成像光谱技术中机上实时数据压缩方法研究

根据成像光谱仪的特点用一系列串行的一维压缩实现二维图像压缩.提出了在机上对原始数据从光谱方向进行实时压缩的“二真值线性预测方法”.该法可做到压缩/复原后光谱特征信息不丢失.实验表明,对大多数光谱数据在1%的重建精度下,至少可获得2:1的压缩比.从总体而言,压缩后原始数据率可降低3～4倍.文中还对压缩数据的编码和误差进行了讨论.     

Likelihood estimation of soft-core interaction potentials for Gibbsian point patterns

The likelihood method is developed for the analysis of socalled regular point patterns. Approximating the normalizing factor of Gibbs canonical distribution, we simultaneously estimate two parameters, one for the scale and the other which measures the softness (or hardness), of repulsive interactions between points. The approximations are useful up to a considerably high density. Some real data are analyzed to illustrate the utility of the parameters for characterizing the regular point pattern.     

FTS-20E富里叶红外光谱仪数据系统改造

报道了ＦＴＳ－２０Ｆ富里叶红外光谱仪数据系统改造的工作采用ＩＢＭ４８６计算机及新的数据接口取代了陈旧的ＮＯＶＡ４数据系统，文章详细描述了其硬件设计和软件编辑，改造不仅更新了ＦＴＳ－２０Ｅ里叶红外光谱仪，而且还使其达到９０年代的水平。     

Chemical Reactions in the Manufacture of Waveguides for Long Distance Optical Data Transmission

One of the modern high technologies which has advanced enormously in the last few years is glass fiber technology. This is used in the manufacture of glass fibers for lighting purposes and for the optical transfer of analog and digital data with a high transfer density. The technical demands made on the glass fibers required for data transfer, the optical waveguides, are extremely high and are already fulfilled to a large extent by industry. At present about four million kilometers of fiber, worth ca. 800 million DM are produced worldwide (10% in the Federal Republic of Germany). Numerous chemical processes take place during the manufacture of optical waveguides. However, in contrast both to the high and constantly growing demands on the quality and to the increasing production volume of such fibers, little is in fact known about the reactions involved. The present article will attempt to develop a picture of the multifarious reactions occurring in the course of this technical process on the basis of literature data and our own studies.     

人工神经网络及其在分析化学中的应用

人工神经网络是一种新兴的计算方法，有着广阔的发展前途，目前在分析化学领域已经有了多方面的应用。本文简要介绍了人工神经网络的原理及其在分析化学中的应用。     

Modeling Studies of the Formation and Destruction of NO in Pulsed Barrier Discharges in Nitrogen and Air

This paper presents the results of modeling studies on the formation and destruction of NO in pulsed barrier discharges in nitrogen and air. The goals of this work are to identify the major processes involved in the formation and destruction of NO in air discharges, to distinguish between oxidative and reductive paths for NO destruction, to explore the potential importance of excited state reactions, to evaluate the role of water in such systems, and to identify the final products in the absence of heterogeneous processes. In all cases, the systems were modeled with 100×10^–4% (100 ppm) of added NO, with and without 3% added water. The focus in all of this work is chemistry in the post-pulse regime.     

气相色谱质谱联用仪与微机的数据传输和处理

报道了一种用于气相色谱质谱联用仪和微机之间实现数据传输和处理的方法。方法可更有效地利用质谱仪采集的数据，解决了工作站处理数据的局限性。经数据格式转换，原始数据可以在微机上实现色谱峰再现，从而为色谱条件的优化和定量数据处理创造了条件。     

微机控制离子色谱仪自动操作与数据处理系统

用转换器和ＩＢＭＰＣ／ＸＴ微机与Ｄｉｏｎｅｘ２０２０ｉ型离子色谱仪连接组成自动控制与数据处理系统，转换器由８０３１及８２５５等芯片组成，其功能是采集数据和转送数据，软件由汇编及Ｃ语言编制。这套新系统增加了注入／记录同步，分级梯度淋洗，自动连续进样等功能以及很强的数据处理能力。     

Quality evaluation of fingerprints of herbal medicine with chromatographic data

In this study, local least squares (LLS) and principal component analysis (PCA) were applied to deal with the disturbances in a data set of chromatographic fingerprints after necessary data transformations. It has been demonstrated that PCA with standard normal variate (SNV) transformation of data led to meaningful classification of 33 different Erigeron breviscapus herbal samples. The result was also corroborated by variance squares discriminant method. The quality of herbal objects was further evaluated, and the causes of this fact have been explained from a chemical point of view. At the same time, it implied an idea for qualitative evaluation of the herbal objects with a common class pattern of chromatographic fingerprints.     

A Method for Clustering and Screening of Long-dimensional Chemical Data Based on Fingerprints and Similarity Measurements

A method for the treatment of long-dimensional chemical data arrays is presented in this work with the aim of maximising classification models. The method is based on the construction of fingerprints and the subsequent generation of a similarity matrix. The similarity calculation has been modified through a scaling process to take into account different significance shown by the variables. The method was applied to spectral measurements of wines and several aspects were studied, namely: threshold considered in the construction of fingerprints and patterns, weighting factor used for scaling, normalisation method, etc. The application of both Principal Components Analysis and Soft-Independent Modelling of Class Analogies to the similarity matrices gave better classifications of the information than those obtained using original data.