基于Data Access规范的OPC Server的研究与实现

为了实现OPC数据存取服务器,依据OPC数据存取2．05a技术规范,采用了ATL技术,建立了OPC数据存取服务器的结构模型,实现了OPC数据存取服务器的构建及OPC数据存取服务器的主要功能．

Construction of a reusable data access layer based on .NET

A new design solution of data access layer for N-tier architecture is presented. It can solve the problems such as low efficiency of development and difficulties in transplantation, update and reuse. The solution utilizes the reflection technology of .NET and design pattern. A typical application of the solution demonstrates that the new solution of data access layer performs better than the current N-tier architecture. More importantly, the application suggests that the new solution of data access layer can be reused effectively.

Enhancing Interest Forwarding for Fast Recovery from Unanticipated Data Access Failure in NDN

We show that an aggregated Interest in Named Data Networking (NDN) may fail to retrieve desired data since the Interest previously sent upstream for the same content is judged as a duplicate one and then dropped by an upstream node due to its multipath forwarding. Furthermore, we propose NDRUDAF, a NACK based mechanism that enhances the Interest forwarding and enables Detection and fast Recovery from such Unanticipated Data Access Failure. In the NDN enhanced with NDRUDAF, the router that aggregates the Interest detects such unanticipated data access failure based on a negative acknowledgement from the upstream node that judges the Interest as a duplicate one. Then the router retransmits the Interest as soon as possible on behalf of the requester whose Interest is aggregated to fast recover from the data access failure. We qualitatively and quantitatively analyze the performance of the NDN enhanced with our proposed NDRUDAF and compare it with that of the present NDN. Our experimental results validate that NDRUDAF improves the system performance in case of such unanticipated data access failure in terms of data access delay and network resource utilization efficiency at routers.

Ensuring Security, Confidentiality and Fine-Grained Data Access Control of Cloud Data Storage Implementation Environment

With the development of cloud computing, the mutual understandability among distributed data access control has become an important issue in the security field of cloud computing. To ensure security, confidentiality and fine-grained data access control of Cloud Data Storage (CDS) environment, we proposed Multi-Agent System (MAS) architecture. This architecture consists of two agents: Cloud Service Provider Agent (CSPA) and Cloud Data Confidentiality Agent (CDConA). CSPA provides a graphical interface to the cloud user that facilitates the access to the services offered by the system. CDConA provides each cloud user by definition and enforcement expressive and flexible access structure as a logic formula over cloud data file attributes. This new access control is named as Formula-Based Cloud Data Access Control (FCDAC). Our proposed FCDAC based on MAS architecture consists of four layers: interface layer, existing access control layer, proposed FCDAC layer and CDS layer as well as four types of entities of Cloud Service Provider (CSP), cloud users, knowledge base and confidentiality policy roles. FCDAC, it’s an access policy determined by our MAS architecture, not by the CSPs. A prototype of our proposed FCDAC scheme is implemented using the Java Agent Development Framework Security (JADE-S). Our results in the practical scenario defined formally in this paper, show the Round Trip Time (RTT) for an agent to travel in our system and measured by the times required for an agent to travel around different number of cloud users before and after implementing FCDAC.

Data Virtualization with SAP HANA Smart Data Access

Digital transformation has been corner stone of business innovation in the last decade, and these innovations have dramatically changed the definition and boundaries of enterprise business applications. Introduction of new products/ services, version management of existing products/ services, management of customer/partner connections, management of multi-channel service delivery (web, social media, web etc.), merger/acquisitions of new businesses and adoption of new innovations/technologies will drive data growth in business applications. These datasets exist in different sharing nothing business applications at different locations and in various forms. So, to make sense of this information and derive insight, it is essential to break the data silos, streamline data retrieval and simplify information access across the entire organization. The information access framework must support just-in-time processing capabilities to bring data from multiple sources, be fast and powerful enough to transform and process huge amounts of data quickly, and be agile enough to accommodate new data sources per user needs. This paper discusses the SAP HANA Smart Data Access data-virtualization technology to enable unified access to heterogenous data across the organization and analysis of huge volume of data in real-time using SAP HANA in-memory platform.

Detection of Turbulence Anomalies Using a Symbolic Classifier Algorithm in Airborne Quick Access Record(QAR)Data Analysis

As the risks associated with air turbulence are intensified by climate change and the growth of the aviation industry,it has become imperative to monitor and mitigate these threats to ensure civil aviation safety.The eddy dissipation rate(EDR)has been established as the standard metric for quantifying turbulence in civil aviation.This study aims to explore a universally applicable symbolic classification approach based on genetic programming to detect turbulence anomalies using quick access recorder(QAR)data.The detection of atmospheric turbulence is approached as an anomaly detection problem.Comparative evaluations demonstrate that this approach performs on par with direct EDR calculation methods in identifying turbulence events.Moreover,comparisons with alternative machine learning techniques indicate that the proposed technique is the optimal methodology currently available.In summary,the use of symbolic classification via genetic programming enables accurate turbulence detection from QAR data,comparable to that with established EDR approaches and surpassing that achieved with machine learning algorithms.This finding highlights the potential of integrating symbolic classifiers into turbulence monitoring systems to enhance civil aviation safety amidst rising environmental and operational hazards.

KnowID:An Architecture for Efficient Knowledge-Driven Information and Data Access

Modern information systems require the orchestration of ontologies,conceptual data modeling techniques,and efficient data management so as to provide a means for better informed decision-making and to keep up with new requirements in organizational needs.A major question in delivering such systems,is which components to design and put together to make up the required“knowledge to data”pipeline,as each component and process has trade-offs.In this paper,we introduce a new knowledge-to-data architecture,KnowID.It pulls together both recently proposed components and we add novel transformation rules between Enhanced Entity-Relationship(EER)and the Abstract Relational Model to complete the pipeline.KnowID’s main distinctive architectural features,compared to other ontology-based data access approaches,are that runtime use can avail of the closed world assumption commonly used in information systems and of full SQL augmented with path queries.

Accessing Multi-Source Geological Data through Network in MORPAS Software System

MORPAS is a special GIS (geographic information system) software system, based on the MAPGIS platform whose aim is to prospect and evaluate mineral resources quantificationally by synthesizing geological, geophysical, geochemical and remote sensing data. It overlays geological database management, geological background and geological abnormality analysis, image processing of remote sensing and comprehensive abnormality analysis, etc.. It puts forward an integrative solution for the application of GIS in basic-level units and the construction of information engineering in the geological field. As the popularization of computer networks and the request of data sharing, it is necessary to extend its functions in data management so that all its data files can be accessed in the network server. This paper utilizes some MAPGIS functions for the second development and ADO (access data object) technique to access multi-source geological data in SQL Server databases. Then remote visiting and congruous management will be realized in the MORPAS system.

应用Access,Epi Data软件建设胸痹心痛临床研究数据库的方法及其比较

目的介绍应用Access,Epi Data软件建设胸痹心痛临床研究数据库的方法并进行比较,以探讨其可行性、实用性。方法以胸痹心痛临床研究的病例报告表(CRF)为例,分别介绍应用Access,Epi Data软件建设数据库的步骤和流程,并进行比较。结果应用Access,Epi Data软件建设胸痹心痛临床研究数据库的共同特点为:占用空间较小,界面友好,直观性强,简单易学,操作方便,可以较好的服务于数据管理;区别主要在于费用、存储空间、自动保存、网络功能、管理权限和导出格式等方面。结论应用Access,Epi Data软件建设胸痹心痛临床研究数据库的方法简单、实用,对于我国现阶段一般的中医药临床研究比较适用,也很适合临床单位中以科室或医生个人为主体开展的研究使用,且对于数据管理的普及、规范和进步有重要意义。

Database-oriented storage based on LMDB and linear octree for massive block model

Data organization requires high efficiency for large amount of data applied in the digital mine system. A new method of storing massive data of block model is proposed to meet the characteristics of the database, including ACID-compliant, concurrency support, data sharing, and efficient access. Each block model is organized by linear octree, stored in LMDB（lightning memory-mapped database）. Geological attribute can be queried at any point of 3D space by comparison algorithm of location code and conversion algorithm from address code of geometry space to location code of storage. The performance and robustness of querying geological attribute at 3D spatial region are enhanced greatly by the transformation from 3D to 2D and the method of 2D grid scanning to screen the inner and outer points. Experimental results showed that this method can access the massive data of block model, meeting the database characteristics. The method with LMDB is at least 3 times faster than that with etree, especially when it is used to read. In addition, the larger the amount of data is processed, the more efficient the method would be.

Thermal stability and data retention of resistive random access memory with HfOx/ZnO double layers

As an industry accepted storage scheme, hafnium oxide（HfO_x） based resistive random access memory（RRAM）should further improve its thermal stability and data retention for practical applications. We therefore fabricated RRAMs with HfO_x/ZnO double-layer as the storage medium to study their thermal stability as well as data retention. The HfO_x/ZnO double-layer is capable of reversible bipolar switching under ultralow switching current（〈 3 μA） with a Schottky emission dominant conduction for the high resistance state and a Poole–Frenkel emission governed conduction for the low resistance state. Compared with a drastically increased switching current at 120℃ for the single HfO_x layer RRAM, the HfO_x/ZnO double-layer exhibits excellent thermal stability and maintains neglectful fluctuations in switching current at high temperatures（up to 180℃）, which might be attributed to the increased Schottky barrier height to suppress current at high temperatures. Additionally, the HfO_x/ZnO double-layer exhibits 10-year data retention @85℃ that is helpful for the practical applications in RRAMs.

Study on Mandatory Access Control in a Secure Database Management System

This paper proposes a security policy model for mandatory access control in class B1 database management system whose level of labeling is tuple. The relation hierarchical data model is extended to multilevel relation hierarchical data model. Based on the multilevel relation hierarchical data model, the concept of upper lower layer relational integrity is presented after we analyze and eliminate the covert channels caused by the database integrity. Two SQL statements are extended to process polyinstantiation in the multilevel secure environment. The system is based on the multilevel relation hierarchical data model and is capable of integratively storing and manipulating multilevel complicated objects ( e.g., multilevel spatial data) and multilevel conventional data ( e.g., integer, real number and character string).

Reevaluating Data Stall Time with the Consideration of Data Access Concurrency

Data access delay has become the prominent performance bottleneck of high-end computing systems. The key to reducing data access delay in system design is to diminish data stall time. Memory locality and concurrency are the two essential factors influencing the performance of modern memory systems. However, existing studies in reducing data stall time rarely focus on utilizing data access concurrency because the impact of memory concurrency on overall memory system performance is not well understood. In this study, a pair of novel data stall time models, the L-C model for the combined effort of locality and concurrency and the P-M model for the effect of pure miss on data stall time, are presented. The models provide a new understanding of data access delay and provide new directions for performance optimization. Based on these new models, a summary table of advanced cache optimizations is presented. It has 38 entries contributed by data concurrency while only has 21 entries contributed by data locality, which shows the value of data concurrency. The L-C and P-M models and their associated results and opportunities introduced in this study are important and necessary for future data-centric architecture and algorithm design of modern computing systems.

基于Access的灌溉信息管理系统

针对目前灌溉试验资料的管理、整编、归档、查询仍靠试验人员手工完成的落后局面,为有效地管理和查询灌溉试验数据,在windows 2000或windows XP操作系统下,使用Access开发了灌溉信息管理查询系统。该系统具有对灌溉试验数据进行输入、查询、修改、删除等功能,系统不仅功能全面,且可靠性高,稳定性好,界面可视性强,易于操作。

基于全球研究数据注册仓储Re3data.org的医学科学数据仓储建设

目的:总结全球医学领域科学数据仓储建设现状、经验与不足,为我国医学科学数据仓储建设提供参考和借鉴。方法:利用统计分析、共现分析和社会网络分析等方法,结合可视化图表对2018年Re3data.org中收录的637个医学科学数据仓储的分布、建设等情况进行分析。结果:美国、英国和国际组织在仓储合作建设中贡献最为突出,其中美国参与建设的数据仓储占50%,独立建设仓储达241个。多数仓储收录3～6类数据,科学和统计数据是被收录最多的类型,收录数据主题丰富,64.36%的仓储提供数据质控。Dspace等7种软件被用于数据仓储建设,数据管理涉及5种唯一标识符、16种元数据。结论:欧美国家占据了数据仓储建设高地,需多方合作共促数据开放共享。开源技术降低了仓储搭建门槛,标准规范建设保障仓储运管,数据分级共享提供接口支持,政策许可可保障多方权益。

用ACCESS实现进口铁矿质量的数据分析

利用小型数据库Access对各产地进口铁矿品质的化学分析、物理试验结果进行质量分析以及对各产地、用户的贸易量进行统计 ,从而使质检部门能及时掌握了解进口铁矿动态信息 ,为检验和监管部门提供参考和帮助。

DataReader与DataSet对象之比较分析

随着数据库技术在软件开发中的广泛应用,数据库访问技术在管理系统的设计中得到了广大开发人员的重视。通过对ADO.NET中经常用到的DataReader与DataSet数据访问对象的基本属性、方法以及应用环境的深入比较和分析,找出了他们之间的区别,同时给出了他们在实际应用中的程序设计案例,由此得出了DataReader对象适合在连接工作环境下使用,而DataSet对象更适合在非连接工作环境下使用的结论,同时给数据库开发人员提供有益的参考。

MapGIS数据与Geodatabase数据格式转换关键技术研究

MapGIS软件分别用*.wt、*.wl、*.wp文件来存储点、线、面信息,其中包括空间信息和属性信息。Geodatabase是ArcGIS平台采用的新一代空间数据库技术。项目需要将MapGIS格式的文件转换到ArcGIS的Geodatabase空间数据库中。两种数据格式的转换过程中采用了数据字典技术和MapGIS数据在Geodatabase中的无损存取等技术,实现MapGIS数据在Geodatabase中的统一管理,提高数据的共享性。

利用Access数据库进行计量器具管理

介绍应用Access数据库进行计量器具管理的具体操作方法 ,包括有关数据表和查询表的设计、建立及使用方法。