基于位图连接索引的复杂多维层次的连接和聚集算法

在ROLAP中往往涉及到大量数据的复杂即席查询，从SQL角度看，这些查询通常都包含多表连接和分组聚集操作。本文提出了一种连接和聚集操作的新算法JAMDHBJI，该算法充分考虑了ROLAP中复杂多维层次的特点，同时考虑到并非全部维都具有维层次的语义特性，将维层次编码和位图连接索引有效结合，把复杂的连接和分组聚集操作转化为在事实表上的区域查询，从而大大提高了连接和分组聚集的效率。理论分析表明该算法是高效的。     

一种基于维层次编码的OLAP聚集查询算法

联机分析处理(OLAP)查询往往需在海量数据上进行即席的复杂分组聚集查询，在其SQL语句中通常包含多表连接和分组聚集操作，因而减少多表连接和压缩关键字，以及对查询数据进行有效地分组聚集操作，成为ROLAP查询处理的关键问题。提出了一种基于维层次编码的新型预分组聚集算法DHEPGA．DHEPGA算法充分利用了编码长度较小的维层次编码及其前缀，来快速检索出与查询关键字相匹配的维层次编码，求得维层次属性的查询范围，减少了I／O开销，提高了OLAP查询效率。理论分析和实验结果表明，DHEPGA算法性能是非常有效的。     

数据仓库中的一种提高多表连接效率的有效方法

联机分析处理OLAP查询经常涉及多表连接,所以提高多表连接的性能就成了提高OLAP查询处理的关键性问题．针对目前直接提高多表连接效率的方法、并行多表连接算法和连接索引,提出了变形多表连接索引．该方法基于使用SQL语句表述的查询模型库QMB建立一系列符合条件的变形多表连接事实表,并建立这些变形多表连接事实表的索引．在特定的多表连接查询中,变形多表连接事实表能替代原事实表与各维表连接,并在查询处理过程中动态更新．理论分析和实验结果表明,该方法可以有效地提高多表连接的查询效率．     

基于分组序号的聚集算法

联机分析处理OLAP(online analytical processing)查询作为一种复杂查询,当使用SQL(structured query language)语句来表述时,通常都包含多表连接和分组聚集操作,因此提高多表连接和分组聚集计算的性能就成为ROLAP(relational OLAP)查询处理的关键问题.提出一种基于分组序号的聚集算法MuGA(group number based aggregation with multi-table join),该方法充分考虑数据仓库星型模式的特点,将聚集操作和新的多表连接算法MJoin(multi-table join)相结合,使用分组序号进行分组聚集计算,代替通常的排序或者哈希计算,从而有效地减少CPU运算以及磁盘存取的开销.算法的实验数据表明,提出的MuGA算法与传统的关系数据库聚集查询处理方法以及改进后的基于排序的聚集算法相比,性能都有显著提高.     

一种复杂多维层次的连接和聚集算法

由于数据仓库中存储着不同粒度、容量巨大的数据记录，所以如何有效地执行联机分析处理(OLAP)查询操作，特别是连接和聚集操作，便成为数据仓库领域的核心问题之一．为此，提出了一种降低连接和聚集操作的新算法(join and aggregation based on the complex multi-dimensional hierarchies，JACMDH)．算法充分考虑了复杂多维层次的特点，在原有的位图连接索引(bitmap join index)的基础上，采用层次联合代理(hierarchy combined surrogate)和预先分组排序的方法，使得复杂的多维层次上的连接和聚集操作转化成事实表上的区域查询，从而在处理多维层次聚集的同时，提高了连接和聚集的效率．算法性能分析和实验数据表明，JACMDH算法和目前流行的算法相比，其性能有显著的提高．     

一种改进的分组序号聚集算法

ROLAP是OLAP（联机分析处理）中使用最广泛的一种类型,其主要功能是管理决策所需要的总结数据。总结数据一般都涉及多表连接和分组聚集操作,提高这些操作的性能成为提高OLAP操作响应速度的关键。为此,提出一种基于分组序号的新聚集算法IMuGA。算法充分利用时间维表特殊性,通过对事实表关键字直接获得分组属性值,减少了多表连接中时间维度的连接次数,提高了联机分析处理查询效率。实验结果表明,该算法是有效的。     

联机分析查询处理中的一种聚集算法

联机分析处理(online analytical processing,简称OLAP)查询是涉及大量数据的即席复杂查询,从SQL(structured query language)角度来看,这些查询通常都包含多表连接和分组聚集操作.从OLAP查询处理角度出发,提出一种新的基于排序的聚集查询算法MuSA(sort-based aggregation with multi-table join).该方法充分考虑到数据仓库星型模式的特点,将聚集操作和新的多表连接算法MJoin相结合,排序时采用     

动态更新实物化视图以提高OLAP查询效率

在数据仓库系统中,OLAP查询一般都涉及多表连接和分组聚集两部分操作,提高这些查询的性能成为提高OLAP响应速度的关键。利用实物化视图,可以准确地计算并保存表连接或聚集等耗时较多的操作的结果。研究基于查询频率的实物化视图的更新算法,可以使实物化视图得到最大效率的使用,明显地缩短查询的响应时间,从而提高OLAP的查询效率。     

基于层次有序维的分组聚集算法

在联机分析处理(OLAP)中,有效地维度模型对海量数据的即席复杂分组聚集查询起着关键的作用.在偏序和映射的基础上,通过定义层次有序维,提出一种基于层次有序维的分组聚集算法.该算法利用维属性之间的聚集关系,通过约束层次链中的元素次序,实现了分组聚集计算中多表连接转换为维范围的查询,提高了连接和聚集效率.最后,实验结果验证了该算法的有效性.     

列存储中的OLAP多查询优化方法

为了使列存储OLAP(on-line analytical processing)操作中I/O和CPU开销较大的扫描、连接、聚集操作实现有效的共享和复用,提出了一个多查询优化技术。根据列存储以及OLAP操作的特点,提出了一系列转换规则,为OLAP查询请求产生的一组相关查询语句生成一个单一全局查询计划。为了达到共享复用的目的,在全局计划中引入新的过滤结点、分组结点、合并结点和聚集结点。同时,借用MuGA(multiply group by algo-rithm)算法,通过分组结点、合并结点、连接结点实现维表及事实表元组的分组序号标记,从而实现列扫描、列连接的共享。并为聚集结点提出了一个多阶段聚集算法,结合最终生成的事实表复合分组序号,实现聚集操作的复用。在SSB(star schema benchmark)数据集上设计实验,证明了该多查询优化策略的有效性。     

Call for Papers The 6^th International Conference on Grid and Cooperative Computing

Recent years have seen rapid advances in various grid-related technologies, middleware, and applications. The GCC conference has become one of the largest scientific events worldwide in grid and cooperative computing. The 6th international conference on grid and cooperative computing (GCC2007) Sponsored by China Computer Federation (CCF),Institute of Computing Technology, Chinese Academy of Sciences (ICT) and Xinjiang University ,and in Cooperation with IEEE Computer Soceity ,is to be held from August 16 to 18, 2007 in Urumchi, Xinjiang, China.     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

法律信息库系统

本文分析了法律数据库的结构和特点，介绍了采用面向对象设计方法和超文本数据库技术开发和实现法律信息库系统将作为重要网络资源之一为不同用户进行法律咨询服务。     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.     

International Journal of Automation and Computing Table of Contents

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Information for authors

正SCIENCE CHINA Information Sciences(Sci China Inf Sci),cosponsored by the Chinese Academy of Sciences and the National Natural Science Foundation of China,and published by Science China Press,is committed to publishing highquality,original results of both basic and applied research in all areas of information sciences,including computer science and technology;systems science,control science and engineering(published in Issues with odd numbers);information and communication engineering;electronic science and technology(published in Issues with even numbers).Sci China Inf Sci is published monthly in both print and electronic forms.It is indexed by Academic OneFile,Astrophysics Data System(ADS),CSA,Cabells,Current Contents/Engineering,Computing and Technology,DBLP,Digital Mathematics Registry,Earthquake Engineering Abstracts,Engineering Index,Engineered Materials Abstracts,Gale,Google,INSPEC,Journal Citation Reports/Science Edition,Mathematical Reviews,OCLC,ProQuest,SCOPUS,Science Citation Index Expanded,Summon by Serial Solutions,VINITI,Zentralblatt MATH.     

Erratum to: Fast global kernel fuzzy c-means clustering algorithm for consonant/vowel segmentation of speech signal

正Erratum to:J Zhejiang Univ-Sci C(ComputElectron)2014 15(7):551-563doi:10.1631/jzus.C1300320The original version of this article unfortunately contained mistakes.Algorithm 6 should be as follows:Algorithm 6 FGKFCM-F clustering Input:(1)X={x_1,x_2,…,x_N},,x_iR~d,i=1,2,…,N,the dataset;(2)C,1C≤N,the number of clusters;(3)ε0,the stopping criterion;     

Journal of Zhejiang University-SCIENCE C (Computers & Electronics) Total contents

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A pragmatic multi-method investigation of discrepant technological events: Coping,attributions, and ‘accidental’ learning

Discrepant technological events or situations that entail a problem, a misunderstanding or a difficulty with the Information Technology (IT) being employed, are common in the workplace, and can lead to frustration and avoidance behaviors. Little is known, however, about how individuals cope with these events. This paper examines these events by using a multi-method pragmatic approach informed by coping theory. The results of two studies – a critical incident study and an experiment – serve to build and test, respectively, a theoretical model that posits that individuals use a variety of strategies when dealing with these events: they experience negative emotions, make external attributions, and adopt engagement coping strategies directed at solving the event, eventually switching to a disengagement coping strategy when they feel they have no control over the situation. Furthermore, users’ efforts may result in ‘accidental’ learning as they try to overcome the discrepant IT events through engagement coping. The paper ends with a discussion of the results in light of existing literature, future opportunities for research, and implications for practice.