Tow different computer calculation methods for distortion of the wide-band diode bridge track and hold amplifier (THA) are presented based on a high frequency Schottky diode model. One of the computer programs calcula...Tow different computer calculation methods for distortion of the wide-band diode bridge track and hold amplifier (THA) are presented based on a high frequency Schottky diode model. One of the computer programs calculates the distortion of weekly nonlinear THA based on the KCL and the nonlinear-current method. The other calculates the weekly nonlinear distortion by using a Volterra series method and a nodal formulation. Comparative calculation results for the diode bridge THA have shown good agreement with these two computer program calculation methods, whereas the overall computational efficiency of the nonlinear-current method is better than that of the nodal formulation method in a special evaluation.展开更多
The unique phase profile and polarization distribution of the vector vortex beam(VVB)have been a subject of increasing interest in classical and quantum optics.The development of higher-order Poincarésphere(HOPS)...The unique phase profile and polarization distribution of the vector vortex beam(VVB)have been a subject of increasing interest in classical and quantum optics.The development of higher-order Poincarésphere(HOPS)and hybrid-order Poincarésphere(HyOPS)has provided a systematic description of VVB.However,the generation of arbitrary VVBs on a HOPS and a HyOPS via a metasurface lacks a unified design framework,despite numerous reported approaches.We present a unified design framework incorporating all design parameters(e.g.,focal lengths and orders)of arbitrary HOPS and HyOPS beams into a single equation.In proof-of-concept experiments,we experimentally demonstrated four metasurfaces to generate arbitrary beams on the fifth-order HOPS(nonfocused and tightly focused,NA 0.89),0-2 order,and 0-1 order HyOPS.We showed HOPS beams’propagation and focusing properties,the superresolution focusing characteristics of the first-order cylindrical VVBs,and the different focusing properties of integerorder and fractional-order cylindrical VVBs.The simplicity and feasibility of the proposed design framework make it a potential catalyst for arbitrary VVBs using metasurfaces in applications of optical imaging,communication,and optical trapping.展开更多
The rapid and increasing growth in the volume and number of cyber threats from malware is not a real danger;the real threat lies in the obfuscation of these cyberattacks,as they constantly change their behavior,making...The rapid and increasing growth in the volume and number of cyber threats from malware is not a real danger;the real threat lies in the obfuscation of these cyberattacks,as they constantly change their behavior,making detection more difficult.Numerous researchers and developers have devoted considerable attention to this topic;however,the research field has not yet been fully saturated with high-quality studies that address these problems.For this reason,this paper presents a novel multi-objective Markov-enhanced adaptive whale optimization(MOMEAWO)cybersecurity model to improve the classification of binary and multi-class malware threats through the proposed MOMEAWO approach.The proposed MOMEAWO cybersecurity model aims to provide an innovative solution for analyzing,detecting,and classifying the behavior of obfuscated malware within their respective families.The proposed model includes three classification types:Binary classification and multi-class classification(e.g.,four families and 16 malware families).To evaluate the performance of this model,we used a recently published dataset called the Canadian Institute for Cybersecurity Malware Memory Analysis(CIC-MalMem-2022)that contains balanced data.The results show near-perfect accuracy in binary classification and high accuracy in multi-class classification compared with related work using the same dataset.展开更多
With the rapid development of artificial intelligence and Internet of Things technologies,video action recognition technology is widely applied in various scenarios,such as personal life and industrial production.Howe...With the rapid development of artificial intelligence and Internet of Things technologies,video action recognition technology is widely applied in various scenarios,such as personal life and industrial production.However,while enjoying the convenience brought by this technology,it is crucial to effectively protect the privacy of users’video data.Therefore,this paper proposes a video action recognition method based on personalized federated learning and spatiotemporal features.Under the framework of federated learning,a video action recognition method leveraging spatiotemporal features is designed.For the local spatiotemporal features of the video,a new differential information extraction scheme is proposed to extract differential features with a single RGB frame as the center,and a spatialtemporal module based on local information is designed to improve the effectiveness of local feature extraction;for the global temporal features,a method of extracting action rhythm features using differential technology is proposed,and a timemodule based on global information is designed.Different translational strides are used in the module to obtain bidirectional differential features under different action rhythms.Additionally,to address user data privacy issues,the method divides model parameters into local private parameters and public parameters based on the structure of the video action recognition model.This approach enhancesmodel training performance and ensures the security of video data.The experimental results show that under personalized federated learning conditions,an average accuracy of 97.792%was achieved on the UCF-101 dataset,which is non-independent and identically distributed(non-IID).This research provides technical support for privacy protection in video action recognition.展开更多
In this paper,we investigate an reconfigurable intelligent surface-aided Integrated Sensing And Communication(ISAC)system.Our objective is to maximize the achievable sum rate of the multi-antenna communication users t...In this paper,we investigate an reconfigurable intelligent surface-aided Integrated Sensing And Communication(ISAC)system.Our objective is to maximize the achievable sum rate of the multi-antenna communication users through the joint active and passive beamforming.Specifically,the weighted minimum mean-square error method is first used to reformulate the original problem into an equivalent one.Then,we utilize an alternating optimization algorithm to decouple the optimization variables and decompose this challenging problem into two subproblems.Given reflecting coefficients,a penalty-based algorithm is utilized to deal with the non-convex radar Signal-to-Noise Ratio(SNR)constraints.For the given beamforming matrix of the base station,we apply majorization-minimization to transform the problem into a Quadratic Constraint Quadratic Programming(QCQP)problem,which is ultimately solved using a Semi-Definite Relaxation(SDR)based algorithm.Simulation results illustrate the advantage of deploying reconfigurable intelligent surface in the considered multi-user MultipleInput Multiple-Output(MIMO)ISAC systems.展开更多
With the advent of the digital era,the field of communications is undergoing profound transformation.Among the most groundbreaking developments is the emergence of non-terrestrial networks(NTN),which represent not onl...With the advent of the digital era,the field of communications is undergoing profound transformation.Among the most groundbreaking developments is the emergence of non-terrestrial networks(NTN),which represent not only a technological leap forward but also a major trend shaping the future of global connectivity.As a layered heterogeneous network,NTN integrates multiple aerial platforms—including satellites,high-altitude platform systems(HAPS),and unmanned aerial systems(UAS)—to provide flexible and composable solutions aimed at achieving seamless worldwide communication coverage.展开更多
Cardiovascular diseases(CVDs)remain one of the foremost causes of death globally;hence,the need for several must-have,advanced automated diagnostic solutions towards early detection and intervention.Traditional auscul...Cardiovascular diseases(CVDs)remain one of the foremost causes of death globally;hence,the need for several must-have,advanced automated diagnostic solutions towards early detection and intervention.Traditional auscultation of cardiovascular sounds is heavily reliant on clinical expertise and subject to high variability.To counter this limitation,this study proposes an AI-driven classification system for cardiovascular sounds whereby deep learning techniques are engaged to automate the detection of an abnormal heartbeat.We employ FastAI vision-learner-based convolutional neural networks(CNNs)that include ResNet,DenseNet,VGG,ConvNeXt,SqueezeNet,and AlexNet to classify heart sound recordings.Instead of raw waveform analysis,the proposed approach transforms preprocessed cardiovascular audio signals into spectrograms,which are suited for capturing temporal and frequency-wise patterns.The models are trained on the PASCAL Cardiovascular Challenge dataset while taking into consideration the recording variations,noise levels,and acoustic distortions.To demonstrate generalization,external validation using Google’s Audio set Heartbeat Sound dataset was performed using a dataset rich in cardiovascular sounds.Comparative analysis revealed that DenseNet-201,ConvNext Large,and ResNet-152 could deliver superior performance to the other architectures,achieving an accuracy of 81.50%,a precision of 85.50%,and an F1-score of 84.50%.In the process,we performed statistical significance testing,such as the Wilcoxon signed-rank test,to validate performance improvements over traditional classification methods.Beyond the technical contributions,the research underscores clinical integration,outlining a pathway in which the proposed system can augment conventional electronic stethoscopes and telemedicine platforms in the AI-assisted diagnostic workflows.We also discuss in detail issues of computational efficiency,model interpretability,and ethical considerations,particularly concerning algorithmic bias stemming from imbalanced datasets and the need for real-time processing in clinical settings.The study describes a scalable,automated system combining deep learning,feature extraction using spectrograms,and external validation that can assist healthcare providers in the early and accurate detection of cardiovascular disease.AI-driven solutions can be viable in improving access,reducing delays in diagnosis,and ultimately even the continued global burden of heart disease.展开更多
A more general narrowband regular-shaped geometry-based statistical model(RS-GBSM) combined with the line of sight(LoS) and single bounce(SB) rays for unmanned aerial vehicle(UAV) multiple-input multiple-output(MIMO) ...A more general narrowband regular-shaped geometry-based statistical model(RS-GBSM) combined with the line of sight(LoS) and single bounce(SB) rays for unmanned aerial vehicle(UAV) multiple-input multiple-output(MIMO) channel is proposed in this paper. The channel characteristics, including space-time correlation function(STCF), Doppler power spectral density(DPSD), level crossing rate(LCR) and average fade duration(AFD), are derived based on the single sphere reference model for a non-isotropic environment. The corresponding sum-of-sinusoids(SoS) simulation models including both the deterministic model and statistical model with finite scatterers are also proposed for practicable implementation. The simulation results illustrate that the simulation models well reproduce the channel characteristics of the single sphere reference model with sufficient simulation scatterers. And the statistical model has a better approximation of the reference model in comparison with the deterministic one when the simulation trials of the stochastic model are sufficient. The effects of the parameters such as flight height, moving direction and Rice factor on the characteristics are also studied.展开更多
Ethics and governance are vital to the healthy and sustainable development of artificial intelligence(AI).With the long-term goal of keeping AI beneficial to human society,governments,research organizations,and compan...Ethics and governance are vital to the healthy and sustainable development of artificial intelligence(AI).With the long-term goal of keeping AI beneficial to human society,governments,research organizations,and companies in China have published ethical guidelines and principles for AI,and have launched projects to develop AI governance technologies.This paper presents a survey of these efforts and highlights the preliminary outcomes in China.It also describes the major research challenges in AI governance research and discusses future research directions.展开更多
To achieve the artificial general intelligence （AGI）, imitate the intelligence？ or imitate the brain？ This is the question! Most artificial intelligence （AI） approaches set the understanding of the intelligence ...To achieve the artificial general intelligence （AGI）, imitate the intelligence？ or imitate the brain？ This is the question! Most artificial intelligence （AI） approaches set the understanding of the intelligence principle as their premise. This may be correct to implement specific intelligence such as computing, symbolic logic, or what the AlphaGo could do. However, this is not correct for AGI, because to understand the principle of the brain intelligence is one of the most difficult challenges for our human beings. It is not wise to set such a question as the premise of the AGI mission. To achieve AGI, a practical approach is to build the so-called neurocomputer, which could be trained to produce autonomous intelligence and AGI. A neurocomputer imitates the biological neural network with neuromorphic devices which emulate the bio-neurons, synapses and other essential neural components. The neurocomputer could perceive the environment via sensors and interact with other entities via a physical body. The philosophy under the ＂new＂ approach, so-called as imitationalism in this paper, is the engineering methodology which has been practiced for thousands of years, and for many cases, such as the invention of the first airplane, succeeded. This paper compares the neurocomputer with the conventional computer. The major progress about neurocomputer is also reviewed.展开更多
A new scheme of small compact optical frequency standard based on thermal calcium beam with application of 423 nm shelving detection and sharp-angle velocity selection detection is proposed. Combining these presented ...A new scheme of small compact optical frequency standard based on thermal calcium beam with application of 423 nm shelving detection and sharp-angle velocity selection detection is proposed. Combining these presented techniques, we conclude that a small compact optical frequency standard based on thermal calcium beam will outperform the commercial caesium-beam microwave dock, like the 5071 Cs clock （from Hp to Agilent, now Symmetricom company）, both in accuracy and stability.展开更多
The sixth generation(6G)mobile networks will reshape the world by offering instant,efficient,and intelligent hyper-connectivity,as envisioned by the previously proposed Ubiquitous-X 6G networks.Such hyper-massive and ...The sixth generation(6G)mobile networks will reshape the world by offering instant,efficient,and intelligent hyper-connectivity,as envisioned by the previously proposed Ubiquitous-X 6G networks.Such hyper-massive and global connectivity will introduce tremendous challenges into the operation and management of 6G networks,calling for revolutionary theories and technological innovations.To this end,we propose a new route to boost network capabilities toward a wisdom-evolutionary and primitive-concise network(WePCN)vision for the Ubiquitous-X 6G network.In particular,we aim to concretize the evolution path toward the WePCN by first conceiving a new semantic representation framework,namely semantic base,and then establishing an intelligent and efficient semantic communication(IE-SC)network architecture.In the IE-SC architecture,a semantic intelligence plane is employed to interconnect the semantic-empowered physical-bearing layer,network protocol layer,and application-intent layer via semantic information flows.The proposed architecture integrates artificial intelligence and network technologies to enable intelligent interactions among various communication objects in 6G.It features a lower bandwidth requirement,less redundancy,and more accurate intent identification.We also present a brief review of recent advances in semantic communications and highlight potential use cases,complemented by a range of open challenges for 6G.展开更多
This paper reports that two identical external-cavity-diode-laser （ECDL） based spectrometers are constructed at 634nm referencing on the hyperfine B-X transition R（80）8-4 of 127I2. The lasers are stabilized on the...This paper reports that two identical external-cavity-diode-laser （ECDL） based spectrometers are constructed at 634nm referencing on the hyperfine B-X transition R（80）8-4 of 127I2. The lasers are stabilized on the Doppler-free absorption signals using the third-harmonic detection technique. The instability of the stabilized laser is measured to be 2.8 × 10^-12 （after 1000 s） by counting the beat note between the two lasers. The absolute optical frequency of the transition is, for the first time, determined to be 472851936189.5 kHz by using an optical frequency comb referenced on the microwave caesium atomic clock. The uncertainty of the measurement is less than 4.9 kHz.展开更多
The explosive growth of data and information has motivated various emerging non-von Neumann computational approaches in the More-than-Moore era.Photonics neuromorphic computing has attracted lots of attention due to t...The explosive growth of data and information has motivated various emerging non-von Neumann computational approaches in the More-than-Moore era.Photonics neuromorphic computing has attracted lots of attention due to the fascinating advantages such as high speed,wide bandwidth,and massive parallelism.Here,we offer a review on the optical neural computing in our research groups at the device and system levels.The photonics neuron and photonics synapse plasticity are presented.In addition,we introduce several optical neural computing architectures and algorithms including photonic spiking neural network,photonic convolutional neural network,photonic matrix computation,photonic reservoir computing,and photonic reinforcement learning.Finally,we summarize the major challenges faced by photonic neuromorphic computing,and propose promising solutions and perspectives.展开更多
Norm optimal iterative learning control(NOILC) has recently been applied to iterative learning control(ILC) problems in which tracking is only required at a subset of isolated time points along the trial duration. Thi...Norm optimal iterative learning control(NOILC) has recently been applied to iterative learning control(ILC) problems in which tracking is only required at a subset of isolated time points along the trial duration. This problem addresses the practical needs of many applications, including industrial automation, crane control, satellite positioning and motion control within a medical stroke rehabilitation context. This paper provides a substantial generalization of this framework by providing a solution to the problem of convergence at intermediate points with simultaneous tracking of subsets of outputs to reference trajectories on subintervals. This formulation enables the NOILC paradigm to tackle tasks which mix "point to point" movements with linear tracking requirements and hence substantially broadens the application domain to include automation tasks which include welding or cutting movements, or human motion control where the movement is restricted by the task to straight line and/or planar segments. A solution to the problem is presented in the framework of NOILC and inherits NOILC s well-defined convergence properties. Design guidelines and supporting experimental results are included.展开更多
Recyclability and self-healing are two most critical factors in developing sustainable polymers to deal with environmental pollution and resource waste.In this work,a dynamic cross-linked polyimide insulation film wit...Recyclability and self-healing are two most critical factors in developing sustainable polymers to deal with environmental pollution and resource waste.In this work,a dynamic cross-linked polyimide insulation film with full closed-loop recyclability is successfully prepared,which also possesses good self-healing ability after being mechanical/electrical damaged depending on the Schiff base dynamic covalent bonds.The recycled and self-healed polyimide film still maintain its good tensile strength(r t)>60 MPa with Young’s modulus(E)>4 GPa,high thermal stability with glass transition temperature(T g)>220℃,and outstanding insulation property with breakdown strength(E 0)>358 kV mm^(-1),making it a very promising low energy consumption and high temperature resistant insulation material.The strategy of using Schiff base dynamic covalent bonds for reversible repairing the structure of high T g polyimides promotes the wider application of such sustainable and recyclable material in the field of electrical power and micro-electronics.展开更多
In this paper, we consider a novel two-dimensional(2D) geometry-based stochastic model(GBSM) for multiple-input multiple-output(MIMO) vehicle-to-vehicle(V2V) wideband fading channels. The proposed model employs the co...In this paper, we consider a novel two-dimensional(2D) geometry-based stochastic model(GBSM) for multiple-input multiple-output(MIMO) vehicle-to-vehicle(V2V) wideband fading channels. The proposed model employs the combination of a two-ring model and a multiple confocal ellipses model, where the signal is sum of the line-of-sight(Lo S) component, single-bounced(SB) rays, and double-bounced(DB) rays. Based on the reference model, we derive some expressions of channel statistical properties, including space-time correlation function(STCF), Doppler spectral power density(DPSD), envelope level crossing rate(LCR) and average fade duration(AFD). In addition, corresponding deterministic and stochastic simulation models are developed based on the reference model. Moreover, we compare the statistical properties of the reference model and the two simulation models in different scenarios and investigate the impact of different vehicular traffic densities(VTDs) on the channel statistical properties of the proposed model. Finally, the great agreement between simulation models and the reference model demonstrates not only the utility of simulation models, but also the correctness of theoretical derivations and simulations.展开更多
The electrocardiogram （ECG） has broad applications in clinical diagnosis and prognosis of cardiovascular disease. Many researchers have contributed to its progressive development. To commemorate those pioneers, and ...The electrocardiogram （ECG） has broad applications in clinical diagnosis and prognosis of cardiovascular disease. Many researchers have contributed to its progressive development. To commemorate those pioneers, and to better study and promote the use of ECG, we reviewed and present here a systematic introduction about the history, hotspots, and trends of ECG. In the historical part, information including the invention, improvement, and extensive applications of ECG, such as in long QT syndrome （LQTS）, angina, and myocardial infarction （MI）, are chronologi- cally presented. New technologies and applications from the 1990s are also introduced. In the second part, we use the bibliometric analysis me- thod to analyze the hotspots in the field of ECG-related research. By using total citations and year-specific total citations as our main criteria, four key hotspots in ECG-related research were identified from 11 articles, including atrial fibrillation, LQTS, angina and MI, and heart rate variability. Recent studies in those four areas are also reported. In the final part, we discuss the future trends concerning ECG-related research. The authors believe that improvement of the ECG instrumentation, big data mining for ECG, and the accuracy of diagnosis and application will be areas of continuous concern.展开更多
The ability of accurate and scalable mobile device recognition is critically important for mobile network operators and ISPs to understand their customers' behaviours and enhance their user experience.In this pape...The ability of accurate and scalable mobile device recognition is critically important for mobile network operators and ISPs to understand their customers' behaviours and enhance their user experience.In this paper,we propose a novel method for mobile device model recognition by using statistical information derived from large amounts of mobile network traffic data.Specifically,we create a Jaccardbased coefficient measure method to identify a proper keyword representing each mobile device model from massive unstructured textual HTTP access logs.To handle the large amount of traffic data generated from large mobile networks,this method is designed as a set of parallel algorithms,and is implemented through the MapReduce framework which is a distributed parallel programming model with proven low-cost and high-efficiency features.Evaluations using real data sets show that our method can accurately recognise mobile client models while meeting the scalability and producer-independency requirements of large mobile network operators.Results show that a 91.5% accuracy rate is achieved for recognising mobile client models from 2 billion records,which is dramatically higher than existing solutions.展开更多
We demonstrate an 852-nm external cavity diode laser（ECDL） system whose wavelength is mainly determined by an interference filter instead of other wavelength selective elements. The Lorentzian linewidth measured by ...We demonstrate an 852-nm external cavity diode laser（ECDL） system whose wavelength is mainly determined by an interference filter instead of other wavelength selective elements. The Lorentzian linewidth measured by the heterodyne beating between two identical lasers is 28.3 k Hz. Moreover, we test the application of the ECDL in the Faraday atomic filter.Besides saturated absorption spectrum, the transmission spectrum of the Faraday atomic filter at 852 nm is measured by using the ECDL. This interference filter ECDL method can also be extended to other wavelengths and widen the application range of diode laser.展开更多
文摘Tow different computer calculation methods for distortion of the wide-band diode bridge track and hold amplifier (THA) are presented based on a high frequency Schottky diode model. One of the computer programs calculates the distortion of weekly nonlinear THA based on the KCL and the nonlinear-current method. The other calculates the weekly nonlinear distortion by using a Volterra series method and a nodal formulation. Comparative calculation results for the diode bridge THA have shown good agreement with these two computer program calculation methods, whereas the overall computational efficiency of the nonlinear-current method is better than that of the nodal formulation method in a special evaluation.
基金the Chinese Scholarship Council is acknowledged.This work was supported by the UK’s Engineering and Physical Sciences Research Council(Grant Nos.EP/V000624/1,EP/X03495X/1,EP/X041166/1,and EP/T02643X/1)the Royal Society(Grant No.RG\R2\232531).
文摘The unique phase profile and polarization distribution of the vector vortex beam(VVB)have been a subject of increasing interest in classical and quantum optics.The development of higher-order Poincarésphere(HOPS)and hybrid-order Poincarésphere(HyOPS)has provided a systematic description of VVB.However,the generation of arbitrary VVBs on a HOPS and a HyOPS via a metasurface lacks a unified design framework,despite numerous reported approaches.We present a unified design framework incorporating all design parameters(e.g.,focal lengths and orders)of arbitrary HOPS and HyOPS beams into a single equation.In proof-of-concept experiments,we experimentally demonstrated four metasurfaces to generate arbitrary beams on the fifth-order HOPS(nonfocused and tightly focused,NA 0.89),0-2 order,and 0-1 order HyOPS.We showed HOPS beams’propagation and focusing properties,the superresolution focusing characteristics of the first-order cylindrical VVBs,and the different focusing properties of integerorder and fractional-order cylindrical VVBs.The simplicity and feasibility of the proposed design framework make it a potential catalyst for arbitrary VVBs using metasurfaces in applications of optical imaging,communication,and optical trapping.
文摘The rapid and increasing growth in the volume and number of cyber threats from malware is not a real danger;the real threat lies in the obfuscation of these cyberattacks,as they constantly change their behavior,making detection more difficult.Numerous researchers and developers have devoted considerable attention to this topic;however,the research field has not yet been fully saturated with high-quality studies that address these problems.For this reason,this paper presents a novel multi-objective Markov-enhanced adaptive whale optimization(MOMEAWO)cybersecurity model to improve the classification of binary and multi-class malware threats through the proposed MOMEAWO approach.The proposed MOMEAWO cybersecurity model aims to provide an innovative solution for analyzing,detecting,and classifying the behavior of obfuscated malware within their respective families.The proposed model includes three classification types:Binary classification and multi-class classification(e.g.,four families and 16 malware families).To evaluate the performance of this model,we used a recently published dataset called the Canadian Institute for Cybersecurity Malware Memory Analysis(CIC-MalMem-2022)that contains balanced data.The results show near-perfect accuracy in binary classification and high accuracy in multi-class classification compared with related work using the same dataset.
基金supported by National Natural Science Foundation of China(Grant No.62071098)Sichuan Science and Technology Program(Grants 2022YFG0319,2023YFG0301 and 2023YFG0018).
文摘With the rapid development of artificial intelligence and Internet of Things technologies,video action recognition technology is widely applied in various scenarios,such as personal life and industrial production.However,while enjoying the convenience brought by this technology,it is crucial to effectively protect the privacy of users’video data.Therefore,this paper proposes a video action recognition method based on personalized federated learning and spatiotemporal features.Under the framework of federated learning,a video action recognition method leveraging spatiotemporal features is designed.For the local spatiotemporal features of the video,a new differential information extraction scheme is proposed to extract differential features with a single RGB frame as the center,and a spatialtemporal module based on local information is designed to improve the effectiveness of local feature extraction;for the global temporal features,a method of extracting action rhythm features using differential technology is proposed,and a timemodule based on global information is designed.Different translational strides are used in the module to obtain bidirectional differential features under different action rhythms.Additionally,to address user data privacy issues,the method divides model parameters into local private parameters and public parameters based on the structure of the video action recognition model.This approach enhancesmodel training performance and ensures the security of video data.The experimental results show that under personalized federated learning conditions,an average accuracy of 97.792%was achieved on the UCF-101 dataset,which is non-independent and identically distributed(non-IID).This research provides technical support for privacy protection in video action recognition.
基金supported in part by the National Natural Science Foundation of China under Grants 62201137 and 62331023in part by the Fundamental Research Funds for the Central Universities under Grant 2242022k60001in part by the Fundamental Research Funds for the Central Universities under Grant 2242025K20001。
文摘In this paper,we investigate an reconfigurable intelligent surface-aided Integrated Sensing And Communication(ISAC)system.Our objective is to maximize the achievable sum rate of the multi-antenna communication users through the joint active and passive beamforming.Specifically,the weighted minimum mean-square error method is first used to reformulate the original problem into an equivalent one.Then,we utilize an alternating optimization algorithm to decouple the optimization variables and decompose this challenging problem into two subproblems.Given reflecting coefficients,a penalty-based algorithm is utilized to deal with the non-convex radar Signal-to-Noise Ratio(SNR)constraints.For the given beamforming matrix of the base station,we apply majorization-minimization to transform the problem into a Quadratic Constraint Quadratic Programming(QCQP)problem,which is ultimately solved using a Semi-Definite Relaxation(SDR)based algorithm.Simulation results illustrate the advantage of deploying reconfigurable intelligent surface in the considered multi-user MultipleInput Multiple-Output(MIMO)ISAC systems.
文摘With the advent of the digital era,the field of communications is undergoing profound transformation.Among the most groundbreaking developments is the emergence of non-terrestrial networks(NTN),which represent not only a technological leap forward but also a major trend shaping the future of global connectivity.As a layered heterogeneous network,NTN integrates multiple aerial platforms—including satellites,high-altitude platform systems(HAPS),and unmanned aerial systems(UAS)—to provide flexible and composable solutions aimed at achieving seamless worldwide communication coverage.
基金funded by the deanship of scientific research(DSR),King Abdulaziz University,Jeddah,under grant No.(G-1436-611-309).
文摘Cardiovascular diseases(CVDs)remain one of the foremost causes of death globally;hence,the need for several must-have,advanced automated diagnostic solutions towards early detection and intervention.Traditional auscultation of cardiovascular sounds is heavily reliant on clinical expertise and subject to high variability.To counter this limitation,this study proposes an AI-driven classification system for cardiovascular sounds whereby deep learning techniques are engaged to automate the detection of an abnormal heartbeat.We employ FastAI vision-learner-based convolutional neural networks(CNNs)that include ResNet,DenseNet,VGG,ConvNeXt,SqueezeNet,and AlexNet to classify heart sound recordings.Instead of raw waveform analysis,the proposed approach transforms preprocessed cardiovascular audio signals into spectrograms,which are suited for capturing temporal and frequency-wise patterns.The models are trained on the PASCAL Cardiovascular Challenge dataset while taking into consideration the recording variations,noise levels,and acoustic distortions.To demonstrate generalization,external validation using Google’s Audio set Heartbeat Sound dataset was performed using a dataset rich in cardiovascular sounds.Comparative analysis revealed that DenseNet-201,ConvNext Large,and ResNet-152 could deliver superior performance to the other architectures,achieving an accuracy of 81.50%,a precision of 85.50%,and an F1-score of 84.50%.In the process,we performed statistical significance testing,such as the Wilcoxon signed-rank test,to validate performance improvements over traditional classification methods.Beyond the technical contributions,the research underscores clinical integration,outlining a pathway in which the proposed system can augment conventional electronic stethoscopes and telemedicine platforms in the AI-assisted diagnostic workflows.We also discuss in detail issues of computational efficiency,model interpretability,and ethical considerations,particularly concerning algorithmic bias stemming from imbalanced datasets and the need for real-time processing in clinical settings.The study describes a scalable,automated system combining deep learning,feature extraction using spectrograms,and external validation that can assist healthcare providers in the early and accurate detection of cardiovascular disease.AI-driven solutions can be viable in improving access,reducing delays in diagnosis,and ultimately even the continued global burden of heart disease.
基金supported in part by the National Natural Science Foundation of China under Grant 61622101 and Grant 61571020National Science and Technology Major Project under Grant 2018ZX03001031
文摘A more general narrowband regular-shaped geometry-based statistical model(RS-GBSM) combined with the line of sight(LoS) and single bounce(SB) rays for unmanned aerial vehicle(UAV) multiple-input multiple-output(MIMO) channel is proposed in this paper. The channel characteristics, including space-time correlation function(STCF), Doppler power spectral density(DPSD), level crossing rate(LCR) and average fade duration(AFD), are derived based on the single sphere reference model for a non-isotropic environment. The corresponding sum-of-sinusoids(SoS) simulation models including both the deterministic model and statistical model with finite scatterers are also proposed for practicable implementation. The simulation results illustrate that the simulation models well reproduce the channel characteristics of the single sphere reference model with sufficient simulation scatterers. And the statistical model has a better approximation of the reference model in comparison with the deterministic one when the simulation trials of the stochastic model are sufficient. The effects of the parameters such as flight height, moving direction and Rice factor on the characteristics are also studied.
文摘Ethics and governance are vital to the healthy and sustainable development of artificial intelligence(AI).With the long-term goal of keeping AI beneficial to human society,governments,research organizations,and companies in China have published ethical guidelines and principles for AI,and have launched projects to develop AI governance technologies.This paper presents a survey of these efforts and highlights the preliminary outcomes in China.It also describes the major research challenges in AI governance research and discusses future research directions.
基金supported by the Natural Science Foundation of China(Nos.61425025 and 61390515)
文摘To achieve the artificial general intelligence （AGI）, imitate the intelligence？ or imitate the brain？ This is the question! Most artificial intelligence （AI） approaches set the understanding of the intelligence principle as their premise. This may be correct to implement specific intelligence such as computing, symbolic logic, or what the AlphaGo could do. However, this is not correct for AGI, because to understand the principle of the brain intelligence is one of the most difficult challenges for our human beings. It is not wise to set such a question as the premise of the AGI mission. To achieve AGI, a practical approach is to build the so-called neurocomputer, which could be trained to produce autonomous intelligence and AGI. A neurocomputer imitates the biological neural network with neuromorphic devices which emulate the bio-neurons, synapses and other essential neural components. The neurocomputer could perceive the environment via sensors and interact with other entities via a physical body. The philosophy under the ＂new＂ approach, so-called as imitationalism in this paper, is the engineering methodology which has been practiced for thousands of years, and for many cases, such as the invention of the first airplane, succeeded. This paper compares the neurocomputer with the conventional computer. The major progress about neurocomputer is also reviewed.
基金Supported by the National Key Basic Research and Development Programme of China under Grant No 2005CB724500, and the National Natural Science Foundation of China under Grant Nos 60178016 and 10104002.
文摘A new scheme of small compact optical frequency standard based on thermal calcium beam with application of 423 nm shelving detection and sharp-angle velocity selection detection is proposed. Combining these presented techniques, we conclude that a small compact optical frequency standard based on thermal calcium beam will outperform the commercial caesium-beam microwave dock, like the 5071 Cs clock （from Hp to Agilent, now Symmetricom company）, both in accuracy and stability.
基金the National Key Research and Development Program of China(2019YFC1511302)in part by the National Natural Science Foundation of China(61871057)in part by the Fundamental Research Funds for the Central Universities(2019XD-A13).
文摘The sixth generation(6G)mobile networks will reshape the world by offering instant,efficient,and intelligent hyper-connectivity,as envisioned by the previously proposed Ubiquitous-X 6G networks.Such hyper-massive and global connectivity will introduce tremendous challenges into the operation and management of 6G networks,calling for revolutionary theories and technological innovations.To this end,we propose a new route to boost network capabilities toward a wisdom-evolutionary and primitive-concise network(WePCN)vision for the Ubiquitous-X 6G network.In particular,we aim to concretize the evolution path toward the WePCN by first conceiving a new semantic representation framework,namely semantic base,and then establishing an intelligent and efficient semantic communication(IE-SC)network architecture.In the IE-SC architecture,a semantic intelligence plane is employed to interconnect the semantic-empowered physical-bearing layer,network protocol layer,and application-intent layer via semantic information flows.The proposed architecture integrates artificial intelligence and network technologies to enable intelligent interactions among various communication objects in 6G.It features a lower bandwidth requirement,less redundancy,and more accurate intent identification.We also present a brief review of recent advances in semantic communications and highlight potential use cases,complemented by a range of open challenges for 6G.
基金Project supported by the National Fundamental Research Program of China (Grant Nos 2005CB3724500 and 2006CB921400)the Major Program of National Natural Science Foundation of China (Grant No 60490280)National Natural Science Foundation of China (Grant No 10574005)
文摘This paper reports that two identical external-cavity-diode-laser （ECDL） based spectrometers are constructed at 634nm referencing on the hyperfine B-X transition R（80）8-4 of 127I2. The lasers are stabilized on the Doppler-free absorption signals using the third-harmonic detection technique. The instability of the stabilized laser is measured to be 2.8 × 10^-12 （after 1000 s） by counting the beat note between the two lasers. The absolute optical frequency of the transition is, for the first time, determined to be 472851936189.5 kHz by using an optical frequency comb referenced on the microwave caesium atomic clock. The uncertainty of the measurement is less than 4.9 kHz.
基金This work was supported in part by the National Outstanding Youth Science Fund Project of National Natural Science Foundation of China(62022062)the National Natural Science Foundation of China(61974177,61674119)the Fundamental Research Funds for the Central Universities.
文摘The explosive growth of data and information has motivated various emerging non-von Neumann computational approaches in the More-than-Moore era.Photonics neuromorphic computing has attracted lots of attention due to the fascinating advantages such as high speed,wide bandwidth,and massive parallelism.Here,we offer a review on the optical neural computing in our research groups at the device and system levels.The photonics neuron and photonics synapse plasticity are presented.In addition,we introduce several optical neural computing architectures and algorithms including photonic spiking neural network,photonic convolutional neural network,photonic matrix computation,photonic reservoir computing,and photonic reinforcement learning.Finally,we summarize the major challenges faced by photonic neuromorphic computing,and propose promising solutions and perspectives.
文摘Norm optimal iterative learning control(NOILC) has recently been applied to iterative learning control(ILC) problems in which tracking is only required at a subset of isolated time points along the trial duration. This problem addresses the practical needs of many applications, including industrial automation, crane control, satellite positioning and motion control within a medical stroke rehabilitation context. This paper provides a substantial generalization of this framework by providing a solution to the problem of convergence at intermediate points with simultaneous tracking of subsets of outputs to reference trajectories on subintervals. This formulation enables the NOILC paradigm to tackle tasks which mix "point to point" movements with linear tracking requirements and hence substantially broadens the application domain to include automation tasks which include welding or cutting movements, or human motion control where the movement is restricted by the task to straight line and/or planar segments. A solution to the problem is presented in the framework of NOILC and inherits NOILC s well-defined convergence properties. Design guidelines and supporting experimental results are included.
基金This work was financially supported by the National Natural Science Foundation of China (No.51977114,52177020)Fundamental Research Funds for the Central Universities (No.FRF-NP-19-008 and FRF-TP-20-02B2)Scientific and Techno-logical Innovation Foundation of Foshan (BK21BE006).
文摘Recyclability and self-healing are two most critical factors in developing sustainable polymers to deal with environmental pollution and resource waste.In this work,a dynamic cross-linked polyimide insulation film with full closed-loop recyclability is successfully prepared,which also possesses good self-healing ability after being mechanical/electrical damaged depending on the Schiff base dynamic covalent bonds.The recycled and self-healed polyimide film still maintain its good tensile strength(r t)>60 MPa with Young’s modulus(E)>4 GPa,high thermal stability with glass transition temperature(T g)>220℃,and outstanding insulation property with breakdown strength(E 0)>358 kV mm^(-1),making it a very promising low energy consumption and high temperature resistant insulation material.The strategy of using Schiff base dynamic covalent bonds for reversible repairing the structure of high T g polyimides promotes the wider application of such sustainable and recyclable material in the field of electrical power and micro-electronics.
基金supported in part by the project from the ZTEthe National Natural Science Foundation of China under Grant 61622101 and Grant 61571020National Science and Technology Major Project under Grant 2018ZX03001031
文摘In this paper, we consider a novel two-dimensional(2D) geometry-based stochastic model(GBSM) for multiple-input multiple-output(MIMO) vehicle-to-vehicle(V2V) wideband fading channels. The proposed model employs the combination of a two-ring model and a multiple confocal ellipses model, where the signal is sum of the line-of-sight(Lo S) component, single-bounced(SB) rays, and double-bounced(DB) rays. Based on the reference model, we derive some expressions of channel statistical properties, including space-time correlation function(STCF), Doppler spectral power density(DPSD), envelope level crossing rate(LCR) and average fade duration(AFD). In addition, corresponding deterministic and stochastic simulation models are developed based on the reference model. Moreover, we compare the statistical properties of the reference model and the two simulation models in different scenarios and investigate the impact of different vehicular traffic densities(VTDs) on the channel statistical properties of the proposed model. Finally, the great agreement between simulation models and the reference model demonstrates not only the utility of simulation models, but also the correctness of theoretical derivations and simulations.
基金This research was supported in part by National Natural Science Foundation of China，supported by Research Funds of China Space Medical Engineering，supported by State Key Laboratory of Space Medicine Fundamentals and Applications, China Astronaut Research and Training Centre
文摘The electrocardiogram （ECG） has broad applications in clinical diagnosis and prognosis of cardiovascular disease. Many researchers have contributed to its progressive development. To commemorate those pioneers, and to better study and promote the use of ECG, we reviewed and present here a systematic introduction about the history, hotspots, and trends of ECG. In the historical part, information including the invention, improvement, and extensive applications of ECG, such as in long QT syndrome （LQTS）, angina, and myocardial infarction （MI）, are chronologi- cally presented. New technologies and applications from the 1990s are also introduced. In the second part, we use the bibliometric analysis me- thod to analyze the hotspots in the field of ECG-related research. By using total citations and year-specific total citations as our main criteria, four key hotspots in ECG-related research were identified from 11 articles, including atrial fibrillation, LQTS, angina and MI, and heart rate variability. Recent studies in those four areas are also reported. In the final part, we discuss the future trends concerning ECG-related research. The authors believe that improvement of the ECG instrumentation, big data mining for ECG, and the accuracy of diagnosis and application will be areas of continuous concern.
基金supported in part by the National Natural Science Foundation of China under Grant No.61072061the National Science and Technology Major Projects under Grant No.2012ZX03002008the Fundamental Research Funds for the Central Universities under Grant No.2012RC0121
文摘The ability of accurate and scalable mobile device recognition is critically important for mobile network operators and ISPs to understand their customers' behaviours and enhance their user experience.In this paper,we propose a novel method for mobile device model recognition by using statistical information derived from large amounts of mobile network traffic data.Specifically,we create a Jaccardbased coefficient measure method to identify a proper keyword representing each mobile device model from massive unstructured textual HTTP access logs.To handle the large amount of traffic data generated from large mobile networks,this method is designed as a set of parallel algorithms,and is implemented through the MapReduce framework which is a distributed parallel programming model with proven low-cost and high-efficiency features.Evaluations using real data sets show that our method can accurately recognise mobile client models while meeting the scalability and producer-independency requirements of large mobile network operators.Results show that a 91.5% accuracy rate is achieved for recognising mobile client models from 2 billion records,which is dramatically higher than existing solutions.
基金supported by the National Natural Science Foundation of China(Grant No.91436210)the International Science and Technology Cooperation Program of China(Grant No.2010DFR10900)
文摘We demonstrate an 852-nm external cavity diode laser（ECDL） system whose wavelength is mainly determined by an interference filter instead of other wavelength selective elements. The Lorentzian linewidth measured by the heterodyne beating between two identical lasers is 28.3 k Hz. Moreover, we test the application of the ECDL in the Faraday atomic filter.Besides saturated absorption spectrum, the transmission spectrum of the Faraday atomic filter at 852 nm is measured by using the ECDL. This interference filter ECDL method can also be extended to other wavelengths and widen the application range of diode laser.
