DETECTING AND ADJUSTING FOR NON-LINEARITIES IN CALIBRATION OF NEAR-INFRARED DATA USING PRINCIPAL COMPONENTS

A new regression method for non-linear near-infrared spectroscopic data is proposed.The technique isbased on a model which is linear in the principal components and simple functions(squares and products)of them.Added variable plots are used to determine which squares and products to incorporate into themodel.The regression coefficients are estimated by a Stein estimate which shrinks towards the estimatedetermined by the first several principal components and the selected non-linear terms.The technique isnot computationally intensive and is appropriate for routine predictions of chemical concentrations.Themethod is tested on three data sets and in all cases gives more accurate predictions than does linearprincipal components regression.     

ASSESSMENT OF THE EFFECTIVE RANK OF A (CO)VARIANCE MATRIX: A NON-PARAMETRIC GOODNESS-OF-FIT TEST

Each eigenvector of the dispersion matrix[X]~T[X]was shown to be a partial predictor of the originaldata matrix [X],the sum of the predictions from the individual principal components being equal to theexpectance of [X].By comparing the distributions of the members of two neighbouring predictedmatrices,[X]_(1...i)and [X](1...i+1)(i.e.the sums of the first i and i+1 individual predictions respectively),it was shown that they should be indistinguishable provided that i is equal to or greater than the effectiverank of [X],and significantly different otherwise.This was confirmed by analysing the visible absorptionspectra of methyl orange and methyl red solutions as well as the Raman spectra of Na_2SO_4 and MgSO_4solutions.On the grounds of these findings,a non-parametric goodness-of-fit test for assessing theeffective rank of[X]was proposed which proved to be comparatively conservative and more robust thanmost currently used tests.     

北京冬小麦产量预报的一种建模方案

针对农业产量气象预测的各类统计模式中所存在的某些不足，如趋势产量外推的稳定性，预报因子的物理及生物学意义、相关阶段性、多元共线性，回归系数稳定性和剩余产量的处理等，提出了不同的解决办法。在北京冬小麦产量预报试验中收到较好的效果。     

青藏高原南部第四纪花粉植物群及古气候

本文选择了青藏高原南部具有代表性的６个花粉剖面，应用主成分分析处理这些剖面的花粉数据，重建了这些地区的古植被和古气候。研究表明，在青藏高原南部，早、中更新世的植被类型主要是松林、云杉林、铁杉林、桦林、桤木林和栎林，晚更新世和全新世的植被类型主要是高山灌丛草原、小半灌木草原、杂类草草甸、亚高山灌丛和落叶阔叶灌丛；在早、中更新世气候条件良好，有森林生长，晚更新世以后气候明显恶化，基本无森林生长。     

A molecular stratigraphic approach to palaeoenvironmental assessment and the recognition of changes in source inputs in marls of the Mulhouse Basin (Alsace, France)

Principal components analysis (PCA) has been used to investigate changes in concentrations of the components of the hydrocarbon fractions extracted from 71 marl samples, selected to cover two total organic carbon (TOC) maxima in the lower part of the Salt IV formation, a Lower Oligocene evaporitic sequence from the Mulhouse Basin, France. The analysis indicates that the fractions can be ascribed as lying between two end member distributions. The changes in these distributions are gradual, suggesting that they resulted from fairly gradual changes in the depositional palaeoenvironment. These changes are related to increased algal productivity associated with the evolution of a restricted lacustrine environment through to one with a greater marine influence. Systematic variations in the concentrations of selected components relative to the TOC profile point to a repeated sequential evolution in the biological assemblage during deposition of the sequence.     

NOC model of the earth's main magnetic field

The international geomagnetic reference field (IGRF) is a standard model for describing the spatial structure and temporal variation of the earth抯 main magnetic field[1—3]. The first IGRF model, designated IGRF 1965, was adopted by IAGA in 1968[4]. In l…     

SPOT5影像纹理特征提取与土地利用信息识别方法

本文以太湖流域西苕溪上游安吉地区SPOT5影像600像元×600像元为试验区,首先采用主成分分析对SPOT5影像进行数据压缩和几何信息增强,再采用小波分析方法对影像进行滤波和噪音处理,利用灰度共生矩阵对高分辨率图像的纹理信息进行分析,以对比度和熵为统计指标,确定对比度和熵的最佳阈值,进行边界匹配和图像的分割,将此分割结果与NDVI阈值法分类结果进行叠合,得到最终的分类结果。试验结果表明:将纹理分析方法应用于图像分类中可区分光谱混淆的地物,光谱与纹理特征结合得到的分类精度高于单纯依靠光谱特征进行分类和单纯依靠纹理分类的分类精度。     

嵌入式导航终端互补分级路网拓扑模型的研究及实现

路径分析是嵌入式导航终端的基本功能。在层次空间数据模型的基础上,本文提出了互补分级数据模型,将整个路网拓扑分为概括拓扑和辅助拓扑两级,并给出两级路网拓扑数据快速合并机制形成详细路网拓扑,使得嵌入式硬件平台上远距离路径分析效率更高。     

Geochemical significance of hydrocarbons desorbed from asphaltenes

Saturate hydrocarbon fractions desorbed (cleaned) from asphaltenes extracted and separated from two core samples (a tar sand and a reservoir sandstone sample) were analyzed by gas chromatography-mass spectrometry (GC-MS). The results indicated thatn-alkanes adsorbed in asphaltenes were kept quite well during and after severe biodegradation over 360 Ma. Hydrocarbon desorption could be an alternative method of, or even better than the pyrolysis of asphaltenes to reconstruct the hydrocarbon fingerprints of primary oils and extend the understanding of the origins of hydrocarbon reservoirs. Project supported by the Chinese Academy of Sciences, State Key Laboratory of Organic Geochemistry and Research Center of Tarim Petroleum Exploration and Development.