新冠肺炎交通防控政策对长沙市人口流动的影响

为探究新冠肺炎疫情下交通防控政策对长沙市人口流动的影响，本文根据长沙市在新冠 肺炎疫情期间颁布的交通防控政策和疫情实时防控情况划分防控阶段，基于百度迁徙大数据，利 用双重差分模型，识别长沙市不同阶段的交通防控政策以及量化防控效果，分析交通防控政策对 长沙市人口流动的影响。结果显示，长沙市在交通管制阶段，平均人口迁出强度、平均人口迁入 强度及城市内部出行强度分别下降了83.68%、69.24%及59.74%，有效地控制了人口流动，降低了 疫情扩散危险。在交通恢复阶段，长沙市人口流动强度逐渐反弹，城市内部出行强度基本恢复到 2019年同期水平。本文研究结果显示了交通管制对疫情扩散限制的有效性，为常态化疫情防控 下精准防控政策和复工复产政策制定提供参考。     

一种激光测距装置的设计与实现

针对目前舰船横向航行补给时两舰距离测量方法,通过激光测距技术研究,设计了一种船用激光测距装置.详细介绍了其工作原理、结构设计和软件设计,并对其传感器信号融合处理关键技术进行了攻关与验证,解决了距离索测量时无法连续自动提供距离及其变化速率信息的问题,为舰船航行补给和靠离码头安全操纵提供保障.     

Toward using social media to support ridesharing services: challenges and opportunities

Ridesharing has been attracting increasing attention from both academia and industry. One of the challenges posed by the study of ridesharing is to identify the most valuable information for improving the ridesharing decisions taken by participants. Another challenge is to use harvesting techniques to extract specific types of travel-related information. Many methods have been developed by the community in order to solve these issues. However, due to a lack of information sharing between different transit authorities and the difficulty of identifying subjective perceptions of the experience of ridesharing, understanding and evaluating how social media data might support or obstruct goals for mobility, safety and environmental sustainability in ridesharing is a difficult task. In this survey, we first analyze the literature on ridesharing with a focus on the properties and model of service, and introduce a framework to describe the major components required for a ridesharing service. Then, we illustrate the potential value of information extracted from social media and present the rationale for harvesting travel-related data. Finally, we detail some possible directions and different approaches for using social media data, and highlight their assets and drawbacks.     

大型船舶钨极氩弧重熔工艺应用

疲劳破坏是船体结构的主要破坏形式之一。改进结构节点的设计和施工工艺,可保证船体结构中受交变载荷作用的构件有足够的疲劳寿命。钨极氩弧(Tungsten Inert Gas, TIG)重熔是改善结构节点焊后疲劳强度的有效方法。与目前船上常用的几种改善疲劳强度的方法进行分析对比,对TIG重熔工艺的重要性进行充分论证,获得实施TIG重熔工艺的技术标准和操作要点。TIG重熔工艺不仅改善结构节点疲劳强度,而且为建造具有较长疲劳寿命的大型船舶找到一个行之有效的方法,可产生良好的经济和社会效益。     

联合极值分布在码头顶高程计算中的应用

介绍国际工程中常用的码头顶高程计算方法和二维极值分布，指出码头顶高程计算中主要考虑的变量是波高和水位。以几内亚铝矾土出口码头项目为例，提出波峰面高度重现期的概念。采用极值分布理论对水位和波高分别进行拟合，选择了合适的水位和波高联合极值分布模型。从案例计算结果对比分析发现，引入波峰面高度重现期的概念，采用水位和波高联合极值分布所计算的码头顶高程比采用二者单独一维极值分布计算的码头顶高程低。在波浪较小区域，该计算结论对EPC承包商控制成本、提高履约能力有积极作用。     

基于量表型选择集的出行信息需求有序选择模型

研究了城市出行者日常活动和出行所需要的关键信息, 提出了一种针对量表数据的量化分析方法; 以出行者信息需求为研究对象, 设计了一项基于李克特5级量表的问卷调查; 总结了出行个体对各类出行信息需求程度的排名, 分别构建并标定了驾车线路、目的地位置和实时路况信息需求的有序选择模型; 与多项Logit模型在参数显著度、赤池信息量准则和对数似然函数值等指标上进行对比, 以验证有序选择模型的有效性, 并对影响信息需求的关键变量进行了局部效应分析。研究结果表明: 出行者在通勤出行前最需要公交运营变更信息, 而在通勤出行中最需要实时路况信息; 非通勤出行者最关注目的地位置信息, 在出发前和途中对目的地位置信息的需求概率较通勤出行前分别高出31.08%和29.25%;在职人员对信息的需求程度普遍高于学生和自由职业者, 说明时间价值高的人群更期望通过全面及时的信息获取来合理安排出行; 女性比男性对实时路况信息的需求概率高出10.23%, 说明女性对延误的风险规避意识更强; 20~40岁的人群出行信息需求最强烈, 随着年龄的增长该需求将逐渐下降; 各年龄段对实时路况信息都表现出了较高的需求, 说明人们对于有可能带来负面影响的信息更为敏感。可见, 采用有序选择模型能够精确分析量表型选择集。      

考虑洪水漫延过程的地铁车站人员疏散研究

提出一种基于元胞自动机同时分析洪水漫延和人员疏散的新方法,以此研究洪水漫延对行人疏散过程的动态影响.基于元胞自动机原理,利用元胞及其周围相邻元胞上一个时间步长的相关状态变量进行水量转移计算,结合洪水漫延对行人的移动速度和运动方向的影响,建立洪水漫延下人员疏散的分析模型,通过数值仿真研究洪水漫延和人员疏散的动力过程.详细分析不同进水口位置和进水流量对地铁车站应急疏散效率的影响.研究结果表明:有洪水时人员疏散的效率显著低于无洪水的情况;进水流量的增加会导致人员疏散效率降低;进水口位置的不同也会对人员疏散的效率造成很大的影响.     

Time-series analysis of remote-sensed chlorophyll and environmental factors in the Santa Monica–San Pedro Basin off Southern California

The time-series of remote-sensed surface chlorophyll concentration measured by SeaWiFS radiometer from September 1997 to December 2001 and the relevant hydrological and meteorological factors (remote-sensed sea surface temperature, atmospheric precipitation, air temperature and wind stress) in Santa Monica Bay and adjacent waters off southern California were analyzed using wavelet and cross-correlation statistical methods. All parameters exhibited evident seasonal patterns of variation. Wavelet analysis revealed salient long-term variations most evident in air temperature during El Niño 1997–1998 and in wind stress during La Niña 1998–1999. Short-period (<100 days) variations of remote-sensed chlorophyll biomass were mostly typical to spring seasons. Chlorophyll biomass was significantly correlated with air temperature and wind stress: an increase of chlorophyll biomass followed with 5–6-day time lag an increase of wind stress accompanied by a simultaneous decrease of air temperature. The mechanism of these variations was an intensification of phytoplankton growth resulting from the mixing of water column by wind stress and entrainment of nutrients into the euphotic layer.