DATABASE STRUCTURE FOR THE INTEGRATION OF RS WITH GIS BASED ON SEMANTIC NETWORK

The integration of remote sensing (RS) with geographical information system (GIS) is a hotspot in geographical information science.A good database structure is important to the integration of RS with GIS,which should be beneficial to the complete integration of RS with GIS,able to deal with the disagreement between the resolution of remote sensing images and the precision of GIS data,and also helpful to the knowledge discovery and exploitation.In this paper,the database structure storing the spatial data based on semantic network is presented.This database structure has several advantages.Firstly,the spatial data is stored as raster data with space index,so the image processing can be done directly on the GIS data that is stored hierarchically according to the distinguishing precision.Secondly,the simple objects are aggregated into complex ones.Thirdly,because we use the indexing tree to depict the relationship of aggregation and the indexing pictures expressed by 2_D strings to describe the topology structure of the objects,the concepts of surrounding and region are expressed clearly and the semantic content of the landscape can be illustrated well.All the factors that affect the recognition of the objects are depicted in the factor space,which provides a uniform mathematical frame for the fusion of the semantic and non_semantic information.Lastly,the object node,knowledge node and the indexing node are integrated into one node.This feature enhances the ability of system in knowledge expressing,intelligent inference and association.The application shows that this database structure can benefit the interpretation of remote sensing image with the information of GIS.

基于GeoDatabase的地震构造背景场数据库设计与实现

在介绍GeoDatabase基本结构的基础上,阐述了以个人版GeoDatabase数据模型为基础的云南省地震构造背景场数据库的设计方法实现过程。该数据库建立后能够有效管理多源地震专业数据,可满足地震构造背景数据的一体化管理的需要,并为今后地震构造领域的信息化建设提供了一定的科学依据。

Utilizing Machine Learning with Unique Pentaplet Data Structure to Enhance Data Integrity

Data protection in databases is critical for any organization,as unauthorized access or manipulation can have severe negative consequences.Intrusion detection systems are essential for keeping databases secure.Advancements in technology will lead to significant changes in the medical field,improving healthcare services through real-time information sharing.However,reliability and consistency still need to be solved.Safeguards against cyber-attacks are necessary due to the risk of unauthorized access to sensitive information and potential data corruption.Dis-ruptions to data items can propagate throughout the database,making it crucial to reverse fraudulent transactions without delay,especially in the healthcare industry,where real-time data access is vital.This research presents a role-based access control architecture for an anomaly detection technique.Additionally,the Structured Query Language(SQL)queries are stored in a new data structure called Pentaplet.These pentaplets allow us to maintain the correlation between SQL statements within the same transaction by employing the transaction-log entry information,thereby increasing detection accuracy,particularly for individuals within the company exhibiting unusual behavior.To identify anomalous queries,this system employs a supervised machine learning technique called Support Vector Machine(SVM).According to experimental findings,the proposed model performed well in terms of detection accuracy,achieving 99.92%through SVM with One Hot Encoding and Principal Component Analysis(PCA).

MULTI-RESOLUTION SEAMLESS IMAGE DATABASE

This paper presents the basic concepts and principles,data structure and high efficient spatial index for multi_resolution image database.The database is characterized by arrangement of multi_resource image data and seamless mosaic,distribution_based storage and management,integration with other spatial database software such as GeoStar and GeoGrid developed by Wuhan Technical University of Surveying and Mapping.

Materials databases for the computational materials scientist

Until recently, many computational materials scientists have shown little interest in materials databases. This is now changing be-cause the amount of computational data is rapidly increasing and the potential for data mining provides unique opportunities for discovery and optimization. Here, a few examples of such opportunities are discussed relating to structural analysis and classification, discovery of correlations between materials properties, and discovery of unsuspected compounds.

Visualizing risk factors of dementia from scholarly literature using knowledge maps and next-generation data models

Scholarly communication of knowledge is predominantly document-based in digital repositories,and researchers find it tedious to automatically capture and process the semantics among related articles.Despite the present digital era of big data,there is a lack of visual representations of the knowledge present in scholarly articles,and a time-saving approach for a literature search and visual navigation is warranted.The majority of knowledge display tools cannot cope with current big data trends and pose limitations in meeting the requirements of automatic knowledge representation,storage,and dynamic visualization.To address this limitation,the main aim of this paper is to model the visualization of unstructured data and explore the feasibility of achieving visual navigation for researchers to gain insight into the knowledge hidden in scientific articles of digital repositories.Contemporary topics of research and practice,including modifiable risk factors leading to a dramatic increase in Alzheimer’s disease and other forms of dementia,warrant deeper insight into the evidence-based knowledge available in the literature.The goal is to provide researchers with a visual-based easy traversal through a digital repository of research articles.This paper takes the first step in proposing a novel integrated model using knowledge maps and next-generation graph datastores to achieve a semantic visualization with domain-specific knowledge,such as dementia risk factors.The model facilitates a deep conceptual understanding of the literature by automatically establishing visual relationships among the extracted knowledge from the big data resources of research articles.It also serves as an automated tool for a visual navigation through the knowledge repository for faster identification of dementia risk factors reported in scholarly articles.Further,it facilitates a semantic visualization and domain-specific knowledge discovery from a large digital repository and their associations.In this study,the implementation of the proposed model in the Neo4j graph data repository,along with the results achieved,is presented as a proof of concept.Using scholarly research articles on dementia risk factors as a case study,automatic knowledge extraction,storage,intelligent search,and visual navigation are illustrated.The implementation of contextual knowledge and its relationship for a visual exploration by researchers show promising results in the knowledge discovery of dementia risk factors.Overall,this study demonstrates the significance of a semantic visualization with the effective use of knowledge maps and paves the way for extending visual modeling capabilities in the future.

数据知识产权登记:商业秘密模式抑或数据库模式

数据知识产权登记试点实践的背后隐含着商业秘密模式和数据库模式的理论分歧。数据的商业秘密保护存在影响数据访问、阻碍数据流通利用的负面效应,不值得在制度上予以强化激励。与其通过商业秘密模式寻求数据与知识产权的关联,不如转向数据库模式。我国数据知识产权登记实践中普遍存在“数据结构”要求,与欧盟的数据库概念具有相通之处。“数据结构”可以体现数据集合的智力成果属性。在大数据时代,数据知识产权保护具有超越传统的数据库保护的内涵。相比欧盟“限缩保护范围—权能宽泛模糊”的数据库特殊权利范式,我国可以选择“扩张保护范围—限缩权利内容”的对应范式,从而适应数字时代数据财产保护的新需求,打造数据库保护的中国升级版。

DDE-岩浆岩数据库初步构建与应用

21世纪是大数据的时代,数据、模型驱动下的科学研究新范式与知识发现成为当今科学领域的新态势。本文介绍了在“深时数字地球”(Deep-time Digital Earth,DDE)国际大科学计划框架下构建的DDE-岩浆岩数据库。该数据库以“数据+编图+研究”三位一体的建库思路,基于岩浆岩知识体系,构建了岩浆岩数据库,包括后台服务(云端)、网站(Web端)和科研工作平台(桌面端)。数据主要来源于公开发表的文献、研究团队测试、实验室测试数据等,涉及全球重要造山带、克拉通及部分海洋(大洋钻探数据)等。此外,还设立了22个地域性、学科性专题数据库。数据类型为岩浆岩岩石类型、产状、空间位置等基本信息,以及年代学、地球化学、(Sr-Nd-Hf-Pb-O)同位素及非传统(或新兴)同位素数据。与国际最常用的有关数据库相比,本数据库具有以下优势:(1)“数-图-文”三位一体的设计思路,拥有编图和研究平台;(2)以研究为导向,组织构建了22个专题数据库,更多一线专家参与数据库建设,在某些地域和领域(如中亚、非传统同位素等)形成优势;(3)对数据都尽可能挖掘和补充了年龄、经纬度等时空信息;(4)创建了学科专家可以依据新的发展和需求及时调整数据库结构的技术与功能,而不需要重新编程;(5)有强大的DDE平台支持,为与国际有关数据库互联互通提供了有利条件。最后,利用DDE-岩浆岩数据库的核心数据(年代学、同位素等),对复杂大陆拼合过程、地壳生长、地球深部物质组成架构与演化等重大地球科学问题进行了探索并取得了一些进展,说明该数据库将对推动数据驱动的岩浆岩研究具有重要意义。

MAPGIS在建立地质图数据库中的应用

MAPGIS在国内应用相当广泛,主要用于数字制图及空间数据库管理、空间分析。MAPGIS数据格式可与其他的地理信息系统软件如ArcGis的数据相互转换。本文主要介绍了利用MAPGIS地理信息系统,以新疆、甘肃、青海、宁夏地质图为例,应用第二代《中国地质图集》(中文版)中的MAPCAD数据,讨论建立1∶200万地质图数据库的方法、步骤及建立地质图数据库的意义。

加强专病数据库质控提升乳腺癌诊疗科研转化价值研究

目的:设计一套质量控制策略,使缺乏专病数据管理平台的医院通过较低的技术门槛来评估专病结构化模板数据的质量。方法:通过672例确诊后直接手术的早期乳腺癌患者数据的训练,形成一套基于函数的“模板-条目-字段”三级质控方案,分级评估从专病结构化模板采集并整合的数据。结果:结合人工复核,总结了不同时点模板数据缺失的客观现实因素,与主观可改进因素相区别。结合临床反馈与改进,乳腺癌专病结构化病历模板的使用比例提高了30.7%以上,手术术式描述从43种简化为12种。保留了更多结构化诊疗数据,提高了数据字段规范化的程度。结论:三级质控策略实施技术门槛低,有助于提高专病结构化病历模板的使用率,促进底层数据治理,提高数据的科研转化价值,可作为医院或专科实施专病结构化数据质控的备选方案。

MapGIS下空间数据库的建立及其典型问题研究

以云南省地质图、水文地质图空间数据库的建立为例,通过对空间数据库建设中资料准备、图形矢量化、空间数据处理及文件转换四个过程的分析,总结了在进行回溯型空间数据库建库过程中需要注意的一些典型问题,并提出了解决的办法。论述了在MapGIS下空间数据库建立过程中的一些技巧及经验。

基于MapGIS与Oracle的地质数据库建设

与普通的数据相比,地质数据有着多源、多量、多类、多元、多维、多主题等特点。由于地质数据自身的特点,如何有效地存储管理海量地质成果资料和相关信息要素,已经成为当前的热门研究课题。以矿产资源潜力评价数据为例,在Oracle 10G、Map GIS K9平台基础上完成全国矿产资源潜力评价数据的数据库建设工作。在原有软件的基础上,对海量地质数据进行统一管理,为地质数据的应用提供基础保障,从而提高地质数据的信息化服务能力。

新型基础测绘中二维地理实体数据接边流程探讨

由于地理实体数据体量大、数据结构特殊、语义关系复杂的特点,传统的接边方式并不适用于地理实体数据生产流程。本文引入了地理实体生产库,配合生产软件,通过接边数据提交、边界判断、数据标记、数据下载、接边生产、数据上传更新的全过程接边流程设计,提高了接边的效率和质量,保证了数据的完整性。经过工程实例验证,本文设计的接边流程合理有效,效率较高,有效支撑了国家新型基础测绘北京试点的建设。

基于MapGIS市政管线系统的某道路数字化研究

文章结合江苏省某道路工程实例,通过对管线信息的数据转换和空间数据矢量化,创建了市政管线系统数据库,并将其与MapGIS属性库进行动态连接;基于MapGIS软件,对市政管线系统进行空间分析,通过管线网络分析实现了对各种管线的路径查询、属性统计和网线追踪等功能。研究表明,市政管线系统数字化具有一定的可操作性和实用性,可为城市管网的日常管理与信息共享提供参考。

智库大数据存储器面盖层叠精密模设计

结合大数据存储器面盖高精度一模多腔大批量注射成型生产的需要,采用CAE分析确定单腔浇注系统、冷却系统,然后,构建多腔浇注系统,得到的成型方案为单腔采用牛角浇口进浇、热流道+冷流道复合式浇注系统进行供料,基于此,设计了一种双层叠层注射模具,模具模腔设置为1模8腔,分为上下2层、每层设置4个模腔,8个模腔的成型塑件的精度均能达到MT3级。模具中,结合塑件内壁倒扣、插桩等特征的脱模需要,单腔模腔配套设置了1个滑块机构和4个斜顶机构,滑块机构依靠模具的开模动力采用斜导柱驱动,斜顶及顶针采用油缸驱动推板进行顶出。热流道系统由5个热嘴和1块热流道板组成,采用H型布局,保证了8个模腔得到均衡充填。模具分为2次开模顺序打开,采用专用型开闭顺序控制机构进行开闭顺序控制,利用多重导柱机构件对开模时中间定模部分进行运动导向,保证模腔的闭合复位稳定可靠。设计的模具有效地解决了实际生产中一模多腔布置时难以得到精度较高且等级一致的塑件的难题。

基于iData数据工厂的地形图入库方案及关键技术研究

地形图数据入库是智慧城市基础地理信息建设中非常重要的内容。文章先是对目前行业内相关技术发展现状进行了阐述,分析了地形图入库的难点,然后介绍了iData数据工厂的地形图入库流程,同时根据相关项目设计了相应的数据库模板和入库转换方案,并将其投入应用。结果表明,基于iData数据工厂的地形图入库方案不仅操作简便,易于掌握,且灵活度高,适用范围广,是一种高效的数据处理方法。

GIS数据在快速地图制图中的应用研究

地图是一种信息表达的重要方式,其在整个测绘行业发展中有着十分重要的地位,地图的制图技术随着计算机图形学和地图数据库的发展而发展,促使地图的制图技术能够得到进一步的提升。该文基于GIS数据快速制图技术,结合其特点、流程等,根据某地区地图制图案例进行研究,探讨GIS数据在快速地图制图中的详细应用,以供相关行业和单位人员参考与借鉴。