一种基于Ohta-Okamoto签名的门限群签名方案

在修改的Ohta_Okamoto数字签名方案基础上,设计出了一个新的(t,n)门限签名方案。该方案具有可验证性和防止内部成员合谋攻击;而且验证者在验证群签名的有效性计算的复杂性与一般个人签名方案一样。该方案的安全性是基于大整数的因式分解,因此在计算上是安全的。     

Influence of Structural Non-Stationarity of Surface Roughness on Morphological Characterization and Mechanical Deformation of Rock Joints

Summary Structural non-stationarity of surface roughness affects accurate morphological characterization as well as mechanical behaviour of rock joints at the laboratory scale using samples with a size below the stationarity threshold. In this paper, the effect of structural non-stationarity of surface roughness is investigated by studying the scale dependence of surface roughness and mechanical behaviour of rock joints. The results show that the structural non-stationarity mainly affects the accurate characterization of the surface roughness of the fracture samples. It also controls the amount and location of the contact areas during shear tests, which in turn affects the mechanical properties and asperity degradation of the samples. It is concluded that for accurate determination of the morphological and mechanical properties of rock joints at laboratory and field scales, samples with size equal to or larger than the stationarity threshold are required. Author’s address: Nader Fardin, Rock Mechanics Group, Department of Mining Engineering, Faculty of Engineering, University of Tehran, P.O. Box: 11365/4563, Tehran, Iran     

基于EMD与神经网络的机械故障诊断技术

经验模式分解 (EMD)是分析非线性、非平稳信号的有力工具 ,它将信号分解为突出了原信号的不同时间尺度的局部特征信息的内在模函数 (IMF)分量。本文通过将各 IMF分量输入到 BP网络中进行训练学习和故障诊断 ,比直接输入原信号可以提高 BP网络对故障诊断的准确率 ,而且减少了训练时间。     

经验模式分解对恒电量瞬态响应信号的预处理

应用经验模式分解（EMD）将恒电量瞬态响应信号分解为不同时间尺度的内在模函数（IMF）分量。去除其中的小时间尺度的干扰噪声分量。然后经过拉普拉斯变换获得恒电量频谱以研究电化学腐蚀过程。     

Effect of Multipoint Heterogeneity on Nonlinear Transformations for Geological Modeling： Porosity-Permeability Relations Revisited

An analysis of statistical expected values for transformations is performed in this study to quantify the effect of heterogeneity on spatial geological modeling and evaluations. Algebraic transformations are frequently applied to data from logging to allow for the modeling of geological properties. Transformations may be powers, products, and exponential operations which are commonly used in well-known relations (e.g., porosity-permeability transforms). The results of this study show that correct computations must account for residual transformation terms which arise due to lack of independence among heterogeneous geological properties. In the case of an exponential porosity-permeability transform, the values may be positive. This proves that a simple exponential model back-transformed from linear regression underestimates permeability. In the case of transformations involving two or more properties, residual terms may represent the contribution of heterogeneous components which occur when properties vary together, regardless of a pair-wise linear independence. A consequence of power- and product-transform models is that regression equationswithin those transformations need corrections via residual cumulants. A generalization of this result isthat transformations of multivariate spatial attributes require multiple-point random variable relations. This analysis provides practical solutions leading to a methodology for nonlinear modeling using correct back transformations in geology.     

改进的自适应遗传算法在遥感图像分割中的应用

为了自动确定遥感图像分割的最佳阈值,本文提出了一种改进的自适应遗传算法,并利用该算法对二维Otsu图像阈值分割函数进行了全局优化,提高了分割闻值的求解速度。该算法能够根据个体适应度大小和群体的分散程度自动调整遗传控制参数,从而能够在保持群体多样性的同时加快收敛速度,克服基本遗传算法的收敛性差、易早熟问题。实验结果表明,该算法具有良好的收敛速度和稳定性,达到较好的图像分割效果,大大缩短了计算时间。     

干旱区植被生态需水理论研究进展

综述了植被生态需水的概念及其内涵,评价了植被生态需水的主要研究理论——生态适宜性理论、系统阈值理论、水文循环水量平衡理论、农业气象学理论,评析了各种理论在实践应用中的优缺点。指出在未来的植被生态需水研究中应加强生态体系健康标准建立、定量评价指标体系的数值模拟模型构建,研究中还必须注重植被生态需水的时空特性,充分利用“3S”技术手段和先进的科学试验设备,全方位、多角度获取不同研究区域的基础信息,为建立植被生态需水理论提供可靠的数据支撑。     

小波变换阈值去噪法在GPS数据处理中的应用

在介绍小波变换阈值去噪法的特性及其有点的基础上,结合武汉某大学教学楼GPS变形监测数据,首先使用不同的小波函数及阈值策略分别对GPS观测数据的非差、单差相位观测值和伪距观测值进行阈值去噪处理,然后分别使用Bernese高精度数据处理和Trimble TG0软件对消噪前后的单差相位观测值、非差相位观测值和伪距观测值进行基线解算。最后,比较消噪前后基线解算结果,分析不同小波函数和阂值策略对基线解算精度的影响,探讨小波变换阅值去噪的合理方法。     

经验模式分解的尺度阈值滤波在变形分析中的应用

本文将信号处理领域的经验模式分解算法应用于变形信息的提取中,通过引入阈值函数,建立了基于经验模式分解的尺度阈值滤波模型,采用优化模型确定了经验模式分解的次数。分别通过模拟试验和实测数据与小波阈值法和多项式拟合法进行了比对,分析表明:在低噪声情况下,三种方法都有一定的滤波效果;在高噪声情况下,经验模式分解的尺度阈值滤波法具有与小波阈值去噪法相等的精度,而且瞬时强噪声识别能力更好,优于多项式拟合法。