基于XML和本体的物联网数据交换标准体系研究

针对当前物联网应用层中相关数据交换标准纷繁复杂,相关标准主体各行其是的问题,从XML(可扩展标记语言)和本体的角度出发,从互联网、语义网和物联网的关系入手,提出了建立物联网数据交换标准体系的思路,即标准应以XML为语法格式,以标准化的本体为语义共识;标准体系应以顶级本体为基础,以纵向的领域本体和横向的任务本体为支撑,建立起各种不同的应用本体标准。文章最后通过一个应用实例分析了所述标准体系发展的若干关键要点。     

Filematch: a format for the interchange of computer-based files of structured data

The structure of data in computer-based files is information which may not be explicit in the files themselves, but is incorporated in part in the computer software designed to process the files. If a computer-processable file of data is to be processed using a “system” other than the one used to generate the file initially, conversion of the file to another format is normally necessary. A format, called FILEMATCH, is presented which for structures encountered in earth science data, incorporates the structural information in the files themselves, thus providing a medium for interchange of files among a variety of software systems.     

XRules: An effective algorithm for structural classification of XML data

XML documents have recently become ubiquitous because of their varied applicability in a number of applications. Classification is an important problem in the data mining domain, but current classification methods for XML documents use IR-based methods in which each document is treated as a bag of words. Such techniques ignore a significant amount of information hidden inside the documents. In this paper we discuss the problem of rule based classification of XML data by using frequent discriminatory substructures within XML documents. Such a technique is more capable of finding the classification characteristics of documents. In addition, the technique can also be extended to cost sensitive classification. We show the effectiveness of the method with respect to other classifiers. We note that the methodology discussed in this paper is applicable to any kind of semi-structured data. Editors: Hendrik Blockeel, David Jensen and Stefan Kramer An erratum to this article is available at .     

XML在数字化校园数据同步平台中的应用研究

为了解决数字化校园建设中存在的"信息孤岛"问题,针对这一特定领域在数据同步方面的特点和要求,提出了一种数据同步平台(DSP)的解决方案.分析和描述了系统的工作原理和流程,并对XML在数据同步平台的设计与实现中主要技术环节的应用给出了充分的论述.实践结果表明,XML及其相关技术无疑是数字化校园数据同步平台建设的有效手段.     

一种数字图像的栅格矢量混合文件格式

基于数字图像的自适应非均匀矩形剖分,定义了一种数字图像的栅格矢量混合的文件格式,称之为RV文件格式,它是在给定剖分精度下,对图像的不同剖分层次自适应地采用不同的储存方式,层次高的以栅格方式储存,层次低的以矢量方式储存。其优势表现在可以节省空间,对数字图像有压缩效果。特别是对巨幅图像的存储,空间节省优势更为显著。对巨幅logo图像进行了压缩性能评价实验,结果表明数字图像的RV文件对大面积连续灰度的图像有显著的压缩效果。     

From tabular data to knowledge graphs: A survey of semantic table interpretation tasks and methods

Tabular data often refers to data that is organized in a table with rows and columns. We observe that this data format is widely used on the Web and within enterprise data repositories. Tables potentially contain rich semantic information that still needs to be interpreted. The process of extracting meaningful information out of tabular data with respect to a semantic artefact, such as an ontology or a knowledge graph, is often referred to as Semantic Table Interpretation (STI) or Semantic Table Annotation. In this survey paper, we aim to provide a comprehensive and up-to-date state-of-the-art review of the different tasks and methods that have been proposed so far to perform STI. First, we propose a new categorization that reflects the heterogeneity of table types that one can encounter, revealing different challenges that need to be addressed. Next, we define five major sub-tasks that STI deals with even if the literature has mostly focused on three sub-tasks so far. We review and group the many approaches that have been proposed into three macro families and we discuss their performance and limitations with respect to the various datasets and benchmarks proposed by the community. Finally, we detail what are the remaining scientific barriers to be able to truly automatically interpret any type of tables that can be found in the wild Web.     

数据点表在远程监管系统中的应用研究

针对煤矿监测系统存在网络瓶颈、采集终端不兼容的现状,提出了一种基于数据点表的矿井瓦斯远程多级监控监管网络系统构架平台。该平台集成了远程监控系统的数据点表的结构、数据采集的文件格式、数据传输的数据格式、基础数据的生成和上传等核心技术。利用数据点表规定的标准接口消息方式实现系统远程监测和监控的数据传递及命令传达,使整个系统很好地解决了低投入与高效率之间的矛盾,具有远程监控、监管、维护、故障诊断和事故预警与决策功能。通过煤矿瓦斯监测监控工程实际应用说明,这种通信方式不受系统地理条件的限制,在数据传递过程中能够确     

基于面向对象XML的存储模式的设计与实现

通过扩展DTD和XML文档的解析建立面向对象的XML存储模式中的数据仓支持XML数据之间的继承关系和基于XML的面向对象的数据查询方式。文章阐述了解析器的系统设计与实现算法,并给出进一步的研究方向。     

决策树在XML数据库挖掘中的研究

传统数据挖掘是基于关系型数据库的,XML技术的出现,使它在短时间内成为表示和交换信息的标准,为数据挖掘提供了新的方法.对决策树、XML技术作了简要介绍,并对基于XML的数据挖掘基本过程进行了探讨研究,提出了一种决策树在XML数据库挖掘的分析模型.最后,通过一个实例来说明如何利用这个模型进行数据挖掘,并指明了今后的研究方向.     

GLONASS卫星信号模拟器导航电文生成

导航电文的生成是GLONASS卫星信号模拟器研制中的关键部分,获得正确的导航电文信息是接收机实现定位、测速以及授时等功能的前提条件。为了满足接收机测试的需要,GLO-NASS卫星信号模拟器输出信号必须调制正确的导航电文。GLONASS卫星信号模拟器由模拟器仿真软件和信号生成单元组成。主要研究GLONASS卫星信号模拟器的软件部分。在分析GLONASS卫星信号模拟器结构和导航电文结构的基础上,详细介绍了GLONASS卫星信号模拟器中导航电文的生成过程。重点对从R inex文件中读取星历参数并转化成二进制格式导航电文的程序实现进行了深入研究,利用GLONASS接收机对卫星信号模拟器输出的仿真信号进行电文解析和定位解算,试验结果可以验证卫星信号模拟器中导航电文生成的正确性。     

基于XML的异构数据库数据交换技术研究

对实现了一个从关系数据库到XML Schema文档的转换过程进行了详细的研究。通过将数据库的结构及数据提取为XML格式,数据库的结构和数据变得清晰明了,非常适合于网络上的信息交换。在将XML数据写入数据库的过程中,考虑到了数据库结构的有关约束,以保证数据库信息的正确更新。     

State of the art in big data applications in microgrid: A review

The prospering Big data era is emerging in the power grid. Multiple world-wide studies are emphasizing the big data applications in the microgrid due to the huge amount of produced data. Big data analytics can impact the design and applications towards safer, better, more profitable, and effective power grid. This paper presents the recognition and challenges of the big data and the microgrid. The construction of big data analytics is introduced. The data sources, big data opportunities, and enhancement areas in the microgrid like stability improvement, asset management, renewable energy prediction, and decision-making support are summarized. Diverse case studies are presented including different planning, operation control, decision making, load forecasting, data attacks detection, and maintenance aspects of the microgrid. Finally, the open challenges of big data in the microgrid are discussed.     

A distributed-memory implementation of the MCHF atomic structure package

The MCHF (Multiconfiguration Hartree-Fock) atomic structure package consists of a series of programs that predict a range of atomic properties and communicate information through files. Several of these have now been modified for the distributed-memory environment. On the Intel iPSC/860 the restricted amount of memory and the lack of virtual memory required a redesign of the data organization with large arrays residing on disk. The data structures also had to be modified. To a large extent, data could be distributed among the nodes, but crucial to the performance of the MCHF program was the global information that is needed for an even distribution of the workload. This paper outlines the computational problems that must be solved in an atomic structure calculation and describes the strategies used to distribute both the data and the workload on a distributed-memory system. Performance data are provided for some benchmark calculations on the Intel iPSC/860.     

Millau: an encoding format for efficient representation and exchange of XML over the Web

XML is poised to take the World Wide Web to the next level of innovation. XML data, large or small, with or without associated schema, will be exchanged between increasing number of applications running on diverse devices. Efficient storage and transportation of such data is an important issue. We have designed a system called Millau for efficient encoding and streaming of XML structures. In this paper we describe the Millau algorithms for compression of XML structures and data. Millau compression algorithms, in addition to separating structure and text for compression, take advantage of the associated schema (if available) in compressing the structure. Millau also defines a programming model corresponding to XML DOM and SAX for XML APIs for Millau streams of XML documents. Our experiments have shown significant performance gains of our algorithms and APIs. We describe some of these results in this paper. We also describe some applications of XML-based remote procedure calls and client-server applications based on Millau that take advantage of the compression and streaming technology defined by the system.     

DAS中一种XML查询完全性验证算法

随着XML数据库管理系统的发展,数据所有者和服务提供者分离.要享受第三方提供服务的前提是需要确保查询结果的正确性和完全性.在第三方提供查询服务的情况下,算法确保了客户端查询结果的正确性和完全性.该算法的基本思想是对查询结果二次构建Merkle Hash树来验证结果的正确性和完全性.     

Sensitive-by-distance: quasi-health data in the algorithmic era

This article offers a new perspective on the boundaries between health and non-health data in the age of ‘Quantified-Self’ apps: the ‘data-sensitiveness-by-computational-distance’ approach-or, more simply, the ‘sensitive-by-distance’ approach. This approach takes into account two variables: the intrinsic sensitiveness (a static variable) of personal data and the computational distance (a dynamic variable) between some kinds of personal data and pure health (or sensitive) data, which depends upon computational capacity. From an objective perspective, computational capacity depends on the level of development of data retrieval technologies at a certain moment, the availability of ‘accessory data’, and the applicable legal restraints on processing data. From a subjective perspective, computational capacity depends on the specific data mining efforts (or the ability to invest in them) taken by a given data controller: economic resources, human resources, and the use of accessory data. A direct consequence of the expansion of augmented humanity in collecting and inferring personal data is the increasing loss of health data processing ‘legibility’ for data subjects. In order to address this issue, we propose exploiting the existing legal tools in the General Data Protection Regulation to empower data subjects (the right to data access, the right to know the logic involved in automated decision-making, data portability, etc.).     

基于XML的卫星数据迁移方案的研究

在遥感卫星目录系统的信息化建设过程中，随着技术的发展，原有的目录系统将被功能更强大的新系统所取代。在新旧系统的切换过程中。必然要面临一个数据迁移的问题。本针对实际工作中面临的问题，结合XML语言的特点，提出一种新的基于XML的数据迁移的解决方案。     

Multi‐scale navigation of large trace data: A survey

Dynamic analysis through execution traces is frequently used to analyze the runtime behavior of software systems. However, tracing long running executions generates voluminous data, which are complicated to analyze and manage. Extracting interesting performance or correctness characteristics out of large traces of data from several processes and threads is a challenging task. Trace abstraction and visualization are potential solutions to alleviate this challenge. Several efforts have been made over the years in many subfields of computer science for trace data collection, maintenance, analysis, and visualization. Many analyses start with an inspection of an overview of the trace, before digging deeper and studying more focused and detailed data. These techniques are common and well supported in geographical information systems, automatically adjusting the level of details depending on the scale. However, most trace visualization tools operate at a single level of representation, which are not adequate to support multilevel analysis. Sophisticated techniques and heuristics are needed to address this problem. Multi‐scale (multilevel) visualization with support for zoom and focus operations is an effective way to enable this kind of analysis. Considerable research and several surveys are proposed in the literature in the field of trace visualization. However, multi‐scale visualization has yet received little attention. In this paper, we provide a survey and methodological structure for categorizing tools and techniques aiming at multi‐scale abstraction and visualization of execution trace data and discuss the requirements and challenges faced to be able to meet evolving user demands.     

Coping with indefinite and negative data in deductive databases: A survey

A problem with current database systems is the limitation placed on the type of data which may be represented and manipulated within such systems. In an attempt to broaden this to a wider class of data (i.e. rules as well as facts) and a more powerful set of manipulations, the concept of a deductive database was introduced. However, for the sake of efficiency the type of rule which is allowed in a deductive database is restricted in form. This paper surveys a number of attempts to move towards less restrictive forms of rules in deductive databases which allow indefinite and negative data to be handled.     

A neural network-based local rainfall prediction system using meteorological data on the Internet: A case study using data from the Japan Meteorological Agency

In this study, we develop and test a local rainfall (precipitation) prediction system based on artificial neural networks (ANNs). Our system can automatically obtain meteorological data used for rainfall prediction from the Internet. Meteorological data from equipment installed at a local point is also shared among users in our system. The final goal of the study was the practical use of “big data” on the Internet as well as the sharing of data among users for accurate rainfall prediction. We predicted local rainfall in regions of Japan using data from the Japan Meteorological Agency (JMA). As neural network (NN) models for the system, we used a multi-layer perceptron (MLP) with a hybrid algorithm composed of back-propagation (BP) and random optimization (RO) methods, and radial basis function network (RBFN) with a least squares method (LSM), and compared the prediction performance of the two models. Precipitation (total amount of rainfall above 0.5 mm between 12:00 and 24:00 JST (Japan standard time)) at Matsuyama, Sapporo, and Naha in 2012 was predicted by NNs using meteorological data for each city from 2011. The volume of precipitation was also predicted (total amount above 1.0 mm between 17:00 and 24:00 JST) at 16 points in Japan and compared with predictions by the JMA in order to verify the universality of the proposed system. The experimental results showed that precipitation in Japan can be predicted by the proposed method, and that the prediction performance of the MLP model was superior to that of the RBFN model for the rainfall prediction problem. However, the results were not better than those generated by the JMA. Finally, heavy rainfall (above 10 mm/h) in summer (Jun.–Sep.) afternoons (12:00–24:00 JST) in Tokyo in 2011 and 2012 was predicted using data for Tokyo between 2000 and 2010. The results showed that the volume of precipitation could be accurately predicted and the caching rate of heavy rainfall was high. This suggests that the proposed system can predict unexpected local heavy rainfalls as “guerrilla rainstorms.”