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
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
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
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
An effective algorithm is proposed to detect copy-move forgery.In this algorithm,first,the PatchMatch algorithm is improved by using a reliable order-statistics-based approximate nearest neighbor search algorithm(ROSA...An effective algorithm is proposed to detect copy-move forgery.In this algorithm,first,the PatchMatch algorithm is improved by using a reliable order-statistics-based approximate nearest neighbor search algorithm(ROSANNA)to modify the propagation process.Then,fractional quaternion Zernike moments(FrQZMs)are considered to be features extracted from color forged images.Finally,the extracted FrQZMs features are matched by the improved PatchMatch algorithm.The experimental results on two publicly available datasets(FAU and GRIP datasets)show that the proposed algorithm performs better than the state-of-the-art algorithms not only in objective criteria F-measure value but also in visual.Moreover,the proposed algorithm is robust to some attacks,such as additive white Gaussian noise,JPEG compression,rotation,and scaling.展开更多
A new algorithm using orthogonal polynomials and sample moments was presented for estimating probability curves directly from experimental or field data of rock variables. The moments estimated directly from a sample ...A new algorithm using orthogonal polynomials and sample moments was presented for estimating probability curves directly from experimental or field data of rock variables. The moments estimated directly from a sample of observed values of a random variable could be conventional moments (moments about the origin or central moments) and probability-weighted moments (PWMs). Probability curves derived from orthogonal polynomials and conventional moments are probability density functions (PDF), and probability curves derived from orthogonal polynomials and PWMs are inverse cumulative density functions (CDF) of random variables. The proposed approach is verified by two most commonly-used theoretical standard distributions: normal and exponential distribution. Examples from observed data of uniaxial compressive strength of a rock and concrete strength data are presented for illustrative purposes. The results show that probability curves of rock variable can be accurately derived from orthogonal polynomials and sample moments. Orthogonal polynomials and PWMs enable more secure inferences to be made from relatively small samples about an underlying probability curve.展开更多
In order to understand the wave forces and moments on a gravity pier foundation which consists of an upper column and a bottom gravity base,a model experiment with a scale of 1:60 has been conducted in a laboratory fl...In order to understand the wave forces and moments on a gravity pier foundation which consists of an upper column and a bottom gravity base,a model experiment with a scale of 1:60 has been conducted in a laboratory flume.A corresponding numerical calculation by using the boundary element method has been carried out to provide a comparative analysis.It is shown by the comparisons that the numerical wave forces and moments agree well with the experimental results.It is proved that the wave forces and moments acting on the foundation are completely in their inertia dominative areas for wave loads.With the diffraction effects considered into the inertia item,appropriate inertia coefficients are assessed by the experimental results for the inertia item of the Morison equation.The formula of the inertia item can be used to estimate wave forces and moments on such gravity foundations.展开更多
We present the joint probability density function(PDF) between the bucket signals and reference signals in thermal light ghost imaging, by regarding these signals as stochastic variables. The joint PDF allows us to ex...We present the joint probability density function(PDF) between the bucket signals and reference signals in thermal light ghost imaging, by regarding these signals as stochastic variables. The joint PDF allows us to examine the fractional-order moments of the bucket and the reference signals, in which the correlation orders are fractional numbers,other than positive integers in previous studies. The experimental results show that various images can be reconstructed from fractional-order moments. Negative(positive) ghost images are obtained with negative(positive) orders of the bucket signals. The visibility and peak signal-to-noise ratios of the diverse ghost images depend greatly on the fractional orders.展开更多
Non-local means(NLM)method is a state-of-the-art denoising algorithm, which replaces each pixel with a weighted average of all the pixels in the image. However, the huge computational complexity makes it impractical f...Non-local means(NLM)method is a state-of-the-art denoising algorithm, which replaces each pixel with a weighted average of all the pixels in the image. However, the huge computational complexity makes it impractical for real applications. Thus, a fast non-local means algorithm based on Krawtchouk moments is proposed to improve the denoising performance and reduce the computing time. Krawtchouk moments of each image patch are calculated and used in the subsequent similarity measure in order to perform a weighted averaging. Instead of computing the Euclidean distance of two image patches, the similarity measure is obtained by low-order Krawtchouk moments, which can reduce a lot of computational complexity. Since Krawtchouk moments can extract local features and have a good antinoise ability, they can classify the useful information out of noise and provide an accurate similarity measure. Detailed experiments demonstrate that the proposed method outperforms the original NLM method and other moment-based methods according to a comprehensive consideration on subjective visual quality, method noise, peak signal to noise ratio(PSNR), structural similarity(SSIM) index and computing time. Most importantly, the proposed method is around 35 times faster than the original NLM method.展开更多
In order to obtain high order spectral moments, the residual moment M(w(n))(i) = integral(0)(wn) w(i)S(w)dw, as proposed by Denis s, is presented for approximate estimation of spectral moment m(i) = integral(0)(infini...In order to obtain high order spectral moments, the residual moment M(w(n))(i) = integral(0)(wn) w(i)S(w)dw, as proposed by Denis s, is presented for approximate estimation of spectral moment m(i) = integral(0)(infinity) w(i)S(w)dw. Glazman's partial averaging idea is discussed. It is pointed out that Glazman's method and definition of non-dimensional spectral moment can not be used to estimate spectral moments for engineering purposes and that method is not supported by theory and computation. The non-dimensional spectral moment of PM spectrum, which should be expressed as [GRAPHICS] is related to wind speed. The 0 - 8th moments of PM spectrum are estimated for wind speeds of 10, 20 and 30 m/s and some discussions are given.展开更多
A parabolic-bistable potential system driven by colored noise is studied. The exact analytical expressions of the stationary probability distribution (SPD) and the moments of the system are derived. Furthermore, the m...A parabolic-bistable potential system driven by colored noise is studied. The exact analytical expressions of the stationary probability distribution (SPD) and the moments of the system are derived. Furthermore, the mean first-passage time is calculated by the use of two approximate methods, respectively. It is found that (i) the double peaks of SPD are rubbed-down into a flat single peak with the increasing of noise intensity; (ii) a minimum occurs on the curve of the second-order moment of the system vs. noise intensity at the point ; (iii) the results obtained by our approximate approach are in good agreement with the numerical calculations for either small or large correlation time , while the conventional steepest descent approximation leads to poor results.展开更多
Analyzing comovements and connectedness is critical for providing significant implications for crypto-portfolio risk management.However,most existing research focuses on the lower-order moment nexus(i.e.the return and...Analyzing comovements and connectedness is critical for providing significant implications for crypto-portfolio risk management.However,most existing research focuses on the lower-order moment nexus(i.e.the return and volatility interactions).For the first time,this study investigates the higher-order moment comovements and risk connectedness among cryptocurrencies before and during the COVID-19 pandemic in both the time and frequency domains.We combine the realized moment measures and wavelet coherence,and the newly proposed time-varying parameter vector autoregression-based frequency connectedness approach(Chatziantoniou et al.in Integration and risk transmission in the market for crude oil a time-varying parameter frequency connectedness approach.Technical report,University of Pretoria,Department of Economics,2021)using intraday high-frequency data.The empirical results demonstrate that the comovement of realized volatility between BTC and other cryp-tocurrencies is stronger than that of the realized skewness,realized kurtosis,and signed jump variation.The comovements among cryptocurrencies are both time-dependent and frequency-dependent.Besides the volatility spillovers,the risk spillovers of high-order moments and jumps are also significant,although their magnitudes vary with moments,making them moment-dependent as well and are lower than volatility connectedness.Frequency connectedness demonstrates that the risk connectedness is mainly transmitted in the short term(1–7 days).Furthermore,the total dynamic connectedness of all realized moments is time-varying and has been significantly affected by the outbreak of the COVID-19 pandemic.Several practical implications are drawn for crypto investors,portfolio managers,regulators,and policymakers in optimizing their investment and risk management tactics.展开更多
This paper puts forward a Poisson-generalized Pareto (Poisson-GP) distribution. This new form of compound extreme value distribution expands the existing application of compound extreme value distribution, and can be ...This paper puts forward a Poisson-generalized Pareto (Poisson-GP) distribution. This new form of compound extreme value distribution expands the existing application of compound extreme value distribution, and can be applied to predicting financial risk, large insurance settlement and high-grade earthquake, etc. Compared with the maximum likelihood estimation (MLE) and compound moment estimation (CME), probability-weighted moment estimation (PWME) is used to estimate the parameters of the distribution function. The specific formulas are presented. Through Monte Carlo simulation with sample sizes 10, 20, 50, 100, 1 000, it is concluded that PWME is an efficient method and it behaves steadily. The mean square errors (MSE) of estimators by PWME are much smaller than those of estimators by CME, and there is no significant difference between PWME and MLE. Finally, an example of foreign exchange rate is given. For Dollar/Pound exchange rates from 1990-01-02 to 2006-12-29, this paper formulates the distribution function of the largest loss among the investment losses exceeding a certain threshold by Poisson-GP compound extreme value distribution, and obtains predictive values at different confidence levels.展开更多
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 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.
基金The National Natural Science of China(No.61572258,61771231,61772281,61672294)the Priority Academic Program Development of Jiangsu Higher Education Institutionsthe Qing Lan Project of Jiangsu Higher Education Institutions
文摘An effective algorithm is proposed to detect copy-move forgery.In this algorithm,first,the PatchMatch algorithm is improved by using a reliable order-statistics-based approximate nearest neighbor search algorithm(ROSANNA)to modify the propagation process.Then,fractional quaternion Zernike moments(FrQZMs)are considered to be features extracted from color forged images.Finally,the extracted FrQZMs features are matched by the improved PatchMatch algorithm.The experimental results on two publicly available datasets(FAU and GRIP datasets)show that the proposed algorithm performs better than the state-of-the-art algorithms not only in objective criteria F-measure value but also in visual.Moreover,the proposed algorithm is robust to some attacks,such as additive white Gaussian noise,JPEG compression,rotation,and scaling.
文摘A new algorithm using orthogonal polynomials and sample moments was presented for estimating probability curves directly from experimental or field data of rock variables. The moments estimated directly from a sample of observed values of a random variable could be conventional moments (moments about the origin or central moments) and probability-weighted moments (PWMs). Probability curves derived from orthogonal polynomials and conventional moments are probability density functions (PDF), and probability curves derived from orthogonal polynomials and PWMs are inverse cumulative density functions (CDF) of random variables. The proposed approach is verified by two most commonly-used theoretical standard distributions: normal and exponential distribution. Examples from observed data of uniaxial compressive strength of a rock and concrete strength data are presented for illustrative purposes. The results show that probability curves of rock variable can be accurately derived from orthogonal polynomials and sample moments. Orthogonal polynomials and PWMs enable more secure inferences to be made from relatively small samples about an underlying probability curve.
基金the Technology Project of Ministry of Transport of China(No.2011318494150)
文摘In order to understand the wave forces and moments on a gravity pier foundation which consists of an upper column and a bottom gravity base,a model experiment with a scale of 1:60 has been conducted in a laboratory flume.A corresponding numerical calculation by using the boundary element method has been carried out to provide a comparative analysis.It is shown by the comparisons that the numerical wave forces and moments agree well with the experimental results.It is proved that the wave forces and moments acting on the foundation are completely in their inertia dominative areas for wave loads.With the diffraction effects considered into the inertia item,appropriate inertia coefficients are assessed by the experimental results for the inertia item of the Morison equation.The formula of the inertia item can be used to estimate wave forces and moments on such gravity foundations.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11674273,11304016,and 11204062)
文摘We present the joint probability density function(PDF) between the bucket signals and reference signals in thermal light ghost imaging, by regarding these signals as stochastic variables. The joint PDF allows us to examine the fractional-order moments of the bucket and the reference signals, in which the correlation orders are fractional numbers,other than positive integers in previous studies. The experimental results show that various images can be reconstructed from fractional-order moments. Negative(positive) ghost images are obtained with negative(positive) orders of the bucket signals. The visibility and peak signal-to-noise ratios of the diverse ghost images depend greatly on the fractional orders.
基金Supported by the Open Fund of State Key Laboratory of Marine Geology,Tongji University(No.MGK1412)Open Fund(No.PLN1303)of State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation(Southwest Petroleum University)+2 种基金Open Fund of Jiangsu Key Laboratory of Quality Control and Further Processing of Cereals and Oils,Nanjing University of Finance Economics(No.LYPK201304)Foundation of Graduate Innovation Center in NUAA(No.kfjj201430)Fundamental Research Funds for the Central Universities
文摘Non-local means(NLM)method is a state-of-the-art denoising algorithm, which replaces each pixel with a weighted average of all the pixels in the image. However, the huge computational complexity makes it impractical for real applications. Thus, a fast non-local means algorithm based on Krawtchouk moments is proposed to improve the denoising performance and reduce the computing time. Krawtchouk moments of each image patch are calculated and used in the subsequent similarity measure in order to perform a weighted averaging. Instead of computing the Euclidean distance of two image patches, the similarity measure is obtained by low-order Krawtchouk moments, which can reduce a lot of computational complexity. Since Krawtchouk moments can extract local features and have a good antinoise ability, they can classify the useful information out of noise and provide an accurate similarity measure. Detailed experiments demonstrate that the proposed method outperforms the original NLM method and other moment-based methods according to a comprehensive consideration on subjective visual quality, method noise, peak signal to noise ratio(PSNR), structural similarity(SSIM) index and computing time. Most importantly, the proposed method is around 35 times faster than the original NLM method.
基金This work was financially supported by the National Natural Science Foundation of China(Grant No.49776282)
文摘In order to obtain high order spectral moments, the residual moment M(w(n))(i) = integral(0)(wn) w(i)S(w)dw, as proposed by Denis s, is presented for approximate estimation of spectral moment m(i) = integral(0)(infinity) w(i)S(w)dw. Glazman's partial averaging idea is discussed. It is pointed out that Glazman's method and definition of non-dimensional spectral moment can not be used to estimate spectral moments for engineering purposes and that method is not supported by theory and computation. The non-dimensional spectral moment of PM spectrum, which should be expressed as [GRAPHICS] is related to wind speed. The 0 - 8th moments of PM spectrum are estimated for wind speeds of 10, 20 and 30 m/s and some discussions are given.
文摘A parabolic-bistable potential system driven by colored noise is studied. The exact analytical expressions of the stationary probability distribution (SPD) and the moments of the system are derived. Furthermore, the mean first-passage time is calculated by the use of two approximate methods, respectively. It is found that (i) the double peaks of SPD are rubbed-down into a flat single peak with the increasing of noise intensity; (ii) a minimum occurs on the curve of the second-order moment of the system vs. noise intensity at the point ; (iii) the results obtained by our approximate approach are in good agreement with the numerical calculations for either small or large correlation time , while the conventional steepest descent approximation leads to poor results.
文摘Analyzing comovements and connectedness is critical for providing significant implications for crypto-portfolio risk management.However,most existing research focuses on the lower-order moment nexus(i.e.the return and volatility interactions).For the first time,this study investigates the higher-order moment comovements and risk connectedness among cryptocurrencies before and during the COVID-19 pandemic in both the time and frequency domains.We combine the realized moment measures and wavelet coherence,and the newly proposed time-varying parameter vector autoregression-based frequency connectedness approach(Chatziantoniou et al.in Integration and risk transmission in the market for crude oil a time-varying parameter frequency connectedness approach.Technical report,University of Pretoria,Department of Economics,2021)using intraday high-frequency data.The empirical results demonstrate that the comovement of realized volatility between BTC and other cryp-tocurrencies is stronger than that of the realized skewness,realized kurtosis,and signed jump variation.The comovements among cryptocurrencies are both time-dependent and frequency-dependent.Besides the volatility spillovers,the risk spillovers of high-order moments and jumps are also significant,although their magnitudes vary with moments,making them moment-dependent as well and are lower than volatility connectedness.Frequency connectedness demonstrates that the risk connectedness is mainly transmitted in the short term(1–7 days).Furthermore,the total dynamic connectedness of all realized moments is time-varying and has been significantly affected by the outbreak of the COVID-19 pandemic.Several practical implications are drawn for crypto investors,portfolio managers,regulators,and policymakers in optimizing their investment and risk management tactics.
基金National Natural Science Foundation of China (No.70573077)
文摘This paper puts forward a Poisson-generalized Pareto (Poisson-GP) distribution. This new form of compound extreme value distribution expands the existing application of compound extreme value distribution, and can be applied to predicting financial risk, large insurance settlement and high-grade earthquake, etc. Compared with the maximum likelihood estimation (MLE) and compound moment estimation (CME), probability-weighted moment estimation (PWME) is used to estimate the parameters of the distribution function. The specific formulas are presented. Through Monte Carlo simulation with sample sizes 10, 20, 50, 100, 1 000, it is concluded that PWME is an efficient method and it behaves steadily. The mean square errors (MSE) of estimators by PWME are much smaller than those of estimators by CME, and there is no significant difference between PWME and MLE. Finally, an example of foreign exchange rate is given. For Dollar/Pound exchange rates from 1990-01-02 to 2006-12-29, this paper formulates the distribution function of the largest loss among the investment losses exceeding a certain threshold by Poisson-GP compound extreme value distribution, and obtains predictive values at different confidence levels.
