基于离散ID序列的RFID标签认证协议

针对RFID的安全问题,提出一种基于离散ID序列的RFID标签认证协议——DSTAP,在此基础上,将DSTAP协议与其他认证协议进行比较分析,桑用BAN逻辑对所提出的协议进行形式化分析。分析结果表明,DSTAP协议达到指定的安全设计要求,同时可减少计算量。     

Expedited simulation‐driven design optimization of UWB antennas by means of response features

In this work, a method for fast design optimization of broadband antennas is considered. The approach is based on a feature‐based optimization (FBO) concept where reflection characteristics of the structure at hand are formulated in terms of suitably defined feature points. Redefinition of the design problem allows for reducing the design optimization cost, because the dependence of feature point coordinates on antenna dimensions is less nonlinear than for the original frequency characteristics (here, S‐parameters). This results in faster convergence of the optimization algorithm. The cost of the design process is further reduced using variable‐fidelity electromagnetic (EM) simulation models. In case of UWB antennas, the feature points are defined, among others, as the levels of the reflection characteristic at its local in‐band maxima, as well as location of the frequency point which corresponds to acceptable reflection around the lower corner frequency within the UWB band. Also, the number of characteristic points depends on antenna topology and its dimensions. Performance of FBO‐based design optimization is demonstrated using two examples of planar UWB antennas. Moreover, the computational cost of the approach is compared with conventional optimization driven by a pattern search algorithm. Experimental validation of the numerical results is also provided.     

词语序差的分布特点与文本间词汇异同

该文在已有关于“频级”“频序”研究的基础上,结合两种不同类型的语料,采用词汇计量分析方法,考察词语的“序差”所具有的分布特点。该研究发现,对于两种文本的共有词集,词的序差呈对称分布,且集中分布于中位数附近,存在离群值序差。这一特点在序差图上表现为“中段平直,双尾翘曲”的“双尾分布”形态。根据词语序差的分布规律,可以将文本共有词划分为“中段”“下尾”“上尾”三个层次。“中段”词语反映两个文本的共性特征,“下尾”及“上尾”词语反映两个文本的差异性特征,这些特征具有反映文本的主题内容和文体风格的语言学意义。     

基于词包和特征融合的目标识别算法

针对现有词包模型对目标识别性能的不足,对特征提取、图像表示等方面进行改进以提高目标识别的准确率。首先,以密集提取关键点的方式取代SIFT关键点提取,减少了计算时间并最大程度地描述了图像底层信息。然后采用尺度不变特征变换(Scale-invariant feature transform, SIFT)描述符和统一模式的局部二值模式(Local binary pattern,LBP)描述符描述关键点周围的形状特征和纹理特征,引入K-Means聚类算法分别生成视觉词典,然后将局部描述符进行近似局部约束线性编码,并进行最大值特征汇聚。分别采用空间金字塔匹配生成具有空间信息的直方图,最后将金字塔直方图相串联,形成特征的图像级融合,并送入SVM进行分类识别。在公共数据库中进行实验,实验结果表明,本文所提方法能取得较高的目标识别准确率。     

基于目标轮廓几何特征的电容元件定位方法

随着印刷电路板(PCB)生产工艺愈加复杂,电容元件的定位识别难度也随之增加。在实际生产中,为了节约成本、减少出错率,需要在焊接之前对电路板进行检测,同时为了固定电路板上元器件,一般会使用压板固定电路板。针对此种情况,提出一种复杂背景下被遮盖电容元件的定位方法,通过对采集到的PCB图像进行预处理、阈值分割、边缘提取和Harris角点检测等操作,进而根据电容元件目标轮廓的几何特征对元件进行定位。该方法已经在实践中得到应用,定位准确率高、速度快,能广泛应用于实际生产中。     

距离法求语言特征主成分

语言特征成分的数量决定了成分对语言特征的影响度.作者把影响度视作距离,建立了一个数学模型,通过距离判断来求取语言特征主成分.     

低层特征融合的图像检索算法设计

现阶段基于单一的特征提取算法已不能满足人们对图像查准率、查全率的要求。有效地整合图像的颜色、纹理、形状等特征,使得各特征优势互补,进而提高系统检索效率现已成为一个值得研究并深入的课题[1]。从颜色、纹理两方面的特征出发,研究并设计了一整套的方案,很好的解决了查准率、查全率等问题。     

Multi-class supervised classification of electrical borehole wall images using texture features

Electrical borehole wall images represent micro-resistivity measurements at the borehole wall. The lithology reconstruction is often based on visual interpretation done by geologists. This analysis is very time-consuming and subjective. Different geologists may interpret the data differently. In this work, linear discriminant analysis (LDA) in combination with texture features is used for an automated lithology reconstruction of ODP (Ocean Drilling Program) borehole 1203A drilled during Leg 197. Six rock groups are identified by their textural properties in resistivity data obtained by a Formation MircoScanner (FMS). Although discriminant analysis can be used for multi-class classification, non-optimal decision criteria for certain groups could emerge. For this reason, we use a combination of 2-class (binary) classifiers to increase the overall classification accuracy. The generalization ability of the combined classifiers is evaluated and optimized on a testing dataset where a classification rate of more than 80% for each of the six rock groups is achieved. The combined, trained classifiers are then applied on the whole dataset obtaining a statistical reconstruction of the logged formation. Compared to a single multi-class classifier the combined binary classifiers show better classification results for certain rock groups and more stable results in larger intervals of equal rock type.     

基于固定内存和状态管理的模型检测方法*

在研究固定内存和状态管理的基础上,提出了一种新的模型检测方法,使得在任何计算机上都能对任意规模的并发系统进行模型检测.     

序列模糊概念格模型及其渐进式构造

传统的序列模式挖掘主要是挖掘满足最小支持度的频繁序列,没有考虑序列在实际中的重要度。为了能够有效地挖掘重要的序列模式,提出了一种序列模糊概念格模型,对所有序列的项目引入了重要度权值,定义了序列的重要度及可以动态调整最小支持度minsup的自适应系数;扩展了模糊形式背景,使其能够方便地表示序列,定义了概念的Galois闭包连接、序列模糊概念及序列模糊格结构,并给出了序列模糊概念格的渐进式构造算法 ScqFuzCL。实验表明,序列模糊概念格模型可以方便有效地组织自适应序列模式,在时间与空间上都具有良好的性能,并为进一步挖掘自适应序列模式提供了理论支持。