湖南省环境统计数据综合分析现状及改善建议

环境统计是环境保护工作的基础,环境统计数据的综合分析是环境形势判断和决策的一个重要前提条件。随着环境管理和经济管理工作的深入发展,环境统计指标和统计范围不断扩大,做好环境统计年报工作和污染物排放的综合分析评价工作,对完成好各项环境保护目标,对污染减排核查核算提供基础数据支持具有重要意义。     

The USGS Water Availability and Use Science Program: Needs,Establishment, and Goals of a Water Census

Many reports have recognized the need for a national water census for the United States and have called upon the U.S. Geological Survey to undertake this challenge. For example, the National Science and Technology Council stated: “The United States has a strong need for an ongoing census of water that describes the status of our Nation's water resource at any point in time and identifies trends over time.” Responding to the need for this information, the U.S. Congress established the SECURE Water Act. The directives are to provide a more accurate assessment of the status of the water resources of the United States; determine the quantity of water available for beneficial uses; identify long‐term trends in water availability; assist in determination of the quality of the water resources; and develop the basis for an improved ability to forecast the availability of water for future economic, energy production, and environmental uses. This article provides summary and new information on the process and progress on work to estimate water budget components nationwide, involvement of stakeholder interests, efforts to examine water‐use characteristics throughout the Nation, studies of water availability in geographically focused areas and the initiation of methods to provide open access to existing and new water resources information contributing to Open Water Data Initiative (OWDI) efforts and objectives.     

“互联网+”时代的环境风险评估探讨

环境风险评估是环境管理的前提和依据。目前比较成熟的方法分为项目"事先"环评和健康"事后"风险评估。以上两种风险评估方法由于多种原因制约,无法提供给环境管理部门实时在线的环境风险结果。实际上,环境风险评估方法在不断完善中,随着互联网、物联网、云计算、三网融合等IT与通信技术的迅猛发展,环境保护领域也迎来了大数据时代,风险评估也将逐渐步入"互联网+"时代。新型环境风险评估更具系统性,将以数字化的形式体现环境(E)—污染物(M)—人为因素(H)的风险耦合度。虽然数字化环境风险评估在相关风险因子和风险评估方法上仍处于起步阶段,但它是新形势下环境风险管理的一个全新方向,其应用将对环境管理领域产生巨大影响。本文将分析传统环境风险评估与"互联网+"时代的环境风险评估差异,探讨新型数字化环境风险评估需要的支撑硬件与平台,并对数字化环境风险评估的发展趋势与挑战做出展望。     

北京和上海居民旧衣物回收再利用体系建设初探

北京和上海在迈向国际化大都市进程中，随着人口的迅速增长，生活垃圾产生量与日俱增，垃圾减量从源头做起。旧衣物作为可回收、可再利用资源，现有的垃圾分类标准和回收箱的设置，不利于旧衣物的回收和再利用。目前，北京和上海在政府的支持和推动下，设专项开展旧衣物回收试点工作，已取得良好的效果。未来，如何使北京和上海旧衣物回收再利用成为一种常态，仍需政府的支持和全社会的共同参与。     

民族八省区城镇化发展质量研究

本文以2007-2014年民族八省区的相关社会经济统计数据为样本,基于柯布—道格拉斯的生产函数理论,将民族八省区的城镇化发展过程概括为各类资源要素投入进而得到相应产出的过程,运用数据包络分析方法,计算民族八省区城镇化发展质量的评价指数,进一步分析民族八省区城镇化发展质量水平。研究结果显示:民族八省区的城镇化发展质量评价指数区域间差异性显著,在时间序列上大部分省区呈现不同程度的下降趋势,云南、广西和贵州主要受资本和资源要素过度投入影响,近年来城镇化发展质量评价指数逐年下降;新疆和宁夏两省区主要受第二三产业从业人口外流影响,导致第二三产业地区生产总值增长缓慢,城镇化发展质量指数呈一定的下降趋势;通过优化路径分析,民族八省区城镇化发展的投入要素优化存在巨大空间。     

Fatal crash between a car operating with automated control systems and a tractor-semitrailer truck

Abstract

Objective: The objective of this investigation was to evaluate the interaction between an SAE level 2 automated vehicle and the driver, including the limitations imposed by the vehicle on the driver.

Methods: A case study of the first fatal crash involving a vehicle operating with an automated control system was performed using scene evidence, vehicle damage, and recorded data available from the vehicle, and information from both drivers, including experience, phone records, computer systems, and medical information, was reviewed.

Results: System performance data downloaded from the car indicated that the driver was operating it using the Traffic-Aware Cruise Control and Autosteer lane-keeping systems, which are automated vehicle control systems within Tesla’s Autopilot suite. As the car crested the hill, a tractor trailer began its left turn onto a crossing roadway. Although reconstruction of the crash determined that there was sufficient sight distance for both drivers to see each other and take action, neither responded to the circumstances leading to the collision. Further, based on the speeds of the vehicles and simulations of the truck’s path, the car driver had at least 10.4?s to detect the truck and take evasive action. Neither the car driver nor the Autopilot system changed the vehicle’s velocity.

?At the time of the crash, the system performance data indicated that the last driver interaction with the system was 1?min 51?s prior when the cruise control speed was set to 74?mph. The driver was operating the vehicle using the Autopilot system for 37 of the 41?min in the last trip. During this period, the vehicle detected the driver’s hands on the steering wheel for a total of 25?s; each time his hands were detected on the wheel was preceded by a visual alert or auditory warning.

Conclusions: The National Transportation Safety Board (NTSB) determined that the probable cause of the Williston, Florida, crash was the truck driver’s failure to yield the right of way to the car, combined with the car driver’s inattention due to overreliance on vehicle automation, which resulted in the car driver’s lack of reaction to the presence of the truck. Contributing to the car driver’s overreliance on the vehicle automation was the car’s operational design, which permitted the driver’s prolonged disengagement from the driving task and his use of the automation in ways inconsistent with guidance and warnings from the manufacturer.     

基于Multi-class SVM的车辆换道行为识别模型研究

自动安全换道是车辆实现无人驾驶的关键,为精确识别行驶车辆换道状态,保证行车安全,设计了一种基于多分类支持向量机(Multi-class Support Vector Machine,Multiclass SVM)的车辆换道识别模型。从NGSIM数据集中选取美国101公路车辆轨迹数据进行分类处理,并将车辆换道过程划分为车辆跟驰阶段、车辆换道准备阶段和车辆换道执行阶段。采用网格搜索结合粒子群优化算法(Grid Search-PSO)对SVM模型中惩罚参数C和核参数g进行寻优标定,利用多分类支持向量机换道识别模型对样本数据进行训练和测试,模型测试精度达97.68%。研究表明,模型能够很好地识别车辆在换道过程中的行为状态,为车辆换道阶段的研究提供支持。     

交通事故现场警务取证区块化溯源分析方法*

为突破以现场为中心的取证模式，研究基于交通事故过程导向的交通事故现场警务取证系统化方法，以审判为中心理念重构警务取证的新模式，应用区块链溯源方法的思想与技术，提出警务取证区块化溯源分析方法。结果表明:交通事故现场警务取证，应当以交通事故认定的交通事故构成的“七何”要件为证明标准；警务取证包括交通事故全过程的道路交通系统、交通事故现场、交通事故事实3个区块节点；取证具体涉及交通安全风险控制系统的8个系统要素，现场系统的7个系统要素，以及交通事故元素的2个事实要素。该方法的双向溯源技术可确保警务取证的成效，有效提升取证执法效能。     

Estimating Root Zone Soil Moisture at Continental Scale Using Neural Networks

This study investigates the feasibility of artificial neural networks (ANNs) to retrieve root zone soil moisture (RZSM) at the depths of 20 cm (SM20) and 50 cm (SM50) at a continental scale, using surface information. To train the ANNs to capture interactions between land surface and various climatic patterns, data of 557 stations over the continental United States were collected. A sensitivity analysis revealed that the ANNs were able to identify input variables that directly affect the water and energy balance in root zone. The data important for RZSM retrieval in a large area included soil texture, surface soil moisture, and the cumulative values of air temperature, surface soil temperature, rainfall, and snowfall. The results showed that the ANNs had high skill in retrieving SM20 with a correlation coefficient above 0.7 in most cases, but were less effective at estimating SM50. The comparison of the ANNs showed that using soil texture data improved the model performance, especially for the estimation of SM50. It was demonstrated that the ANNs had high flexibility for applications in different climatic regions. The method was used to generate RZSM in North America using Soil Moisture and Ocean Salinity (SMOS) soil moisture data, and achieved a spatial soil moisture pattern comparable to that of Global Land Data Assimilation System Noah model with comparable performance to the SMOS surface soil moisture retrievals. The models can be efficient alternatives to assimilate remote sensing soil moisture data for shallow RZSM retrieval.