Conceptual Model for Automatic Early Warning Information System of Infectious Diseases Based on Internet Reporting Surveillance System

Objective To establish a conceptual model of automatic early warning of infectious diseases based on internet reporting surveillance system, with a view to realizing an automated warning system on a dally basis and timely identifying potential outbreaks of infectious diseases. Methods The statistic conceptual model was established using historic surveillance data with movable percentile method. Results Based on the infectious disease surveillance information platform, the conceptual model for early warning was established. The parameter, threshold, and revised sensitivity and specificity of early warning value were changed to realize dynamic alert of infectious diseases on a dally basis. Conclusion The instructive conceptual model of dynamic alert can be used as a validating tool in institutions of infectious disease surveillance in different districts.

Research and application of real-time monitoring and early warning thresholds for multi-temporal agricultural products information

Monitoring and early warning is an important means to effectively prevent risks in agricultural production,consumption and price.In particular,with the change of modes of national administration against the background of big data,improving the capacity to monitor agricultural products is of great significance for macroeconomic decision-making.Agricultural product information early warning thresholds are the core of agricultural product monitoring and early warning.How to appropriately determine the early warning thresholds of multi-temporal agricultural product information is a key question to realize real-time and dynamic monitoring and early warning.Based on the theory of abnormal fluctuation of agricultural product information and the research of substantive impact on the society,this paper comprehensively discussed the methods to determine the thresholds of agricultural product information fluctuation in different time dimensions.Based on the data of the National Bureau of Statistics of China(NBSC)and survey data,this paper used a variety of statistical methods to determine the early warning thresholds of the production,consumption and prices of agricultural products.Combined with Delphi expert judgment correction method,it finally determined the early warning thresholds of agricultural product information in multiple time,and carried out early warning analysis on the fluctuation of agricultural product monitoring information in 2018.The results show that:(1)the daily,weekly and monthly monitoring and early warning thresholds of agricultural products play an important early warning role in monitoring abnormal fluctuations with agricultural products;(2)the multitemporal monitoring and early warning thresholds of agricultural product information identified by the research institute can provide effective early warning on current abnormal fluctuation of agricultural product information,provide a benchmarking standard for China's agricultural production,consumption and price monitoring and early warning at the national macro level,and further improve the application of China's agricultural product monitoring and early warning.

Designing a Teaching Website for Early Warning Technology Support Specialty Based on Information Architecture

With the advancement of education informatization,learning through the internet has become a very important approach.Existing teaching websites generally have problems such as low accuracy of information grouping and obvious disconnection between the navigation system and content.Based on information architecture,a teaching website for early warning technical support specialty is designed in this paper from four aspects:content organization,identification,navigation,and interaction.The unification of information processing and information requirements is achieved using this method,which improves the quality of professional course construction for early warning technology support specialty.

Research on Technology Early-Warning System Based on Dynamic Information Monitoring

Relying on the advanced information technologies, such as information monitoring, data mining, natural language processing etc., the dynamic technology early-warning system is constructed. The system consists of technology information automatic retrieval, technology information monitoring, technology threat evaluation, and crisis response and management subsystem, which implements uninterrupted dynamic monitoring, trace and crisis early-warning to the specific technology. Empirical study testifies that the system improves the accuracy, timeliness and reliability of technology early-warning.

A Personalized Adverse Drug Reaction Early Warning Method Based on Contextual Ontology and Rules Learning

Background: The fatality of adverse drug reactions (ADR) has become one of the major causes of the non-natural disease deaths globally, with the issue of drug safety emerging as a common topic of concern. Objective: The personalized ADR early warning method, based on contextual ontology and rule learning, proposed in this study aims to provide a reference method for personalized health and medical information services. Methods: First, the patient data is formalized, and the user contextual ontology is constructed, reflecting the characteristics of the patient population. The concept of ontology rule learning is then proposed, which is to mine the rules contained in the data set through machine learning to improve the efficiency and scientificity of ontology rule generation. Based on the contextual ontology of ADR, the high-level context information is identified and predicted by means of reasoning, so the occurrence of the specific adverse reaction in patients from different populations is extracted. Results: Finally, using diabetes drugs as an example, contextual information is identified and predicted through reasoning, to mine the occurrence of specific adverse reactions in different patient populations, and realize personalized medication decision-making and early warning of ADR.

Early Warning System of Important Meteorological Disasters in Hunan Province

Based on technologies of GRADS, Delphi, WEB and an SQLServer, distri- bution system for major meteorological disasters early warning information in Hunan Province was established. The system consists of warning tips, early warning for different media and early warning query statistics and the network terminal of the system platform includes a business database server, a message platform database server, a sending server and a receiving terminal. The system enjoys some func- tions, such as examination by different users, on-time updating and effectiveness of flood prevention, construction of excessive warning channel, construction of compre-hensive warning information platform and further improvement of information distribution. The system provides references for prevention and reduction of important me- teorological disasters in Hunan.

Development and Application of Meteorological Disaster Monitoring and Early Warning Platform for Characteristic Agriculture in Huzhou City Based on GIS

Based on the needs of characteristic agricultural production for meteorological services in Huzhou City,we use C# programming language to develop the meteorological disaster monitoring and early warning platform for characteristic agriculture in Huzhou City. This platform integrates the functions of meteorological and agricultural information monitoring,disaster identification and early warning,fine weather forecast product display,and data query and management,which effectively enhances the capacity of meteorological disaster monitoring and early warning for characteristic agriculture in Huzhou City,and provides strong technical support for the meteorological and agricultural departments in the agricultural meteorological services.

The Development of Intelligent Operation Method of Urban Public Infrastructure Driven by Accurate Spatio-temporal Information

Urban public infrastructure is an important basis for urban development.It is of great significance to deepen the research on intelligent management and control of urban public infrastructure.Spatio-temporal information contains the law of state evolution of urban public infrastructure,which is the information base of intelligent control of infrastructure.Due to the needs of operation management and emergency response,efficient sharing and visualization of spatio-temporal information are important research contents of comprehensive management and control of urban public infrastructure.On the basis of summarizing the theoretical research and application in recent years,the basic methods and current situation of the acquisition and analysis of spatio-temporal information,the forecast and early warning,and the intelligent control of urban public infrastructure are reviewed in this paper.

How reliable is online diffusion of medical information targeting patients and families?

AIM: To determine whether online diffusion of the "Ten Warning Signs of Primary Immunodeficiency Diseases(PID)'' adheres to accepted scientific standards.METHODS: We analyzed how reproducible is online diffusion of a unique instrument, the "Ten Warning Signs of PID", created by the Jeffrey Modell Foundation(JMF),by Google-assisted searches among highly visited sites from professional, academic and scientific organizations;governmental agencies; and patient support/advocacy organizations. We examined the diffusion, consistency of use and adequate referencing of this instrument.Where applicable, variant versions of the instrument were examined for changes in factual content that would have practical impact on physicians or on patients and their families.RESULTS: Among the first 100 sites identified by Google search, 85 faithfully reproduced the JMF model, and correctly referenced to its source. By contrast, the other15 also referenced the JMF source but presented one or more changes in content relative to their purported model and therefore represent uncontrolled variants, of unknown origin. Discrepancies identified in the latter included changes in factual content of the original JMF list(C), as well as removal(R) and introduction(I) of novel signs(Table 2), all made without reference to any scientific publications that might account for the drastic changes in factual content. Factual changes include changes inthe number of infectious episodes considered necessary to raise suspicion of PID, as well as the inclusion of various medical conditions not mentioned in the original.Together, these changes will affect the way physicians use the instrument to consult or to inform patients,and the way patients and families think about the need for specialist consultation in view of a possible PID diagnosis.CONCLUSION: The retrieved adaptations and variants,which significantly depart from the original instrument,raise concerns about standards for scientific information provided online to physicians, patients and families.

An Intelligent Early Warning Method of Press-Assembly Quality Based on Outlier Data Detection and Linear Regression

Focusing on controlling the press-assembly quality of high-precision servo mechanism,an intelligent early warning method based on outlier data detection and linear regression is proposed.Linear regression is used to deal with the relationship between assembly quality and press-assembly process,then the mathematical model of displacement-force in press-assembly process is established and a qualified press-assembly force range is defined for assembly quality control.To preprocess the raw dataset of displacement-force in the press-assembly process,an improved local outlier factor based on area density and P weight(LAOPW)is designed to eliminate the outliers which will result in inaccuracy of the mathematical model.A weighted distance based on information entropy is used to measure distance,and the reachable distance is replaced with P weight.Experiments show that the detection efficiency of the algorithm is improved by 5.6 ms compared with the traditional local outlier factor(LOF)algorithm,and the detection accuracy is improved by about 2%compared with the local outlier factor based on area density(LAOF)algorithm.The application of LAOPW algorithm and the linear regression model shows that it can effectively carry out intelligent early warning of press-assembly quality of high precision servo mechanism.

基于分形维数的高速铁路地震预警系统地震P波震相识别方法

为更好保障高速铁路的运营安全,高速铁路地震预警系统的实施十分必要。5级以下的小震事件占据地震事件的95%以上,提高高速铁路预警系统在小震震相识别的速度与精度能有效保障高铁安全运营。提出一种基于分形维数的地震震相识别算法,优化传统分形维数的计算方法,提高分形维数的计算速度。引入分形斜率曲线并划分为4个阶段,分析临界点的分形斜率特征,通过识别分形斜率极值时刻判断地震波精准到达时刻。提出的算法平均误差达到0.006 3 s,标准差达到0.043 8 s,满足高速铁路地震预警系统的时效性和准确度要求。

基于云计算的地震网络数据安全态势感知仿真

地震发生前具有特殊波动响应特征,通过地震台网灾害信息可确定震灾范围,但是网络个人用户无法通过终端服务器及时查询地震数据,导致对地震的安全感知出现延迟问题。针对地震数据处理的任务密集、流程复杂的计算需求,提出基于云计算的地震网络数据安全态势感知方法。在地震节点布局中融入贝叶斯结构,构成混合结构化安全态势采集模型。应用数据分类方法估计出地震态势数据,提取地震发生的隶属度特征,构建地震网络数据安全态势感知模型。按照区域影响因子算出地震信息量,利用相似原则区分灾害程度,检测地震发生范围的安全态势。实验结果证明:研究方法感知获取的地震层间位移与震中国方位角和实际情况一致,偏差较小,能够明确当前地震区域的安全态势。

数字孪生驱动的长江流域干旱防御平台设计与开发

在全球气候变化的背景下,长江流域发生了多次严重的高温干旱灾害,流域抗旱管理面临着旱情监测告警效率较低、旱灾预报预警精度不高、抗旱预案推演能力不足等瓶颈,迫切需要开展数字化转型。从长江流域抗旱减灾业务管理和“四预”应用需求出发,基于智慧水利和数字孪生建设的总体要求,综合运用WebGL、GIS等技术,建立了干旱防御数字孪生平台,研发了遥感干旱监测评估、干旱专业模型动态加载、旱警水位超限预警、抗旱预案可视化等关键技术,初步实现了“预报-预警-预演-预案”全链条贯通业务应用,切实提升了长江流域抗旱管理智能化、精细化水平,为流域干旱防灾减灾提供了技术支撑。

国家紧急地震信息服务系统的设计、开发及实践

紧急地震信息服务系统是国家地震烈度速报与预警工程五大技术系统的重要组成部分之一,也是对外发布紧急地震信息的关键环节和出口。作为国家地震烈度速报与预警工程“先行先试”单位,四川省地震局基于分布式服务架构开发平台,运用MQTT消息队列等技术,采用JAVA语言完成了四川紧急地震信息服务系统(B系统)的设计与定制开发。目前,该系统已纳入国家地震烈度速报与预警工程紧急地震信息发布的核心业务系统并在全国范围内部署应用,解决了现有紧急地震信息发布系统单一运行的风险,进一步提高了信息发布的稳定性、安全性和时效性。

完善信息化追溯系统风险预警及干预对策对达芬奇手术器械处理流程的影响

目的探讨完善信息化追溯系统风险预警及干预对策对达芬奇手术器械处理流程的影响。方法选择2021年2月至2023年4月医院的162件达芬奇手术机器人的手术器械为研究对象,按照完善信息化追溯系统风险预警及干预对策实施时间分组,将2021年2月至2022年2月实施完善信息化追溯系统风险预警及干预对策前的80件达芬奇手术机器人的手术器械作为对照组,将2022年3月至2023年4月实施完善信息化追溯系统风险预警及干预对策后的82件达芬奇手术机器人的手术器械为观察组。对比两组灭菌工作质量、质量管理效果及使用满意度。结果观察组灭菌工作质量中的清洗合格率、包装正确率、监测记录合格率、存储发放正确率均高于对照组,差异有统计学意义(P<0.05);观察组器械管理质量中收发速度、供应质量、问题追溯、沟通服务方面评分均高于对照组,差异有统计学意义(P<0.05);观察组使用满意度高于对照组,差异有统计学意义(P<0.05)。结论完善信息化追溯系统风险预警及干预对策优化达芬奇手术机器人手术器械的处理流程,提高灭菌与管理质量,提升器械使用满意度。

江苏地震预警信息服务系统分析

对国家地震烈度速报与预警工程江苏预警信息服务系统进行了介绍,分析了2023年6月系统试运行以来的预警信息发布情况。结果显示,预警信息发布的主要延时存在于地震发生到国家一级融合决策系统正式发布预警信息的过程,最短延时为4 s,平均延时为14.358 6 s,江苏省预警系统的预警信息发布各环节延时较少,平均总延时不超过0.9 s,Ⅱ类省级预警中心所在地发生地震后,预警信息发布时延会略长于Ⅰ类。整体来看,江苏地震预警信息服务系统满足时效性要求并具有良好的稳定性,在省预警项目建设完成后,将实现省内破坏性秒级地震预警信息发布与示范服务。

信息触达:灾害预警信息语言表达的影响研究

在自然灾害情境下,应急预警信息的有效触达对目标受众提前做好应急预案、减轻灾害损失具有重要价值,是影响应急管理效果的关键因素之一。本研究基于前景理论与参考点效应,运用实验研究方法收集城市暴雨灾害情境下预警信息受众的自反馈感知和行为数据,对不同参考点语境下灾害预警信息表达对信息触达效果的影响进行研究。结果表明,基于不同参考点设计的信息表达方式对灾害预警信息的触达效果有不同影响,其中具体信息参考点和社会比较参考点显著影响信息受众对灾害严重性和风险性的感知,而消极影响参考点则影响不显著。同时,认知负担会影响包含综合参考点以及与防范措施有关的具体信息参考点的信息触达效果。本研究推进了信息触达理论研究,对于改进政务信息表达、提升灾害预警信息触达效果、增强自然灾害应急管理能力具有重要意义。

网络金融犯罪预警系统结构及优化研究——基于信息生态视角

[研究目的]网络金融犯罪预警系统是实现网络金融犯罪数字化治理的重要工具,但目前在预警体系构建、信息及技术共享、制度供给等方面尚存在诸多不足。将信息生态理论应用于网络金融犯罪预警系统研究中,可基于系统观、互动观、人本观和平衡观对网络金融犯罪预警系统结构进行全面分析和观察,为理清系统优化路径、推动系统健康可持续运行提供理论和实践指导。[研究方法]结合信息生态理论,系统梳理和分析网络金融犯罪预警系统构成要素的内涵、作用和关联关系,明确网络金融犯罪预警系统的形态和动态结构,在此基础上构建网络金融犯罪预警系统结构模型,并结合现实困境提出若干有针对性的优化对策建议。[研究结论]分析得出网络金融犯罪预警系统是由人员层、数据层和环境层通过建立依存与影响、补充与抑制、支持与促进的两两交织关系而形成的动态信息系统,且人员层存在链带、迭升和子集关系,数据层存在同源、遗传变异、离易和重生关系。系统可通过优化预警和组织体系、推动多链式区块链技术创新应用和完善信息共享机制、相关法律法规及绩效考评制度等路径实现健康可持续运行。

基于文本数据的灾害信息风险监测与预警集成方法研究

基于灾害信息的文本数据,该文提出一种风险监测与预警集成方法,以提高灾害信息风险监测效率及监测支持预警的针对性。首先,运用八爪鱼数据采集器采集和处理灾害信息的文本数据;其次,运用BTM主题模型构建灾害信息风险监测模型,得到主题热度趋势并确定具有高风险且亟待预警的话题;然后,提出灾害信息风险预警指标体系和预警等级判定方法,计算所确定话题的风险综合指标预警加权值,并结合预警区间判定预警等级;最后,以2021年“7·20”郑州特大暴雨灾害信息的风险监测和预警为例进行实验分析,验证所提方法的可行性。研究表明,该方法可将灾害信息的文本数据贯穿于风险监测与预警两个过程,有助于为监测结果更有针对性地支持预警工作提供参考。

基于CIM的城市地下空间安全预警系统研究

为了有效防范和应对地下空间可能发生的火灾、水灾、气体泄漏、结构破坏、人员踩踏等事故,通过提出了一种基于城市信息模型(CIM)的地下空间安全预警系统方法研究了城市地下空间安全风险及其分析规律。结果表明:该系统可利用CIM技术整合地下空间的三维模型、属性数据和监测数据,实现对地下空间的实时感知、动态分析和智能预警。该系统还可利用云计算和物联网技术,实现与上层平台和应急部门的数据共享和联动处置,可对提高城市安全风险综合监测预警平台的效能和水平提供支持。本文以某城市地铁站地下空间为例,可见该系统前沿的设计思路、完善的功能模块和良好的预期效果,为基于CIM技术的安全预警研究提供理论依据和研究思路。