An improved R-tree based on childnode＇s probability

R-Tree is a good structure for spatial searching. But in this indexing structure, either the sequence of nodes in the same level or sequence of traveling these nodes when queries are made is random. Since the possibility that the object appears in different MBR which have the same parents node is different, if we make the subnode who has the most possibility be traveled first, the time cost will be decreased in most of the cases. In some case, the possibility of a point belong to a rectangle will shows direct proportion with the size of the rectangle. But this conclusion is based on an assumption that the objects are symmetrically distributing in the area and this assumption is not always coming into existence. Now we found a more direct parameter to scale the possibility and made a little change on the structure of R-tree, to increase the possibility of founding the satisfying answer in the front sub trees. We names this structure probability based arranged R-tree (PBAR-tree).     

An improved R-tree based on childnode''''s probability

R Tree is a good structure for spatial searching. But in this indexing structure, either the sequence of nodes in the same level or sequence of traveling these nodes when queries are made is random. Since the possibility that the object appears in different MBR which have the same parents node is different, if we make the subnode who has the most possibility be traveled first, the time cost will be decreased in most of the cases. In some case, the possibility of a point belong to a rectangle will shows direct proportion with the size of the rectangle. But this conclusion is based on an assumption that the objects are symmetrically distributing in the area and this assumption is not always coming into existence. Now we found a more direct parameter to scale the possibility and made a little change on the structure of R tree, to increase the possibility of founding the satisfying answer in the front sub trees. We names this structure probability based arranged R tree (PBAR tree).     

基于空间索引的物流中心选址方法

确定合理的城市物流节点位置,对优化物流网络、提高物流服务水平、改善城市交通状况都具有十分重要的作用． 文中提出了一种实用新型的选址查询方法,在已知人口分布和已建物流中心位置的基础上,从候选位置集中返回前k个最具有影响的位置,作为待建物流中心的参考,这种查询在决策支持系统中有广泛的应用． 该算法利用R-tree为3个已知位置集进行了索引,并提出基于候选位置影响力的排序方法,以此制定了有效的剪枝规则,大大减少了搜索复杂度． 实验表明,该算法具有很好的查询效率．     

多维空间数据索引结构的并发控制方案

R树是支持多维空间数据访问的重要索引结构之一，但由于缺乏适用的并发控制机制来保证并发环境下数据的一致性，因此至今大多数商用数据库系统都不支持基于R树的并发处理。建立在R树基础上的R-link树解决了并发控制中出现的部分难题，但它仍然存在幻像等问题，因此分析R-link树中的尚存的问题，并通过设计一个基于内存的操作控制列表来预先避免可能冲突的并发操作，从而实现完全的并发控制。实验证明所提方案是正确的且有利于提高系统性能。     

一种高效的空间索引结构

为高效地处理空间数据，必须对数据库建立索引机制以快速存取数据。然而，由于空间数据的特殊性使得传统索引方法不能很好地适应空间数据的存取。介绍了一种目前较流行的索引结构－R树及其主要算法。在所研究的空间分析数据库系统SADBS中实现了R树索引。     

基于活跃度的网络免疫策略

免疫策略是抑制复杂网络传播过程的有效方法。虽然基于网络拓扑的免疫策略取得了良好的免疫效果,但这些策略都基于同构性假设,即:网络中的节点具有相同的属性。然而,越来越多的研究揭示了网络节点的异构特征,如传播过程中节点具有不同的活跃度,活跃的节点能够促进传播。笔者结合网络结构和节点活跃度,提出了一种新的免疫策略,在真实网络和人工网络中的仿真结果表明,所提免疫策略能够有效抑制传播扩散。     

基于混合聚类算法的动态R-树

针对动态R-树是通过动态插入算法建立起来的, 其节点分裂算法的性能直接影响到R-树的性能和查询效率的问题, 为了使动态R-树适应多维复杂空间数据的要求, 提出一种用于实现R-树节点分裂的混合聚类算法（HCR）, 它建立在普通聚类算法的基础上, 并进行了一系列扩充. 针对空间对象的均匀分布与不均匀分布, HCR算法在实现R-树节点分裂时分别采用不同的聚类准则以提高其聚类效果和查询效率. 此外, 还将HCR算法与其他算法进行对比实验, 结果表明该算法具有较高的查询效率.     

基于Voronoi图的最近邻查询的索引结构的研究

基于Voronoi图的最近邻查询在计算几何中已被研究了相当长一段时间。但在以往的研究中,基于Voronoi图的最近邻查询究竟是基于何种具体的索引结构去实现对查询空间的搜索的,却很少被提及。本文把传统的R树和Voronoi图在解决最近邻查询问题中的优越性相结合,提出了一种新的索引结构:VR树。进而提出了基于VR树索引结构的NN查询算法并对这该算法进行分析,在理论上证明了这个算法较基于R树索引结构的最近邻查询算法优。     

Indexing large moving objects from past to future with PCFI

In moving object database, the moving objects' current position must be kept in memory, also to the trajectory, in some case, as same as the future. But the current existing indexes such as SEB-tree, SETI-tree, 2+3R-tree, 2-3RT-tree and etc. can only provide the capability for past and current query, and the TPR-Tree, TPR*-Tree and etc.can only provide the capability for current and future query. None of them can provide a strategy for indexing the past, current and also the future information of moving objects.In this paper, we propose the past-current-future Index (PCFI-Index) to index the past,current & future information of the moving objects. It is the combination of SETI-tree and TPR*-tree, the SETI liking index is used for indexing the historical trajectory segments except the front line structure, and the moving objects' current positions, velocities are indexed via the in-memory frontline structure which mainly implemented with TPR*-tree.Considering the large update operations on TPR-tree of large population, a hash table considering cache sensitivity is also introduced. It works with the frontline part, leading a bottom-up update of the tree. The performance analysis proves that the PCFI-index can handle most of the query efficiently and provides a uniform solution for the trajectory query, time-slice query, internal query and moving query.     

矩形复数势和delta复数势的隧穿相时的研究

矩形与delta势是两种不同的势,但当矩形势的宽度趋于无穷小时,理论上就过渡为delta势,本文研究两种复数势的隧穿相时问题,以及相时大小与势的实部和虚部的关系,并推导出矩形势和delta势的关系,以及波函数的微商跃变条件。     

自适应 TD-LTE 公网集群系统竞争 Preamble 序列配置方案

集群通信系统凭借其组网简单的优势,在应急通信中得到了广泛的应用,但现有的基于TD-LTE的宽带集群通信系统所采用的随机序列的利用率和发送成功率都不高.针对此问题,在对现有TD-LTE系统的随机接入Preamble序列配置现状展开研究的基础上,结合公网集群通信系统支持资源共用但不相互干扰的性能要求,提出一种适用于公网集群通信系统的竞争Preamble序列配置方案.该方案提出在低接入负载的环境中采用共用模式,用户根据系统的分配,选择适当的Preamble序列完成接入;而在高接入负载的环境中采用分类模式,将集群用户分为4个集合,根据用户分类的不同选取不同的Preamble序列完成接入.仿真结果证明,该方案提高了Preamble序列的利用率和发送成功率,避免了混合接入碰撞,提高了网络的运行效率.     

基于网络结构及节点活动网络的PSN协议

将网络关联结构和位置匹配的思想引入到公共交换网络(PSN)的路由协议设计中, 从全局搜索和局部搜索两方面解决了消息报文的路由问题. 首先, 探索全局搜索时网络关联结构对信息传播的影响, 可知在复杂网络中最有效的传播节点应该是位于网络关联结构的最核心节点, 而不是全局社会度高的节点. 其次, 探讨局部搜索时基于位置匹配度的合理性和可行性. 最后, 提出一个基于社会结构度和节点活动网络的路由协议, 即K核. 报文开始时在全局社区进行转发, 将报文转发给处于网络中心位置的节点, 直至找到转发报文的节点位于报文目的节点的附近, 再根据该附近区域的节点位置匹配度进行转发报文. 与经典协议相比, 该方法可以保证在几乎相同的报文延迟基础上, 实现更高的投递成功率及更少的花费.     

矩形花键轴的扭转强度计算和少齿数齿轮轴的扭转实验研究

首先,基于极惯性矩的概念和平面假设理论推导出了矩形花键轴横截面的极惯性矩和最大扭转切应力公式,并验证了此计算方法的准确性.其次,采用Ansys软件对矩形花键轴的扭转切应力分布规律进行了仿真研究.最后,对少齿数齿轮进行正反转扭转实验,得出了一些重要结论.     

基于搜索效率的复杂网络多模型并行演化分析

很多真实的复杂网络呈现无标度性．但是,这些网络为什么在增长过程中遵从优先连接规则？现有研究尚未给出有力的解释．一个合理的猜想是：这些网络如果不遵从优先连接规则,则将处于不利的地位．为证实这一猜想,采用搜索效率作为评价指标,量化评价不同演化模型的优劣．首先提出一种新的复杂网络并行演化模式,使得同一网络中不同的局部遵从不同的演化模型,从而在统一的基础上比较不同演化模型搜索效率的优劣．以BA无标度网络、WS小世界网络和随机网络为基础,构建了异质复杂网络．其次,采用随机游走搜索策略和DS最大度搜索策略,比较遵从不同演化模型的异质子网的搜索效率,力图解释复杂网络中演化模式同质化的原因．实验发现一种“信息壁垒”现象,即处于劣势的网络模型,其所属节点很难被其他模型的节点访问到．实验结果表明：对于以搜索为重要功能的复杂网络,无标度网络具有最强的适应性,从而在一定程度上解释了无标度现象在众多现实复杂网络中存在的原因．     

Hierarchically Clustered HMM for Protein Sequence Motif Extraction with Variable Length

Protein sequence motifs extraction is an important field of bioinformatics since its relevance to the structural analysis. Two major problems are related to this field：（1） searching the motifs within the same protein family; and（2） assuming a window size for the motifs search. This work proposes the Hierarchically Clustered Hidden Markov Model（HC-HMM） approach, which represents the behavior and structure of proteins in terms of a Hidden Markov Model chain and hierarchically clusters each chain by minimizing distance between two given chains＇ structure and behavior. It is well known that HMM can be utilized for clustering, however, methods for clustering on Hidden Markov Models themselves are rarely studied. In this paper, we developed a hierarchical clustering based algorithm for HMMs to discover protein sequence motifs that transcend family boundaries with no assumption on the length of the motif. This paper carefully examines the effectiveness of this approach for motif extraction on 2593 proteins that share no more than 25% sequence identity. Many interesting motifs are generated.Three example motifs generated by the HC-HMM approach are analyzed and visualized with their tertiary structure.We believe the proposed method provides a unique protein sequence motif extraction strategy. The related data mining fields using Hidden Markova Model may also benefit from this clustering on HMM themselves approach.     

滤波窗口对二元误差扩散编码光栅的影响

三维传感系统中,二元误差扩散编码光栅可应用于产生质量较好的正弦结构光场.光学系统的低通滤波窗口成为影响系统测量精度的因素之一.比较了3种常见滤波函数,分析各自特点.计算机仿真实验表明,应用二元误差扩散编码光栅,采用高斯窗、汉宁窗或矩形窗作为PMP系统滤波窗口时,系统测量精度为同一量级,且窗口宽度取6倍光栅基频最佳.     

基于双树双索引结构的移动查询方法

为实现对有限范围内海量移动对象的有效索引,构建通用的移动查询解决方案,针对移动对象在道路网格中的运动特点,提出了预测实时运动速度的速度积累模型和预测未来聚集位置的基于双树双索引结构的移动对象查询方法.双树双索引结构利用网格划分思想构建空间分割树,实现对现有GG TPR-tree查询结构的拓展,并结合GG TPR-tree索引及建立于内存中的Hash索引以满足各种类型的移动查询请求.仿真实验表明,在回答受限范围内海量移动对象的确定性查询和统计性查询时,与传统方法相比,双树双索引结构在查询结果准确率方面有明显的改善.     

采用模压技术的聚合物矩形光栅制作

在适当的压力条件下,通过控制压制的温度,制作出性能优良的PC(Polycarbonate)聚合物矩形光栅,光栅压制模板为采用感应耦合等离子体(ICP)技术刻蚀的熔融石英矩形光栅模板.对聚合物光栅的衍射观察和测量,证明用模压技术制作的PC聚合物矩形光栅具有很好的衍射效率和表面质量.     

PR-tree:P2P环境下一种多维数据的分布式索引结构

提出了一种基于R-tree的更适用于P2P环境的新型多维空间索引结构———PR-tree,并且在这种新型的索引结构下进行了高维数据的查询操作.这种新型的空间索引结构有两个主要的特点:对需要查询的数据空间进行层次划分;并且对结点的插入、删除等操作具有高度的灵活性.实验表明这种新型的空间索引结构在查询效率等方面都优于其他的索引形式.     

RM-structure alignment based statistical machine translation model

A novel model based on structure alignments is proposed for statistical machine translation in this paper. Meta-structure and sequence of meta-structure for a parse tree are defined. During the translation process, a parse tree is decomposed to deal with the structure divergence and the alignments can be constructed at different levels of recombination of meta-structure （RM）. This method can perform the structure mapping across the sub-tree structure between languages. As a result, we get not only the translation for the target language, but sequence of meta-stmctu .re of its parse tree at the same time. Experiments show that the model in the framework of log-linear model has better generative ability and significantly outperforms Pharaoh, a phrase-based system.