Peer-to-peer bichromatic reverse nearest neighbours in mobile ad-hoc networks

The increasing use of mobile communications has raised many issues of decision support and resource allocation. A crucial problem is how to solve queries of Reverse Nearest Neighbour (RNN). An RNN query returns all objects that consider the query object as their nearest neighbour. Existing methods mostly rely on a centralised base station. However, mobile P2P systems offer many benefits, including self-organisation, fault-tolerance and load-balancing. In this study, we propose and evaluate 3 distinct P2P algorithms focusing on bichromatic RNN queries, in which mobile query peers and static objects of interest are of two different categories, based on a time-out mechanism and a boundary polygon around the mobile query peers. The Brute-Force Search Algorithm provides a naive approach to exploit shared information among peers whereas two other Boundary Search Algorithms filter a number of peers involved in query processing. The algorithms are evaluated in the MiXiM simulation framework with both real and synthetic datasets. The results show the practical feasibility of the P2P approach for solving bichromatic RNN queries for mobile networks.     

疲劳与蠕变复合作用下PS的应变与寿命

对PS在疲劳/蠕变复合作用下应变与寿命进行了研究。结果表明：其疲劳/蠕变曲线与纯蠕变曲线十分相似。加载时间周期越短和疲劳载荷变化越频繁。结束普弹应变阶段应变越小，进入延迟弹性变形的平台应变阶段越早。在疲劳/蠕变复合作用下聚苯乙烯存在疲劳和蠕变的交互损伤，其断裂寿命比纯疲劳或纯蠕变的断裂寿命低。断裂寿命减小，疲劳/蠕变的交互损伤程度与温度密切相关，PS在较低温度的疲劳/蠕变交互损伤作用大于较高温度的交互损伤作用。随温度升高，疲劳/蠕变断裂寿命下降是疲劳和蠕变各自的单独损伤增加所致。     

基于空间加权互信息的非刚性医学图像配准

互信息作为相似性测度标准在医学图像配准领域应用广泛,尤其是在刚性配准研究中,能实现较高配准精度和非常稳健的配准效果。然而由于非线性形变的复杂性,在非刚性配准领域,对基于互信息的配准方法进行深入研究势在必行。提出的方案采用基于B样条的自由变换模型模拟医学图像中解剖结构的非线性形变,同时根据变换模型,考虑空间信息对配准效果的影响,以空间加权的方式对互信息方法进行改进。使用对大规模参数优化效果较好的LBFGS方法对配准参数进行优化,编程实现程序,并通过实验对效果进行验证和分析。实验结果显示,该方案配准精度明显优于传统的互信息方法。     

基于DXF格式的优化数控代码自动生成方法

DXF是AutoCAD与其他软件进行数据交换的CAD通用图形文件格式。实现了一种DXF读取方式并自动生成数控加工代码。传统算法的读取结果无序,不适用于实际加工,针对这一问题根据提取结果及位置关系生成图元轮廓树,并利用最近邻插入算法对图元轮廓优化排序,得到全局优化的最短切割路径,并通过实例证实了算法的有效性,能满足实际自动编程数控系统的工作需要。     

LDE融合光谱回归分类的光照变化人脸识别

针对光照变化人脸识别问题中传统的光谱回归算法不能很好地进行特征提取而严重影响识别性能的问题,提出了局部判别嵌入优化光谱回归分类的人脸识别算法。计算出训练样本的特征向量;借助于数据的近邻和分类关系,利用局部判别嵌入算法构建分类问题所需的嵌入,同时学习每种分类的子流形所需的嵌入;利用光谱回归分类算法计算投影矩阵,并利用最近邻分类器完成人脸的识别。在两大人脸数据库扩展YaleB及CMU PIE上的实验验证了该算法的有效性,实验结果表明,相比其他光谱回归算法,该算法取得了更高的识别率、更好的工作特性,并且降低了计算复杂度。     

Persistence of nonprotein seed amino acid s-(β-carboxyethyl)-cysteine in young leaves ofCalliandra rubescens Ecological implications

The insecticidal nonprotein amino acid S-(-carboxyethyl)-cysteine (S-CEC) is the major free amino acid in the seeds of severalCalliandra spp. where it accounts for up to 2.9 % of dry weight. Lesser amounts of other related S-containing amino acids and an array of nonprotein imino acids derived from pipecolic acid are other constituents. High concentrations of imino acids, which also show insecticidal activity, are maintained in the mature leaves, but sulfur compounds are lacking. In this study the disappearance of S-CEC from the germinating seeds and young seedlings ofC. rubescens was monitored over time. After 10 weeks, S-CEC continues to be found in high concentrations in the stems and new leaves. As young leaves mature, sulfur compounds quickly decrease in concentration. Traces of S-CEC are found in new leaves of plants up to nine months after germination. Whether high concentration of S-CEC in young leaves is due to transportation from the seed or de novo synthesis is unclear. The ecological implications are discussed.     

Novel image fusion scheme based on dependency measure for robust multispectral palmprint recognition

Multispectral palmprint is considered as an effective biometric modality to accurately recognize a subject with high confidence. This paper presents a novel multispectral palmprint recognition system consisting of three functional blocks namely: (1) novel technique to extract Region of Interest (ROI) from the hand images acquired using a contact less sensor (2) novel image fusion scheme based on dependency measure (3) new scheme for feature extraction and classification. The proposed ROI extraction scheme is based on locating the valley regions between fingers irrespective of the hand pose. We then propose a novel image fusion scheme that combines information from different spectral bands using a Wavelet transform from various sub-bands. We then perform the statistical dependency analysis between these sub-bands to perform fusion either by selection or by weighted fusion. To effectively process the information from the fused image, we perform feature extraction using Log-Gabor transform whose feature dimension is reduced using Kernel Discriminant Analysis (KDA) before performing the classification by employing a Sparse Representation Classifier (SRC). Extensive experiments are carried out on a CASIA multispectral palmprint database that shows the strong superiority of our proposed fusion scheme when benchmarked with contemporary state-of-the-art image fusion schemes.     

一种基于稀疏表示的WLAN室内定位算法

随着科技进步和人民生活水平的提高,越来越多的用户对定位技术需求变得日益迫切。基于WLAN的室内定位技术研究在此背景下应运而生,但是该技术容易受非视距离以及多径影响。而位置指纹算法有效地克服了上述缺点,并得到了广泛应用。提出一种基于稀疏表示的WLAN室内定位算法,以解决位置指纹算法K近邻方法中参数选择问题、不能综合利用全局参考点信息问题,并对其进行了实验仿真。     

基于Voronoi图的连续反向最近邻查询

为解决动态环境中移动点的连续反向最近邻查询问题,将连续反向最近邻查询分为单色和双色2种情况进行研究。利用移动点Voronoi图,分别给出单色连续反向最近邻查询算法、双色连续反向最近邻查询算法以及相关定理,对算法正确性和可终止性进行证明,分析算法时间复杂性。按照移动点Voronoi图的拓扑结构是否改变分为2种情况,分析每种情况下候选所在区域的变化,在变化区域内进行Voronoi图的重构,得到对应的解决方法。在多数情况下,该算法只需生成局部移动点的Voronoi图即可找到结果,减小了连续反向最近邻查询的代价。     

无线传感器网络不确定数据PT-Top k查询处理技术

在无线传感器网络现实应用中,感知数据普遍存在不确定性。由于不确定数据引入了概率维度,使得不确定数据查询种类更加丰富,同时也给查询处理带来困难。不确定数据Top-k查询是一个典型的不确定数据查询任务。考虑到无线传感器网络查询处理技术对查询响应时间和网络通信消耗的高要求,研究了面向层次聚簇结构的无线传感器网络不确定数据Top-k查询处理技术。通过分析不确定数据特点,基于x-tuple规则元组模型,采用簇内与簇间的两阶段数据查询处理机制,提出了基于Poisson分布的分布式不确定数据PT-Top k查询处理近似算法TPQP。通过实验,从总体通信消耗、与概率阈值p相关分析、与排序数k相关分析以及数据敏感度分析等方面,说明了TPQP算法在通信消耗、查询响应时间上的优越性。