The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,th...The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,this study proposes an intelligent decision-making framework based on a deep long short-term memory Q-network.This framework transforms the real-time sequencing for bolter recovery problem into a partially observable Markov decision process.It employs a stacked long shortterm memory network to accurately capture the long-range temporal dependencies of bolter event chains and fuel consumption.Furthermore,it integrates a prioritized experience replay training mechanism to construct a safe and adaptive scheduling system capable of millisecond-level real-time decision-making.Experimental demonstrates that,within large-scale mass recovery scenarios,the framework achieves zero safety violations in static environments and maintains a fuel safety violation rate below 10%in dynamic scenarios,with single-step decision times at the millisecond level.The model exhibits strong generalization capability,effectively responding to unforeseen emergent situations—such as multiple bolters and fuel emergencies—without requiring retraining.This provides robust support for efficient carrier-based aircraft recovery operations.展开更多
Space-division multiplexing(SDM)utilizing uncoupled multi-core fibers(MCF)is considered a promising candidate for nextgeneration high-speed optical transmission systems due to its huge capacity and low inter-core cros...Space-division multiplexing(SDM)utilizing uncoupled multi-core fibers(MCF)is considered a promising candidate for nextgeneration high-speed optical transmission systems due to its huge capacity and low inter-core crosstalk.In this paper,we demonstrate a realtime high-speed SDM transmission system over a field-deployed 7-core MCF cable using commercial 400 Gbit/s backbone optical transport network(OTN)transceivers and a network management system.The transceivers employ a high noise-tolerant quadrature phase shift keying(QPSK)modulation format with a 130 Gbaud rate,enabled by optoelectronic multi-chip module(OE-MCM)packaging.The network management system can effectively manage and monitor the performance of the 7-core SDM OTN system and promptly report failure events through alarms.Our field trial demonstrates the compatibility of uncoupled MCF with high-speed OTN transmission equipment and network management systems,supporting its future deployment in next-generation high-speed terrestrial cable transmission networks.展开更多
Micro-nano Earth Observation Satellite(MEOS)constellation has the advantages of low construction cost,short revisit cycle,and high functional density,which is considered a promising solution for serving rapidly growin...Micro-nano Earth Observation Satellite(MEOS)constellation has the advantages of low construction cost,short revisit cycle,and high functional density,which is considered a promising solution for serving rapidly growing observation demands.The observation Scheduling Problem in the MEOS constellation(MEOSSP)is a challenging issue due to the large number of satellites and tasks,as well as complex observation constraints.To address the large-scale and complicated MEOSSP,we develop a Two-Stage Scheduling Algorithm based on the Pointer Network with Attention mechanism(TSSA-PNA).In TSSA-PNA,the MEOS observation scheduling is decomposed into a task allocation stage and a single-MEOS scheduling stage.In the task allocation stage,an adaptive task allocation algorithm with four problem-specific allocation operators is proposed to reallocate the unscheduled tasks to new MEOSs.Regarding the single-MEOS scheduling stage,we design a pointer network based on the encoder-decoder architecture to learn the optimal singleMEOS scheduling solution and introduce the attention mechanism into the encoder to improve the learning efficiency.The Pointer Network with Attention mechanism(PNA)can generate the single-MEOS scheduling solution quickly in an end-to-end manner.These two decomposed stages are performed iteratively to search for the solution with high profit.A greedy local search algorithm is developed to improve the profits further.The performance of the PNA and TSSA-PNA on singleMEOS and multi-MEOS scheduling problems are evaluated in the experiments.The experimental results demonstrate that PNA can obtain the approximate solution for the single-MEOS scheduling problem in a short time.Besides,the TSSA-PNA can achieve higher observation profits than the existing scheduling algorithms within the acceptable computational time for the large-scale MEOS scheduling problem.展开更多
Solar energy is a pivotal clean energy source in the transition to carbon neutrality from fossil fuels.However,the intermittent and stochastic characteristics of solar radiation pose challenges for accurate simulation...Solar energy is a pivotal clean energy source in the transition to carbon neutrality from fossil fuels.However,the intermittent and stochastic characteristics of solar radiation pose challenges for accurate simulation and prediction.Accurately simulating and predicting solar radiation and its variability are crucial for optimizing solar energy utilization.This study conducted simulation experiments using the WRF-Solar model from 25 June to 25 July 2022,to evaluate the accuracy and performance of the simulated solar radiation across China.The simulations covered the whole country with a grid spacing of 27 km and were compared with ground observation network data from the Chinese Ecosystem Research Network.The results indicated that WRF-Solar can accurately capture the spatiotemporal patterns of global horizontal irradiance over China,but there is still an overestimation of solar radiation,and the model underestimates the total cloud cover.The root-mean-square error ranged from 92.83 to 188.13 W m^(-2) and the mean bias(MB)ranged from 21.05 to 56.22 W m^(-2).The simulation showed the smallest MB at Lhasa on the Qinghai–Tibet Plateau,while the largest MB was observed in Southeast China.To enhance the accuracy of solar radiation simulation,the authors compared the Fast All-sky Radiation Model for Solar with the Rapid Radiative Transfer Model for General Circulation Models and found that the former provides better simulation.展开更多
The current research of real-time observation for vehicle roll steer angle and compliance steer angle（both of them comprehensively referred as the additional steer angle in this paper） mainly employs the linear vehi...The current research of real-time observation for vehicle roll steer angle and compliance steer angle（both of them comprehensively referred as the additional steer angle in this paper） mainly employs the linear vehicle dynamic model, in which only the lateral acceleration of vehicle body is considered. The observation accuracy resorting to this method cannot meet the requirements of vehicle real-time stability control, especially under extreme driving conditions. The paper explores the solution resorting to experimental method. Firstly, a multi-body dynamic model of a passenger car is built based on the ADAMS/Car software, whose dynamic accuracy is verified by the same vehicle＇s roadway test data of steady static circular test. Based on this simulation platform, several influencing factors of additional steer angle under different driving conditions are quantitatively analyzed. Then ε-SVR algorithm is employed to build the additional steer angle prediction model, whose input vectors mainly include the sensor information of standard electronic stability control system（ESC）. The method of typical slalom tests and FMVSS 126 tests are adopted to make simulation, train model and test model＇s generalization performance. The test result shows that the influence of lateral acceleration on additional steer angle is maximal （the magnitude up to 1°）, followed by the longitudinal acceleration-deceleration and the road wave amplitude （the magnitude up to 0.3°）. Moreover, both the prediction accuracy and the calculation real-time of the model can meet the control requirements of ESC This research expands the accurate observation methods of the additional steer angle under extreme driving conditions.展开更多
Due to the excellent comprehensive mechanical properties and toughness of bainite steels,bainite is regarded as a most desirable microstructure for the new generation of high-strength weathering steels.The formation o...Due to the excellent comprehensive mechanical properties and toughness of bainite steels,bainite is regarded as a most desirable microstructure for the new generation of high-strength weathering steels.The formation of bainite was observed in real time in a high-strength weathering steel,and the results showed that bainite laths show impingement during phase transformation.The preferred regions of nucleation sites were identified,and the growth rate of bainite was measured.The growth mechanism of bainite was demonstrated to exhibit growth rate contributions from both the diffusion mechanism and the shear mechanism.Subsequently,the heterogeneous phases that form preferred sites for bainite nucleation were quantitatively identified by scanning electron microscopy(SEM),energy-dispersive X-ray spectrometry(EDS),and calculation of phase diagram(CALPHAD).The austenite grain sizes in crease with increasing austenite temperature,which leads to longer bainite laths.The influence of a small lattice disregistry between the heterogeneous phases and bainite on the bainite nucleation was studied.The disregistries between the favorable heterogeneous phases of VN,VC,TiN,or TiC and the ot-Fe in bainite are 2.9,3.1,3.9,and 4.6%,respectively.Therefore,VN,VC,TiN,and TiC can act as highly effective nuclei for bainite during the bainite transformation.展开更多
A fuzzy observations-based radial basis function neural network （FORBFNN） is presented for modeling nonlinear systems in which the observations of response are imprecise but can be represented as fuzzy membership fu...A fuzzy observations-based radial basis function neural network （FORBFNN） is presented for modeling nonlinear systems in which the observations of response are imprecise but can be represented as fuzzy membership functions. In the FORBFNN model, the weight coefficients of nodes in the hidden layer are identified by using the fuzzy expectation-maximization （ EM ） algorithm, whereas the optimal number of these nodes as well as the centers and widths of radial basis functions are automatically constructed by using a data-driven method. Namely, the method starts with an initial node, and then a new node is added in a hidden layer according to some rules. This procedure is not terminated until the model meets the preset requirements. The method considers both the accuracy and complexity of the model. Numerical simulation results show that the modeling method is effective, and the established model has high prediction accuracy.展开更多
Introduction Integrins are a large family of adhesion molecules broadly expressed on the surface of a wide variety of cells as heterodimers. Binding of integrins to ligands provides not only mechanical anchorage for t...Introduction Integrins are a large family of adhesion molecules broadly expressed on the surface of a wide variety of cells as heterodimers. Binding of integrins to ligands provides not only mechanical anchorage for the cell to another cell or展开更多
With the flourishing development of Unmanned Aerial Vehicles(UAVs), the mission tasks of UAVs have become more and more complex. Consequently, a Real-Time Operating System(RTOS) that provides operating environments fo...With the flourishing development of Unmanned Aerial Vehicles(UAVs), the mission tasks of UAVs have become more and more complex. Consequently, a Real-Time Operating System(RTOS) that provides operating environments for various mission services on these UAVs has become crucial, which leads to the necessity of having a deep understanding of an RTOS. In this paper, an empirical study is conducted on FreeRTOS, a commonly used RTOS for UAVs, from a complex network perspective. A total of 85 releases of FreeRTOS, from V2.4.2 to V10.0.0, are modeled as directed networks, in which the nodes represent functions and the edges denote function calls. It is found that the size of the FreeRTOS network has grown almost linearly with the evolution of the versions, while its main core has evolved steadily. In addition, a k-core analysis-based metric is proposed to identify major functionality changes of FreeRTOS during its evolution.The result shows that the identified versions are consistent with the version change logs. Finally,it is found that the clustering coefficient of the Linux OS scheduler is larger than that of the FreeRTOS scheduler. In conclusion, the empirical results provide useful guidance for developers and users of UAV RTOSs.展开更多
The application and development of a wide-area measurement system(WAMS)has enabled many applications and led to several requirements based on dynamic measurement data.Such data are transmitted as big data information ...The application and development of a wide-area measurement system(WAMS)has enabled many applications and led to several requirements based on dynamic measurement data.Such data are transmitted as big data information flow.To ensure effective transmission of wide-frequency electrical information by the communication protocol of a WAMS,this study performs real-time traffic monitoring and analysis of the data network of a power information system,and establishes corresponding network optimization strategies to solve existing transmission problems.This study utilizes the traffic analysis results obtained using the current real-time dynamic monitoring system to design an optimization strategy,covering the optimization in three progressive levels:the underlying communication protocol,source data,and transmission process.Optimization of the system structure and scheduling optimization of data information are validated to be feasible and practical via tests.展开更多
To achieve smart and personalized medicine, the development of hydrogel dressings with sensing properties and biotherapeutic properties that can act as a sensor to monitor of human health in real-time while speeding u...To achieve smart and personalized medicine, the development of hydrogel dressings with sensing properties and biotherapeutic properties that can act as a sensor to monitor of human health in real-time while speeding up wound healing face great challenge. In the present study, a biocompatible dual-network composite hydrogel(DNCGel) sensor was obtained via a simple process. The dual network hydrogel is constructed by the interpenetration of a flexible network formed of poly(vinyl alcohol)(PVA) physical cross-linked by repeated freeze-thawing and a rigid network of iron-chelated xanthan gum(XG) impregnated with Fe^(3+) interpenetration. The pure PVA/XG hydrogels were chelated with ferric ions by immersion to improve the gel strength(compressive modulus and tensile modulus can reach up to 0.62 MPa and0.079 MPa, respectively), conductivity(conductivity values ranging from 9 × 10^(-4) S/cm to 1 × 10^(-3)S/cm)and bacterial inhibition properties(up to 98.56%). Subsequently, the effects of the ratio of PVA and XG and the immersion time of Fe^(3+) on the hydrogels were investigated, and DNGel3 was given the most priority on a comprehensive consideration. It was demonstrated that the DNCGel exhibit good biocompatibility in vitro, effectively facilitate wound healing in vivo(up to 97.8% healing rate) under electrical stimulation, and monitors human movement in real time. This work provides a novel avenue to explore multifunctional intelligent hydrogels that hold great promise in biomedical fields such as smart wound dressings and flexible wearable sensors.展开更多
The effects of real-time traffic information system(RTTIS)on traffic performance under parallel,grid and ring networks were investigated.The simulation results show that the effects of the proportion of RTTIS usage de...The effects of real-time traffic information system(RTTIS)on traffic performance under parallel,grid and ring networks were investigated.The simulation results show that the effects of the proportion of RTTIS usage depend on the road network structures.For traffic on a parallel network,the performance of groups with and without RTTIS level is improved when the proportion of vehicles using RTTIS is greater than 0 and less than 30%,and a proportion of RTTIS usage higher than 90%would actually deteriorate the performance.For both grid and ring networks,a higher proportion of RTTIS usage always improves the performance of groups with and without RTTIS.For all three network structures,vehicles without RTTIS benefit from some proportion of RTTIS usage in a system.展开更多
This paper examines the effect of the observation time on source identification of a discrete-time susceptible-infectedrecovered diffusion process in a network with snapshot of partial nodes.We formulate the source id...This paper examines the effect of the observation time on source identification of a discrete-time susceptible-infectedrecovered diffusion process in a network with snapshot of partial nodes.We formulate the source identification problem as a maximum likelihood(ML)estimator and develop a statistical inference method based on Monte Carlo simulation(MCS)to estimate the source location and the initial time of diffusion.Experimental results in synthetic networks and real-world networks demonstrate evident impact of the observation time as well as the fraction of the observers on the concerned problem.展开更多
The Global Navigation Satellite System （GNSS） is becoming important for monitoring the variations in the earth＇s ionosphere based on the total electron content （TEC） and iono- spheric electron density （IED）. Th...The Global Navigation Satellite System （GNSS） is becoming important for monitoring the variations in the earth＇s ionosphere based on the total electron content （TEC） and iono- spheric electron density （IED）. The Crustal Movement Observation Network of China （CMONOC）, which includes GNSS stations across China's Mainland, enables the continuous monitoring of the ionosphere over China as accurately as possible. A series of approaches for GNSS-based ionospheric remote sensing and software has been proposed and devel- oped by the Institute of Geodesy and Geophysics （IGG） in Wuhan. Related achievements include the retrieval of ionospheric observables from raw GNSS data, differential code biases estimations in satellites and receivers, models of local and regional ionospheric TEC, and algorithms of ionospheric tomography. Based on these achievements, a software for processing GNSS data to determine the variations in ionospheric TEC and IED over China has been designed and developed by IGG. This software has also been installed at the CMONOC data centers belonging to the China Earthquake Administration and China Meteorological Administration. This paper briefly introduces the related research achievements and indicates potential directions of future work.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 application of unmanned driving in the Internet of Things is one of the concrete manifestations of the application of artificial intelligence technology.Image semantic segmentation can help the unmanned driving sy...The application of unmanned driving in the Internet of Things is one of the concrete manifestations of the application of artificial intelligence technology.Image semantic segmentation can help the unmanned driving system by achieving road accessibility analysis.Semantic segmentation is also a challenging technology for image understanding and scene parsing.We focused on the challenging task of real-time semantic segmentation in this paper.In this paper,we proposed a novel fast architecture for real-time semantic segmentation named DuFNet.Starting from the existing work of Bilateral Segmentation Network(BiSeNet),DuFNet proposes a novel Semantic Information Flow(SIF)structure for context information and a novel Fringe Information Flow(FIF)structure for spatial information.We also proposed two kinds of SIF with cascaded and paralleled structures,respectively.The SIF encodes the input stage by stage in the ResNet18 backbone and provides context information for the feature fusionmodule.Features from previous stages usually contain rich low-level details but high-level semantics for later stages.Themultiple convolutions embed in Parallel SIF aggregate the corresponding features among different stages and generate a powerful global context representation with less computational cost.The FIF consists of a pooling layer and an upsampling operator followed by projection convolution layer.The concise component provides more spatial details for the network.Compared with BiSeNet,our work achieved faster speed and comparable performance with 72.34%mIoU accuracy and 78 FPS on Cityscapes Dataset based on the ResNet18 backbone.展开更多
With the popularity of smart handheld devices, mobile streaming video has multiplied the global network traffic in recent years. A huge concern of users' quality of experience(Qo E) has made rate adaptation method...With the popularity of smart handheld devices, mobile streaming video has multiplied the global network traffic in recent years. A huge concern of users' quality of experience(Qo E) has made rate adaptation methods very attractive. In this paper, we propose a two-phase rate adaptation strategy to improve users' real-time video Qo E. First, to measure and assess video Qo E, we provide a continuous Qo E prediction engine modeled by RNN recurrent neural network. Different from traditional Qo E models which consider the Qo E-aware factors separately or incompletely, our RNN-Qo E model accounts for three descriptive factors(video quality, rebuffering, and rate change) and reflects the impact of cognitive memory and recency. Besides, the video playing is separated into the initial startup phase and the steady playback phase, and we takes different optimization goals for each phase: the former aims at shortening the startup delay while the latter ameliorates the video quality and the rebufferings. Simulation results have shown that RNN-Qo E can follow the subjective Qo E quite well, and the proposed strategy can effectively reduce the occurrence of rebufferings caused by the mismatch between the requested video rates and the fluctuated throughput and attains standout performance on real-time Qo E compared with classical rate adaption methods.展开更多
The unreasonable observation arrangements in the satellite operation control center(SOCC)may result in the observation data cannot be downloaded as scheduled.Meanwhile,if the operation instructions released by the sat...The unreasonable observation arrangements in the satellite operation control center(SOCC)may result in the observation data cannot be downloaded as scheduled.Meanwhile,if the operation instructions released by the satellite telemetry tracking center(STTC)for the on-board payloads are not injected on the specific satellites in time,the corresponding satellites cannot perform the observation operations as planned.Therefore,there is an urgent need to design an integrated instruction release,and observation task planning(I-IRO-TP)scheme by efficiently collaborating the SOCC and STTC.Motivated by this fact,we design an interaction mechanism between the SOCC and the STTC,where we first formulate the I-IRO-TP problem as a constraint satisfaction problem aiming at maximizing the number of completed tasks.Furthermore,we propose an interactive imaging task planning algorithm based on the analysis of resource distribution in the STTC during the previous planning periods to preferentially select the observation arcs that not only satisfy the requirements in the observation resource allocation phase but also facilitate the arrangement of measurement and control instruction release.We conduct extensive simulations to demonstrate the effectiveness of the proposed algorithm in terms of the number of completed tasks.展开更多
In this paper, the model of the online real-time information transmission network, such as wechat, micro-blog, and QQ network, is proposed and built, based on the connection properties between users of the online real...In this paper, the model of the online real-time information transmission network, such as wechat, micro-blog, and QQ network, is proposed and built, based on the connection properties between users of the online real-time information transmission network, and combined with the local world evolving characteristics in complex network, then the statistical topological properties of the network is obtained by numerical simulation. Furthermore, we simulated the process of information transmission on the network, according to the actual characteristics of the online real-time information transmission. Statistics show that the degree distribution presents the characteristics of scale free network, presenting power law distribution, while the average path length, the average clustering coefficient and the average size of the network also has a power-law relationship, moreover, the model parameters has no effect on power-law exponent. The spread of information on the network represents obvious fluctuation scaling, reflecting the characteristics that information transmission fluctuates over time.展开更多
It is a debated topic if there are any observable precursor anomalies prior to the earthquake(EQ hereafter)and if the stronger EQ can be successfully predicted.During last few decades quite a lot of observable electro...It is a debated topic if there are any observable precursor anomalies prior to the earthquake(EQ hereafter)and if the stronger EQ can be successfully predicted.During last few decades quite a lot of observable electromagnetic(EM)precursors were published by using techniques equipped in either satellites or on ground-based stations.But there are only a few cases that the shortterm precursor anomalies of EM field before earthquakes were observed by using alternate EM fields on ground.This paper will present a new EM observation network built in recent years and show a new finding of EM field with the variation of a one-year cycle observed using the network.As an example,the short-term precursor anomalies of apparent resistivity before the Yangbi EQ(Ms 5.1)occurred on March 27,2017 in Yunnan Province will be studied.The observed anomalous phenomena indicate that the anomaly before the EQ can be captured only if reasonable effective methods including sophisticated analytical techniques are used,and it is believed that continuously observed data on the fixed observation network for a long time is an effective means for studying anomalies that appeared before earthquakes.This network can also play an important role in studying the EM environment from space.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.62403486)。
文摘The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,this study proposes an intelligent decision-making framework based on a deep long short-term memory Q-network.This framework transforms the real-time sequencing for bolter recovery problem into a partially observable Markov decision process.It employs a stacked long shortterm memory network to accurately capture the long-range temporal dependencies of bolter event chains and fuel consumption.Furthermore,it integrates a prioritized experience replay training mechanism to construct a safe and adaptive scheduling system capable of millisecond-level real-time decision-making.Experimental demonstrates that,within large-scale mass recovery scenarios,the framework achieves zero safety violations in static environments and maintains a fuel safety violation rate below 10%in dynamic scenarios,with single-step decision times at the millisecond level.The model exhibits strong generalization capability,effectively responding to unforeseen emergent situations—such as multiple bolters and fuel emergencies—without requiring retraining.This provides robust support for efficient carrier-based aircraft recovery operations.
文摘Space-division multiplexing(SDM)utilizing uncoupled multi-core fibers(MCF)is considered a promising candidate for nextgeneration high-speed optical transmission systems due to its huge capacity and low inter-core crosstalk.In this paper,we demonstrate a realtime high-speed SDM transmission system over a field-deployed 7-core MCF cable using commercial 400 Gbit/s backbone optical transport network(OTN)transceivers and a network management system.The transceivers employ a high noise-tolerant quadrature phase shift keying(QPSK)modulation format with a 130 Gbaud rate,enabled by optoelectronic multi-chip module(OE-MCM)packaging.The network management system can effectively manage and monitor the performance of the 7-core SDM OTN system and promptly report failure events through alarms.Our field trial demonstrates the compatibility of uncoupled MCF with high-speed OTN transmission equipment and network management systems,supporting its future deployment in next-generation high-speed terrestrial cable transmission networks.
基金supported by the National Natural Science Foundation of China(No.62101587)the National Funded Postdoctoral Researcher Program of China(No.GZC20233578)。
文摘Micro-nano Earth Observation Satellite(MEOS)constellation has the advantages of low construction cost,short revisit cycle,and high functional density,which is considered a promising solution for serving rapidly growing observation demands.The observation Scheduling Problem in the MEOS constellation(MEOSSP)is a challenging issue due to the large number of satellites and tasks,as well as complex observation constraints.To address the large-scale and complicated MEOSSP,we develop a Two-Stage Scheduling Algorithm based on the Pointer Network with Attention mechanism(TSSA-PNA).In TSSA-PNA,the MEOS observation scheduling is decomposed into a task allocation stage and a single-MEOS scheduling stage.In the task allocation stage,an adaptive task allocation algorithm with four problem-specific allocation operators is proposed to reallocate the unscheduled tasks to new MEOSs.Regarding the single-MEOS scheduling stage,we design a pointer network based on the encoder-decoder architecture to learn the optimal singleMEOS scheduling solution and introduce the attention mechanism into the encoder to improve the learning efficiency.The Pointer Network with Attention mechanism(PNA)can generate the single-MEOS scheduling solution quickly in an end-to-end manner.These two decomposed stages are performed iteratively to search for the solution with high profit.A greedy local search algorithm is developed to improve the profits further.The performance of the PNA and TSSA-PNA on singleMEOS and multi-MEOS scheduling problems are evaluated in the experiments.The experimental results demonstrate that PNA can obtain the approximate solution for the single-MEOS scheduling problem in a short time.Besides,the TSSA-PNA can achieve higher observation profits than the existing scheduling algorithms within the acceptable computational time for the large-scale MEOS scheduling problem.
基金supported by the National Natural Science Foundation of China[grant number 42175132]the National Key R&D Program[grant number 2020YFA0607802]the CAS Information Technology Program[grant number CAS-WX2021SF-0107-02]。
文摘Solar energy is a pivotal clean energy source in the transition to carbon neutrality from fossil fuels.However,the intermittent and stochastic characteristics of solar radiation pose challenges for accurate simulation and prediction.Accurately simulating and predicting solar radiation and its variability are crucial for optimizing solar energy utilization.This study conducted simulation experiments using the WRF-Solar model from 25 June to 25 July 2022,to evaluate the accuracy and performance of the simulated solar radiation across China.The simulations covered the whole country with a grid spacing of 27 km and were compared with ground observation network data from the Chinese Ecosystem Research Network.The results indicated that WRF-Solar can accurately capture the spatiotemporal patterns of global horizontal irradiance over China,but there is still an overestimation of solar radiation,and the model underestimates the total cloud cover.The root-mean-square error ranged from 92.83 to 188.13 W m^(-2) and the mean bias(MB)ranged from 21.05 to 56.22 W m^(-2).The simulation showed the smallest MB at Lhasa on the Qinghai–Tibet Plateau,while the largest MB was observed in Southeast China.To enhance the accuracy of solar radiation simulation,the authors compared the Fast All-sky Radiation Model for Solar with the Rapid Radiative Transfer Model for General Circulation Models and found that the former provides better simulation.
基金supported by National Natural Science Foundation of China(Grant No.51105001)State Key Laboratory of Automotive Safety and Energy,Tsinghua University,China(Grant No.KF14022)
文摘The current research of real-time observation for vehicle roll steer angle and compliance steer angle（both of them comprehensively referred as the additional steer angle in this paper） mainly employs the linear vehicle dynamic model, in which only the lateral acceleration of vehicle body is considered. The observation accuracy resorting to this method cannot meet the requirements of vehicle real-time stability control, especially under extreme driving conditions. The paper explores the solution resorting to experimental method. Firstly, a multi-body dynamic model of a passenger car is built based on the ADAMS/Car software, whose dynamic accuracy is verified by the same vehicle＇s roadway test data of steady static circular test. Based on this simulation platform, several influencing factors of additional steer angle under different driving conditions are quantitatively analyzed. Then ε-SVR algorithm is employed to build the additional steer angle prediction model, whose input vectors mainly include the sensor information of standard electronic stability control system（ESC）. The method of typical slalom tests and FMVSS 126 tests are adopted to make simulation, train model and test model＇s generalization performance. The test result shows that the influence of lateral acceleration on additional steer angle is maximal （the magnitude up to 1°）, followed by the longitudinal acceleration-deceleration and the road wave amplitude （the magnitude up to 0.3°）. Moreover, both the prediction accuracy and the calculation real-time of the model can meet the control requirements of ESC This research expands the accurate observation methods of the additional steer angle under extreme driving conditions.
文摘Due to the excellent comprehensive mechanical properties and toughness of bainite steels,bainite is regarded as a most desirable microstructure for the new generation of high-strength weathering steels.The formation of bainite was observed in real time in a high-strength weathering steel,and the results showed that bainite laths show impingement during phase transformation.The preferred regions of nucleation sites were identified,and the growth rate of bainite was measured.The growth mechanism of bainite was demonstrated to exhibit growth rate contributions from both the diffusion mechanism and the shear mechanism.Subsequently,the heterogeneous phases that form preferred sites for bainite nucleation were quantitatively identified by scanning electron microscopy(SEM),energy-dispersive X-ray spectrometry(EDS),and calculation of phase diagram(CALPHAD).The austenite grain sizes in crease with increasing austenite temperature,which leads to longer bainite laths.The influence of a small lattice disregistry between the heterogeneous phases and bainite on the bainite nucleation was studied.The disregistries between the favorable heterogeneous phases of VN,VC,TiN,or TiC and the ot-Fe in bainite are 2.9,3.1,3.9,and 4.6%,respectively.Therefore,VN,VC,TiN,and TiC can act as highly effective nuclei for bainite during the bainite transformation.
基金The National Natural Science Foundation of China(No.51106025,51106027,51036002)Specialized Research Fund for the Doctoral Program of Higher Education(No.20130092110061)the Youth Foundation of Nanjing Institute of Technology(No.QKJA201303)
文摘A fuzzy observations-based radial basis function neural network （FORBFNN） is presented for modeling nonlinear systems in which the observations of response are imprecise but can be represented as fuzzy membership functions. In the FORBFNN model, the weight coefficients of nodes in the hidden layer are identified by using the fuzzy expectation-maximization （ EM ） algorithm, whereas the optimal number of these nodes as well as the centers and widths of radial basis functions are automatically constructed by using a data-driven method. Namely, the method starts with an initial node, and then a new node is added in a hidden layer according to some rules. This procedure is not terminated until the model meets the preset requirements. The method considers both the accuracy and complexity of the model. Numerical simulation results show that the modeling method is effective, and the established model has high prediction accuracy.
基金supported by US National Institutes of Health grant R01 AI44902 (to C Z )a Pre-doctoral Fellowship from the American Heart Association (to W C )
文摘Introduction Integrins are a large family of adhesion molecules broadly expressed on the surface of a wide variety of cells as heterodimers. Binding of integrins to ligands provides not only mechanical anchorage for the cell to another cell or
基金supported by the National Natural Science Foundation of China (No. 61772055)Equipment Preliminary R&D Project of China (No. 41402020102)
文摘With the flourishing development of Unmanned Aerial Vehicles(UAVs), the mission tasks of UAVs have become more and more complex. Consequently, a Real-Time Operating System(RTOS) that provides operating environments for various mission services on these UAVs has become crucial, which leads to the necessity of having a deep understanding of an RTOS. In this paper, an empirical study is conducted on FreeRTOS, a commonly used RTOS for UAVs, from a complex network perspective. A total of 85 releases of FreeRTOS, from V2.4.2 to V10.0.0, are modeled as directed networks, in which the nodes represent functions and the edges denote function calls. It is found that the size of the FreeRTOS network has grown almost linearly with the evolution of the versions, while its main core has evolved steadily. In addition, a k-core analysis-based metric is proposed to identify major functionality changes of FreeRTOS during its evolution.The result shows that the identified versions are consistent with the version change logs. Finally,it is found that the clustering coefficient of the Linux OS scheduler is larger than that of the FreeRTOS scheduler. In conclusion, the empirical results provide useful guidance for developers and users of UAV RTOSs.
文摘The application and development of a wide-area measurement system(WAMS)has enabled many applications and led to several requirements based on dynamic measurement data.Such data are transmitted as big data information flow.To ensure effective transmission of wide-frequency electrical information by the communication protocol of a WAMS,this study performs real-time traffic monitoring and analysis of the data network of a power information system,and establishes corresponding network optimization strategies to solve existing transmission problems.This study utilizes the traffic analysis results obtained using the current real-time dynamic monitoring system to design an optimization strategy,covering the optimization in three progressive levels:the underlying communication protocol,source data,and transmission process.Optimization of the system structure and scheduling optimization of data information are validated to be feasible and practical via tests.
基金supported by Physical Chemical Materials Analytical&Testing Center of Shandong University at Weihai,Natural Science Foundation of Shandong Province(No.ZR2022QD057)Open Project Fund for Hubei Key Laboratory of Oral and Maxillofacial Development and Regeneration(No.2021kqhm003)+1 种基金State Key Laboratory of Advanced Technology for Materials Synthesis and Processing(Wuhan University of Technology)the Science Fund of Shandong Laboratory of Advanced Materials and Green Manufacturing(Yantai,No.AMGM2021F02)。
文摘To achieve smart and personalized medicine, the development of hydrogel dressings with sensing properties and biotherapeutic properties that can act as a sensor to monitor of human health in real-time while speeding up wound healing face great challenge. In the present study, a biocompatible dual-network composite hydrogel(DNCGel) sensor was obtained via a simple process. The dual network hydrogel is constructed by the interpenetration of a flexible network formed of poly(vinyl alcohol)(PVA) physical cross-linked by repeated freeze-thawing and a rigid network of iron-chelated xanthan gum(XG) impregnated with Fe^(3+) interpenetration. The pure PVA/XG hydrogels were chelated with ferric ions by immersion to improve the gel strength(compressive modulus and tensile modulus can reach up to 0.62 MPa and0.079 MPa, respectively), conductivity(conductivity values ranging from 9 × 10^(-4) S/cm to 1 × 10^(-3)S/cm)and bacterial inhibition properties(up to 98.56%). Subsequently, the effects of the ratio of PVA and XG and the immersion time of Fe^(3+) on the hydrogels were investigated, and DNGel3 was given the most priority on a comprehensive consideration. It was demonstrated that the DNCGel exhibit good biocompatibility in vitro, effectively facilitate wound healing in vivo(up to 97.8% healing rate) under electrical stimulation, and monitors human movement in real time. This work provides a novel avenue to explore multifunctional intelligent hydrogels that hold great promise in biomedical fields such as smart wound dressings and flexible wearable sensors.
文摘The effects of real-time traffic information system(RTTIS)on traffic performance under parallel,grid and ring networks were investigated.The simulation results show that the effects of the proportion of RTTIS usage depend on the road network structures.For traffic on a parallel network,the performance of groups with and without RTTIS level is improved when the proportion of vehicles using RTTIS is greater than 0 and less than 30%,and a proportion of RTTIS usage higher than 90%would actually deteriorate the performance.For both grid and ring networks,a higher proportion of RTTIS usage always improves the performance of groups with and without RTTIS.For all three network structures,vehicles without RTTIS benefit from some proportion of RTTIS usage in a system.
基金the National Natural Science Foundation of China(Grant Nos.61673027 and 62106047)the Beijing Social Science Foundation(Grant No.21GLC042)the Humanity and Social Science Youth foundation of Ministry of Education,China(Grant No.20YJCZH228)。
文摘This paper examines the effect of the observation time on source identification of a discrete-time susceptible-infectedrecovered diffusion process in a network with snapshot of partial nodes.We formulate the source identification problem as a maximum likelihood(ML)estimator and develop a statistical inference method based on Monte Carlo simulation(MCS)to estimate the source location and the initial time of diffusion.Experimental results in synthetic networks and real-world networks demonstrate evident impact of the observation time as well as the fraction of the observers on the concerned problem.
基金partially funded by the Crustal Movement Observation Network of China(CMONOC)iGMAS,the National Basic Research Program of China(2012CB825604)+4 种基金China Natural Science Funds(41304034,41231064,41204031)China Scholarship Council,and CAS/SAFEA International Partnership Program for Creative Research Teams(KZZD-EW-TZ-05)Beijing Natural Science Funds(4144094)863programs(2012AA121803)the State Key Laboratory of Geodesy and Earth's Dynamics(SKLGED2014-3-1-E,SKLGED2014-3-7-E)
文摘The Global Navigation Satellite System （GNSS） is becoming important for monitoring the variations in the earth＇s ionosphere based on the total electron content （TEC） and iono- spheric electron density （IED）. The Crustal Movement Observation Network of China （CMONOC）, which includes GNSS stations across China's Mainland, enables the continuous monitoring of the ionosphere over China as accurately as possible. A series of approaches for GNSS-based ionospheric remote sensing and software has been proposed and devel- oped by the Institute of Geodesy and Geophysics （IGG） in Wuhan. Related achievements include the retrieval of ionospheric observables from raw GNSS data, differential code biases estimations in satellites and receivers, models of local and regional ionospheric TEC, and algorithms of ionospheric tomography. Based on these achievements, a software for processing GNSS data to determine the variations in ionospheric TEC and IED over China has been designed and developed by IGG. This software has also been installed at the CMONOC data centers belonging to the China Earthquake Administration and China Meteorological Administration. This paper briefly introduces the related research achievements and indicates potential directions of future work.
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supported in part by the National Key RD Program of China (2021YFF0602104-2,2020YFB1804604)in part by the 2020 Industrial Internet Innovation and Development Project from Ministry of Industry and Information Technology of Chinain part by the Fundamental Research Fund for the Central Universities (30918012204,30920041112).
文摘The application of unmanned driving in the Internet of Things is one of the concrete manifestations of the application of artificial intelligence technology.Image semantic segmentation can help the unmanned driving system by achieving road accessibility analysis.Semantic segmentation is also a challenging technology for image understanding and scene parsing.We focused on the challenging task of real-time semantic segmentation in this paper.In this paper,we proposed a novel fast architecture for real-time semantic segmentation named DuFNet.Starting from the existing work of Bilateral Segmentation Network(BiSeNet),DuFNet proposes a novel Semantic Information Flow(SIF)structure for context information and a novel Fringe Information Flow(FIF)structure for spatial information.We also proposed two kinds of SIF with cascaded and paralleled structures,respectively.The SIF encodes the input stage by stage in the ResNet18 backbone and provides context information for the feature fusionmodule.Features from previous stages usually contain rich low-level details but high-level semantics for later stages.Themultiple convolutions embed in Parallel SIF aggregate the corresponding features among different stages and generate a powerful global context representation with less computational cost.The FIF consists of a pooling layer and an upsampling operator followed by projection convolution layer.The concise component provides more spatial details for the network.Compared with BiSeNet,our work achieved faster speed and comparable performance with 72.34%mIoU accuracy and 78 FPS on Cityscapes Dataset based on the ResNet18 backbone.
基金supported by the National Nature Science Foundation of China(NSFC 60622110,61471220,91538107,91638205)National Basic Research Project of China(973,2013CB329006),GY22016058
文摘With the popularity of smart handheld devices, mobile streaming video has multiplied the global network traffic in recent years. A huge concern of users' quality of experience(Qo E) has made rate adaptation methods very attractive. In this paper, we propose a two-phase rate adaptation strategy to improve users' real-time video Qo E. First, to measure and assess video Qo E, we provide a continuous Qo E prediction engine modeled by RNN recurrent neural network. Different from traditional Qo E models which consider the Qo E-aware factors separately or incompletely, our RNN-Qo E model accounts for three descriptive factors(video quality, rebuffering, and rate change) and reflects the impact of cognitive memory and recency. Besides, the video playing is separated into the initial startup phase and the steady playback phase, and we takes different optimization goals for each phase: the former aims at shortening the startup delay while the latter ameliorates the video quality and the rebufferings. Simulation results have shown that RNN-Qo E can follow the subjective Qo E quite well, and the proposed strategy can effectively reduce the occurrence of rebufferings caused by the mismatch between the requested video rates and the fluctuated throughput and attains standout performance on real-time Qo E compared with classical rate adaption methods.
基金supported by the Natural Science Foundation of China under Grants U19B2025,62121001,and 62001347in part by Key Research and Development Program of Shaanxi(ProgramNo.2022ZDLGY05-02)in part by Young Talent Support Program of Xi’an Association for Science and Technology(No.095920221337).
文摘The unreasonable observation arrangements in the satellite operation control center(SOCC)may result in the observation data cannot be downloaded as scheduled.Meanwhile,if the operation instructions released by the satellite telemetry tracking center(STTC)for the on-board payloads are not injected on the specific satellites in time,the corresponding satellites cannot perform the observation operations as planned.Therefore,there is an urgent need to design an integrated instruction release,and observation task planning(I-IRO-TP)scheme by efficiently collaborating the SOCC and STTC.Motivated by this fact,we design an interaction mechanism between the SOCC and the STTC,where we first formulate the I-IRO-TP problem as a constraint satisfaction problem aiming at maximizing the number of completed tasks.Furthermore,we propose an interactive imaging task planning algorithm based on the analysis of resource distribution in the STTC during the previous planning periods to preferentially select the observation arcs that not only satisfy the requirements in the observation resource allocation phase but also facilitate the arrangement of measurement and control instruction release.We conduct extensive simulations to demonstrate the effectiveness of the proposed algorithm in terms of the number of completed tasks.
文摘In this paper, the model of the online real-time information transmission network, such as wechat, micro-blog, and QQ network, is proposed and built, based on the connection properties between users of the online real-time information transmission network, and combined with the local world evolving characteristics in complex network, then the statistical topological properties of the network is obtained by numerical simulation. Furthermore, we simulated the process of information transmission on the network, according to the actual characteristics of the online real-time information transmission. Statistics show that the degree distribution presents the characteristics of scale free network, presenting power law distribution, while the average path length, the average clustering coefficient and the average size of the network also has a power-law relationship, moreover, the model parameters has no effect on power-law exponent. The spread of information on the network represents obvious fluctuation scaling, reflecting the characteristics that information transmission fluctuates over time.
基金National Development and Reform Committee of China(No.15212Z0000001)National Science Foundation of China(No.41374077)。
文摘It is a debated topic if there are any observable precursor anomalies prior to the earthquake(EQ hereafter)and if the stronger EQ can be successfully predicted.During last few decades quite a lot of observable electromagnetic(EM)precursors were published by using techniques equipped in either satellites or on ground-based stations.But there are only a few cases that the shortterm precursor anomalies of EM field before earthquakes were observed by using alternate EM fields on ground.This paper will present a new EM observation network built in recent years and show a new finding of EM field with the variation of a one-year cycle observed using the network.As an example,the short-term precursor anomalies of apparent resistivity before the Yangbi EQ(Ms 5.1)occurred on March 27,2017 in Yunnan Province will be studied.The observed anomalous phenomena indicate that the anomaly before the EQ can be captured only if reasonable effective methods including sophisticated analytical techniques are used,and it is believed that continuously observed data on the fixed observation network for a long time is an effective means for studying anomalies that appeared before earthquakes.This network can also play an important role in studying the EM environment from space.
