网格中代码数据库访问与集成的研究

东营市组织机构代码数据库和扫描库在2001年已经和全省代码数据库共享,通过省中心与国家代码中心数据库联网,汇集了大量分布、异构、多管理域的数据资源,使得网格用户对代码数据的访问变得非常复杂,必须为用户提供行之有效的方法,实现方便、高效、透明、统一的数据访问。该文描述了一种基于包装器—仲裁器(Wrapper-Mediator)[4]方法,这种方法采用虚拟数据集的机制将汇聚在网格中的存储系统抽象成一个虚拟一体化系统,实现了网格数据的统一视图和一种网格环境中的数据统一访问方法。     

混合仿人智能图式的无人艇自主驾控系统设计

针对高度动态、不可预测的海洋环境,开展了无人艇智能运动控制系统的设计研究.首先本文利用认知学科的"图式"概念来分析人体运动控制系统的结构,提出一种混合式分层递阶结构,把人类的先验知识、专家经验融入到该结构中,并在实践中不断学习和完善,则形成了一种混合仿人智能图式;然后根据该图式的思想,设计了自主驾控系统的体系结构,并编制成简单实用、逻辑性强、能实时运行的控制流程;最后进行了无人艇的航线跟踪和安全自主航行的半实物仿真试验,仿真结果表明该无人艇可以安全的避开其他船舶并尽量跟踪航线.     

The pragmatic quality of Resources‐ Events‐Agents diagrams: an experimental evaluation

The Resources‐Events‐Agents (REA) model is a semantic data model for the development of enterprise information systems. Although this model has been proposed as a benchmark for enterprise information modelling, only few studies have attempted to empirically validate the claimed benefits of REA modelling. Moreover, these studies focused on the evaluation of REA‐based system implementations rather than directly assessing the REA‐modelled conceptual schemas that these systems are based on. This paper presents a laboratory experiment that measured the user understanding of diagrammatic conceptual schemas developed using the REA model. The theoretical foundation for the hypotheses are cognitive theories that explain pattern recognition phenomena and the resulting reduction in cognitive effort for understanding conceptual schemas. The results of the experiment indicate a more accurate understanding of the business processes and policies modelled when users recognize the REA model’s core pattern of enterprise information in the diagram. The implication for modelling practice is that the use of the REA model improves the requirements engineering process by facilitating the user validation of conceptual schemas produced by analysts, and thus helps ensuring the quality of the enterprise information system that is developed or implemented.     

基于部分函数依赖的结构匹配方法

模式匹配是模式集成、数据仓库、电子商务以及语义查询等领域中的一个难点.它主要利用元素自身信息(如元素名、数据类型等信息)、数据实例信息(模式中的数据)和结构信息(模式元素相互关联的关系)来挖掘元素语义以获得正确的映射关系.文中介绍了一种将数据实例信息与结构信息相结合来辅助匹配的新方法.此方法首先根据模式对应的数据实例信息来计算模式元素间的部分函数依赖度(模式结构信息),然后根据部分函数依赖关系建立模式元素间的依赖图,再根据元素依赖图计算元素间的结构相似度,最后得到模式元素间的映射关系.由于利用了更多的结构信息辅助匹配,所以文中方法在性能上要优于其它仅使用完全函数依赖结构信息进行匹配的方法.实验表明此方法在查准率、查全率以及全面性等各个指标上都优于已有的其它方法.     

Adaptive relaxation for querying heterogeneous XML data sources

Searching XML data with a structured XML query can improve the precision of results compared with a keyword search. However, the structural heterogeneity of the large number of XML data sources makes it difficult to answer the structured query exactly. As such, query relaxation is necessary. Previous work on XML query relaxation poses the problem of unnecessary computation of a big number of unqualified relaxed queries. To address this issue, we propose an adaptive relaxation approach which relaxes a query against different data sources differently based on their conformed schemas. In this paper, we present a set of techniques that supports this approach, which includes schema-aware relaxation rules for relaxing a query adaptively, a weighted model for ranking relaxed queries, and algorithms for adaptive relaxation of a query and top-k query processing. We discuss results from a comprehensive set of experiments that show the effectiveness and the efficiency of our approach.     

一种利用XML和XSLT生成数据库访问层代码的方法

设计了一种生成数据库访问层程序代码的方法。该方法先从现有数据库或PowerDesigner模型文件中解析出数据库架构信息,并将这些信息用XML格式描述,然后利用XSLT将该XML格式文件转换为用高级程序语言表示的程序代码．     

对双亲／孩子结构连接算法的研究与改进

结合区间编码和结点模型映射方法提出一种用于关系数据库的扩展存储模式.通过按广度优先遍历XML树实现对双亲/孩子关系结构连接算法的改进.改进后的算法降低了内存空间的开销,缩小了列表的扫描范围,明显提高了查找匹配速度,达到了查询优化的目的.     

A manufacturing XML schema definition and its application to a data management system on the shop floor

Digitization for sharing knowledge on the shop floor in the machinery industry has been given much attention recently. To help engineers use digitization practically and efficiently, this paper proposes a method based on manufacturing case data that has a direct relation to manufacturing operations. The data are represented in XML schema, as it can be easily applied to Web-based systems on the shop floor. The definitions were made for eight manufacturing methods including machining and welding. The derived definitions consist of four divisions of metadata, work-piece, process and evaluation. Three divisions except for the “process” division are common to the manufacturing methods. The average number of elements for a manufacturing method is about 200. The represented schema is also used to convey knowledge such as operation standards and manufacturing troubleshooting on the shop floor. Using the definitions, a data management system is developed. It is a Web-based Q&A system, in which the engineers specify the manufacturing case data mainly by selecting from the candidates. Then, the system fills in the blank portions and/or shows messages to help complete the case data. The proposed method is evaluated through practical scenarios of arc welding and machining.     

A relational–XML data warehouse for data aggregation with SQL and XQuery

Integrating information from multiple data sources is becoming increasingly important for enterprises that partner with other companies for e‐commerce. However, companies have their internal business applications deployed on diverse platforms and no standard solution for integrating information from these sources exists. To support business intelligence query activities, it is useful to build a data warehouse on top of middleware that aggregates the data obtained from various heterogeneous database systems. Online analytical processing (OLAP) can then be used to provide fast access to materialized views from the data warehouse. Since extensible markup language (XML) documents are a common data representation standard on the Internet and relational tables are commonly used for production data, OLAP must handle both relational and XML data. SQL and XQuery can be used to process the materialized relational and XML data cubes created from the aggregated data. This paper shows how to handle the two kinds of data cubes from a relational–XML data warehouse using extract, transformation and loading. Copyright © 2008 John Wiley & Sons, Ltd.