Assessing relevance of tweets for risk communication

ABSTRACT

Although Twitter is used for emergency management activities, the relevance of tweets during a hazard event is still open to debate. In this study, six different computational (i.e. Natural Language Processing) and spatiotemporal analytical approaches were implemented to assess the relevance of risk information extracted from tweets obtained during the 2013 Colorado flood event. Primarily, tweets containing information about the flooding events and its impacts were analysed. Examination of the relationships between tweet volume and its content with precipitation amount, damage extent, and official reports revealed that relevant tweets provided information about the event and its impacts rather than any other risk information that public expects to receive via alert messages. However, only 14% of the geo-tagged tweets and only 0.06% of the total fire hose tweets were found to be relevant to the event. By providing insight into the quality of social media data and its usefulness to emergency management activities, this study contributes to the literature on quality of big data. Future research in this area would focus on assessing the reliability of relevant tweets for disaster related situational awareness.     

Bounding Cube:一种无线传感器网络节点三维定位算法

无线传感器网络经常会部署在三维区域内,但目前大部分节点定位方法仅考虑的是二维应用.针对无线传感器网络节点能量有限特点,提出1种三维节点定位算法bounding cube,研究算法的原理和实现方法,并进行仿真分析.仿真结果表明,在100 m×100 m×100 m的三维空间内随机部署400个节点,当已知节点密度>20%,通信半径分别为r=30 m,r=40 m,r=50 m时,相对定位误差均<40%,当已知节点密度>20%、通信半径>30 m时,一次定位比例可以达到100%.该算法的突出特点是方法简单、计算量小.     

Complex behaviour of a coal sample in a large scalein situ compression test

Summary A large scalein situ compression test of a laminated coal cube is described. The cube was uniformly loaded by a system of hydraulic jacks supplied simultaneously from one pump. At the same time both load and deformations were controlled. Deformations were measured by 60 longitudinal gauges located at the side surface of the cube in the regular net. Due to the heterogeneity of the rock the readings showed scatter. As a first approximation, the scattered data were fitted to the plane using the least square method. Orientations of the planes were analysed and show permanent relative movement between adjacent lamina indicating complex behaviour of the cube under loading. Detailed analysis of this behaviour indicated that the cube was subjected to both bending and twisting.     

Test method for single interior right angle in a corner cube prism

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自由落体绝对重力仪中参考棱镜振动测量技术

精确测量绝对重力仪参考棱镜的振动信号并将其用于补偿绝对重力测量值是提高绝对重力仪测量精度的一种解决方案。 对此, 本文介绍了参考棱镜振动测量的原理, 设计了参考棱镜振动加速度测量装置, 推导参考棱镜振动测量装置的传递函数。 研究表明, 可以将测量装置等效为加速度计, 通过成熟的加速度计测量方法, 可获得等效的加速度计传递函数参数, 从而得到测量装置输出电压对参考棱镜振动加速度的传递函数, 该函数能够解算出参考棱镜的振动加速度, 以补偿绝对重力测量值。 在实验室测得的数据与理论数据相符的基础上, 通过在北京国家地球观象台做垂直振动摆的振动实验得出, 实验曲线与理论模型公式刻画的幅频特性曲线重合, 验证了参考棱镜振动测量装置在实际中使用的可靠性。     

地理空间元数据关联网络的构建

利用资源描述框架（RDF）设计地理空间元数据关联模型,根据地理空间元数据之间的语义关系和语义相关度的计算,以构建以元数据为节点、元数据之间的语义关系为边、语义相关度为权重的关联网络。在这一网络中,一个节点是一个地理空间元数据的资源描述图,包含属性特征（数据来源、空间特征、时间特征、内容）及其关系特征（元数据之间的语义关系、语义相关度）。实验及其分析表明,地理空间元数据关联网络可以有效地支持地理空间数据语义关联检索、推荐等应用,这与传统的基于关键词的元数据检索方式相比,具有更高的准确度。     

模糊地理实体不确定性综合描述研究

从二型模糊的角度讨论了模糊地理实体的不确定性,基于空间数据的位置误差,利用模糊集的λ-截集和圆误差带模型推导了模糊地理实体隶属度的误差模型,并给出了隶属度不确定性的度量方法,提出了用隶属度误差立方体来综合描述模糊点的不确定性。     

Visualizing spatiotemporal trajectories of mobile social media users using space–time cube

The implementation of social network applications on mobile platforms has significantly elevated the activity of mobile social networking. Mobile social networking offers a channel for recording an individual’s spatiotemporal behaviors when location-detecting capabilities of devices are enabled. It also facilitates the study of time geography on an individual level, which has previously suffered from a scarcity of georeferenced movement data. In this paper, we report on the use of georeferenced tweets to display and analyze the spatiotemporal patterns of daily user trajectories. For georeferenced tweets having both location information in longitude and latitude values and recorded creation time, we apply a space–time cube approach for visualization. Compared to the traditional methodologies for time geography studies such as the travel diary-based approach, the analytics using social media data present challenges broadly associated with those of Big Data, including the characteristics of high velocity, large volume, and heterogeneity. For this study, a batch processing system has been developed for extracting spatiotemporal information from each tweet and then creating trajectories of each individual mobile Twitter user. Using social media data in time geographic research has the benefits of study area flexibility, continuous observation and non-involvement with contributors. For example, during every 30-minute cycle, we collected tweets created by about 50,000 Twitter users living in a geographic region covering New York City to Washington, DC. Each tweet can indicate the exact location of its creator when the tweet was posted. Thus, the linked tweets show a Twitter users’ movement trajectory in space and time. This study explores using data intensive computing for processing Twitter data to generate spatiotemporal information that can recreate the space–time trajectories of their creators.