手机定位人口数据在应急救援中的应用

随着智能手机的普及,基于手机定位的人口数据在突发性灾害应急救援领域发挥着日益重要的作用.以近几年地震灾区为主要研究对象,选择灾区中有代表性的旅游景区、县城及乡镇,获取这些区域手机定位的人口数据,同时采用传统方法估算区域内人口数量,并进行差异性对比.研究结果表明:差异性最大的是旅游景区、其次是县城和乡镇;在人口年度变化上...     

Measurement and Management of Human-Induced Patterns of Forest Fragmentation: A Case Study

In many tropical developing countries, the twin pressures of population and poverty are resulting in substantial fragmentation of forests, increasing the probability of extinction for many species, Forest fragmentation occurs when large contiguous forests are perforated by small holes or broken up into edges and smaller patches to form a nonforested matrix of open spaces. Thus, forest fragmentation refers not only to the area of forest cleared, but also to the pattern of this clearance, the resulting forest’s spatial properties. Both characteristics are important for species survivability. Apart from opening up forests to many abiotic and biotic influences, fragmentation can affect species dispersal and migration through its effects on forest connectivity. Landscape ecology conceptualizes connectivity as a gradient of critical thresholds, ranging from the large intact forest to the small unconnected forest patch. This article reports results from a multiple-scale analysis of forest fragmentation in Jamaica’s Cockpit Country, an area of once contiguous forest now under threat from human encroachment. Spatial forest data derived from classification of ETM+ satellite imagery are used to measure fragmentation patterns representing various degrees of forest connectivity and density. The results suggest that, overall, 81% of the region is in forest. However, fragmentation patterns also suggest that this forest is riven with extensive perforations indicative of an early stage in the decline of contiguity. The results provided by the spatial fragmentation model are a first step in the design of effective conservation and rehabilitation plans for the area. The article concludes with a discussion of possible multiscale management options for the region.     

基于大数据挖掘技术的地震舆情感知研究

对地震舆情信息的深入感知和有效管理,能够保障社会和谐发展.提出一个基于大数据技术和深度学习的地震舆情感知平台,基于Hadoop和MongoDB大数据技术实现对海量实时地震舆情数据的处理和存储.基于Word2vec和LSTM的融合模型能够有效实现震后网民的情感识别,为舆情预警提供支持.以台湾5.8级地震舆情数据为例,对该...     

A critical overview of driver recording tools

Introduction: Technological advancements during recent decades have led to the development of a wide array of tools and methods in order to record driving behavior and measure various aspects of driving performance. The aim of the present study is to present and comparatively assess the various driver recording tools that researchers have at their disposal. Method: In order to achieve this aim, a multitude of published studies from the international literature have been examined based on the driver recording methodologies that have been implemented. An examination of more traditional survey methods (questionnaires, police reports, and direct observer methods) is initially conducted, followed by investigating issues pertinent to the use of driving simulators. Afterwards, an extensive section is provided for naturalistic driving data tools, including the utilization of on-board diagnostics (OBD) and in-vehicle data recorders (IVDRs). Lastly, in-depth incident analysis and the exploitation of smartphone data are discussed. Results: A critical synthesis of the results is conducted, providing the advantages and disadvantages of utilizing each tool and including additional knowledge regarding ease of experimental implementation, data handling issues, impacts on subsequent analyses, as well as the respective cost parameters. Conclusions: New technologies provide undeniably powerful tools that allow for seamless data handling, storage, and analysis, such as smartphones and in-vehicle data recorders. However, this sometimes comes at considerable costs (which may or may not pay off at a later stage), while legacy driver recording methods still have their own niches to fill in research. Practical Applications: The present research supports researchers when designing driver behavior monitoring studies. The present work enables better scheduling and pacing of research activities, but can also provide insights for the distribution of research funds.     

基于第二次全国污染源普查质量保证的思考及体系建设初探

通过对清查数据的结果分析,确定第二次全国污染源入户普查的对象,基于企业填报、现场入户、资料收集审核、数据核查等具体工作的实施与开展,思考和归总普查工作中影响数据质量的现实问题和难点,初步构建污染源普查质量保证体系,以期为全国污染源普查数据质量保证提供有益参考。     

大数据环境下企业安全绩效管理的基础性问题*

为明晰大数据对安全绩效管理的影响,把握信息时代下企业安全绩效管理的研究方向,基于大数据时代下安全绩效管理内容,阐述数据驱动下安全绩效管理的应用优势,探讨数据驱动下安全绩效管理的研究变革,剖析大数据环境下企业安全绩效管理的数据流向,构建数据驱动下安全绩效管理的框架模型,并提出数据驱动下企业安全绩效管理应用对策。结果表明:基于大数据的安全绩效管理有助于提升企业安全管理水平,也为安全生产系统优化提供理论依据。     

数据挖掘在预测组织事故防控效果中的应用*

为进一步探索数据挖据技术在组织事故预防工作中的融入性与适用性,基于24Model构建事故预控基础模型,通过预测准确率数值及接受者操作特性曲线（ROC曲线）对比分析随机森林（RF）、支持向量机(SVM)、决策树（DT）与神经网络（NN）4种方法对组织事故防控效果的预测性能。结果表明:针对事故率控制（Y1）、职业危害预防（Y2）、财产损失3类预测目标（Y3）,RF方法均能达到较高的准确率及稳定性,具有较优的预测性能。根据特征重要度（FI）排序,明确对组织事故水平影响最显著的因素为安全实践活动认知（SC5）及安全管理程序文件（SMS3）,FI值均大于0.150 0。研究结果可为有效预测组织事故防控效果提供方法依据,同时为企业安全工作的规划设计提供思路。     

探究环境监测数据在环境执法中的应用

伴随经济发展的迅速,人们对环境越来越重视,国家也制定了相应的环境执法与保护措施,保障环境质量。在环境执法的过程中,必须严格依照环境监测的数据,从而保障信息的准确性,使环境执法策略的开展能够顺应时代发展,符合目前发展的现状。因此,环境执法中环境监测数据占据重要的位置。基于此,本文分析了环境执法中环境监测数据的应用,笔者根据自身经验提出相应的建议。