Mechanical properties of wood materials using near-infrared spectroscopy based on correlation local embedding and partial least-squares

This study used near-infrared(NIR)spectroscopy to predict mechanical properties of wood.NIR spectra were collected in wavelengths 900–1700 nm,and spectra averaged by radial and tangential surface spectra were used to establish a partial least square(PLS)model based on correlation local embedding(CLE).Mongolian oak(Quercus mongolica Fisch.ex Ledeb.)was used to test the eff ectiveness of the model.The cross-validation method was used to verify the robustness of the CLE–PLS model.Ninety samples were tested as the calibration set and forty-fi ve as the validation set.The results show that the prediction coeffi cient of determination(R2 p)is 0.80 for MOR,and 0.78 for MOE.The ratio of performance to deviation is 2.23 for MOR and 2.15 for MOE.

Experimental Study of Submergence Ratio on Local Scour Around a Square Pile in Steady Flow

Scour around a submerged square pile was realized experimentally in a steady flow to study the effects of flow depth on local scour.Flow depth to pile height ratios ranging from 1.5 to 5 in uniform sand and 2 to 5 in non-uniform sand were tested in the approaching flow velocity to critical velocity(larger than which the sediment particle is motivated)ratios of 0.56 and 1.03,respectively.The influences of flow depth were investigated on the basis of analysis of the three-dimensional topography,temporal maximum scour depth,bed profile development,and equilibrium scour depth.Results showed that the maximum scour depth was at the upstream corners of the pile other than at the stagnation point.The evolutions of the maximum scour depth data in non-uniform sand were well fitted with a recent exponential function,which characterized the initial,developing,and equilibrium stages of scour depth.The scour hole slopes upstream of the pile were found to be parallel to each other in the process of each test and were mainly governed by the sediment repose underwater.The equilibrium scour depth varied slightly with flow depth when the submergence ratio was larger than 1 in uniform sand while it was 2 in non-uniform sand.The armoring effects of coarse sediment particles markedly reduced the sediment transport in non-uniform sand despite the 0.34 increment in non-uniformity.

A MESHLESS LOCAL PETROV-GALERKIN METHOD FOR GEOMETRICALLY NONLINEAR PROBLEMS

Nonlinear formulations of the meshless local Petrov-Galerkin （MLPG） method are presented for geometrically nonlinear problems. The method requires no mesh in computation and therefore avoids mesh distortion difficulties in the large deformation analysis. The essential boundary conditions in the present formulation axe imposed by a penalty method. An incremental and iterative solution procedure is used to solve geometrically nonlinear problems. Several examples are presented to demonstrate the effectiveness of the method in geometrically nonlinear problems analysis. Numerical results show that the MLPG method is an effective one and that the values of the unknown variable are quite accurate.

NUMERICAL ANALYSIS OF MINDLIN SHELL BY MESHLESS LOCAL PETROV-GALERKIN METHOD

The objectives of this study are to employ the meshless local Petrov-Galerkin method （MLPGM） to solve three-dimensional shell problems. The computational accuracy of MLPGM for shell problems is affected by many factors, including the dimension of compact support domain, the dimension of quadrture domain, the number of integral cells and the number of Gauss points. These factors＇ sensitivity analysis is to adopt the Taguchi experimental design technology and point out the dimension of the quadrature domain with the largest influence on the computational accuracy of the present MLPGM for shells and give out the optimum combination of these factors. A few examples are given to verify the reliability and good convergence of MLPGM for shell problems compared to the theoretical or the finite element results.

A STUDY ON THE WEIGHT FUNCTION OF THE MOVING LEAST SQUARE APPROXIMATION IN THE LOCAL BOUNDARY INTEGRAL EQUATION METHOD

The meshless method is a new numerical technique presented in recent years.It uses the moving least square(MLS)approximation as a shape function.The smoothness of the MLS approximation is determined by that of the basic function and of the weight function,and is mainly determined by that of the weight function.Therefore,the weight function greatly affects the accuracy of results obtained.Different kinds of weight functions,such as the spline function, the Gauss function and so on,are proposed recently by many researchers.In the present work,the features of various weight functions are illustrated through solving elasto-static problems using the local boundary integral equation method.The effect of various weight functions on the accuracy, convergence and stability of results obtained is also discussed.Examples show that the weight function proposed by Zhou Weiyuan and Gauss and the quartic spline weight function are better than the others if parameters c and α in Gauss and exponential weight functions are in the range of reasonable values,respectively,and the higher the smoothness of the weight function,the better the features of the solutions.

Novel passive localization algorithm based on weighted restricted total least square

A novel multi-observer passive localization algorithm based on the weighted restricted total least square （WRTLS） is proposed to solve the bearings-only localization problem in the presence of observer position errors. Firstly, the unknown matrix perturbation information is utilized to form the WRTLS problem. Then, the corresponding constrained optimization problem is transformed into an unconstrained one, which is a generalized Rayleigh quotient minimization problem. Thus, the solution can be got through the generalized eigenvalue decomposition and requires no initial state guess process. Simulation results indicate that the proposed algorithm can approach the Cramer-Rao lower bound （CRLB）, and the localization solution is asymptotically unbiased.

Chaotic time series multi-step direct prediction with partial least squares regression

Considering chaotic time series multi-step prediction, multi-step direct prediction model based on partial least squares （PLS） is proposed in this article, where PLS, the method for predicting a set of dependent variables forming a large set of predictors, is used to model the dynamic evolution between the space points and the corresponding future points. The model can eliminate error accumulation with the common single-step local model algorithm~ and refrain from the high multi-collinearity problem in the reconstructed state space with the increase of embedding dimension. Simulation predictions are done on the Mackey-Glass chaotic time series with the model. The satisfying prediction accuracy is obtained and the model efficiency verified. In the experiments, the number of extracted components in PLS is set with cross-validation procedure.

Constrained Weighted Least Squares Location Algorithm Using Received Signal Strength Measurements

Determine the location of a target has gained considerable interest over the past few years. The Received Signal Strength(RSS) measurements and Differential RSS(DRSS) measurements can be converted to distance or distance ratio estimates for constructing a set of linear equations. Based on these linear equations, a constrained weighted least Squares(CWLS) algorithm for target localization is derived. In addition, an iterative technique based on Newton's method is utilized to give a solution. The covariance and bias of the CWLS algorithm is derived using perturbation analysis. Simulation shows that the proposed estimator achieves better performance than existing algorithms with reasonable complexity.

Quasi Ellipsoid Gear Surface Reconstruction Based on Meshless Local Petrov-Galerkin Method and Transmission Characteristic

Special transmission 3D model simulation must be based on surface discretization and reconstruction, but special transmission usually has complicated tooth shape and movement, so present software can＇t provide technical support for special transmission 3D model simulation. Currently, theoretical calculation and experimental method are difficult to exactly solve special transmission contact analysis problem. How to reduce calculation and computer memories consume and meet calculation precision is key to resolve special transmission contact analysis problem. According to 3D model simulation and surface reconstruction of quasi ellipsoid gear is difficulty, this paper employes meshless local Petrov-Galerkin （MLPG） method. In order to reduce calculation and computer memories consume, we disperse tooth mesh into finite points--sparseness points cloud or grid mesh, and then we do interpolation reconstruction in some necessary place of the 3D surface model during analysis. Moving least square method （MLSM） is employed for tooth mesh interpolation reconstruction, there are some advantages to do interpolation by means of MLSM, such as high precision, good flexibility and no require of tooth mesh discretization into units. We input the quasi ellipsoid gear reconstruction model into simulation software, we complete tooth meshing simulation. Simulation transmission ratio during meshing period was obtained, compared with theoretical transmission ratio, the result inosculate preferably. The method using curve reconstruction realizes surface reconstruction, reduce simulation calculation enormously, so special gears simulation can be realized by minitype computer. The method provides a novel solution for special transmission 3D model simulation analysis and contact analysis.

GIS-Based Local Spatial Statistical Model of Cholera Occurrence: Using Geographically Weighted Regression

Global statistical techniques often assume homogeneity of relationships between dependent variable and predictors across space. This assumption has been criticized by statistical geographers as a fundamental weakness that may yield misleading result when it is applied to dataset with spatial context. To strengthen this weakness, a new method that accounts for heterogeneity in relationships across geographic space has been presented. This is one of the family of local spatial statistical techniques referred to as geographically weighted regression (GWR). The method captures non-stationarity of relationship in spatial data that the ordinary least square (OLS) regression fails to account for. Thus, the paper is designed to explore and analyze the spatial relationships between cholera occurrence and household sources of water supply using GIS-based GWR, also to compare the modeling fitness of OLS and GWR. Vector dataset (spatial) of the study region by state levels and statistical data (non-spatial) on cholera cases, household sources of water supply and population data were used in this exploratory analysis. The result shows that GWR is a significant improvement on the global model. Comparing both models with the AICc value and the R2 value revealed that for the former, the value is reduced from 698.7 (for OLS model) to 691.5 (for GWR model). For the latter, OLS explained 66.4 percent while GWR explained 86.7 percent. This implies that local model’s fitness is higher than global model. In addition, the empirical analysis revealed that cholera occurrence in the study region is significantly associated with household sources of water supply. This relationship, as detected by GWR, largely varies across the region.

Prediction of the Local Scour at the Bridge Square Pier Using a 3D Numerical Model

In this paper, the problem on local scour around a single square pier was studied by using both the numerical and physical models. The numerical model for the study is FSUM based on a finite-difference method to solve the Reynolds averaged Navier-Stokes equations (RANS) and the equations for suspended sediment concentration and bed morphology. The computed result was verified through data measured in the experimental flume with a sand bed. In general, the typical features of local scour around the pier were successfully simulated by FSUM, such as stream flow, bow flow, down flow, horseshoe vortex. The comparison between the computation and experiment data shows a quite good fitness. Both numerical model and experiment results show that the maximum scour depth occurs at two front edges of the pier. Although the computed result shows a little bigger scour depth in comparison with the measurement in the physical model, it still confirms the reliability of numerical model in some measure.

Dimension decomposition algorithm for multiple source localization using uniform circular array

A dimension decomposition(DIDE)method for multiple incoherent source localization using uniform circular array(UCA)is proposed.Due to the fact that the far-field signal can be considered as the state where the range parameter of the nearfield signal is infinite,the algorithm for the near-field source localization is also suitable for estimating the direction of arrival(DOA)of far-field signals.By decomposing the first and second exponent term of the steering vector,the three-dimensional(3-D)parameter is transformed into two-dimensional(2-D)and onedimensional(1-D)parameter estimation.First,by partitioning the received data,we exploit propagator to acquire the noise subspace.Next,the objective function is established and partial derivative is applied to acquire the spatial spectrum of 2-D DOA.At last,the estimated 2-D DOA is utilized to calculate the phase of the decomposed vector,and the least squares(LS)is performed to acquire the range parameters.In comparison to the existing algorithms,the proposed DIDE algorithm requires neither the eigendecomposition of covariance matrix nor the search process of range spatial spectrum,which can achieve satisfactory localization and reduce computational complexity.Simulations are implemented to illustrate the advantages of the proposed DIDE method.Moreover,simulations demonstrate that the proposed DIDE method can also classify the mixed far-field and near-field signals.

曲线曲面局部最小二乘渐进迭代逼近

作为一种有效的大数据拟合方法,曲线曲面最小二乘渐进迭代逼近方法(LSPIA)吸引了众多研究者的关注,并获得了广泛的应用。针对LSPIA算法拟合局部数据点效果较差的问题,提出了一种局部的LSPIA算法,称为LOCAL-LSPIA。首先,给定初始曲线(曲面)并从给定的数据点中选择部分数据点;然后在初始曲线(曲面)上选择需要调整的控制点;最后,LOCAL-LSPIA通过迭代调整这一部分控制点来生成一系列局部变化的拟合曲线(曲面),并且保证生成的曲线(曲面)的极限是在仅调整这部分控制点的情况下拟合部分数据点的最小二乘结果。在多个曲线曲面拟合上的实验结果表明,为达到相同的拟合精度,LOCAL-LSPIA算法比LSPIA算法需要的步骤和运算时间更少。因此,LOCAL-LSPIA是有效的,而且在拟合局部数据的情况下比LSPIA算法的收敛速度更快。

NIR光谱的LLE-PLS非线性建模方法及应用

传统的偏最小二乘(PLS)建模方法不能有效反映近红外(NIR)光谱与分析样本的物理化学性质之间存在的非线性关系。局部线性嵌入(LLE)是一种新的非线性降维方法,属于流形学习方法,它能有效地发现高维数据中的本真低维结构。结合LLE和PLS,提出一种近红外光谱非线性建模的新方法,并用于建立丹参多酚酸盐柱层析过程中丹酚酸B含量的回归校正模型。该方法首先用LLE对NIR光谱数据降维,再用PLS建立校正模型。结果表明,与多元散射校正、一阶导等预处理方法结合PLS建模比较,参数优化后的LLE-PLS方法能更准确地预测丹酚酸B的含量,其交叉验证均方根误差为0.128mg.mL-1、决定系数为0.9988。基于NIR光谱及LLE-PLS建模,可实现丹参多酚酸盐柱层析过程的在线检测。

水流强度对淹没式方桩局部冲刷特性的影响

为研究不同水流强度作用下淹没式方桩的局部冲刷特性及流场变化,开展了非均匀沙条件下的桩基局部冲刷试验,分析了桩周的冲刷地形、冲刷深度变化规律;利用OpenFOAM对不同水流强度下的桩周流场进行了模拟,讨论了桩前马蹄涡、桩周回流和下降水流的分布特点。结果表明:在清水冲刷条件下,桩周的冲刷坑深度、沙丘高度和受冲刷影响区域大小均随水流强度的增大而增大;在平衡冲刷地形下,高水流强度冲刷后桩周流动更加复杂,冲刷坑内的涡流强度大幅度提高;当水流强度接近1时,粗颗粒泥沙对细颗粒的屏蔽效应会在一定程度上影响桩周最大冲刷深度。

NIR光谱结合LLE-PLS建模用于安神补脑液提取过程分析的研究

目的:探讨安神补脑液提取过程近红外(NIR)光谱分析的可行性及其方法。方法:提出NIR光谱建模的局部线性嵌入(LLE)-偏最小二乘(PLS)方法,该方法首先用LLE对NIR光谱数据降维,再用PLS建立校正模型。结果:参数优化后的LLE-PLS,二苯乙烯苷留-法交叉验证均方根误差(RMSECV)为0.0457mg/mL、决定系数(R2)为0.9673,淫羊藿苷RMSECV为0.0333mg/mL、R2为0.9809,均优于常规的PLS建模方法。结论:基于NIR光谱和LLE-PLS方法可实现安神补脑液提取过程的在线分析。

融合改进YOLOv7与UNet的编码点定位方法

针对编码点的定位存在误检率高和精准度差的问题,提出了一种融合改进YOLOv7与UNet的圆形编码点定位方法。第1阶段使用改进的YOLOv7检测编码点的位置,改进的YOLOv7首先将DCN-v2可变形卷积引入ELAN模块,提升特征提取能力;其次把卷积块注意力模块(CBAM)机制嵌入骨干网络使网络更关注目标特征;然后使用Focal-EIoU Loss提高收敛速度;最后构建OD-Cat模块替换ConCat模块以提升网络检测精度。提取出每个圆形编码点的ROI后,第2阶段通过UNet分割出编码点的中心轮廓后,使用最小二乘法拟合出编码点的中心。实验结果表明,改进后的模型比原YOLOv7的精确率提高了6.33%,平均精度均值(mAP)提升了5.76%;提出的定位方法验证了在噪声、亮度不足或曝光等复杂环境下可以准确定位出编码点的中心椭圆轮廓,在实际工业视觉测量中具备鲁棒性。

未知信号传播速度的TDOA定位方法研究

研究了未知信号传播速度时的到达时间差(Time-Difference-Of-Arrival,TDOA)定位问题,提出两种联合估计信号传播速度和目标位置的定位方法。第一种方法为两步加权最小二乘方法。在该方法中,首先不考虑变量之间关系,得到一个关于未知变量的初始加权最小二乘估计。为改进第一步估计的性能,第二步考虑第一步估计中变量之间的关系,将其转换为一个标准的广义信赖域子问题,最终获得更高精度的估计性能。第二种方法为半正定松弛方法,通过构建非线性非凸加权最小二乘问题,然后利用半正定松弛技术将其松弛为凸的半正定规划问题,容易求解。仿真结果表明,所提两种方法均能够在高斯噪声下,且噪声不太大时达到克拉美-罗界。

基于正交拉丁方的局部修复码构造

针对目前具有(r,t)局部性的局部修复码码率较低且构造过程中计算复杂度过高的问题,提出基于正交拉丁方的二元局部修复码构造方法.根据正交拉丁方元素与矩阵位置的对应关系构造关联矩阵,得到具有全符号局部性的局部修复码(AS-LRCs),该码的码率和码长渐近边界条件,且最小距离较大.利用关联矩阵级联单位矩阵构造信息位具有(r,t=2)局部性的单校验局部修复码,该码的最小距离和码率均满足最优边界条件,为最优局部修复码.考虑到实际分布式存储系统中存在高故障率节点,利用正交拉丁方完备组构造具有信息位局部性的高可用性单校验局部修复码(IS-LRCs),可以灵活选择可用性t,提高了系统的鲁棒性与灵活性.

基于LLE和LS_SVM的胃粘膜肿瘤细胞图像分类

胃粘膜肿瘤细胞图像的复杂性,组织器官形状的不规则性以及不同细胞的差异性,使得采用一般的线性分类方法对其进行分类很困难,结合局部线性嵌入(LLE)在处理非线性数据及最小二乘支持向量机(LS_SVM)在处理小样本、高维数及泛化问题方面的优势,文章提出一种基于LLE+LS_SVM的胃粘膜肿瘤细胞图像分类方法,并采用LS_SVM的线性拟合误差来判断实验效果,最后比较本文方法与其他分类方法的优越性。实验结果表明,该方法在分类准确率和运行时间方面都有很大的优势。