The prediction of coal properties using compressed infrared data from osculating polynomials

Reduction of the representation of infrared spectra from coal samples by osculating polynomials of degree nine is discussed. The reduced representation contains polynomial coefficients of order zero to four. Mathematical models of the original spectra are obtained by linear combination of the coefficients. These compressed models are statistically correlated to coal properties, namely, volatile matter, fixed carbon, ash content, heating value, hydrogen, carbon, sulphur, nitrogen, and maximum vitrinite reflectance, and the results are compared with those previously obtained from second derivatives of the same spectra. The use of compressed data, while giving slightly better correlations for some of the properties, has the advantage of requiring less computational time.     

耗散准模腔场与激子相互作用的量子统计性质

研究了耗散准模腔场与激子相互作用的量子统计特性 ,给出了当腔场初始处于真空态而激子处于真空态与粒子数态大于 2的叠加态时的腔场与激子能量交换的表达式。研究结果表明 ,激子和腔场可以呈现亚泊松分布状态 ,激子与腔场之间的关联是经典的 ,不存在Cauchy Schwartz不等式的偏离现象。     

热声驱动系统中的压力测量

介绍了自制的用于热声驱动脉管制冷装置的计算机压力波数据采集系统。该系统由硅压电压力传感器、数据采集卡、PC机和基于 Labview软件的图形化用户界面 GUI( Graphical User In-terface)组成。试验证明 ,它具有结构简单、高效精确、操作简便等特点 ,在捕捉被测系统内的动态压力变化方面具有优势 ,不但能很好地满足热声驱动器的压力测量要求 ,而且亦可移植到任何类似的测量气体压力的场合     

多目标跟踪数据互联的动态规划法

本文提出了在密集环境下多目标跟踪数据互联的动态规划法。为在噪声背景下进行实时多目标数据处理提供了理论依据和新途径．     

苯对N,N-二甲基甲酰胺化合物~1H NMR的影响研究

本文研究了N,N-二甲基甲酰胺(DMF)在四氯化碳和苯混合溶剂中的~1H NMR。观察到N,N-二甲基甲酰胺(DMF)分子中两个甲基和混合溶剂中苯的共振吸收峰的化学位移随苯的摩尔分数增加而逐渐移向高场,而且两个甲基共振吸收峰向高场移动的程度不同,α甲基较β甲基为甚。DMF分子中两个甲基和混合溶剂中苯的化学位移可以用线性方程表示(δ=A+Bx),这里x是混合溶剂中苯的摩尔分数。相关系数R接近于-1。     

Improved customer choice predictions using ensemble methods

In this paper various ensemble learning methods from machine learning and statistics are considered and applied to the customer choice modeling problem. The application of ensemble learning usually improves the prediction quality of flexible models like decision trees and thus leads to improved predictions. We give experimental results for two real-life marketing datasets using decision trees, ensemble versions of decision trees and the logistic regression model, which is a standard approach for this problem. The ensemble models are found to improve upon individual decision trees and outperform logistic regression.     

Bivariate Free Knot Splines

We consider the least squares approximation of gridded 2D data by tensor product splines with free knots. The smoothing functional to be minimized—a generalization of the univariate Schoenberg functional—is chosen in such a way that the solution of the bivariate problem separates into the solution of a sequence of univariate problems in case of fixed knots. The resulting optimization problem is a constrained separable least squares problem with tensor product structure. Based on some ideas developed by the authors for the univariate case, an efficient method for solving the specially structured 2D problem is proposed, analyzed and tested on hand of some examples from the literature.     

Exchange环的K0群的正向凸子群格

本文证明了：(1)Exchange环R的K0群的正向凸子群格同构于R的稳定余有限半本原理想格；(2)稳定有限、半本原的exchange环R是单的当且仅当它是K0-单的并且满足逼近弱s^*—可比性，推广了Goodearl，Ara等人的结果。     

逆序数的应用

本文通过“1 4-1 5”智力玩具和最优戴断切割问题两个实例 ,讨论了逆序数在解决实际问题中的应用     

Clustering Effect on the Statistical Estimation Accuracy of Distribution Density

The paper is devoted to statistical nonparametric estimation of multivariate distribution density. The influence of data pre-clustering on the estimation accuracy of multimodal density is analyzed by means of the Monte Carlo method. It is shown that the soft clustering is more advantageous than the hard one. While a moderate increase in the number of clusters also increases the calculation time, it considerably reduces the estimation error.