AIM:To study the relationships between amplitude of low-frequency fluctuations(ALFF)changes and clinical ophthalmic parameters in patients with primary open angle glaucoma(POAG)and analyze the diagnostic value of ALFF...AIM:To study the relationships between amplitude of low-frequency fluctuations(ALFF)changes and clinical ophthalmic parameters in patients with primary open angle glaucoma(POAG)and analyze the diagnostic value of ALFF.METHODS:Twenty-four POAG patients and 24 healthy controls(HCs)underwent resting-state functional magnetic resonance imaging(rs-fMRI).Nonparametric rank-sum tests were used to compare the ALFF values in the slow-4 and slow-5 bands,and Spearman or Pearson correlation analysis was used to assess the correlation between ALFF changes and clinical ophthalmic parameters in POAG patients.Receiver operating characteristic(ROC)curves were used to evaluate the diagnostic performance of the ALFF.RESULTS:There were 16 males in POAG patients(median age 48y)and 12 males in HCs(median age 39y).Compared with HCs,POAG patients presented increased or decreased ALFF values in different brain regions,and similar changes were observed in mild POAG patients.The ALFF values were correlated with retinal nerve fiber layer(RNFL)thickness,inner limiting membrane-retinal pigment epithelium thickness changes and the degree of visual field defects.Analysis of the diagnostic value of the ALFF via ROC curves revealed that the right medial frontal gyrus[area under the curve(AUC)=0.9063]and superior frontal gyrus(AUC=0.9097)had better diagnostic value than did the optic disc area(AUC=0.8019),visual field index(VFI%,AUC=0.8988)and macular parameters.CONCLUSION:POAG patients present altered cortical function that is significantly correlated with the optic nerve and retinal thickness and had good diagnostic value,which may reflect the underlying neuropathological mechanism of POAG.展开更多
Increasing penetration of power electronic(PE)grid-tied devices has caused more and more dynamic problems with unknown mechanisms.Since grid operation asks for a certain voltage amplitude and frequency level when ther...Increasing penetration of power electronic(PE)grid-tied devices has caused more and more dynamic problems with unknown mechanisms.Since grid operation asks for a certain voltage amplitude and frequency level when there is a power imbalance,roles of the PE grid-tied devices during dynamics must be characterized as internal voltage response under power excitation,in which the voltage vector evolves through its timevarying amplitude and frequency.Existing modeling works,unfortunately,fail to recognize amplitude and frequency modulation essence of grid voltage during dynamics,so corresponding linear models are inapplicable to small-perturbation grid dynamic analysis.Thus,taking current control timescale of grid-tied voltage source converter(VSC)for example,this paper establishes a model with active and reactive current excitation and internal voltage amplitude and frequency response.Especially,the role of the terminal voltage detection-based phase-locked loop(PLL)in the excitation-response relationship is revealed.Linearization is conducted by clarifying amplitude and frequency operating points and corresponding increments of AC signals.This model intuitively reflects the evolution of internal voltage amplitude and frequency excited by active and reactive currents,which represents characteristics of the device during dynamics.Then,simulations for verification of the linear model and time-varying nature of amplitude and frequency are presented.Features of the characteristics of VSC are preliminarily discussed.展开更多
The dynamics of network power response play a crucial role in system stability.However,the integration of power electronic equipment leads to amplitude and angular frequency(abbreviated as"frequency")time-va...The dynamics of network power response play a crucial role in system stability.However,the integration of power electronic equipment leads to amplitude and angular frequency(abbreviated as"frequency")time-varying characteristics of the node voltage during dynamic processes.As a result,traditional calcu-lation methods for and characteristics of the power response of the network based on phasor and impe-dance lose their validity.Therefore,this paper undertakes mathematical calculations to reveal the power response of a network under excitation by voltage with time-varying amplitude and frequency(TVAF),relying on the original mathematical relationships and superimposed step response.Then,the multi-timescale characteristics of both the active and reactive power of the network are explored physically.Additionally,this paper reveals a new phenomenon of storing and releasing the active and reactive power of the network.To meet practical engineering requirements,a simplified power expression is presented.Finally,the theoretical analysis is validated through time-domain simulations.展开更多
This paper designs a high-frequency stable wireless amplitude modulation(AM)system based on a Pierce circuit.The system utilizes an oscillator and comparator to generate a 20 kHz square wave with an adjustable duty cy...This paper designs a high-frequency stable wireless amplitude modulation(AM)system based on a Pierce circuit.The system utilizes an oscillator and comparator to generate a 20 kHz square wave with an adjustable duty cycle,combined with a 41 MHz carrier wave produced by a passive crystal oscillator Pierce circuit.A 100% modulation index amplitude modulation is achieved through the AD835 multiplier.The modulated signal is amplified by a power amplifier circuit and transmitted wirelessly via the transmitter antenna.Upon reception,the signal undergoes two-stage highfrequency amplification before passing through a Schottky diode envelope detector.The NE5532 shaping circuit then restores the square wave.Experimental results demonstrate reliable 11-meter transmission with carrier frequency deviation<0.75% and demodulation error<1%.展开更多
Energy storage-equipped photovoltaic(PV-storage)systems can meet frequency regulation requirements under various operating conditions,and their coordinated support for grid frequency has become a future trend.To addre...Energy storage-equipped photovoltaic(PV-storage)systems can meet frequency regulation requirements under various operating conditions,and their coordinated support for grid frequency has become a future trend.To address frequency stability issues caused by low inertia and weak damping,this paper proposes a multi-timescale frequency regulation coordinated control strategy for PV-storage integrated systems.First,a self-synchronizing control strategy for grid-connected inverters is designed based on DC voltage dynamics,enabling active inertia support while transmitting frequency variation information.Next,an energy storage inertia support control strategy is developed to enhance the frequency nadir,and an active frequency support control strategy for PV system considering a frequency regulation deadband is proposed,where the deadband value is determined based on the power regulation margin of synchronous generators,allowing the PV-storage system to adaptively switch between inertia support and primary frequency regulation under different disturbance conditions.This approach ensures system frequency stability while fully leveraging the regulation capabilities of heterogeneous resources.Finally,the real-time digital simulation results of the PV-storage integrated system demonstrate that,compared to existing control methods,the proposed strategy effectively reduces the rate of change of frequency and improves the frequency nadir under various disturbance scenarios,verifying its effectiveness.展开更多
With the increasing penetration of renewable energy,the coordination of energy storage with thermal power for frequency regulation has become an effective means to enhance grid frequency security.Addressing the challe...With the increasing penetration of renewable energy,the coordination of energy storage with thermal power for frequency regulation has become an effective means to enhance grid frequency security.Addressing the challenge of improving the frequency regulation performance of a thermal-storage primary frequency regulation system while reducing its associated losses,this paper proposes a multi-dimensional cooperative optimization strategy for the control parameters of a combined thermal-storage system,considering regulation losses.First,the frequency regulation losses of various components within the thermal power unit are quantified,and a calculation method for energy storage regulation loss is proposed,based on Depth of Discharge(DOD)and C-rate.Second,a thermal-storage cooperative control method based on series compensation is developed to improve the system’s frequency regulation performance.Third,targeting system regulation loss cost and regulation output,and considering constraints on output overshoot and system parameters,an improved Particle Swarm Optimization(PSO)algorithm is employed to tune the parameters of the low-pass filter and the series compensator,thereby reducing regulation losses while enhancing performance.Finally,simulation results demonstrate that the total loss cost of the proposed control strategy is comparable to that of a system with only thermal power participation.However,the thermal power loss cost is reduced by 42.16%compared to the thermal-only case,while simultaneously improving system frequency stability.Thus,the proposed strategy effectively balances system frequency stability and economic efficiency.展开更多
In wave-equation migration and demigration,the cross-correlation imaging/forwarding step implicitly injects an additional copy of the source wavelet,so that the amplitude spectrum of the wavelet is applied redundantly...In wave-equation migration and demigration,the cross-correlation imaging/forwarding step implicitly injects an additional copy of the source wavelet,so that the amplitude spectrum of the wavelet is applied redundantly(effectively imposing a wavelet-spectrum weighting,often akin to an amplitude-squared bias).This redundancy degrades structural fidelity and amplitude balance yet is frequently overlooked.We(i)formalize the mechanism by which cross-correlation duplicates the source-wavelet amplitude effect in both migration and demigration,and(ii)introduce a source-equalized operator that removes the redundancy by deconvolving(or dividing by)the wavelet amplitude spectrum in the imaging condition and its demigration counterpart,while leaving phase/kinematics intact.Using a band-limited Ricker wavelet on a two-layer model and on Marmousi,we show that,if unmanaged,the redundant wavelet spectrum broadens main lobes,introduces ringing,and suppresses vertical resolution in migrated images,and inflates spectrum mismatches between demigrated and observed data even when peak times agree.With our correction,images recover observed-data-consistent bandwidth and sharpened interfaces,and demigrated data also exhibit improved spectrum conformity and reduced amplitude misfit.The results clarify when source amplitudes matter,why cross-correlation makes them redundantly matter,and how a lightweight spectral correction restores physically meaningful amplitude behavior in wave-equation migration/demigration.展开更多
Frequency hopping(FH)communication has good anti-fading,anti-jamming and anti-eavesdropping capabilities,so it is one of the main ways to combat electronic jamming.In order to further improve the anti-jamming capabili...Frequency hopping(FH)communication has good anti-fading,anti-jamming and anti-eavesdropping capabilities,so it is one of the main ways to combat electronic jamming.In order to further improve the anti-jamming capability of FH communication,the parameters such as fixed frequency interval,hopping rate and hopping frequency in conventional FH can be assigned with time-varying characteristics.In order to set appropriate hopping parameters to improve the performance of the system in the electromagnetic environment with various types of jamming,a heuristically accelerated Q-learning(HAQL)method is proposed in this paper.Firstly,a theoretical model for the parameter decision-making of FH system is made,and the key parameters affecting the energy efficiency of the system are analyzed.Secondly,a Q-learning model in complex electromagnetic environment is proposed,which includes setting states,actions and rewards,as well as a HAQL-based decisionmaking algorithm is put forward.Lastly,simulations are carried out under different jamming environments,and simulation results show that the average energy efficiency of HAQL algorithm is higher than that of the SARSA algorithm,the e-greedy QL algorithm and the HQL-OSGM algorithm,respectively.展开更多
Making full use of the operator ordering method and the integration within ordered products,we obtain the analytical evolution law of a general quadratic state in the amplitude decay channel,and find that it is determ...Making full use of the operator ordering method and the integration within ordered products,we obtain the analytical evolution law of a general quadratic state in the amplitude decay channel,and find that it is determined not only by the decay rate of the amplitude decay channel but also by the coefficients of the initial quadratic state.Further,the quantum statistical properties of the initial quadratic state for amplitude decay are investigated via its average photon number and photon-counting distribution,and its Wigner distribution function evolution is discussed in detail.展开更多
Underwater images often affect the effectiveness of underwater visual tasks due to problems such as light scattering,color distortion,and detail blurring,limiting their application performance.Existing underwater imag...Underwater images often affect the effectiveness of underwater visual tasks due to problems such as light scattering,color distortion,and detail blurring,limiting their application performance.Existing underwater image enhancement methods,although they can improve the image quality to some extent,often lead to problems such as detail loss and edge blurring.To address these problems,we propose FENet,an efficient underwater image enhancement method.FENet first obtains three different scales of images by image downsampling and then transforms them into the frequency domain to extract the low-frequency and high-frequency spectra,respectively.Then,a distance mask and a mean mask are constructed based on the distance and magnitude mean for enhancing the high-frequency part,thus improving the image details and enhancing the effect by suppressing the noise in the low-frequency part.Affected by the light scattering of underwater images and the fact that some details are lost if they are directly reduced to the spatial domain after the frequency domain operation.For this reason,we propose a multi-stage residual feature aggregation module,which focuses on detail extraction and effectively avoids information loss caused by global enhancement.Finally,we combine the edge guidance strategy to further enhance the edge details of the image.Experimental results indicate that FENet outperforms current state-of-the-art underwater image enhancement methods in quantitative and qualitative evaluations on multiple publicly available datasets.展开更多
Dynamic disturbances with various frequencies could trigger different failure modes of deep excavations.Superimposed on this static stress are dynamic disturbances due to various dynamic vibrations,e.g.excavation blas...Dynamic disturbances with various frequencies could trigger different failure modes of deep excavations.Superimposed on this static stress are dynamic disturbances due to various dynamic vibrations,e.g.excavation blasting,blasting,tunnel boring machine(TBM)vibration,rockburst wave,earthquakes.Specifically,these dynamic sources are characterized by a wide range of wave frequencies f,resulting in differences in failure modes.A series of true-triaxial compression tests were conducted on granite to simulate the excavation-induced stress path in three-dimensional(3D)stresses.Subsequently,a dynamic disturbance with various frequencies was applied to a cuboid specimen,to reveal the behavior associated with brittle failure.The dynamic disturbance with frequencies f of 5 Hz,10 Hz,and 40 Hz generates less disturbed energy components in the granite together with higher peak strength.However,dynamic disturbances with f of 20 Hz and 30 Hz resulted in a lower peak strength;the peak strength of the rock increases sp albeit it decreases at first,then increases.This U-shaped phenomenon relates to the natural frequency of the granite under such stress conditions.Different rock lithologies consisting of diverse mineral composition,respond differently to each sensitive resonance frequency.Interestingly,the weak disturbance stress with a high frequency f and low amplitude A increases the ratio of crack damage to peak strength(scd/sp)in the granite.This leads to the inhibition of the expansion of the granite during the dynamic disturbance process.Multiple penetrating tensileeshear cracks appear in the s3-direction as the disturbance frequency f increases.展开更多
This paper presents a programmable frequency scan algorithm based on harmonic balance.The core idea involves treating systems under perturbation as nonlinear time-periodic(NTP)systems.Steady-state harmonics are first ...This paper presents a programmable frequency scan algorithm based on harmonic balance.The core idea involves treating systems under perturbation as nonlinear time-periodic(NTP)systems.Steady-state harmonics are first solved via Newton-Raphson iteration through a set of nonlinear equations,and then input-output variables are selected to estimate the linear transfer function of the original NTP system without perturbations.The applications and insights of the proposed algorithm are discussed,particularly in guiding existing frequency scan algorithms,which are restricted by time-domain signal generation or measurement.This improvement is achieved through linear stability analysis of NTP systems with perturbations.展开更多
Understanding how rock slopes respond to blasting loads is crucial for maintaining excavation safety and slope stability.Nevertheless,the spatiotemporal evolution,nonlinear dependence on blasting parameters,and predic...Understanding how rock slopes respond to blasting loads is crucial for maintaining excavation safety and slope stability.Nevertheless,the spatiotemporal evolution,nonlinear dependence on blasting parameters,and predictive behavior of dominant frequency responses in slope vibrations remain insufficiently understood and quantified.This study combines time-frequency analysis with machine learning to explore how the dominant frequency(f_(d))evolves in slopes under blasting.Continuous Wavelet Transform(CWT)was employed to characterize the temporal-frequency evolution of vibration signals,revealing that the dominant frequency exhibits strong spatial dependence and nonlinear variability influenced by blasting parameters and rock mass structures.Three machine learning models,namely Back Propagation Neural Network(BP),Support Vector Machine(SVM),and Random Forest(RF),were developed to predict f_(d) based on 1,000 monitoring samples obtained from numerical and field simulations.Among them,the RF model achieved the highest prediction accuracy,with mean absolute percentage errors(MAPE)below 15%,demonstrating strong robustness and generalization capability.Our analysis shows that external excitation factors,especially the loading frequency(f_(d)),mainly control the frequency response,while internal controlling factors,such as spatial position,lithological variation,and mechanical heterogeneity,modulate localized frequency amplification and energy redistribution.The results reveal that f_(d) tends to decrease with elevation and distance from the blasting source,whereas structural planes and weathered zones induce high-frequency amplification due to scattering and modal coupling effects.This study offers a new framework combining time-frequency analysis and machine learning to measure the nonlinear interaction between blasting and rock mass response,offering new insights for dynamic stability evaluation and hazard mitigation in complex rock slope systems.展开更多
The radio frequency(RF)fingerprint technique is a robust method for security enhancement of the physical layer by leveraging the unique RF imperfections inherent in various wireless devices.Among these imperfections,t...The radio frequency(RF)fingerprint technique is a robust method for security enhancement of the physical layer by leveraging the unique RF imperfections inherent in various wireless devices.Among these imperfections,the carrier frequency offset(CFO)stands out as a primary RF fingerprint(RFF)of the transmitter,offering the potential to distinguish among different transmitters.However,accurately estimating CFO in time-varying channels poses significant challenges due to multipath effects and Doppler shifts.In this paper,we focus on estimating CFO for wireless device identification in the orthogonal frequency division multiplexing(OFDM)communication system.To achieve precise CFO estimation under time-varying channels,we propose a frequency domain correlation and spline interpolation(FCSI)algorithm.This approach utilizes pilots distributed across different subcarriers to correlate with prior local sequences,facilitating accurate CFO estimation.Classification is then performed based on the Euclidean distance between the prior RFF and the tested RFF dataset.Simulation results demonstrate that the proposed Mconsecutive average method effectively reduces the classification error rate in the challenging high-frequency(HF)skywave channel environment.展开更多
In the image fusion field,fusing infrared images(IRIs)and visible images(VIs)excelled is a key area.The differences between IRIs and VIs make it challenging to fuse both types into a high-quality image.Accordingly,eff...In the image fusion field,fusing infrared images(IRIs)and visible images(VIs)excelled is a key area.The differences between IRIs and VIs make it challenging to fuse both types into a high-quality image.Accordingly,efficiently combining the advantages of both images while overcoming their shortcomings is necessary.To handle this challenge,we developed an end-to-end IRI andVI fusionmethod based on frequency decomposition and enhancement.By applying concepts from frequency domain analysis,we used the layering mechanism to better capture the salient thermal targets from the IRIs and the rich textural information from the VIs,respectively,significantly boosting the image fusion quality and effectiveness.In addition,the backbone network combined Restormer Blocks and Dense Blocks;Restormer blocks utilize global attention to extract shallow features.Meanwhile,Dense Blocks ensure the integration between shallow and deep features,thereby avoiding the loss of shallow attributes.Extensive experiments on TNO and MSRS datasets demonstrated that the suggested method achieved state-of-the-art(SOTA)performance in various metrics:Entropy(EN),Mutual Information(MI),Standard Deviation(SD),The Structural Similarity Index Measure(SSIM),Fusion quality(Qabf),MI of the pixel(FMI_(pixel)),and modified Visual Information Fidelity(VIF_(m)).展开更多
Deep transfer learning has achieved significant success in anomaly detection over the past decade,but data acquisition challenges in practical engineering hinder high-quality feature representation for few-shot learni...Deep transfer learning has achieved significant success in anomaly detection over the past decade,but data acquisition challenges in practical engineering hinder high-quality feature representation for few-shot learning tasks.To address this issue,a novel time-frequency-assisted deep feature enhancement(TFE)mechanism is proposed.Unlike traditional methods that integrate time-frequency analysis with deep neural networks,TFE employs a wavelet scattering transform to establish a parallel time-frequency feature space,where a dual interaction strategy facilitates collaboration between deep feature and time-frequency spaces through two operations:1)Enhancement,where a frequency-importance-driven contrastive learning(FICL)network transfers physically-aware information from wavelet scattering features to deep features,and 2)Feedback,which uses a detection rule adaptation module to minimize bias in wavelet scattering features based on deep feature performance.TFE is applied to a domain-adversarial anomaly detection framework and,through alternating training,significantly enhances both deep feature discriminative power and few-shot anomaly detection.Theoretical analysis confirms that the proposed dual interaction strategy reduces the upper bound of classification error.Experiments on benchmark datasets and a real-world industrial dataset from a large steel factory demonstrate TFE's superior performance and highlight the importance of frequency saliency in transfer learning.Thus,collaboration is shown to outperform integration for few-shot transfer learning in anomaly detection.展开更多
This study investigates the frequency-temperature behaviors in AT-cut quartz crystal resonators(QCRs).First,the dispersion relations of an infinite quartz plate are obtained through a semi-analytical finite element(SA...This study investigates the frequency-temperature behaviors in AT-cut quartz crystal resonators(QCRs).First,the dispersion relations of an infinite quartz plate are obtained through a semi-analytical finite element(SAFE)analysis,which explicitly reveals the intrinsic frequency-temperature dependence of different vibration modes.Subsequently,we address practical resonator configurations by examining finite quartz plates,where numerical simulations uncover critical interactions between the operational thickness-shear(TS)mode and coupling modes,i.e.,the flexure(F),face-shear(FS),and extension(E)modes.Through the frequency spectra analysis,we demonstrate that both the plate aspect ratio and thermal variations affect mode-coupling behaviors.Unstable frequency-temperature variations(activity dips)are observed at critical resonator dimensions.Validation through the free-vibration eigen-frequency analysis and forced-vibration admittance characterization confirms the stable or unstable states predicted by the frequency spectra.The established framework not only reveals the origin of temperatureinduced activity dips but also provides the crucial design criteria for suppressing the mode-coupling interference in high-stability resonators.展开更多
This paper investigates the detection and mitigation of coordinated cyberattacks on Load Frequency Control(LFC)systems integrated with Battery Energy Storage Systems(BESS).As renewable energy sources gain greater pene...This paper investigates the detection and mitigation of coordinated cyberattacks on Load Frequency Control(LFC)systems integrated with Battery Energy Storage Systems(BESS).As renewable energy sources gain greater penetration,power grids are becoming increasingly vulnerable to cyber threats,potentially leading to frequency instability and widespread disruptions.We model two significant attack vectors:load-altering attacks(LAAs)and false data injection attacks(FDIAs)that corrupt frequency measurements.These are analyzed for their impact on grid frequency stability in both linear and nonlinear LFC models,incorporating generation rate constraints and nonlinear loads.A coordinated attack strategy is presented,combining LAAs and FDIAs to achieve stealthiness by concealing frequency deviations from system operators,thereby maximizing disruption while evading traditional detection.To counteract these threats,we propose an Unknown Input Observer(UIO)-based detection framework for linear and nonlinear LFCs.The UIO is designed using linear matrix inequalities(LMIs)to estimate system states while isolating unknown attack inputs,enabling attack detection through monitoring measurement residuals against a predefined threshold.For mitigation,we leverage BESS capabilities with two adaptive strategies:dynamic mitigation for dynamic LAAs,which tunes BESS parameters to enhance the system’s stability margin and accelerate convergence to equilibrium;and staticmitigation for static LAAs and FDIAs.Simulations show that the UIO achieves high detection accuracy,with residuals exceeding thresholds promptly under coordinated attacks,even in nonlinear models.Mitigation strategies reduce frequency deviations by up to 80%compared to unmitigated cases,restoring stability within seconds.展开更多
Objective: To develop an evidence-based plan for cleaning operating room and evaluate the impact on high-frequency contact surfaces. Method: The evidence application model of the JBI Evidence-Based Nursing Center was ...Objective: To develop an evidence-based plan for cleaning operating room and evaluate the impact on high-frequency contact surfaces. Method: The evidence application model of the JBI Evidence-Based Nursing Center was utilized to create a strategy, which was implemented in a tertiary-level hospital in Yunnan Province. The adenosine triphosphate (ATP) biological biofluorescence detection method was used to assess the quality of cleaning before and after the intervention. Results: A total of 17 quality review indicators were established in this study. Following the application of evidence, the implementation rate for 16 quality review indicators increased significantly, from a range of 0-65.8% to 81.5-100%. Moreover, the pass rate of ATP bioluminescence detection on high-frequency contact surfaces increased from 14.07% to 47.19%, with significant difference (p < 0.05). Conclusion: The evidence-based environmental cleaning program proved to enhance the overall cleanliness of operating room and reduce the risk of surgical infections. This strategy holds promise for effective cleaning of operating room.展开更多
The large-scale integration of power electronic interface-based renewable energy with intermittency and uncertainty poses severe challenges for power system secure operation,especially frequency security.Determining t...The large-scale integration of power electronic interface-based renewable energy with intermittency and uncertainty poses severe challenges for power system secure operation,especially frequency security.Determining the system frequency regulation ability under contingency is an open problem.To bridge this gap,a unit commitment(UC)to concentrate solar power considering operational risk and frequency dynamic constraints(RFUC-CSP)is proposed in this paper.A concentrating solar power(CSP)plant with renewable energy characteristics and synchronous units is employed to improve renewable energy utilization and provide frequency support.Firstly,an analytical operational risk model is established to quantify the operational risk under renewable energy integration.Then,the frequency dynamic response characteristic of the system is considered to construct frequency security constraints.A novel RFUC-CSP framework is formulated by incorporating operational risk and frequency security constraints into the UC model,which can allocate operational flexibility of power systems by optimizing the admissible uncertainty level to reduce operational risk.The effectiveness of the proposed RFUC-CSP model is demonstrated by case studies on the modified IEEE 30-bus and IEEE RTS-79 system,and the cost-effectiveness of the CSP plant is quantified.展开更多
基金Supported by National Natural Science Foundation of China(No.82260203).
文摘AIM:To study the relationships between amplitude of low-frequency fluctuations(ALFF)changes and clinical ophthalmic parameters in patients with primary open angle glaucoma(POAG)and analyze the diagnostic value of ALFF.METHODS:Twenty-four POAG patients and 24 healthy controls(HCs)underwent resting-state functional magnetic resonance imaging(rs-fMRI).Nonparametric rank-sum tests were used to compare the ALFF values in the slow-4 and slow-5 bands,and Spearman or Pearson correlation analysis was used to assess the correlation between ALFF changes and clinical ophthalmic parameters in POAG patients.Receiver operating characteristic(ROC)curves were used to evaluate the diagnostic performance of the ALFF.RESULTS:There were 16 males in POAG patients(median age 48y)and 12 males in HCs(median age 39y).Compared with HCs,POAG patients presented increased or decreased ALFF values in different brain regions,and similar changes were observed in mild POAG patients.The ALFF values were correlated with retinal nerve fiber layer(RNFL)thickness,inner limiting membrane-retinal pigment epithelium thickness changes and the degree of visual field defects.Analysis of the diagnostic value of the ALFF via ROC curves revealed that the right medial frontal gyrus[area under the curve(AUC)=0.9063]and superior frontal gyrus(AUC=0.9097)had better diagnostic value than did the optic disc area(AUC=0.8019),visual field index(VFI%,AUC=0.8988)and macular parameters.CONCLUSION:POAG patients present altered cortical function that is significantly correlated with the optic nerve and retinal thickness and had good diagnostic value,which may reflect the underlying neuropathological mechanism of POAG.
基金supported by the National Key Research and Development Program of China(2017YFB0902901)and National Natural Science Foundation of China(51627811).
文摘Increasing penetration of power electronic(PE)grid-tied devices has caused more and more dynamic problems with unknown mechanisms.Since grid operation asks for a certain voltage amplitude and frequency level when there is a power imbalance,roles of the PE grid-tied devices during dynamics must be characterized as internal voltage response under power excitation,in which the voltage vector evolves through its timevarying amplitude and frequency.Existing modeling works,unfortunately,fail to recognize amplitude and frequency modulation essence of grid voltage during dynamics,so corresponding linear models are inapplicable to small-perturbation grid dynamic analysis.Thus,taking current control timescale of grid-tied voltage source converter(VSC)for example,this paper establishes a model with active and reactive current excitation and internal voltage amplitude and frequency response.Especially,the role of the terminal voltage detection-based phase-locked loop(PLL)in the excitation-response relationship is revealed.Linearization is conducted by clarifying amplitude and frequency operating points and corresponding increments of AC signals.This model intuitively reflects the evolution of internal voltage amplitude and frequency excited by active and reactive currents,which represents characteristics of the device during dynamics.Then,simulations for verification of the linear model and time-varying nature of amplitude and frequency are presented.Features of the characteristics of VSC are preliminarily discussed.
基金supported in part by the National Natural Science Fundation of China(52225704 and 52107096).
文摘The dynamics of network power response play a crucial role in system stability.However,the integration of power electronic equipment leads to amplitude and angular frequency(abbreviated as"frequency")time-varying characteristics of the node voltage during dynamic processes.As a result,traditional calcu-lation methods for and characteristics of the power response of the network based on phasor and impe-dance lose their validity.Therefore,this paper undertakes mathematical calculations to reveal the power response of a network under excitation by voltage with time-varying amplitude and frequency(TVAF),relying on the original mathematical relationships and superimposed step response.Then,the multi-timescale characteristics of both the active and reactive power of the network are explored physically.Additionally,this paper reveals a new phenomenon of storing and releasing the active and reactive power of the network.To meet practical engineering requirements,a simplified power expression is presented.Finally,the theoretical analysis is validated through time-domain simulations.
文摘This paper designs a high-frequency stable wireless amplitude modulation(AM)system based on a Pierce circuit.The system utilizes an oscillator and comparator to generate a 20 kHz square wave with an adjustable duty cycle,combined with a 41 MHz carrier wave produced by a passive crystal oscillator Pierce circuit.A 100% modulation index amplitude modulation is achieved through the AD835 multiplier.The modulated signal is amplified by a power amplifier circuit and transmitted wirelessly via the transmitter antenna.Upon reception,the signal undergoes two-stage highfrequency amplification before passing through a Schottky diode envelope detector.The NE5532 shaping circuit then restores the square wave.Experimental results demonstrate reliable 11-meter transmission with carrier frequency deviation<0.75% and demodulation error<1%.
基金supported by the State Grid Corporation of China under Grant for Science and Technology Projects(No.SGNXJYOOZWJS2500029).
文摘Energy storage-equipped photovoltaic(PV-storage)systems can meet frequency regulation requirements under various operating conditions,and their coordinated support for grid frequency has become a future trend.To address frequency stability issues caused by low inertia and weak damping,this paper proposes a multi-timescale frequency regulation coordinated control strategy for PV-storage integrated systems.First,a self-synchronizing control strategy for grid-connected inverters is designed based on DC voltage dynamics,enabling active inertia support while transmitting frequency variation information.Next,an energy storage inertia support control strategy is developed to enhance the frequency nadir,and an active frequency support control strategy for PV system considering a frequency regulation deadband is proposed,where the deadband value is determined based on the power regulation margin of synchronous generators,allowing the PV-storage system to adaptively switch between inertia support and primary frequency regulation under different disturbance conditions.This approach ensures system frequency stability while fully leveraging the regulation capabilities of heterogeneous resources.Finally,the real-time digital simulation results of the PV-storage integrated system demonstrate that,compared to existing control methods,the proposed strategy effectively reduces the rate of change of frequency and improves the frequency nadir under various disturbance scenarios,verifying its effectiveness.
基金supported by the Science and Technology Development Project of Jilin Province(Project No.YDZJ202301ZYTS284).
文摘With the increasing penetration of renewable energy,the coordination of energy storage with thermal power for frequency regulation has become an effective means to enhance grid frequency security.Addressing the challenge of improving the frequency regulation performance of a thermal-storage primary frequency regulation system while reducing its associated losses,this paper proposes a multi-dimensional cooperative optimization strategy for the control parameters of a combined thermal-storage system,considering regulation losses.First,the frequency regulation losses of various components within the thermal power unit are quantified,and a calculation method for energy storage regulation loss is proposed,based on Depth of Discharge(DOD)and C-rate.Second,a thermal-storage cooperative control method based on series compensation is developed to improve the system’s frequency regulation performance.Third,targeting system regulation loss cost and regulation output,and considering constraints on output overshoot and system parameters,an improved Particle Swarm Optimization(PSO)algorithm is employed to tune the parameters of the low-pass filter and the series compensator,thereby reducing regulation losses while enhancing performance.Finally,simulation results demonstrate that the total loss cost of the proposed control strategy is comparable to that of a system with only thermal power participation.However,the thermal power loss cost is reduced by 42.16%compared to the thermal-only case,while simultaneously improving system frequency stability.Thus,the proposed strategy effectively balances system frequency stability and economic efficiency.
基金supported by the National Natural Science Foundation of China(42430303)Strategy Priority Research Program(Category B)of the Chinese Academy of Sciences(XDB0710000)+2 种基金National Natural Science Foundation of China(42288201)the National Key R&D Program of China(2023YFF0803203)the IGGCAS start-up funding(Grant No.E251510101).
文摘In wave-equation migration and demigration,the cross-correlation imaging/forwarding step implicitly injects an additional copy of the source wavelet,so that the amplitude spectrum of the wavelet is applied redundantly(effectively imposing a wavelet-spectrum weighting,often akin to an amplitude-squared bias).This redundancy degrades structural fidelity and amplitude balance yet is frequently overlooked.We(i)formalize the mechanism by which cross-correlation duplicates the source-wavelet amplitude effect in both migration and demigration,and(ii)introduce a source-equalized operator that removes the redundancy by deconvolving(or dividing by)the wavelet amplitude spectrum in the imaging condition and its demigration counterpart,while leaving phase/kinematics intact.Using a band-limited Ricker wavelet on a two-layer model and on Marmousi,we show that,if unmanaged,the redundant wavelet spectrum broadens main lobes,introduces ringing,and suppresses vertical resolution in migrated images,and inflates spectrum mismatches between demigrated and observed data even when peak times agree.With our correction,images recover observed-data-consistent bandwidth and sharpened interfaces,and demigrated data also exhibit improved spectrum conformity and reduced amplitude misfit.The results clarify when source amplitudes matter,why cross-correlation makes them redundantly matter,and how a lightweight spectral correction restores physically meaningful amplitude behavior in wave-equation migration/demigration.
基金State Key Program of National Natural Science of China under grant nos.U19B2016。
文摘Frequency hopping(FH)communication has good anti-fading,anti-jamming and anti-eavesdropping capabilities,so it is one of the main ways to combat electronic jamming.In order to further improve the anti-jamming capability of FH communication,the parameters such as fixed frequency interval,hopping rate and hopping frequency in conventional FH can be assigned with time-varying characteristics.In order to set appropriate hopping parameters to improve the performance of the system in the electromagnetic environment with various types of jamming,a heuristically accelerated Q-learning(HAQL)method is proposed in this paper.Firstly,a theoretical model for the parameter decision-making of FH system is made,and the key parameters affecting the energy efficiency of the system are analyzed.Secondly,a Q-learning model in complex electromagnetic environment is proposed,which includes setting states,actions and rewards,as well as a HAQL-based decisionmaking algorithm is put forward.Lastly,simulations are carried out under different jamming environments,and simulation results show that the average energy efficiency of HAQL algorithm is higher than that of the SARSA algorithm,the e-greedy QL algorithm and the HQL-OSGM algorithm,respectively.
文摘Making full use of the operator ordering method and the integration within ordered products,we obtain the analytical evolution law of a general quadratic state in the amplitude decay channel,and find that it is determined not only by the decay rate of the amplitude decay channel but also by the coefficients of the initial quadratic state.Further,the quantum statistical properties of the initial quadratic state for amplitude decay are investigated via its average photon number and photon-counting distribution,and its Wigner distribution function evolution is discussed in detail.
基金supported in part by the National Natural Science Foundation of China[Grant number 62471075]the Major Science and Technology Project Grant of the Chongqing Municipal Education Commission[Grant number KJZD-M202301901].
文摘Underwater images often affect the effectiveness of underwater visual tasks due to problems such as light scattering,color distortion,and detail blurring,limiting their application performance.Existing underwater image enhancement methods,although they can improve the image quality to some extent,often lead to problems such as detail loss and edge blurring.To address these problems,we propose FENet,an efficient underwater image enhancement method.FENet first obtains three different scales of images by image downsampling and then transforms them into the frequency domain to extract the low-frequency and high-frequency spectra,respectively.Then,a distance mask and a mean mask are constructed based on the distance and magnitude mean for enhancing the high-frequency part,thus improving the image details and enhancing the effect by suppressing the noise in the low-frequency part.Affected by the light scattering of underwater images and the fact that some details are lost if they are directly reduced to the spatial domain after the frequency domain operation.For this reason,we propose a multi-stage residual feature aggregation module,which focuses on detail extraction and effectively avoids information loss caused by global enhancement.Finally,we combine the edge guidance strategy to further enhance the edge details of the image.Experimental results indicate that FENet outperforms current state-of-the-art underwater image enhancement methods in quantitative and qualitative evaluations on multiple publicly available datasets.
基金supported by the National Natural Science Foundation of China(Grant Nos.52222810 and 52178383).
文摘Dynamic disturbances with various frequencies could trigger different failure modes of deep excavations.Superimposed on this static stress are dynamic disturbances due to various dynamic vibrations,e.g.excavation blasting,blasting,tunnel boring machine(TBM)vibration,rockburst wave,earthquakes.Specifically,these dynamic sources are characterized by a wide range of wave frequencies f,resulting in differences in failure modes.A series of true-triaxial compression tests were conducted on granite to simulate the excavation-induced stress path in three-dimensional(3D)stresses.Subsequently,a dynamic disturbance with various frequencies was applied to a cuboid specimen,to reveal the behavior associated with brittle failure.The dynamic disturbance with frequencies f of 5 Hz,10 Hz,and 40 Hz generates less disturbed energy components in the granite together with higher peak strength.However,dynamic disturbances with f of 20 Hz and 30 Hz resulted in a lower peak strength;the peak strength of the rock increases sp albeit it decreases at first,then increases.This U-shaped phenomenon relates to the natural frequency of the granite under such stress conditions.Different rock lithologies consisting of diverse mineral composition,respond differently to each sensitive resonance frequency.Interestingly,the weak disturbance stress with a high frequency f and low amplitude A increases the ratio of crack damage to peak strength(scd/sp)in the granite.This leads to the inhibition of the expansion of the granite during the dynamic disturbance process.Multiple penetrating tensileeshear cracks appear in the s3-direction as the disturbance frequency f increases.
基金supported by China Southern Power Grid Corporation(036000KC23090005(GDKJXM20231027)).
文摘This paper presents a programmable frequency scan algorithm based on harmonic balance.The core idea involves treating systems under perturbation as nonlinear time-periodic(NTP)systems.Steady-state harmonics are first solved via Newton-Raphson iteration through a set of nonlinear equations,and then input-output variables are selected to estimate the linear transfer function of the original NTP system without perturbations.The applications and insights of the proposed algorithm are discussed,particularly in guiding existing frequency scan algorithms,which are restricted by time-domain signal generation or measurement.This improvement is achieved through linear stability analysis of NTP systems with perturbations.
基金supported by the National Natural Science Foundation of China(Grant Nos.52379098,52274075)the Project of Xingliao Talents Program(XLYC2203008)the Science and Technology Program Project of Liaoning Province(2025JH2/101900011).
文摘Understanding how rock slopes respond to blasting loads is crucial for maintaining excavation safety and slope stability.Nevertheless,the spatiotemporal evolution,nonlinear dependence on blasting parameters,and predictive behavior of dominant frequency responses in slope vibrations remain insufficiently understood and quantified.This study combines time-frequency analysis with machine learning to explore how the dominant frequency(f_(d))evolves in slopes under blasting.Continuous Wavelet Transform(CWT)was employed to characterize the temporal-frequency evolution of vibration signals,revealing that the dominant frequency exhibits strong spatial dependence and nonlinear variability influenced by blasting parameters and rock mass structures.Three machine learning models,namely Back Propagation Neural Network(BP),Support Vector Machine(SVM),and Random Forest(RF),were developed to predict f_(d) based on 1,000 monitoring samples obtained from numerical and field simulations.Among them,the RF model achieved the highest prediction accuracy,with mean absolute percentage errors(MAPE)below 15%,demonstrating strong robustness and generalization capability.Our analysis shows that external excitation factors,especially the loading frequency(f_(d)),mainly control the frequency response,while internal controlling factors,such as spatial position,lithological variation,and mechanical heterogeneity,modulate localized frequency amplification and energy redistribution.The results reveal that f_(d) tends to decrease with elevation and distance from the blasting source,whereas structural planes and weathered zones induce high-frequency amplification due to scattering and modal coupling effects.This study offers a new framework combining time-frequency analysis and machine learning to measure the nonlinear interaction between blasting and rock mass response,offering new insights for dynamic stability evaluation and hazard mitigation in complex rock slope systems.
基金supported by ZTE Industry-University-Institute Cooperation Funds under Grant No.IA20240723011National Natural Science Foundation of China under Grant No.62371123+1 种基金Young Elite Scientists Sponsorship Program of the Beijing High Innovation Plan under Grant No.20251077Research Fund of National Mobile Communications Research Laboratory,Southeast University under Grant No.2023A03。
文摘The radio frequency(RF)fingerprint technique is a robust method for security enhancement of the physical layer by leveraging the unique RF imperfections inherent in various wireless devices.Among these imperfections,the carrier frequency offset(CFO)stands out as a primary RF fingerprint(RFF)of the transmitter,offering the potential to distinguish among different transmitters.However,accurately estimating CFO in time-varying channels poses significant challenges due to multipath effects and Doppler shifts.In this paper,we focus on estimating CFO for wireless device identification in the orthogonal frequency division multiplexing(OFDM)communication system.To achieve precise CFO estimation under time-varying channels,we propose a frequency domain correlation and spline interpolation(FCSI)algorithm.This approach utilizes pilots distributed across different subcarriers to correlate with prior local sequences,facilitating accurate CFO estimation.Classification is then performed based on the Euclidean distance between the prior RFF and the tested RFF dataset.Simulation results demonstrate that the proposed Mconsecutive average method effectively reduces the classification error rate in the challenging high-frequency(HF)skywave channel environment.
基金funded by Anhui Province University Key Science and Technology Project(2024AH053415)Anhui Province University Major Science and Technology Project(2024AH040229)+3 种基金Talent Research Initiation Fund Project of Tongling University(2024tlxyrc019)Tongling University School-Level Scientific Research Project(2024tlxyptZD07)TheUniversity Synergy Innovation Programof Anhui Province(GXXT-2023-050)Tongling City Science and Technology Major Special Project(Unveiling and Commanding Model)(200401JB004).
文摘In the image fusion field,fusing infrared images(IRIs)and visible images(VIs)excelled is a key area.The differences between IRIs and VIs make it challenging to fuse both types into a high-quality image.Accordingly,efficiently combining the advantages of both images while overcoming their shortcomings is necessary.To handle this challenge,we developed an end-to-end IRI andVI fusionmethod based on frequency decomposition and enhancement.By applying concepts from frequency domain analysis,we used the layering mechanism to better capture the salient thermal targets from the IRIs and the rich textural information from the VIs,respectively,significantly boosting the image fusion quality and effectiveness.In addition,the backbone network combined Restormer Blocks and Dense Blocks;Restormer blocks utilize global attention to extract shallow features.Meanwhile,Dense Blocks ensure the integration between shallow and deep features,thereby avoiding the loss of shallow attributes.Extensive experiments on TNO and MSRS datasets demonstrated that the suggested method achieved state-of-the-art(SOTA)performance in various metrics:Entropy(EN),Mutual Information(MI),Standard Deviation(SD),The Structural Similarity Index Measure(SSIM),Fusion quality(Qabf),MI of the pixel(FMI_(pixel)),and modified Visual Information Fidelity(VIF_(m)).
基金supported in part by the National Natural Science Foundation of China(62472146)the Key Technologies Research Development Joint Foundation of Henan Province of China(225101610001)。
文摘Deep transfer learning has achieved significant success in anomaly detection over the past decade,but data acquisition challenges in practical engineering hinder high-quality feature representation for few-shot learning tasks.To address this issue,a novel time-frequency-assisted deep feature enhancement(TFE)mechanism is proposed.Unlike traditional methods that integrate time-frequency analysis with deep neural networks,TFE employs a wavelet scattering transform to establish a parallel time-frequency feature space,where a dual interaction strategy facilitates collaboration between deep feature and time-frequency spaces through two operations:1)Enhancement,where a frequency-importance-driven contrastive learning(FICL)network transfers physically-aware information from wavelet scattering features to deep features,and 2)Feedback,which uses a detection rule adaptation module to minimize bias in wavelet scattering features based on deep feature performance.TFE is applied to a domain-adversarial anomaly detection framework and,through alternating training,significantly enhances both deep feature discriminative power and few-shot anomaly detection.Theoretical analysis confirms that the proposed dual interaction strategy reduces the upper bound of classification error.Experiments on benchmark datasets and a real-world industrial dataset from a large steel factory demonstrate TFE's superior performance and highlight the importance of frequency saliency in transfer learning.Thus,collaboration is shown to outperform integration for few-shot transfer learning in anomaly detection.
基金Project supported by the National Key Research and Development Program of China(No.2023YFE0111000)the National Natural Science Foundation of China(Nos.12102183,12172171,and U24A2005)the Shenzhen Science and Technology Program of China(No.JCYJ20230807142004009)。
文摘This study investigates the frequency-temperature behaviors in AT-cut quartz crystal resonators(QCRs).First,the dispersion relations of an infinite quartz plate are obtained through a semi-analytical finite element(SAFE)analysis,which explicitly reveals the intrinsic frequency-temperature dependence of different vibration modes.Subsequently,we address practical resonator configurations by examining finite quartz plates,where numerical simulations uncover critical interactions between the operational thickness-shear(TS)mode and coupling modes,i.e.,the flexure(F),face-shear(FS),and extension(E)modes.Through the frequency spectra analysis,we demonstrate that both the plate aspect ratio and thermal variations affect mode-coupling behaviors.Unstable frequency-temperature variations(activity dips)are observed at critical resonator dimensions.Validation through the free-vibration eigen-frequency analysis and forced-vibration admittance characterization confirms the stable or unstable states predicted by the frequency spectra.The established framework not only reveals the origin of temperatureinduced activity dips but also provides the crucial design criteria for suppressing the mode-coupling interference in high-stability resonators.
基金supported by the Natural Science Foundation of China No.62303126the project Major Scientific and Technological Special Project of Guizhou Province([2024]014).
文摘This paper investigates the detection and mitigation of coordinated cyberattacks on Load Frequency Control(LFC)systems integrated with Battery Energy Storage Systems(BESS).As renewable energy sources gain greater penetration,power grids are becoming increasingly vulnerable to cyber threats,potentially leading to frequency instability and widespread disruptions.We model two significant attack vectors:load-altering attacks(LAAs)and false data injection attacks(FDIAs)that corrupt frequency measurements.These are analyzed for their impact on grid frequency stability in both linear and nonlinear LFC models,incorporating generation rate constraints and nonlinear loads.A coordinated attack strategy is presented,combining LAAs and FDIAs to achieve stealthiness by concealing frequency deviations from system operators,thereby maximizing disruption while evading traditional detection.To counteract these threats,we propose an Unknown Input Observer(UIO)-based detection framework for linear and nonlinear LFCs.The UIO is designed using linear matrix inequalities(LMIs)to estimate system states while isolating unknown attack inputs,enabling attack detection through monitoring measurement residuals against a predefined threshold.For mitigation,we leverage BESS capabilities with two adaptive strategies:dynamic mitigation for dynamic LAAs,which tunes BESS parameters to enhance the system’s stability margin and accelerate convergence to equilibrium;and staticmitigation for static LAAs and FDIAs.Simulations show that the UIO achieves high detection accuracy,with residuals exceeding thresholds promptly under coordinated attacks,even in nonlinear models.Mitigation strategies reduce frequency deviations by up to 80%compared to unmitigated cases,restoring stability within seconds.
文摘Objective: To develop an evidence-based plan for cleaning operating room and evaluate the impact on high-frequency contact surfaces. Method: The evidence application model of the JBI Evidence-Based Nursing Center was utilized to create a strategy, which was implemented in a tertiary-level hospital in Yunnan Province. The adenosine triphosphate (ATP) biological biofluorescence detection method was used to assess the quality of cleaning before and after the intervention. Results: A total of 17 quality review indicators were established in this study. Following the application of evidence, the implementation rate for 16 quality review indicators increased significantly, from a range of 0-65.8% to 81.5-100%. Moreover, the pass rate of ATP bioluminescence detection on high-frequency contact surfaces increased from 14.07% to 47.19%, with significant difference (p < 0.05). Conclusion: The evidence-based environmental cleaning program proved to enhance the overall cleanliness of operating room and reduce the risk of surgical infections. This strategy holds promise for effective cleaning of operating room.
基金supported by the National Natural Science Foundation of China General Program(No.52277106)the Project funded by China Postdoctoral Science Foundation(No.2022M721773).
文摘The large-scale integration of power electronic interface-based renewable energy with intermittency and uncertainty poses severe challenges for power system secure operation,especially frequency security.Determining the system frequency regulation ability under contingency is an open problem.To bridge this gap,a unit commitment(UC)to concentrate solar power considering operational risk and frequency dynamic constraints(RFUC-CSP)is proposed in this paper.A concentrating solar power(CSP)plant with renewable energy characteristics and synchronous units is employed to improve renewable energy utilization and provide frequency support.Firstly,an analytical operational risk model is established to quantify the operational risk under renewable energy integration.Then,the frequency dynamic response characteristic of the system is considered to construct frequency security constraints.A novel RFUC-CSP framework is formulated by incorporating operational risk and frequency security constraints into the UC model,which can allocate operational flexibility of power systems by optimizing the admissible uncertainty level to reduce operational risk.The effectiveness of the proposed RFUC-CSP model is demonstrated by case studies on the modified IEEE 30-bus and IEEE RTS-79 system,and the cost-effectiveness of the CSP plant is quantified.
