Efficient fingerprint search based on database clustering

Fingerprint identification has been a great challenge due to its complex search of database. This paper proposes an efficient fingerprint search algorithm based on database clustering, which narrows down the search space of fine matching. Fingerprint is non-uniformly partitioned by a circular tessellation to compute a multi-scale orientation field as the main search feature. The average ridge distance is employed as an auxiliary feature. A modified K-means clustering technique is proposed to partition the orientation feature space into clusters. Based on the database clustering, a hierarchical query processing is proposed to facilitate an efficient fingerprint search, which not only greatly speeds up the search process but also improves the retrieval accuracy. The experimental results show the effectiveness and superiority of the proposed fingerprint search algorithm.     

Making smooth transitions based on a multi-dimensional transition database for joining Chinese sign-language videos

This paper proposes a new method to generate smooth transition frames for serializing Chinese sign-language video clips. Each transition frame is composed of images of arms, hands, head and torso. Of them, the hand images are computed based on 3D hand models, and images of other parts are selected from a database. Experimental results show the method provided by this paper can improve the joined video??s visual presentation.     

Incomplete information in a deductive database

The problem of handling incomplete information efficiently has been studied in the context of relational databases by various workers. However, dealing with incomplete information in a deductive database is a more difficult problem. This paper discusses the problem of interpretation of incomplete information in a deductive database and puts forward a model to assist in understanding the different interpretations and their effect on the evaluation of queries.     

Progress in database search strategies

Retrieval speed and precision ultimately determine the success of any database system. This article outlines the challenges posed by distributed and heterogeneous database systems, including those that store unstructured data, and surveys recent work. Much work remains to help users retrieve information with ease and efficiency from a heterogeneous environment in which relational, object-oriented, textual, and pictorial databases coexist. The article outlines the progress that has been made in query processing in distributed relational database systems and heterogeneous and multidatabase systems     

基于多维力传感器的手写信息采集系统设计

针对传统手写信息采集系统存在的信息获取不全面的弊端,设计了一种基于多维力传感器的手写信息采集系统,给出了系统的总体框架.系统以多维力传感器为核心,不仅实现了对手写过程静态轨迹信息的获取,同时实现了对手写多维力信息的获取.整个系统由用户接口模块、数据采集模块和数据处理模块组成,分析了各模块的设计思想和工作原理,并基于WinCE系统开发了一种手写信息采集系统.实验证明：该系统工作稳定,性能优良,实现了对手写过程中力和位置信息的全面获取.     

基于颜色特征的视频数据库检索系统

为了在视频数据库中提供有效的视频检索和浏览功能,必须建立高效的索引.由于视频数据具有层次性的结构,在镜头边界检测后,可以利用聚类方法按不同的相似性尺度对镜头关键帧进行处理,对视频数据建立索引.该系统采用颜色特征,使用Twin Comparison算法实现镜头检测和直方图平均法实现关键帧提取,对关键帧采用K均值聚类算法处理,建立视频数据库索引.实验结果表明该系统能较好地实现视频快速浏览和检索功能.     

Mining method of massive data of mobile library under information asymmetry facing large-scare database

The current method generates a large number of candidate sets when mining data in mobile libraries under asymmetric information, and the mining time and efficiency are poor. To this end, a new method for mobile library massive data mining based on improved Apriori algorithm is proposed to collect, clean and reduce massive data. Calculate the reader's interest distance by analyzing the borrowed historical data, and use the Apriori algorithm to find the association rules in the frequent itemsets of the data. In order to make up for the shortcomings of the current method, while filtering out infrequent candidate sets, the corresponding transaction set is also collaboratively filtered, which can reduce the amount of calculation and time consumption. Experimental results show that the proposed method can mine more valuable rules. The improved execution time is only 10 s, the CPU utilization exceeds 90%, and the acceleration ratio exceeds 1.81 s, which can better meet the needs of decision makers.     

基于语义网的高效信息查询方法

为了提高Web信息检索的准确率,提出一种基于语义网的高效信息查询方法。首先从本体库中提取目标资源与查询关键字之间的语义路径,通过分析语义路径所包含的属性的权重和识别能力,分别计算每个语义路径的权重;然后,根据资源与查询关键字之间的语义路径的权重、数量和特异性,分别计算每个资源与各关键字之间的语义相关性,并结合关键字的涵盖范围和识别能力综合计算每个资源与关键字集之间的语义相关性;最后,以该相关性为依据对所有资源进行排序和输出。实验结果表明,与OntoLook、tf*idf和TMSubtree三种语义网查询算法相比,基于语义网的高效信息查询方法的平均正确率分别提高了69.0、25.0和21.0个百分点;平均召回率分别提高了77.1、28.3和24.3个百分点;平均F测度值分别提高了72.4、26.4和22.4个百分点。实验结果表明:该方法不仅能够有效提升语义查询的准确率,而且对隐性信息也有很好的查询效果。     

Using a relational database for scalable XML search

XML is a flexible and powerful tool that enables information and security sharing in heterogeneous environments. Scalable technologies are needed to effectively manage the growing volumes of XML data. A wide variety of methods exist for storing and searching XML data; the two most common techniques are conventional tree-based and relational approaches. Tree-based approaches represent XML as a tree and use indexes and path join algorithms to process queries. In contrast, the relational approach utilizes the power of a mature relational database to store and search XML. This method relationally maps XML queries to SQL and reconstructs the XML from the database results. To date, the limited acceptance of the relational approach to XML processing is due to the need to redesign the relational schema each time a new XML hierarchy is defined. We, in contrast, describe a relational approach that is fixed schema eliminating the need for schema redesign at the expense of potentially longer runtimes. We show, however, that these potentially longer runtimes are still significantly shorter than those of the tree approach. We use a popular XML benchmark to compare the scalability of both approaches. We generated large collections of heterogeneous XML documents ranging in size from 500 MB to 8 GB using the XBench benchmark. The scalability of each method was measured by running XML queries that cover a wide range of XML search features on each collection. We measure the scalability of each method over different query features as the collection size increases. In addition, we examine the performance of each method as the result size and the number of predicates increase. Our results show that our relational approach provides a scalable approach to XML retrieval by leveraging existing relational database optimizations. Furthermore, we show that the relational approach typically outperforms the tree-based approach while scaling consistently over all collections studied.

基于对象代理数据库的微生物信息服务系统

提出了一种采用对象代理数据库实现微生物数据管理的新方法。该方法将微生物菌种资源数据的共性描述信息定义为基本微生物对象,其代理对象可以用来表示微生物菌种资源分类的多样性,并定义不同菌种的特性性状信息,也可以用来定义微生物资源不同类别的扩展关联信息;通过对象更新迁移可以支持数据动态分类,利用对象视图机制可以支持模式演化,跨类查询机制则实现了高效的数据检索;实现了一个基于对象代理数据库的微生物信息服务系统。实验测试表明,该方法比传统方法更有效。     

基于多维高斯贝叶斯算法在雷达故障信息诊断系统应用

为提升雷达故障信息的诊断效率,节约执行故障诊断指令所需消耗的数据成本,设计基于多维高斯贝叶斯算法的雷达故障信息诊断系统;利用完整的框架结构设计客户机/服务器模式,联合服务器与信息查询模块,实现雷达故障信息诊断系统的体系结构搭建;在此基础上,计算故障信息的松弛度数值,通过判定迭代门限的方式,实现对多维系数信号的处理,完成基于多维高斯贝叶斯算法的雷达故障信息感知;联合已嵌入的雷达故障信息,连接Access数据库,实现诊断系统的接口技术研究;综合上述所有理论依据,设计基于多维高斯贝叶斯算法的雷达故障信息诊断系统;借助Windows平台,分别连接上述系统与远程故障诊断原型系统,在雷达故障信息诊断系统的应用过程中得出,基于多维高斯贝叶斯算法雷达故障信息诊断系统的诊断效率最大值为45%,RSR指标最大值为16.7%,指令执行消耗的数据成本较低,表明所设计系统具有一定的实际应用性。     

基于多维信息特征映射模型的在线学习路径优化方法

针对目前在线学习路径优化方法存在学习路径与学习者匹配度不高的问题,首先构建在线学习路径的多维信息特征映射模型(MIFMM),该模型根据学习者与学习资源的多维信息特征建立,融合了kolb学习风格和学习资源类型信息;然后设计双映射二进制粒子群优化算法(DMBPSO),DMBPSO算法根据进化因子ef将学习路径推荐过程分为收敛和跳出局部最优两种进化状态,采用与进化状态特征相匹配的映射函数选择策略,并对惯性权重进行动态非线性调整,提高学习路径推荐性能;接着将MIFMM模型与DMBPSO算法相融合提出基于多维信息特征映射模型的在线学习路径优化方法(MIFMM-POA);最后将MIFMM-POA方法与其他4种粒子群算法为核心的学习路径优化方法相比较,从寻优精度、寻优过程与寻优时间3个角度进行分析,实验表明MIFMM-POA方法是优化学习路径的有效方法.     

The concept of mindfulness in information systems research: a multi-dimensional analysis

The concept of mindfulness has garnered increasing attention during the last decade. Initially proposed within the scope of information systems (IS) research as a means of creating a deeper knowledge foundation for decision making regarding information technology (IT) innovations, it soon became broadly applied throughout IS research. To gain a better understanding of the evolved diversity of this concept, this paper reviews and analyzes extant IS research by means of (a) the investigated IS themes, (b) the purpose of using the concept, (c) the level of application of the concept, and (d) the tendency to focus either on mindfulness, mindlessness, or both. By synthesizing research findings, we derive a high-level IS mindfulness theory. We then propose future research opportunities, such as the explanation of the relationships between different levels of mindfulness, applying mindfulness to bridge the different phases of the software development process, and the identification of guidelines for designing information systems that facilitate mindfulness. As the first review on the application of mindfulness in IS research, we contribute to the overall understanding of mindfulness and address the four abovementioned dimensions from which mindfulness emerges in order to demonstrate that mindfulness provides a meaningful platform for generating knowledge.     

数据库关键字查询技术研究

随着互联网技术与数据库技术的不断发展和相互结合,越来越多的用户需要访问在线数据库来获取各种信息,在该过程中,用户要对数据库中的数据进行查询。因此,用户就必需要掌握一定的结构化查询语言SQL,而且还要对数据库模式有一个认识和了解。但事实上,多数用户并不会使用结构化查询语言,也不了解数据库模式。所以,便产生了一个很自然的用户需求——数据库支持基于关键字的查询,文章主要就是对数据库支持基于关键字的查询进行简要的分析和探讨。     

Protein database search of hybrid alignment algorithm based on GPU parallel acceleration

In biological research, alignment of protein sequences by computer is often needed to find similarities between them. Although results can be computed in a reasonable time for alignment of two sequences, it is still very central processing unit (CPU) time-consuming when solving massive sequences alignment problems such as protein database search. In this paper, an optimized protein database search method is presented and tested with Swiss-Prot database on graphic processing unit (GPU) devices, and further, the power of CPU multi-threaded computing is also involved to realize a GPU-based heterogeneous parallelism. In our proposed method, a hybrid alignment approach is implemented by combining Smith–Waterman local alignment algorithm with Needleman–Wunsch global alignment algorithm, and parallel database search is realized with compute unified device architecture (CUDA) parallel computing framework. In the experiment, the algorithm is tested on a lower-end and a higher-end personal computers equipped with GeForce GTX 750 Ti and GeForce GTX 1070 graphics cards, respectively. The results show that the parallel method proposed in this paper can achieve a speedup up to 138.86 times over the serial counterpart, improving efficiency and convenience of protein database search significantly.     

非一致性数据库关键词非聚集约束查询与性能分析

在分析非一致性数据库一致性查询方法的基础上,结合非聚集约束条件,以关键词为元数据,利用B-树与二叉树的原理,提出一种新的针对非一致性数据库的查询方法.通过节点分组访问、分层迭代查询的方法,不仅解决非一致性数据库约束条件难写的问题,而且容易组合选择查询条件,有助于提高查询的灵活性与准确性.     

基于Access数据库的辅助电极管理信息系统

利用Visual Basic 6.0程序,设计开发了基于Access 2003数据库的辅助电极管理信息系统,以减少工作量,提高管理效率,实现锻棒和辅助电极日常管理的系统化、信息化和高效化。同时,通过查询功能,实时掌握锻棒和辅助电极库存信息,可以为合理安排生产进度提供依据。     

基于双层索引网络模型的P2P数据库关键字搜索

分布式数据库系统中信息检索对网络状态稳定程度要求高,并不适用于P2P网络.目前的P2P数据库系统也存在通信量高,搜索计算量大等缺点.介绍了一种基于双层索引网络模型的P2P数据库的关键字搜索策略,采用双层索引模型大大减小网络通信量,同时使得在节点成员关系频繁变化的情况下也很有效.采用的关键字搜索根据相似度进行匹配,使用局部结果合并以获得更丰富的结果.     

踩点式信息搜索的新方法

从小偷踩点获取藏金信息中受到启发，提出了一种互联网信息智能搜索新方法。能够从已经分好类的特定领域网站中，准确高效地搜索出隐藏于其内部的目标网页。把所有的搜索网页根据检索信息分成两类：一类是信息点，一类是信息路径。采用信息路径特征与信息点信息量特征描述有机结合而形成的一种新的搜索知识表示方法。基于这种知识表示方法，智能搜索方法不仅能够对网站中网页进行深度优先的智能搜索，而且还能够通过对其搜索过程和结果的自学习来获取更多更好的搜索知识。     

基于 K-center和信息增益的 Web搜索结果聚类方法 *

基于 K-center和信息增益的概念 ,将改进后的 FPF( furthest-point-first)算法用于 Web搜索结果聚类 ,提出了聚类标志方法 ,使得聚类呈现出的结果更易于用户理解 ,给出了评价聚类质量的模型。将该算法与 Lingo, K-means算法进行比较 ,其结果表明 ,本算法能够较好地平衡聚类质量和速度 ,更加适用于 Web检索聚类。