极端气候事件对膨胀土路基水毁影响的研究

定性地分析了极端气候事件对膨胀土路基水毁的影响,指出日降雨极值和干旱持续时间是影响膨胀土路基水毁的极端气候事件.定量地计算了不同重现期的日降雨极值和不同干旱级别的干旱持续时间对膨胀土路基水毁的影响.     

上海公交车辆安全行驶特征分析

上海市历来重视公共交通服务安全保障,为能进一步掌握公共交通安全情况,本文以公交车辆行驶违章情况为抓手,以大数据分析为技术手段,探究违章行为分类,剖析违章发生的时空特征及其与天气的相关性,并结合典型数据分析违章原因,为规范驾驶行为、改善驾驶环境、提升公交车辆安全行驶水平提供必要支撑。     

面向列控系统安全软件黑盒测试的 危险分析方法

针对高速铁路列控系统安全软件黑盒测试中对危险事件的可测性、全面性和优先性的需求,研究能够生成有效危险事件测试集的危险分析方法。根据列控系统接口交互信息的类型及特点,改进HAZOP的引导词及节点参数并进行接口危险辨识;然后利用风险矩阵评估接口危险事件的风险等级,提出面向安全软件黑盒测试的接口危险分析方法—HAZOP-I;将该方法应用到CTCS-3级列车运行控制系统运行场景中。研究结果表明:该方法能够为列控系统安全软件黑盒测试提供满足需求的危险事件测试集。     

大风浪中船舶抗风浪航法浅议

本文通过分析大风浪天气对船舶航行安全的影响，探讨了避航、锚泊避风、迎风行驶、顺风行驶等航法，以及在大风浪中掉头的方法。     

定量分析雷达回波——雾天中的船舶驾驶

文章利用数学、物理中行程问题等理论,通过特定的雷达指标,把目标回波相对观察船的移动速动和方向进行描述,测定来船速度和方向,经简化,确定来船动态,实现船舶在能见度不良在航时安全选择航路及其避让的目的。     

寒地城市地铁客流特性及网络失效研究

为分析寒地城市地铁客流与网络特性，挖掘客流与寒地气候的相关性，本文利用《寒区城市多模式公交协同运营技术与示范工程》2013—2020 年共 8 年 11 万余条地铁客流数据进行研究。提出效用阻抗Space L-Space P模型建立地铁抽象网络，将时间维度细分为周、月和年这3类， 研究地铁客流特性与扰动因素，并建立寒地城市地铁网络失效模型，分析扰动后地铁站点与线路的客流分布。进一步选取哈尔滨市与南京市地铁数据，运用转移熵因果关系分析地铁网络客流分布与气候的相关性，得到寒地气候对地铁客流的影响。研究表明：所采集的地铁客流数据能够充分展现客流的状态与变化趋势，能够满足客流数据分析的精度与质量要求。近8年，哈尔滨市地铁客流呈现明显的增长趋势，地铁客流分布呈现2月为客流低峰，3月客流逐步回升，3~12月客 流较平稳且具有轻微波幅；换乘客流中夏季呈现8月大于7月大于6月的趋势，冬季则2月换乘客流最低，大多在周一与周五达到周换乘客流量极值。由地铁网络失效模型识别出关键站点，得到 哈尔滨市冬季客流略高于其余3季，冬季地铁网络较脆弱，结合实际数据的模拟分析表明，温度与地铁客流具有一定相关性，且哈尔滨市的相关性大于南京市。     

基于嵌入式服务器的多模航行信息接收系统设计

文章设计了一种基于嵌入式服务器的多模航行信息接收系统,具有自动接收船舶识别信息、航行告警信息和气象传真信息的功能,同时具备了通过多功能显示器和热敏打印装置进行集中显示和图像打印的功能。文中给出了系统硬件组态及相应软件设计流程,测试和试用结果显示系统具有极高可靠性和实用性,具有很大的市场推广价值。     

Regulation and Approval of Drugs and Pesticides Used in Canadian Salmon Culture

When Canadian salmon farmers find the health of their stock is compromised by infection or disease, the use of drugs or pesticides can be required. In Canada, there is a very limited range of these chemicals legally available to farmers and veterinarians. The formal approval and registration process for these chemotherapeutants is complicated. It involves the overlap of a variety of government departments, depending on the method of application of the therapeutic compound. These formal channels, through which chemotherapeutic products, specifically drugs and pesticides, are licensed for use, are both lengthy and costly to navigate. Often, these costs exceed any potential returns from the sale of the products (OCAD, 2001; Harper, 2002). Consequently, unapproved drugs, which would not normally be available for use, are obtained through alternative channels, which may pose a number of environmental, human, and animal safety concerns. This article seeks to provide a better understanding of the approval process and regulations governing drugs and pesticides and how they are made available for use in Canadian salmon culture.     

Cluster-based correlation of severe driving events with time and location

In this article, a systematic strategy is proposed to identify severe driving events occurrence correlation with time and location. The proposed approach, which is constructed based on batch clustering and real-time clustering techniques, incorporates historical and real-time data to predict the time and location of severe driving events. Batch clustering is implemented with the combination of subtractive clustering and fuzzy c-means clustering to generate clusters representing the initial correlation patterns. Real-time clustering is then developed to create and update real-time correlation patterns on the foundation of the batch clustering using the evolving Gustafson–Kessel like (eGKL) algorithm. In both clustering processes, the correlation of the events within time domain is identified first, and then two different levels of accurate correlations are conducted for the location domain. Real-time data of operating vehicles each equipped with a data acquisition and wireless communication platform are used to validate the proposed strategy. Batch clustering results reveal the severe braking events distribution and concentration at daytime and nighttime. Real-time clustering provides and updates the variation of the correlations/intercorrelation of different regions. Drivers can be notified of the potential severe driving locations through maps showing the driving routes. Through the variation of the correlations, drivers can recognize the events occurrence at different times and locations. The generated time series can be potentially used to develop spatial-time models for regions to model and forecast the events occurrence.     

The Arctic Shipping and Environmental Management Agreement: A Regime for Marine Pollution

Climate change is predicted to have particularly challenging impacts throughout the Arctic. For instance, there is a great probability of sea ice melting, leading to increased vessel traffic and oil pollution. Eight major nation-states have vested concerns in the potential opening of Arctic sea routes. They each have pledged to take protective action through the Arctic Council. However, there is still a need to develop an international institution to simultaneously address Arctic marine pollution and protect the needs of these states. This article seeks to design a legally binding regime for oil pollution control in the Arctic. In creating this new regime, we shall utilize several shared design elements of historically effective international regimes and take advantage of the legal innovations of these agreements. Our new regime, entitled the Arctic Shipping and Environmental Management Agreement (ASEMA), will take into account both the economic and environmental interests of the parties involved.