期刊文献+
任意字段
题名或关键词
题名
关键词
摘要
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息
共找到2,315篇文章
< 1 2 … 116 >
每页显示 20 50 100
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
显示方式：
A novel small perturbation analytical model to investigate temperature control characteristics of spacecraft thermal systems in frequency domain 认领 引用
1
作者 Yuehang SUN Yunze LI +3 位作者 Yupeng ZHOU Ran WEI Hao DANG Xin ZHAO 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第2期100-114,共15页
This paper introduces a small perturbation frequency domain thermal analysis model based on the nonlinear dynamics model.The model can be applied to study the high-precision temperature control of thermal systems unde... This paper introduces a small perturbation frequency domain thermal analysis model based on the nonlinear dynamics model.The model can be applied to study the high-precision temperature control of thermal systems under low-frequency complex perturbations.The frequency domain characteristics of the space gravitational wave detection satellite are analyzed,and a multi-channel perturbation structure is established.The effects of three kinds of heat flow perturbations,including external heat flow,power generation power,and waste heat of electronic equipment,on the temperature through five transfer paths are investigated.It has been discovered that the waste heat from electronic equipment inside the satellite has the most noticeable effect on the temperature power spectral density of temperature-sensitive optical loads,serving as the primary factor influencing thermal stability.For complex noise signals,the small perturbation analysis method can decompose the different frequency components or ranges,reducing the problem to linearized analysis and simplifying complex calculations.The results indicate that the temperature power spectral density decreases as signal frequency increases,with low-frequency signals exerting a greater influence on temperature stability.The small perturbation analysis method is a novel and effective method for temperature control of space thermal systems,with high accuracy and stability. 展开更多
关键词 Frequency domain analysis Gravitational prospecting Perturbation techniques Power spectral density Temperature control
暂未订购 下载PDF
Use of a Neural Network with a Perturbation Forecast Model to Emulate the Effect of Moist Physics Parameterization 认领 引用
2
作者 FENG Ye-rong XUE Ji-shan +1 位作者 LI Meng-jie XU Dao-sheng 《Journal of Tropical Meteorology》 SCIE CAS CSCD 2026年第2期107-118,共12页
To develop a novel moist physics parameterization scheme,this study analyzed Typhoon Mujigae in the South China Sea.The China Meteorological Administration’s Tropical Region Atmospheric Model System,a regional numeri... To develop a novel moist physics parameterization scheme,this study analyzed Typhoon Mujigae in the South China Sea.The China Meteorological Administration’s Tropical Region Atmospheric Model System,a regional numerical weather prediction model,was run using alternately activated and deactivated conventional moist physics parameterization schemes.The difference between the outputs of these runs formed a dataset used to train a fully connected neural network.This network predicts the temporal tendencies of potential temperature and specific humidity,representing the heating and drying effects of moist physical processes.A perturbation forecast approach was employed to isolate these moist physical effects from the influence of large-scale dynamical processes on heat and moisture transport.The results demonstrate that the trained neural network scheme successfully replicates the heating and drying features,primarily latent heat release,around the typhoon center.It exhibited spatial distributions of heat sources and moisture sinks comparable to those of the conventional scheme.The analysis revealed a key characteristic of typhoon convection:heat sources correspond to moisture sinks.Vertically averaged moisture sinks exceed the heat sources,indicating an excess latent heat release that necessitates balancing by radiative cooling.This study confirmed that a deep-learning moist physics scheme can effectively emulate traditional parameterization schemes,particularly for typhoons. 展开更多
关键词 deep neural network moist physics effect perturbation forecast model regional numerical weather prediction model
暂未订购 下载PDF
Generalized Dual s-Frames and Their Perturbations in S-Hilbert Spaces 认领 引用
3
作者 Fu Yanling Bai Xiaobei Tian Yu 《Journal of Mathematical Research with Applications》 CSCD 2026年第4期527-545,共19页
Soft Hilbert spaces(S-Hilbert spaces for short)play an important role in the field of mathematical modeling and decision-making,which has received widespread attention.This article addresses the dual soft frame(s-fram... Soft Hilbert spaces(S-Hilbert spaces for short)play an important role in the field of mathematical modeling and decision-making,which has received widespread attention.This article addresses the dual soft frame(s-frame for short)theory in S-Hilbert spaces.We introduce the notion of generalized dual s-frames(dual s-frames and approximately dual s-frames)in SHilbert spaces and our motivation is to seek their applications in decision-making.We prove that a pair of generalized dual s-frames may induce a pair of dual s-frames,and obtain that generalized dual s-frames have a preservation effect under the action of a pair of invertible operators.We propose a method for constructing more generalized dual s-frames from known ones,and find that the best generalized dual of an s-frame is the canonical dual.Finally,we investigate the perturbation-stability properties of generalized dual s-frames. 展开更多
关键词 soft Hilbert space dual soft frame generalized dual perturbation
暂未订购 下载PDF
Brief comments on“Perturbation response scanning of drug-target networks:Drug repurposing for multiple sclerosis” 认领 引用
4
作者 Alessandro Giuliani 《Journal of Pharmaceutical Analysis》 SCIE CAS CSCD 2026年第1期1-2,共2页
The recent Nobel prizes in Physics to Giorgio Parisi,Geoffrey Hinton,and John Hopfield,officially proclaimed a deep epistemological change:the unity of different sciences is no more considered to stem from the fact t... The recent Nobel prizes in Physics to Giorgio Parisi,Geoffrey Hinton,and John Hopfield,officially proclaimed a deep epistemological change:the unity of different sciences is no more considered to stem from the fact that‘any entity is made by the same basic bricks’but on the recognition than‘any entity can be represented as a set of mutually interacting parts’.That is to say that any system[1]can be formalized as a‘network of interactions among its elements’. 展开更多
关键词 drug repurposing interactions its elements unity different sciences perturbation response scanning mutually interacting parts drug target networks multiple sclerosis deep epistemological change
暂未订购 下载PDF
MIXED LOCAL-NONLOCAL QUASILINEAR PROBLEMS WITH CRITICAL GROWTH AND LOGARITHMIC PERTURBATION 认领 引用
5
作者 Aliang XIA 《Acta Mathematica Scientia》 SCIE CSCD 2026年第3期1269-1286,共18页
In this paper,we investigate the existence of weak solutions for a class of critical quasilinear problems involving an operator of mixed order obtained by the sum of a classical p-Laplacian and a fractional p-Laplacia... In this paper,we investigate the existence of weak solutions for a class of critical quasilinear problems involving an operator of mixed order obtained by the sum of a classical p-Laplacian and a fractional p-Laplacian,and with logarithmic perturbation termμ∣u∣q-2u log∣u∣q.Forμ∈R\{0},we obtain the existence and multiplicity of nontrivial weak solutions subject to certain conditions on the exponent q and the sign of parameterμ.Due to the sign∣u∣q-2u log∣u∣qbeing uncertain,some more detailed analysis will eventually be needed. 展开更多
关键词 operators of mixed order p-Laplacian critical exponents logarithmic perturbation
暂未订购 下载PDF
BOUT++simulation study of turbulence transport during n=4 resonant magnetic perturbation induced edge localized mode suppression phase in EAST 认领 引用
6
作者 Ziming Zhen Taihao Huang +10 位作者 Yuchen Xu Hui Sheng Tianyuan Liu Xueruoqi Liang Manni Jia Xuemin Wu Shifeng Mao Yanlong Li Tianyang Xia Youwen Sun Minyou Ye 《Chinese Physics B》 SCIE EI CAS CSCD 2026年第4期484-494,共11页
The effect of the resonant magnetic perturbation(RMP)on the turbulence transport during the edge localized mode(ELM)suppression phase is investigated by the BOUT++six-field two-fluid simulations.Based on the edge plas... The effect of the resonant magnetic perturbation(RMP)on the turbulence transport during the edge localized mode(ELM)suppression phase is investigated by the BOUT++six-field two-fluid simulations.Based on the edge plasma profiles during the ELM suppression phase in EAST experiment with n=4 RMP(n is the toroidal mode number),the plasma response field is calculated using CLTx and introduced in the BOUT++simulation.Compared with the case without RMP,the simulated flux-surface averaged radial particle flux at the position of peak pressure gradient increases to~1.5 times for the case with RMP,which is close to the estimated particle flux according to the experimental plasma profiles.It implies that the turbulence transport could have a dominating contribution to the radial transport for maintaining the pedestal density profile during ELM suppression phase after density pump-out,especially when the stochasticity of the magnetic field is not significant in the pedestal region.The increase in the radial particle flux for the case with RMP is due to the significant increase in electric drift flux,which is partly offset by the magnetic flutter flux.The enhancement of the turbulent electric drift flux is mainly due to the enhanced density and electric potential perturbations.The change in the phase difference between them further enhances the contributions of the medium-n modes and suppresses the contribution of the low-n modes.Further complexity-entropy analysis indicates that the turbulence is more stochastic,which could be related to the enhanced mode-mode coupling due to RMP effect. 展开更多
关键词 pedestal resonant magnetic perturbation density pump-out turbulent transport BOUT++
暂未订购 下载PDF
Adversarial Example Transfer Method for Vision-Language Pre-Training Models Based on Negative Sample Feature Perturbation 认领 引用
7
作者 Zhichao Pei Ou Ye +1 位作者 Panyu Yang Kaiwen He 《Computers, Materials & Continua》 SCIE EI 2026年第8期1201-1221,共21页
To address the issue of insufficient transferability of existing adversarial example generation methods for vision-language pre-training(VLP)models,this paper proposes an adversarial example transfer method for VLP mo... To address the issue of insufficient transferability of existing adversarial example generation methods for vision-language pre-training(VLP)models,this paper proposes an adversarial example transfer method for VLP models based on negative sample feature perturbation.First,a novel cross-modal collaborative perturbation strategy is constructed.By introducing negative samples into the cross-modal perturbation mechanism,the strategy explores more perturbation directions,breaks the original modal alignment constraints and avoids the local focus of adversarial perturbations.Then,to reduce the computational cost,a dynamic threshold attack strategy is built to measure the modal similarity of the generated adversarial examples.Finally,with the help of a multi-modal fusion encoder,a cross-modal fusion semantic attack(CFSA)module is designed.This module extracts the middle-layer features of image-text pairs and improves the transfer attack effect of adversarial examples.The proposed attack method is experimentally evaluated on the Flickr30K and MSCOCO datasets.The results show that for the adversarial examples generated on the Flickr30K dataset,the attack success rate(ASR)of the proposed method reaches up to 95.3%on multiple black-box models;for those generated on the MSCOCO dataset,the maximum attack success rate on multiple black-box models reaches 70.17%.Compared with the current methods,the adversarial examples generated by the proposed method achieve better attack performance. 展开更多
关键词 Vision-language pre-training model multimodal adversarial attack transferability cross-modality perturbation negative samples
暂未订购 下载PDF
Physics-informed neural networks with Poincaré-Lighthill-Kuo method for singular perturbation problems 认领 引用
8
作者 Qingyong Luo Lei Zhang Guowei He 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第6期211-222,共12页
Physics-informed neural networks(PINNs)have recently emerged as a powerful tool to solve differential equations for nonlinear mechanics.However,PINNs struggle with singular perturbation problems due to their locally a... Physics-informed neural networks(PINNs)have recently emerged as a powerful tool to solve differential equations for nonlinear mechanics.However,PINNs struggle with singular perturbation problems due to their locally abrupt behavior and singularities.The Poincaré-Lighthill-Kuo(PLK)method has been efficiently used to address these problems by applying perturbation expansions to both dependent and independent variables.This paper proposes a combination of the PLK method and PINNs,termed PLK-PINNs.The PLK-PINNs employ a parametric expression through two neural networks:one representing the mapping from parametric variables to independent variables,and the other approximating the solution of dependent variables with respect to parametric variables.Moreover,an auxiliary loss term is proposed to constrain the Jacobian determinant of the mapping within a constant sign interval to ensure the bijectivity of the mapping.The effectiveness of the proposed method is demonstrated through tests on typical singularity-shift and secular-term problems,with conventional PINNs in comparison. 展开更多
关键词 Physics-informed neural networks Singular perturbation problems Poincaré-Lighthill-Kuo method Parametric expressions
暂未订购 下载PDF
Differentially Private Stochastic Gradient Descent with Vertical Gradient Perturbation and Selective Updates 认领 引用
9
作者 Li Xiaoye Zhao Wei +1 位作者 Sun Zhenlong Yuan Yuan 《China Communications》 SCIE EI CSCD 2026年第6期181-195,共15页
In the process of minimizing the training loss of machine learning model pursuit,it is very easy to inadvertently remember sensitive private data,which leads to data reconstruction,member reasoning attacks and other s... In the process of minimizing the training loss of machine learning model pursuit,it is very easy to inadvertently remember sensitive private data,which leads to data reconstruction,member reasoning attacks and other security problems.In order to mitigate these risks,differentiated privacy has become a key standard for privacy preserving machine learning.The classical differential privacy depth learning algorithm,differential privacy stochastic gradient descent(DP-SGD),that adapts the standard stochastic gradient descent(SGD)algorithm to incorporate differential privacy,ensuring that the trained model doesn’t reveal sensitive information about individual training data points.However,DP-SGD has the problems of slow convergence speed and large utility loss.We propose an effective solution that is the cooperative combination of selective updating and early vertical gradient disturbance.Selective updating ensures that the training track of the model is aligned with the optimal direction,significantly accelerating convergence.Subsequently,the application of vertical gradient perturbation ensures that the model with significantly improved accuracy can be achieved even under strict privacy constraints(small privacy budget).Through theoretical analysis and a large number of experiments,this paper proves that DP-VGPSU has superior performance in convergence speed and accuracy. 展开更多
关键词 deep learning differential privacy selective updates stochastic gradient descent vertical gradients perturbation
暂未订购 下载PDF
Dynamics of Electric Field Perturbation in Gold Nanobipyramids During Dual-Pulse Two-Photon Coherent Excitation 认领 引用
10
作者 Qiong Li Yao Li 《Journal of Electronic Research and Application》 2026年第3期141-147,共7页
Optical-based microwave electric field detection has emerged as a research hotspot due to its advantages of high spatial resolution and immunity to electromagnetic interference.However,existing techniques are often li... Optical-based microwave electric field detection has emerged as a research hotspot due to its advantages of high spatial resolution and immunity to electromagnetic interference.However,existing techniques are often limited by their sensitivity or reliance on specialized fluorescent materials.Gold nanobipyramids(AuNBPs),serving as nanoprobes with tip-enhancement effects and a well-defined three-level system,exhibit high sensitivity in their two-photon photoluminescence(TPPL)process to phase perturbations and plasmon resonance changes induced by microwave fields.By establishing a quantitative mapping model between microwave intensity and TPPL signal strength,we achieved an absolute measurement of microwave field strength with a spatial resolution that breaks the 100-nanometer barrier.Through comparative analysis of microwave responses under different pulse delays,we reveal that the microwave field primarily modulates TPPL intensity by interfering with the coherent excitation pathway.The most significant response of TPPL intensity to microwave power was observed near the zero-delay point,where the quantum coherence is strongest. 展开更多
关键词 Two-photon photoluminescence Dual-pulse coherent excitation Gold nanobipyramids Microwave electric field perturbation
暂未订购 下载PDF
A Comparison of the Practical Predictability of Hail with Initial Perturbations of Climatological and Flow-Dependent Uncertainty in Ensembles 认领 引用
11
作者 Xiaofei LI 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2025年第7期1349-1364,共16页
The practical predictability of hail precipitation rates is significantly influenced by initial meteorological perturbations,stemming from various uncertainty sources.This study thoroughly assessed the predictability ... The practical predictability of hail precipitation rates is significantly influenced by initial meteorological perturbations,stemming from various uncertainty sources.This study thoroughly assessed the predictability of hail precipitation rates in both climatologically and flow-dependent perturbed ensembles(CEns and FEns).These ensembles incorporated initial meteorological uncertainties derived separately from two operational ensembles.Leveraging the Weather Research and Forecasting model,we conducted cloud-resolving simulations of an idealized hailstorm.The practical predictability of hail responded comparably to both climatological and flow-dependent uncertainties,which was revealed across the entire ensemble of 50 members.However,a notable difference emerged when comparing the peak hail precipitation rates among the top 10 and bottom 10 members.From a thermodynamic perspective,the primary source of uncertainty in hail precipitation lay in the significant variations in temperature stratification,particularly at-20℃and-40℃.On the microphysical front,perturbations within CEns generated greater uncertainty in the process of rainwater collection by hail,contributing significantly to the microphysical growth mechanisms of hail.Furthermore,the findings reveal a stronger dependency of hail precipitation uncertainty on thermodynamic perturbations compared to kinematic perturbations.These insights enhance the comprehension of the practical predictability of hail and contribute significantly to the understanding of ensemble forecasting for hail events. 展开更多
关键词 hail predictability uncertainty climatological perturbation flow-dependent perturbation
暂未订购 下载PDF
Thermoporoelastic stress perturbations from hydraulic fracturing and thermal depletion in enhanced geothermal systems(EGS)and implications for fault reactivation and seismicity 认领 引用 被引量：2
12
作者 Mengke An Rui Huang +2 位作者 Derek Elsworth Fengshou Zhang Egor Dontsov 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2025年第5期2893-2903,共11页
Hydraulic fracturing then fluid circulation in enhanced geothermal system(EGS)reservoirs have been shown to induce seismicity remote from the stimulation-potentially generated by the distal projection of thermoporoela... Hydraulic fracturing then fluid circulation in enhanced geothermal system(EGS)reservoirs have been shown to induce seismicity remote from the stimulation-potentially generated by the distal projection of thermoporoelastic stresses.We explore this phenomenon by evaluating stress perturbations resulting from stimulation of a single stage of hydraulic fracturing that is followed by thermal depletion of a prismatic zone adjacent to the hydraulic fracture.We use Coulomb failure stress to assess the effect of resulting stress perturbations on instability on adjacent critically-stressed faults.Results show that hydraulic fracturing in a single stage is capable of creating stress perturbations at distances to 1000 m that reach 10-5-10-4MPa.At a closer distance,the magnitude of stress perturbations increases even further.The stress perturbation induced by temperature depletion could also reach 10-3-10-2MPa within 1000 m-much higher than that by hydraulic fracturing.Considering that a critical change in Coulomb failure stress for fault instability is 10-2MPa,a single stage of hydraulic fracturing and thermal drawdown are capable of reactivating critically-stressed faults at distances within 200 m and 1000 m,respectively.These results have important implications for understanding the distribution and magnitudes of stress perturbations driven by thermoporoelastic effects and the associated seismicity during the simulation and early production of EGS reservoirs. 展开更多
关键词 Thermoporoelastic stress perturbations Hot-dry rock Enhanced geothermal system Hydraulic fracturing Thermal depletion Fault instability
暂未订购 下载PDF
Perturbation response scanning of drug-target networks:Drug repurposing for multiple sclerosis 认领 引用 被引量：2
13
作者 Yitan Lu Ziyun Zhou +10 位作者 Qi Li Bin Yang Xing Xu Yu Zhu Mengjun Xie Yuwan Qi Fei Xiao Wenying Yan Zhongjie Liang Qifei Cong Guang Hu 《Journal of Pharmaceutical Analysis》 SCIE CAS CSCD 2025年第6期1277-1290,共14页
Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-targe... Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-target networks(DTNs),which could provide a promising avenue in network medicine.We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework,for drug repurposing of multiple sclerosis(MS).First,the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes.Then,based on topological analysis and functional annotation,the neurotransmission module was identified as the“therapeutic module”of MS.Further,perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis,giving a list of repurposable drugs for MS.Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of se-rotonin 2B receptor(HTR2B).Finally,we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex.These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS.As a useful systematic method,our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases. 展开更多
关键词 Network perturbations Mechanism of action Multiple sclerosis HTR2B
暂未订购 下载PDF
An Extension of Conditional Nonlinear Optimal Perturbation in the Time Dimension and Its Applications in Targeted Observations 认领 引用 被引量：1
14
作者 Ziqing ZU Mu MU +1 位作者 Jiangjiang XIA Qiang WANG 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2025年第9期1783-1797,共15页
The Conditional Nonlinear Optimal Perturbation(CNOP)method works essentially for conventional numerical models;however,it is not fully applicable to the commonly used deep-learning forecasting models(DLMs),which typic... The Conditional Nonlinear Optimal Perturbation(CNOP)method works essentially for conventional numerical models;however,it is not fully applicable to the commonly used deep-learning forecasting models(DLMs),which typically input multiple time slices without deterministic dependencies.In this study,the CNOP for DLMs(CNOP-DL)is proposed as an extension of the CNOP in the time dimension.This method is useful for targeted observations as it indicates not only where but also when to deploy additional observations.The CNOP-DL is calculated for a forecast case of sea surface temperature in the South China Sea with a DLM.The CNOP-DL identifies a sensitive area northwest of Palawan Island at the last input time.Sensitivity experiments demonstrate that the sensitive area identified by the CNOP-DL is effective not only for the CNOP-DL itself,but also for random perturbations.Therefore,this approach holds potential for guiding practical field campaigns.Notably,forecast errors are more sensitive to time than to location in the sensitive area.It highlights the crucial role of identifying the time of the sensitive area in targeted observations,corroborating the usefulness of extending the CNOP in the time dimension. 展开更多
关键词 deep-learning forecasting model conditional nonlinear optimal perturbation targeted observation sensitive area
暂未订购 下载PDF
Bridging the Gap Between Individual and Universal Adversarial Perturbations 认领 引用
15
作者 Li Yanchun Li Zemin +2 位作者 Zeng Li Zhu Jiang Song Jingkuan 《China Communications》 SCIE EI CSCD 2025年第9期244-263,共20页
In recent years,universal adversarial per-turbation(UAP)has attracted the attention of many re-searchers due to its good generalization.However,in order to generate an appropriate UAP,current methods usually require e... In recent years,universal adversarial per-turbation(UAP)has attracted the attention of many re-searchers due to its good generalization.However,in order to generate an appropriate UAP,current methods usually require either accessing the original dataset or meticulously constructing optimization functions and proxy datasets.In this paper,we aim to elimi-nate any dependency on proxy datasets and explore a method for generating Universal Adversarial Pertur-bations(UAP)on a single image.After revisiting re-search on UAP,we discovered that the key to gener-ating UAP lies in the accumulation of Individual Ad-versarial Perturbation(IAP)gradient,which prompted us to study the method of accumulating gradients from an IAP.We designed a simple and effective process to generate UAP,which only includes three steps:pre-cessing,generating an IAP and scaling the perturba-tions.Through our proposed process,any IAP gener-ated on an image can be constructed into a UAP with comparable performance,indicating that UAP can be generated free of data.Extensive experiments on var-ious classifiers and attack approaches demonstrate the superiority of our method on efficiency and aggressiveness. 展开更多
关键词 black-box attack data-independent transferability universal adversarial perturbation
暂未订购 下载PDF
A renormalization method without spectrum theory for the perturbation of solitons 认领 引用
16
作者 Cheng-shi Liu 《Communications in Theoretical Physics》 SCIE CAS CSCD 2025年第10期15-21,共7页
A direct renormalization method without spectrum theory is proposed to compute the perturbation of solitons in nearly integrable systems with multiple small parameters.The evolution equations of these parameters in un... A direct renormalization method without spectrum theory is proposed to compute the perturbation of solitons in nearly integrable systems with multiple small parameters.The evolution equations of these parameters in unperturbed solitons are obtained as the renormalization equations.Compared with routine methods,the advantages of the renormalization method are that the formulation is only based on a clear and simple mathematical theory,namely the Taylor expansion at a general point,the secular terms in perturbation series are eliminated automatically,any priori physical assumption on the form of the solution is avoided,multiple time scales arise naturally from the final naive perturbation expansion,and the Green’s function and corresponding spectrum of linear differential operators are not needed.As applications,the perturbation of solitons for KDV,MKdV and nonlinear Schrodinger equations,are obtained. 展开更多
关键词 soliton perturbation renormalization method asymptotic analysis nearly integrable system perturbation theory
暂未订购 下载PDF
Global Ensemble Weather Prediction from a Deep Learning–Based Model(Pangu-Weather)with the Initial Condition Perturbations of CMA-GEPS 认领 引用
17
作者 Xin LIU Jing CHEN +6 位作者 Yuejian ZHU Yongzhu LIU Fajing CHEN Zhenhua HUO Fei PENG Yanan MA Yuhang GONG 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2025年第8期1636-1660,共25页
Pangu-Weather(PGW),trained with deep learning–based methods(DL-based model),shows significant potential for global medium-range weather forecasting.However,the interpretability and trustworthiness of global medium-ra... Pangu-Weather(PGW),trained with deep learning–based methods(DL-based model),shows significant potential for global medium-range weather forecasting.However,the interpretability and trustworthiness of global medium-range DLbased models raise many concerns.This study uses the singular vector(SV)initial condition(IC)perturbations of the China Meteorological Administration's Global Ensemble Prediction System(CMA-GEPS)as inputs of PGW for global ensemble prediction(PGW-GEPS)to investigate the ensemble forecast sensitivity of DL-based models to the IC errors.Meanwhile,the CMA-GEPS forecasts serve as benchmarks for comparison and verification.The spatial structures and prediction performance of PGW-GEPS are discussed and compared to CMA-GEPS based on seasonal ensemble experiments.The results show that the ensemble mean and dispersion of PGW-GEPS are similar to those of CMA-GEPS in the medium range but with smoother forecasts.Meanwhile,PGW-GEPS is sensitive to the SV IC perturbations.Specifically,PGWGEPS can generate realistic ensemble spread beyond the sub-synoptic scale(wavenumbers≤64)with SV IC perturbations.However,PGW's kinetic energy is significantly reduced at the sub-synoptic scale,leading to error growth behavior inconsistent with CMA-GEPS at that scale.Thus,this behavior indicates that the effective resolution of PGW-GEPS is beyond the sub-synoptic scale and is limited to predicting mesoscale atmospheric motions.In terms of the global mediumrange ensemble prediction performance,the probability prediction skill of PGW-GEPS is comparable to CMA-GEPS in the extratropic when they use the same IC perturbations.That means that PGW has a general ability to provide skillful global medium-range forecasts with different ICs from numerical weather prediction. 展开更多
关键词 deep learning ensemble prediction forecast uncertainty initial condition perturbations CMA-GEPS Pangu-Weather
暂未订购 下载PDF
Numerical Simulation via Homotopy Perturbation Approach of a Dissipative Squeezed Carreau Fluid Flow Due to a Sensor Surface 认领 引用
18
作者 Sara I.Abdelsalam W.Abbas +2 位作者 Ahmed M.Megahed Hassan M.H.Sadek M.S.Emam 《Frontiers in Heat and Mass Transfer》 EI CAS 2025年第5期1511-1527,共17页
This study rigorously examines the interplay between viscous dissipation,magnetic effects,and thermal radiation on the flow behavior of a non-Newtonian Carreau squeezed fluid passing by a sensor surface within a micro... This study rigorously examines the interplay between viscous dissipation,magnetic effects,and thermal radiation on the flow behavior of a non-Newtonian Carreau squeezed fluid passing by a sensor surface within a micro cantilever channel,aiming to deepen our understanding of heat transport processes in complex fluid dynamics scenarios.The primary objective is to elucidate how physical operational parameters influence both the velocity of fluid flow and its temperature distribution,utilizing a comprehensive numerical approach.Employing a combination of mathematical modeling techniques,including similarity transformation,this investigation transforms complex partial differential equations into more manageable ordinary ones,subsequently solving them using the homotopy perturbation method.By analyzing the obtained solutions and presenting them graphically,alongside detailed analysis,the study sheds light on the pivotal role of significant parameters in shaping fluid movement and energy distribution.Noteworthy observations reveal a substantial increase in fluid velocity with escalating magnetic parameters,while conversely,a contrasting trend emerges in the temperature distribution,highlighting the intricate relationship between magnetic effects,flow dynamics,and thermal behavior in non-Newtonian fluids.Further,the suction velocity enhance both the local skin friction and Nusselt numbers,whereas theWeissenberg number reduces them,opposite to the effect of the power-law index. 展开更多
关键词 Homotopy perturbation method squeezed flow Carreau fluid sensor surface magnetic field viscous dissipation
暂未订购 下载PDF
Influence of 3D helical magnetic perturbations on runaway electron generation in J-TEXT tokamak 认领 引用
19
作者 Wei YAN Guinan ZOU +22 位作者 Zhongyong CHEN You LI Jiangang FANG Zhifang LIN Zhonghe JIANG Nengchao WANG Bo RAO Yangbo LI Zhengkang REN Chuanxu ZHAO Yu ZHONG Fanxi LIU Yinlong YU Zisen NIE Xun ZHOU Yuan SHENG Yuwei SUN Song ZHOU Xiaoqing ZHANG Zhoujun YANG Zhipeng CHEN Yonghua DING the J-TEXT Team 《Plasma Science and Technology》 SCIE EI CSCD 2025年第3期36-44,共9页
A large number of runaway electrons(REs)generated during disruption can cause significant damage to next-generation large-scale tokamaks.The influence of three-dimensional(3D)helical magnetic perturbations on the supp... A large number of runaway electrons(REs)generated during disruption can cause significant damage to next-generation large-scale tokamaks.The influence of three-dimensional(3D)helical magnetic perturbations on the suppression of RE generation was explored using a set of 3D helical coils in J-TEXT tokamak,which can excite m=-2/2 helical magnetic perturbations.Experimental evidence shows that the-2/2 magnetic perturbations caused by the opposite coil current direct plasma toward the high-field side,simultaneously enhancing the magnetic fluctuations,which would enhance the radial loss of REs and even prevent RE generation.On the other hand,-2/2 magnetic perturbations can also reduce the cooling time during the disruption phase and generate a population of high-energy REs,which can interact with high-frequency magnetic fluctuations and in turn suppress RE generation.The critical helical coil current was found to correlate with electron density,requiring higher coil currents at higher densities.According to the statistical analysis of RE generation at different electron densities,the applied-2/2 magnetic perturbations can increase the magnetic fluctuations to the same level at lower electron densities,which can decrease the threshold electron density for RE suppression.This will be beneficial for RE mitigation in future large tokamak devices. 展开更多
关键词 3D helical magnetic perturbations runaway electron J-TEXT tokamak
暂未订购 下载PDF
Adversarial Perturbation for Sensor Data Anonymization: Balancing Privacy and Utility 认领 引用
20
作者 Tatsuhito Hasegawa Kyosuke Fujino 《Computers, Materials & Continua》 SCIE EI 2025年第8期2429-2454,共26页
Recent advances in wearable devices have enabled large-scale collection of sensor data across healthcare,sports,and other domains but this has also raised critical privacy concerns,especially under tightening regulati... Recent advances in wearable devices have enabled large-scale collection of sensor data across healthcare,sports,and other domains but this has also raised critical privacy concerns,especially under tightening regulations such as the General Data Protection Regulation(GDPR),which explicitly restrict the processing of data that can re-identify individuals.Although existing anonymization approaches such as the AnonymizingAutoEncoder(AAE)can reduce the risk of re-identification,they often introduce substantial waveform distortions and fail to preserve information beyond a single classification task(e.g.,human activity recognition).This study proposes a novel sensor data anonymization method based onAdversarial Perturbations(AP)to address these limitations.By generating minimal yet targeted noise,the proposed method significantly degrades the accuracy of identity classification while retaining essential features for multiple tasks such as activity,gender,or device-position recognition.Moreover,to enhance robustness against frequency-domain analysis,additional models trained on transformed(e.g.,short-time Fourier transform(STFT))representations are incorporated into the perturbation process.A multi-task formulation is introduced that selectively suppresses person-identifying features while reinforcing those relevant to other desired tasks without retraining large autoencoder-based architectures.The proposed framework is,to our knowledge,the first AP-based anonymization technique that(i)defends simultaneously against time-and frequency-domain attacks and(ii)allows per-task trade-off control on a single forward-back-propagation run,enabling real-time,on-device deployment on commodity hardware.On three public datasets,the proposed method reduces person-identification accuracy from 60–90%to near-chance levels(≤5%)while preserving the original activity-recognition F1 both in the time and frequency domains.Compared with the baseline AAE,the proposed method improves downstream task F1 and lowers waveform mean squared error,demonstrating a better privacy-utility trade-off without additional model retraining.These findings underscore the effectiveness and flexibility of AP in privacy-preserving sensor-data processing,offering a practical solution that safeguards user identity while retaining rich,application-critical information. 展开更多
关键词 Human activity recognition privacy-aware IoT adversarial perturbation
暂未订购 下载PDF
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
上一页 1 2 … 116 下一页 到第 页
在线咨询 使用帮助 返回顶部 意见反馈