时空数据库变体最近邻查询问题探讨

最近邻查询在地理信息系统、智能交通系统、多媒体应用以及数据挖掘等领域有着广泛的应用,随着对最近邻查询问题研究的深入,其应用前景和发展空间将更为广阔。针对近几年时空数据库中提出的最近邻查询的多种变体查询问题进行了详细地介绍和分析,总结了解决这些变体最近邻查询问题的有效方法,最后对最近邻查询问题的发展方向进行了展望。     

均衡收益和风险的Web服务Skyline查询

为解决基于服务质量(QoS)的web服务选择中只考虑QoS的收益(均值),不考虑风险(即动态变化)的Skyline查询问题,提出均值标准差描述QoS(均值描述QoS的收益,标准差描述QoS的风险)的服务Skyline计算方法和4种服务Skyline查询算法,即基于均值标准差的BNL算法(BNL_MS)、基于均值标准差的D&C算法(DC_MS)、基于均值标准差的NN算法(NN_MS)、基于均值标准差的BBS算法(BBS_MS).该方法能剔除被支配服务,给出QoS属性全优且稳定的服务集,有效缩减备选服务集.实例和实验结果表明:1)均值标准差较均值、区间数、模糊数、随机数不仅能很好地刻画QoS的收益还能刻画风险;2)服务Skyline计算能有效计算服务最优集;3)BBS_MS算法较BNL_MS、D&C_MS和NN_MS算法具有更好的性能.     

Path Integration on a Quantum Computer

We study path integration on a quantum computer that performs quantum summation. We assume that the measure of path integration is Gaussian, with the eigenvalues of its covariance operator of order j^-k with k>1. For the Wiener measure occurring in many applications we have k=2. We want to compute an -approximation to path integrals whose integrands are at least Lipschitz. We prove: Path integration on a quantum computer is tractable. Path integration on a quantum computer can be solved roughly ^-1 times faster than on a classical computer using randomization, and exponentially faster than on a classical computer with a worst case assurance. The number of quantum queries needed to solve path integration is roughly the square root of the number of function values needed on a classical computer using randomization. More precisely, the number of quantum queries is at most 4.46 ^-1. Furthermore, a lower bound is obtained for the minimal number of quantum queries which shows that this bound cannot be significantly improved. The number of qubits is polynomial in ^-1. Furthermore, for the Wiener measure the degree is 2 for Lipschitz functions, and the degree is 1 for smoother integrands. PACS: 03.67.Lx; 31.15Kb; 31.15.-p; 02.70.-c     

An Efficient PAB‐Based Query Indexing for Processing Continuous Queries on Moving Objects

Existing methods to process continuous range queries are not scalable. In particular, as the number of continuous range queries on a large number of moving objects becomes larger, their performance degrades significantly. We propose a novel query indexing method called the projected attribute bit (PAB)‐based query index. We project a two‐dimensional continuous range query on each axis to get two one‐dimensional bit lists. Since the queries are transformed to bit lists and query evaluation is performed by bit operations, the storage cost of indexing and query evaluation time are reduced significantly. Through various experiments, we show that our method outperforms the containment‐encoded squares‐based indexing method, which is one of the most recently proposed methods.     

Evaluation of aluminium/alumina/titanium composites produced by continual annealing and roll-bonding process

Anodising, continual annealing and roll-bonding (CAR) processes were employed to fabricate aluminium/alumina/titanium composites with different amounts of alumina. After each rolling cycle, annealing treatment was performed at 300°C for 1?h. After six cycles of CAR process, the Al/0.22 vol.-% Al₂O₃/13vol.-%Ti composite showed uniform alumina and titanium particles distribution. The tensile strength of the composites first decreased after the first cycle, then increased up to 200?MPa after the sixth cycle. Conversely, by increasing the alumina content (Al/0.43vol.-%Al₂O₃/13vol.-%Ti composite), microhardness and tensile strength immediately increased. SEM micrographs demonstrated that by increasing the number of cycles, the dimples density increased from 0.007 to 0.028?µm^?2 for the first and the last cycles, respectively.     

Approximate all nearest neighbor search for high dimensional entropy estimation for image registration

Information theoretic criteria such as mutual information are often used as similarity measures for inter-modality image registration. For better performance, it is useful to consider vector-valued pixel features. However, this leads to the task of estimating entropy in medium to high dimensional spaces, for which standard histogram entropy estimator is not usable. We have therefore previously proposed to use a nearest neighbor-based Kozachenko-Leonenko (KL) entropy estimator.Here we address the issue of determining a suitable all nearest neighbor (NN) search algorithm for this relatively specific task.We evaluate several well-known state-of-the-art standard algorithms based on k-d trees (FLANN), balanced box decomposition (BBD) trees (ANN), and locality sensitive hashing (LSH), using publicly available implementations. In addition, we present our own method, which is based on k-d trees with several enhancements and is tailored for this particular application.We conclude that all tree-based methods perform acceptably well, with our method being the fastest and most suitable for the all-NN search task needed by the KL estimator on image data, while the ANN and especially FLANN methods being most often the fastest on other types of data. On the other hand, LSH is found the least suitable, with the brute force search being the slowest.     

A systolic VLSI matrix for a family of fundamental searching problems

A simple and general VLSI-architecture, designed to solve a family of basic searching problems, is presented. The actual chip (the H-matrix) may generally be set up to trap requested objects or to detect specific properties in high-rate bit-serial datastreams flowing through the chip.The most important problem for which the design is applicable corresponds to the database operation known as General Range Queries which includes standard String Pattern Matching. The problem of reporting intersecting pairs in large sets of rectilinear rectangles, a crucial step in checking the design rules for VLSI circuitry, is also a member in the family of problems that can be handled.Other possible applications of the design, such as real-time collection of statistics and distribution sorting, are discussed. A hierarchical implementation of the critical cells, described by familiar high-level language notations, is presented.The actual design has been successfully implemented in NMOS.     

连续服务请求下基于假位置的用户隐私增强方法

基于假位置的隐私保护方案在为用户提供准确位置服务查询结果的同时,还无需第三方和共享密钥。然而,当用户连续请求位置服务时,由于现有保护单次查询的假位置方案未考虑相邻位置集合间的时空关系,使攻击者能推断出假位置,降低用户的位置隐私保护等级。针对上述问题,采用现有假位置方案生成候选假位置,并通过连续合理性检查和单次隐私增强对其进行筛选,提出一个适用于连续请求的假位置隐私保护增强方法。安全性分析表明,所提方法能保证连续请求中形成的移动路径在时空上不可区分,有效保护连续请求中的用户位置隐私。大量实验表明,所提方法在不增加用户计算开销的同时,与采用的候选假位置生成方案相比,还能提高用户单次查询的隐私保护等级。     

云计算环境下支持多属性查找的混合对等网络

针对云计算环境下,云资源的多属性查找问题,设计了一种混合结构的对等网络。该网络采用多星形拓扑结构,将云资源以统一的编码方式规范化之后部署到该网络上,可较好地实现多属性查找。文中描述了多属性查找算法,分析了网络性能,该网络旨在降低资源查找的跳数,因此文中主要分析网络查找跳数。实验表明,资源查找跳数得到优化,达到了预期效果。