实时专家智能控制系统与外部控制过程的数据通信

本文介绍一个实时专家智能控制系统EICS.文中着重简述了专家系统与控制过程的数据通信方法、程序接口.     

Datacryptor~64E剖析

Datacryptor 64E是数据包端一端保密机,用于保护经公用和专用X.25包交换网传输的敏感而有价值的信息。在传输之前先将数据加密,加密后的数据经网络传输,在其终点予以解密。 Datacryptor 64E仅对包的数据字段加密,地址和控制信息仍为明文,以保证数据包正确地通过网的路由传输。既然本设备用于端一端加密,这就意味着它仅安装在网络的终点处,而不是安装在每个网络的链路上。     

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.     

数据融合在C^3I系统中的应用

多传感器数据融合技术已在军事领域受到广泛重视，并逐步走向实际应用，本文简要介绍它的一般组成、特点以及在军事Ｃ＾３Ｉ系统应用中的主要功效。     

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     

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.     

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.     

Evaluation of Commodity Trading Advisors using fixed and variable and benchmark models

This paper examines the performance of Commodity Trading Advisors (CTAs) using fixed and variable benchmarking models. In order to avoid the troublesome passive and active commodity and managed futures benchmarks (indices) when examining the performance of CTAs, we innovate by using data envelopment analysis (DEA). Because this alternative class has non-linear returns due to long/short positions, and derivatives (i.e., dynamic trading strategies), DEA can alleviate the problems usually associated with these indices. The effectiveness of using benchmarking models in a DEA setting will provide investors with an alternative technique in assessing the performance and identifying efficient CTAs.     

The Center Problem for a Linear Center Perturbed by Homogeneous Polynomials

The centers of the polynomial differential systems with homogeneous polynomials have been studied for the degrees s = 2, 3, 4, 5. for s = 2, 3, and partially classified for s = 4, 5. In this paper we recall and we give new centers for s = 6, 7 a linear center perturbed by They are completely classified these results for s = 2, 3, 4, 5,