Three-dimensional conjugate gradient inversion of magnetotelluric full information data

Based on the analysis of impedance tensor data, tipper data, and the conjugate gradient algorithm, we develop a three-dimensional （3D） conjugate gradient algorithm for inverting magnetotelluric full information data determined from five electric and magnetic field components and discuss the method to use the full information data for quantitative interpretation of 3D inversion results. Results from the 3D inversion of synthetic data indicate that the results from inverting full information data which combine the impedance tensor and tipper data are better than results from inverting only the impedance tensor data （or tipper data） in improving resolution and reliability. The synthetic examples also demonstrate the validity and stability of this 3D inversion algorithm.

Challenges and Solutions of Information Security Issues in the Age of Big Data

Big data has been taken as a Chinese national strategy in order to satisfy the developments of the social and economic requirements and the development of new information technology. The prosperity of big data brings not only convenience to people's daily life and more opportunities to enterprises, but more challenges with information security as well. This paper has a research on new types and features of information security issues in the age of big data, and puts forward the solutions for the above issues: build up the big data security management platform, set up the establishment of information security system and implement relevant laws and regulations.

Application of Big Data in Agricultural Informationization in Shandong Province under the Background of "Internet +"

This paper explains the basic concepts of " Internet + " and big data,analyzes the main problems in the application of big data technology in agricultural informationization of Shandong Province,summarizes corresponding solutions from the aspects of government guidance,financial input,open sharing of agricultural big data,big data storage and processing,data mining,etc.,and prospects the application trend of big data technology in agricultural informationization to achieve the connotative development of agriculture in Shandong Province.

Information Science Roles in the Emerging Field of Data Science

There has long been discussion about the distinctions of library science,information science,and informatics,and how these areas differ and overlap with computer science.Today the term data science is emerging that generates excitement and questions about how it relates to and differs from these other areas of study.

Chinese Journal of Library and Information Science(CJLIS) 正式更名为Journal of Data and Information Science(JDIS)

经国内外专家深入探讨和反复论证,经主管、主办单位同意,经国家新闻出版广电总局正式批准(新广出审[2015]1187号文),由中国科学院文献情报中心主办的Chinese Journal of Library and Information Science(《中国文献情报(英)》,CJLIS)将于2016年起正式更名为Journal of Data and Information Science(《数据与情报科学学报(英)》,JDIS)。作为国内唯一的图书馆学情报学领域英文学术期刊,CJLIS自2008年创刊以来,以刊发符合国际规范的高水平学术研究论文、推动中国图书馆学情报学学科发展为己任,组织优秀稿源、坚守学术规范、推动开放获取、严控评议流程,赢得了业界的充分肯定和广

A STUDY OF SOIL CONSERVATION MONITORING INFORMATION SYSTEM BASED ON REMOTELY SENSED DATA FOR A CATCHMENT ON THE LOESS PLATEAU

The Soil Conservation Monitorins Information System (SCMIS) presented in this paper is oriented to soil erosion control, resources exploitation, utilization, planning and management for a small watershed (about 10 sq. km.) on the Loess Plateau. It sums up Remote sensing (RS), Geographical Information System (GIS) and Expert System (ES) and consists of a integrated system. As a basic level information system of Loess Plateau, its perfection and psreading will bring about a great advance in resources exploitation and management of Loess Plateau.

Structural Modal Parameter Recognition and Related Damage Identification Methods under Environmental Excitations: A Review

Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.

大数据时代高校资产管理信息化建设研究

随着大数据技术的快速发展和广泛应用,高校资产管理正面临着信息化建设的新机遇与挑战。利用大数据技术可以使高校资产管理更加精确、高效和透明。文章深入探讨大数据时代下开展高校资产管理信息化建设的意义、问题和策略,旨在帮助高校更好地实施资产管理信息化建设,提高其资产管理的质量和效率。

传感数据:智能时代学习分析的新视角

智能时代,各种智慧教育场所、移动智能终端和可穿戴设备中应用的传感技术可以对学习者的生理特征、行为动作及学习场所等相关数据进行捕捉,使学习者“身体”重新回归到教育者视野,并通过低倾入性的方式采集真实情境中的序列数据,为实现全方位、情境性和过程性的学习分析提供条件。当前,在教育实践中,传感数据已逐步应用于认知监测、行为分析、情感识别以及自适应情境学习等方面,为智能化学习分析与评价提供了良好支持。随着技术与实践的发展,学习分析中的传感技术将从“有感”走向“无感”,传感设备将从单一设备转变为集成系统,应用目的将从对学习过程的合理解释走向精准干预,并从实验研究走向多样化实践。在传感数据应用于学习分析的实践中,教育部门、研究机构和企业应共同努力,以应对理论基础、技术成本和伦理隐私等方面的挑战。

大数据时代企业财务管理信息化转型研究

财务管理对企业经营发展具有重要作用,财务管理质量好坏直接关系到企业经营水平。为了明确大数据时代企业财务管理信息化转型情况,在分析企业财务管理信息化转型意义的基础上结合企业财务管理信息化转型的问题与困境进行研究,最后得出从加速企业财务大数据系统建设、提高财务数据共享水平、树立业财融合理念,提高部门协同、构建完善的财务信息安全防御体系等方面实现企业财务管理信息化转型,为大数据时代企业财务管理体系建设提供相应参考。

“互联网+”与大数据技术导向下医保服务信息化建设对策探微

在“互联网+”与大数据技术的导向下,医保服务信息化建设成为推动医疗保健行业创新发展的重要方向之一。文章旨在探讨“互联网+”与大数据技术导向下医保服务信息化建设的对策,并对相关的实践经验进行总结和分享,以期为医疗保险行业的信息化建设提供参考和借鉴。

大数据和AI技术在江西省药品智慧监管中的探索和应用

目的:深入剖析大数据与AI技术在江西省药品智慧监管中的应用情况,分析存在的问题,并提出改进措施,以提升药品监管效率和公众用药的安全性。方法:通过详细分析国家和江西省内的相关政策,总结江西省药品智慧监管现状,全面探讨了大数据与AI技术在药品监管领域的实际应用。结果及结论:大数据和AI技术已在江西省药品监管中有所应用,但仍存在信息孤岛、监管资源短缺和技术更新缓慢等问题。为此,本研究认为应构建药店智慧监管大数据平台,利用大数据、云计算、电子政务网络等先进技术,并引入YOLO算法模型和Level大模型等AI手段,以增强药品监管的科学性、精确性和整体效率。本研究为江西省药品监管的现代化提供了理论支撑,同时也为全国范围内的药品智慧监管贡献了实践经验和未来发展方向的参考。通过整合大数据和AI技术,可有效解决当前药品监管面临的挑战,从而提升监管水平,确保公众用药安全。

大数据时代信息化运维中的数据安全与隐私保护策略——以朔黄铁路为例

随着信息技术的快速发展,数据安全与隐私保护成为朔黄铁路发展的关键挑战。本文着重探讨朔黄铁路在信息化运维过程中如何应对这些挑战,详细分析了其采用的数据安全技术和隐私保护策略。从数据加密和访问控制到入侵检测和安全审计技术的应用,朔黄铁路展现了其在应对复杂网络威胁方面的先进措施。同时,通过实施数据匿名化和最小化策略,公司加强了对用户隐私的保护。文章还探讨了持续的风险评估、管理优化及员工培训在提升整体信息安全性中的重要性。这些措施不仅提升了朔黄铁路的运营效率,还为铁路行业在数据安全与隐私保护方面提供了宝贵的经验。

教育档案管理信息化建设存在的问题及措施

随着技术的迅速发展,教育档案管理的信息化已成为提升工作效率和服务质量的关键。但教育档案信息化建设在系统兼容性、成本维护、用户培训和数据管理等方面面临着诸多挑战。为应对这些问题,需要采取一系列策略,包括加强系统集成、平衡成本与投资、实施定制化培训及建立全面的数据策略,以提高教育档案管理的效率和安全性。

Exploring the Potentialities of Automatic Extraction of University Webometric Information

Purpose:The main objective of this work is to show the potentialities of recently developed approaches for automatic knowledge extraction directly from the universities’websites.The information automatically extracted can be potentially updated with a frequency higher than once per year,and be safe from manipulations or misinterpretations.Moreover,this approach allows us flexibility in collecting indicators about the efficiency of universities’websites and their effectiveness in disseminating key contents.These new indicators can complement traditional indicators of scientific research(e.g.number of articles and number of citations)and teaching(e.g.number of students and graduates)by introducing further dimensions to allow new insights for“profiling”the analyzed universities.Design/methodology/approach:Webometrics relies on web mining methods and techniques to perform quantitative analyses of the web.This study implements an advanced application of the webometric approach,exploiting all the three categories of web mining:web content mining;web structure mining;web usage mining.The information to compute our indicators has been extracted from the universities’websites by using web scraping and text mining techniques.The scraped information has been stored in a NoSQL DB according to a semistructured form to allow for retrieving information efficiently by text mining techniques.This provides increased flexibility in the design of new indicators,opening the door to new types of analyses.Some data have also been collected by means of batch interrogations of search engines(Bing,www.bing.com)or from a leading provider of Web analytics(SimilarWeb,http://www.similarweb.com).The information extracted from the Web has been combined with the University structural information taken from the European Tertiary Education Register(https://eter.joanneum.at/#/home),a database collecting information on Higher Education Institutions(HEIs)at European level.All the above was used to perform a clusterization of 79 Italian universities based on structural and digital indicators.Findings:The main findings of this study concern the evaluation of the potential in digitalization of universities,in particular by presenting techniques for the automatic extraction of information from the web to build indicators of quality and impact of universities’websites.These indicators can complement traditional indicators and can be used to identify groups of universities with common features using clustering techniques working with the above indicators.Research limitations:The results reported in this study refers to Italian universities only,but the approach could be extended to other university systems abroad.Practical implications:The approach proposed in this study and its illustration on Italian universities show the usefulness of recently introduced automatic data extraction and web scraping approaches and its practical relevance for characterizing and profiling the activities of universities on the basis of their websites.The approach could be applied to other university systems.Originality/value:This work applies for the first time to university websites some recently introduced techniques for automatic knowledge extraction based on web scraping,optical character recognition and nontrivial text mining operations(Bruni&Bianchi,2020).

A Tailor-made Data Quality Approach for Higher Educational Data

Purpose: This paper relates the definition of data quality procedures for knowledge organizations such as Higher Education Institutions. The main purpose is to present the flexible approach developed for monitoring the data quality of the European Tertiary Education Register(ETER) database, illustrating its functioning and highlighting the main challenges that still have to be faced in this domain.Design/methodology/approach: The proposed data quality methodology is based on two kinds of checks, one to assess the consistency of cross-sectional data and the other to evaluate the stability of multiannual data. This methodology has an operational and empirical orientation. This means that the proposed checks do not assume any theoretical distribution for the determination of the threshold parameters that identify potential outliers, inconsistencies, and errors in the data. Findings: We show that the proposed cross-sectional checks and multiannual checks are helpful to identify outliers, extreme observations and to detect ontological inconsistencies not described in the available meta-data. For this reason, they may be a useful complement to integrate the processing of the available information.Research limitations: The coverage of the study is limited to European Higher Education Institutions. The cross-sectional and multiannual checks are not yet completely integrated.Practical implications: The consideration of the quality of the available data and information is important to enhance data quality-aware empirical investigations, highlighting problems, and areas where to invest for improving the coverage and interoperability of data in future data collection initiatives.Originality/value: The data-driven quality checks proposed in this paper may be useful as a reference for building and monitoring the data quality of new databases or of existing databases available for other countries or systems characterized by high heterogeneity and complexity of the units of analysis without relying on pre-specified theoretical distributions.

教务信息化管理下的课程质量保证体系和运行机制研究

该文探讨教务信息化管理下的课程质保体系与运行机制,构建包含标准、监控、评价三层面的框架,并细化建设、过程、监控及评估标准,进而分析信息化平台、大数据、AI在质保中的应用,以优化机制,确保教学质量高效提升。

感知数据分析技术在矿井安全风险预警中的应用

目前各煤矿企业和管理机构已经建立了一套针对矿井生产过程、生产环境、井下人员的监测监控体系,急需对体系产生的海量感知数据进行整理分析,及时预警矿井安全风险、纠正违规行为。矿井感知数据分析是个全新的技术领域,正处在发展的前期阶段。目前初步形成体系的是轴线关联分析法,是以相关法律法规、技术标准为依据,先确定甲烷、一氧化碳、通风、供电等若干关键安全要素,按照控制、状态、时间、空间等关联关系,逐步将每一个关键要素传感器的数据与其关联传感器数据合并观察分析,从而发现违规行为和风险因素。通过案例得出不同对象、不同关联关系的具体分析过程和结论,并系统化、理论化归纳阐述预警分析技术,促进该技术进一步成熟发展和在矿山安全管理工作中推广应用。

Rural Habitation Multistage Nature Boundary Extraction Based on Geographic Name Database

In order to extract the boundary of rural habitation, based on geographic name data and basic geographic information data, an extraction method that use polygon aggregation is raised, it can extract the boundary of three levels of rural habitation consists of town, administrative village and nature village. The method first extracts the boundary of nature village by aggregating the resident polygon, then extracts the boundary of administrative village by aggregating the boundary of nature village, and last extracts the boundary of town by aggregating the boundary of administrative village. The related methods of extracting the boundary of those three levels rural habitation has been given in detail during the experiment with basic geographic information data and geographic name data. Experimental results show the method can be a reference for boundary extraction of rural habitation.