Analysis and Enlightenment of Big Data Platform for Adverse Drug Reaction Supervision in China and the United States

Objective To introduce the relevant big data platforms of FDA regulatory sciences and to provide reference for the construction of big data platform for China’s regulatory science under the“14th five-year plan”to deepen the reform of medical and health system.Methods A comparative analysis was made on China’s big data for regulatory science after studying the development process,operation mode,practical significance and characteristics of the big data platform for FDA regulatory science,which would help China to establish a perfect big database.Results and Conclusion The construction of big data platform for China’s regulatory science is not comprehensive compared with that in the United States.It is necessary to build data platforms in line with China’s national conditions through efforts in law,talents,standards,and other aspects.

Hotshots of Spatio-temporal Behavior of Chinese Residents in the Context of Big Data:Visual Analysis Based on CiteSpace

By using CiteSpace software to create a knowledge map of authors,institutions and keywords,the literature on the spatio-temporal behavior of Chinese residents based on big data in the architectural planning discipline published in the China Academic Network Publishing Database(CNKI)was analyzed and discussed.It is found that there was a lack of communication and cooperation among research institutions and scholars;the research hotspots involved four main areas,including“application in tourism research”,“application in traffic travel research”,“application in work-housing relationship research”,and“application in personal family life research”.

Construction of Smart City Spatio-Temporal Information Cloud Platform in Weifang,China

On the basis of the digital Weifang geospatial framework,Smart Weifang spatio-temporal information cloud platform(WFCP)integrated legal person information,population,place name and address data,macroeconomic data and so on.And it also expanded the data contents,such as the indoor and outdoor data,the overground and underground data,panoramic data and real data.It also introduced the contents of historical geographical information in different periods and real-time location information,address information of sensing equipment,real-time perception and interpreting information.It has overcome the difficulties of real-time access of Internet of Things(IoT)perception,multi-node collaboration,64-bit support,cluster deployment and has the characteristics of spatio-temporal management,ondemand service,large data analysis and micro-service architecture.It built spatio-temporal information big data center and spatio-temporal information cloud platform,realized the convergence and management of the distributed big data,deeply applied for land,transportation,environmental protection,police and subdistrict five areas,by supporting the integrated application of multi-source information and supporting intelligent deep application.In the aspect of hardware environment construction,according to the top-level design and unified arrangement of Smart Weifang,the WFCP was migrated to Weifang cloud computing center,to achieve the on-demand computing resources and dynamic scheduling load-based computing resources,to support the generalizing load map application.

Discussion on the Construction of Spatiotemporal Big Data Platform for Smart City

The so-called smart city is a new form of information technology that is achieved through the integration of the contemporary advanced big data technology,Internet of Things technology,cloud computing technology,and spatial geographic information.At present,the application of this technology is important for the urban construction,planning,and services as well as management.This technology also provides great convenience in these aspects,which has allowed the cities to develop and transform towards the direction of smart cities.Based on this situation,the construction of spatiotemporal big data platforms in smart cities was analyzed in this article,and this analysis may provide a reference for the construction and development of todays smart cities.

Application of Big Data Information Platform in Medical Equipment

The application of big data in the medical device industry mainly refers to the analysis and processing of various medical devices,so as to provide patients with better treatment and rehabilitation services.At present,our country already has a relatively mature and reliable large database system.This article studies the application of medical equipment in the big data information platform.The main methods used in this article are survey method,case analysis method,and interview method.The big data information platform and medical devices are studied from different aspects.The survey results show that 41%of people completely agree with the role of big data information platforms in medical devices.

Overview of Construction and Application of Big Data Analysis Platform

Big data technology is widely spread around the world,and is constantly developing and applying.In order to enhance the application value of big data analysis platform,it is necessary to constantly improve the data analysis and processing capacity of big data platform,so as to build a complete data analysis platform,realize resource sharing and real-time data collection.As a key point of contemporary information development,big data analysis platform is of great significance to promote social data exchange.Based on this,this paper focuses on two aspects:first,it describes the construction process and content of big data platform;second,it summarizes the relevant application and development of big data platform for reference.

Research on the Relationship Between Garlic and Young GarlicShoot Based on Big Data

In view of the problems such as frequent fluctuation of garlic price, lack ofefficient forecasting means and difficulty in realizing the steady development of garlicindustry, combined with the current situation of garlic industry and the collected datainformation. Taking Big Data platform of garlic industry chain as the core, using themethods of correlation analysis, smoothness test, co-integration test, and Grangercausality test, this paper analyzes the correlation, dynamic, and causality between garlicprice and young garlic shoot price. According to the current situation of garlic industry,the garlic industry service based on Big Data is put forward. It is concluded that there is apositive correlation between garlic price and young garlic shoot price, and there is a longtermstable dynamic equilibrium relationship between young garlic shoot price and garlicprice fluctuation, and young garlic shoot price can affect garlic price. Finally, it isproposed to strengthen the infrastructure construction of garlic Big Data, increase thetechnological innovation and application of garlic Big Data technology, and promote thesafety and security ability of the whole industry to promote the development of garlicindustry.

Design and Implementation of the Sense Egypt Platform for Real-Time Analysis of IoT Data Streams

Nowadays, we experience an abundance of Internet of Things middleware solutions that make the sensors and the actuators are able to connect to the Internet. These solutions, referred to as platforms to gain a widespread adoption, have to meet the expectations of different players in the IoT ecosystem, including devices [1]. Low cost devices are easily able to connect wirelessly to the Internet, from handhelds to coffee machines, also known as Internet of Things (IoT). This research describes the methodology and the development process of creating an IoT platform. This paper also presents the architecture and implementation for the IoT platform. The goal of this research is to develop an analytics engine which can gather sensor data from different devices and provide the ability to gain meaningful information from IoT data and act on it using machine learning algorithms. The proposed system is introducing the use of a messaging system to improve the overall system performance as well as provide easy scalability.

Preliminary build and application of a data analysis platform for coiled tubing steel strips

To solve the problems in the quality control and improvement of coiled tubing steel strips production, such as scattered and inefficient production data, difficult performance fluctuation factor analysis, complex multivariate statistical analysis, and low accuracy and difficulty in mechanical property prediction, an industrial data analysis platform for coiled tubing steel strips production has been preliminarily developed.As the premise and foundation of analysis, industrial data collection, storage, and utilization are realized by using multiple big data technologies.With Django as the agile development framework, data visualization and comprehensive analyses are achieved.The platform has functions including overview survey, stability analysis, comprehensive analysis(such as exploratory data analysis, correlation analysis, and multivariate statistics),precise steel strength prediction, and skin-passing process recommendation.The platform is helpful for production overviewing and prompt responding, laying a foundation for an in-depth understanding of product characteristics and improving product performance stability.

Text Mining Based on the Korean Word Segmentation System in the Context of Big Data

Text mining is a text data analysis,found that the relationship between concepts and underlying concepts from unstructured text,it is extracted from large text database has not yet been realized patterns or associations,some information retrieval and text processing system can find the relationship between words and paragraphs.This article first describes the data sources and a brief introduction to the related platforms and functional components.Secondly,it explains the Chinese word segmentation and the Korean word segmentation system.At last,it takes the news,documents and materials of the Korean Peninsula as well as the various public opinion data on the network as the basic data for the research.The examples of word frequency graph and word cloud graph is carried out to show the results of text mining through Chinese word segmentation system and Korean word segmentation system.

从技术赋能到整体重塑:公共体育服务数字化治理的模式重构、组织变革及推进机制

数字时代我国公共体育服务从“技术赋能”到“整体重塑”的数字化进程被视为一个重塑多元主体治理关系及其能力的演变历程,对于提高公共体育服务供给效率具有重要意义。运用文献资料法、逻辑分析法等厘清了公共体育服务数字化治理的基本内涵及现存困境,重新审视了其模式重构的核心维度,深入阐释了其组织变革的动因特征,重点讨论了其推进机制的实践要素。研究认为:理念重构、价值重构、方式重构等形成模式重构的核心维度;管理思维转换、运行范式转换、决策方式转换等构成组织变革的动因特征;管理机制、考核机制、协调机制等为推进机制的实践要素。

基础教育资源配置大数据分析平台的整体架构与运行保障

教育大数据是反映基础教育资源配置现状、需求和问题的数据集合,也是重塑基础教育资源配置结构、构建良好教育生态的有效工具。教育大数据能够为资源精准配置提供客观依据、助力理性决策、拓展实践路径、提供监测反馈,可从数据资源层、处理层、分析层和可视化层,整体架构基础教育资源配置大数据分析平台,实现多学段基础教育数据精准采集、多模态基础教育数据分类储存、多因素基础教育数据指标计量、多维度基础教育数据结果呈现。基础教育资源配置大数据分析平台顺利运行的保障措施主要包括:政策跟进,赋予数据驱动合法地位;强化治理,保障平台教育数据质量;注重成效,发挥数据分析平台价值;多元联动,助力数据分析平台共建。通过这些措施,努力实现数据驱动基础教育资源优化配置,促进决策科学化、供给精准化、评估动态化。

地面自动气象站数据流式处理设计与实现

针对观测密度和频次日益增加的海量地面自动气象站数据,在气象大数据云平台(天擎)中设计了基于Storm的实时流式处理,利用大规模并行处理的优势提高地面自动气象站数据的处理时效。在流式处理中,设计处理拓扑直接解码标准格式的数据消息;消息确认采用手工确认的方式,将数据解码组件锚定数据接入组件,实现每条数据的可靠处理;数据解码时进行字节校验和时间检查等,过滤异常数据;应用批量加定时的发送策略,解决海量监控信息发送气象综合业务实时监控系统(天镜)的问题;集群部署时保留部分剩余资源,有效应对单节点异常。应用效果表明:国家气象站小时数据的服务时效由全国综合气象信息共享系统(CIMISS)的175 s提高至天擎的78 s,约6×10^(4)个区域气象站小时数据的服务时效由CIMISS的5 min提高至天警的2 min,实况分析系统将数据源切换至天擎后,相同时间检索可获取的站点数量较CIMISS增加1倍。2021年12月基于Storm的流式处理与天擎一同在国省业务化运行,实现了长期稳定运行,为MICAPS4、SWAN2.0、实况分析系统等用户提供高效稳定的地面自动气象站数据。

大数据背景下的电力营销信息管理平台设计

为了提升电力营销大数据处理和调度效率,设计大数据背景下的电力营销信息管理平台。基于Hadoop和MapReduce设计平台存储和技术框架,利用大数据技术划分电力营销大数据,实现电力营销信息状态安全分析和监控;采用云计算技术分析和处理电力营销数据。测试结果显示,所设计平台的大数据处理吞吐量较高、大数据处理加速比稳定;数据调度计算效率较高、性能稳定;将电力营销数据以对象形式缓存到内存中时,执行时间较短、耗费内存较小。该平台具备较好的数据处理及调度能力。

大庆油田CIFLog测井数智云平台建设应用实践

针对大庆油田生产中测井数据量大、类型多和数据来源复杂等问题,以中国石油天然气集团有限公司大型测井处理解释软件CIFLog为基础,以业务需求为主导,采用微服务架构和测井分布式云计算技术体系,研发测井大数据存储管理、中间服务层和云端测井处理解释应用等新功能,形成了大庆油田测井数智云应用平台。目前,平台已全面安装部署到大庆油田相关单位,应用效果显著。特别在大庆油田智能决策中心,平台直接用于重点水平井随钻地质导向的现场决策,大幅提升了Ⅰ类储层的钻遇率。未来平台将重点围绕新功能研发、油田数智化应用场景建设和标准化技术体系构建等开展工作,并将取得的成果及时推广复制到西南油田、塔里木油田等油气田。CIFLog云平台作为中国油气工业软件数智化建设应用的先行典范,必将发挥越来越重要的示范引领作用。

智慧灌溉大数据管理平台设计与应用

以粗放型为主的漫灌方式浪费水资源,探索高效节水农业灌溉意义重大。本研究研制了集数据采集、数据管理、数据可视化、分析决策和远程管理为一体的智慧灌溉大数据管理平台,旨在以数字化管理与智能化控制方式提升水资源利用效率。平台利用嵌入式、物联网、互联网、3S(GIS、GPS、RS)等技术,采取“1+1+N”的设计模式,构建作物需水预报模型与灌溉决策模型,基于B/S构架和Java语言,设计了1个灌溉数据中心、1个灌溉数据管理系统、4个应用系统,打造了智慧灌溉大数据管理平台。平台在河北、河南、山东、江苏等地区设有多个示范基地,汇聚了8个科研小组、24个试验基地的有关多种作物的生长、灌溉、气象、土壤等数据,平均采集数据18829条/天,帮助管理人员摸清家底;集成了多个团队的软件系统和62套物联网设备,及时、定量地呈现了农作物生长状况及环境状态,实现了农作区动态监测,助力生产决策;生成农作物需水预报和灌溉决策方案,完成了远程灌溉目标,并且经过实地试验,验证了自动灌溉的有效性,将灌溉水有效利用系数最高提升了31%以上;形成了大田产业、温室中心、数字科研和区域灌溉等不同专题可视化布局,满足多种农业场景应用需求。为农业生产和跨区域管理提供了便捷工具,为农业灌溉数字化系统搭建和应用提供了参考。

基于GIS与大数据分析的矿压监测预警平台

为响应国家关于加快煤矿智能化发展的号召,针对煤矿GIS“一张图”中巷道路径不能实现精确计算,矿压数据不能实现高效甄别、有效提取的问题,以及矿压预警需要实现在线推演、可视化展示的需求,提出建立基于GIS与大数据分析的矿压监测预警平台。采用GIS“一张图”、巷道结点-路径拓扑算法、多源异构监测数据处理技术、矿压大数据分析技术,搭建成能够实现矿井下复杂情况切实反映、矿压监测数据有效提取、采掘风险在线预测、可视化程度高的矿压监测预警平台。通过在李雅庄矿的实际应用,表明该系统运行稳定可靠,可有效提升煤矿的矿压风险监测预警。

数据驱动的学校周边道路拥堵识别

为定量分析多个中小学周边道路拥堵情况,针对性地改善学校周边拥堵状况,对比通学时期与非通学时期的交通拥堵数据.建立学校周边道路拥堵指标,通过拥堵评价函数,分析各道路受周边学校出行影响的程度,识别重点拥堵道路.提出了一种基于地图开放平台获取交通大数据的算法,对南京主城区79所中小学周边道路进行实例分析,给出了各道路受学校出行影响的拥堵值.结果表明:在通学期间交通整体拥堵程度高于非通学时期,通学时期平均拥堵指数为1.973,非通学时期平均拥堵指数为1.664,通学时期比非通学时期平均拥堵指数提高了18.57%.

气象应用业务融入气象大数据云平台的设计

针对现有气象应用不能直接融入气象大数据平台的现状,该文采用“云+端”融入的方法,对气象应用的数据存储、产品加工、业务监控、应用接口以及应用端进行改造设计,使现有气象应用业务能够快速接入气象大数据云平台。该设计在湖北气象业务进行应用,避免了因气象业务智能化建设而造成的重复建设和资源浪费,有利于推动气象业务智能化发展,为今后气象应用改造提供了参考。