As the popularization of dual ring fieldbus, the optimized dual ring synchronization methods are still in short. The current synchronization methods are generally established in traditional industrial fieldbus, in whi...As the popularization of dual ring fieldbus, the optimized dual ring synchronization methods are still in short. The current synchronization methods are generally established in traditional industrial fieldbus, in which transmission is commonly considered in single track, the two-way transmitting cannot take full effect, and would result in unwanted idle load on equipment lines. In stamp-transferring part, the synchronizing algorithm is not properly processed to diminish the latency, so the real-time performance of entire system cannot be ensured. To support the synchronization control of stations in the CNC system, a real-time time synchronization method for dual ring fieldbus in the CNC system is designed in this paper. In this method a synchronizing message transmission scheme based on dual ring architecture and the synchronization algorithm between master and secondary stations are integrated. In the scheme, the clock models of both master and secondary stations are optimized with corresponding modules and the stamp data transmission based on the dual ring fieldbus is devised exclusively, so the transmitting efficiency improves with less idle work. In the algorithm, all the secondary stations can accomplish the consistent state with master station by updating clock discrepancy information in one communication cycle, and it takes the advantage of two-way transmitting and makes the best use of dual ring structure, so the real-time performance of the system can be promoted while retaining the precision of synchronization. To evaluate the performance, the costs of the method and errors during synchronizing are noted and analyzed based on the actual running environment in the industrial fieldbus. The results show that it reduces communication cost and ensures the smoothness of the system with low lag effects under heavy load. The proposed time synchronization method optimizes the architecture of sync message transmission in dual ring fieldbus, and improves the efficiency of time synchronization in the stations of CNC system.展开更多
Optical non-reciprocity is a fundamental phenomenon in photonics.It is crucial for developing devices that rely on directional signal control,such as optical isolators and circulators.However,most research in this fie...Optical non-reciprocity is a fundamental phenomenon in photonics.It is crucial for developing devices that rely on directional signal control,such as optical isolators and circulators.However,most research in this field has focused on systems in equilibrium or steady states.In this work,we demonstrate a room-temperature Rydberg atomic platform where the unidirectional propagation of light acts as a switch to mediate time-crystalline-like collective oscillations through atomic synchronization.展开更多
Clock synchronization has important applications in multi-agent collaboration(such as drone light shows,intelligent transportation systems,and game AI),group decision-making,and emergency rescue operations.Synchroniza...Clock synchronization has important applications in multi-agent collaboration(such as drone light shows,intelligent transportation systems,and game AI),group decision-making,and emergency rescue operations.Synchronization method based on pulse-coupled oscillators(PCOs)provides an effective solution for clock synchronization in wireless networks.However,the existing clock synchronization algorithms in multi-agent ad hoc networks are difficult to meet the requirements of high precision and high stability of synchronization clock in group cooperation.Hence,this paper constructs a network model,named DAUNet(unsupervised neural network based on dual attention),to enhance clock synchronization accuracy in multi-agent wireless ad hoc networks.Specifically,we design an unsupervised distributed neural network framework as the backbone,building upon classical PCO-based synchronization methods.This framework resolves issues such as prolonged time synchronization message exchange between nodes,difficulties in centralized node coordination,and challenges in distributed training.Furthermore,we introduce a dual-attention mechanism as the core module of DAUNet.By integrating a Multi-Head Attention module and a Gated Attention module,the model significantly improves information extraction capabilities while reducing computational complexity,effectively mitigating synchronization inaccuracies and instability in multi-agent ad hoc networks.To evaluate the effectiveness of the proposed model,comparative experiments and ablation studies were conducted against classical methods and existing deep learning models.The research results show that,compared with the deep learning networks based on DASA and LSTM,DAUNet can reduce the mean normalized phase difference(NPD)by 1 to 2 orders of magnitude.Compared with the attention models based on additive attention and self-attention mechanisms,the performance of DAUNet has improved by more than ten times.This study demonstrates DAUNet’s potential in advancing multi-agent ad hoc networking technologies.展开更多
In the real-time scheduling theory,schedulability and synchronization analyses are used to evaluate scheduling algorithms and real-time locking protocols,respectively,and the empirical synthesis experiment is one of t...In the real-time scheduling theory,schedulability and synchronization analyses are used to evaluate scheduling algorithms and real-time locking protocols,respectively,and the empirical synthesis experiment is one of the major methods to compare the performance of such analyses.However,since many sophisticated techniques have been adopted to improve the analytical accuracy,the implementation of such analyses and experiments is often time-consuming.This paper proposes a schedulability experiment toolkit for multiprocessor real-time systems(SET-MRTS),which provides a framework with infrastructures to implement the schedulability and synchronization analyses and the deployment of empirical synthesis experiments.Besides,with well-designed peripheral components for the input and output,experiments can be conducted easily and flexibly on SET-MRTS.This demonstration further proves the effectiveness of SET-MRTS in both functionality and availability.展开更多
This article briefly reviews the topic of complex network synchronization,with its graph-theoretic criterion,showing that the homogeneous and symmetrical network structures are essential for optimal synchronization.Fu...This article briefly reviews the topic of complex network synchronization,with its graph-theoretic criterion,showing that the homogeneous and symmetrical network structures are essential for optimal synchronization.Furthermore,it briefly reviews the notion of higher-order network topologies and shows their promising potential in application to evaluating the optimality of network synchronizability.展开更多
[ Objective] This study aimed to establish a simultaneous detection method of shrimp viruses by real-time fluorescence quantitative RT-PCR, to improve the efficiency of inspection and quarantine. [ Method] A novel rea...[ Objective] This study aimed to establish a simultaneous detection method of shrimp viruses by real-time fluorescence quantitative RT-PCR, to improve the efficiency of inspection and quarantine. [ Method] A novel real-time fluorescence quantitative RT-PCR assay was established and optimized for simultaneously detecting DNA/RNA of four shrimp viruses （WSSV, IHHNV, TSV and YHV ）. [ Result] The optimized real-time fluorescence quantitative RT-PCR system gener- ated typical amplification curves with high amplification efficiencies （E = 1.06, 1.07, 0.92 and 0.92, respectively）, good hnear relationship （ r = 1 ）, uniform repeatability （ standard deviation = 0.05 - 0.46 ; variation coefficient = 0.26% - 1.62% ） and high sensitivity, exhibiting no significant differences compared with re- al-time fluorescence quantitative PCR （average error of Ct value = 0.04 -0.40; T = 0.53 -2.50; P 〉 0.05 ）. The total detection time was about 1 h. [ Conclusion] The optimized real-time fluorescence quantitative RT-PCR system can be used for rapid detection of WSSV, IHHNV, TSV and YHV.展开更多
This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-tri...This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-triggered mechanism(MBAETM)is designed based on sequential growth rates,focusing on event-triggered conditions and thresholds.Subsequently,from the perspective of defenders,non-periodic DoS attacks are re-characterized,and a model of irregular DoS attacks with cyclic fluctuations within time series is further introduced to enhance the system's defense capabilities more effectively.Additionally,considering the unified demands of network security and communication efficiency,a resilient memory-based adaptive event-triggered mechanism(RMBAETM)is proposed.A unified Lyapunov-Krasovskii functional is then constructed,incorporating a loop functional to thoroughly consider information at trigger moments.The master-slave system achieves synchronization through the application of linear matrix inequality techniques.Finally,the proposed methods'effectiveness and superiority are confirmed through four numerical simulation examples.展开更多
This paper describes a real-time beam tuning method with an improved asynchronous advantage actor–critic(A3C)algorithm for accelerator systems.The operating parameters of devices are usually inconsistent with the pre...This paper describes a real-time beam tuning method with an improved asynchronous advantage actor–critic(A3C)algorithm for accelerator systems.The operating parameters of devices are usually inconsistent with the predictions of physical designs because of errors in mechanical matching and installation.Therefore,parameter optimization methods such as pointwise scanning,evolutionary algorithms(EAs),and robust conjugate direction search are widely used in beam tuning to compensate for this inconsistency.However,it is difficult for them to deal with a large number of discrete local optima.The A3C algorithm,which has been applied in the automated control field,provides an approach for improving multi-dimensional optimization.The A3C algorithm is introduced and improved for the real-time beam tuning code for accelerators.Experiments in which optimization is achieved by using pointwise scanning,the genetic algorithm(one kind of EAs),and the A3C-algorithm are conducted and compared to optimize the currents of four steering magnets and two solenoids in the low-energy beam transport section(LEBT)of the Xi’an Proton Application Facility.Optimal currents are determined when the highest transmission of a radio frequency quadrupole(RFQ)accelerator downstream of the LEBT is achieved.The optimal work points of the tuned accelerator were obtained with currents of 0 A,0 A,0 A,and 0.1 A,for the four steering magnets,and 107 A and 96 A for the two solenoids.Furthermore,the highest transmission of the RFQ was 91.2%.Meanwhile,the lower time required for the optimization with the A3C algorithm was successfully verified.Optimization with the A3C algorithm consumed 42%and 78%less time than pointwise scanning with random initialization and pre-trained initialization of weights,respectively.展开更多
The rise of time-sensitive applications with broad geographical scope drives the development of time-sensitive networking(TSN)from intra-domain to inter-domain to ensure overall end-to-end connectivity requirements in...The rise of time-sensitive applications with broad geographical scope drives the development of time-sensitive networking(TSN)from intra-domain to inter-domain to ensure overall end-to-end connectivity requirements in heterogeneous deployments.When multiple TSN networks interconnect over non-TSN networks,all devices in the network need to be syn-chronized by sharing a uniform time reference.How-ever,most non-TSN networks are best-effort.Path delay asymmetry and random noise accumulation can introduce unpredictable time errors during end-to-end time synchronization.These factors can degrade syn-chronization performance.Therefore,cross-domain time synchronization becomes a challenging issue for multiple TSN networks interconnected by non-TSN networks.This paper presents a cross-domain time synchronization scheme that follows the software-defined TSN(SD-TSN)paradigm.It utilizes a com-bined control plane constructed by a coordinate con-troller and a domain controller for centralized control and management of cross-domain time synchroniza-tion.The general operation flow of the cross-domain time synchronization process is designed.The mecha-nism of cross-domain time synchronization is revealed by introducing a synchronization model and an error compensation method.A TSN cross-domain proto-type testbed is constructed for verification.Results show that the scheme can achieve end-to-end high-precision time synchronization with accuracy and sta-bility.展开更多
Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and ev...Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and even a chaotic or hyperchaotic system,the response network is complex system coupled by N nodes,and every node is showed by the approximately linear part of the drive system.Only controlling any one node of the response network by designed controller can achieve the projective synchronization.Some numerical examples were employed to verify the effectiveness and correctness of the designed controller.展开更多
Aiming at issues on multimedia communication in synchronous real-time teleteaching (SRT) systems over IP network, a 4-tuple structural mode of multimedia communication is proposed in the paper, and an SRT-oriented dis...Aiming at issues on multimedia communication in synchronous real-time teleteaching (SRT) systems over IP network, a 4-tuple structural mode of multimedia communication is proposed in the paper, and an SRT-oriented distributed MCU model is built according to the mode. Moreover, the mechanism of multicast communication across subnets is discussed. The distributed MCU model has been applied successfully in our interactive synchronous real-time telesteaching system RealClass and has shown good extendibility in operation.展开更多
The Internet of Things(IoT)and mobile technology have significantly transformed healthcare by enabling real-time monitoring and diagnosis of patients.Recognizing Medical-Related Human Activities(MRHA)is pivotal for he...The Internet of Things(IoT)and mobile technology have significantly transformed healthcare by enabling real-time monitoring and diagnosis of patients.Recognizing Medical-Related Human Activities(MRHA)is pivotal for healthcare systems,particularly for identifying actions critical to patient well-being.However,challenges such as high computational demands,low accuracy,and limited adaptability persist in Human Motion Recognition(HMR).While some studies have integrated HMR with IoT for real-time healthcare applications,limited research has focused on recognizing MRHA as essential for effective patient monitoring.This study proposes a novel HMR method tailored for MRHA detection,leveraging multi-stage deep learning techniques integrated with IoT.The approach employs EfficientNet to extract optimized spatial features from skeleton frame sequences using seven Mobile Inverted Bottleneck Convolutions(MBConv)blocks,followed by Convolutional Long Short Term Memory(ConvLSTM)to capture spatio-temporal patterns.A classification module with global average pooling,a fully connected layer,and a dropout layer generates the final predictions.The model is evaluated on the NTU RGB+D 120 and HMDB51 datasets,focusing on MRHA such as sneezing,falling,walking,sitting,etc.It achieves 94.85%accuracy for cross-subject evaluations and 96.45%for cross-view evaluations on NTU RGB+D 120,along with 89.22%accuracy on HMDB51.Additionally,the system integrates IoT capabilities using a Raspberry Pi and GSM module,delivering real-time alerts via Twilios SMS service to caregivers and patients.This scalable and efficient solution bridges the gap between HMR and IoT,advancing patient monitoring,improving healthcare outcomes,and reducing costs.展开更多
Along with process control,perception represents the main function performed by the Edge Layer of an Internet of Things(IoT)network.Many of these networks implement various applications where the response time does no...Along with process control,perception represents the main function performed by the Edge Layer of an Internet of Things(IoT)network.Many of these networks implement various applications where the response time does not represent an important parameter.However,in critical applications,this parameter represents a crucial aspect.One important sensing device used in IoT designs is the accelerometer.In most applications,the response time of the embedded driver software handling this device is generally not analysed and not taken into account.In this paper,we present the design and implementation of a predictable real-time driver stack for a popular accelerometer and gyroscope device family.We provide clear justifications for why this response time is extremely important for critical applications in the acquisition process of such data.We present extensive measurements and experimental results that demonstrate the predictability of our solution,making it suitable for critical real-time systems.展开更多
This paper propose a comprehensive data-driven prediction framework based on machine learning methods to investigate the lag synchronization phenomenon in coupled chaotic systems,particularly in cases where accurate m...This paper propose a comprehensive data-driven prediction framework based on machine learning methods to investigate the lag synchronization phenomenon in coupled chaotic systems,particularly in cases where accurate mathematical models are challenging to establish or where system equations remain unknown.The Long Short-Term Memory(LSTM)neural network is trained using time series acquired from the desynchronization system states,subsequently predicting the lag synchronization transition.In the experiments,we focus on the Lorenz system with time-varying delayed coupling,studying the effects of coupling coefficients and time delays on lag synchronization,respectively.The results indicate that with appropriate training,the machine learning model can adeptly predict the lag synchronization occurrence and transition.This study not only enhances our comprehension of complex network synchronization behaviors but also underscores the potential and practical applications of machine learning in exploring nonlinear dynamic systems.展开更多
Background Two-dimensional speckle tracking imaging （2D-STI） and real-time three-dimensional echocardiography （RT-3DE） have more advantages in evaluating left ventricular （LV） systolic dyssynchrony than traditio...Background Two-dimensional speckle tracking imaging （2D-STI） and real-time three-dimensional echocardiography （RT-3DE） have more advantages in evaluating left ventricular （LV） systolic dyssynchrony than traditional echocardiographic techniques. The study aimed to evaluate LV dyssynchrony parameters by both 2D-STI and RT-3DE, and the correlation between these two techniques. Methods A total of 43 chronic heart failure （CHF） patients and 27 healthy volunteers were enrolled. There were 23 dyssynchrony parameters selected to evaluate left ventricular systolic synchronization, involving 15 from 2D-STI and 8 from RT-3DE. Results Few of the dyssynchrony parametersshowednegative correlations with LV ejection fraction （LVEF） in the CHF group. The difference between time to peak-systolic radial strain of the anteroseptal and posterior segments at the level of papillary muscles [AS-P（RS）] from 2D-STI showed positive correlations with parts of the parameters from RT-3DE （P 〈 0.05）. Conclusions LV systolic dysfunction does not correlate with dyssynchrony. Moreover, there is a weak association between 2D-STI and RT-3DE in assessment of left ventricular dyssynchrony.展开更多
Real-time semantic segmentation tasks place stringent demands on network inference speed,often requiring a reduction in network depth to decrease computational load.However,shallow networks tend to exhibit degradation...Real-time semantic segmentation tasks place stringent demands on network inference speed,often requiring a reduction in network depth to decrease computational load.However,shallow networks tend to exhibit degradation in feature extraction completeness and inference accuracy.Therefore,balancing high performance with real-time requirements has become a critical issue in the study of real-time semantic segmentation.To address these challenges,this paper proposes a lightweight bilateral dual-residual network.By introducing a novel residual structure combined with feature extraction and fusion modules,the proposed network significantly enhances representational capacity while reducing computational costs.Specifically,an improved compound residual structure is designed to optimize the efficiency of information propagation and feature extraction.Furthermore,the proposed feature extraction and fusion module enables the network to better capture multi-scale information in images,improving the ability to detect both detailed and global semantic features.Experimental results on the publicly available Cityscapes dataset demonstrate that the proposed lightweight dual-branch network achieves outstanding performance while maintaining low computational complexity.In particular,the network achieved a mean Intersection over Union(mIoU)of 78.4%on the Cityscapes validation set,surpassing many existing semantic segmentation models.Additionally,in terms of inference speed,the network reached 74.5 frames per second when tested on an NVIDIA GeForce RTX 3090 GPU,significantly improving real-time performance.展开更多
Complex networks play a crucial role in the study of collective behavior,encompassing the analysis of dynamical properties and network topology.In real-world systems,higher-order interactions among multiple entities a...Complex networks play a crucial role in the study of collective behavior,encompassing the analysis of dynamical properties and network topology.In real-world systems,higher-order interactions among multiple entities are widespread and significantly influence collective dynamics.Here,we extend the synchronization alignment function framework to hypergraphs of arbitrary order by leveraging the multi-order Laplacian matrix to encode higher-order interactions.Our findings reveal that the upper bound of synchronous behavior is determined by the maximum eigenvalue of the multi-order Laplacian matrix.Furthermore,we decompose the contribution of each hyperedge to this eigenvalue and utilize it as a basis for designing an eigenvalue-based topology modification algorithm.This algorithm effectively enhances the upper bound of synchronous behavior without altering the total number of higher-order interactions.Our study provides new insights into dynamical optimization and topology tuning in hypergraphs,advancing the understanding of the interplay between higher-order interactions and collective dynamics.展开更多
Here,a novel real-time monitoring sensor that integrates the oxidation of peroxymonosulfate(PMS)and the in situ monitoring of the pollutant degradation process is proposed.Briefly,FeCo@carbon fiber(FeCo@CF)was utilize...Here,a novel real-time monitoring sensor that integrates the oxidation of peroxymonosulfate(PMS)and the in situ monitoring of the pollutant degradation process is proposed.Briefly,FeCo@carbon fiber(FeCo@CF)was utilized as the anode electrode,while graphite rods served as the cathode electrode in assembling the galvanic cell.The FeCo@CF electrode exhibited rapid reactivity with PMS,generating reactive oxygen species that efficiently degrade organic pollutants.The degradation experiments indicate that complete bisphenol A(BPA)degradation was achieved within 10 min under optimal conditions.The real-time electrochemical signal was measured in time during the catalytic reaction,and a linear relationship between BPA concentration and the real-time charge(Q)was confirmed by the equation ln(C0/C)=4.393Q(correlation coefficients,R^(2)=0.998).Furthermore,experiments conducted with aureomycin and tetracycline further validated the effectiveness of the monitoring sensor.First-principles investigation confirmed the superior adsorption energy and improved electron transfer in FeCo@CF.The integration of pollutant degradation with in situ monitoring of catalytic reactions offers promising prospects for expanding the scope of the monitoring of catalytic processes and making significant contributions to environmental purification.展开更多
The information exchange among satellites is crucial for the implementation of cluster satellite cooperative missions.However,achieving fast perception,rapid networking,and highprecision time synchronization among nod...The information exchange among satellites is crucial for the implementation of cluster satellite cooperative missions.However,achieving fast perception,rapid networking,and highprecision time synchronization among nodes without the support of the Global Navigation Satellite System(GNSS)and other prior information remains a formidable challenge to real-time wireless networks design.Therefore,a self-organizing network methodology based on multi-agent negotiation is proposed,which autonomously determines the master node through collaborative negotiation and competitive elections.On this basis,a real-time network protocol design is carried out and a high-precision time synchronization method with motion compensation is proposed.Simulation results demonstrate that the proposed method enables rapid networking with the capability of selfdiscovery,self-organization,and self-healing.For a cluster of 8 satellites,the networking time and the reorganization time are less than 4 s.The time synchronization accuracy exceeds 10-10s with motion compensation,demonstrating excellent real-time performance and stability.The research presented in this paper provides a valuable reference for the design and application of spacebased self-organizing networks for satellite cluster.展开更多
基金supported by National Projects for Science and Technology Development of China(Grant No.2011ZX04016-071)National Basic Research Program of China(973 Program,Grant No.2011CB302400-G,the mathematical mechanization method and its application in digital design and manufacturing)
文摘As the popularization of dual ring fieldbus, the optimized dual ring synchronization methods are still in short. The current synchronization methods are generally established in traditional industrial fieldbus, in which transmission is commonly considered in single track, the two-way transmitting cannot take full effect, and would result in unwanted idle load on equipment lines. In stamp-transferring part, the synchronizing algorithm is not properly processed to diminish the latency, so the real-time performance of entire system cannot be ensured. To support the synchronization control of stations in the CNC system, a real-time time synchronization method for dual ring fieldbus in the CNC system is designed in this paper. In this method a synchronizing message transmission scheme based on dual ring architecture and the synchronization algorithm between master and secondary stations are integrated. In the scheme, the clock models of both master and secondary stations are optimized with corresponding modules and the stamp data transmission based on the dual ring fieldbus is devised exclusively, so the transmitting efficiency improves with less idle work. In the algorithm, all the secondary stations can accomplish the consistent state with master station by updating clock discrepancy information in one communication cycle, and it takes the advantage of two-way transmitting and makes the best use of dual ring structure, so the real-time performance of the system can be promoted while retaining the precision of synchronization. To evaluate the performance, the costs of the method and errors during synchronizing are noted and analyzed based on the actual running environment in the industrial fieldbus. The results show that it reduces communication cost and ensures the smoothness of the system with low lag effects under heavy load. The proposed time synchronization method optimizes the architecture of sync message transmission in dual ring fieldbus, and improves the efficiency of time synchronization in the stations of CNC system.
基金supported by the National Natural Science Foundation of China (Grant No.12274131)the Innovation Program for Quantum Science and Technology (Grant No.2024ZD0300101)。
文摘Optical non-reciprocity is a fundamental phenomenon in photonics.It is crucial for developing devices that rely on directional signal control,such as optical isolators and circulators.However,most research in this field has focused on systems in equilibrium or steady states.In this work,we demonstrate a room-temperature Rydberg atomic platform where the unidirectional propagation of light acts as a switch to mediate time-crystalline-like collective oscillations through atomic synchronization.
文摘Clock synchronization has important applications in multi-agent collaboration(such as drone light shows,intelligent transportation systems,and game AI),group decision-making,and emergency rescue operations.Synchronization method based on pulse-coupled oscillators(PCOs)provides an effective solution for clock synchronization in wireless networks.However,the existing clock synchronization algorithms in multi-agent ad hoc networks are difficult to meet the requirements of high precision and high stability of synchronization clock in group cooperation.Hence,this paper constructs a network model,named DAUNet(unsupervised neural network based on dual attention),to enhance clock synchronization accuracy in multi-agent wireless ad hoc networks.Specifically,we design an unsupervised distributed neural network framework as the backbone,building upon classical PCO-based synchronization methods.This framework resolves issues such as prolonged time synchronization message exchange between nodes,difficulties in centralized node coordination,and challenges in distributed training.Furthermore,we introduce a dual-attention mechanism as the core module of DAUNet.By integrating a Multi-Head Attention module and a Gated Attention module,the model significantly improves information extraction capabilities while reducing computational complexity,effectively mitigating synchronization inaccuracies and instability in multi-agent ad hoc networks.To evaluate the effectiveness of the proposed model,comparative experiments and ablation studies were conducted against classical methods and existing deep learning models.The research results show that,compared with the deep learning networks based on DASA and LSTM,DAUNet can reduce the mean normalized phase difference(NPD)by 1 to 2 orders of magnitude.Compared with the attention models based on additive attention and self-attention mechanisms,the performance of DAUNet has improved by more than ten times.This study demonstrates DAUNet’s potential in advancing multi-agent ad hoc networking technologies.
基金supported by the National Natural Science Foundation of China under Grant No.61802052the Fundamental Research Funds for the Central Universities under Grant No.A030202063008085the China Postdoctoral Science Foundation Funded Project under Grant No.2017M612947。
文摘In the real-time scheduling theory,schedulability and synchronization analyses are used to evaluate scheduling algorithms and real-time locking protocols,respectively,and the empirical synthesis experiment is one of the major methods to compare the performance of such analyses.However,since many sophisticated techniques have been adopted to improve the analytical accuracy,the implementation of such analyses and experiments is often time-consuming.This paper proposes a schedulability experiment toolkit for multiprocessor real-time systems(SET-MRTS),which provides a framework with infrastructures to implement the schedulability and synchronization analyses and the deployment of empirical synthesis experiments.Besides,with well-designed peripheral components for the input and output,experiments can be conducted easily and flexibly on SET-MRTS.This demonstration further proves the effectiveness of SET-MRTS in both functionality and availability.
基金Hong Kong Research Grants Council under the GRF(9043664).
文摘This article briefly reviews the topic of complex network synchronization,with its graph-theoretic criterion,showing that the homogeneous and symmetrical network structures are essential for optimal synchronization.Furthermore,it briefly reviews the notion of higher-order network topologies and shows their promising potential in application to evaluating the optimality of network synchronizability.
文摘[ Objective] This study aimed to establish a simultaneous detection method of shrimp viruses by real-time fluorescence quantitative RT-PCR, to improve the efficiency of inspection and quarantine. [ Method] A novel real-time fluorescence quantitative RT-PCR assay was established and optimized for simultaneously detecting DNA/RNA of four shrimp viruses （WSSV, IHHNV, TSV and YHV ）. [ Result] The optimized real-time fluorescence quantitative RT-PCR system gener- ated typical amplification curves with high amplification efficiencies （E = 1.06, 1.07, 0.92 and 0.92, respectively）, good hnear relationship （ r = 1 ）, uniform repeatability （ standard deviation = 0.05 - 0.46 ; variation coefficient = 0.26% - 1.62% ） and high sensitivity, exhibiting no significant differences compared with re- al-time fluorescence quantitative PCR （average error of Ct value = 0.04 -0.40; T = 0.53 -2.50; P 〉 0.05 ）. The total detection time was about 1 h. [ Conclusion] The optimized real-time fluorescence quantitative RT-PCR system can be used for rapid detection of WSSV, IHHNV, TSV and YHV.
文摘This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-triggered mechanism(MBAETM)is designed based on sequential growth rates,focusing on event-triggered conditions and thresholds.Subsequently,from the perspective of defenders,non-periodic DoS attacks are re-characterized,and a model of irregular DoS attacks with cyclic fluctuations within time series is further introduced to enhance the system's defense capabilities more effectively.Additionally,considering the unified demands of network security and communication efficiency,a resilient memory-based adaptive event-triggered mechanism(RMBAETM)is proposed.A unified Lyapunov-Krasovskii functional is then constructed,incorporating a loop functional to thoroughly consider information at trigger moments.The master-slave system achieves synchronization through the application of linear matrix inequality techniques.Finally,the proposed methods'effectiveness and superiority are confirmed through four numerical simulation examples.
文摘This paper describes a real-time beam tuning method with an improved asynchronous advantage actor–critic(A3C)algorithm for accelerator systems.The operating parameters of devices are usually inconsistent with the predictions of physical designs because of errors in mechanical matching and installation.Therefore,parameter optimization methods such as pointwise scanning,evolutionary algorithms(EAs),and robust conjugate direction search are widely used in beam tuning to compensate for this inconsistency.However,it is difficult for them to deal with a large number of discrete local optima.The A3C algorithm,which has been applied in the automated control field,provides an approach for improving multi-dimensional optimization.The A3C algorithm is introduced and improved for the real-time beam tuning code for accelerators.Experiments in which optimization is achieved by using pointwise scanning,the genetic algorithm(one kind of EAs),and the A3C-algorithm are conducted and compared to optimize the currents of four steering magnets and two solenoids in the low-energy beam transport section(LEBT)of the Xi’an Proton Application Facility.Optimal currents are determined when the highest transmission of a radio frequency quadrupole(RFQ)accelerator downstream of the LEBT is achieved.The optimal work points of the tuned accelerator were obtained with currents of 0 A,0 A,0 A,and 0.1 A,for the four steering magnets,and 107 A and 96 A for the two solenoids.Furthermore,the highest transmission of the RFQ was 91.2%.Meanwhile,the lower time required for the optimization with the A3C algorithm was successfully verified.Optimization with the A3C algorithm consumed 42%and 78%less time than pointwise scanning with random initialization and pre-trained initialization of weights,respectively.
基金supported in part by National Key R&D Program of China(Grant No.2022YFC3803700)in part by the National Natural Science Foundation of China(Grant No.92067102)in part by the project of Beijing Laboratory of Advanced Information Networks.
文摘The rise of time-sensitive applications with broad geographical scope drives the development of time-sensitive networking(TSN)from intra-domain to inter-domain to ensure overall end-to-end connectivity requirements in heterogeneous deployments.When multiple TSN networks interconnect over non-TSN networks,all devices in the network need to be syn-chronized by sharing a uniform time reference.How-ever,most non-TSN networks are best-effort.Path delay asymmetry and random noise accumulation can introduce unpredictable time errors during end-to-end time synchronization.These factors can degrade syn-chronization performance.Therefore,cross-domain time synchronization becomes a challenging issue for multiple TSN networks interconnected by non-TSN networks.This paper presents a cross-domain time synchronization scheme that follows the software-defined TSN(SD-TSN)paradigm.It utilizes a com-bined control plane constructed by a coordinate con-troller and a domain controller for centralized control and management of cross-domain time synchroniza-tion.The general operation flow of the cross-domain time synchronization process is designed.The mecha-nism of cross-domain time synchronization is revealed by introducing a synchronization model and an error compensation method.A TSN cross-domain proto-type testbed is constructed for verification.Results show that the scheme can achieve end-to-end high-precision time synchronization with accuracy and sta-bility.
基金Supported by the National Natural Science Foundation of China (11161027)。
文摘Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and even a chaotic or hyperchaotic system,the response network is complex system coupled by N nodes,and every node is showed by the approximately linear part of the drive system.Only controlling any one node of the response network by designed controller can achieve the projective synchronization.Some numerical examples were employed to verify the effectiveness and correctness of the designed controller.
基金ThisworkwassupportedbytheNationalScienceFoundationofChina (No .60 10 3 0 2 2 ) .
文摘Aiming at issues on multimedia communication in synchronous real-time teleteaching (SRT) systems over IP network, a 4-tuple structural mode of multimedia communication is proposed in the paper, and an SRT-oriented distributed MCU model is built according to the mode. Moreover, the mechanism of multicast communication across subnets is discussed. The distributed MCU model has been applied successfully in our interactive synchronous real-time telesteaching system RealClass and has shown good extendibility in operation.
基金funded by the ICT Division of theMinistry of Posts,Telecommunications,and Information Technology of Bangladesh under Grant Number 56.00.0000.052.33.005.21-7(Tracking No.22FS15306)support from the University of Rajshahi.
文摘The Internet of Things(IoT)and mobile technology have significantly transformed healthcare by enabling real-time monitoring and diagnosis of patients.Recognizing Medical-Related Human Activities(MRHA)is pivotal for healthcare systems,particularly for identifying actions critical to patient well-being.However,challenges such as high computational demands,low accuracy,and limited adaptability persist in Human Motion Recognition(HMR).While some studies have integrated HMR with IoT for real-time healthcare applications,limited research has focused on recognizing MRHA as essential for effective patient monitoring.This study proposes a novel HMR method tailored for MRHA detection,leveraging multi-stage deep learning techniques integrated with IoT.The approach employs EfficientNet to extract optimized spatial features from skeleton frame sequences using seven Mobile Inverted Bottleneck Convolutions(MBConv)blocks,followed by Convolutional Long Short Term Memory(ConvLSTM)to capture spatio-temporal patterns.A classification module with global average pooling,a fully connected layer,and a dropout layer generates the final predictions.The model is evaluated on the NTU RGB+D 120 and HMDB51 datasets,focusing on MRHA such as sneezing,falling,walking,sitting,etc.It achieves 94.85%accuracy for cross-subject evaluations and 96.45%for cross-view evaluations on NTU RGB+D 120,along with 89.22%accuracy on HMDB51.Additionally,the system integrates IoT capabilities using a Raspberry Pi and GSM module,delivering real-time alerts via Twilios SMS service to caregivers and patients.This scalable and efficient solution bridges the gap between HMR and IoT,advancing patient monitoring,improving healthcare outcomes,and reducing costs.
文摘Along with process control,perception represents the main function performed by the Edge Layer of an Internet of Things(IoT)network.Many of these networks implement various applications where the response time does not represent an important parameter.However,in critical applications,this parameter represents a crucial aspect.One important sensing device used in IoT designs is the accelerometer.In most applications,the response time of the embedded driver software handling this device is generally not analysed and not taken into account.In this paper,we present the design and implementation of a predictable real-time driver stack for a popular accelerometer and gyroscope device family.We provide clear justifications for why this response time is extremely important for critical applications in the acquisition process of such data.We present extensive measurements and experimental results that demonstrate the predictability of our solution,making it suitable for critical real-time systems.
基金supported by the National Natural Science Foundation of China(No.52174184)。
文摘This paper propose a comprehensive data-driven prediction framework based on machine learning methods to investigate the lag synchronization phenomenon in coupled chaotic systems,particularly in cases where accurate mathematical models are challenging to establish or where system equations remain unknown.The Long Short-Term Memory(LSTM)neural network is trained using time series acquired from the desynchronization system states,subsequently predicting the lag synchronization transition.In the experiments,we focus on the Lorenz system with time-varying delayed coupling,studying the effects of coupling coefficients and time delays on lag synchronization,respectively.The results indicate that with appropriate training,the machine learning model can adeptly predict the lag synchronization occurrence and transition.This study not only enhances our comprehension of complex network synchronization behaviors but also underscores the potential and practical applications of machine learning in exploring nonlinear dynamic systems.
文摘Background Two-dimensional speckle tracking imaging （2D-STI） and real-time three-dimensional echocardiography （RT-3DE） have more advantages in evaluating left ventricular （LV） systolic dyssynchrony than traditional echocardiographic techniques. The study aimed to evaluate LV dyssynchrony parameters by both 2D-STI and RT-3DE, and the correlation between these two techniques. Methods A total of 43 chronic heart failure （CHF） patients and 27 healthy volunteers were enrolled. There were 23 dyssynchrony parameters selected to evaluate left ventricular systolic synchronization, involving 15 from 2D-STI and 8 from RT-3DE. Results Few of the dyssynchrony parametersshowednegative correlations with LV ejection fraction （LVEF） in the CHF group. The difference between time to peak-systolic radial strain of the anteroseptal and posterior segments at the level of papillary muscles [AS-P（RS）] from 2D-STI showed positive correlations with parts of the parameters from RT-3DE （P 〈 0.05）. Conclusions LV systolic dysfunction does not correlate with dyssynchrony. Moreover, there is a weak association between 2D-STI and RT-3DE in assessment of left ventricular dyssynchrony.
文摘Real-time semantic segmentation tasks place stringent demands on network inference speed,often requiring a reduction in network depth to decrease computational load.However,shallow networks tend to exhibit degradation in feature extraction completeness and inference accuracy.Therefore,balancing high performance with real-time requirements has become a critical issue in the study of real-time semantic segmentation.To address these challenges,this paper proposes a lightweight bilateral dual-residual network.By introducing a novel residual structure combined with feature extraction and fusion modules,the proposed network significantly enhances representational capacity while reducing computational costs.Specifically,an improved compound residual structure is designed to optimize the efficiency of information propagation and feature extraction.Furthermore,the proposed feature extraction and fusion module enables the network to better capture multi-scale information in images,improving the ability to detect both detailed and global semantic features.Experimental results on the publicly available Cityscapes dataset demonstrate that the proposed lightweight dual-branch network achieves outstanding performance while maintaining low computational complexity.In particular,the network achieved a mean Intersection over Union(mIoU)of 78.4%on the Cityscapes validation set,surpassing many existing semantic segmentation models.Additionally,in terms of inference speed,the network reached 74.5 frames per second when tested on an NVIDIA GeForce RTX 3090 GPU,significantly improving real-time performance.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12247153,T2293771,and 12247101)the Zhejiang Provincial Natural Science Foundation of China(Grant No.LTGY24A050002)+3 种基金the Sichuan Science and Technology Program(Grant Nos.2024NSFSC1364 and 2023NSFSC1919)the Project of Huzhou Science and Technology Bureau(Grant No.2022YZ29)the UESTCYDRI research start-up(Grant No.U03210066)the New Cornerstone Science Foundation through the Xplorer Prize。
文摘Complex networks play a crucial role in the study of collective behavior,encompassing the analysis of dynamical properties and network topology.In real-world systems,higher-order interactions among multiple entities are widespread and significantly influence collective dynamics.Here,we extend the synchronization alignment function framework to hypergraphs of arbitrary order by leveraging the multi-order Laplacian matrix to encode higher-order interactions.Our findings reveal that the upper bound of synchronous behavior is determined by the maximum eigenvalue of the multi-order Laplacian matrix.Furthermore,we decompose the contribution of each hyperedge to this eigenvalue and utilize it as a basis for designing an eigenvalue-based topology modification algorithm.This algorithm effectively enhances the upper bound of synchronous behavior without altering the total number of higher-order interactions.Our study provides new insights into dynamical optimization and topology tuning in hypergraphs,advancing the understanding of the interplay between higher-order interactions and collective dynamics.
基金supported by the National Natural Science Foundation of China(No.22306076)the Natural Science Foundation of Jiangsu Province(No.BK20230676)the Natural Science Foundation of Jiangsu Higher Education Institutions of China(No.22KJB610011).
文摘Here,a novel real-time monitoring sensor that integrates the oxidation of peroxymonosulfate(PMS)and the in situ monitoring of the pollutant degradation process is proposed.Briefly,FeCo@carbon fiber(FeCo@CF)was utilized as the anode electrode,while graphite rods served as the cathode electrode in assembling the galvanic cell.The FeCo@CF electrode exhibited rapid reactivity with PMS,generating reactive oxygen species that efficiently degrade organic pollutants.The degradation experiments indicate that complete bisphenol A(BPA)degradation was achieved within 10 min under optimal conditions.The real-time electrochemical signal was measured in time during the catalytic reaction,and a linear relationship between BPA concentration and the real-time charge(Q)was confirmed by the equation ln(C0/C)=4.393Q(correlation coefficients,R^(2)=0.998).Furthermore,experiments conducted with aureomycin and tetracycline further validated the effectiveness of the monitoring sensor.First-principles investigation confirmed the superior adsorption energy and improved electron transfer in FeCo@CF.The integration of pollutant degradation with in situ monitoring of catalytic reactions offers promising prospects for expanding the scope of the monitoring of catalytic processes and making significant contributions to environmental purification.
基金supported by the National Natural Science Foundation of China(No.62401597)the Natural Science Foundation of Hunan Province,China(No.2024JJ6469)the Scientific Research Project of National University of Defense Technology,China(No.ZK22-02)。
文摘The information exchange among satellites is crucial for the implementation of cluster satellite cooperative missions.However,achieving fast perception,rapid networking,and highprecision time synchronization among nodes without the support of the Global Navigation Satellite System(GNSS)and other prior information remains a formidable challenge to real-time wireless networks design.Therefore,a self-organizing network methodology based on multi-agent negotiation is proposed,which autonomously determines the master node through collaborative negotiation and competitive elections.On this basis,a real-time network protocol design is carried out and a high-precision time synchronization method with motion compensation is proposed.Simulation results demonstrate that the proposed method enables rapid networking with the capability of selfdiscovery,self-organization,and self-healing.For a cluster of 8 satellites,the networking time and the reorganization time are less than 4 s.The time synchronization accuracy exceeds 10-10s with motion compensation,demonstrating excellent real-time performance and stability.The research presented in this paper provides a valuable reference for the design and application of spacebased self-organizing networks for satellite cluster.
