地震前兆资料减灾信息的综合开发

近一、二十年建立起来的地震前兆观测台网,不仅为地震预测预报提供了大量科学数据,而且蕴藏着丰富的减灾信息,有待我们去开发。综合观测、综合分析和综合预报是防灾减灾的必由之路。     

Importance of timely metadata curation to the global surveillance of genetic diversity

Genetic diversity within species represents a fundamental yet underappreciated level of biodiversity. Because genetic diversity can indicate species resilience to changing climate, its measurement is relevant to many national and global conservation policy targets. Many studies produce large amounts of genome-scale genetic diversity data for wild populations, but most (87%) do not include the associated spatial and temporal metadata necessary for them to be reused in monitoring programs or for acknowledging the sovereignty of nations or Indigenous peoples. We undertook a distributed datathon to quantify the availability of these missing metadata and to test the hypothesis that their availability decays with time. We also worked to remediate missing metadata by extracting them from associated published papers, online repositories, and direct communication with authors. Starting with 848 candidate genomic data sets (reduced representation and whole genome) from the International Nucleotide Sequence Database Collaboration, we determined that 561 contained mostly samples from wild populations. We successfully restored spatiotemporal metadata for 78% of these 561 data sets (n = 440 data sets with data on 45,105 individuals from 762 species in 17 phyla). Examining papers and online repositories was much more fruitful than contacting 351 authors, who replied to our email requests 45% of the time. Overall, 23% of our email queries to authors unearthed useful metadata. The probability of retrieving spatiotemporal metadata declined significantly as age of the data set increased. There was a 13.5% yearly decrease in metadata associated with published papers or online repositories and up to a 22% yearly decrease in metadata that were only available from authors. This rapid decay in metadata availability, mirrored in studies of other types of biological data, should motivate swift updates to data-sharing policies and researcher practices to ensure that the valuable context provided by metadata is not lost to conservation science forever.     

Radarsat observations and forecasting of oil slick trajectory movements

RADARSAT data have a potential role for coastal pollution monitoring. This study presents a new approach to detect and forecast oil slick trajectory movements. The oil slick trajectory movements is based on the tidal current effects and Fay‘s algorithm for oil slick spreading mechanisms. The oil spill trajectory model contains the integration between Doppler frequency shift model and Lagrangian model. Doppler frequency shift model implemented to simulate tidal current pattem from RADARSAT data while the Lagrangian model used to predict oil spill spreading pattern. The classical Fay‘s algorithm was implemented with the two models to simulate the oil spill trajectory movements. The study shows that the slick lengths are effected by tidal current V component with maximum velocity of 1.4 m/s. This indicates that oil slick trajectory path is moved towards the north direction. The oil slick parcels are accumulated along the coastline after 48 h. The analysis indicated that tidal current V components were the dominant forcing for oil slick spreading.     

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。     

基于专利数据分析的污染地下水修复技术发展现状及趋势分析

为明确地下水污染修复技术在世界范围的研究布局和发展态势,本研究基于智慧芽全球专利数据库对1989-2018年地下水污染修复技术专利进行计量学统计,并探讨该技术的研究布局、研究重点及授权趋势。结果显示,从申请量来看,世界范围内地下水污染修复技术涉及的申请量逐渐增长,但绝对申请量和专利授权比相对较低,地下水污染修复技术研发的重视程度依然不够,有待进一步加强;中国是该技术领域主要专利申请国,也是最大的技术来源国;科研单位在该领域的研发实力显著高于企业机构。基于以上研究,认为今后应加强研发,并且创造高效经济的地下水污染修复技术,注重科研机构与企业单位合作及已有专利成果的转化,促进专利的市场应用,使其发挥更大的社会和经济效益。     

水质自动监测参数的相关性分析及在水环境监测中的应用

通过水质自动监测数据与常规监测数据比较,表明了自动监测与常规监测数据的一致性;通过对自动监测数据分析,发现五参数可以更直接地反映水质变化,并且五参数之间以及五参数与其他监测指标之间都存在一定的相关性;典型污染事故预警监测案例的分析,更加凸显了五参数连续监测在预警监测中的重要性。     

优化布点中模式计算结合历史数据估算的分析方法及研究

随着城市建设发展,城市建成区不断扩大,在空气质量监测中,旧的城区监测点位很难准确反映新的区域内的空气质量时空变化,文章尝试在新的发展区建立一个数学模型,预测新区域内有代表性的某一特征监测点浓度,与旧城区监测点位优选点共同构成整个区域的空气质量监测系统。     

一种新型CO气敏双层薄膜材料

介绍了一种新型结构 CO气敏的半导体薄膜材料——粉末溅射方法制备的表面层掺杂 Sn O2 /Sn O2 ∶ Pt双层膜的气敏特性。分析了双层膜中的导电层厚度对气敏特性的影响 ,并对气敏机理的有关问题进行了讨论     

基于顶层设计方法的生态环境大数据总体框架研究

生态环境大数据建设是一项长期性、系统性的工作,需要科学、合理的顶层设计从全局的角度出发,对任务的各方面、各层次、各要素统筹规划,集中有效资源,高效、快捷地实现既定目标。本文总结了开展总体框架设计面临的主要问题;论述了顶层设计的基本概念和特征、原则和设计方法,阐述了大数据顶层设计与信息化顶层设计的关系,提出了生态环境大数据业务架构的设计方法、总体框架,并探讨了总体框架落地的主要思路。     

基于多速率卡尔曼滤波方法的位移和加速度数据融合

为了尽可能地利用加速度传感器和位移传感器中的冗余信息、提高振动实测数据的精度,将结构同一位置的加速度和位移观测值进行数据融合处理,提出了一种基于维纳过程加速度模型的多速率卡尔曼滤波数据融合方法。首先给出了基于维纳过程的多速率卡尔曼滤波数融合模型;然后在加速度和位移观测值的基础上,通过多速率卡尔曼滤波数据融合得到位移、速度以及加速度的的最优估计,并对融合结果进行卡尔曼平滑处理,进一步提高了状态估计准确性;最后数值分析了不同噪声水平和采样频率比对融合算法的影响,而且与相关文献的结果作了对比分析。结果表明,本文方法合理有效且具有一定的噪声鲁棒性。