基于仿真的交通事故机动车驾驶人识别方法

为正确识别交通事故中的机动车驾驶人,借助仿真软件,提出一种基于仿真的机动车驾驶人识别方法。先根据事故现场痕迹,借助Pc-Crash软件仿真车辆的运动轨迹;再根据Pc-Crash仿真所得速度、位置等信息,借助Madymo软件仿真乘员的运动;然后通过分析车辆运动轨迹、人体损伤和人体最终停止位置等仿真结果确定驾驶人。最后用该方法识别了一例2车侧面碰撞事故中的驾驶人,所得结果与警方调查结果一致。借助仿真方法并充分利用事故现场痕迹,能够识别机动车驾驶人。     

基于改进极端学习机的混沌时间序列瓦斯涌出量预测

为更准确地预测瓦斯涌出量,预防瓦斯灾害,有必要建立和应用基于改进极端学习机(IELM)的混沌时间序列预测模型。首先,对瓦斯涌出量监测数据构成的多变量时间序列进行相空间重构,采用互信息法与虚假邻点法得到每一变量的延迟时间和最佳嵌入维数;然后,通过最小二乘方法和误差反馈原理计算出最优的网络输入层到隐含层的学习参数,对极端学习机(ELM)进行改进;最后,借助IELM建立瓦斯混沌时间序列的预测模型。通过仿真试验,运用该预测模型预测的最大相对误差为3.290 2%,最小相对误差为0.898 2%,平均相对误差为1.952 8%。     

过硫酸铵含铜废液预处理工艺改造

采用离子交换工艺对过硫酸铵含铜废液预处理原有工艺进行改造,改造后降低了废液预处理成本,减少二次污染,提高铜资源的回收率,达到综合利用的目的,具有很高的环境效益及经济效益。     

小波分析在PM10浓度时间序列分析中的应用

以西安市PM10日平均浓度时间序列为例,根据小波分析的基本原理,应用小波分解和重构对PM10浓度时间序列的变化进行了分析,得到PM10的年变化趋势和突变特征。研究结果表明,用小波分析应用于大气污染物浓度时间序列的分析是可行的。     

青南地区城镇污水处理厂综合效率评估分析

青南地区地处青藏高原腹地,是我国多条大江大河发源地,该地区污水处理对下游江河水环境质量改善具有重要意义.对青南地区(玉树、果洛和黄南)污水处理厂的综合效率进行定量评估分析并指出制约其效率提升的因素,对推动该地区污水处理产业的后续发展具有重要意义.因此,本文以青南地区11座城镇污水处理厂为研究对象,利用层次分析法和模糊综...     

中国农村环境问题的法律思考

改革开放以来,随着中国农村经济的快速发展,农村环境问题也日益突出,严重影响了社会主义新农村建设的“生产发展、生活宽裕、乡风文明、村容整洁、管理民主”目标和要求的实现,阻碍了农村乃至全国经济、社会和环境的协调发展。加强农村环境保护,是新农村建设的当务之急,是全面建设小康社会和构建和谐社会的迫切要求。文中在现有研究的基础上,考察农村环境问题之现状,从法律视角,深入分析农村环境的问题之所在,提出解决农村环境问题的对策,努力探寻一条与中国农村实际相适合的生态环境保护道路。     

后重建时代汶川大地震极重灾区旅游发展策略探析

2008年汶川大地震给四川省旅游业发展在短期内造成了极大困难,但也给当地遗留了大量的地震遗存,拥有重要的科学考查、科普教育和纪念价值。后重建时代极重灾区面临的旅游发展问题大同小异,虽然开发了许多新项目,但问题并没有从根本上解决。从当地自然环境禀赋各异、少数民族文化开发程度低、旅游商品外来化严重、旅游安全等方面分析了面临的各种问题,提出了具有针对性的对策和建议。     

适宜性评价视角下的煤矿土地复垦技术措施研究——以白山市道清沟煤矿为例

基于土地适宜性评价方法,着重选取极限值条件法、AHP层次分析法、加权指数和法对白山市道清沟煤矿区的土地适宜类和土地质量等进行系统综合的分析,判定道清沟煤矿待复垦土地的类型、数量和质量。基于土地破坏现状和适宜性评价结果,提出以工程措施为主、生物化学措施为辅助的土地生态重构对策。     

新型汽封在超临界600MW机组的应用

介绍了一种新型汽封在国产600 MW机组节能改造中的应用。改造方案为将汽轮机组原通流部分及轴端的梳齿型汽封改为新型接触式密封齿＋蜂窝汽封＋铁素体齿的组合汽封,改造后漏汽量大幅减少,高、中、低压缸效率和机组运行的经济性明显提高,对同类型汽轮机通流部分节能改造具有较好的借鉴意义。     

Retrospective exposure assessment in a chemical research and development facility

The objective of this exposure assessment was to reconstruct cumulative historical exposures for workers who have been exposed to multiple chemicals and chemical groups to better understand a cluster of brain cancers within a research and development lab. Chemicals of interest, including acrylates, bis-chloromethyl ether (BCME), chloromethyl methyl ether (CMME), isothiazolones and nitrosoamines, were selected on the basis of the plausibility of penetrating the blood-brain barrier and the uniqueness of the chemical's biological activity.In a complicated exposure setting such as a chemical R&D facility, multiple exposure estimation methods were needed. First, similarly exposure groups (SEGs) were created for these materials based on department group, time period of the department's existence and function associated with job titles. A probabilistic framework for assessing exposures was developed using Bayesian analysis of historical monitoring data, mathematical exposure modeling and professional judgments of current and former industrial hygienists at the facility were used to reconstruct the exposure history for acrylates, BCME and CMME for each SEG over the time period of interest. Since sufficient measurement data for isothiazolones and nitrosoamines were not available, the exposure histories for each SEG for these chemicals were estimated. This was done using objective formaldehyde levels and subjective employee interviews. The interviews assessed workplace determinants of exposure as distinct surrogates for estimating inhalation and dermal exposures. The exposure assessments by these methods were compared against each other to estimate the potential for exposure misclassification. A job exposure matrix (JEM) was constructed that contained the exposures obtained from above multiple approaches for each of these chemical groups for each SEG for each year of interest. The combination of methods used in this work is a unique and potentially helpful framework that can be used in analogous workplace settings involving multiple exposures with incomplete objective measurement information.