A Review of Atmospheric Electricity Research in China from 2011 to 2018

Atmospheric electricity research has been conducted actively in China, having profited from the development and application of high temporal and spatial resolution lightning detection and location technologies. This paper reviews the scientific advances made in the field of atmospheric electricity in China from 2011 to 2018, covering the following five aspects:(1)lightning detection and location techniques;(2) discharge processes and parameters associated with rocket-triggered lightning;(3) physical processes in natural lightning and attachment to the ground;(4) lightning activities and charge structure in different thunderstorms; and(5) effects of thunderstorms on the upper atmosphere. In addition, some outstanding questions for future research are outlined.     

Who governs here? Informal resource extraction,state enforcement,and conflict in Ghana

Over the past two decades, “illegal” natural resource extraction has become a significant driver of environmental change and social conflict across the Global South. In response, numerous Sub-Saharan African states have engaged in governance reforms that heed calls to securitize – or, establish and consolidate state control over – natural resources. In Ghana, securitization has served to entrench the informal economy as domestic producers, marginalized in the process of reform, continue to utilize non-state institutions to maintain access. While the Ghanaian state has branded “illegal” resource extraction a major environmental, social, and national security concern, it has responded to this threat unevenly; it has violently enforced its authority in some contexts but remained relatively indifferent in others. This article explores the phenomenon of selective enforcement to explain patterns of violence that have emerged between state and society in response to both securitization and informality. Drawing on a multimethod approach, I find that natural resource governance authority remains fragmented across resource contexts, and that the configuration of authority and interests on the ground shapes the extent of state intervention. I propose a natural resource typology that identifies when the state is most likely to enforce its authority, and the degree of violent conflict likely to result. Ultimately, I contend that domestic patterns of enforcement are shaped primarily by: 1) competition with local power holders over resource entitlements and 2) global conservation and extraction priorities. While specific to Ghana, this argument can provide important insights into the relationship between informal extraction, state enforcement, and social conflict in other Global South contexts.     

文本特征提取的研究进展

文本理解是人工智能的一个重要分支,其技术推动了人与计算机之间在自然语言上的有效交互.为了让计算机准确地理解和感知文本数据,文本特征提取是最为基础和关键的步骤之一.基于此,本文介绍文本特征提取研究的发展历史,以及近年来主流特征提取的方法,并对未来的研究方向进行展望.首先,介绍语义最底层的词级表示;接着,总结在词级表示基础上衍生出的句级表示上的研究进展;随后,介绍比词级表示和句级表示更高层的篇分析;最后,通过文本特征提取的一个典型应用——问答系统的介绍,阐述文本特征提取的最新方法和技术在问答系统上的应用,并对未来的研究方向做了展望.     

植被高光谱特征分析及其病害信息提取研究

高光谱(hyperspectral)遥感是20世纪末地球观测系统中最重要的技术突破之一。根据植被高光谱数据的植被冠层光谱反射特征和诊断性光谱吸收特征,利用光谱连续统去除法,探讨光谱一阶微分反射比(FDR)和从连续统去除的光谱吸收特征中获得的波段深度(BD)、连续统去除后微分反射比(CRDR)、波段深度比(BDR)和归一化波段深度指数(NBDI)等光谱特征参量。结合多时相的条锈病小麦PHI航空高光谱影像,分析条锈病对小麦光谱的影响及其光谱特征,并运用光谱特征参量和波谱角制图(SAM)技术监测和识别小麦条锈病。     

Small target extraction based on independent component analysis for hyperspectral imagery

IntroductionFeature extraction or transformation is a key stepfor target detection in hyperspectral imagery. Thepurpose is to transform the high-dimensional imageinto low-dimensional image series so that the differ-ences between the targets and the backgr…     

基于小波变换的射频干扰消除方法的研究

在射电天文观测中,射频干扰(Radio Frequency Interference, RFI)会以多种形式混入望远镜接收系统,给观测带来误判或者降低观测信噪比.近年来国内国际射电天文快速发展,国内国际大型射电望远镜和阵列先后建设,观测灵敏度大为提高,射频干扰的影响尤为突出.随着科技发展和人类活动的加剧,射频干扰日益严重且不可逆转.提出利用2维离散小波变换的方法分析射电天文观测的数据,对望远镜系统输出的时间频率序列进行小波变换,根据小波系数分离出原始信号中各分量,每个分量统计得到相应的阈值,将各分量与阈值相比较识别干扰成分并标记去除.利用该方法对实际观测数据进行了处理,结果表明该方法能够很好地标记并消减干扰信号,且提高了观测的信噪比.     

The Basic Shape Classification of Space Debris with Light Curves

We study the machine learning method for classifying the basic shape of space debris in both simulated and observed data experiments, where light curves are used as the input features. In the dataset for training and testing, simulated light curves are derived from four types of debris within different shapes and materials. Observed light curves are extracted from Mini-Mega TORTORA (MMT) database which is a publicly accessible source of space object photometric records. The experiments employ the deep convolutional neural network, make comparisons with other machine learning algorithms, and the results show CNN (Convolutional Neural Network) is better. In simulational experiments, both types of cylinder can be distinguished perfectly, and two other types of satellite have around 90% probability to be classified. Rockets and defunct satellites can achieve 99% success rate in binary classification, but in further sub-classes classifications, the rate becomes relatively lower.     

The problem of the sighting line stabilization for axial meridian circles

The paper deals with the method based on treating the axial meridian circle and a long-focus light mark in the prime vertical as a single virtual instrument that has properties of meridian circle. A horizontal axis, a sighting line, and a micrometer cross-wire of the instrument are created by optical means. The key function here is performed by the light mark that ensures a reference direction used for formation of instrumental principal planes and directions. Stability of instrumental azimuth, inclination, and collimation is expected to be about ±0.″01. Besides, an accuracy of observations is not affected by any temperature and weight deformations of telescope mechanics. Owing to the last circumstance, the design is cheap and the telescope aperture may be increased significantly, to about 1m. An estimate of accuracy of observations depends on the adopted model of image motion, and for sites with excellent seeing and bright stars is ±0.″03 to ±0.″05 (rms).     

奇异性理论在弱异常信息提取中的应用—以冀北隐伏中-酸性侵入岩体为例

冀北地区是河北省矿产资源重要聚集地之一,成矿条件优越,其中中-酸性侵入岩体与银铅锌多金属矿床成矿密切相关。然而,大量的第四系覆盖压制了一些深部及隐伏弱异常成矿信息,使得常规化探方法在该覆盖区提取效果微弱。本文运用奇异性分析及主成分分析对冀北1：20万水系沉积物常量元素化探数据进行分析处理,提取区内成矿元素弱异常,并将其与未进行奇异性处理的结果进行对比。结合区域地质背景、物化探资料圈定覆盖区内与中-酸性侵入岩体有关的异常区,对成矿作用、成矿规律进行分析、讨论,以期揭示区内元素富集规律。结果显示,上述组合方法可以有效提取元素弱异常并进行成矿有利区圈定,并且圈定位置与已知岩体位置、区域构造条件相吻合,共圈出隐伏异常点7个,推测其为成矿远景区。     

一种COVID-19病例个体时空轨迹交互式提取与质量评估方法

针对当前新型冠状病毒肺炎(coronavirus disease 2019,COVID-19)病例个体时空轨迹描述文本高度非结构化的特点,提出了一种基于自然语言处理(natural language processing, NLP)辅助的交互式轨迹提取方法,用于提高轨迹提取的效率和质量.设计了交互式轨迹提取和质量评估流...