完全与截尾样本时半参数回归模型估计的强相合性

对于固定设计下的半参数回归模型：ｙ_ｉ=ｘｉβ＋ｇ（ｔｉ）＋ｅｉ,ｉ＝１,…,ｎ．其中｛ｅｉ｝为独立随机误差序列（不必同分布）,且Ｅｅｉ＝０,Ｅｅｉ２＝σ_ｉ~２＞０．对完全和截尾样本,仿文献［２］给出了β、ｇ（·）的估计量,并证明了他们的强相合性．     

无失效数据失效率的综合多层Bayes估计

文章对指数分布无失效数据的失效率,在先验分布为Ｇａｍｍａ分布时,在引进失效信息后,给出了多层Ｂａｙｅｓ估计以及综合多层Ｂａｙｅｓ估计,并给出了可靠度的综合估计。最后,结合实际问题进行了计算     

基于串行通信的高速DSP芯片 实验系统设计与实现

本文在总结国内外现有DSP仿真系统的基础上提出了一种借助单片机和串行通信实现数字信号处理程序实时运行和调试的新方法,并在此基础上介绍了在WINDOWS95平台下该DSP实验系统的设计过程。     

Calorimetric Data and Phase Equilibria Assessment in Silicate Systems Optimization of Mixing Properties of Silicate Melts

The thermodynamic data are assessed by using molecular solution model with excess Gibbs energy of mixing expressed by Redlich-Kister equation with temperature dependent parameters. The optimized data involve phase equilibria, enthalpy and entropy of formation of crystalline phases, heat capacity (C_p) data of solid and liquid pure components, enthalpy of mixing of liquid pure components, enthalpy and entropy of fusion of solid phases. Thermodynamic quantities consistent with available experimental phase equilibria and calorimetric measurements are established for solid phases and liquids in the system CaO·SiO₂ (CS)-CaO·Al₂O₃·2SiO₂ (CAS₂)-2CaO·Al₂O₃·SiO₂ (C₂AS). This revised version was published online in July 2006 with corrections to the Cover Date.     

Hybrid numerical methods in static and dynamic fracture mechanics

In this article, the concept of the hybrid numerical methods is clarified. On the basis of this concept, various hybrid numerical methods used in static and dynamic fracture mechanics are classified into five categories: (i) hybrid experimental–numerical methods, (ii) hybrid numerical–experimental methods, (iii) hybrid analytical–numerical methods, (iv) hybrid numerical–analytical methods, and (v) hybrid numerical–numerical methods. Features of each category of hybrid numerical method are presented with pertinent numerical results.     

Quantitative AES and XPS: convergence between theory and experimental databases

Experimental spectral databases have been recorded for AES and XPS using fully calibrated instruments. These instruments have been calibrated so that the spectra have the true shape and peak area intensities may be integrated to give absolute yields for AES and relative yields for XPS. Removal of all the backgrounds requires care but may be completed by using information from both databases. The resultant yields may be compared with theory. The correlations for AES are the more complex and involve the total intensities for all transitions originating in each shell. The correlations are excellent using significant changes to the traditional approach. These involve the use of the Casnati et al. ionisation cross section and the restriction of the number of electrons for use in the inelastic mean free path calculations to electrons of 14 eV or less binding energy in the s, p or d sub-shells. The average ratio of experiment to theory is 1.04 with a standard uncertainty of the mean of 4%. Results for XPS are excellent using Scofield’s ionisation cross section together with the above rules for the inelastic mean free path calculations. Improvements for certain elements are still needed for removing the inelastically scattered Auger and photoelectrons in both databases. To assist analysts in using such databases a simpler measure of Auger electron intensity is developed involving differential spectra broadened with a Gaussian function of 15–20 eV width. The peak-to-peak intensities from these broadened spectra are reasonably closely related to the peak area of the direct spectra except in a few exceptional cases. The unbroadened differential spectra show strong contributions from the spectrometer resolution and changes in the chemical state which are avoided by the spectral broadening. To simplify calculations for the analyst when studying homogeneous materials by AES and XPS, the relative sensitivity factors are re-defined to be for an average matrix instead of the pure element. This leads to a matrix-less equation for calculating compositions from the spectra.     

多媒体时代的增强IDE接口

着重论述了增强ＩＤＥ接口对多媒体信息要求的存储容量大、传输速度快、设备数量和种类多的硬软件支持．     

Parameter Analysis of Multiscale Two-Dimensional Fuzzy and Dispersion Entropy Measures Using Machine Learning Classification

Two-dimensional fuzzy entropy, dispersion entropy, and their multiscale extensions (MFuzzyEn2D and MDispEn2D, respectively) have shown promising results for image classifications. However, these results rely on the selection of key parameters that may largely influence the entropy values obtained. Yet, the optimal choice for these parameters has not been studied thoroughly. We propose a study on the impact of these parameters in image classification. For this purpose, the entropy-based algorithms are applied to a variety of images from different datasets, each containing multiple image classes. Several parameter combinations are used to obtain the entropy values. These entropy values are then applied to a range of machine learning classifiers and the algorithm parameters are analyzed based on the classification results. By using specific parameters, we show that both MFuzzyEn2D and MDispEn2D approach state-of-the-art in terms of image classification for multiple image types. They lead to an average maximum accuracy of more than 95% for all the datasets tested. Moreover, MFuzzyEn2D results in a better classification performance than that extracted by MDispEn2D as a majority. Furthermore, the choice of classifier does not have a significant impact on the classification of the extracted features by both entropy algorithms. The results open new perspectives for these entropy-based measures in textural analysis.     

Non Deterministic Classical Logic: The λμ++ ‐calculus

In this paper, we present an extension of λμ‐calculus called λμ⁺⁺‐calculus which has the following properties: subject reduction, strong normalization, unicity of the representation of data and thus confluence only on data types. This calculus allows also to program the parallel‐or.