Transfer-based Adversarial Attacks(TAAs)can deceive a victim model even without prior knowledge.This is achieved by leveraging the property of adversarial examples.That is,when generated from a surrogate model,they re...Transfer-based Adversarial Attacks(TAAs)can deceive a victim model even without prior knowledge.This is achieved by leveraging the property of adversarial examples.That is,when generated from a surrogate model,they retain their features if applied to other models due to their good transferability.However,adversarial examples often exhibit overfitting,as they are tailored to exploit the particular architecture and feature representation of source models.Consequently,when attempting black-box transfer attacks on different target models,their effectiveness is decreased.To solve this problem,this study proposes an approach based on a Regularized Constrained Feature Layer(RCFL).The proposed method first uses regularization constraints to attenuate the initial examples of low-frequency components.Perturbations are then added to a pre-specified layer of the source model using the back-propagation technique,in order to modify the original adversarial examples.Afterward,a regularized loss function is used to enhance the black-box transferability between different target models.The proposed method is finally tested on the ImageNet,CIFAR-100,and Stanford Car datasets with various target models,The obtained results demonstrate that it achieves a significantly higher transfer-based adversarial attack success rate compared with baseline techniques.展开更多
Full waveform inversion(FWI)is a complex data fitting process based on full wavefield modeling,aiming to quantitatively reconstruct unknown model parameters from partial waveform data with high-resolution.However,this...Full waveform inversion(FWI)is a complex data fitting process based on full wavefield modeling,aiming to quantitatively reconstruct unknown model parameters from partial waveform data with high-resolution.However,this process is highly nonlinear and ill-posed,therefore achieving high-resolution imaging of complex biological tissues within a limited number of iterations remains challenging.We propose a multiscale frequency–domain full waveform inversion(FDFWI)framework for ultrasound computed tomography(USCT)imaging of biological tissues,which innovatively incorporates Sobolev space norm regularization for enhancement of prior information.Specifically,we investigate the effect of different types of hyperparameter on the imaging quality,during which the regularization weight is dynamically adapted based on the ratio of the regularization term to the data fidelity term.This strategy reduces reliance on predefined hyperparameters,ensuring robust inversion performance.The inversion results from both numerical and experimental tests(i.e.,numerical breast,thigh,and ex vivo pork-belly tissue)demonstrate the effectiveness of our regularized FWI strategy.These findings will contribute to the application of the FWI technique in quantitative imaging based on USCT and make USCT possible to be another high-resolution imaging method after x-ray computed tomography and magnetic resonance imaging.展开更多
Dear Editor,This letter explores optimal formation control for a network of unmanned surface vessels(USVs).By designing an individual objective function for each USV,the optimal formation problem is transformed into a...Dear Editor,This letter explores optimal formation control for a network of unmanned surface vessels(USVs).By designing an individual objective function for each USV,the optimal formation problem is transformed into a noncooperative game.Under this game theoretic framework,the optimal formation is achieved by seeking the Nash equilibrium of the regularized game.A modular structure consisting of a distributed Nash equilibrium seeker and a regulator is proposed.展开更多
The selection of hyperparameters in regularized least squares plays an important role in large-scale system identification. The traditional methods for selecting hyperparameters are based on experience or marginal lik...The selection of hyperparameters in regularized least squares plays an important role in large-scale system identification. The traditional methods for selecting hyperparameters are based on experience or marginal likelihood maximization method, which are inaccurate or computationally expensive. In this paper, two posterior methods are proposed to select hyperparameters based on different prior knowledge (constraints), which can obtain the optimal hyperparameters using the optimization theory. Moreover, we also give the theoretical optimal constraints, and verify its effectiveness. Numerical simulation shows that the hyperparameters and parameter vector estimate obtained by the proposed methods are the optimal ones.展开更多
Dynamic mode decomposition(DMD) aims at extracting intrinsic mechanisms in a time sequence via linear recurrence relation of its observables, thereby predicting later terms in the sequence. Stability is a major concer...Dynamic mode decomposition(DMD) aims at extracting intrinsic mechanisms in a time sequence via linear recurrence relation of its observables, thereby predicting later terms in the sequence. Stability is a major concern in DMD predictions. We adopt a regularized form and propose a Regularized DMD(Re DMD) algorithm to determine the regularization parameter. This leverages stability and accuracy. Numerical tests for Burgers' equation demonstrate that Re DMD effectively stabilizes the DMD prediction while maintaining accuracy. Comparisons are made with the truncated DMD algorithm.展开更多
In this paper,we study the three-dimensional regularized MHD equations with fractional Laplacians in the dissipative and diffusive terms.We establish the global existence of mild solutions to this system with small in...In this paper,we study the three-dimensional regularized MHD equations with fractional Laplacians in the dissipative and diffusive terms.We establish the global existence of mild solutions to this system with small initial data.In addition,we also obtain the Gevrey class regularity and the temporal decay rate of the solution.展开更多
The existing multi-view subspace clustering algorithms based on tensor singular value decomposition(t-SVD)predominantly utilize tensor nuclear norm to explore the intra view correlation between views of the same sampl...The existing multi-view subspace clustering algorithms based on tensor singular value decomposition(t-SVD)predominantly utilize tensor nuclear norm to explore the intra view correlation between views of the same samples,while neglecting the correlation among the samples within different views.Moreover,the tensor nuclear norm is not fully considered as a convex approximation of the tensor rank function.Treating different singular values equally may result in suboptimal tensor representation.A hypergraph regularized multi-view subspace clustering algorithm with dual tensor log-determinant(HRMSC-DTL)was proposed.The algorithm used subspace learning in each view to learn a specific set of affinity matrices,and introduced a non-convex tensor log-determinant function to replace the tensor nuclear norm to better improve global low-rankness.It also introduced hyper-Laplacian regularization to preserve the local geometric structure embedded in the high-dimensional space.Furthermore,it rotated the original tensor and incorporated a dual tensor mechanism to fully exploit the intra view correlation of the original tensor and the inter view correlation of the rotated tensor.At the same time,an alternating direction of multipliers method(ADMM)was also designed to solve non-convex optimization model.Experimental evaluations on seven widely used datasets,along with comparisons to several state-of-the-art algorithms,demonstrated the superiority and effectiveness of the HRMSC-DTL algorithm in terms of clustering performance.展开更多
Tin(Sn)-lead(Pb)mixed halide perovskites have attracted widespread interest due to their wider re-sponse wavelength and lower toxicity than lead halide perovskites,Among the preparation methods,the two-step method mor...Tin(Sn)-lead(Pb)mixed halide perovskites have attracted widespread interest due to their wider re-sponse wavelength and lower toxicity than lead halide perovskites,Among the preparation methods,the two-step method more easily controls the crystallization rate and is suitable for preparing large-area per-ovskite devices.However,the residual low-conductivity iodide layer in the two-step method can affect carrier transport and device stability,and the different crystallization rates of Sn-and Pb-based per-ovskites may result in poor film quality.Therefore,Sn-Pb mixed perovskites are mainly prepared by a one-step method.Herein,a MAPb_(0.5)Sn_(0.5)I_(3)-based self-powered photodetector without a hole transport layer is fabricated by a two-step method.By adjusting the concentration of the ascorbic acid(AA)addi-tive,the final perovskite film exhibited a pure phase without residues,and the optimal device exhibited a high responsivity(0.276 A W^(-1)),large specific detectivity(2.38×10^(12) Jones),and enhanced stability.This enhancement is mainly attributed to the inhibition of Sn2+oxidation,the control of crystal growth,and the sufficient reaction between organic ammonium salts and bottom halides due to the AA-induced pore structure.展开更多
High-performance graphite materials have important roles in aerospace and nuclear reactor technologies because of their outstanding chemical stability and high-temperature performance.Their traditional production meth...High-performance graphite materials have important roles in aerospace and nuclear reactor technologies because of their outstanding chemical stability and high-temperature performance.Their traditional production method relies on repeated impregnation-carbonization and graphitization,and is plagued by lengthy preparation cycles and high energy consumption.Phase transition-assisted self-pressurized selfsintering technology can rapidly produce high-strength graphite materials,but the fracture strain of the graphite materials produced is poor.To solve this problem,this study used a two-step sintering method to uniformly introduce micro-nano pores into natural graphite-based bulk graphite,achieving improved fracture strain of the samples without reducing their density and mechanical properties.Using natural graphite powder,micron-diamond,and nano-diamond as raw materials,and by precisely controlling the staged pressure release process,the degree of diamond phase transition expansion was effectively regulated.The strain-to-failure of the graphite samples reached 1.2%,a 35%increase compared to samples produced by fullpressure sintering.Meanwhile,their flexural strength exceeded 110 MPa,and their density was over 1.9 g/cm^(3).The process therefore produced both a high strength and a high fracture strain.The interface evolution and toughening mechanism during the two-step sintering process were investigated.It is believed that the micro-nano pores formed have two roles:as stress concentrators they induce yielding by shear and as multi-crack propagation paths they significantly lengthen the crack propagation path.The two-step sintering phase transition strategy introduces pores and provides a new approach for increasing the fracture strain of brittle materials.展开更多
The finite volume method was applied to numerically simulate the bottom pressure field induced by regular waves,vehicles in calm water and vehicles in regular waves.The solution of Navier-Stokes(N-S)equations in the v...The finite volume method was applied to numerically simulate the bottom pressure field induced by regular waves,vehicles in calm water and vehicles in regular waves.The solution of Navier-Stokes(N-S)equations in the vicinity of numerical wave tank's boundary was forced towards the wave theoretical solution by incorporating momentum source terms,thereby reducing adverse effects such as wave reflection.Simulations utilizing laminar flow,turbulent flow,and ideal fluid models were all found capable of effectively capturing the waveform and bottom pressure of regular waves,agreeing well with experimental data.In predicting the bottom pressure field of the submerged vehicle,turbulent simulations considering fluid viscosity and boundary layer development provided more accurate predictions for the stern region than inviscid simulations.Due to sphere's diffractive effect,the sphere's bottom pressure field in waves is not a linear superposition of the wave's and the sphere's bottom pressure field.However,a slender submerged vehicle exhibits a weaker diffractive effect on waves,thus the submerged vehicle's bottom pressure field in waves can be approximated as a linear superposition of the wave's and the submerged vehicle's bottom pressure field,which simplifies computation and analysis.展开更多
This paper delves into the baseline design under the baseline parameterization model in experimental design, focusing on the relationship between the K-aberration criterion and the word length pattern (WLP) of regular...This paper delves into the baseline design under the baseline parameterization model in experimental design, focusing on the relationship between the K-aberration criterion and the word length pattern (WLP) of regular two-level designs. The paper provides a detailed analysis of the relationship between K5and the WLP for regular two-level designs with resolution t=3, and proposes corresponding theoretical results. These results not only theoretically reveal the connection between the orthogonal parameterization model and the baseline parameterization model but also provide theoretical support for finding the K-aberration optimal regular two-level baseline designs. It demonstrates how to apply these theories to evaluate and select the optimal experimental designs. In practical applications, experimental designers can utilize the theoretical results of this paper to quickly assess and select regular two-level baseline designs with minimal K-aberration by analyzing the WLP of the experimental design. This allows for the identification of key factors that significantly affect the experimental outcomes without frequently changing the factor levels, thereby maximizing the benefits of the experiment.展开更多
A custom micro-arc oxidation(MAO)apparatus is employed to produce coatings under optimized constant voltage–current two-step power supply mode.Various analytical techniques,including scanning electron microscopy,conf...A custom micro-arc oxidation(MAO)apparatus is employed to produce coatings under optimized constant voltage–current two-step power supply mode.Various analytical techniques,including scanning electron microscopy,confocal laser microscopy,X-ray diffraction,X-ray photoelectron spectroscopy,transmission electron microscopy,and electrochemical analysis,are employed to characterize MAO coatings at different stages of preparation.MAO has MgO,hydroxyapatite,Ca_(3)(PO_(4))_(2),and Mg2SiO4 phases.Its microstructure of the coating is characterized by"multiple breakdowns,pores within pores",and"repaired blind pores".The porosity and the uniformity of MAO coating first declines in the constant voltage mode,then augments while the discharge phenomenon takes place,and finally decreases in the repair stage.These analyses reveal a four-stage growth pattern for MAO coatings:anodic oxidation stage,micro-arc oxidation stage,breakdown stage,and repairing stage.During anodic oxidation and MAO stages,inward growth prevails,while the breakdown stage sees outward and accelerated growth.Simultaneous inward and outward growth in the repair stage results in a denser,more uniform coating with increased thickness and improved corrosion resistance.展开更多
Magnesium alloy thin-walled cylindrical components with the advantages of high specific stiffness and strength present broad prospect for the lightweight of aerospace components.However,poor formability resulting from...Magnesium alloy thin-walled cylindrical components with the advantages of high specific stiffness and strength present broad prospect for the lightweight of aerospace components.However,poor formability resulting from the hexagonal close-packed crystal structure in magnesium alloy puts forwards a great challenge for thin-walled cylindrical components fabrication,especially for extreme structure with the thicknesschanging web and the high thin-wall.In this research,an ZK61 magnesium alloy thin-walled cylindrical component was successfully fabricated by two-step forging,i.e.,the pre-forging and final-forging is mainly used for wed and thin-wall formation,respectively.Microstructure and mechanical properties at the core,middle and margin of the web and the thin-wall of the pre-forged and final-forged components are studied in detail.Due to the large strain-effectiveness and metal flow along the radial direction(RD),the grains of the web are all elongated along RD for the pre-forged component,where an increasingly elongated trend is found from the core to the margin of the wed.A relatively low recrystallized degree occurs during pre-forging,and the web at different positions are all with prismatic and pyramid textures.During finalforging,the microstructures of the web and the thin-wall are almost equiaxed due to the remarkable occurrence of dynamic recrystallization.Similarity,except for few basal texture of the thin-wall,only prismatic and pyramid textures are found for the final-forged component.Compared with the initial billet,an obviously improved mechanical isotropy is achieved during pre-forging,which is well-maintained during final-forging.展开更多
Efficient and accurate simulation of unsteady flow presents a significant challenge that needs to be overcome in computational fluid dynamics.Temporal discretization method plays a crucial role in the simulation of un...Efficient and accurate simulation of unsteady flow presents a significant challenge that needs to be overcome in computational fluid dynamics.Temporal discretization method plays a crucial role in the simulation of unsteady flows.To enhance computational efficiency,we propose the Implicit-Explicit Two-Step Runge-Kutta(IMEX-TSRK)time-stepping discretization methods for unsteady flows,and develop a novel adaptive algorithm that correctly partitions spatial regions to apply implicit or explicit methods.The novel adaptive IMEX-TSRK schemes effectively handle the numerical stiffness of the small grid size and improve computational efficiency.Compared to implicit and explicit Runge-Kutta(RK)schemes,the IMEX-TSRK methods achieve the same order of accuracy with fewer first derivative calculations.Numerical case tests demonstrate that the IMEX-TSRK methods maintain numerical stability while enhancing computational efficiency.Specifically,in high Reynolds number flows,the computational efficiency of the IMEX-TSRK methods surpasses that of explicit RK schemes by more than one order of magnitude,and that of implicit RK schemes several times over.展开更多
In existing studies, most slope stability analyses concentrate on conditions with constant temperature, assuming the slope is intact, and employ the Mohr-Coulomb (M-C) failure criterion for saturated soil to character...In existing studies, most slope stability analyses concentrate on conditions with constant temperature, assuming the slope is intact, and employ the Mohr-Coulomb (M-C) failure criterion for saturated soil to characterize the strength of the backfill. However, the actual working temperature of slopes varies, and natural phenomena such as rainfall and groundwater infiltration commonly result in unsaturated soil conditions, with cracks typically present in cohesive slopes. This study introduces a novel approach for assessing the stability of unsaturated soil stepped slopes under varying temperatures, incorporating the effects of open and vertical cracks. Utilizing the kinematic approach and gravity increase method, we developed a three-dimensional (3D) rotational wedge failure mechanism to simulate slope collapse, enhancing the traditional two-dimensional analyses. We integrated temperature-dependent functions and nonlinear shear strength equations to evaluate the impact of temperature on four typical unsaturated soil types. A particle swarm optimization algorithm was employed to calculate the safety factor, ensuring our method’s accuracy by comparing it with existing studies. The results indicate that considering 3D effects yields a higher safety factor, while cracks reduce slope stability. Each unsaturated soil exhibits a distinctive temperature response curve, highlighting the importance of understanding soil types in the design phase.展开更多
In this study,we present a deterministic convergence analysis of Gated Recurrent Unit(GRU)networks enhanced by a smoothing L_(1)regularization technique.While GRU architectures effectively mitigate gradient vanishing/...In this study,we present a deterministic convergence analysis of Gated Recurrent Unit(GRU)networks enhanced by a smoothing L_(1)regularization technique.While GRU architectures effectively mitigate gradient vanishing/exploding issues in sequential modeling,they remain prone to overfitting,particularly under noisy or limited training data.Traditional L_(1)regularization,despite enforcing sparsity and accelerating optimization,introduces non-differentiable points in the error function,leading to oscillations during training.To address this,we propose a novel smoothing L_(1)regularization framework that replaces the non-differentiable absolute function with a quadratic approximation,ensuring gradient continuity and stabilizing the optimization landscape.Theoretically,we rigorously establish threekey properties of the resulting smoothing L_(1)-regularizedGRU(SL_(1)-GRU)model:(1)monotonic decrease of the error function across iterations,(2)weak convergence characterized by vanishing gradients as iterations approach infinity,and(3)strong convergence of network weights to fixed points under finite conditions.Comprehensive experiments on benchmark datasets-spanning function approximation,classification(KDD Cup 1999 Data,MNIST),and regression tasks(Boston Housing,Energy Efficiency)-demonstrate SL_(1)-GRUs superiority over baseline models(RNN,LSTM,GRU,L_(1)-GRU,L2-GRU).Empirical results reveal that SL_(1)-GRU achieves 1.0%-2.4%higher test accuracy in classification,7.8%-15.4%lower mean squared error in regression compared to unregularized GRU,while reducing training time by 8.7%-20.1%.These outcomes validate the method’s efficacy in balancing computational efficiency and generalization capability,and they strongly corroborate the theoretical calculations.The proposed framework not only resolves the non-differentiability challenge of L_(1)regularization but also provides a theoretical foundation for convergence guarantees in recurrent neural network training.展开更多
Ti-based bulk metallic glasses(BMGs)have attracted increasing attention due to their high specific strength.However,a fundamental conflict exists between the specific strength and glass-forming ability(GFA)of Ti-based...Ti-based bulk metallic glasses(BMGs)have attracted increasing attention due to their high specific strength.However,a fundamental conflict exists between the specific strength and glass-forming ability(GFA)of Ti-based BMGs,restricting their commercial applications significantly.In this study,this challenge was addressed by introducing a two-step alloying strategy to mitigate the remarkable density increment effect associated with heavy alloying elements required for enhancing the GFA.Consequently,through two-step alloying with Al and Fe in sequence,simultaneous enhancements in specific strength and GFA were achieved based on a Ti-Zr-Be ternary metallic glass,resulting in the development of a series of centimeter-sized metallic glasses exhibiting ultrahigh-specific strength.Notably,the newly developed(Ti_(45)Zr_(20)Be_(31)A_(l4))_(94)Fe_(6)alloy established a new record for the specific strength of Ti-based BMGs.Along with a critical diameter(D_(c))of 10 mm,it offers the optimal scheme for balancing the specific strength and GFA of Ti-based BMGs.The present results further brighten the application prospects of Ti-based BMGs as lightweight materials.展开更多
Absorption compensation is a process involving the exponential amplification of reflection amplitudes.This process amplifies the seismic signal and noise,thereby substantially reducing the signal-tonoise ratio of seis...Absorption compensation is a process involving the exponential amplification of reflection amplitudes.This process amplifies the seismic signal and noise,thereby substantially reducing the signal-tonoise ratio of seismic data.Therefore,this paper proposes a multichannel inversion absorption compensation method based on structure tensor regularization.First,the structure tensor is utilized to extract the spatial inclination of seismic signals,and the spatial prediction filter is designed along the inclination direction.The spatial prediction filter is then introduced into the regularization condition of multichannel inversion absorption compensation,and the absorption compensation is realized under the framework of multichannel inversion theory.The spatial predictability of seismic signals is also introduced into the objective function of absorption compensation inversion.Thus,the inversion system can effectively suppress the noise amplification effect during absorption compensation and improve the recovery accuracy of high-frequency signals.Synthetic and field data tests are conducted to demonstrate the accuracy and effectiveness of the proposed method.展开更多
Energy resolution calibration is crucial for gamma-ray spectral analysis,as measured using a scintillation detector.A locally constrained regularization method was proposed to determine the resolution calibration para...Energy resolution calibration is crucial for gamma-ray spectral analysis,as measured using a scintillation detector.A locally constrained regularization method was proposed to determine the resolution calibration parameters.First,a Monte Carlo simulation model consistent with an actual measurement system was constructed to obtain the energy deposition distribution in the scintillation crystal.Subsequently,the regularization objective function is established based on weighted least squares and additional constraints.Additional constraints were designed using a special weighting scheme based on the incident gamma-ray energies.Subsequently,an intelligent algorithm was introduced to search for the optimal resolution calibration parameters by minimizing the objective function.The most appropriate regularization parameter was determined through mathematical experiments.When the regularization parameter was 30,the calibrated results exhibited the minimum RMSE.Simulations and test pit experiments were conducted to verify the performance of the proposed method.The simulation results demonstrate that the proposed algorithm can determine resolution calibration parameters more accurately than the traditional weighted least squares,and the test pit experimental results show that the R-squares between the calibrated and measured spectra are larger than 0.99.The accurate resolution calibration parameters determined by the proposed method lay the foundation for gamma-ray spectral processing and simulation benchmarking.展开更多
基金supported by the Intelligent Policing Key Laboratory of Sichuan Province(No.ZNJW2022KFZD002)This work was supported by the Scientific and Technological Research Program of Chongqing Municipal Education Commission(Grant Nos.KJQN202302403,KJQN202303111).
文摘Transfer-based Adversarial Attacks(TAAs)can deceive a victim model even without prior knowledge.This is achieved by leveraging the property of adversarial examples.That is,when generated from a surrogate model,they retain their features if applied to other models due to their good transferability.However,adversarial examples often exhibit overfitting,as they are tailored to exploit the particular architecture and feature representation of source models.Consequently,when attempting black-box transfer attacks on different target models,their effectiveness is decreased.To solve this problem,this study proposes an approach based on a Regularized Constrained Feature Layer(RCFL).The proposed method first uses regularization constraints to attenuate the initial examples of low-frequency components.Perturbations are then added to a pre-specified layer of the source model using the back-propagation technique,in order to modify the original adversarial examples.Afterward,a regularized loss function is used to enhance the black-box transferability between different target models.The proposed method is finally tested on the ImageNet,CIFAR-100,and Stanford Car datasets with various target models,The obtained results demonstrate that it achieves a significantly higher transfer-based adversarial attack success rate compared with baseline techniques.
基金supported by the National Natural Science Foundation of China(Grant No.12474461)the Basic and Frontier Exploration Project Independently Deployed by Institute of Acoustics,Chinese Academy of Sciences(Grant No.JCQY202402)the Goal-Oriented Project Independently Deployed by Institute of Acoustics,Chinese Academy of Sciences(Grant No.MBDX202113).
文摘Full waveform inversion(FWI)is a complex data fitting process based on full wavefield modeling,aiming to quantitatively reconstruct unknown model parameters from partial waveform data with high-resolution.However,this process is highly nonlinear and ill-posed,therefore achieving high-resolution imaging of complex biological tissues within a limited number of iterations remains challenging.We propose a multiscale frequency–domain full waveform inversion(FDFWI)framework for ultrasound computed tomography(USCT)imaging of biological tissues,which innovatively incorporates Sobolev space norm regularization for enhancement of prior information.Specifically,we investigate the effect of different types of hyperparameter on the imaging quality,during which the regularization weight is dynamically adapted based on the ratio of the regularization term to the data fidelity term.This strategy reduces reliance on predefined hyperparameters,ensuring robust inversion performance.The inversion results from both numerical and experimental tests(i.e.,numerical breast,thigh,and ex vivo pork-belly tissue)demonstrate the effectiveness of our regularized FWI strategy.These findings will contribute to the application of the FWI technique in quantitative imaging based on USCT and make USCT possible to be another high-resolution imaging method after x-ray computed tomography and magnetic resonance imaging.
基金supported by the National Key R&D Program of China(2022ZD0119604)the National Natural Science Foundation of China(NSFC),(62222308,62173181,62221004)+1 种基金the Natural Science Foundation of Jiangsu Province(BK20220139)the Young Elite Scientists Sponsorship Program by CAST(2021QNRC001)。
文摘Dear Editor,This letter explores optimal formation control for a network of unmanned surface vessels(USVs).By designing an individual objective function for each USV,the optimal formation problem is transformed into a noncooperative game.Under this game theoretic framework,the optimal formation is achieved by seeking the Nash equilibrium of the regularized game.A modular structure consisting of a distributed Nash equilibrium seeker and a regulator is proposed.
文摘The selection of hyperparameters in regularized least squares plays an important role in large-scale system identification. The traditional methods for selecting hyperparameters are based on experience or marginal likelihood maximization method, which are inaccurate or computationally expensive. In this paper, two posterior methods are proposed to select hyperparameters based on different prior knowledge (constraints), which can obtain the optimal hyperparameters using the optimization theory. Moreover, we also give the theoretical optimal constraints, and verify its effectiveness. Numerical simulation shows that the hyperparameters and parameter vector estimate obtained by the proposed methods are the optimal ones.
基金supported by the National Nature Science Foundation of China (Grant No.11988102)National Undergraduate Training Program for Innovation and Entrepreneurship。
文摘Dynamic mode decomposition(DMD) aims at extracting intrinsic mechanisms in a time sequence via linear recurrence relation of its observables, thereby predicting later terms in the sequence. Stability is a major concern in DMD predictions. We adopt a regularized form and propose a Regularized DMD(Re DMD) algorithm to determine the regularization parameter. This leverages stability and accuracy. Numerical tests for Burgers' equation demonstrate that Re DMD effectively stabilizes the DMD prediction while maintaining accuracy. Comparisons are made with the truncated DMD algorithm.
基金supported by the Opening Project of Guangdong Province Key Laboratory of Cyber-Physical System(20168030301008)supported by the National Natural Science Foundation of China(11126266)+4 种基金the Natural Science Foundation of Guangdong Province(2016A030313390)the Quality Engineering Project of Guangdong Province(SCAU-2021-69)the SCAU Fund for High-level University Buildingsupported by the National Key Research and Development Program of China(2020YFA0712500)the National Natural Science Foundation of China(11971496,12126609)。
文摘In this paper,we study the three-dimensional regularized MHD equations with fractional Laplacians in the dissipative and diffusive terms.We establish the global existence of mild solutions to this system with small initial data.In addition,we also obtain the Gevrey class regularity and the temporal decay rate of the solution.
基金supported by National Natural Science Foundation of China(No.61806006)Priority Academic Program Development of Jiangsu Higher Education Institutions。
文摘The existing multi-view subspace clustering algorithms based on tensor singular value decomposition(t-SVD)predominantly utilize tensor nuclear norm to explore the intra view correlation between views of the same samples,while neglecting the correlation among the samples within different views.Moreover,the tensor nuclear norm is not fully considered as a convex approximation of the tensor rank function.Treating different singular values equally may result in suboptimal tensor representation.A hypergraph regularized multi-view subspace clustering algorithm with dual tensor log-determinant(HRMSC-DTL)was proposed.The algorithm used subspace learning in each view to learn a specific set of affinity matrices,and introduced a non-convex tensor log-determinant function to replace the tensor nuclear norm to better improve global low-rankness.It also introduced hyper-Laplacian regularization to preserve the local geometric structure embedded in the high-dimensional space.Furthermore,it rotated the original tensor and incorporated a dual tensor mechanism to fully exploit the intra view correlation of the original tensor and the inter view correlation of the rotated tensor.At the same time,an alternating direction of multipliers method(ADMM)was also designed to solve non-convex optimization model.Experimental evaluations on seven widely used datasets,along with comparisons to several state-of-the-art algorithms,demonstrated the superiority and effectiveness of the HRMSC-DTL algorithm in terms of clustering performance.
基金supported by the National Natural Science Foun-dation of China(Nos.52025028,52332008,52372214,52202273,and U22A20137)the Priority Academic Program Development(PAPD)of Jiangsu Higher Education Institutions.
文摘Tin(Sn)-lead(Pb)mixed halide perovskites have attracted widespread interest due to their wider re-sponse wavelength and lower toxicity than lead halide perovskites,Among the preparation methods,the two-step method more easily controls the crystallization rate and is suitable for preparing large-area per-ovskite devices.However,the residual low-conductivity iodide layer in the two-step method can affect carrier transport and device stability,and the different crystallization rates of Sn-and Pb-based per-ovskites may result in poor film quality.Therefore,Sn-Pb mixed perovskites are mainly prepared by a one-step method.Herein,a MAPb_(0.5)Sn_(0.5)I_(3)-based self-powered photodetector without a hole transport layer is fabricated by a two-step method.By adjusting the concentration of the ascorbic acid(AA)addi-tive,the final perovskite film exhibited a pure phase without residues,and the optimal device exhibited a high responsivity(0.276 A W^(-1)),large specific detectivity(2.38×10^(12) Jones),and enhanced stability.This enhancement is mainly attributed to the inhibition of Sn2+oxidation,the control of crystal growth,and the sufficient reaction between organic ammonium salts and bottom halides due to the AA-induced pore structure.
基金Natural Science Foundation of Shanghai(24ZR1400800)he Natural Science Foundation of China(U23A20685,52073058,91963204)+1 种基金the National Key R&D Program of China(2021YFB3701400)Shanghai Sailing Program(23YF1400200)。
文摘High-performance graphite materials have important roles in aerospace and nuclear reactor technologies because of their outstanding chemical stability and high-temperature performance.Their traditional production method relies on repeated impregnation-carbonization and graphitization,and is plagued by lengthy preparation cycles and high energy consumption.Phase transition-assisted self-pressurized selfsintering technology can rapidly produce high-strength graphite materials,but the fracture strain of the graphite materials produced is poor.To solve this problem,this study used a two-step sintering method to uniformly introduce micro-nano pores into natural graphite-based bulk graphite,achieving improved fracture strain of the samples without reducing their density and mechanical properties.Using natural graphite powder,micron-diamond,and nano-diamond as raw materials,and by precisely controlling the staged pressure release process,the degree of diamond phase transition expansion was effectively regulated.The strain-to-failure of the graphite samples reached 1.2%,a 35%increase compared to samples produced by fullpressure sintering.Meanwhile,their flexural strength exceeded 110 MPa,and their density was over 1.9 g/cm^(3).The process therefore produced both a high strength and a high fracture strain.The interface evolution and toughening mechanism during the two-step sintering process were investigated.It is believed that the micro-nano pores formed have two roles:as stress concentrators they induce yielding by shear and as multi-crack propagation paths they significantly lengthen the crack propagation path.The two-step sintering phase transition strategy introduces pores and provides a new approach for increasing the fracture strain of brittle materials.
文摘The finite volume method was applied to numerically simulate the bottom pressure field induced by regular waves,vehicles in calm water and vehicles in regular waves.The solution of Navier-Stokes(N-S)equations in the vicinity of numerical wave tank's boundary was forced towards the wave theoretical solution by incorporating momentum source terms,thereby reducing adverse effects such as wave reflection.Simulations utilizing laminar flow,turbulent flow,and ideal fluid models were all found capable of effectively capturing the waveform and bottom pressure of regular waves,agreeing well with experimental data.In predicting the bottom pressure field of the submerged vehicle,turbulent simulations considering fluid viscosity and boundary layer development provided more accurate predictions for the stern region than inviscid simulations.Due to sphere's diffractive effect,the sphere's bottom pressure field in waves is not a linear superposition of the wave's and the sphere's bottom pressure field.However,a slender submerged vehicle exhibits a weaker diffractive effect on waves,thus the submerged vehicle's bottom pressure field in waves can be approximated as a linear superposition of the wave's and the submerged vehicle's bottom pressure field,which simplifies computation and analysis.
文摘This paper delves into the baseline design under the baseline parameterization model in experimental design, focusing on the relationship between the K-aberration criterion and the word length pattern (WLP) of regular two-level designs. The paper provides a detailed analysis of the relationship between K5and the WLP for regular two-level designs with resolution t=3, and proposes corresponding theoretical results. These results not only theoretically reveal the connection between the orthogonal parameterization model and the baseline parameterization model but also provide theoretical support for finding the K-aberration optimal regular two-level baseline designs. It demonstrates how to apply these theories to evaluate and select the optimal experimental designs. In practical applications, experimental designers can utilize the theoretical results of this paper to quickly assess and select regular two-level baseline designs with minimal K-aberration by analyzing the WLP of the experimental design. This allows for the identification of key factors that significantly affect the experimental outcomes without frequently changing the factor levels, thereby maximizing the benefits of the experiment.
文摘A custom micro-arc oxidation(MAO)apparatus is employed to produce coatings under optimized constant voltage–current two-step power supply mode.Various analytical techniques,including scanning electron microscopy,confocal laser microscopy,X-ray diffraction,X-ray photoelectron spectroscopy,transmission electron microscopy,and electrochemical analysis,are employed to characterize MAO coatings at different stages of preparation.MAO has MgO,hydroxyapatite,Ca_(3)(PO_(4))_(2),and Mg2SiO4 phases.Its microstructure of the coating is characterized by"multiple breakdowns,pores within pores",and"repaired blind pores".The porosity and the uniformity of MAO coating first declines in the constant voltage mode,then augments while the discharge phenomenon takes place,and finally decreases in the repair stage.These analyses reveal a four-stage growth pattern for MAO coatings:anodic oxidation stage,micro-arc oxidation stage,breakdown stage,and repairing stage.During anodic oxidation and MAO stages,inward growth prevails,while the breakdown stage sees outward and accelerated growth.Simultaneous inward and outward growth in the repair stage results in a denser,more uniform coating with increased thickness and improved corrosion resistance.
基金supported by the National Natural Science Foundation of China(No.52405408,No.U21A20131,No.U2037204,No.52422510)the Natural Science Foundation of Hubei Province(No.2023AFB116)+1 种基金the State Key Laboratory of Materials Processing and Die&Mould TechnologyHuazhong University of Science and Technology(No.P2022-005)。
文摘Magnesium alloy thin-walled cylindrical components with the advantages of high specific stiffness and strength present broad prospect for the lightweight of aerospace components.However,poor formability resulting from the hexagonal close-packed crystal structure in magnesium alloy puts forwards a great challenge for thin-walled cylindrical components fabrication,especially for extreme structure with the thicknesschanging web and the high thin-wall.In this research,an ZK61 magnesium alloy thin-walled cylindrical component was successfully fabricated by two-step forging,i.e.,the pre-forging and final-forging is mainly used for wed and thin-wall formation,respectively.Microstructure and mechanical properties at the core,middle and margin of the web and the thin-wall of the pre-forged and final-forged components are studied in detail.Due to the large strain-effectiveness and metal flow along the radial direction(RD),the grains of the web are all elongated along RD for the pre-forged component,where an increasingly elongated trend is found from the core to the margin of the wed.A relatively low recrystallized degree occurs during pre-forging,and the web at different positions are all with prismatic and pyramid textures.During finalforging,the microstructures of the web and the thin-wall are almost equiaxed due to the remarkable occurrence of dynamic recrystallization.Similarity,except for few basal texture of the thin-wall,only prismatic and pyramid textures are found for the final-forged component.Compared with the initial billet,an obviously improved mechanical isotropy is achieved during pre-forging,which is well-maintained during final-forging.
基金supported by the National Natural Science Foundation of China(No.92252201)the Fundamental Research Funds for the Central Universitiesthe Academic Excellence Foundation of Beihang University(BUAA)for PhD Students。
文摘Efficient and accurate simulation of unsteady flow presents a significant challenge that needs to be overcome in computational fluid dynamics.Temporal discretization method plays a crucial role in the simulation of unsteady flows.To enhance computational efficiency,we propose the Implicit-Explicit Two-Step Runge-Kutta(IMEX-TSRK)time-stepping discretization methods for unsteady flows,and develop a novel adaptive algorithm that correctly partitions spatial regions to apply implicit or explicit methods.The novel adaptive IMEX-TSRK schemes effectively handle the numerical stiffness of the small grid size and improve computational efficiency.Compared to implicit and explicit Runge-Kutta(RK)schemes,the IMEX-TSRK methods achieve the same order of accuracy with fewer first derivative calculations.Numerical case tests demonstrate that the IMEX-TSRK methods maintain numerical stability while enhancing computational efficiency.Specifically,in high Reynolds number flows,the computational efficiency of the IMEX-TSRK methods surpasses that of explicit RK schemes by more than one order of magnitude,and that of implicit RK schemes several times over.
基金Project(51378510) supported by the National Natural Science Foundation of China。
文摘In existing studies, most slope stability analyses concentrate on conditions with constant temperature, assuming the slope is intact, and employ the Mohr-Coulomb (M-C) failure criterion for saturated soil to characterize the strength of the backfill. However, the actual working temperature of slopes varies, and natural phenomena such as rainfall and groundwater infiltration commonly result in unsaturated soil conditions, with cracks typically present in cohesive slopes. This study introduces a novel approach for assessing the stability of unsaturated soil stepped slopes under varying temperatures, incorporating the effects of open and vertical cracks. Utilizing the kinematic approach and gravity increase method, we developed a three-dimensional (3D) rotational wedge failure mechanism to simulate slope collapse, enhancing the traditional two-dimensional analyses. We integrated temperature-dependent functions and nonlinear shear strength equations to evaluate the impact of temperature on four typical unsaturated soil types. A particle swarm optimization algorithm was employed to calculate the safety factor, ensuring our method’s accuracy by comparing it with existing studies. The results indicate that considering 3D effects yields a higher safety factor, while cracks reduce slope stability. Each unsaturated soil exhibits a distinctive temperature response curve, highlighting the importance of understanding soil types in the design phase.
基金supported by the National Science Fund for Distinguished Young Scholarship(No.62025602)National Natural Science Foundation of China(Nos.U22B2036,11931015)+2 种基金the Fok Ying-Tong Education Foundation China(No.171105)the Fundamental Research Funds for the Central Universities(No.G2024WD0151)in part by the Tencent Foundation and XPLORER PRIZE.
文摘In this study,we present a deterministic convergence analysis of Gated Recurrent Unit(GRU)networks enhanced by a smoothing L_(1)regularization technique.While GRU architectures effectively mitigate gradient vanishing/exploding issues in sequential modeling,they remain prone to overfitting,particularly under noisy or limited training data.Traditional L_(1)regularization,despite enforcing sparsity and accelerating optimization,introduces non-differentiable points in the error function,leading to oscillations during training.To address this,we propose a novel smoothing L_(1)regularization framework that replaces the non-differentiable absolute function with a quadratic approximation,ensuring gradient continuity and stabilizing the optimization landscape.Theoretically,we rigorously establish threekey properties of the resulting smoothing L_(1)-regularizedGRU(SL_(1)-GRU)model:(1)monotonic decrease of the error function across iterations,(2)weak convergence characterized by vanishing gradients as iterations approach infinity,and(3)strong convergence of network weights to fixed points under finite conditions.Comprehensive experiments on benchmark datasets-spanning function approximation,classification(KDD Cup 1999 Data,MNIST),and regression tasks(Boston Housing,Energy Efficiency)-demonstrate SL_(1)-GRUs superiority over baseline models(RNN,LSTM,GRU,L_(1)-GRU,L2-GRU).Empirical results reveal that SL_(1)-GRU achieves 1.0%-2.4%higher test accuracy in classification,7.8%-15.4%lower mean squared error in regression compared to unregularized GRU,while reducing training time by 8.7%-20.1%.These outcomes validate the method’s efficacy in balancing computational efficiency and generalization capability,and they strongly corroborate the theoretical calculations.The proposed framework not only resolves the non-differentiability challenge of L_(1)regularization but also provides a theoretical foundation for convergence guarantees in recurrent neural network training.
基金supported by the National Natural Science Foundation of China(Nos.52271148 and 51871129).
文摘Ti-based bulk metallic glasses(BMGs)have attracted increasing attention due to their high specific strength.However,a fundamental conflict exists between the specific strength and glass-forming ability(GFA)of Ti-based BMGs,restricting their commercial applications significantly.In this study,this challenge was addressed by introducing a two-step alloying strategy to mitigate the remarkable density increment effect associated with heavy alloying elements required for enhancing the GFA.Consequently,through two-step alloying with Al and Fe in sequence,simultaneous enhancements in specific strength and GFA were achieved based on a Ti-Zr-Be ternary metallic glass,resulting in the development of a series of centimeter-sized metallic glasses exhibiting ultrahigh-specific strength.Notably,the newly developed(Ti_(45)Zr_(20)Be_(31)A_(l4))_(94)Fe_(6)alloy established a new record for the specific strength of Ti-based BMGs.Along with a critical diameter(D_(c))of 10 mm,it offers the optimal scheme for balancing the specific strength and GFA of Ti-based BMGs.The present results further brighten the application prospects of Ti-based BMGs as lightweight materials.
基金funded by the National Key R&D Program of China(Grant no.2018YFA0702504)the Sinopec research project(P22162).
文摘Absorption compensation is a process involving the exponential amplification of reflection amplitudes.This process amplifies the seismic signal and noise,thereby substantially reducing the signal-tonoise ratio of seismic data.Therefore,this paper proposes a multichannel inversion absorption compensation method based on structure tensor regularization.First,the structure tensor is utilized to extract the spatial inclination of seismic signals,and the spatial prediction filter is designed along the inclination direction.The spatial prediction filter is then introduced into the regularization condition of multichannel inversion absorption compensation,and the absorption compensation is realized under the framework of multichannel inversion theory.The spatial predictability of seismic signals is also introduced into the objective function of absorption compensation inversion.Thus,the inversion system can effectively suppress the noise amplification effect during absorption compensation and improve the recovery accuracy of high-frequency signals.Synthetic and field data tests are conducted to demonstrate the accuracy and effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(No.41804141)。
文摘Energy resolution calibration is crucial for gamma-ray spectral analysis,as measured using a scintillation detector.A locally constrained regularization method was proposed to determine the resolution calibration parameters.First,a Monte Carlo simulation model consistent with an actual measurement system was constructed to obtain the energy deposition distribution in the scintillation crystal.Subsequently,the regularization objective function is established based on weighted least squares and additional constraints.Additional constraints were designed using a special weighting scheme based on the incident gamma-ray energies.Subsequently,an intelligent algorithm was introduced to search for the optimal resolution calibration parameters by minimizing the objective function.The most appropriate regularization parameter was determined through mathematical experiments.When the regularization parameter was 30,the calibrated results exhibited the minimum RMSE.Simulations and test pit experiments were conducted to verify the performance of the proposed method.The simulation results demonstrate that the proposed algorithm can determine resolution calibration parameters more accurately than the traditional weighted least squares,and the test pit experimental results show that the R-squares between the calibrated and measured spectra are larger than 0.99.The accurate resolution calibration parameters determined by the proposed method lay the foundation for gamma-ray spectral processing and simulation benchmarking.
