Background:Emerging adulthood is a critical period for ego identity exploration and consolidation,and self-presentation on social media constitutes a salient online context for this developmental process.However,limit...Background:Emerging adulthood is a critical period for ego identity exploration and consolidation,and self-presentation on social media constitutes a salient online context for this developmental process.However,limited research has explored the associations between self-presentation on WeChat Moments and ego identity.This study aims to examine these associations,focusing on the mediating role of online positive feedback and the moderating role of gender.Methods:Using a three-wave longitudinal design,this study followed 767 Chinese college students(Mean age=18.96 years)through cluster sampling.Participants completed self-report questionnaires assessing self-presentation on WeChat Moments,online positive feedback,and ego identity status.Data analyses were conducted using mediation modeling and multi-group structural equation modeling.Results:Authentic self-presentation was positively associated with identity achievement and negatively associated with identity diffusion,whereas positive self-presentation was linked to higher levels of identity foreclosure.Online positive feedback played a significant mediating role in the associations between self-presentation strategies and identity statuses,and gender differences were observed in this mediating pathway.For both males and females,authentic self-presentation was associated with higher identity achievement through online positive feedback.However,indirect associations with identity foreclosure and diffusion were observed only among females:authentic self-presentation was linked to lower levels,whereas positive self-presentation was linked to higher levels of foreclosure and diffusion through online positive feedback.No comparable indirect associations were detected among males.Conclusions:Online positive feedback is closely linked to self-presentation strategies and ego identity statuses,with these associations varying by gender.展开更多
Beyond business,the CIIE is a vibrant platform where diverse cultures meet,share,and shine The eighth China International Import Expo,held from 5 to 10 November in Shanghai,once again served as a premier stage for exh...Beyond business,the CIIE is a vibrant platform where diverse cultures meet,share,and shine The eighth China International Import Expo,held from 5 to 10 November in Shanghai,once again served as a premier stage for exhibitors from around the world to showcase their distinctive cultures.From food and clothing to a wide array of arts,the more than 900,000 visitors were treated to a rich tapestry of cultural experiences from across the globe.展开更多
On the morning of 13th September,the themed event Characters:A Bond Connecting Cultures--China Tour:Anyang Moments was held at Yinxu Museum(Museum of the Ruins of the Shang Dynasty).The event was co-hosted by the Chin...On the morning of 13th September,the themed event Characters:A Bond Connecting Cultures--China Tour:Anyang Moments was held at Yinxu Museum(Museum of the Ruins of the Shang Dynasty).The event was co-hosted by the China NGO Network for International Exchanges(CNIE)and Anyang Municipal People's Government.展开更多
This paper employs Granger causality analysis and the generalized impulse response function(GIRF)to study the higher-order moment spillover effects among Bitcoin,stock markets,and foreign exchange markets in the U.S.U...This paper employs Granger causality analysis and the generalized impulse response function(GIRF)to study the higher-order moment spillover effects among Bitcoin,stock markets,and foreign exchange markets in the U.S.Using intraday high-frequency data,the research focuses on the interactions across higher-order moments,including volatility,jumps,skewness,and kurtosis.The results reveal significant bidirectional spillover effects between Bitcoin and traditional financial assets,particularly in terms of volatility and jump behavior,indicating that the cryptocurrency market has become a crucial component of global financial risk transmission.This study provides new theoretical perspectives and policy recommendations for global asset allocation,market regulation,and risk management,underscoring the importance of proactive management measures in addressing the complex risk interactions between cryptocurrencies and traditional financial markets.展开更多
In the current digital context,safeguarding copyright is a major issue,particularly for architectural drawings produced by students.These works are frequently the result of innovative academic thinking combining creat...In the current digital context,safeguarding copyright is a major issue,particularly for architectural drawings produced by students.These works are frequently the result of innovative academic thinking combining creativity and technical precision.They are particularly vulnerable to the risk of illegal reproduction when disseminated in digital format.This research suggests,for the first time,an innovative approach to copyright protection by embedding a double digital watermark to address this challenge.The solution relies on a synergistic fusion of several sophisticated methods:Krawtchouk Optimized Octonion Moments(OKOM),Quaternion Singular Value Decomposition(QSVD),and Discrete Waveform Transform(DWT).To improve watermark embedding,the biologically inspired algorithm Chaos-White Shark Optimization(CWSO)is used,which allows dynamically adapting essential parameters such as the scaling factor of the insertion.Thus,two watermarks are inserted at the same time:an institutional logo and a student image,encoded in the main image(the architectural plan)through octonionic projections.This allows minimizing the amount of data to be integrated while increasing resistance.The suggested approach guarantees a perfect balance between the discreetness of the watermark(validated by PSNR indices>47 dB and SSIM>0.99)and its resistance to different attacks(JPEG compression,noise,rotation,resizing,filtering,etc.),as proven by the normalized correlation values(NC>0.9)obtained following the extraction.Therefore,this method represents a notable progress for securing academic works in architecture,providing an effective,discreet and reversible digital protection,which does not harm the visual appearance of the original works.展开更多
In this paper, we establish asymptotic formulas for a cubic moment of Dirichlet L-functions restricted to a coset, as well as for a mixed moment of Dirichlet L-functions and twists of GL(2) L-functions along a coset. ...In this paper, we establish asymptotic formulas for a cubic moment of Dirichlet L-functions restricted to a coset, as well as for a mixed moment of Dirichlet L-functions and twists of GL(2) L-functions along a coset. Our main tool is a power-saving estimate of bilinear forms of hyper-Kloosterman sums due to Kowalski–Michel–Sawin.展开更多
To resolve the completeness and independence of an invariant set derived by the traditional method, a systematic method for deriving a complete set of pseudo-Zernike moment similarity （translation, scale and rotation...To resolve the completeness and independence of an invariant set derived by the traditional method, a systematic method for deriving a complete set of pseudo-Zernike moment similarity （translation, scale and rotation） invariants is described. First, the relationship between pseudo-Zernike moments of the original image and those of the image having the same shape but distinct orientation and scale is established. Based on this relationship, a complete set of similarity invariants can be expressed as a linear combination of the original pseudo-Zernike moments of the same order and lower order. The problem of image reconstruction from a finite set of the pseudo-Zernike moment invariants （PZMIs） is also investigated. Experimental results show that the proposed PZMIs have better performance than complex moment invariants.展开更多
As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a no...As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a novel,unified deep learning framework for vehicle detection,tracking,counting,and classification in aerial imagery designed explicitly for modern smart city infrastructure demands.Our approach begins with adaptive histogram equalization to optimize aerial image clarity,followed by a cutting-edge scene parsing technique using Mask2Former,enabling robust segmentation even in visually congested settings.Vehicle detection leverages the latest YOLOv11 architecture,delivering superior accuracy in aerial contexts by addressing occlusion,scale variance,and fine-grained object differentiation.We incorporate the highly efficient ByteTrack algorithm for tracking,enabling seamless identity preservation across frames.Vehicle counting is achieved through an unsupervised DBSCAN-based method,ensuring adaptability to varying traffic densities.We further introduce a hybrid feature extraction module combining Convolutional Neural Networks(CNNs)with Zernike Moments,capturing both deep semantic and geometric signatures of vehicles.The final classification is powered by NASNet,a neural architecture search-optimized model,ensuring high accuracy across diverse vehicle types and orientations.Extensive evaluations of the VAID benchmark dataset demonstrate the system’s outstanding performance,achieving 96%detection,94%tracking,and 96.4%classification accuracy.On the UAVDT dataset,the system attains 95%detection,93%tracking,and 95%classification accuracy,confirming its robustness across diverse aerial traffic scenarios.These results establish new benchmarks in aerial traffic analysis and validate the framework’s scalability,making it a powerful and adaptable solution for next-generation intelligent transportation systems and urban surveillance.展开更多
Computing electrostatic interaction on non-cooperative targets with unknown meshes is crucial for electrostatic-based space on-orbit services.Although meshes for electrostatic interaction computations can be reconstru...Computing electrostatic interaction on non-cooperative targets with unknown meshes is crucial for electrostatic-based space on-orbit services.Although meshes for electrostatic interaction computations can be reconstructed from point clouds,they are usually too dense,leading to high computational costs.This paper presents an optimization method for converting dense meshes into optimal meshes,enabling fast and accurate computation of the electrostatic interaction by point clouds.First,the dense mesh reconstructed from point clouds is simplified into a coarse mesh using local operators.Second,the simplified mesh is refined by an iterative strategy that integrates a lightweight method of moments and an impedance matrix inheritance technique,ultimately yielding an optimal mesh for computing the electrostatic interaction.Simulation results show that our method effectively optimizes dense meshes,making electrostatic interaction computations using point clouds approximately 63.4 times more efficient than the previous method.展开更多
Within the sufficient dimension reduction framework,research on nonignorable missing data remains relatively scarce,primarily due to the associated identifiability issues.This paper considers the problem of sufficient...Within the sufficient dimension reduction framework,research on nonignorable missing data remains relatively scarce,primarily due to the associated identifiability issues.This paper considers the problem of sufficient dimension reduction when the response is subject to nonignorable missingness.By adopting a flexible semiparametric missingness mechanism to ensure identifiability,the authors construct three classes of estimating equations based on inverse probability weighting,regression imputation and augmented inverse probability weighting.The novel aspects of the proposed methods also include the incorporation of sufficient dimension reduction techniques in the implementation of these estimating equations to mitigate the high-dimensional effect,and the construction of the estimator for the conditional expectation of the estimating functions given both the covariates and the missingness indicator.The authors prove that the resulting three estimators are asymptotically normally distributed.Comprehensive simulation studies are conducted to assess the finite-sample performance of the proposed methods,and an application to PM2.5 concentration data is also presented.展开更多
A detailed understanding of seismicity originating from the Nanga Parbat syntaxis in the northwestern Himalaya is crucial for characterizing the active fault systems and associated neotectonic processes in the region....A detailed understanding of seismicity originating from the Nanga Parbat syntaxis in the northwestern Himalaya is crucial for characterizing the active fault systems and associated neotectonic processes in the region.Continuous earthquake monitoring through local seismic stations enables high-precision results by constraining the velocity structure.In this study,seismogram data from 244 small-magnitude earthquakes are analyzed to delineate the crustal thickness and investigate the source mechanisms beneath the Nanga Parbat syntaxis.The results are achieved with the application of Coupled Hypocenter Velocity Inversion(CHVI)analysis and Time Domain Moment Tensor(TDMT)analysis.The velocity inversion suggests that the Moho discontinuity lies at 60 km depth with an average vP/vS ratio of 1.735±0.017.The minimum 1D velocity model obtained through velocity inversion with least RMS error is further utilized in determining the source mechanism solution.In contrast to earlier studies,which highlighted strike-slip displacement accompanied by reverse dip-slip components,the present research provides a revised interpretation.The moment tensor analysis conducted in this study provides evidence of transtensional deformation associated with neotectonics,attributed to the presence of multiple shear zones.The results of the source mechanism for the selected earthquakes unveiled that the oblique-slip deformation is significantly controlled by the shear stresses coupled with the normal component of dip-slip movement.This is further supported by the higher values of the doublecouple moment tensor(85%),which indicate shear deformation,while the positive value of the compensated linear vector dipole(15%)confirms the presence of a normal component.The coexistence of transpressive and transtensive stresses,together with shallow hypocentral depths and high-amplitude tangential waveforms,can potentially cause devastating impacts in the surroundings of the Nanga Parbat syntaxis.展开更多
In this paper,we propose a learning algorithm termed linear multistep adaptive moment(LMAdam) to enhance the adaptive moment(Adam) algorithm for machine learning.Considering Adam as a single-step discretization of its...In this paper,we propose a learning algorithm termed linear multistep adaptive moment(LMAdam) to enhance the adaptive moment(Adam) algorithm for machine learning.Considering Adam as a single-step discretization of its continuous counterpart,we develop the LMAdam algorithm based on a linear multistep discretization scheme.We design a feedforward neural network for learning the coefficients of the multistep terms with ensured consistency and select the coefficients to ensure zero stability of the multistep terms.We experimentally demonstrate the superiority of the LMAdam via extensive experimentation on benchmark datasets for training various deep neural networks in three applications.展开更多
A deep neural network(DNN)was developed to accurately predict the nuclear charge density distributions for nuclei with proton numbers Z≥8.By incorporating essential nuclear structure features,the model achieved a sig...A deep neural network(DNN)was developed to accurately predict the nuclear charge density distributions for nuclei with proton numbers Z≥8.By incorporating essential nuclear structure features,the model achieved a significant improvement in predictive accuracy over conventional methods.The charge density distributions were analyzed using a Fourier-Bessel(FB)series expansion,and the DNN was trained on a comprehensive dataset derived from relativistic continuum Hartree-Bogoliubov(RCHB)theory calculations.The model demonstrated exceptional performance,with root-mean-square deviations of 0.0123fm and 0.0198 fm for the charge radii on the training and validation sets,respectively,which remarkably surpassed the precision of the original RCHB calculations.In addition to advancing nuclear physics research,this high-precision model provides critical data for applications in atomic physics,nuclear astrophysics,and related fields.展开更多
Among the charged leptons,theτelectric dipole moment dτis the least constrained.We show that the Im[d_(τ)]imposes strong constraints on new physics that have yet to be discussed.Motivated in particular by the Super...Among the charged leptons,theτelectric dipole moment dτis the least constrained.We show that the Im[d_(τ)]imposes strong constraints on new physics that have yet to be discussed.Motivated in particular by the Super Tau-Charm Facility(STCF),which will provide a uniquely clean environment for precisionτ-physics,we study the momentum-transfer dependence of d_(τ)(q^(2))and compare the projected sensitivities of STCF and BelleⅡ.Our analysis shows that an axion-like coupling of the τ lepton can induce sizable real and imaginary components of the EDM.The predicted EDM values may approach the present experimental sensitivities,making them accessible to future measurements at Belle II and the STCF.展开更多
When calculating electromagnetic scattering using method of moments （MoM）, integral of the singular term has a significant influence on the results. This paper transforms the singular surface integral to the contour...When calculating electromagnetic scattering using method of moments （MoM）, integral of the singular term has a significant influence on the results. This paper transforms the singular surface integral to the contour integral. The integrand is expanded to Taylor series and the integral results in a closed form. The cut-off error is analyzed to show that the series converges fast and only about 2 terms can agree wel with the accurate result. The comparison of the perfect electric conductive （PEC） sphere＇s bi-static radar cross section （RCS） using MoM and the accurate method validates the feasibility in manipulating the singularity. The error due to the facet size and the cut-off terms of the series are analyzed in examples.展开更多
Based on the gravity field models EGM96 and EIGEN-GL04C, the Earth＇s time-dependent principal moments of inertia A, B, C are obtained, and the variable rotation of the Earth is determined. Numerical results show that...Based on the gravity field models EGM96 and EIGEN-GL04C, the Earth＇s time-dependent principal moments of inertia A, B, C are obtained, and the variable rotation of the Earth is determined. Numerical results show that A, B, and C have increasing tendencies; the tilt of the rotation axis increases 2.1×10^ 8 mas/yr; the third component of the rotational angular velocity, ω3 , has a decrease of 1.0×10^ 22 rad/s^2, which is around 23% of the present observed value. Studies show in detail that both 0 and ω3 experience complex fluctuations at various time scales due to the variations of A, B and C.展开更多
Radar parameters including radar reflectivity, Doppler velocity, and Doppler spectrum width were obtained from Doppler spectrum moments. The Doppler spectrum moment is the convolution of both the particle spectrum and...Radar parameters including radar reflectivity, Doppler velocity, and Doppler spectrum width were obtained from Doppler spectrum moments. The Doppler spectrum moment is the convolution of both the particle spectrum and the mean air vertical motion. Unlike strong precipitation, the motion of particles in cirrus clouds is quite close to the air motion around them. In this study, a method of Doppler moments was developed and used to retrieve cirrus cloud microphysical properties such as the mean air vertical velocity, mass-weighted diameter, effective particle size, and ice content. Ice content values were retrieved using both the Doppler spectrum method and classic Z-IWC （radar reflectivity-ice water content） relationships; however, the former is a more reasonable method.展开更多
Let(Z_(n))be a branching process with immigration in a random environmentξ,whereξis an independent and identically distributed sequence of random variables.We show asymptotic properties for all the moments of Z_(n) ...Let(Z_(n))be a branching process with immigration in a random environmentξ,whereξis an independent and identically distributed sequence of random variables.We show asymptotic properties for all the moments of Z_(n) and describe the decay rates of the n-step transition probabilities.As applications,a large deviation principle for the sequence log Z_(n) is established,and related large deviations are also studied.展开更多
A computational model combining large .eddy simulation with quadrature moment method was em-ployed to study nanoparticle evolution in a confined impinging jet. The investigated particle size is limited in the transien...A computational model combining large .eddy simulation with quadrature moment method was em-ployed to study nanoparticle evolution in a confined impinging jet. The investigated particle size is limited in the transient regime, and the particle collision kernel was obtained by using the theory of flux matching. The simulation was validated by comparing it with the experimental results. The numerical results show coherent structure acts to dominate particle number intensity, size and polydispersity distributions, and it also induce particle-laden iet to be diluted by .the ambient.The evolution of particle dynarnics in.the impinging jet flow are strongly related to the Rey-nolds number and nozzle-to-plate distance, and their relationships were analyzed.展开更多
To improve the accuracy of illumination estimation while maintaining a relative fast execution speed, a novel learning-based color constancy using color edge moments and regularized regression in an anchored neighborh...To improve the accuracy of illumination estimation while maintaining a relative fast execution speed, a novel learning-based color constancy using color edge moments and regularized regression in an anchored neighborhood is proposed. First, scene images are represented by the color edge moments of various orders. Then, an iterative regression with a squared Frobenius norm（F-norm） regularizer is introduced to learn the mapping between the edge moments and illuminants in the neighborhood of the anchored sample.Illumination estimation for the test image finally becomes the nearest anchored point search followed by a matrix multiplication using the associated mapping matrix which can be precalculated and stored. Experiments on two standard image datasets show that the proposed approach significantly outperforms the state-of-the-art algorithms with a performance increase of at least 10. 35% and 7. 44% with regard to median angular error.展开更多
基金supported by the National Social Science Fund of China(No.23BSH123).
文摘Background:Emerging adulthood is a critical period for ego identity exploration and consolidation,and self-presentation on social media constitutes a salient online context for this developmental process.However,limited research has explored the associations between self-presentation on WeChat Moments and ego identity.This study aims to examine these associations,focusing on the mediating role of online positive feedback and the moderating role of gender.Methods:Using a three-wave longitudinal design,this study followed 767 Chinese college students(Mean age=18.96 years)through cluster sampling.Participants completed self-report questionnaires assessing self-presentation on WeChat Moments,online positive feedback,and ego identity status.Data analyses were conducted using mediation modeling and multi-group structural equation modeling.Results:Authentic self-presentation was positively associated with identity achievement and negatively associated with identity diffusion,whereas positive self-presentation was linked to higher levels of identity foreclosure.Online positive feedback played a significant mediating role in the associations between self-presentation strategies and identity statuses,and gender differences were observed in this mediating pathway.For both males and females,authentic self-presentation was associated with higher identity achievement through online positive feedback.However,indirect associations with identity foreclosure and diffusion were observed only among females:authentic self-presentation was linked to lower levels,whereas positive self-presentation was linked to higher levels of foreclosure and diffusion through online positive feedback.No comparable indirect associations were detected among males.Conclusions:Online positive feedback is closely linked to self-presentation strategies and ego identity statuses,with these associations varying by gender.
文摘Beyond business,the CIIE is a vibrant platform where diverse cultures meet,share,and shine The eighth China International Import Expo,held from 5 to 10 November in Shanghai,once again served as a premier stage for exhibitors from around the world to showcase their distinctive cultures.From food and clothing to a wide array of arts,the more than 900,000 visitors were treated to a rich tapestry of cultural experiences from across the globe.
文摘On the morning of 13th September,the themed event Characters:A Bond Connecting Cultures--China Tour:Anyang Moments was held at Yinxu Museum(Museum of the Ruins of the Shang Dynasty).The event was co-hosted by the China NGO Network for International Exchanges(CNIE)and Anyang Municipal People's Government.
文摘This paper employs Granger causality analysis and the generalized impulse response function(GIRF)to study the higher-order moment spillover effects among Bitcoin,stock markets,and foreign exchange markets in the U.S.Using intraday high-frequency data,the research focuses on the interactions across higher-order moments,including volatility,jumps,skewness,and kurtosis.The results reveal significant bidirectional spillover effects between Bitcoin and traditional financial assets,particularly in terms of volatility and jump behavior,indicating that the cryptocurrency market has become a crucial component of global financial risk transmission.This study provides new theoretical perspectives and policy recommendations for global asset allocation,market regulation,and risk management,underscoring the importance of proactive management measures in addressing the complex risk interactions between cryptocurrencies and traditional financial markets.
文摘In the current digital context,safeguarding copyright is a major issue,particularly for architectural drawings produced by students.These works are frequently the result of innovative academic thinking combining creativity and technical precision.They are particularly vulnerable to the risk of illegal reproduction when disseminated in digital format.This research suggests,for the first time,an innovative approach to copyright protection by embedding a double digital watermark to address this challenge.The solution relies on a synergistic fusion of several sophisticated methods:Krawtchouk Optimized Octonion Moments(OKOM),Quaternion Singular Value Decomposition(QSVD),and Discrete Waveform Transform(DWT).To improve watermark embedding,the biologically inspired algorithm Chaos-White Shark Optimization(CWSO)is used,which allows dynamically adapting essential parameters such as the scaling factor of the insertion.Thus,two watermarks are inserted at the same time:an institutional logo and a student image,encoded in the main image(the architectural plan)through octonionic projections.This allows minimizing the amount of data to be integrated while increasing resistance.The suggested approach guarantees a perfect balance between the discreetness of the watermark(validated by PSNR indices>47 dB and SSIM>0.99)and its resistance to different attacks(JPEG compression,noise,rotation,resizing,filtering,etc.),as proven by the normalized correlation values(NC>0.9)obtained following the extraction.Therefore,this method represents a notable progress for securing academic works in architecture,providing an effective,discreet and reversible digital protection,which does not harm the visual appearance of the original works.
基金Supported by the National Key R&D Program of China(Grant No.2021YFA1000700)National Natural Science Foundation of China(Grant No.12031008)。
文摘In this paper, we establish asymptotic formulas for a cubic moment of Dirichlet L-functions restricted to a coset, as well as for a mixed moment of Dirichlet L-functions and twists of GL(2) L-functions along a coset. Our main tool is a power-saving estimate of bilinear forms of hyper-Kloosterman sums due to Kowalski–Michel–Sawin.
基金The National Natural Science Foundation of China(No.61071192,61073138)
文摘To resolve the completeness and independence of an invariant set derived by the traditional method, a systematic method for deriving a complete set of pseudo-Zernike moment similarity （translation, scale and rotation） invariants is described. First, the relationship between pseudo-Zernike moments of the original image and those of the image having the same shape but distinct orientation and scale is established. Based on this relationship, a complete set of similarity invariants can be expressed as a linear combination of the original pseudo-Zernike moments of the same order and lower order. The problem of image reconstruction from a finite set of the pseudo-Zernike moment invariants （PZMIs） is also investigated. Experimental results show that the proposed PZMIs have better performance than complex moment invariants.
基金funded by the Open Access Initiative of the University of Bremen and the DFG via SuUB BremenThe authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Group Project under grant number(RGP2/367/46)+1 种基金This research is supported and funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R410)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a novel,unified deep learning framework for vehicle detection,tracking,counting,and classification in aerial imagery designed explicitly for modern smart city infrastructure demands.Our approach begins with adaptive histogram equalization to optimize aerial image clarity,followed by a cutting-edge scene parsing technique using Mask2Former,enabling robust segmentation even in visually congested settings.Vehicle detection leverages the latest YOLOv11 architecture,delivering superior accuracy in aerial contexts by addressing occlusion,scale variance,and fine-grained object differentiation.We incorporate the highly efficient ByteTrack algorithm for tracking,enabling seamless identity preservation across frames.Vehicle counting is achieved through an unsupervised DBSCAN-based method,ensuring adaptability to varying traffic densities.We further introduce a hybrid feature extraction module combining Convolutional Neural Networks(CNNs)with Zernike Moments,capturing both deep semantic and geometric signatures of vehicles.The final classification is powered by NASNet,a neural architecture search-optimized model,ensuring high accuracy across diverse vehicle types and orientations.Extensive evaluations of the VAID benchmark dataset demonstrate the system’s outstanding performance,achieving 96%detection,94%tracking,and 96.4%classification accuracy.On the UAVDT dataset,the system attains 95%detection,93%tracking,and 95%classification accuracy,confirming its robustness across diverse aerial traffic scenarios.These results establish new benchmarks in aerial traffic analysis and validate the framework’s scalability,making it a powerful and adaptable solution for next-generation intelligent transportation systems and urban surveillance.
基金supported by the National Natural Science Foundation of China(No.62003269).
文摘Computing electrostatic interaction on non-cooperative targets with unknown meshes is crucial for electrostatic-based space on-orbit services.Although meshes for electrostatic interaction computations can be reconstructed from point clouds,they are usually too dense,leading to high computational costs.This paper presents an optimization method for converting dense meshes into optimal meshes,enabling fast and accurate computation of the electrostatic interaction by point clouds.First,the dense mesh reconstructed from point clouds is simplified into a coarse mesh using local operators.Second,the simplified mesh is refined by an iterative strategy that integrates a lightweight method of moments and an impedance matrix inheritance technique,ultimately yielding an optimal mesh for computing the electrostatic interaction.Simulation results show that our method effectively optimizes dense meshes,making electrostatic interaction computations using point clouds approximately 63.4 times more efficient than the previous method.
基金supported by the Youth Program of the National Natural Science Foundation of China under Grant No.12401368the Youth Talent Special Support Program of Yunnan Provincial Xingdian Talent Support Plan+4 种基金the Scientific Research Fund Project of Yunnan Provincial Department of Education under Grant No.2020J0373the Scientific Research Fund Project of Yunnan University of Finance and Economics under Grant No.2022D11supported by the General Programs of the National Natural Science Foundation of China under Grant Nos.12271510 and 11871460the Innovative Research Group Program under Grant No.61621003a grant from the Key Laboratory of Random Complex Structures and Data Science,Chinese Academy of Sciences。
文摘Within the sufficient dimension reduction framework,research on nonignorable missing data remains relatively scarce,primarily due to the associated identifiability issues.This paper considers the problem of sufficient dimension reduction when the response is subject to nonignorable missingness.By adopting a flexible semiparametric missingness mechanism to ensure identifiability,the authors construct three classes of estimating equations based on inverse probability weighting,regression imputation and augmented inverse probability weighting.The novel aspects of the proposed methods also include the incorporation of sufficient dimension reduction techniques in the implementation of these estimating equations to mitigate the high-dimensional effect,and the construction of the estimator for the conditional expectation of the estimating functions given both the covariates and the missingness indicator.The authors prove that the resulting three estimators are asymptotically normally distributed.Comprehensive simulation studies are conducted to assess the finite-sample performance of the proposed methods,and an application to PM2.5 concentration data is also presented.
文摘A detailed understanding of seismicity originating from the Nanga Parbat syntaxis in the northwestern Himalaya is crucial for characterizing the active fault systems and associated neotectonic processes in the region.Continuous earthquake monitoring through local seismic stations enables high-precision results by constraining the velocity structure.In this study,seismogram data from 244 small-magnitude earthquakes are analyzed to delineate the crustal thickness and investigate the source mechanisms beneath the Nanga Parbat syntaxis.The results are achieved with the application of Coupled Hypocenter Velocity Inversion(CHVI)analysis and Time Domain Moment Tensor(TDMT)analysis.The velocity inversion suggests that the Moho discontinuity lies at 60 km depth with an average vP/vS ratio of 1.735±0.017.The minimum 1D velocity model obtained through velocity inversion with least RMS error is further utilized in determining the source mechanism solution.In contrast to earlier studies,which highlighted strike-slip displacement accompanied by reverse dip-slip components,the present research provides a revised interpretation.The moment tensor analysis conducted in this study provides evidence of transtensional deformation associated with neotectonics,attributed to the presence of multiple shear zones.The results of the source mechanism for the selected earthquakes unveiled that the oblique-slip deformation is significantly controlled by the shear stresses coupled with the normal component of dip-slip movement.This is further supported by the higher values of the doublecouple moment tensor(85%),which indicate shear deformation,while the positive value of the compensated linear vector dipole(15%)confirms the presence of a normal component.The coexistence of transpressive and transtensive stresses,together with shallow hypocentral depths and high-amplitude tangential waveforms,can potentially cause devastating impacts in the surroundings of the Nanga Parbat syntaxis.
基金supported in part by the National Natural Science Foundation of China(62506148 and 62476115)the Fundamental Research Funds for the Central Universities(lzujbky-2025-pd05 and lzujbky-2025-ytB01)+2 种基金the Research Grants Council of the Hong Kong Special Administrative Region of China(AoE/E-407/24-N and C1013-24G)the Postdoctoral Fellowship Program(Grade C) of China Postdoctoral Science Foundation(GZC20251039)the Supercomputing Center of Lanzhou University。
文摘In this paper,we propose a learning algorithm termed linear multistep adaptive moment(LMAdam) to enhance the adaptive moment(Adam) algorithm for machine learning.Considering Adam as a single-step discretization of its continuous counterpart,we develop the LMAdam algorithm based on a linear multistep discretization scheme.We design a feedforward neural network for learning the coefficients of the multistep terms with ensured consistency and select the coefficients to ensure zero stability of the multistep terms.We experimentally demonstrate the superiority of the LMAdam via extensive experimentation on benchmark datasets for training various deep neural networks in three applications.
基金the National Natural Science Foundation of China(No.12475119)the Key Laboratory of Nuclear Data Foundation(JCKY2025201C154)the JSPS Grant-in-Aid for Scientific Research(S)(No.20H05648)。
文摘A deep neural network(DNN)was developed to accurately predict the nuclear charge density distributions for nuclei with proton numbers Z≥8.By incorporating essential nuclear structure features,the model achieved a significant improvement in predictive accuracy over conventional methods.The charge density distributions were analyzed using a Fourier-Bessel(FB)series expansion,and the DNN was trained on a comprehensive dataset derived from relativistic continuum Hartree-Bogoliubov(RCHB)theory calculations.The model demonstrated exceptional performance,with root-mean-square deviations of 0.0123fm and 0.0198 fm for the charge radii on the training and validation sets,respectively,which remarkably surpassed the precision of the original RCHB calculations.In addition to advancing nuclear physics research,this high-precision model provides critical data for applications in atomic physics,nuclear astrophysics,and related fields.
基金supported by the National Natural Science Foundation of China (Grant Nos.12090064,12205063,12375088,and W2441004)the Fundamental Research Funds for the Central Universitiesin part by the National Key Research and Development Program of China (Grant No.2020YFC2201501)。
文摘Among the charged leptons,theτelectric dipole moment dτis the least constrained.We show that the Im[d_(τ)]imposes strong constraints on new physics that have yet to be discussed.Motivated in particular by the Super Tau-Charm Facility(STCF),which will provide a uniquely clean environment for precisionτ-physics,we study the momentum-transfer dependence of d_(τ)(q^(2))and compare the projected sensitivities of STCF and BelleⅡ.Our analysis shows that an axion-like coupling of the τ lepton can induce sizable real and imaginary components of the EDM.The predicted EDM values may approach the present experimental sensitivities,making them accessible to future measurements at Belle II and the STCF.
基金supported by the National Natural Science Foundationof China for the Youth(51307004)
文摘When calculating electromagnetic scattering using method of moments （MoM）, integral of the singular term has a significant influence on the results. This paper transforms the singular surface integral to the contour integral. The integrand is expanded to Taylor series and the integral results in a closed form. The cut-off error is analyzed to show that the series converges fast and only about 2 terms can agree wel with the accurate result. The comparison of the perfect electric conductive （PEC） sphere＇s bi-static radar cross section （RCS） using MoM and the accurate method validates the feasibility in manipulating the singularity. The error due to the facet size and the cut-off terms of the series are analyzed in examples.
基金Founded by the National Natural Science Foundation of China （No.40637034, No.40574004）, the National 863 Program of China （No. 2006AA12Z211） and the Fund of Key Lab of Geodynamic Geodesy of Chinese Academy （No. L06-02）.
文摘Based on the gravity field models EGM96 and EIGEN-GL04C, the Earth＇s time-dependent principal moments of inertia A, B, C are obtained, and the variable rotation of the Earth is determined. Numerical results show that A, B, and C have increasing tendencies; the tilt of the rotation axis increases 2.1×10^ 8 mas/yr; the third component of the rotational angular velocity, ω3 , has a decrease of 1.0×10^ 22 rad/s^2, which is around 23% of the present observed value. Studies show in detail that both 0 and ω3 experience complex fluctuations at various time scales due to the variations of A, B and C.
基金the National Natural Science Foundation of China (Grant No. 40975014)the basic scientific and operational project "observation and retrieval of microphysical parameters with multiple wavelength radars"
文摘Radar parameters including radar reflectivity, Doppler velocity, and Doppler spectrum width were obtained from Doppler spectrum moments. The Doppler spectrum moment is the convolution of both the particle spectrum and the mean air vertical motion. Unlike strong precipitation, the motion of particles in cirrus clouds is quite close to the air motion around them. In this study, a method of Doppler moments was developed and used to retrieve cirrus cloud microphysical properties such as the mean air vertical velocity, mass-weighted diameter, effective particle size, and ice content. Ice content values were retrieved using both the Doppler spectrum method and classic Z-IWC （radar reflectivity-ice water content） relationships; however, the former is a more reasonable method.
基金partially supported by the National Nature Science Foundation of China(11601286,11501146)。
文摘Let(Z_(n))be a branching process with immigration in a random environmentξ,whereξis an independent and identically distributed sequence of random variables.We show asymptotic properties for all the moments of Z_(n) and describe the decay rates of the n-step transition probabilities.As applications,a large deviation principle for the sequence log Z_(n) is established,and related large deviations are also studied.
基金Supported by the Ministry of Science and Technology of China (No.2005CCA06900).
文摘A computational model combining large .eddy simulation with quadrature moment method was em-ployed to study nanoparticle evolution in a confined impinging jet. The investigated particle size is limited in the transient regime, and the particle collision kernel was obtained by using the theory of flux matching. The simulation was validated by comparing it with the experimental results. The numerical results show coherent structure acts to dominate particle number intensity, size and polydispersity distributions, and it also induce particle-laden iet to be diluted by .the ambient.The evolution of particle dynarnics in.the impinging jet flow are strongly related to the Rey-nolds number and nozzle-to-plate distance, and their relationships were analyzed.
基金The National Natural Science Foundation of China(No.61503303,51409215)the Fundamental Research Funds for the Central Universities(No.G2015KY0102)
文摘To improve the accuracy of illumination estimation while maintaining a relative fast execution speed, a novel learning-based color constancy using color edge moments and regularized regression in an anchored neighborhood is proposed. First, scene images are represented by the color edge moments of various orders. Then, an iterative regression with a squared Frobenius norm（F-norm） regularizer is introduced to learn the mapping between the edge moments and illuminants in the neighborhood of the anchored sample.Illumination estimation for the test image finally becomes the nearest anchored point search followed by a matrix multiplication using the associated mapping matrix which can be precalculated and stored. Experiments on two standard image datasets show that the proposed approach significantly outperforms the state-of-the-art algorithms with a performance increase of at least 10. 35% and 7. 44% with regard to median angular error.
