Estimating areal means and variances of forest attributes using the k-Nearest Neighbors technique and satellite imagery

The k-Nearest Neighbor (k-NN) technique has become extremely popular for a variety of forest inventory mapping and estimation applications. Much of this popularity may be attributed to the non-parametric, multivariate features of the technique, its intuitiveness, and its ease of use. When used with satellite imagery and forest inventory plot data, the technique has been shown to produce useful estimates of many forest attributes including forest/non-forest, volume, and basal area. However, variance estimators for quantifying the uncertainty of means or sums of k-NN pixel-level predictions for areas of interest (AOI) consisting of multiple pixels have not been reported. The primary objectives of the study were to derive variance estimators for AOI estimates obtained from k-NN predictions and to compare precision estimates resulting from different approaches to k-NN prediction and different interpretations of those predictions. The approaches were illustrated by estimating proportion forest area, tree volume per unit area, tree basal area per unit area, and tree density per unit area for 10-km AOIs. Estimates obtained using k-NN approaches and traditional inventory approaches were compared and found to be similar. Further, variance estimates based on different interpretations of k-NN predictions were similar. The results facilitate small area estimation and simultaneous and consistent mapping and estimation of multiple forest attributes.     

Application of an improved control-variate scheme to local neoclassical transport simulations

A new radially local neoclassical transport code is developed based on the radially global two-weight δf$\delta f$ Monte Carlo code, FORTEC-3D (Satake et al., 2008). In the collisional two-weight δf$\delta f$ method, the variance of weight increases in time due to the so-called weight spreading, which leads to an increasing numerical noise in long time simulations. A new improved control-variate scheme was proposed by Kleiber et al. (2011) to reduce the variance. We investigate the effectiveness and validity of the new control-variate scheme for a practical collisional transport problem in a plasma described by the drift kinetic equation. It is demonstrated that the new scheme reduces the variance of weight by approximately 75% in an axisymmetric magnetic field configuration. The burst-like behavior of a transport observable caused by a large numerical noise can be avoided. As a result, the time evolution of a transport observable can be successfully smoothed.     

基于逻辑回归模型的木片和树皮的图像识别

为了提高木片生物能的利用率,需要除去木片中的树皮杂质。识别木片和树皮的图像对于实现二者分离具有重要作用。提出一种基于逻辑回归模型来对木片和树皮进行图像识别的算法。算法流程包括计算各种可以描述木片和树皮纹理的参数,利用SAS统计分析出最佳参数,将最佳参数计算所得的样本数据用于SAS LOGISTIC过程得到预测方程,再将预测方程用于逻辑回归模型来实现木片和树皮的图像识别。通过实验可知,最佳参数为灰度方差,该图像识别算法的正确率能达到97.4%。     

Monte Carlo and variance reduction methods for structural reliability analysis: A comprehensive review

Monte Carlo methods have attracted constant and even increasing attention in structural reliability analysis with a wide variety of developments seamlessly presented over decades. Along the way, a number of specialized reviews and benchmark studies have been provided from time to time, aiming at summarizing and comparing selected few approaches in detail, mainly from an implementation point of view. In contrast, the aim of the present survey is to play a comprehensive role as a methodological guidebook on Monte Carlo simulation and its related, especially variance reduction, techniques through a covering of 444 references in the relevant literature. To achieve this goal, we present an extensive review of formulations and techniques along with insightful summaries of developments of existing numerical methods, ranging from the general formulation, sub-categories and variants, to their combined uses with other simulation techniques and surrogate models, as well as the key advantages and assumptions.     

MHD角速度传感器随机漂移误差补偿方法研究

为了补偿磁流体动力学(MHD)角速度传感器的随机漂移误差,在对其建立时间序列模型的基础上,采用卡尔曼滤波算法对MHD角速度传感器的漂移数据进行了处理,并用方差和Allan方差分析的方法,对滤波前后的数据进行了分析对比.实验结果表明此方法能有效地提高MHD角速度传感器的测量精度.     

爱伦·坡《阿芒提拉多的酒桶》的哥特空间批评

爱伦·坡的《阿芒提拉多的酒桶》是一部充满哥特色彩的短篇小说。该小说采用谋杀者蒙特利瑟自述的形式,讲述50年前他对弗图那多的谋杀,呈现了阴森酒窖里性格扭曲的蒙特利瑟活埋弗图那多的恐怖画面。借助当代文学批评理论中的空间话语研究该短篇小说中的哥特书写,从建筑场景、人物并置和叙事特征方面分析小说哥特空间的构建,进一步突出故事的哥特主题——恐怖、扭曲和死亡。     

随机模拟技术在储层预测中的应用

随机模拟是一种基于地质统计学的储层预测方法,将井资料和波阻抗反演结果联合进行模拟,可以提高预测的精度,适用于滚动勘探开发初期及中后期。本次应用在对储层测井响应特征和物性参数分析的基础上,通过直方、变差分析,选择合理的反演参数,进行随机模拟,进而预测储层的分布规律,实际应用表明,随机模拟方法可提高储层反演的分辨率。     

干涉型光纤陀螺随机噪声的分析研究

系统地分析了光纤陀螺所包含随机噪声的种类及其来源和特性,介绍了分析光纤陀螺随机噪声的工具———A llan方差法和国军标模型拟合法。对某型干涉型光纤陀螺的静态实验数据,分别应用上述2种分析方法,计算分析了光纤陀螺信号中的噪声分量。计算结果表明:试验所用的光纤陀螺输出的静态信号中含有量化噪声、角随机游走噪声、角速率随机游走噪声、零偏不稳定性和速率斜坡噪声,其中,角速率随机游走噪声、零偏不稳定性和速率斜坡噪声含量较大。该分析研究对光纤陀螺的研究有很好的应用价值。     

直接测频装置在时域测量中应用

本文介绍时钟频率源在时域中的测量及评估方法,给出PicoTime测试仪的特征及其在时域测量中的应用.     

About the relevance of roughness parameters used for characterizing worn femoral heads

This study aims to contribute to the definition of a methodology, which can help to select a relevant roughness parameter with a view to describing the topography of orthopaedic bearing surfaces. In this investigation, the surface topography of a retrieved titanium alloy (TA6V) femoral head was characterized using visual inspection, optical microscopy and three-dimensional contacting profilometry. A numerical analysis of roughness measurements was then undertaken to assess in a first step the values of different roughness parameters of interest found in papers dealing with the topography of orthopaedic bearing surfaces. In a second step, the Analysis of Variance (ANOVA) and the Computer-Based Bootstrap Method were combined to determine statistically, and without preconceived opinion, which of those parameters is the most relevant to describe the different investigated worn regions of the studied femoral head.