基于网络数据统计的食品欺诈研究分析

目的 建立符合我国国情的食品欺诈数据库, 补充国际上已建立的经济利益驱动型掺假(economically motivated adulteration, EMA)数据库空白。方法 搜集2001~2019年发生的食品欺诈行为, 初步建立具有中国国情的食品欺诈数据库。对数据库中信息完备的454条欺诈数据进行分析。结果 媒体报道数据占食品欺诈信息总数的71.6%; 食用农产品、酒类、乳制品、肉制品等11类产品是欺诈事件发生较多的食品类别; 产品欺诈(72.2%)高居食品欺诈类型的首位; 2001~2019年食品欺诈事件数量呈现出先上升后降低, 再上升再降低的“M”状趋势; 目前食品欺诈检测技术主要以理化分析技术为主, 针对的食品类别还有限; 食品欺诈信息以中国为主(89.0%), 涉及到世界各个地区。结论 食品欺诈是广泛存在的全球性问题, 本研究建立的食品欺诈数据库为预防食品安全风险起到了重要的技术支撑作用。     

A benchmark data set for two-phase Coriolis metering

For more than a decade there has been growing interest in the use of Coriolis mass flow metering applied to two-phase (gas/liquid) and multiphase (oil/water/gas) conditions. It is well-established that the mass flow and density measurements generated from multiphase flows are subject to large errors, and a variety of physical models and correction techniques have been proposed to explain and/or to compensate for these errors. One difficulty is the absence of a common basis for comparing correction techniques, because different flowtube designs and configurations, as well as liquid and gas properties, may result in quite different error curves. Furthermore, some researchers with interests in the modelling aspects of the field may not have suitable multiphase laboratory facilities to generate their own data sets. This paper offers a small data set that may be used by researchers as a benchmark i.e. a common data set for comparing correction techniques. The data set was collected at the UK National Flow Laboratory TUV-NEL, using air and a viscous oil, and provides experimental points over a wide flow range (8:1 turndown) and with Gas Volume Fraction (GVF) values up to 60%. As a first investigation using the benchmark data set, we consider how data sparsity (i.e. the flow rate and GVF spacing in the experimental grid) affects the accuracy of a correction model. A range of neural network models are evaluated, based on different subsets of the benchmark data set. The data set and some exemplary code are provided with the paper. Additional data sets are available on a web site created to support this initiative.     

Smart firefighting construction in China: Status,problems, and reflections

“Smart firefighting” construction as a part of the “smart city” has been a concern of the public security and fire agencies at all levels. In this study, the status, problems, and reflections of “smart firefighting” construction in China are discussed. A recent survey indicates that China has launched its smart firefighting construction and initially created a new perspective on its regional smart firefighting work based on three main aspects: intelligent disaster perception by Internet of Things (IoT) construction, intelligent disaster prevention by big data construction, and intelligent disaster disposal by emergency rescue platform construction. However, the current smart firefighting construction in China still has some prominent problems such as the data interconnectivity and normalized management of various platforms, the extensibility of smart firefighting platforms, and the intelligent level of smart firefighting researches, which need to be solved urgently. Therefore, we argue that smart firefighting construction in China should establish data interconnectivity, industrial normalized management, 2D/3D geographic information interaction and extension, high-integration fire protection theory, and many other aspects in the near future and truly realize firefighting visualization and efficient data applications for 4D time space. This study could provide valuable reference for smart firefighting and smart city construction.     

基于SSM框架的大坝监测数据管理系统设计

针对目前大坝安全监测存在数据不能实时计算分析、展示,长期运行产生的大量数据主要靠人工整编且易出错等问题,结合现代信息化技术手段,以Java作为服务开发语言,设计了基于Spring+SpringMVC+Mybatis(SSM)框架的大坝安全监测数据管理平台,用于大坝监测数据的管理和分析,实现数据采集、存储、查询、计算分析、绘图、生成报表报告、实时监控及远程展示等功能,同时亦为监测仪器管理提供了可视化界面,方便仪器管理。结果表明,基于SSM框架的大坝安全监测数据管理系统实时反馈效果好,操作便捷,数据存取性能好、可视化程度高,便于大坝监测数据的管理与实时分析,为大坝安全运行与决策提供支撑。     

智能变电站设备管控大数据分析系统研究

结合数据挖掘、大数据技术在电力系统中的应用现状，分析和设计了一种智能变电站设备管控大数据分析系统。对变电站设备运行状态的大数据特征及基本框架进行了分析，并重点阐述了变电站设备运行状态大数据分析系统的数据集成与预处理、数据存储与处理、设备状态评估模型以及数据可视化展示。实验结果表明，所设计的大数据分析系统能够大幅度提升变电站设备数据分析智能化水平，为变电站管控稳定运行提供更加有效和实用性的技术支撑。     

Seismic life-cycle cost analysis of ageing highway bridges under chloride exposure conditions: modelling and recommendations

Chloride-induced corrosion of highway bridges constitutes a critical form of environmental deterioration and may result in significant escalation of seismic life-cycle costs due to increased fragility during earthquake events. Most of existing literature tends to adopt simplistic uniform area loss assumptions in lieu of potentially complex, yet realistic and more detrimental, pitting corrosion models for seismic vulnerability analysis. Since the degree of deterioration depends on the severity and duration of exposure, there exists a need to investigate the influence of uniform vs. pitting corrosion assumption on seismic life-cycle costs for varied chloride exposure conditions. A case-study example of a highway bridge in Central and Southeastern US reveals consideration of pitting corrosion as critical for extreme exposures compared to relatively minor settings. Subsequently this study provides recommendations to aid bridge engineers and stakeholders to balance between computational cost and accuracy of results to aid prompt decisions on rehabilitation of ageing bridges in different exposure conditions. A framework is also included to compute seismic life-cycle costs from generic measures of corrosion, independent of assumed exposure scenario. This framework is particularly helpful for seismic loss assessment of highway bridges in chloride exposure zones with periodic field measurements to estimate the extent of structural deterioration.     

Identifying cooperation for innovation―a comparison of data sources

ABSTRACT

The value of social network analysis is critically dependent on the comprehensive and reliable identification of actors and their relationships. We compare regional knowledge networks based on different types of data sources, namely, co-patents, co-publications, and publicly subsidized collaborative R&D projects. Moreover, by combining these three data sources, we construct a multilayer network that provides a comprehensive picture of intraregional interactions. By comparing the networks based on the data sources, we address the problems of coverage and selection bias. We observe that using only one data source leads to a severe underestimation of regional knowledge interactions, especially those of private sector firms and independent researchers.     

A Differentially Private Data Aggregation Method Based on Worker Partition and Location Obfuscation for Mobile Crowdsensing

With the popularity of sensor-rich mobile devices, mobile crowdsensing (MCS) has emerged as an effective method for data collection and processing. However, MCS platform usually need workers’ precise locations for optimal task execution and collect sensing data from workers, which raises severe concerns of privacy leakage. Trying to preserve workers’ location and sensing data from the untrusted MCS platform, a differentially private data aggregation method based on worker partition and location obfuscation (DP-DAWL method) is proposed in the paper. DP-DAWL method firstly use an improved K-means algorithm to divide workers into groups and assign different privacy budget to the group according to group size (the number of workers). Then each worker’s location is obfuscated and his/her sensing data is perturbed by adding Laplace noise before uploading to the platform. In the stage of data aggregation, DP-DAWL method adopts an improved Kalman filter algorithm to filter out the added noise (including both added noise of sensing data and the system noise in the sensing process). Through using optimal estimation of noisy aggregated sensing data, the platform can finally gain better utility of aggregated data while preserving workers’ privacy. Extensive experiments on the synthetic datasets demonstrate the effectiveness of the proposed method.     

大数据在公共卫生应急管理中的应用--以内蒙古自治区为例

在此次新冠肺炎防控中,以大数据为代表的新一代信息技术,广泛应用于疫情管控、追踪溯源、模型预测、资源调配、舆情管控等多个方面,发挥了重大作用。通过对大数据在内蒙古自治区疫情防控中的应用分析,从应用情况、存在问题及对策建议三个方面,探讨如何合理有效地利用丰富的数据资源、大数据应用技术,对完善重大疫情防控体制机制提供强有力的支撑,从而推动自治区,乃至国家公共卫生应急管理体系的健全与完善。