本文主要介绍了GRADE(grading of recommendations assessment,development and evaluation),即推荐分级的评价、制定与评估工作组开发的基于证据形成推荐意见的EtD(evidence to decision),即证据到决策框架,该框架包含提出问题、评价...本文主要介绍了GRADE(grading of recommendations assessment,development and evaluation),即推荐分级的评价、制定与评估工作组开发的基于证据形成推荐意见的EtD(evidence to decision),即证据到决策框架,该框架包含提出问题、评价证据和形成推荐意见3个部分,为从证据形成推荐意见提供了结构化的决策工具。然后以“妊娠期糖尿病非药物管理患者指南”中1个临床问题“与常规护理或者不进行有氧运动相比,有氧运动是否能够降低妊娠期糖尿病(gestational diabetes mellitus,GDM)孕妇的血糖水平,改善妊娠结局?”为例,根据EtD框架,呈现如何从提出问题、评价证据到形成推荐意见的完整过程,为指南制订者形成推荐意见提供思路和方法。展开更多
时间延迟估计在雷达和声纳等方面有着广泛的应用。为了在空间相关或不相关的高斯背景噪声下获得比较精确的时延估计值,提出了一种基于四阶累积量、借助于ETDE(Explicit Time Delay Estimation,利用sinc函数采样FIR滤波器)算法的自适应...时间延迟估计在雷达和声纳等方面有着广泛的应用。为了在空间相关或不相关的高斯背景噪声下获得比较精确的时延估计值,提出了一种基于四阶累积量、借助于ETDE(Explicit Time Delay Estimation,利用sinc函数采样FIR滤波器)算法的自适应时延估计算法。此方法可以抑制相关或不相关高斯噪声的影响,可以跟踪时延,从而保证时延的唯一性,进而得到信号准确的时延估计。该算法在较低信噪比下能得到非高斯信号较准确的时延估计。理论分析和仿真结果证明了算法的有效性。展开更多
To efficiently simulate and calculate the radar cross section(RCS) related electromagnetic problems by employing the finite-difference time-domain(FDTD) algorithm, an efficient stretched coordinate perfectly matched l...To efficiently simulate and calculate the radar cross section(RCS) related electromagnetic problems by employing the finite-difference time-domain(FDTD) algorithm, an efficient stretched coordinate perfectly matched layer(ESC-PML) based upon the exponential time differencing(ETD) method is proposed.The proposed implementation can not only reduce the number of auxiliary variables in the SC-PML regions but also maintain the ability of the original SC-PML in terms of the absorbing performance. Compared with the other existed algorithms, the ETDFDTD method shows the least memory consumption resulting in the computational efficiency. The effectiveness and efficiency of the proposed ESC-PML scheme is verified through the RCS relevant problems including the perfect E conductor(PEC) sphere model and the patch antenna model. The results indicate that the proposed scheme has the advantages of the ETD-FDTD method and ESC-PML scheme in terms of high computational efficiency and considerable computational accuracy.展开更多
The monitoring of flue gas of the thermal power plants is of great significance in energy conservation and environmental protection.Spectral technique has been widely used in the gas monitoring system for predicting t...The monitoring of flue gas of the thermal power plants is of great significance in energy conservation and environmental protection.Spectral technique has been widely used in the gas monitoring system for predicting the concentrations of specific gas components.This paper proposes flue gas monitoring system with empirically-trained dictionary(ETD)to deal with the complexity and biases brought by the uninformative spectral data.Firstly,ETD is extracted from the raw spectral data by an alternative optimization between the sparse coding stage and the dictionary update stage to minimize the error of sparse representation.D1,D2 and D3 are three types of ETD obtained by different methods.Then,the predictive model of component concentration is constructed on the ETD.In the experiments,two real flue gas spectral datasets are collected and the proposed method combined with the partial least squares,the background propagation neural network and the support vector machines are performed.Moreover,the optimal parameters are chosen according to the 10-fold root-mean-square error of cross validation.The experimental results demonstrate that the proposed method can be used for quantitative analysis effectively and ETD can be applied to the gas monitoring systems.展开更多
In this paper, we propose a nearly analytic exponential time difference （NETD） method for solving the 2D acoustic and elastic wave equations. In this method, we use the nearly analytic discrete operator to approxima...In this paper, we propose a nearly analytic exponential time difference （NETD） method for solving the 2D acoustic and elastic wave equations. In this method, we use the nearly analytic discrete operator to approximate the high-order spatial differential operators and transform the seismic wave equations into semi-discrete ordinary differential equations （ODEs）. Then, the converted ODE system is solved by the exponential time difference （ETD） method. We investigate the properties of NETD in detail, including the stability condition for 1-D and 2-D cases, the theoretical and relative errors, the numerical dispersion relation for the 2-D acoustic case, and the computational efficiency. In order to further validate the method, we apply it to simulating acoustic/elastic wave propagation in mul- tilayer models which have strong contrasts and complex heterogeneous media, e.g., the SEG model and the Mar- mousi model. From our theoretical analyses and numerical results, the NETD can suppress numerical dispersion effectively by using the displacement and gradient to approximate the high-order spatial derivatives. In addition, because NETD is based on the structure of the Lie group method which preserves the quantitative properties of differential equations, it can achieve more accurate results than the classical methods.展开更多
文摘本文主要介绍了GRADE(grading of recommendations assessment,development and evaluation),即推荐分级的评价、制定与评估工作组开发的基于证据形成推荐意见的EtD(evidence to decision),即证据到决策框架,该框架包含提出问题、评价证据和形成推荐意见3个部分,为从证据形成推荐意见提供了结构化的决策工具。然后以“妊娠期糖尿病非药物管理患者指南”中1个临床问题“与常规护理或者不进行有氧运动相比,有氧运动是否能够降低妊娠期糖尿病(gestational diabetes mellitus,GDM)孕妇的血糖水平,改善妊娠结局?”为例,根据EtD框架,呈现如何从提出问题、评价证据到形成推荐意见的完整过程,为指南制订者形成推荐意见提供思路和方法。
文摘时间延迟估计在雷达和声纳等方面有着广泛的应用。为了在空间相关或不相关的高斯背景噪声下获得比较精确的时延估计值,提出了一种基于四阶累积量、借助于ETDE(Explicit Time Delay Estimation,利用sinc函数采样FIR滤波器)算法的自适应时延估计算法。此方法可以抑制相关或不相关高斯噪声的影响,可以跟踪时延,从而保证时延的唯一性,进而得到信号准确的时延估计。该算法在较低信噪比下能得到非高斯信号较准确的时延估计。理论分析和仿真结果证明了算法的有效性。
基金supported by the National Natural Science Foundation of China(61571022611971022)。
文摘To efficiently simulate and calculate the radar cross section(RCS) related electromagnetic problems by employing the finite-difference time-domain(FDTD) algorithm, an efficient stretched coordinate perfectly matched layer(ESC-PML) based upon the exponential time differencing(ETD) method is proposed.The proposed implementation can not only reduce the number of auxiliary variables in the SC-PML regions but also maintain the ability of the original SC-PML in terms of the absorbing performance. Compared with the other existed algorithms, the ETDFDTD method shows the least memory consumption resulting in the computational efficiency. The effectiveness and efficiency of the proposed ESC-PML scheme is verified through the RCS relevant problems including the perfect E conductor(PEC) sphere model and the patch antenna model. The results indicate that the proposed scheme has the advantages of the ETD-FDTD method and ESC-PML scheme in terms of high computational efficiency and considerable computational accuracy.
基金supported by the National Natural Science Foundation of China(61375055)the Program for New Century Excellent Talents in University(NCET-12-0447)+2 种基金the Natural Science Foundation of Shaanxi Province of China(2014JQ8365)the State Key Laboratory of Electrical Insulation and Power Equipment(EIPE16313)the Fundamental Research Funds for the Central University
文摘The monitoring of flue gas of the thermal power plants is of great significance in energy conservation and environmental protection.Spectral technique has been widely used in the gas monitoring system for predicting the concentrations of specific gas components.This paper proposes flue gas monitoring system with empirically-trained dictionary(ETD)to deal with the complexity and biases brought by the uninformative spectral data.Firstly,ETD is extracted from the raw spectral data by an alternative optimization between the sparse coding stage and the dictionary update stage to minimize the error of sparse representation.D1,D2 and D3 are three types of ETD obtained by different methods.Then,the predictive model of component concentration is constructed on the ETD.In the experiments,two real flue gas spectral datasets are collected and the proposed method combined with the partial least squares,the background propagation neural network and the support vector machines are performed.Moreover,the optimal parameters are chosen according to the 10-fold root-mean-square error of cross validation.The experimental results demonstrate that the proposed method can be used for quantitative analysis effectively and ETD can be applied to the gas monitoring systems.
文摘In this paper, we propose a nearly analytic exponential time difference （NETD） method for solving the 2D acoustic and elastic wave equations. In this method, we use the nearly analytic discrete operator to approximate the high-order spatial differential operators and transform the seismic wave equations into semi-discrete ordinary differential equations （ODEs）. Then, the converted ODE system is solved by the exponential time difference （ETD） method. We investigate the properties of NETD in detail, including the stability condition for 1-D and 2-D cases, the theoretical and relative errors, the numerical dispersion relation for the 2-D acoustic case, and the computational efficiency. In order to further validate the method, we apply it to simulating acoustic/elastic wave propagation in mul- tilayer models which have strong contrasts and complex heterogeneous media, e.g., the SEG model and the Mar- mousi model. From our theoretical analyses and numerical results, the NETD can suppress numerical dispersion effectively by using the displacement and gradient to approximate the high-order spatial derivatives. In addition, because NETD is based on the structure of the Lie group method which preserves the quantitative properties of differential equations, it can achieve more accurate results than the classical methods.
