novel approach for channel estimation in high mobility scenarios using a reconstruction and recovery network.In this method,the time-frequency response of the channel is considered as a two-dimensional image.The Fast Super-Resolution Convolution Neural Network(FSRCNN)is used to first reconstruct channel images.Next,the Denoising Convolution Neural Network(DnCNN)is applied to reduce the channel noise and improve the accuracy of channel estimation.Simulation results show that the accuracy of the channel estimation model surpasses that of the standard channel estimation method,while also exhibiting reduced algorithmic complexity.
基金Foundation： National Natural Science Foundation of China, No. 41271134
文摘Traffic is an indispensable prerequisite for a tourism system. The ＂four vertical and four horizontal＂ HSR network represents an important milestone of the ＂traffic revolution＂ in China. It will affect the spatial pattern of tourism accessibility in Chinese cities, thus substan- tially increasing their power to attract tourists and their radiation force. This paper examines the evolution and spatial characteristics of the power to attract tourism of cities linked by China＇s HSR network by measuring the influence of accessibility of 338 HSR-linked cities using GIS analysis. The results show the following. （1） The accessibility of Chinese cities is optimized by the HSR network, whose spatial pattern of accessibility exhibits an obvious traf- fic direction and causes a high-speed rail-corridor effect. （2） The spatial pattern of tourism field strength in Chinese cities exhibits the dual characteristics of multi-center annular diver- gence and dendritic diffusion. Dendritic diffusion is particularly more obvious along the HSR line. The change rate of urban tourism field strength forms a high-value corridor along the HSR line and exhibits a spatial pattern of decreasing area from the center to the outer limit along the HSR line. （3） The influence of the higher and highest tourism field strength areas along the HSR line is most significant, and the number of cities that distribute into these two types of tourism field strengths significantly increases： their area expands by more than 100% HSR enhances the tourism field strength value of regional central cities, and the radiation range of tourism attraction extends along the HSR line.
基金National Key R&D Program(Grant No.2020YFB2007700),National Natural Science Foundation of China(Grant Nos.11790282,12032017,12002221 and 11872256)S&T Program of Hebei(Grant No.20310803D)+1 种基金Natural Science Foundation of Hebei Province(Grant No.A2020210028)State Foundation for Studying Abroad.
文摘High-speed trains often use temperature sensors to monitor the motion state of bearings.However,the temperature of bearings can be affected by factors such as weather and faults.Therefore,it is necessary to analyze in detail the relationship between the bearing temperature and influencing factors.In this study,a dynamics model of the axle box bearing of high-speed trains is established.The model can obtain the contact force between the rollers and raceway and its change law when the bearing contains outer-ring,inner-ring,and rolling-element faults.Based on the model,a thermal network method is introduced to study the temperature field distribution of the axle box bearings of high-speed trains.In this model,the heat generation,conduction,and dispersion of the isothermal nodes can be solved.The results show that the temperature of the contact point between the outer-ring raceway and rolling-elements is the highest.The relationships between the node temperature and the speed,fault type,and fault size are analyzed,finding that the higher the speed,the higher the node temperature.Under different fault types,the node temperature first increases and then decreases as the fault size increases.The effectiveness of the model is demonstrated using the actual temperature data of a high-speed train.This study proposes a thermal network model that can predict the temperature of each component of the bearings on a high-speed train under various speed and fault conditions.
基金The National Natural Science Foundation of China(No.51465035)the Natural Science Foundation of Gansu,China(No.20JR5R-A466)。
文摘To predict the temperature of a motorized spindle more accurately,a novel temperature prediction model based on the back-propagation neural network optimized by adaptive particle swarm optimization(APSO-BPNN)is proposed.First,on the basis of the PSO-BPNN algorithm,the adaptive inertia weight is introduced to make the weight change with the fitness of the particle,the adaptive learning factor is used to obtain different search abilities in the early and later stages of the algorithm,the mutation operator is incorporated to increase the diversity of the population and avoid premature convergence,and the APSO-BPNN model is constructed.Then,the temperature of different measurement points of the motorized spindle is forecasted by the BPNN,PSO-BPNN,and APSO-BPNN models.The experimental results demonstrate that the APSO-BPNN model has a significant advantage over the other two methods regarding prediction precision and robustness.The presented algorithm can provide a theoretical basis for intelligently controlling temperature and developing an early warning system for high-speed motorized spindles and machine tools.
基金supported by International Science and Technology Cooperation project(Grant No.2008DFA71750)
文摘In metal cutting industry it is a common practice to search for optimal combination of cutting parameters in order to maximize the tool life for a fixed minimum value of material removal rate(MRR).After the advent of high-speed milling(HSM)pro cess,lots of experimental and theoretical researches have been done for this purpose which mainly emphasized on the optimization of the cutting parameters.It is highly beneficial to convert raw data into a comprehensive knowledge-based expert system using fuzzy logic as the reasoning mechanism.In this paper an attempt has been presented for the extraction of the rules from fuzzy neural network(FNN)so as to have the most effective knowledge-base for given set of data.Experiments were conducted to determine the best values of cutting speeds that can maximize tool life for different combinations of input parameters.A fuzzy neural network was constructed based on the fuzzification of input parameters and the cutting speed.After training process,raw rule sets were extracted and a rule pruning approach was proposed to obtain concise linguistic rules.The estimation process with fuzzy inference showed that the optimized combination of fuzzy rules provided the estimation error of only 6.34 m/min as compared to 314 m/min of that of randomized combination of rule s.
基金Sponsored by the National High Technology Development Program of China (Grant No. 2002AA142020).
文摘With the increasing enlargement of network scale and the rapid development of network techniques, large numbers of the network applications begin to appear. Packet capture plays an important role as one basic technique used in each field of the network applications. In a high-speed network, the heavy traffic of network transmission challenges the packet capture techniques. This paper does an in-depth analysis on the traditional packet capture mechanisms in Linux, and then measures the performance bottleneck in the process of packet capture. The methods for improving the packet capture performance are presented and an optimized packet capture scheme is also designed and implemented. The test demonstrates that the new packet capture mechanism (Libpacket) can greatly improve the packet capture performance of the network application systems in a high-speed network.
基金National High-Tech Research and Development Program of China (863 Program) (No.2007AA01Z309)
文摘With the continual growth of the variety and complexity of network crime means, the traditional packet feature matching cannot detect all kinds of intrusion behaviors completely. It is urgent to reassemble network stream to perform packet processing at a semantic level above the network layer. This paper presents an efficient TCP stream reassembly mechanism for real-time processing of high-speed network traffic. By analyzing the characteristics of network stream in high-speed network and TCP connection establishment process, several polices for designing the reassembly mechanism are built. Then, the reassembly implementation is elaborated in accordance with the policies. Finally, the reassembly mechanism is compared with the traditional reassembly mechanism by the network traffic captured in a typical gigabit gateway. Experiment results illustrate that the reassembly mechanism is efficient and can satisfy the real-time property requirement of traffic analysis system in high-speed network.
基金financially supported by the National Key Research and Development Program(No.2018YFA0702900)the National Natural Science Foundation of China(Nos.51774265 and 51701225)+3 种基金the National Science and Technology Major Project of China(Nos.2019ZX06004010 and 2017-VII008-0101)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDC04000000)the LingChuang Research Project of China National Nuclear Corporation Program of CAS Interdisciplinary Innovation TeamYouth Innovation Promotion Association,CAS。
文摘The interfacial oxidation behavior of Cr_(4)Mo_(4) V high-speed steel(HSS)joints undergoing hot-compression bonding was investigated by using optical microscopy(OM),scanning electron microscopy(SEM),and transmission electron microscopy(TEM).In the heating and holding processes,dispersed rod-like and granularδ-Al_(2)O_(3) oxides were formed at the interface and in the matrix near the interface due to the selective oxidation and internal oxidation of Al,while irregular Si-Al-O compounds and spheroidal SiO_(2) particles were formed at the interface.After the post-holding treatment,SiO_(2) oxides and Si-Al-O compounds were dissolved into the matrix,andδ-Al_(2)O_(3) oxides were transformed into nanoscaleα-Al_(2)O_(3) particles,which did not deteriorate the mechanical properties of the joints.The formation and migration of newly-formed grain boundaries by plastic deformation and post-holding treatment were the main mechanism for interface healing.The tensile test results showed that the strength of the healed joints was comparable to that of the base material,and the in-situ tensile observations proved that the fracture was initiated at the grain boundary of the matrix rather than at the interface.The clarification of interfacial oxides and microstructure is essential for the application of hot-compression bonding of HSSs.
文摘The congestion control mechanisms of the current standard TCP constrain the congestion windows that can be achieved by TCP in high-speed networks, which leads to low link utilization. HSTCP is one solution to solve this problem by modifying the congestion control mechanism to have the characteristics of TCP friendliness in high loss rate environment and high scalability in low loss rate environment. However, experiments revealed that HSTCP has severe RTT unfairness. After analyzing the RTT unfairness in HSTCP with a model, we proposed CW-HSTCP, which added a fair factor to decrease the difference of congestion window caused by different RTT. Fair factor of long RTT flows can cause a sharp window increment that is easy to cause a bursty traffic, so a method called block-pacing was adopted. Simulation results showed that our new proposal could alleviate the RTT unfairness while keeping advantages of HSTCP.
基金Project supported by the National Key Research and Development Program of China(Grant No.2019YFF0301400)the National Natural Science Foundation of China(Grant Nos.61671031,61722102,41722103,and 61961146005)。
文摘China has the largest high-speed railway(HSR) system in the world, and it has gradually reshaped the urban network.The HSR system can be represented as different types of networks in terms of the nodes and various relationships(i.e.,linkages) between them. In this paper, we first introduce a general dual network model, including a physical network(PN)and a logical network(LN) to provide a comparative analysis for China’s high-speed rail network via complex network theory. The PN represents a layout of stations and rail tracks, and forms the basis for operating all trains. The LN is a network composed of the origin and destination stations of each high-speed train and the train flows between them. China’s high-speed railway(CHSR) has different topological structures and link strengths for PN in comparison with the LN. In the study, the community detection is used to analyze China’s high-speed rail networks and several communities are found to be similar to the layout of planned urban agglomerations in China. Furthermore, the hierarchies of urban agglomerations are different from each other according to the strength of inter-regional interaction and intra-regional interaction, which are respectively related to location and spatial development strategies. Moreover, a case study of the Yangtze River Delta shows that the hub stations have different resource divisions and are major contributors to the gap between train departure and arrival flows.
文摘The hot deformation behavior of TI (18W-4Cr-1V) high-speed steel was investigated by means of continuous compression tests performed on Gleeble 1500 thermomechan- ical simulator in a wide range of tempemtures (950℃-1150℃) with strain rotes of 0.001s-1-10s-1 and true strains of 0-0. 7. The flow stress at the above hot defor- mation conditions is predicted by using BP artificial neural network. The architecture of network includes there are three input parameters:strain rate,temperature T and true strain , and just one output parameter, the flow stress ,2 hidden layers are adopted, the first hidden layer includes 9 neurons and second 10 negroes. It has been verified that BP artificial neural network with 3-9-10-1 architecture can predict flow stress of high-speed steel during hot deformation very well. Compared with the prediction method of flow stress by using Zaped-Holloman parumeter and hyperbolic sine stress function, the prediction method by using BP artificial neurul network has higher efficiency and accuracy.
文摘For the congestion problems in high-speed networks, a genetic based fuzzy Q-learning flow controller is proposed. Because of the uncertainties and highly time-varying, it is not easy to accurately obtain the complete information for high-speed networks. In this case, the Q-learning, which is independent of mathematic model, and prior-knowledge, has good performance. The fuzzy inference is introduced in order to facilitate generalization in large state space, and the genetic operators are used to obtain the consequent parts of fuzzy rules. Simulation results show that the proposed controller can learn to take the best action to regulate source flow with the features of high throughput and low packet loss ratio, and can avoid the occurrence of congestion effectively.
基金Supported by the National Natural Science Foundation of China(No.61302080)Scientific Research Starting Foundation of Fuzhou University(No.022572)Science and Technology Development Foundation of Fuzhou University(No.2013-XY-27)
文摘High-speed train communication system is a typical high-mobility wireless communication network. Resource allocation problem has a great impact on the system performance. However, conventional resource allocation approaches in cellular network cannot be directly applied to this kind of special communication environment. A multidomain resource allocation strategy was proposed in the orthogonal frequency-division multiple access(OFDMA) of high-speed. By analyzing the effect of Doppler shift, sub-channels, antennas, time slots and power were jointly considered to maximize the energy efficiency under the constraint of total transmission power. For the purpose of reducing the computational complexity, noisy chaotic neural network algorithm was used to solve the above optimization problem. Simulation results showed that the proposed resource allocation method had a better performance than the traditional strategy.
基金the National Natural Science Foundation of China(41871151).
文摘The construction of high-speed rail(HSR)network has promoted the social-economic ties of cities,accelerated the compression of time and space,and changed the pattern of regional development.In this paper,with the adoption of the operation frequency data of HSR from 12306 website,and based on the HSR connection strength model and social network analysis model,as well as according to the HSR connection strength,HSR network density,centrality,agglomeration subgroup,and other indicators,we analyzed the characteristics of HSR network structure in Northeast China.Results show that the number of HSR cities in Northeast China is small,cities in HSR network generally exhibit weak connectivity,and the existence of HSR network marginalizes cities such as Ulanhot,Baicheng,and Songyuan,which significantly reduce the overall network connectivity of Northeast China.The overall centrality of HSR network in Northeast China is characterized by“one axis,four edges”;specifically,the one axis is located in Harbin-Dalian transportation line and the four edges are located on both sides of the main axis of Harbin-Dalian transportation line.Eight agglomeration subgroups(four double city subgroups and four multi city subgroups)have formed in Northeast China.The core status of Shenyang in HSR network is improved significantly,and“one axis and two wings”HSR network in Liaoning Province is improved significantly.With the gradual expansion of Chaoyang-Fuxin,Dandong-Benxi,and Jilin-Yanji branch networks,the“point axis”HSR network mode in Northeast China has gradually developed and matured.In the future,it is recommended to rely on eight agglomerating subgroups to encrypt HSR network structure,create secondary node central cities,and gradually build a new pattern of opening up in Northeast China.
基金supported by National Key Research and Development Plan,China(Grant No.2020YFB1710900)National Natural Science Foundation of China(Grant No.62022005 and 62172008).
文摘Nowadays,high mobility scenarios have become increasingly common.The widespread adoption of High-speed Rail(HSR)in China exemplifies this trend,while more promising use cases,such as vehicle-to-everything,continue to emerge.However,the Internet access provided in high mobility environments stllstruggles to achieve seamless connectivity.The next generation of wireless cellular technology 5 G further poses more requirements on the endto-end evolution to fully utilize its ultra-high band-width,while existing network diagnostic tools focus on above-IP layers or below-IP layers only.We then propose HiMoDiag,which enables flexible online analysis of the network performance in a cross-layer manner,i.e.,from the top(application layer)to the bottom(physical layer).We believe HiMoDiag could greatly simplify the process of pinpointing the deficiencies of the Internet access delivery on HSR,lead to more timely optimization and ultimately help to improve the network performance.
文摘The rapid advancement of high-speed electronic devices has driven the need for new materials that can meet the demands for higher performance,miniaturization,and energy efficiency.Among these materials,graphene has garnered significant attention due to its exceptional electrical,thermal,and mechanical properties.This paper reviews the research progress on graphene-based composites and their application in high-speed electronics,focusing on the material's unique characteristics and its potential to enhance the performance of electronic devices.The paper examines various graphene-based composite materials,including graphene/polymer,graphene/metal,and graphene/ceramic composites,highlighting their fabrication methods,functionalization strategies,and integration with other materials.Moreover,the paper explores the critical challenges related to scalability,interface compatibility,and integration with existing semiconductor processes.In addition,performance evaluation methodologies and reliability assessments are discussed in the context of electrical,thermal,and mechanical properties.Despite the promising potential of graphene-based composites,challenges such as cost-effective large-scale production,material dispersion,and interface engineering remain.The review concludes by offering insights into future directions for graphene-based materials in high-speed electronic devices,emphasizing the need for further research into scalable manufacturing techniques and functionalization strategies to overcome these challenges.
基金supported by the National Key R&D Program of China(No.2022YFB4301102).
文摘Currently,most trains are equipped with dedicated cameras for capturing pantograph videos.Pantographs are core to the high-speed-railway pantograph-catenary system,and their failure directly affects the normal operation of high-speed trains.However,given the complex and variable real-world operational conditions of high-speed railways,there is no real-time and robust pantograph fault-detection method capable of handling large volumes of surveillance video.Hence,it is of paramount importance to maintain real-time monitoring and analysis of pantographs.Our study presents a real-time intelligent detection technology for identifying faults in high-speed railway pantographs,utilizing a fusion of self-attention and convolution features.We delved into lightweight multi-scale feature-extraction and fault-detection models based on deep learning to detect pantograph anomalies.Compared with traditional methods,this approach achieves high recall and accuracy in pantograph recognition,accurately pinpointing issues like discharge sparks,pantograph horns,and carbon pantograph-slide malfunctions.After experimentation and validation with actual surveillance videos of electric multiple-unit train,our algorithmic model demonstrates real-time,high-accuracy performance even under complex operational conditions.
基金supported by National Natural Science Foundation of China(Nos.62161016,61661025)Gansu Provincial Science and Technology Plan(No.20JR10RA273)。
文摘In order to ensure the uninterrupted communication between high-speed train and base station,driving safety and satisfying online experience of passengers,a dual-link switching algorithm based on CNN-WaveNet decision parameter multi-step prediction model is proposed to establish a two-hop relay communication system model between the high-speed train and the base station.Firstly,the switching algorithm uses convolution neural network(CNN)to extract the time sequence characteristics of decision parameters.Then,it learns the mapping relationship between feature information and decision parameters based on WaveNet and combining with rolling prediction method to realize multi-step prediction of decision parameters.Finally,dual-antenna communication mode is adopted to realize dual-link communication.The simulation results show that the proposed handover algorithm can improve handover trigger rate and handover success rate.
基金support of the Jiangsu Provincial Department of Science and Technology Innovation Support Program(No.BK20222004)the National Natural Science Foundation of China(No.52201077).
文摘Intelligent polymers have garnered significant attention for enhancing component safety,but there are still obstacles to achieving rapid self-healing at room temperature.Here,inspired by the microscopic layered structure of mother-of-pearl,we have developed a biomimetic composite with high strength and self-repairing capabilities,achieved by the ordered arrangement of pearl-like structures within a flexible polyurethane matrix and GO nanosheets functionalized by in situ polymerization of carbon dots(CDs),this biomimetic interface design approach results in a material strength of 8 MPa and toughness(162 MJ m^(-3)),exceptional ductile properties(2697%elongation at break),and a world-record the fast and high-efficient self-healing ability at room temperature(96%at 25℃for 60 min).Thereby these composites overcome the limitations of dynamic composite networks of graphene that struggle to balance repair capability and robustness,and the CDs in situ loaded in the interfacial layer inhibit corrosion and prevent damage to the metal substrate during the repair process.(TheƵ_(f=0.01Hz)was 1.81×10^(9)Ωcm^(2)after 2 h of healing).Besides,the material can be intelligently actuated and shape memory repaired,which provides reliable protection for developments in smart and flexible devices such as robots and electronic skins.
