Applications of sketches in network traffic measurement: A survey

Accurate and timely network traffic measurement is essential for network status monitoring, network fault analysis, network intrusion detection, and network security management. With the rapid development of the network, massive network traffic brings severe challenges to network traffic measurement. However, existing measurement methods suffer from many limitations for effectively recording and accurately analyzing big-volume traffic. Recently, sketches, a family of probabilistic data structures that employ hashing technology for summarizing traffic data, have been widely used to solve these problems. However, current literature still lacks a thorough review on sketch-based traffic measurement methods to offer a comprehensive insight on how to apply sketches for fulfilling various traffic measurement tasks. In this paper, we provide a detailed and comprehensive review on the applications of sketches in network traffic measurement. To this end, we classify the network traffic measurement tasks into four categories based on the target of traffic measurement, namely cardinality estimation, flow size estimation, change anomaly detection, and persistent spreader identification. First, we briefly introduce these four types of traffic measurement tasks and discuss the advantages of applying sketches. Then, we propose a series of requirements with regard to the applications of sketches in network traffic measurement. After that, we perform a fine-grained classification for each sketch-based measurement category according to the technologies applied on sketches. During the review, we evaluate the performance, advantages and disadvantages of current sketch-based traffic measurement methods based on the proposed requirements. Through the thorough review, we gain a number of valuable implications that can guide us to choose and design proper traffic measurement methods based on sketches. We also review a number of general sketches that are highly expected in modern network systems to simultaneously perform multiple traffic measurement tasks and discuss their performance based on the proposed requirements. Finally, through our serious review, we summarize a number of open issues and identify several promising research directions.     

上升气泡内气溶胶沉降机理研究

气溶胶池洗过滤是反应堆严重事故中去除放射性源项的重要手段。本文以严重事故条件下上升气泡中气溶胶的滞留过程为背景，设计搭建了可视化单气泡鼓泡实验装置。通过该装置研究了气溶胶在上升气泡中的沉降效率，并与MELCOR中的气溶胶沉降模型计算结果进行了对比。结果表明，气溶胶沉降效率对气泡尺寸的变化较为敏感，当气体流量大于0.1 L/min时，气泡等效直径迅速增加，相应的气溶胶沉降效率快速降低；与MELCOR模型计算结果的对比表明，两者在总体趋势上呈现出较好的一致性，但计算结果低估了液相对气溶胶的实际去除能力，导致这种偏差的主要原因是气泡在上升过程中存在无规则的晃动以及气液界面的波动。     

Evaluation of the containment vessel failure time from operator’s notifications during a severe accident

This paper aims at clarifying the potential and the limit of the method to surmise the timing of the containment vessel (CV) failure utilizing the Emergency Action Levels (EALs) issued as a nuclear operator’s notification in an early phase of the severe accident (SA). We analyzed the timings of the EALs issued in all kinds of the SA sequences of several PWR plant models by using the SA analysis code, MAAP. We found high correlations between the timing of SE41 (EAL issued at CV pressure of 0.5 design pressure) and the timing of the CV failure in the typical scenarios, e.g. over-pressure failures. We could therefore establish an evaluating method to estimate the time for a CV failure. This method has the potential to support the decision-making in nuclear emergency preparedness.     

Formation of radioactive cesium microparticles originating from the Fukushima Daiichi Nuclear Power Plant accident: characteristics and perspectives

ABSTRACT

Following identification of radioactive Cs microparticles (CsMPs) in aerosol samples from the Fukushima Daiichi Nuclear Power Plant (FDNPP), numerous reports on CsMPs have been published. This paper reviews recent progress in the measurement and characterization of CsMPs by advanced analytical techniques, including advanced transmission electron microscopy (TEM) and synchrotron X-ray analysis. These analyses revealed that the CsMPs contained Si, Fe, Zn, Cs, and minor quantities of U together with some fission products. Uranium in the CsMPs was identified as being in the form of uraninite and (U,Zr)O₂. Detailed advanced TEM analysis has clarified some of the processes resulting in the alteration of constituents of the nuclear fuels and containment vessel materials during this severe accident. In addition, a detailed report on the elemental compositions and structures of the fuel debris fragments collected inside and outside of the primary containment vessel²⁵ highlighted the fact that the fuel debris fragments contained nanoparticles with the U and Zr components having similar structures to that of the CsMPs. This similarity in structures has stimulated further research on the structure and elemental constituents, especially for U and Zr in the CsMPs, and has opened up new avenues for studying the chemical characteristics of the fuel debris.     

An unsafe behaviour formation mechanism based on risk perception

It is commonly acknowledged that human behaviour is implicated in most safety problems. However, research on the formation mechanism of unsafe behaviour remains incomplete. Risk perception is one of the fundamental issues in risk research, and individual risk perception can be identified as a critical antecedent of human behaviour. This study attempts to construct and test a theoretical model to reveal the formation mechanism of unsafe behaviour based on risk perception. First, to lay a solid foundation for the developed new mechanism, several key concepts about risk perception and unsafe behaviour were explained. Second, the formation mechanism of biases in individual risk perception was developed based on psychological distance theory, and the biases in risk perception were subsequently classified. Lastly, an unsafe behaviour formation mechanism was put forward based on risk perception as an explanatory variable. This study is novel in that it uses psychological distance to explore the formation of biases in individual risk perception. Further, the presented work provides a new approach to understanding and explaining the formation mechanism of human unsafe behaviour.     

基于高斯混合隐马尔科夫模型与人工神经网络的紧急换道行为预测方法

为了有效降低因驾驶员紧急换道行为而诱发的交通事故，提高道路交通事故链阻断效率，提出一种基于高斯混合隐马尔科夫模型（GMM-HMM）和人工神经网络（ANN）的紧急换道行为预测方法。首先利用GMM-HMM对车辆行驶状态以及驾驶行为连续观察序列进行换道意图辨识，采用ANN预测下一时段的驾驶行为，再预测换道过程中的横向加速度变化率，从而判断紧急换道的危险程度。驾驶员在环仿真实验及实车实验结果表明，该方法预测避险成功率达92.83%，实验避险成功率达90.32%。该方法能有效地对紧急换道行为进行提前警告与干预。     

基于LSTM-RF模型的城市道路交通流预测

交通流预测作为信号协调和出行时间预测等任务的基础,成为了交通领域的研究点。对于交通流预测问题,研究人员提出了多种方法,但这些方法大多只使用交通流数据的时域信息进行交通流预测,忽略了空间相关性对于预测目标路段流的影响,导致预测精度不理想。基于组合模型的思想提出了一种称为LSTM-RF的交通流预测模型。在交通流预测过程中,首先使用LSTM模型提取预测目标路段的时序特征,再将其预测值与采集的相邻上下游路段信息同时作为随机森林模型的输入特征,进行交通流时空相关性分析,获得最终的预测结果。并通过贵阳市车牌识别系统采集的城区132条路段的交通流数据进行实验验证。结果表明:该方法在预测精度上优于单一模型,并且预测误差相比单一模型有明显减少。     

智能化救援监控系统在煤矿安全生产中的应用

针对煤矿发生事故后传统救援监控系统无法实时对井下人员进行动态定位，导致矿井救援盲目性大、救援效率差、救援难度大等技术难题，为了进一步提高煤矿救援效率，通过技术研究，设计了一套以通信基站为核心的智能化救援监控系统，分析了该系统结构组成、工作原理，通过在担水沟煤矿井下实际应用效果来看，智能化救援监控系统对人员定位精准度达95%，实现人员动态位置三维成像，救援效率提高至80%以上，有效缩短了煤矿事故救援时间，取得了显著应用成效。     

Profiling drunk driving recidivists in Denmark

Drunk drivers are a menace to themselves and to other road users, as drunk driving significantly increases the risk of involvement in road accidents and the probability of severe or fatal injuries. Although injuries and fatalities related to road accidents have decreased in recent decades, the prevalence of drunk driving among drivers killed in road accidents has remained stable, at around 25% or more during the past 10 years. Understanding drunk driving, and in particular, recidivism, is essential for designing effective countermeasures, and accordingly, the present study aims at identifying the differences between non-drunk drivers, drunk driving non-recidivists and drunk driving recidivists with respect to their demographic and socio-economic characteristics, road accident involvement and other traffic and non-traffic-related law violations. This study is based on register-data from Statistics Denmark and includes information from 2008 to 2012 for the entire population, aged 18 or older, of Denmark. The results from univariate and multivariate statistical analyses reveal a five year prevalence of 17% for drunk driving recidivism, and a significant relation between recidivism and the drunk drivers’ gender, age, income, education, receipt of an early retirement pension, household type, and residential area. Moreover, recidivists are found to have a higher involvement in alcohol-related road accidents, as well as other traffic and, in particular, non-traffic-related offences. These findings indicate that drunk driving recidivism is more likely to occur among persons who are in situations of socio-economic disadvantage and marginalisation. Thus, to increase their effectiveness, preventive measures aiming to reduce drunk driving should also address issues related to the general life situations of the drunk driving recidivists that contribute to an increased risk of drunk driving recidivism.     

Engineering accidents in society: A comparison of Chinese and American railway accident investigation

Based on the investigation reports for two major railway accidents in China and the USA, as well as the analysis of related systems, this paper compares the differences between Chinese and American railway accident investigation modes along different dimensions. The four aspects attended to are the investigation purpose, institutional basis, scope and process, and type of conclusion. The results reveal the role of social factors in shaping the investigation pattern of engineering accidents, and show engineering accidents can serve as a window to understanding a society and the ways that learning from engineering accidents is a socially institutionalized process. A final discussion considers possible improvements that might be introduced into the Chinese mode of engineering accident investigation.