A method for correlating thermal light over a wide spectral range is proposed.A multi-wavelength pseudothermal source,prepared by projecting laser beams of multiple wavelengths(650 nm,635 nm,532 nm,and 473 nm)onto a m...A method for correlating thermal light over a wide spectral range is proposed.A multi-wavelength pseudothermal source,prepared by projecting laser beams of multiple wavelengths(650 nm,635 nm,532 nm,and 473 nm)onto a moving thin ground glass plate,is employed in a double-slit interference experiment.The ground glass plate induces random phase differences between light beams of different wavelengths passing through it.This initial random phase difference significantly influences the high-order intensity correlation functions of multi-wavelength thermal beams.Experimentally,second-order correlated interference patterns,including subwavelength interference,of pseudothermal beams with different wavelengths are observed in the intensity correlation measurements.This method facilitates applications of correlated thermal photons in quantum information processing and quantum imaging.展开更多
Discriminative region localization and efficient feature encoding are crucial for fine-grained object recognition.However,existing data augmentation methods struggle to accurately locate discriminative regions in comp...Discriminative region localization and efficient feature encoding are crucial for fine-grained object recognition.However,existing data augmentation methods struggle to accurately locate discriminative regions in complex backgrounds,small target objects,and limited training data,leading to poor recognition.Fine-grained images exhibit“small inter-class differences,”and while second-order feature encoding enhances discrimination,it often requires dual Convolutional Neural Networks(CNN),increasing training time and complexity.This study proposes a model integrating discriminative region localization and efficient second-order feature encoding.By ranking feature map channels via a fully connected layer,it selects high-importance channels to generate an enhanced map,accurately locating discriminative regions.Cropping and erasing augmentations further refine recognition.To improve efficiency,a novel second-order feature encoding module generates an attention map from the fourth convolutional group of Residual Network 50 layers(ResNet-50)and multiplies it with features from the fifth group,producing second-order features while reducing dimensionality and training time.Experiments on Caltech-University of California,San Diego Birds-200-2011(CUB-200-2011),Stanford Car,and Fine-Grained Visual Classification of Aircraft(FGVC Aircraft)datasets show state-of-the-art accuracy of 88.9%,94.7%,and 93.3%,respectively.展开更多
This paper presents a study on the motion response of a tension-leg platform(TLP) under first-and second-order wave forces, including the mean-drift force, difference and sum-frequency forces. The second-order wave fo...This paper presents a study on the motion response of a tension-leg platform(TLP) under first-and second-order wave forces, including the mean-drift force, difference and sum-frequency forces. The second-order wave force is calculated using the full-field quadratic transfer function(QTF). The coupled effect of the horizontal motions, such as surge, sway and yaw motions, and the set-down motion are taken into consideration by the nonlinear restoring matrix. The time-domain analysis with 50-yr random sea state is performed. A comparison of the results of different case studies is made to assess the influence of second-order wave force on the motions of the platform. The analysis shows that the second-order wave force has a major impact on motions of the TLP. The second-order difference-frequency wave force has an obvious influence on the low-frequency motions of surge and sway, and also will induce a large set-down motion which is an important part of heave motion. Besides, the second-order sum-frequency force will induce a set of high-frequency motions of roll and pitch. However, little influence of second-order wave force is found on the yaw motion.展开更多
In recent years,the study of higher-order topological states and their material realizations has become a research frontier in topological condensed matter physics.We demonstrate that twisted bilayer graphene with sma...In recent years,the study of higher-order topological states and their material realizations has become a research frontier in topological condensed matter physics.We demonstrate that twisted bilayer graphene with small twist angles behaves as a second-order topological insulator possessing topological corner charges.Using a tight-binding model,we compute the topological band indices and corner states of finite-sized twisted bilayer graphene flakes.It is found that for any small twist angle,whether commensurate or incommensurate,the gaps both below and above the flat bands are associated with nontrivial topological indices.Our results not only extend the concept of second-order band topology to arbitrary small twist angles but also confirm the existence of corner states at acute-angle corners.展开更多
Continuous control protocols are extensively utilized in traditional MASs,in which information needs to be transmitted among agents consecutively,therefore resulting in excessive consumption of limited resources.To de...Continuous control protocols are extensively utilized in traditional MASs,in which information needs to be transmitted among agents consecutively,therefore resulting in excessive consumption of limited resources.To decrease the control cost,based on ISC,several LFC problems are investigated for second-order MASs without and with time delay,respectively.Firstly,an intermittent sampled controller is designed,and a sufficient and necessary condition is derived,under which state errors between the leader and all the followers approach zero asymptotically.Considering that time delay is inevitable,a new protocol is proposed to deal with the time-delay situation.The error system’s stability is analyzed using the Schur stability theorem,and sufficient and necessary conditions for LFC are obtained,which are closely associated with the coupling gain,the system parameters,and the network structure.Furthermore,for the case where the current position and velocity information are not available,a distributed protocol is designed that depends only on the sampled position information.The sufficient and necessary conditions for LFC are also given.The results show that second-order MASs can achieve the LFC if and only if the system parameters satisfy the inequalities proposed in the paper.Finally,the correctness of the obtained results is verified by numerical simulations.展开更多
In this paper,we investigate the phenomena of electromagnetically induced transparency and the generation of second-order sideband in a Laguerre–Gaussian cavity optorotational system with a Kerr nonlinear medium.Usin...In this paper,we investigate the phenomena of electromagnetically induced transparency and the generation of second-order sideband in a Laguerre–Gaussian cavity optorotational system with a Kerr nonlinear medium.Using the perturbation method,we analyze the first-and second-order sideband generations in the output field from the system under the actions of a strong control field and a weak probe field.Numerical simulations show that the Kerr nonlinearity can lead to the occurrence of the asymmetric line shape in the transmission of the probe field.Comparing with traditional scheme for generating the second-order sideband,our spectral shape of the second-order sideband is amplified and becomes asymmetric,which has potential applications in precision measurement,high-sensitivity devices,and frequency conversion.展开更多
The stabilization problem of second-order bilinear systems with time delay is investigated.Feedback controls are chosen so that the strong and exponential stabilization of the system is ensured.The obtained results ar...The stabilization problem of second-order bilinear systems with time delay is investigated.Feedback controls are chosen so that the strong and exponential stabilization of the system is ensured.The obtained results are illustrated by wave and beam equations with simulation.展开更多
This research,based on Mason's formula,proposes a novel design for a second-order transconductance-mode universal filter with the operational transconductance amplifier(OTA)as the core and the second-generation cu...This research,based on Mason's formula,proposes a novel design for a second-order transconductance-mode universal filter with the operational transconductance amplifier(OTA)as the core and the second-generation current-controlled conveyor(CCCⅡ)as the auxiliary.The circuit incorporates two OTAs,one CCCⅡ,two grounded capacitors,and one grounded resistor.The quality factor Q and natural frequency fo of the filter can be electronically tuned and are not sensitive to temperature.The input and output terminals of the cir-cuit exhibit no loading effect,and the sensitivity of the circuit is low.At last,alternating frequency analysis,parameter scanning analysis,and temperature scanning analysis have been carried out by using Multisim software,confirming the correctness and effectiveness of the designed circuit.展开更多
The automatic loading systems of artillery are critical for the accurate,efficient,and reliable delivery of pro-jectiles and propellants into the gun chamber.In modern artillery,the ammunition conveyor serves as the e...The automatic loading systems of artillery are critical for the accurate,efficient,and reliable delivery of pro-jectiles and propellants into the gun chamber.In modern artillery,the ammunition conveyor serves as the end effector of the automatic loading system,and its motion state significantly impacts the accuracy of projectiles.Therefore,it is of immense importance to precisely and effectively evaluate the reliability of the motion accuracy of the ammunition conveyor.This paper aims to propose a practical and efficient analysis method for evaluating the reliability of the motion accuracy of the ammunition conveyor.The proposed approach involves the use of a deep learning network to approximate the physical model and the extremum method to obtain a single cycle sequence decoupling strategy for solving the time-varying reliability issue of complex systems.Employing this strategy,the time-varying reliability of the ammunition conveyor is transformed into a static reliability problem.The proposed method includes the use of a deep feedforward neural network,second-order saddle point ap-proximation(SPA)method,extremum method,and efficient global optimization(EGO)technology.The results reveal that the reliability of the motion accuracy of the ammunition conveyor is 93.42%,with the maximum failure probability occurring at 0.21 s.These results serve as an important reference for the structural optimi-zation design of the ammunition conveyor based on reliability and the maintenance of the operational process.展开更多
Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frame...Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge.Existing methods typically rely on dense keyframe inputs or complex prior structures,making it difficult to balance motion quality and plausibility under conditions such as sparse constraints,long-term dependencies,and diverse motion styles.To address this,we propose a motion generation framework based on a frequency-domain diffusion model,which aims to better model complex motion distributions and enhance generation stability under sparse conditions.Our method maps motion sequences to the frequency domain via the Discrete Cosine Transform(DCT),enabling more effective modeling of low-frequency motion structures while suppressing high-frequency noise.A denoising network based on self-attention is introduced to capture long-range temporal dependencies and improve global structural awareness.Additionally,a multi-objective loss function is employed to jointly optimize motion smoothness,pose diversity,and anatomical consistency,enhancing the realism and physical plausibility of the generated sequences.Comparative experiments on the Human3.6M and LaFAN1 datasets demonstrate that our method outperforms state-of-the-art approaches across multiple performance metrics,showing stronger capabilities in generating intermediate motion frames.This research offers a new perspective and methodology for human motion generation and holds promise for applications in character animation,game development,and virtual interaction.展开更多
Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,...Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,it remains a critical challenge to simultaneously achieve desirable mechanical and electrical performance along with biocompatibility,adhesion,self-healing,and environmental robustness with excellent sensing metrics.Herein,we report a multifunctional,anti-freezing,selfadhesive,and self-healable organogel pressure sensor composed of cobalt nanoparticle encapsulated nitrogen-doped carbon nanotubes(CoN CNT)embedded in a polyvinyl alcohol-gelatin(PVA/GLE)matrix.Fabricated using a binary solvent system of water and ethylene glycol(EG),the CoN CNT/PVA/GLE organogel exhibits excellent flexibility,biocompatibility,and temperature tolerance with remarkable environmental stability.Electrochemical impedance spectroscopy confirms near-stable performance across a broad humidity range(40%-95%RH).Freeze-tolerant conductivity under sub-zero conditions(-20℃)is attributed to the synergistic role of CoN CNT and EG,preserving mobility and network integrity.The Co N CNT/PVA/GLE organogel sensor exhibits high sensitivity of 5.75 k Pa^(-1)in the detection range from 0 to 20 k Pa,ideal for subtle biomechanical motion detection.A smart human-machine interface for English letter recognition using deep learning achieved 98%accuracy.The organogel sensor utility was extended to detect human gestures like finger bending,wrist motion,and throat vibration during speech.展开更多
Background Computed tomography(CT) and cone-beam computed tomography(CBCT) image registration play pivotal roles in computer-assisted navigation for orthopedic surgery. Traditional methods often apply uniform deformat...Background Computed tomography(CT) and cone-beam computed tomography(CBCT) image registration play pivotal roles in computer-assisted navigation for orthopedic surgery. Traditional methods often apply uniform deformation models, neglecting the biomechanical differences between rigid structures and soft tissues, which compromises registration accuracy, especially during significant bone displacements. Method To address this issue, we introduce RE-Reg, a rigid-elastic CT-CBCT image registration framework that jointly learns rigid bone motion and soft tissue deformation. RE-Reg incorporates a rigid alignment(RA) module to estimate global bone motion and an elastic deformation(ED) module to model soft tissue deformation, preserving bony structures through bone shape preservation(BSP) loss. Result Our comprehensive evaluation on publicly available datasets demonstrates that RE-Reg significantly outperforms existing methods in terms of registration accuracy and rigid bone structure preservation, achieving a 1.3% improvement in Dice similarity coefficient(DSC) and a 23% reduction in rigid bone deformation(%Δvol) compared with the best baseline. Conclusion This framework not only enhances anatomical fidelity but also ensures biomechanical plausibility and provides a valuable tool for image-guided orthopedic surgery. This code is available athttps://github.com/Zq-Huang/RE-Reg.展开更多
In order to optimize the reaming process of the type IV composite hydrogen storage cylinder,the netting theory was employed for the design of stacking sequences,and the thickness in the head section was predicted.A fi...In order to optimize the reaming process of the type IV composite hydrogen storage cylinder,the netting theory was employed for the design of stacking sequences,and the thickness in the head section was predicted.A finite element model of the plastic-lined composite hydrogen storage cylinder,designed to withstand a working pressure of 70.0 MPa,was established by using the wound composite modeler(WCM)in the Abaqus software to analyze the forces acting on the winding layer.The Hashin failure criterion was utilized as the standard for assessing composite failure,and a progressive failure analysis of the cylinder was conducted to predict both the bursting pressure and the failure location of the composite hydrogen storage cylinder.The results indicate that the reaming process can effectively reduce the maximum filament winding thickness in the head section and promote a more uniform transition.At the bursting pressure,the stress within the head liner decreases,thereby enhancing the ultimate bearing capacity of the cylinder.A control system for a four-axis winding machine was designed by utilizing an industrial computer and a programmable multi-axis controller(PMAC).The winding line pattern is designed and the G-code trajectory is generated by the industrial computer.The numerical control system,composed of the PMAC and servo motor,executes the four-axis interpolation motion.展开更多
Next-generation fire safety systems demand precise detection and motion recognition of flames.In-sensor computing,which integrates sensing,memory,and processing capabilities,has emerged as a key technology in flame de...Next-generation fire safety systems demand precise detection and motion recognition of flames.In-sensor computing,which integrates sensing,memory,and processing capabilities,has emerged as a key technology in flame detection.However,the implementation of hardware-level functional demonstrations based on artificial vision systems in the solar-blind ultraviolet(UV)band(200-280 nm)is hindered by the weak detection capability.Here,we propose Ga_(2)O_(3)/In_(2)Se_(3) heterojunctions for the ferroelectric(abbreviation:Fe)optoelectronic sensor(abbreviation:OES)array(5×5 pixels),which is capable of ultraweak UV light detection with an ultrahigh detectivity through ferroelectric regulation and features in configurable multimode functionality.The Fe-OES array can directly sense different flame motions and simulate the non-spiking gradient neurons of insect visual system.Moreover,the flame signal can be effectively amplified in combination with leaky integration-and-fire neuron hardware.Using this Fe-OES system and neuromorphic hardware,we successfully demonstrate three flame processing tasks:achieving efficient flame detection across all time periods with terminal and cloud-based alarms;flame motion recognition with a lightweight convolutional neural network achieving 96.47%accuracy;and flame light recognition with 90.51%accuracy by means of a photosensitive artificial neural system.This work provides effective tools and approaches for addressing a variety of complex flame detection tasks.展开更多
Soft-tissue motion introduces significant challenges in robotic teleoperation,especially in medical scenarios where precise target tracking is critical.Latency across sensing,computation,and actuation chains leads to ...Soft-tissue motion introduces significant challenges in robotic teleoperation,especially in medical scenarios where precise target tracking is critical.Latency across sensing,computation,and actuation chains leads to degraded tracking performance,particularly around high-acceleration segments and trajectory inflection points.This study investigates machine learning-based predictive compensation for latency mitigation in soft-tissue tracking.Three models—autoregressive(AR),long short-term memory(LSTM),and temporal convolutional network(TCN)—were implemented and evaluated on both synthetic and real datasets.By aligning the prediction horizon with the end-to-end system delay,we demonstrate that prediction-based compensation significantly reduces tracking errors.Among the models,TCN achieved superior robustness and accuracy on complex motion patterns,particularly in multi-step prediction tasks,and exhibited better latency–horizon compatibility.The results suggest that TCN is a promising candidate for real-time latency compensation in teleoperated robotic systems involving dynamic soft-tissue interaction.展开更多
There is a strong coupling relationship between the friction characteristics of the ball-groove interface and the ball motion behavior.However,available studies tend to consider ball motion and frictional behavior sep...There is a strong coupling relationship between the friction characteristics of the ball-groove interface and the ball motion behavior.However,available studies tend to consider ball motion and frictional behavior separately.In this paper,a unified tribology-kinematic model is established considering the coupling effect between friction and the ball velocity vector.The friction in ball-groove contact and ball speed are simultaneously measured by a newly developed disc-ball-disc device for studying friction and movement in ball screws.A comprehensive analysis of rubbing interface behavior and ball motion is conducted.The results show that the coupling effect between friction in ball-groove contact and ball motion is quite obvious.The sliding velocity of the ball is much higher with coupling effect than that when ignoring coupling influence,especially at high-speed conditions.The friction in ball-groove contact decreases at first and then shows a dramatic increase with the gradual rise of rotation speed,which is caused by the coupling variation of sliding speed.The studies show that the disc-ball-disc approach is an innovative and valuable method to investigate friction and ball motion in ball screws.展开更多
The aerostatic spindle is a key component of ultra-precision machine tools,and its error motion is crucial to machining accuracy and reliability.Spindle error motion is unavoidable,and its online monitoring and predic...The aerostatic spindle is a key component of ultra-precision machine tools,and its error motion is crucial to machining accuracy and reliability.Spindle error motion is unavoidable,and its online monitoring and prediction are quite important.Currently,there are relatively few studies on the online monitoring and prediction methods for the aerostatic spindle,and the level of intelligence is relatively low.To address this problem,an error motion monitoring system based on digital twin(DT)technology was established for the aerostatic spindle.A spindle error motion prediction method based on a mechanism and data fusion model(MDFM)was proposed.Additionally,a highly available and interactive aerostatic spindle DT service platform was developed.Experimental results have verified the good performance of this platform.The platform facilitates interaction between the physical and virtual entities of the aerostatic spindle,enabling three-dimensional visualization,monitoring,prediction,and simulation of spindle error motion,and shows good potential for engineering applications.展开更多
[Objective]This study aims to investigate the multi-body hydrodynamic interaction mechanisms during offshore lifting operations of aquaculture net cages in wind-fishery integration systems.By integrating numerical sim...[Objective]This study aims to investigate the multi-body hydrodynamic interaction mechanisms during offshore lifting operations of aquaculture net cages in wind-fishery integration systems.By integrating numerical simulations and dynamic analysis methods,this study systematically investigates the coupled dynamic response characteristics during the cage-carrier vessel separation process to reveal its dynamic evolution patterns and key influence mechanisms.[Method]Based on potential flow theory,a fully coupled dynamic analysis model of crane vessel-net cage-semi-submersible barge was established for a marine ranch project in Guangdong.The complete lifting process was dynamically simulated using SESAM software.Five typical operating sea states were configured to investigate the influence of wave parameters on the system's motion response under combined wave-current-wind actions.[Result]The results demonstrate that wave period dominates the system stability.Under short-period conditions,the system maintains stable motion with relatively small horizontal relative displacements,while long-period conditions excite low-frequency resonance,leading to significant slow-drift motions.Vertical response analysis reveals that long-period waves cause severe relative displacement fluctuations between the cage and semi-submersible vessel,with actual displacement amplitudes doubling the preset safety target of 2.045 m.Quantitative analysis further indicates that when significant wave height increases from 1.0 m to 1.5 m,the actual displacement amplitude increases by approximately 20%relative to the target displacement of 2.045 m,demonstrating that its influence is significantly weaker than the displacement variations induced by wave period changes.The complete dynamic simulation successfully captures the continuous dynamic response characteristics during the lifting process.[Conclusion]This research clarifies the influence mechanisms of wave parameters on the cage lifting process,identifying wave period as the crucial factor for operational safety.An operation window assessment method incorporating multi-body coupling effects is established,proposing a safety criterion with peak period not exceeding six seconds as the core requirement.The findings provide theoretical foundation for safe installation of marine ranch net cages and offer valuable references for similar offshore lifting operations.展开更多
In Human–Robot Interaction(HRI),generating robot trajectories that accurately reflect user intentions while ensuring physical realism remains challenging,especially in unstructured environments.In this study,we devel...In Human–Robot Interaction(HRI),generating robot trajectories that accurately reflect user intentions while ensuring physical realism remains challenging,especially in unstructured environments.In this study,we develop a multimodal framework that integrates symbolic task reasoning with continuous trajectory generation.The approach employs transformer models and adversarial training to map high-level intent to robotic motion.Information from multiple data sources,such as voice traits,hand and body keypoints,visual observations,and recorded paths,is integrated simultaneously.These signals are mapped into a shared representation that supports interpretable reasoning while enabling smooth and realistic motion generation.Based on this design,two different learning strategies are investigated.In the first step,grammar-constrained Linear Temporal Logic(LTL)expressions are created from multimodal human inputs.These expressions are subsequently decoded into robot trajectories.The second method generates trajectories directly from symbolic intent and linguistic data,bypassing an intermediate logical representation.Transformer encoders combine multiple types of information,and autoregressive transformer decoders generate motion sequences.Adding smoothness and speed limits during training increases the likelihood of physical feasibility.To improve the realism and stability of the generated trajectories during training,an adversarial discriminator is also included to guide them toward the distribution of actual robot motion.Tests on the NATSGLD dataset indicate that the complete system exhibits stable training behaviour and performance.In normalised coordinates,the logic-based pipeline has an Average Displacement Error(ADE)of 0.040 and a Final Displacement Error(FDE)of 0.036.The adversarial generator makes substantially more progress,reducing ADE to 0.021 and FDE to 0.018.Visual examination confirms that the generated trajectories closely align with observed motion patterns while preserving smooth temporal dynamics.展开更多
The widely distributed loess deposits in the Yellow River Basin exhibit unique engineering geological characteristics.The variations in their thickness and stratigraphic structure significantly amplify ground motion p...The widely distributed loess deposits in the Yellow River Basin exhibit unique engineering geological characteristics.The variations in their thickness and stratigraphic structure significantly amplify ground motion parameters,directly influencing the regional seismic hazard risk level.This study methodically conducted on-site studies and observations of building collapses and damages resulting from seismic amplification effects,using the Wenchuan M_(S)8.0 earthquake as a case study.Comprehensive experimental and numerical simulation studies were carried out.A large-scale shaking table test was performed,and numerical models for 14 different loess sites types were established.Various types of seismic waves were incorporated into these models for systematic numerical simulation calculations.The research reveals the mechanisms by which loess deposit thickness and stratigraphic structure in the Yellow River Basin affect seismic ground motion amplification.The results indicate that as the epicentral distance increases,the peak ground motion shows a marked attenuation trend,with the horizontal component attenuating substantially faster than the vertical component.As the overlying loess layer thickness increases from 50 to 100 m,the seismic intensity may escalate by 3−4 degrees,and the peak acceleration may amplify by 1.5−2.2 times.With the augmentation of loess deposit thickness and the proliferation of soil layers,both the peak acceleration response spectrum and the characteristic period demonstrate an upward tendency,exhibiting slight fluctuations contingent upon the seismic wave type.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.62105278 and 11674273)the Natural Science Foundation of Shandong Province(Grant No.ZR2023MA015)。
文摘A method for correlating thermal light over a wide spectral range is proposed.A multi-wavelength pseudothermal source,prepared by projecting laser beams of multiple wavelengths(650 nm,635 nm,532 nm,and 473 nm)onto a moving thin ground glass plate,is employed in a double-slit interference experiment.The ground glass plate induces random phase differences between light beams of different wavelengths passing through it.This initial random phase difference significantly influences the high-order intensity correlation functions of multi-wavelength thermal beams.Experimentally,second-order correlated interference patterns,including subwavelength interference,of pseudothermal beams with different wavelengths are observed in the intensity correlation measurements.This method facilitates applications of correlated thermal photons in quantum information processing and quantum imaging.
基金supported,in part,by the National Nature Science Foundation of China under Grant 62272236,62376128 and 62306139the Natural Science Foundation of Jiangsu Province under Grant BK20201136,BK20191401.
文摘Discriminative region localization and efficient feature encoding are crucial for fine-grained object recognition.However,existing data augmentation methods struggle to accurately locate discriminative regions in complex backgrounds,small target objects,and limited training data,leading to poor recognition.Fine-grained images exhibit“small inter-class differences,”and while second-order feature encoding enhances discrimination,it often requires dual Convolutional Neural Networks(CNN),increasing training time and complexity.This study proposes a model integrating discriminative region localization and efficient second-order feature encoding.By ranking feature map channels via a fully connected layer,it selects high-importance channels to generate an enhanced map,accurately locating discriminative regions.Cropping and erasing augmentations further refine recognition.To improve efficiency,a novel second-order feature encoding module generates an attention map from the fourth convolutional group of Residual Network 50 layers(ResNet-50)and multiplies it with features from the fifth group,producing second-order features while reducing dimensionality and training time.Experiments on Caltech-University of California,San Diego Birds-200-2011(CUB-200-2011),Stanford Car,and Fine-Grained Visual Classification of Aircraft(FGVC Aircraft)datasets show state-of-the-art accuracy of 88.9%,94.7%,and 93.3%,respectively.
基金supported by the National Natural Science Foundation of China(Nos.51239008 and 51279130)
文摘This paper presents a study on the motion response of a tension-leg platform(TLP) under first-and second-order wave forces, including the mean-drift force, difference and sum-frequency forces. The second-order wave force is calculated using the full-field quadratic transfer function(QTF). The coupled effect of the horizontal motions, such as surge, sway and yaw motions, and the set-down motion are taken into consideration by the nonlinear restoring matrix. The time-domain analysis with 50-yr random sea state is performed. A comparison of the results of different case studies is made to assess the influence of second-order wave force on the motions of the platform. The analysis shows that the second-order wave force has a major impact on motions of the TLP. The second-order difference-frequency wave force has an obvious influence on the low-frequency motions of surge and sway, and also will induce a large set-down motion which is an important part of heave motion. Besides, the second-order sum-frequency force will induce a set of high-frequency motions of roll and pitch. However, little influence of second-order wave force is found on the yaw motion.
基金supported by the National Natural Science Foundation of China(Grant Nos.12104232 and 12074156).
文摘In recent years,the study of higher-order topological states and their material realizations has become a research frontier in topological condensed matter physics.We demonstrate that twisted bilayer graphene with small twist angles behaves as a second-order topological insulator possessing topological corner charges.Using a tight-binding model,we compute the topological band indices and corner states of finite-sized twisted bilayer graphene flakes.It is found that for any small twist angle,whether commensurate or incommensurate,the gaps both below and above the flat bands are associated with nontrivial topological indices.Our results not only extend the concept of second-order band topology to arbitrary small twist angles but also confirm the existence of corner states at acute-angle corners.
基金supported by the National Natural Science Foundation of China under Grants 62476138 and 42375016.
文摘Continuous control protocols are extensively utilized in traditional MASs,in which information needs to be transmitted among agents consecutively,therefore resulting in excessive consumption of limited resources.To decrease the control cost,based on ISC,several LFC problems are investigated for second-order MASs without and with time delay,respectively.Firstly,an intermittent sampled controller is designed,and a sufficient and necessary condition is derived,under which state errors between the leader and all the followers approach zero asymptotically.Considering that time delay is inevitable,a new protocol is proposed to deal with the time-delay situation.The error system’s stability is analyzed using the Schur stability theorem,and sufficient and necessary conditions for LFC are obtained,which are closely associated with the coupling gain,the system parameters,and the network structure.Furthermore,for the case where the current position and velocity information are not available,a distributed protocol is designed that depends only on the sampled position information.The sufficient and necessary conditions for LFC are also given.The results show that second-order MASs can achieve the LFC if and only if the system parameters satisfy the inequalities proposed in the paper.Finally,the correctness of the obtained results is verified by numerical simulations.
基金supported by the National Natural Science Foundation of China(Grant Nos.12174344 and 12175199)Foundation of Department of Science and Technology of Zhejiang Province(Grant No.2022R52047)。
文摘In this paper,we investigate the phenomena of electromagnetically induced transparency and the generation of second-order sideband in a Laguerre–Gaussian cavity optorotational system with a Kerr nonlinear medium.Using the perturbation method,we analyze the first-and second-order sideband generations in the output field from the system under the actions of a strong control field and a weak probe field.Numerical simulations show that the Kerr nonlinearity can lead to the occurrence of the asymmetric line shape in the transmission of the probe field.Comparing with traditional scheme for generating the second-order sideband,our spectral shape of the second-order sideband is amplified and becomes asymmetric,which has potential applications in precision measurement,high-sensitivity devices,and frequency conversion.
文摘The stabilization problem of second-order bilinear systems with time delay is investigated.Feedback controls are chosen so that the strong and exponential stabilization of the system is ensured.The obtained results are illustrated by wave and beam equations with simulation.
基金Supported by the Natural Science Foundation of Shaanxi Province(2017JM6087)。
文摘This research,based on Mason's formula,proposes a novel design for a second-order transconductance-mode universal filter with the operational transconductance amplifier(OTA)as the core and the second-generation current-controlled conveyor(CCCⅡ)as the auxiliary.The circuit incorporates two OTAs,one CCCⅡ,two grounded capacitors,and one grounded resistor.The quality factor Q and natural frequency fo of the filter can be electronically tuned and are not sensitive to temperature.The input and output terminals of the cir-cuit exhibit no loading effect,and the sensitivity of the circuit is low.At last,alternating frequency analysis,parameter scanning analysis,and temperature scanning analysis have been carried out by using Multisim software,confirming the correctness and effectiveness of the designed circuit.
基金Supported by National Natural Science Foundation of China(Grant No.U2141246)Key Laboratory of Artillery Launch and Control Technology of China(Grant No.2021-001)Basic Research of State Administration of Science Technology and Industry for National Defense of China(Grant No.JXJL202208A001).
文摘The automatic loading systems of artillery are critical for the accurate,efficient,and reliable delivery of pro-jectiles and propellants into the gun chamber.In modern artillery,the ammunition conveyor serves as the end effector of the automatic loading system,and its motion state significantly impacts the accuracy of projectiles.Therefore,it is of immense importance to precisely and effectively evaluate the reliability of the motion accuracy of the ammunition conveyor.This paper aims to propose a practical and efficient analysis method for evaluating the reliability of the motion accuracy of the ammunition conveyor.The proposed approach involves the use of a deep learning network to approximate the physical model and the extremum method to obtain a single cycle sequence decoupling strategy for solving the time-varying reliability issue of complex systems.Employing this strategy,the time-varying reliability of the ammunition conveyor is transformed into a static reliability problem.The proposed method includes the use of a deep feedforward neural network,second-order saddle point ap-proximation(SPA)method,extremum method,and efficient global optimization(EGO)technology.The results reveal that the reliability of the motion accuracy of the ammunition conveyor is 93.42%,with the maximum failure probability occurring at 0.21 s.These results serve as an important reference for the structural optimi-zation design of the ammunition conveyor based on reliability and the maintenance of the operational process.
基金supported by the National Natural Science Foundation of China(Grant No.72161034).
文摘Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge.Existing methods typically rely on dense keyframe inputs or complex prior structures,making it difficult to balance motion quality and plausibility under conditions such as sparse constraints,long-term dependencies,and diverse motion styles.To address this,we propose a motion generation framework based on a frequency-domain diffusion model,which aims to better model complex motion distributions and enhance generation stability under sparse conditions.Our method maps motion sequences to the frequency domain via the Discrete Cosine Transform(DCT),enabling more effective modeling of low-frequency motion structures while suppressing high-frequency noise.A denoising network based on self-attention is introduced to capture long-range temporal dependencies and improve global structural awareness.Additionally,a multi-objective loss function is employed to jointly optimize motion smoothness,pose diversity,and anatomical consistency,enhancing the realism and physical plausibility of the generated sequences.Comparative experiments on the Human3.6M and LaFAN1 datasets demonstrate that our method outperforms state-of-the-art approaches across multiple performance metrics,showing stronger capabilities in generating intermediate motion frames.This research offers a new perspective and methodology for human motion generation and holds promise for applications in character animation,game development,and virtual interaction.
基金supported by the Basic Science Research Program(2023R1A2C3004336,RS-202300243807)&Regional Leading Research Center(RS-202400405278)through the National Research Foundation of Korea(NRF)grant funded by the Korea Government(MSIT)。
文摘Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,it remains a critical challenge to simultaneously achieve desirable mechanical and electrical performance along with biocompatibility,adhesion,self-healing,and environmental robustness with excellent sensing metrics.Herein,we report a multifunctional,anti-freezing,selfadhesive,and self-healable organogel pressure sensor composed of cobalt nanoparticle encapsulated nitrogen-doped carbon nanotubes(CoN CNT)embedded in a polyvinyl alcohol-gelatin(PVA/GLE)matrix.Fabricated using a binary solvent system of water and ethylene glycol(EG),the CoN CNT/PVA/GLE organogel exhibits excellent flexibility,biocompatibility,and temperature tolerance with remarkable environmental stability.Electrochemical impedance spectroscopy confirms near-stable performance across a broad humidity range(40%-95%RH).Freeze-tolerant conductivity under sub-zero conditions(-20℃)is attributed to the synergistic role of CoN CNT and EG,preserving mobility and network integrity.The Co N CNT/PVA/GLE organogel sensor exhibits high sensitivity of 5.75 k Pa^(-1)in the detection range from 0 to 20 k Pa,ideal for subtle biomechanical motion detection.A smart human-machine interface for English letter recognition using deep learning achieved 98%accuracy.The organogel sensor utility was extended to detect human gestures like finger bending,wrist motion,and throat vibration during speech.
基金Supported by the National Natural Science Foundation of China(Grant Nos.62025104,62331005,and U22A2052)the Beijing Natural Science Foundation(Grant No.L242100).
文摘Background Computed tomography(CT) and cone-beam computed tomography(CBCT) image registration play pivotal roles in computer-assisted navigation for orthopedic surgery. Traditional methods often apply uniform deformation models, neglecting the biomechanical differences between rigid structures and soft tissues, which compromises registration accuracy, especially during significant bone displacements. Method To address this issue, we introduce RE-Reg, a rigid-elastic CT-CBCT image registration framework that jointly learns rigid bone motion and soft tissue deformation. RE-Reg incorporates a rigid alignment(RA) module to estimate global bone motion and an elastic deformation(ED) module to model soft tissue deformation, preserving bony structures through bone shape preservation(BSP) loss. Result Our comprehensive evaluation on publicly available datasets demonstrates that RE-Reg significantly outperforms existing methods in terms of registration accuracy and rigid bone structure preservation, achieving a 1.3% improvement in Dice similarity coefficient(DSC) and a 23% reduction in rigid bone deformation(%Δvol) compared with the best baseline. Conclusion This framework not only enhances anatomical fidelity but also ensures biomechanical plausibility and provides a valuable tool for image-guided orthopedic surgery. This code is available athttps://github.com/Zq-Huang/RE-Reg.
文摘In order to optimize the reaming process of the type IV composite hydrogen storage cylinder,the netting theory was employed for the design of stacking sequences,and the thickness in the head section was predicted.A finite element model of the plastic-lined composite hydrogen storage cylinder,designed to withstand a working pressure of 70.0 MPa,was established by using the wound composite modeler(WCM)in the Abaqus software to analyze the forces acting on the winding layer.The Hashin failure criterion was utilized as the standard for assessing composite failure,and a progressive failure analysis of the cylinder was conducted to predict both the bursting pressure and the failure location of the composite hydrogen storage cylinder.The results indicate that the reaming process can effectively reduce the maximum filament winding thickness in the head section and promote a more uniform transition.At the bursting pressure,the stress within the head liner decreases,thereby enhancing the ultimate bearing capacity of the cylinder.A control system for a four-axis winding machine was designed by utilizing an industrial computer and a programmable multi-axis controller(PMAC).The winding line pattern is designed and the G-code trajectory is generated by the industrial computer.The numerical control system,composed of the PMAC and servo motor,executes the four-axis interpolation motion.
基金supported by the Major Program(JD)of Hubei Province under Grant No.2023BAA009the National Natural Science Foundation of China(Grant No.22105162)+1 种基金the Natural Science Foundation of Hubei Province(Grant No.2023AFB623)the Original Exploration Seed Fund of Hubei University。
文摘Next-generation fire safety systems demand precise detection and motion recognition of flames.In-sensor computing,which integrates sensing,memory,and processing capabilities,has emerged as a key technology in flame detection.However,the implementation of hardware-level functional demonstrations based on artificial vision systems in the solar-blind ultraviolet(UV)band(200-280 nm)is hindered by the weak detection capability.Here,we propose Ga_(2)O_(3)/In_(2)Se_(3) heterojunctions for the ferroelectric(abbreviation:Fe)optoelectronic sensor(abbreviation:OES)array(5×5 pixels),which is capable of ultraweak UV light detection with an ultrahigh detectivity through ferroelectric regulation and features in configurable multimode functionality.The Fe-OES array can directly sense different flame motions and simulate the non-spiking gradient neurons of insect visual system.Moreover,the flame signal can be effectively amplified in combination with leaky integration-and-fire neuron hardware.Using this Fe-OES system and neuromorphic hardware,we successfully demonstrate three flame processing tasks:achieving efficient flame detection across all time periods with terminal and cloud-based alarms;flame motion recognition with a lightweight convolutional neural network achieving 96.47%accuracy;and flame light recognition with 90.51%accuracy by means of a photosensitive artificial neural system.This work provides effective tools and approaches for addressing a variety of complex flame detection tasks.
基金Support by Sichuan Science and Technology Program[2023YFSY0026,2023YFH0004]Guangzhou Huashang University[2024HSZD01,HS2023JYSZH01].
文摘Soft-tissue motion introduces significant challenges in robotic teleoperation,especially in medical scenarios where precise target tracking is critical.Latency across sensing,computation,and actuation chains leads to degraded tracking performance,particularly around high-acceleration segments and trajectory inflection points.This study investigates machine learning-based predictive compensation for latency mitigation in soft-tissue tracking.Three models—autoregressive(AR),long short-term memory(LSTM),and temporal convolutional network(TCN)—were implemented and evaluated on both synthetic and real datasets.By aligning the prediction horizon with the end-to-end system delay,we demonstrate that prediction-based compensation significantly reduces tracking errors.Among the models,TCN achieved superior robustness and accuracy on complex motion patterns,particularly in multi-step prediction tasks,and exhibited better latency–horizon compatibility.The results suggest that TCN is a promising candidate for real-time latency compensation in teleoperated robotic systems involving dynamic soft-tissue interaction.
基金Supported by National Natural Science Foundation of China(Grant No.52275206).
文摘There is a strong coupling relationship between the friction characteristics of the ball-groove interface and the ball motion behavior.However,available studies tend to consider ball motion and frictional behavior separately.In this paper,a unified tribology-kinematic model is established considering the coupling effect between friction and the ball velocity vector.The friction in ball-groove contact and ball speed are simultaneously measured by a newly developed disc-ball-disc device for studying friction and movement in ball screws.A comprehensive analysis of rubbing interface behavior and ball motion is conducted.The results show that the coupling effect between friction in ball-groove contact and ball motion is quite obvious.The sliding velocity of the ball is much higher with coupling effect than that when ignoring coupling influence,especially at high-speed conditions.The friction in ball-groove contact decreases at first and then shows a dramatic increase with the gradual rise of rotation speed,which is caused by the coupling variation of sliding speed.The studies show that the disc-ball-disc approach is an innovative and valuable method to investigate friction and ball motion in ball screws.
基金supported by the National Natural Science Foundation of China(Grant No.52475494),the Zhejiang Provincial Natural Science Foundation of China(Grant No.LY22E050003),the Fundamental Research Funds for the Provincial Universities of Zhejiang(Grant No.RF-A2020005).
文摘The aerostatic spindle is a key component of ultra-precision machine tools,and its error motion is crucial to machining accuracy and reliability.Spindle error motion is unavoidable,and its online monitoring and prediction are quite important.Currently,there are relatively few studies on the online monitoring and prediction methods for the aerostatic spindle,and the level of intelligence is relatively low.To address this problem,an error motion monitoring system based on digital twin(DT)technology was established for the aerostatic spindle.A spindle error motion prediction method based on a mechanism and data fusion model(MDFM)was proposed.Additionally,a highly available and interactive aerostatic spindle DT service platform was developed.Experimental results have verified the good performance of this platform.The platform facilitates interaction between the physical and virtual entities of the aerostatic spindle,enabling three-dimensional visualization,monitoring,prediction,and simulation of spindle error motion,and shows good potential for engineering applications.
文摘[Objective]This study aims to investigate the multi-body hydrodynamic interaction mechanisms during offshore lifting operations of aquaculture net cages in wind-fishery integration systems.By integrating numerical simulations and dynamic analysis methods,this study systematically investigates the coupled dynamic response characteristics during the cage-carrier vessel separation process to reveal its dynamic evolution patterns and key influence mechanisms.[Method]Based on potential flow theory,a fully coupled dynamic analysis model of crane vessel-net cage-semi-submersible barge was established for a marine ranch project in Guangdong.The complete lifting process was dynamically simulated using SESAM software.Five typical operating sea states were configured to investigate the influence of wave parameters on the system's motion response under combined wave-current-wind actions.[Result]The results demonstrate that wave period dominates the system stability.Under short-period conditions,the system maintains stable motion with relatively small horizontal relative displacements,while long-period conditions excite low-frequency resonance,leading to significant slow-drift motions.Vertical response analysis reveals that long-period waves cause severe relative displacement fluctuations between the cage and semi-submersible vessel,with actual displacement amplitudes doubling the preset safety target of 2.045 m.Quantitative analysis further indicates that when significant wave height increases from 1.0 m to 1.5 m,the actual displacement amplitude increases by approximately 20%relative to the target displacement of 2.045 m,demonstrating that its influence is significantly weaker than the displacement variations induced by wave period changes.The complete dynamic simulation successfully captures the continuous dynamic response characteristics during the lifting process.[Conclusion]This research clarifies the influence mechanisms of wave parameters on the cage lifting process,identifying wave period as the crucial factor for operational safety.An operation window assessment method incorporating multi-body coupling effects is established,proposing a safety criterion with peak period not exceeding six seconds as the core requirement.The findings provide theoretical foundation for safe installation of marine ranch net cages and offer valuable references for similar offshore lifting operations.
基金The authors extend their appreciation to Prince Sattam bin Abdulaziz University for funding this research work through the project number(PSAU/2024/01/32082).
文摘In Human–Robot Interaction(HRI),generating robot trajectories that accurately reflect user intentions while ensuring physical realism remains challenging,especially in unstructured environments.In this study,we develop a multimodal framework that integrates symbolic task reasoning with continuous trajectory generation.The approach employs transformer models and adversarial training to map high-level intent to robotic motion.Information from multiple data sources,such as voice traits,hand and body keypoints,visual observations,and recorded paths,is integrated simultaneously.These signals are mapped into a shared representation that supports interpretable reasoning while enabling smooth and realistic motion generation.Based on this design,two different learning strategies are investigated.In the first step,grammar-constrained Linear Temporal Logic(LTL)expressions are created from multimodal human inputs.These expressions are subsequently decoded into robot trajectories.The second method generates trajectories directly from symbolic intent and linguistic data,bypassing an intermediate logical representation.Transformer encoders combine multiple types of information,and autoregressive transformer decoders generate motion sequences.Adding smoothness and speed limits during training increases the likelihood of physical feasibility.To improve the realism and stability of the generated trajectories during training,an adversarial discriminator is also included to guide them toward the distribution of actual robot motion.Tests on the NATSGLD dataset indicate that the complete system exhibits stable training behaviour and performance.In normalised coordinates,the logic-based pipeline has an Average Displacement Error(ADE)of 0.040 and a Final Displacement Error(FDE)of 0.036.The adversarial generator makes substantially more progress,reducing ADE to 0.021 and FDE to 0.018.Visual examination confirms that the generated trajectories closely align with observed motion patterns while preserving smooth temporal dynamics.
基金supported by the Earthquake Science and Technology Spark Plan Project(No.XH23041C)The Natural Science Foundation of Gansu Province(No.22JR11RA090)Gansu Lanzhou Geophysics National Observation and Research Station(No.2021Y14).
文摘The widely distributed loess deposits in the Yellow River Basin exhibit unique engineering geological characteristics.The variations in their thickness and stratigraphic structure significantly amplify ground motion parameters,directly influencing the regional seismic hazard risk level.This study methodically conducted on-site studies and observations of building collapses and damages resulting from seismic amplification effects,using the Wenchuan M_(S)8.0 earthquake as a case study.Comprehensive experimental and numerical simulation studies were carried out.A large-scale shaking table test was performed,and numerical models for 14 different loess sites types were established.Various types of seismic waves were incorporated into these models for systematic numerical simulation calculations.The research reveals the mechanisms by which loess deposit thickness and stratigraphic structure in the Yellow River Basin affect seismic ground motion amplification.The results indicate that as the epicentral distance increases,the peak ground motion shows a marked attenuation trend,with the horizontal component attenuating substantially faster than the vertical component.As the overlying loess layer thickness increases from 50 to 100 m,the seismic intensity may escalate by 3−4 degrees,and the peak acceleration may amplify by 1.5−2.2 times.With the augmentation of loess deposit thickness and the proliferation of soil layers,both the peak acceleration response spectrum and the characteristic period demonstrate an upward tendency,exhibiting slight fluctuations contingent upon the seismic wave type.
