面向Web的环境信息系统设计与实现

从开发的角度阐述了解决降低环境空间数据采集成本、提高环境信息的共享程度和范围的最佳途径，即通过建立面向Web的环境信息系统（Web-EIS），使不同部门、不同地区、不同领域之间直接进行信息共享和综合应用。对Web-EIS的构架、设计和实现方法进行了详细的分析，并以利用Java编程语言的方法开发出面向Web的武汉市城市环境地理信息系统为例介绍了其功能特点，很好地实现了Web-EIS。     

处置突发事件通信电台终端数据传输软件设计

为确保处置抢险救灾、应急救援等突发性事件通信联络畅通，本文采用模块设计思想，结合32位ARM7TDMI（-S）（Advanced RISC Machines）单片机，完成了一种不同频率无线通信电台间串行数据信息交换控制的软件系统设计。实现了数据信息自动存储转发和最佳传输信道选择，接收端直接打印输出，可提高通信效率5-6倍。     

不确定数据条件下的生命周期评价及其应用

针对产品生命周期评价中普遍存在着的不确定性数据问题，提出基于概率统计的方法，进行生命周期评价以及重要环境影响清单参数的识别与灵敏度分析。结合水源中央空调系统，建立了统计平均意义下的污染排放清单，运用MonteCarlo模拟获得了以均值219．746和方差9．4243所表征的空调机系统生命周期环境影响的概率分布。进一步通过K—S检验与灵敏度分析，识别出10个具有重要环境影响贡献的清单参数及其中4个对环境影响分布较敏感的参数。以概率分布代替固定数值可以反映产品环境绩效的统计信息，能够有效地用于不确定数据条件下的产品生命周期评价。     

水质远程监控通讯安全性问题的探讨——利用现有网络条件确保远程监控通讯安全性的解决方案

针对我国总体水质情况不容乐观的现实 ,提出解决办法之一是对排污口实施大规模远程监控 ,而远程通讯的安全性又是最直接、最核心的问题。文章着重阐述了如何解决在现有网络条件下实时运行的网络运行速度和数据的加解密等具体问题。     

合肥台测震CTS-1系统处理软件

主要介绍了地震数据断记报警软件及其相关地震数据分类处理软件,此软件一方面保证了地震监测数据的连续性,另一方面使科研人员查询地震事件波形,迅速快捷,并可对典型地震事件和震相特征进行查看,提高对一些特殊地震震相的识别,从而也提高了地震的分析水平.     

Effect of clay and organic matter type on the ecotoxicity of zinc and cadmium to the potworm Enchytraeus albidus

Clay and organic matter are considered as important parameters influencing bioavailability and ecotoxicity of metals in soils. As there exists a large variation in the type of clay and organic matter in field soils, the quantity of these variables alone may not be good indicators of metal bioavailability. To test this hypothesis, toxicity experiments with the potworm Enchytraeus albidus were conducted in artificial soils with three types of clay and seven types of organic matter, while the soil pH was kept constant. The 14d LC₅₀ of zinc and cadmium varied from 83.0 to 1140 mg Zn/kg D.W. and from 55.2 to 704 mg Cd/kg D.W., respectively, depending on the type of clay and organic matter that were used. Simultaneous measurements of the cation exchange capacity showed that this soil parameter is a better indicator of the bioavailability as it takes into account the type of clay and organic matter as well as other adsorption phases such as metal oxyhydroxides.     

Modeling drivers’ reaction when being tailgated: A Random Forests Method

Background: Tailgating is a common aggressive driving behavior that has been identified as one of the leading causes of rear-end crashes. Previous studies have explored the behavior of tailgating drivers and have reported effective solutions to decrease the amount or prevalence of tailgating. This paper tries to fill the research gap by focusing on understanding highway tailgating scenarios and examining the leading vehicles’ reaction using existing naturalistic driving data. Method: A total of 1,255 tailgating events were identified by using the one-second time headway threshold criterion. Four types of reactions from the leading vehicles were identified, including changing lanes, slowing down, speeding up, and making no response. A Random Forests algorithm was employed in this study to predict the leading vehicle’s reaction based on corresponding factors including driver, vehicle, and environmental variables. Results: The analysis of the tailgating scenarios and associated factors showed that male drivers were more frequently involved in tailgating events than female drivers and that tailgating was more prevalent under sunny weather and in daytime conditions. Changing lanes was the most prevalent reaction from the leading vehicle during tailgating, which accounted for more than half of the total events. The results of Random Forests showed that mean time headway, duration of tailgating, and minimum time headway were three main factors, which had the greatest impact on the leading vehicle drivers’ reaction. It was found that in 95% of the events, leading vehicles would change lanes when being tailgated for two minutes or longer. Practical Applications: Results of this study can help to better understand the behavior and decision making of drivers. This understanding can be used in designing countermeasures or assistance systems to reduce tailgating behavior and related negative safety consequences.     

面向通风智能化的风速传感器结构化数据降噪方法对比*

为实现风网实时解算、系统优化调节等关键技术,需要去除监测数据噪声,得到结构清晰、纯度较高的通风数据。利用FCM,Rloess和S-G等平滑降噪算法对300组实测风速数据进行分析处理。结果表明:FCM算法处理过程变量引起噪声较为优越,但需提前给定分类数目;窗宽参数选7时,Rloess算法去除由状态变量引起的风速异常数据最优;在窗宽选5、次数为2时,S-G算法降噪和保持数据特性最佳;结合使用FCM-Rloess或FCM-SG算法可有效处理过程变量和状态变量引起的风速异常数据。研究结果可为矿井通风的异常诊断、灾变识别等研究提供合理的基础数据。     

Analysis of the severity of vehicle-bicycle crashes with data mining techniques

Introduction: Although cycling is increasingly being promoted for transportation, the safety concern of bicyclists is one of the major impediments to their adoption. A thorough investigation on the contributing factors to fatalities and injuries involving bicyclist. Method: This paper designs an integrated data mining framework to determine the significant factors that contribute to the severity of vehicle-bicycle crashes based on the crash dataset of Victorian, Australia (2013–2018). The framework integrates imbalanced data resampling, learning-based feature extraction with gradient boosting algorithm and marginal effect analysis. The top 10 significant predictors of the severity of vehicle-bicycle crashes are extracted, which gives an area under ROC curve (AUC) value of 0.8236 and computing time as 37.8 s. Results: The findings provide insights for understanding and developing countermeasures or policy initiatives to reduce severe vehicle-bicycle crashes.     

多环芳烃在中国两种典型土壤中的吸附和解吸行为研究

采用批量实验的方法,研究了多环芳烃类有机化合物萘和菲在两种中国典型土壤样品(草甸土和黑土)中的吸附和解吸行为,并用一种新型解吸模型--"双元平衡解吸(DED)模型"对解吸行为进行了预测.结果表明,萘和菲在两种土壤中的吸附符合传统的线性模型,解吸行为则表现出明显的滞后现象,且DED模型的预测值与实验结果相吻合.DED模型能够利用简单的理化参数更加准确地定量描述憎水性有机污染物的解吸行为,该模型可为我国的土壤风险评价和土壤环境质量标准的制定等工作提供量化手段.