A data and physical model dual-driven based trajectory estimator for long-term navigation

Long-term navigation ability based on consumer-level wearable inertial sensors plays an essential role towards various emerging fields, for instance, smart healthcare, emergency rescue, soldier positioning et al. The performance of existing long-term navigation algorithm is limited by the cumulative error of inertial sensors, disturbed local magnetic field, and complex motion modes of the pedestrian. This paper develops a robust data and physical model dual-driven based trajectory estimation(DPDD-TE) framework, which can be applied for long-term navigation tasks. A Bi-directional Long Short-Term Memory(Bi-LSTM) based quasi-static magnetic field(QSMF) detection algorithm is developed for extracting useful magnetic observation for heading calibration, and another Bi-LSTM is adopted for walking speed estimation by considering hybrid human motion information under a specific time period. In addition, a data and physical model dual-driven based multi-source fusion model is proposed to integrate basic INS mechanization and multi-level constraint and observations for maintaining accuracy under long-term navigation tasks, and enhanced by the magnetic and trajectory features assisted loop detection algorithm. Real-world experiments indicate that the proposed DPDD-TE outperforms than existing algorithms, and final estimated heading and positioning accuracy indexes reaches 5° and less than 2 m under the time period of 30 min, respectively.

Automatic data archiving and visualization at HLS-Ⅱ

The control system of Hefei Light Source II(HLS-Ⅱ) is a distributed system based on the experimental physics and industrial control system(EPICS). It is necessary to maintain the central configuration files for the existing archiving system. When the process variables in the control system are added, removed, or updated, the configuration files must be manually modified to maintain consistency with the control system. This paper presents a new method for data archiving, which realizes the automatic configuration of the archiving parameters. The system uses microservice architecture to integrate the EPICS Archiver Appliance and Rec Sync. In this way, the system can collect all the archived meta-configuration from the distributed input/output controllers and enter them into the EPICS Archiver Appliance automatically. Furthermore, we also developed a web-based GUI to provide automatic visualization of real-time and historical data. At present,this system is under commissioning at HLS-Ⅱ. The results indicate that the new archiving system is reliable and convenient to operate. The operation mode without maintenance is valuable for large-scale scientific facilities.

Scientific Data:Preserving, Archiving and Sharing

Scientific data refers to the data or data sets generated from scientific research process through observations, experiments, calculations and analyses. These data are fundamental components for developing new knowledge, advancing technological progress, and creating wealth. In recent years, scientific data has been attracting more and more attention for its preserving, archiving and sharing.

Design of Low-Power Data Logger of Deep Sea for Long-Term Field Observation

This paper describes the implementation of a data logger for the real-time in-situ monitoring of hydrothermal systems. A compact mechanical structure ensures the security and reliability of data logger when used under deep sea. The data logger is a battery powered instrument, which can connect chemical sensors （pH electrode, H2S electrode, H2 electrode） and temperature sensors. In order to achieve major energy savings, dynamic power management is implemented in hardware design and software design. The working current of the data logger in idle mode and active mode is 15 μA and 1.44 mA respectively, which greatly extends the working time of battery. The data logger has been successftdly tested in the first Sino-American Cooperative Deep Submergence Project from August 13 to September 3, 2005.

A Possible New Data Archive Format for EAST

A new possible data archive format for storing huge amounts of data for EAST control anddata acquisition system is presented. This new general-purpose data archive format is network-transparent, i.e, machine-independent and has been implemented in terms of XDR （eXternal Data Representation）. We test this format by using EFIT （Equilibrium Fitting） code on different operation systems, namely Linux and Windows, different processors, namely Sun and Pc, and different programs, namely in Fortran and C language. It can be easily used by different computers and different programming languages.

Land Use Change in Hongta District in Yuxi City, China Based on Archived Landsat Data of the Past 30 Years

Urban expansion, which has affected ecosystem functioning and services at local to global scale, is projected to have aggravating impacts on landscape in the future. A detailed study on spatiotemporal patterns of Hongta District in Yuxi City over a relatively long timeframe was conducted using multi-temporal Landsat TM, ETM+ and OLI data of 1987-2017 associated with Geographic Information System techniques and landscape analysis approaches. Results showed that sealed surfaces (urban area) have expanded from 1.4% to 11.8%, with an annually increasing rate of 7.63%. Trees, farm areas and barren lands all underwent a slight reduction during this time period, whereby 23.8% of farms and 9.8% of bare lands transferred into sealed surfaces. Focusing on the urban expansion pattern, it presents a uninuclear polarizing polygon mode illustrating the urbanization sprawl over time to all directions. The greatest expansions are seen in NNE and SSE direction, mainly because of the topographic constraints. A trade-off between urbanization and sustainable development is under investigation by reclaiming barren soil at the mountain range to transfer farming areas from low altitude plains to make way for urban growth.

Utilization of Altmetrics as a Measure of Trust of Archival Data

Altmetrics is a new method that is currently used to capture the impact of published scholarly works based on data visibility on the web as a supplement to traditional bibliometric methods. On the other hand, archives contain venerable data that can be extremely helpful to the scholars and public. However, there is no measurement tool that can measure the value and the impact of archival data. Therefore, the aim of this paper is to explore the potentials of embracing altmetrics as a trusted measure of archival data, especially with the lack of studies on altmetrics adoption by archives and cultural heritage organizations.

Oracle Data Guard与GoldenGate技术分析对比

随着财务系统数据库的使用时间增长,数据库中的数据量也会增加,数据量越大也意味着数据库备份与恢复所需要的成本就越高,不仅是备份所需时间越来越长,恢复数据所需时间也随之增长;当数据库发生意外而导致数据库中的数据不可修复的时候,容灾远比备份更能快速有效的恢复生产业务的数据;在实际的使用过程中,我们也可以把容灾当做是一个活动的备份来使用,主要介绍了Oracle Data Guard和GoldenGate。

Provenance Method of Electronic Archives Based on Knowledge Graph in Big Data Environment

With the advent of the era of big data,the Provenance Method of electronic archives based on knowledge graph under the environment of big data has produced a large number of electronic archives due to the development of science and technology.How to guarantee the credential characteristics of electronic archives in the big data environment has attracted wide attention of the academic community.Provenance is an important technical means to guarantee the certification of electronic archives.In this paper,knowledge graph technology is used to provide the concept provenance of electronic archives in large data environment.It not only enriches the provenance method,but also guarantees the certification of electronic archives in the large data environment.

Measuring moisture content of dead fine fuels based on the fusion of spectrum meteorological data

Dead fine fuel moisture content(DFFMC)is a key factor affecting the spread of forest fires,which plays an important role in evaluation of forest fire risk.In order to achieve high-precision real-time measurement of DFFMC,this study established a long short-term memory(LSTM)network based on particle swarm optimization(PSO)algorithm as a measurement model.A multi-point surface monitoring scheme combining near-infrared measurement method and meteorological measurement method is proposed.The near-infrared spectral information of dead fine fuels and the meteorological factors in the region are processed by data fusion technology to construct a spectral-meteorological data set.The surface fine dead fuel of Mongolian oak(Quercus mongolica Fisch.ex Ledeb.),white birch(Betula platyphylla Suk.),larch(Larix gmelinii(Rupr.)Kuzen.),and Manchurian walnut(Juglans mandshurica Maxim.)in the maoershan experimental forest farm of the Northeast Forestry University were investigated.We used the PSO-LSTM model for moisture content to compare the near-infrared spectroscopy,meteorological,and spectral meteorological fusion methods.The results show that the mean absolute error of the DFFMC of the four stands by spectral meteorological fusion method were 1.1%for Mongolian oak,1.3%for white birch,1.4%for larch,and 1.8%for Manchurian walnut,and these values were lower than those of the near-infrared method and the meteorological method.The spectral meteorological fusion method provides a new way for high-precision measurement of moisture content of fine dead fuel.

信息资源管理学科视角下的数据要素研究

[目的/意义]数字经济背景下,信息资源管理学科需要进一步融入到数据要素化市场建设之中,积极建构新的学术增长点。[研究设计/方法]首先分析信息资源管理学科与数据要素的关联逻辑以及学科的角色建构问题,而后介绍信息资源管理学科视域下的若干核心议题,最后对两者融合的未来发展提出思考。[结论/发现]数据要素研究是信息资源管理学科的新领域和新方向,应充分发挥学科特色和优势,有组织地推进数据要素研究与实践。[创新/价值]从信息资源管理学科视域思考数据要素研究,为进一步扩大学科研究视野、拓展学科研究空间提供启示,为数据要素化与数字经济发展中的学科话语建构提供参考。

数据要素化背景下的档案数字转型行动空间展望

数据要素化已成为我国引领全球数字转型的关键路径。档案领域作为数据的关键参与者和贡献者,为了及时跟进档案数字转型进程,必须充分协调与数据要素化的衔接。文章从数据要素化背景出发,解析数据作为生产要素的基本认知、流通交易、安全治理以及试点先行的基本内容,进一步探讨档案数字转型同其关联要素,主要展现为档案作为数据要素的内涵扩充、多维参与数据流通交易、档案工作融入数据治理体系、实践推进导向下的试点示范场景构建,并基于此对档案数字转型可展开的行动空间提出展望。

档案数据要素价值论

大数据时代,档案数据成为档案管理新对象,驱动档案数据要素价值成为档案价值新形态。档案数据是数字中国建设的关键生产要素和新质生产力。档案数据要素价值是指档案数据所具有的生产要素价值,立足数字中国战略背景,从更广泛多元的视域将档案数据视为独具特色的经济要素、管理要素、文化要素、知识要素和生态要素,拉动数字经济发展、驱动数字政府决策、牵动数字文化创新、带动数字社会运行和推动数字生态平衡,赋能数字中国建设。文章聚焦档案数据要素价值主题,揭示档案数据要素价值概念内涵,进行档案数据要素价值质性分析,总结档案数据要素价值实现规律,探索数字中国战略下档案数据要素价值实现方式,助力档案数据要素价值潜能释放,为数字中国建设注入档案数据生产力。

论人工智能技术在我国档案工作中的应用

从档案收管用三个业务环节出发,探讨人工智能技术应用于我国档案工作面临的问题,提出人工智能技术应用于我国档案工作中的建议,以提高我国档案工作的水平。通过文献研究和案例分析,总结人工智能技术应用于我国档案工作中存在的问题,并在此基础上提出优化建议。人工智能技术在我国档案工作中的应用前景广阔,目前已有的实践案例对促进人工智能技术在我国档案工作中的应用起到了积极作用。

理念、实践与风险:大数据时代国外档案数据治理研究述评

论文从多维视角探讨国外档案数据治理研究的最新进展,旨在把握大数据时代国外档案数据治理的本质内涵与工具体系。首先,在理念上侧重于探讨大数据环境下文档概念和来源原则的适用性,阐释了档案数据治理的兴起及其表现;其次,注重从技术与战略的视角分析档案数据治理实践特征,尤其关注电子治理、IT治理、信息治理等不同话语下档案数据治理机制及其适用性;最后,在风险层面集中探讨了档案数据开放与服务活动的信任危机表征及解决策略,而社会大众数据保存热潮及催生的数据行动主义研究尤为引人瞩目。保持坚守与发展间的动态平衡,始终是国外学者开展档案数据治理理论与实践探索的基本准则。

大数据战略下国内档案数据管理研究综述

为了将档案工作融入国家大数据战略当中,文章梳理国内有关大数据与档案数据管理相关的研究,对“大数据、档案大数据、档案数据、档案数据化”的概念和相关实践进行研究。根据当前研究现状得出研究成果丰硕,但核心概念尚需厘清;注重理论研究,但实践指导尚需深化;聚焦档案领域,但交叉研究尚需形成等结论。并据此提出加大档案基本理论体系研究的力度与深度、加大数据档案管理活动研究的广度与宽度、构建国家大数据战略下档案管理框架以及研究国家大数据战略下数据档案应用场景等下一步研究方向,以期为相关研究提供借鉴。

我国档案开放数据资源的建设进展与展望

调查我国档案开放数据资源建设进展,旨在明确档案领域参与公共数据开放的优化策略。通过调查档案机构在档案机构官网及公共数据开放平台开放数据的情况,从数据全面性、数据可获取性、数据及时性、数据可用性以及数据互操作性等方面进行解析。由此,发现我国档案开放数据资源建设目前存在着数据开放规模不足、数据资源价值有待提升以及开放程度有限的问题。因此提出档案开放数据资源建设的优化策略,即完善档案开放数据制度,深化主体参与和协同,推进档案开放数据资源对接融通以及完备档案开放数据资源建设流程。

档案工作数字化转型场域下法规体系的完善理路——以《中华人民共和国档案法实施条例》为分析视角

档案工作数字化转型是适应数字中国重要发展战略、提高档案治理效能、实现档案事业高质量发展的必然路径。《中华人民共和国档案法实施条例》在提高档案法规体系立法质量、推动档案法规体系科学构建,进而完善新时代国家档案法规体系方面具有重要作用。基于此,《中华人民共和国档案法实施条例》从顶层设计、数字资源建设、数字基础设施建设、利用服务四个层面推动档案工作实现数字化转型,但对于相关规定的具体落实仍存在进一步精细化和优化的空间。

档案数据价值链模型构建及实现路径探析

数字经济时代,释放数据要素价值已成为推动高质量发展的重要引擎。档案数据作为一种关键数据要素,蕴藏着丰富且独特的生产价值。文章在解析档案数据价值演进逻辑的基础上,引入价值链理论,构建以档案数据采集、处理、开放共享、利用为基本活动,以制度保障、技术赋能、智力支持为辅助活动的档案数据价值链模型,并围绕加强档案数据资源建设、规范档案数据流通环境、强化档案数据主体能力等方面提出档案数据价值的实现路径,以期充分释放档案数据要素价值,赋能经济社会发展。

数智技术时代的中国档案学学科发展

数智技术,直接导致我国千行百业的原始数据形成,其管理正发生前所未有的变化。为适应从人人相连走向万物智联的大数据安全管理,需要对我国高等教育相关学科专业进行系统研究。梳理数字技术对我国组织的业务活动及其原始记录形成和管理的作用影响之后,提出传统的“中国档案学”学科将演进为“档案大数据工程”学科。并且指出,档案大数据工程学科高等教育包括“管理文秘”“数据资源管理”“大数据技术”等专业,尝试提出以上几个专业建设的发展方向。