Let{Xn:n≥1}be a sequence of independent random variables with common general error distribution GED(v)with shape parameter v>0,and let Mn,r denote the r-th largest order statistics of X1,X2,...,Xn.With different n...Let{Xn:n≥1}be a sequence of independent random variables with common general error distribution GED(v)with shape parameter v>0,and let Mn,r denote the r-th largest order statistics of X1,X2,...,Xn.With different normalizing constants the distributional expansions and the uniform convergence rates of normalized powered order statistics|Mn,r|p are established.An alternative method is presented to estimate the probability of the r-th extremes.Numerical analyses are provided to support the main results.展开更多
This paper describes a novel modeling method for determining the thermal deformation coefficient of the moving shaft of a machine tool.Firstly,the relation between the thermal deformation coefficient and the thermal e...This paper describes a novel modeling method for determining the thermal deformation coefficient of the moving shaft of a machine tool.Firstly,the relation between the thermal deformation coefficient and the thermal expansion coefficient is expounded,revealing that the coefficient of thermal deformation is an important factor affecting the precision of moving shaft feed systems.Then,thermal errors and current boundary and machining conditions are measured using sensors to obtain the first set of parameters for a thermal prediction model.The dynamic characteristics of the positioning and straightness thermal errors of the moving axis of a machine tool are analyzed under different feed speeds and mounting modes of the moving shaft and bearing.Finally,the theoretical model is derived from experimental data,and the axial and radial thermal deformation coefficients at different time and positions are obtained.The expressions for the axial and radial thermal deformation of the moving shaft are modified according to theoretical considerations,and the thermal positioning and straightness error models are established and experimentally verified.This modeling method can be easily extended to other machine tools to determine thermal deformation coefficients that are robust and self-correcting.展开更多
Reversible data hiding(RDH)is a method to embed messages into an image that human eyes are difficult to recognize the differences between the original image and the embedded image.The method needs to make sure that th...Reversible data hiding(RDH)is a method to embed messages into an image that human eyes are difficult to recognize the differences between the original image and the embedded image.The method needs to make sure that the original image and the embedded information can be exactly recovered.The prediction-error expansion(PEE)is a successful way to realize RDH.However,it is fixed when pairing the conventional twodimensional prediction-error histogram(2D-PEH).So,the embedding capacity(EC)and embedding distortion(ED)are not satisfactory.In this study,we propose a method called greedy pairing prediction-error expansion(GPPEE)based on pairwise RDH and demonstrate GPPEE can achieve a more efficient embedding goal and reduce ED.展开更多
In this paper, we consider the solution of the biharmonic equation using Adini nonconforming finite element, and report new results of the asymptotic error expansions of the interpolation error functionals and nonconf...In this paper, we consider the solution of the biharmonic equation using Adini nonconforming finite element, and report new results of the asymptotic error expansions of the interpolation error functionals and nonconforming remainder. These expansions are used to develop two extrapolation formulas and a series of sharp error estimates. Finally, the numerical results have verified the extrapolation theory.展开更多
文摘Let{Xn:n≥1}be a sequence of independent random variables with common general error distribution GED(v)with shape parameter v>0,and let Mn,r denote the r-th largest order statistics of X1,X2,...,Xn.With different normalizing constants the distributional expansions and the uniform convergence rates of normalized powered order statistics|Mn,r|p are established.An alternative method is presented to estimate the probability of the r-th extremes.Numerical analyses are provided to support the main results.
基金This work is financially supported by the National Natural Science Foundation of China(Grant Nos.51775277 and 51575272).
文摘This paper describes a novel modeling method for determining the thermal deformation coefficient of the moving shaft of a machine tool.Firstly,the relation between the thermal deformation coefficient and the thermal expansion coefficient is expounded,revealing that the coefficient of thermal deformation is an important factor affecting the precision of moving shaft feed systems.Then,thermal errors and current boundary and machining conditions are measured using sensors to obtain the first set of parameters for a thermal prediction model.The dynamic characteristics of the positioning and straightness thermal errors of the moving axis of a machine tool are analyzed under different feed speeds and mounting modes of the moving shaft and bearing.Finally,the theoretical model is derived from experimental data,and the axial and radial thermal deformation coefficients at different time and positions are obtained.The expressions for the axial and radial thermal deformation of the moving shaft are modified according to theoretical considerations,and the thermal positioning and straightness error models are established and experimentally verified.This modeling method can be easily extended to other machine tools to determine thermal deformation coefficients that are robust and self-correcting.
基金supported by MOST under Grants No.107-2221-E-845-002-MY3 and No.110-2221-E-845-002-。
文摘Reversible data hiding(RDH)is a method to embed messages into an image that human eyes are difficult to recognize the differences between the original image and the embedded image.The method needs to make sure that the original image and the embedded information can be exactly recovered.The prediction-error expansion(PEE)is a successful way to realize RDH.However,it is fixed when pairing the conventional twodimensional prediction-error histogram(2D-PEH).So,the embedding capacity(EC)and embedding distortion(ED)are not satisfactory.In this study,we propose a method called greedy pairing prediction-error expansion(GPPEE)based on pairwise RDH and demonstrate GPPEE can achieve a more efficient embedding goal and reduce ED.
文摘In this paper, we consider the solution of the biharmonic equation using Adini nonconforming finite element, and report new results of the asymptotic error expansions of the interpolation error functionals and nonconforming remainder. These expansions are used to develop two extrapolation formulas and a series of sharp error estimates. Finally, the numerical results have verified the extrapolation theory.
