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     

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。     

基于时刻独立脉冲耦合神经网络的高空间分辨率摇感影像分割

高空间分辨率遥感影像中地物目标内部光谱信息复杂性的增强,使得传统基于光谱特征值的数据处理方法效果不再显著,影像分割为解决这一问题提供了一种思路,成为当前高空间分辨率遥感影像处理的研究焦点.时刻独立脉冲耦合神经网络具有状态相近、空间相邻神经元相互耦合同步脉冲激发和区域之间神经元脉冲激发时刻独立两大特点,已被应用于非遥感影像分割中,并取得较好效果.本文结合高空间分辨率遥感影像特点,通过对网络参数进行实验和分析,提出一个基于时刻独立脉冲耦合神经网络的高空间分辨率遥感影像分割方法,并利用空间分辨率0.3m的航空影像进行了数据试验,将分割结果进行讨论并与现有时刻独立脉冲耦合神经网络方法和ISODATA方法分割结果进行对比分析.结果表明:时刻独立脉冲耦合神经网络在高空间分辨率遥感影像分割处理中具有很好的应用前景.     

基于空间信息技术的堰塞湖库容分析方法研究

快速准确计算堰塞湖库容,对了解地震堰塞湖险情具有重要的意义.利用遥感和地理信息系统等空间信息技术,提出了一种基于像素的三维水面的计算动库容的方法,能准确计算水面为曲面,包括动库容在内的总库容.该方法利用遥感影像提取水体边界线,与DEM求交后可得到带高程的边界点,利用空间插值技术获得三维水面,然后利用库容计算模型求解.同时,在分析该算法计算效率的基础上,提出了基于河流分段的库容计算优化算法,最后通过实验对比分析了该方法的合理性和优越性.     

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。     

Dynamics of the mid-ocean ridge plate boundary: Recent observations and theory

The global mid-ocean ridge system is one of the most active plate boundaries on the earth and understanding the dynamic processes at this plate boundary is one of the most important problems in geodynamics. In this paper I present recent results of several aspects of mid-ocean ridge studies concerning the dynamics of oceanic lithosphere at these diverging plate boundaries. I show that the observed rift valley to no-rift valley transition (globally due to the increase of spreading rate or locally due to the crustal thickness variations and/or thermal anomalies) can be explained by the strong temperature dependence of the power law rheology of the oceanic lithosphere, and most importantly, by the difference in the rheological behavior of the oceanic crust from the underlying mantle. The effect of this weaker lower crust on ridge dynamics is mainly influenced by spreading rate and crustal thickness variations. The accumulated strain pattern from a recently developed lens model, based on recent seismic observations, was proposed as an appealing mechanism for the observed gabbro layering sequence in the Oman Ophiolite. It is now known that the mid-ocean ridges at all spreading rates are offset into individual spreading segments by both transform and nontransform discontinuities. The tectonics of ridge segmentation are also spreading-rate dependent: the slow-spreading Mid-Atlantic Ridge is characterized by distinct bulls-eye shaped gravity lows, suggesting large along-axis variations in melt production and crustal thickness, whereas the fast-spreading East-Pacific Rise is associated with much smaller along-axis variations. These spreading-rate dependent changes have been attributed to a fundamental differences in ridge segmentation mechanisms and mantle upwelling at mid-ocean ridges: the mantle upwelling may be intrinsically plume-like (3-D) beneath a slow-spreading ridge but more sheet-like (2-D) beneath a fast-spreading ridge.     

Textural segmentation of digital rock images into bedding units using texture energy and cluster labels

The texture of digital rock images, as recorded, for instance, with borehole imaging devices, is shown to reflect different bedding types. Textural segmentation of borehole images, therefore, subdivides the recorded sequence into bedding units. We show that a textural segmentation algorithm based on the concept of texture energy achieves good results when compared with synthetic as well as real data in which petroleum geologists have performed zonations on cores. Texture energy involves filtering of the original image with a set of texture sensitive masks. The filtering is done as a finite convolution over the size of the masks. On the resulting images the variance is computed over a relatively large sliding window, which, in its practical implementation, covers the full width of the image. The resulting nine one-dimensional curves are then clustered hierarchically into a user-determined number of image texture or lithological bedding classes. Principal component analysis previous to clustering can be used to reduce redundancy in the data. A recurring and relatively ill-defined problem in this field are macro-textures, i.e., the cyclic interbedding of two or more bedding types. We show that sliding Fourier transforms and variable mask scale can successfully address the zonation of macro-textures. In general, the method gives best results with mask sizes equivalent to 2–4 centimeters, reflecting the length scale at which the investigated geological bedding seems to have its highest variation.