The proliferation of heterogeneous networks,such as the Internet of Things(IoT),unmanned aerial vehicle(UAV)networks,and edge networks,has increased the complexity of network operation and administration,driving the e...The proliferation of heterogeneous networks,such as the Internet of Things(IoT),unmanned aerial vehicle(UAV)networks,and edge networks,has increased the complexity of network operation and administration,driving the emergence of digital twin networks(DTNs)that create digital-physical network mappings.While DTNs enable performance analysis through emulation testbeds,current research focuses on network-level systems,neglecting equipment-level emulation of critical components like core switches and routers.To address this issue,we propose v Fabric(short for virtual switch),a digital twin emulator for high-capacity core switching equipment.This solution implements virtual switching and network processor(NP)chip models through specialized processes,deployable on single or distributed servers via socket communication.The v Fabric emulator can realize the accurate emulation for the core switching equipment with 720 ports and 100 Gbit/s per port on the largest scale.To our knowledge,this represents the first digital twin emulation framework specifically designed for large-capacity core switching equipment in communication networks.展开更多
Methane in-situ explosive fracturing technology produces shale debris particles within fracture channels,enabling a self-propping effect that enhances the fracture network conductivity and long-term stability.This stu...Methane in-situ explosive fracturing technology produces shale debris particles within fracture channels,enabling a self-propping effect that enhances the fracture network conductivity and long-term stability.This study employs X-ray computed tomography(CT)and digital volume correlation(DVC)to investigate the microstructural evolution and hydromechanical responses of shale self-propped fracture under varying confining pressures,highlighting the critical role of shale particles in maintaining fracture conductivity.Results indicate that the fracture aperture in the self-propped sample is significantly larger than in the unpropped sample throughout the loading process,with shale particles tending to crush rather than embedded into the matrix,thus maintaining flow pathways.As confining pressure increases,contact areas between fracture surfaces and particles expand,enhancing the system's stability and compressive resistance.Geometric analyses show flow paths becoming increasingly concentrated and branched under high stress.This resulted in a significant reduction in connectivity,restricting fracture permeability and amplifying the nonlinear gas flow behavior.This study introduces a permeability-strain recovery zone and a novel sensitivity parameter m,delineating stress sensitivity boundaries for permeability and normal strain,with m-value increasing with stress,revealing four characteristic regions.These findings offer theoretical support for optimizing fracturing techniques to enhance resource extraction efficiency.展开更多
This paper proposes a concurrent neural network model to mitigate non-linear distortion in power amplifiers using a basis function generation approach.The model is designed using polynomial expansion and comprises a f...This paper proposes a concurrent neural network model to mitigate non-linear distortion in power amplifiers using a basis function generation approach.The model is designed using polynomial expansion and comprises a feedforward neural network(FNN)and a convolutional neural network(CNN).The proposed model takes the basic elements that form the bases as input,defined by the generalized memory polynomial(GMP)and dynamic deviation reduction(DDR)models.The FNN generates the basis function and its output represents the basis values,while the CNN generates weights for the corresponding bases.Through the concurrent training of FNN and CNN,the hidden layer coefficients are updated,and the complex multiplication of their outputs yields the trained in-phase/quadrature(I/Q)signals.The proposed model was trained and tested using 300 MHz and 400 MHz broadband data in an orthogonal frequency division multiplexing(OFDM)communication system.The results show that the model achieves an adjacent channel power ratio(ACPR)of less than-48 d B within a 100 MHz integral bandwidth for both the training and test datasets.展开更多
A digital data-acquisition system based on XIA LLC products was used in a complex nuclear reaction experiment using radioactive ion beams.A flexible trigger system based on a field-programmable gate array(FPGA)paramet...A digital data-acquisition system based on XIA LLC products was used in a complex nuclear reaction experiment using radioactive ion beams.A flexible trigger system based on a field-programmable gate array(FPGA)parametrization was developed to adapt to different experimental sizes.A user-friendly interface was implemented,which allows converting script language expressions into FPGA internal control parameters.The proposed digital system can be combined with a conventional analog data acquisition system to provide more flexibility.The performance of the combined system was veri-fied using experimental data.展开更多
Background The triple digital divide refers to the lack of internet access,use and knowledge among specific populations.In China,middle-aged and older adults and those living in rural areas or various regions of the c...Background The triple digital divide refers to the lack of internet access,use and knowledge among specific populations.In China,middle-aged and older adults and those living in rural areas or various regions of the country are more likely to have limited internet access and skills and,thus,have less accessibility to internet services.Few longitudinal studies have explored the association between the digital divide and the progression of depressive symptoms among middle-aged and older Chinese adults.Significantly,none of the existing studies have estimated this long-term relationship from a disparity perspective.Aims This study investigates the association between the triple digital divide and depressive symptom trajectories among middle-aged and older adults in China during a 10-year follow-up period from 2011 to 2020.Methods The sample for this secondary analysis comprises 3019 urban and 10427 rural respondents selected from the China Health and Retirement Longitudinal Study baseline survey in 2011.Depressive symptoms were measured using the Center for Epidemiologic Studies Depression Scale.Employing longitudinal mixed-effects models,this study explored the association between the triple digital divide and depressive symptom trajectories among middle-aged and older Chinese adults by examining gender,rural-urban and regional disparities in this relationship.Results Our findings revealed a significant association between the triple digital divide and increasing trajectories of depressive symptoms,showing significant disparities based on gender,rural-urban dwelling and regional location.Notably,for both male and female participants who resided in urban areas or the central region of the country,their ability to use the internet,coupled with enhanced internet skills and greater access to internet services,was found to have a mitigating effect on the increasing trajectories of depressive symptoms.Conclusions To alleviate some of the confounding influences on the trajectory of depression in middle-aged and older adults,policymakers in China should continue to prioritise the development of internet technology,foster easy access to the internet to ensure it is'elder-friendly',provide internet skill training platforms for this population and broaden access to various internet services appropriate for them.Additionally,the implementation of tailored interventions to address depression,especially targeting the more vulnerable cohorts,such as middle-aged and older women,those residing in rural areas and the western regions,is crucial.Such tailored approaches are essential for addressing the disparities and challenges associated with the triple digital divide.展开更多
With the promotion of digital currency,how to effectively solve the authenticity,privacy and usability of digital currency issuance has been a key problem.Redactable signature scheme(RSS)can provide the verification o...With the promotion of digital currency,how to effectively solve the authenticity,privacy and usability of digital currency issuance has been a key problem.Redactable signature scheme(RSS)can provide the verification of the integrity and source of the generated sub-documents and solve the privacy problem in digital currency by removing blocks from the signed documents.Unfortunately,it has not realized the consolidation of signed documents,which can not solve the problem of merging two digital currencies.Now,we introduce the concept of weight based on the threshold secret sharing scheme(TSSS)and present a redactable signature scheme with merge algorithm(RSS-MA)using the quasi-commutative accumulator.Our scheme can reduce the communication overhead by utilizing the merge algorithm when transmitting multiple digital currency signatures.Furthermore,this can effectively hide the scale of users’private monetary assets and the number of transactions between users.While meeting the three properties of digital currency issuance,in order to ensure the availability of digital currency after redacting,editors shall not remove the relevant identification information block form digital currency.Finally,our security proof and the analysis of efficiency show that RSS-MA greatly improves the communication and computation efficiency when transmitting multiple signatures.展开更多
The social transformation brought aboutby digital technology is deeply impacting various industries.Digital education products, with core technologiessuch as 5G, AI, IoT (Internet of Things),etc., are continuously pen...The social transformation brought aboutby digital technology is deeply impacting various industries.Digital education products, with core technologiessuch as 5G, AI, IoT (Internet of Things),etc., are continuously penetrating areas such as teaching,management, and evaluation. Apps, miniprograms,and emerging large-scale models are providingexcellent knowledge performance and flexiblecross-media output. However, they also exposerisks such as content discrimination and algorithmcommercialization. This paper conducts anevidence-based analysis of digital education productrisks from four dimensions: “digital resourcesinformationdissemination-algorithm design-cognitiveassessment”. It breaks through corresponding identificationtechnologies and, relying on the diverse characteristicsof governance systems, explores governancestrategies for digital education products from the threedomains of “regulators-developers-users”.展开更多
Reducing the control error is vital for high-fidelity digital and analog quantum operations.In superconducting circuits,one disagreeable error arises from the reflection of microwave signals due to impedance mismatch ...Reducing the control error is vital for high-fidelity digital and analog quantum operations.In superconducting circuits,one disagreeable error arises from the reflection of microwave signals due to impedance mismatch in the control chain.Here,we demonstrate a reflection cancelation method when considering that there are two reflection nodes on the control line.We propose to generate the pre-distortion pulse by passing the envelopes of the microwave signal through digital filters,which enables real-time reflection correction when integrated into the field-programmable gate array(FPGA).We achieve a reduction of single-qubit gate infidelity from 0.67%to 0.11%after eliminating microwave reflection.Real-time correction of microwave reflection paves the way for precise control and manipulation of the qubit state and would ultimately enhance the performance of algorithms and simulations executed on quantum processors.展开更多
Processing underwater digital images is critical in ocean engineering,biology,and environmental studies,focusing on challenges such as poor lighting,image de-scattering,and color restoration.Due to environmental condi...Processing underwater digital images is critical in ocean engineering,biology,and environmental studies,focusing on challenges such as poor lighting,image de-scattering,and color restoration.Due to environmental conditions on the sea floor,improving image contrast and clarity is essential for underwater navigation and obstacle avoidance.Particularly in turbid,low-visibility waters,we require robust computer vision techniques and algorithms.Over the past decade,various models for underwater image enrichment have been proposed to address quality and visibility issues under dynamic and natural lighting conditions.This research article aims to evaluate various image improvement methods and propose a robust model that improves image quality,addresses turbidity,and enhances color,ultimately improving obstacle avoidance in autonomous systems.The proposed model demonstrates high accuracy compared to traditional models.The result analysis indicates the proposed model produces images with greatly improved visibility and exceptional color accuracy.Furthermore,research can unlock new possibilities for underwater exploration,monitoring,and intervention by advancing the state-of-the-art models in this domain.展开更多
Digital twins and the physical assets of electric power systems face the potential risk of data loss and monitoring failures owing to catastrophic events,causing surveillance and energy loss.This study aims to refine ...Digital twins and the physical assets of electric power systems face the potential risk of data loss and monitoring failures owing to catastrophic events,causing surveillance and energy loss.This study aims to refine maintenance strategies for the monitoring of an electric power digital twin system post disasters.Initially,the research delineates the physical electric power system along with its digital counterpart and post-disaster restoration processes.Subsequently,it delves into communication and data processing mechanisms,specifically focusing on central data processing(CDP),communication routers(CRs),and phasor measurement units(PMUs),to re-establish an equipment recovery model based on these data transmission methodologies.Furthermore,it introduces a mathematical optimization model designed to enhance the digital twin system’s post-disaster monitoring efficacy by employing the branch-and-bound method for its resolution.The efficacy of the proposed model was corroborated by analyzing an IEEE-14 system.The findings suggest that the proposed branch-and-bound algorithm significantly augments the observational capabilities of a power system with limited resources,thereby bolstering its stability and emergency response mechanisms.展开更多
This paper presents a peer-to-peer community cost optimization approach based on a single-prosumer energy management system.Its objective is to optimize energy costs for prosumers in the community by enhancing the con...This paper presents a peer-to-peer community cost optimization approach based on a single-prosumer energy management system.Its objective is to optimize energy costs for prosumers in the community by enhancing the consumption efficiency.This study was conducted along two main axes.The first axis focuses on designing a digital twin for a residential community microgrid platform.This phase involves data collection,cleaning,exploration,and interpretation.Moreover,it includes replicating the functionality of the real platform and validating the results.The second axis involves the development of a novel approach that incorporates two distinct prosumer behaviors within the same community microgrid,while maintaining the concept of peer-to-peer energy trading.Prosumers without storage utilize their individual PV systems to fulfill their energy requirements and inject excess energy into a local microgrid.Meanwhile,a single prosumer with a storage system actively engages in energy exchange to maximize the community’s profit.This is achieved by optimizing battery usage using a cost optimization solution.The proposed solution is validated using the developed digital twin.展开更多
The rapid development of emerging technologies,such as edge intelligence and digital twins,have added momentum towards the development of the Industrial Internet of Things(IIo T).However,the massive amount of data gen...The rapid development of emerging technologies,such as edge intelligence and digital twins,have added momentum towards the development of the Industrial Internet of Things(IIo T).However,the massive amount of data generated by the IIo T,coupled with heterogeneous computation capacity across IIo T devices,and users’data privacy concerns,have posed challenges towards achieving industrial edge intelligence(IEI).To achieve IEI,in this paper,we propose a semi-federated learning framework where a portion of the data with higher privacy is kept locally and a portion of the less private data can be potentially uploaded to the edge server.In addition,we leverage digital twins to overcome the problem of computation capacity heterogeneity of IIo T devices through the mapping of physical entities.We formulate a synchronization latency minimization problem which jointly optimizes edge association and the proportion of uploaded nonprivate data.As the joint problem is NP-hard and combinatorial and taking into account the reality of largescale device training,we develop a multi-agent hybrid action deep reinforcement learning(DRL)algorithm to find the optimal solution.Simulation results show that our proposed DRL algorithm can reduce latency and have a better convergence performance for semi-federated learning compared to benchmark algorithms.展开更多
Accurate and efficient online parameter identification and state estimation are crucial for leveraging digital twin simulations to optimize the operation of near-carbon-free nuclear energy systems.In previous studies,...Accurate and efficient online parameter identification and state estimation are crucial for leveraging digital twin simulations to optimize the operation of near-carbon-free nuclear energy systems.In previous studies,we developed a reactor operation digital twin(RODT).However,non-differentiabilities and discontinuities arise when employing machine learning-based surrogate forward models,challenging traditional gradient-based inverse methods and their variants.This study investigated deterministic and metaheuristic algorithms and developed hybrid algorithms to address these issues.An efficient modular RODT software framework that incorporates these methods into its post-evaluation module is presented for comprehensive comparison.The methods were rigorously assessed based on convergence profiles,stability with respect to noise,and computational performance.The numerical results show that the hybrid KNNLHS algorithm excels in real-time online applications,balancing accuracy and efficiency with a prediction error rate of only 1%and processing times of less than 0.1 s.Contrastingly,algorithms such as FSA,DE,and ADE,although slightly slower(approximately 1 s),demonstrated higher accuracy with a 0.3%relative L_2 error,which advances RODT methodologies to harness machine learning and system modeling for improved reactor monitoring,systematic diagnosis of off-normal events,and lifetime management strategies.The developed modular software and novel optimization methods presented offer pathways to realize the full potential of RODT for transforming energy engineering practices.展开更多
The rise in breast cancer diagnoses among Chinese women has necessitated the use of X-ray breast screening,which carries a radiation risk.This study aimed to provide a dosimetry protocol for the Chinese female populat...The rise in breast cancer diagnoses among Chinese women has necessitated the use of X-ray breast screening,which carries a radiation risk.This study aimed to provide a dosimetry protocol for the Chinese female population to replace the traditional standard that utilizes simplified breast models,for the accurate estimation of the mean glandular dose of a patient undergoing digital breast tomosynthesis(DBT).The first set of detailed Chinese female breast models and representative breast parameters was constructed.Considering backscatter radiation and computational efficiency,we improved the combination of these models and the Chinese reference adult female whole-body voxel phantom.Image acquisition for four commercial DBT systems that are widely employed in China was simulated using the Monte Carlo method to obtain the normalized glandular dose coefficients of DBT(D_(gN)^(DBT))and the glandular depth dose(D_(g)^(dep)(z))for different breast characteristics and X-ray spectra.We calculated a series of D_(gN)^(DBT) values for breasts with different percentage mass glandularities(5%,25%,50%,75%,and 100%)and compressed breast thicknesses(2,3,4,5,6,and 7 cm)at various tube potentials(25,28,30,32,35,and 49 kV)and target/filter combinations(W/Rh,W/Al,Mo/Mo,Rh/Rh,and Rh/Ag).The parameter dependence of the breast characteristics and beam conditions on D_(gN)^(DBT) in detailed breast models was investigated.The D_(gN)^(DBT) results were 14.6-51.0%lower than those of the traditional dosimetry standard in China.The difference in D_(gN)^(DBT) was mainly due to a decrease in the depth of the main energy deposition area caused by the glandular distribution along the depth direction.The results obtained in this study may be used to improve breast dosimetry in China and provide more detailed information on risk assessment during DBT.展开更多
Zinc ion batteries are considered as potential energy storage devices due to their advantages of low-cost,high-safety,and high theoretical capacity.However,dendrite growth and chemical corrosion occurring on Zn anode ...Zinc ion batteries are considered as potential energy storage devices due to their advantages of low-cost,high-safety,and high theoretical capacity.However,dendrite growth and chemical corrosion occurring on Zn anode limit their commercialization.These problems can be tackled through the optimization of the electrolyte.However,the screening of electrolyte additives using normal electrochemical methods is time-consuming and labor-intensive.Herein,a fast and simple method based on the digital holography is developed.It can realize the in situ monitoring of electrode/electrolyte interface and provide direct information concerning ion concentration evolution of the diffusion layer.It is effective and time-saving in estimating the homogeneity of the deposition layer and predicting the tendency of dendrite growth,thus able to value the applicability of electrolyte additives.The feasibility of this method is further validated by the forecast and evaluation of thioacetamide additive.Based on systematic characterization,it is proved that the introduction of thioacetamide can not only regulate the interficial ion flux to induce dendrite-free Zn deposition,but also construct adsorption molecule layers to inhibit side reactions of Zn anode.Being easy to operate,capable of in situ observation,and able to endure harsh conditions,digital holography method will be a promising approach for the interfacial investigation of other battery systems.展开更多
An emerging railway technology called smart railway promises to deliver higher transportation efficiency,enhanced comfort in services,and greater eco-friendliness.The smart railway is expected to integrate fifth-gener...An emerging railway technology called smart railway promises to deliver higher transportation efficiency,enhanced comfort in services,and greater eco-friendliness.The smart railway is expected to integrate fifth-generation mobile communication(5G),Artificial Intelligence(AI),and other technologies,which poses new problems in the construction,operation and maintenance of railway wireless networks.Wireless Digital Twins(DTs),which have recently emerged as a new paradigm for the design of wireless networks,can address these problems and enable the whole lifecycle management of railway wireless networks.However,there are still many scientific issues and challenges for railway-oriented wireless DT.Relevant key technologies to solve these problems are introduced and described,including characterization of materials'physical-EM properties,autonomous reconstruction of Three-dimensional(3D)environment model,AI-empowered environmental cognition,Ray-Tracing(RT),model-based and AIbased RT acceleration,and generation of multi-spectra sensing data.Moreover,this paper presents our research results for each key technology and describes the wireless network planning and optimization system based on highperformance RT developed by our laboratory.This paper outlines the framework for realizing the wireless DT of smart railways,providing the direction for future research.展开更多
In spacecraft electronic devices,the deformation of solder balls within ball grid array(BGA)packages poses a significant risk of system failure.Therefore,accurately measuring the mechanical behavior of solder balls is...In spacecraft electronic devices,the deformation of solder balls within ball grid array(BGA)packages poses a significant risk of system failure.Therefore,accurately measuring the mechanical behavior of solder balls is crucial for ensuring the safety and reliability of spacecraft.Although finite element simulations have been extensively used to study solder ball deformation,there is a significant lack of experimental validation,particularly under thermal cycling conditions.This is due to the challenges in accurately measuring the internal deformations of solder balls and eliminating the rigid body displacement introduced during ex-situ thermal cycling tests.In this work,an ex-situ three-dimensional deformation measurement method using X-ray computed tomography(CT)and digital volume correlation(DVC)is proposed to overcome these obstacles.By incorporating the layer-wise reliability-guided displacement tracking(LW-RGDT)DVC with a singular value decomposition(SVD)method,this method enables accurate assessment of solder ball mechanical behavior in BGA packages without the influence of rigid body displacement.Experimental results reveal that BGA structures exhibit progressive convex deformation with increased thermal cycling,particularly in peripheral solder balls.This method provides a reliable and effective tool for assessing internal deformations in electronic packages under ex-situ conditions,which is crucial for their design optimization and lifespan predictions.展开更多
Method of testing for dynamic output forces from jet elements is studied, the handwidth is large in testing with this method. By establishing a model of the test system and simulating it, principles of how inherent fe...Method of testing for dynamic output forces from jet elements is studied, the handwidth is large in testing with this method. By establishing a model of the test system and simulating it, principles of how inherent features of the test system affect the dynamic force test are found out. Thus a theoretical foundation is given for the design and error modification to the actual test system.展开更多
The sinusoid curve fit is widely applied in the evaluation of digitized measurement equipment, such as data acquisition system, digital storage oscilloscope, waveform recorder and A/D converter,etc. Because of the di...The sinusoid curve fit is widely applied in the evaluation of digitized measurement equipment, such as data acquisition system, digital storage oscilloscope, waveform recorder and A/D converter,etc. Because of the distortion and noise of sinusoid signal generator, the digitizing and the non linearity errors in measurement, it is impossible to avoid the distortion and the noise in sinusoid sampling series. The distortion and the noise limit the accuracy of curve fit results. Therefore, it is desirable to find a filter that can filter out both distortion and noise of the sinusoid sampling series, and in the meantime, the filter doesn′t influence the amplitude, the frequency, the phase and DC bias of fitting curve of the sine wave. And then, the uncertainty of fitting parameter can be reduced. This filter is designed and realized. Its realization in time domain is described and its transfer function in frequency domain is presented.展开更多
基金supported in part by the National Natural Science Foundation of China(NSFC)under Grant Nos.62171085,62272428,62001087,U20A20156,and 61871097the ZTE Industry-University-Institute Cooperation Funds under Grant No.HC-CN-20220722010。
文摘The proliferation of heterogeneous networks,such as the Internet of Things(IoT),unmanned aerial vehicle(UAV)networks,and edge networks,has increased the complexity of network operation and administration,driving the emergence of digital twin networks(DTNs)that create digital-physical network mappings.While DTNs enable performance analysis through emulation testbeds,current research focuses on network-level systems,neglecting equipment-level emulation of critical components like core switches and routers.To address this issue,we propose v Fabric(short for virtual switch),a digital twin emulator for high-capacity core switching equipment.This solution implements virtual switching and network processor(NP)chip models through specialized processes,deployable on single or distributed servers via socket communication.The v Fabric emulator can realize the accurate emulation for the core switching equipment with 720 ports and 100 Gbit/s per port on the largest scale.To our knowledge,this represents the first digital twin emulation framework specifically designed for large-capacity core switching equipment in communication networks.
基金financially supported by the National Key Research and Development Program of China (No.2020YFA0711800)the National Science Fund for Distinguished Young Scholars (No.51925404)+2 种基金the Graduate Innovation Program of China University of Mining and Technology (No.2023WLKXJ149)the Fundamental Research Funds for the Central Universities (No.2023XSCX040)the Postgraduate Research Practice Innovation Program of Jiangsu Province (No.KYCX23_2864)。
文摘Methane in-situ explosive fracturing technology produces shale debris particles within fracture channels,enabling a self-propping effect that enhances the fracture network conductivity and long-term stability.This study employs X-ray computed tomography(CT)and digital volume correlation(DVC)to investigate the microstructural evolution and hydromechanical responses of shale self-propped fracture under varying confining pressures,highlighting the critical role of shale particles in maintaining fracture conductivity.Results indicate that the fracture aperture in the self-propped sample is significantly larger than in the unpropped sample throughout the loading process,with shale particles tending to crush rather than embedded into the matrix,thus maintaining flow pathways.As confining pressure increases,contact areas between fracture surfaces and particles expand,enhancing the system's stability and compressive resistance.Geometric analyses show flow paths becoming increasingly concentrated and branched under high stress.This resulted in a significant reduction in connectivity,restricting fracture permeability and amplifying the nonlinear gas flow behavior.This study introduces a permeability-strain recovery zone and a novel sensitivity parameter m,delineating stress sensitivity boundaries for permeability and normal strain,with m-value increasing with stress,revealing four characteristic regions.These findings offer theoretical support for optimizing fracturing techniques to enhance resource extraction efficiency.
基金supported by ZTE Industry-University-Institute Cooperation Funds under Grant No.HC-CN-20220722010。
文摘This paper proposes a concurrent neural network model to mitigate non-linear distortion in power amplifiers using a basis function generation approach.The model is designed using polynomial expansion and comprises a feedforward neural network(FNN)and a convolutional neural network(CNN).The proposed model takes the basic elements that form the bases as input,defined by the generalized memory polynomial(GMP)and dynamic deviation reduction(DDR)models.The FNN generates the basis function and its output represents the basis values,while the CNN generates weights for the corresponding bases.Through the concurrent training of FNN and CNN,the hidden layer coefficients are updated,and the complex multiplication of their outputs yields the trained in-phase/quadrature(I/Q)signals.The proposed model was trained and tested using 300 MHz and 400 MHz broadband data in an orthogonal frequency division multiplexing(OFDM)communication system.The results show that the model achieves an adjacent channel power ratio(ACPR)of less than-48 d B within a 100 MHz integral bandwidth for both the training and test datasets.
基金This work was supported by the National Key R&D Program of China(Nos.2023YFA1606403 and 2023YFE0101600)the National Natural Science Foundation of China(Nos.12027809,11961141003,U1967201,11875073 and 11875074).
文摘A digital data-acquisition system based on XIA LLC products was used in a complex nuclear reaction experiment using radioactive ion beams.A flexible trigger system based on a field-programmable gate array(FPGA)parametrization was developed to adapt to different experimental sizes.A user-friendly interface was implemented,which allows converting script language expressions into FPGA internal control parameters.The proposed digital system can be combined with a conventional analog data acquisition system to provide more flexibility.The performance of the combined system was veri-fied using experimental data.
基金supported by the National Postdoctoral Researcher Program(GZC20231325).
文摘Background The triple digital divide refers to the lack of internet access,use and knowledge among specific populations.In China,middle-aged and older adults and those living in rural areas or various regions of the country are more likely to have limited internet access and skills and,thus,have less accessibility to internet services.Few longitudinal studies have explored the association between the digital divide and the progression of depressive symptoms among middle-aged and older Chinese adults.Significantly,none of the existing studies have estimated this long-term relationship from a disparity perspective.Aims This study investigates the association between the triple digital divide and depressive symptom trajectories among middle-aged and older adults in China during a 10-year follow-up period from 2011 to 2020.Methods The sample for this secondary analysis comprises 3019 urban and 10427 rural respondents selected from the China Health and Retirement Longitudinal Study baseline survey in 2011.Depressive symptoms were measured using the Center for Epidemiologic Studies Depression Scale.Employing longitudinal mixed-effects models,this study explored the association between the triple digital divide and depressive symptom trajectories among middle-aged and older Chinese adults by examining gender,rural-urban and regional disparities in this relationship.Results Our findings revealed a significant association between the triple digital divide and increasing trajectories of depressive symptoms,showing significant disparities based on gender,rural-urban dwelling and regional location.Notably,for both male and female participants who resided in urban areas or the central region of the country,their ability to use the internet,coupled with enhanced internet skills and greater access to internet services,was found to have a mitigating effect on the increasing trajectories of depressive symptoms.Conclusions To alleviate some of the confounding influences on the trajectory of depression in middle-aged and older adults,policymakers in China should continue to prioritise the development of internet technology,foster easy access to the internet to ensure it is'elder-friendly',provide internet skill training platforms for this population and broaden access to various internet services appropriate for them.Additionally,the implementation of tailored interventions to address depression,especially targeting the more vulnerable cohorts,such as middle-aged and older women,those residing in rural areas and the western regions,is crucial.Such tailored approaches are essential for addressing the disparities and challenges associated with the triple digital divide.
基金supported by Support Plan of Scientific and Technological Innovation Team in Universities of Henan Province(20IRTSTHN013)Shaanxi Key Laboratory of Information Communication Network and Security,Xi’an University of Posts&Telecommunications,Xi’an,Shaanxi 710121,China(ICNS202006)The National Natural Science Fund(No.61802117).
文摘With the promotion of digital currency,how to effectively solve the authenticity,privacy and usability of digital currency issuance has been a key problem.Redactable signature scheme(RSS)can provide the verification of the integrity and source of the generated sub-documents and solve the privacy problem in digital currency by removing blocks from the signed documents.Unfortunately,it has not realized the consolidation of signed documents,which can not solve the problem of merging two digital currencies.Now,we introduce the concept of weight based on the threshold secret sharing scheme(TSSS)and present a redactable signature scheme with merge algorithm(RSS-MA)using the quasi-commutative accumulator.Our scheme can reduce the communication overhead by utilizing the merge algorithm when transmitting multiple digital currency signatures.Furthermore,this can effectively hide the scale of users’private monetary assets and the number of transactions between users.While meeting the three properties of digital currency issuance,in order to ensure the availability of digital currency after redacting,editors shall not remove the relevant identification information block form digital currency.Finally,our security proof and the analysis of efficiency show that RSS-MA greatly improves the communication and computation efficiency when transmitting multiple signatures.
基金supported by the 2022 National Natural Science Foundation of China(No.62277002)the National Key Research and Development Program of China(2022YFC3303500).
文摘The social transformation brought aboutby digital technology is deeply impacting various industries.Digital education products, with core technologiessuch as 5G, AI, IoT (Internet of Things),etc., are continuously penetrating areas such as teaching,management, and evaluation. Apps, miniprograms,and emerging large-scale models are providingexcellent knowledge performance and flexiblecross-media output. However, they also exposerisks such as content discrimination and algorithmcommercialization. This paper conducts anevidence-based analysis of digital education productrisks from four dimensions: “digital resourcesinformationdissemination-algorithm design-cognitiveassessment”. It breaks through corresponding identificationtechnologies and, relying on the diverse characteristicsof governance systems, explores governancestrategies for digital education products from the threedomains of “regulators-developers-users”.
基金the National Natural Science Foun-dation of China(Grant Nos.12034018 and 11625419).
文摘Reducing the control error is vital for high-fidelity digital and analog quantum operations.In superconducting circuits,one disagreeable error arises from the reflection of microwave signals due to impedance mismatch in the control chain.Here,we demonstrate a reflection cancelation method when considering that there are two reflection nodes on the control line.We propose to generate the pre-distortion pulse by passing the envelopes of the microwave signal through digital filters,which enables real-time reflection correction when integrated into the field-programmable gate array(FPGA).We achieve a reduction of single-qubit gate infidelity from 0.67%to 0.11%after eliminating microwave reflection.Real-time correction of microwave reflection paves the way for precise control and manipulation of the qubit state and would ultimately enhance the performance of algorithms and simulations executed on quantum processors.
文摘Processing underwater digital images is critical in ocean engineering,biology,and environmental studies,focusing on challenges such as poor lighting,image de-scattering,and color restoration.Due to environmental conditions on the sea floor,improving image contrast and clarity is essential for underwater navigation and obstacle avoidance.Particularly in turbid,low-visibility waters,we require robust computer vision techniques and algorithms.Over the past decade,various models for underwater image enrichment have been proposed to address quality and visibility issues under dynamic and natural lighting conditions.This research article aims to evaluate various image improvement methods and propose a robust model that improves image quality,addresses turbidity,and enhances color,ultimately improving obstacle avoidance in autonomous systems.The proposed model demonstrates high accuracy compared to traditional models.The result analysis indicates the proposed model produces images with greatly improved visibility and exceptional color accuracy.Furthermore,research can unlock new possibilities for underwater exploration,monitoring,and intervention by advancing the state-of-the-art models in this domain.
基金supported by the State Grid Jilin Province Electric Power Co,Ltd-Research and Application of Power Grid Resilience Assessment and Coordinated Emergency Technology of Supply and Network for the Development of New Power System in Alpine Region(Project Number is B32342210001).
文摘Digital twins and the physical assets of electric power systems face the potential risk of data loss and monitoring failures owing to catastrophic events,causing surveillance and energy loss.This study aims to refine maintenance strategies for the monitoring of an electric power digital twin system post disasters.Initially,the research delineates the physical electric power system along with its digital counterpart and post-disaster restoration processes.Subsequently,it delves into communication and data processing mechanisms,specifically focusing on central data processing(CDP),communication routers(CRs),and phasor measurement units(PMUs),to re-establish an equipment recovery model based on these data transmission methodologies.Furthermore,it introduces a mathematical optimization model designed to enhance the digital twin system’s post-disaster monitoring efficacy by employing the branch-and-bound method for its resolution.The efficacy of the proposed model was corroborated by analyzing an IEEE-14 system.The findings suggest that the proposed branch-and-bound algorithm significantly augments the observational capabilities of a power system with limited resources,thereby bolstering its stability and emergency response mechanisms.
基金supported by the Tunisian Ministry of Higher Education and Scientific Research under Grant LSE-ENIT-LR 11ES15funded in part by the PAQ-Collabora(PAR&I-Tk)program。
文摘This paper presents a peer-to-peer community cost optimization approach based on a single-prosumer energy management system.Its objective is to optimize energy costs for prosumers in the community by enhancing the consumption efficiency.This study was conducted along two main axes.The first axis focuses on designing a digital twin for a residential community microgrid platform.This phase involves data collection,cleaning,exploration,and interpretation.Moreover,it includes replicating the functionality of the real platform and validating the results.The second axis involves the development of a novel approach that incorporates two distinct prosumer behaviors within the same community microgrid,while maintaining the concept of peer-to-peer energy trading.Prosumers without storage utilize their individual PV systems to fulfill their energy requirements and inject excess energy into a local microgrid.Meanwhile,a single prosumer with a storage system actively engages in energy exchange to maximize the community’s profit.This is achieved by optimizing battery usage using a cost optimization solution.The proposed solution is validated using the developed digital twin.
基金supported in part by the National Nature Science Foundation of China under Grant 62001168in part by the Foundation and Application Research Grant of Guangzhou under Grant 202102020515。
文摘The rapid development of emerging technologies,such as edge intelligence and digital twins,have added momentum towards the development of the Industrial Internet of Things(IIo T).However,the massive amount of data generated by the IIo T,coupled with heterogeneous computation capacity across IIo T devices,and users’data privacy concerns,have posed challenges towards achieving industrial edge intelligence(IEI).To achieve IEI,in this paper,we propose a semi-federated learning framework where a portion of the data with higher privacy is kept locally and a portion of the less private data can be potentially uploaded to the edge server.In addition,we leverage digital twins to overcome the problem of computation capacity heterogeneity of IIo T devices through the mapping of physical entities.We formulate a synchronization latency minimization problem which jointly optimizes edge association and the proportion of uploaded nonprivate data.As the joint problem is NP-hard and combinatorial and taking into account the reality of largescale device training,we develop a multi-agent hybrid action deep reinforcement learning(DRL)algorithm to find the optimal solution.Simulation results show that our proposed DRL algorithm can reduce latency and have a better convergence performance for semi-federated learning compared to benchmark algorithms.
基金supported by the Natural Science Foundation of Shanghai(No.23ZR1429300)Innovation Funds of CNNC(Lingchuang Fund,Contract No.CNNC-LCKY-202234)the Project of the Nuclear Power Technology Innovation Center of Science Technology and Industry(No.HDLCXZX-2023-HD-039-02)。
文摘Accurate and efficient online parameter identification and state estimation are crucial for leveraging digital twin simulations to optimize the operation of near-carbon-free nuclear energy systems.In previous studies,we developed a reactor operation digital twin(RODT).However,non-differentiabilities and discontinuities arise when employing machine learning-based surrogate forward models,challenging traditional gradient-based inverse methods and their variants.This study investigated deterministic and metaheuristic algorithms and developed hybrid algorithms to address these issues.An efficient modular RODT software framework that incorporates these methods into its post-evaluation module is presented for comprehensive comparison.The methods were rigorously assessed based on convergence profiles,stability with respect to noise,and computational performance.The numerical results show that the hybrid KNNLHS algorithm excels in real-time online applications,balancing accuracy and efficiency with a prediction error rate of only 1%and processing times of less than 0.1 s.Contrastingly,algorithms such as FSA,DE,and ADE,although slightly slower(approximately 1 s),demonstrated higher accuracy with a 0.3%relative L_2 error,which advances RODT methodologies to harness machine learning and system modeling for improved reactor monitoring,systematic diagnosis of off-normal events,and lifetime management strategies.The developed modular software and novel optimization methods presented offer pathways to realize the full potential of RODT for transforming energy engineering practices.
基金supported by the National Natural Science Foundation of China(Nos.U2167209 and 12175114)the National Key R&D Program of China(No.2021YFF0603600).
文摘The rise in breast cancer diagnoses among Chinese women has necessitated the use of X-ray breast screening,which carries a radiation risk.This study aimed to provide a dosimetry protocol for the Chinese female population to replace the traditional standard that utilizes simplified breast models,for the accurate estimation of the mean glandular dose of a patient undergoing digital breast tomosynthesis(DBT).The first set of detailed Chinese female breast models and representative breast parameters was constructed.Considering backscatter radiation and computational efficiency,we improved the combination of these models and the Chinese reference adult female whole-body voxel phantom.Image acquisition for four commercial DBT systems that are widely employed in China was simulated using the Monte Carlo method to obtain the normalized glandular dose coefficients of DBT(D_(gN)^(DBT))and the glandular depth dose(D_(g)^(dep)(z))for different breast characteristics and X-ray spectra.We calculated a series of D_(gN)^(DBT) values for breasts with different percentage mass glandularities(5%,25%,50%,75%,and 100%)and compressed breast thicknesses(2,3,4,5,6,and 7 cm)at various tube potentials(25,28,30,32,35,and 49 kV)and target/filter combinations(W/Rh,W/Al,Mo/Mo,Rh/Rh,and Rh/Ag).The parameter dependence of the breast characteristics and beam conditions on D_(gN)^(DBT) in detailed breast models was investigated.The D_(gN)^(DBT) results were 14.6-51.0%lower than those of the traditional dosimetry standard in China.The difference in D_(gN)^(DBT) was mainly due to a decrease in the depth of the main energy deposition area caused by the glandular distribution along the depth direction.The results obtained in this study may be used to improve breast dosimetry in China and provide more detailed information on risk assessment during DBT.
基金supported by the National Natural Science Foundation of China(No.22075115)Natural Science Foundation of Jiangsu Province(No.BK20211352)+2 种基金Joint Funds of the National Natural Science Foundation of China(No.U2141201)Natural Science Foundation(No.22KJA430005)of Jiangsu Education Committee of ChinaPostgraduate Research and Practice Innovation Program of Jiangsu Normal University(No.2021XKT0296).
文摘Zinc ion batteries are considered as potential energy storage devices due to their advantages of low-cost,high-safety,and high theoretical capacity.However,dendrite growth and chemical corrosion occurring on Zn anode limit their commercialization.These problems can be tackled through the optimization of the electrolyte.However,the screening of electrolyte additives using normal electrochemical methods is time-consuming and labor-intensive.Herein,a fast and simple method based on the digital holography is developed.It can realize the in situ monitoring of electrode/electrolyte interface and provide direct information concerning ion concentration evolution of the diffusion layer.It is effective and time-saving in estimating the homogeneity of the deposition layer and predicting the tendency of dendrite growth,thus able to value the applicability of electrolyte additives.The feasibility of this method is further validated by the forecast and evaluation of thioacetamide additive.Based on systematic characterization,it is proved that the introduction of thioacetamide can not only regulate the interficial ion flux to induce dendrite-free Zn deposition,but also construct adsorption molecule layers to inhibit side reactions of Zn anode.Being easy to operate,capable of in situ observation,and able to endure harsh conditions,digital holography method will be a promising approach for the interfacial investigation of other battery systems.
基金supported by Beijing Natural Science Foundation(L212029,L221009)the National Natural Science Foundation of China(62271043,62371033)the Ministry of Education of China(8091B032123).
文摘An emerging railway technology called smart railway promises to deliver higher transportation efficiency,enhanced comfort in services,and greater eco-friendliness.The smart railway is expected to integrate fifth-generation mobile communication(5G),Artificial Intelligence(AI),and other technologies,which poses new problems in the construction,operation and maintenance of railway wireless networks.Wireless Digital Twins(DTs),which have recently emerged as a new paradigm for the design of wireless networks,can address these problems and enable the whole lifecycle management of railway wireless networks.However,there are still many scientific issues and challenges for railway-oriented wireless DT.Relevant key technologies to solve these problems are introduced and described,including characterization of materials'physical-EM properties,autonomous reconstruction of Three-dimensional(3D)environment model,AI-empowered environmental cognition,Ray-Tracing(RT),model-based and AIbased RT acceleration,and generation of multi-spectra sensing data.Moreover,this paper presents our research results for each key technology and describes the wireless network planning and optimization system based on highperformance RT developed by our laboratory.This paper outlines the framework for realizing the wireless DT of smart railways,providing the direction for future research.
文摘In spacecraft electronic devices,the deformation of solder balls within ball grid array(BGA)packages poses a significant risk of system failure.Therefore,accurately measuring the mechanical behavior of solder balls is crucial for ensuring the safety and reliability of spacecraft.Although finite element simulations have been extensively used to study solder ball deformation,there is a significant lack of experimental validation,particularly under thermal cycling conditions.This is due to the challenges in accurately measuring the internal deformations of solder balls and eliminating the rigid body displacement introduced during ex-situ thermal cycling tests.In this work,an ex-situ three-dimensional deformation measurement method using X-ray computed tomography(CT)and digital volume correlation(DVC)is proposed to overcome these obstacles.By incorporating the layer-wise reliability-guided displacement tracking(LW-RGDT)DVC with a singular value decomposition(SVD)method,this method enables accurate assessment of solder ball mechanical behavior in BGA packages without the influence of rigid body displacement.Experimental results reveal that BGA structures exhibit progressive convex deformation with increased thermal cycling,particularly in peripheral solder balls.This method provides a reliable and effective tool for assessing internal deformations in electronic packages under ex-situ conditions,which is crucial for their design optimization and lifespan predictions.
文摘Method of testing for dynamic output forces from jet elements is studied, the handwidth is large in testing with this method. By establishing a model of the test system and simulating it, principles of how inherent features of the test system affect the dynamic force test are found out. Thus a theoretical foundation is given for the design and error modification to the actual test system.
文摘The sinusoid curve fit is widely applied in the evaluation of digitized measurement equipment, such as data acquisition system, digital storage oscilloscope, waveform recorder and A/D converter,etc. Because of the distortion and noise of sinusoid signal generator, the digitizing and the non linearity errors in measurement, it is impossible to avoid the distortion and the noise in sinusoid sampling series. The distortion and the noise limit the accuracy of curve fit results. Therefore, it is desirable to find a filter that can filter out both distortion and noise of the sinusoid sampling series, and in the meantime, the filter doesn′t influence the amplitude, the frequency, the phase and DC bias of fitting curve of the sine wave. And then, the uncertainty of fitting parameter can be reduced. This filter is designed and realized. Its realization in time domain is described and its transfer function in frequency domain is presented.
