An improved multidirectional velocity model was proposed for more accurately locating micro-seismic events in rock engineering. It was assumed that the stress wave propagation velocities from a micro-seismic source to...An improved multidirectional velocity model was proposed for more accurately locating micro-seismic events in rock engineering. It was assumed that the stress wave propagation velocities from a micro-seismic source to three nearest monitoring sensors in a sensor's array arrangement were the same. Since the defined objective function does not require pre-measurement of the stress wave propagation velocity in the field, errors from the velocity measurement can be avoided in comparison to three traditional velocity models. By analyzing 24 different cases, the proposed multidirectional velocity model iterated by the Simplex method is found to be the best option no matter the source is within the region of the sensor's array or not. The proposed model and the adopted iterative algorithm are verified by field data and it is concluded that it can significantly reduce the error of the estimated source location.展开更多
We review some recent approaches to robust approximations of low-rank data matrices.We consider the problem of estimating a low-rank mean matrix when the data matrix is subject to measurement errors as well as gross o...We review some recent approaches to robust approximations of low-rank data matrices.We consider the problem of estimating a low-rank mean matrix when the data matrix is subject to measurement errors as well as gross outliers in some of its entries.The purpose of the paper is to make various algorithms accessible with an understanding of their abilities and limitations to perform robust low-rank matrix approximations in both low and high dimensional problems.展开更多
Design and realization of random measurement scheme for compressed sensing （CS） are presented in this paper, and lower limits of the measurement number are achieved when the precise reconstruction is realized. Four ...Design and realization of random measurement scheme for compressed sensing （CS） are presented in this paper, and lower limits of the measurement number are achieved when the precise reconstruction is realized. Four kinds of random measurement matrices are designed according to the constraint conditions of random measurement. The performance is tested employing the algorithm of stagewise orthogonal matching pursuit （STOMP）. Results of the experiment show that lower limits of the measurement number are much better than the results described in Refs.[ 13-15]. When the ratios of measurement to sparsity are 3.8 and 4.0, the mean relative errors of the reconstructed signals are 8.57 × 10^-13 and 2.43 × 10^-14, respectively, which confh-rns that the random measurement scheme of this paper is very effective.展开更多
For surface hardening of metal,a quasi-Dammann grating (QDG) is proposed and fabricated to generate array spots with proportional-intensity distribution.To get uniformly hardened band distribution and improve the wear...For surface hardening of metal,a quasi-Dammann grating (QDG) is proposed and fabricated to generate array spots with proportional-intensity distribution.To get uniformly hardened band distribution and improve the wear resistance of the sample surface,a three-order QDG is designed to produce array spots with enhanced intensity in the edge.The design and fabrication of the QDG are described in detail.The surface profile of the fabricated grating was measured,which shows that the fabrication error is less than 2%.The laser beam intensity distribution shaped by the QDG was tested by a laser beam analyzer to verify the validity of the QDG.The application of the QDG in the laser surface hardening of metal was experimentally investigated,and the results show that the hardness distribution of the modified layer and the wear resistance of the sample surface are improved significantly by using the QDG.展开更多
This paper studies the estimation and inference for a class of varying-coefficient regression models with error-prone covariates.The authors focus on the situation where the covariates are unobserved,there are no repe...This paper studies the estimation and inference for a class of varying-coefficient regression models with error-prone covariates.The authors focus on the situation where the covariates are unobserved,there are no repeated measurements,and the covariance matrix of the measurement errors is unknown,but some auxiliary information is available.The authors propose an instrumental variable type local polynomial estimator for the unknown varying-coefficient functions,and show that the estimator achieves the optimal nonparametric convergence rate,is asymptotically normal,and avoids using undersmoothing to allow the bandwidths to be selected using data-driven methods.A simulation is carried out to study the finite sample performance of the proposed estimator,and a real date set is analyzed to illustrate the usefulness of the developed methodology.展开更多
基金Project(IRT0950)supported by the Cheung Kong Scholars and the Development Plan of Innovative Team,ChinaProject supported by China Scholarship Council
文摘An improved multidirectional velocity model was proposed for more accurately locating micro-seismic events in rock engineering. It was assumed that the stress wave propagation velocities from a micro-seismic source to three nearest monitoring sensors in a sensor's array arrangement were the same. Since the defined objective function does not require pre-measurement of the stress wave propagation velocity in the field, errors from the velocity measurement can be avoided in comparison to three traditional velocity models. By analyzing 24 different cases, the proposed multidirectional velocity model iterated by the Simplex method is found to be the best option no matter the source is within the region of the sensor's array or not. The proposed model and the adopted iterative algorithm are verified by field data and it is concluded that it can significantly reduce the error of the estimated source location.
基金supported by National Natural Science Foundation of China (Grant No. 11571218)the State Key Program in the Major Research Plan of National Natural Science Foundation of China (Grant No. 91546202)+1 种基金Program for Changjiang Scholars and Innovative Research Team in Shanghai University of Finance and Economics (Grant No. IRT13077)Program for Innovative Research Team of Shanghai University of Finance and Economics
文摘We review some recent approaches to robust approximations of low-rank data matrices.We consider the problem of estimating a low-rank mean matrix when the data matrix is subject to measurement errors as well as gross outliers in some of its entries.The purpose of the paper is to make various algorithms accessible with an understanding of their abilities and limitations to perform robust low-rank matrix approximations in both low and high dimensional problems.
基金supported by the National Natural Science Foundation of China(Nos.61072111 and 60672156)the Project of Science and Technology Commission of Jilin Province(Nos.20100503 and 20110360)
文摘Design and realization of random measurement scheme for compressed sensing （CS） are presented in this paper, and lower limits of the measurement number are achieved when the precise reconstruction is realized. Four kinds of random measurement matrices are designed according to the constraint conditions of random measurement. The performance is tested employing the algorithm of stagewise orthogonal matching pursuit （STOMP）. Results of the experiment show that lower limits of the measurement number are much better than the results described in Refs.[ 13-15]. When the ratios of measurement to sparsity are 3.8 and 4.0, the mean relative errors of the reconstructed signals are 8.57 × 10^-13 and 2.43 × 10^-14, respectively, which confh-rns that the random measurement scheme of this paper is very effective.
基金supported by the National Natural Science Foundation of China (Grant No.10832011)the National Science Foundation for Postdoctoral Scientists of China (Grant No.20100470139)
文摘For surface hardening of metal,a quasi-Dammann grating (QDG) is proposed and fabricated to generate array spots with proportional-intensity distribution.To get uniformly hardened band distribution and improve the wear resistance of the sample surface,a three-order QDG is designed to produce array spots with enhanced intensity in the edge.The design and fabrication of the QDG are described in detail.The surface profile of the fabricated grating was measured,which shows that the fabrication error is less than 2%.The laser beam intensity distribution shaped by the QDG was tested by a laser beam analyzer to verify the validity of the QDG.The application of the QDG in the laser surface hardening of metal was experimentally investigated,and the results show that the hardness distribution of the modified layer and the wear resistance of the sample surface are improved significantly by using the QDG.
基金supported by the Graduate Student Innovation Foundation of SHUFE(#CXJJ-2011-351)supported by the Natural Sciences and Engineering Research Council of Canada
文摘This paper studies the estimation and inference for a class of varying-coefficient regression models with error-prone covariates.The authors focus on the situation where the covariates are unobserved,there are no repeated measurements,and the covariance matrix of the measurement errors is unknown,but some auxiliary information is available.The authors propose an instrumental variable type local polynomial estimator for the unknown varying-coefficient functions,and show that the estimator achieves the optimal nonparametric convergence rate,is asymptotically normal,and avoids using undersmoothing to allow the bandwidths to be selected using data-driven methods.A simulation is carried out to study the finite sample performance of the proposed estimator,and a real date set is analyzed to illustrate the usefulness of the developed methodology.
