Database of molecular masers and variable stars

We present the database of maser sources in H2 O, OH and Si O lines that can be used to identify and study variable stars at evolved stages. Detecting the maser emission in H2 O, OH and Si O molecules toward infrared-excess objects is one of the methods for identifing long-period variables(LPVs, including miras and semiregulars), because these stars exhibit maser activity in their circumstellar shells. Our sample contains 1803 known LPV objects. Forty-six percent of these stars(832 objects) manifest maser emission in the line of at least one molecule: H2 O, OH or Si O. We use the database of circumstellar masers in order to search for LPVs which are not included in the General Catalogue of Variable Stars(GCVS). Our database contains 4806 objects(3866 objects without associations in GCVS) with maser detection in at least one molecule. Therefore it is possible to use the database in order to locate and study the large sample of LPV stars. The database can be accessed at http://maserdb.net.     

Retrieving volume FeO and TiO_2 abundances of lunar regolith with CE-2 CELMS data using BPNN method

The volume FeO and TiO_2 abundances(FTAs) of lunar regolith can be more important for understanding the geological evolution of the Moon compared to the optical and gamma-ray results. In this paper, the volume FTAs are retrieved with microwave sounder(CELMS) data from the Chang'E-2 satellite using the back propagation neural network(BPNN) method. Firstly, a three-layered BPNN network with five-dimensional input is constructed by taking nonlinearity into account. Then, the brightness temperature(TB) and surface slope are set as the inputs and the volume FTAs are set as the outputs of the BPNN network.Thereafter, the BPNN network is trained with the corresponding parameters collected from Apollo, Luna,and Surveyor missions. Finally, the volume FTAs are retrieved with the trained BPNN network using the four-channel TBderived from the CELMS data and the surface slope estimated from Lunar Orbiter Laser Altimeter(LOLA) data. The rationality of the retrieved FTAs is verified by comparing with the Clementine UV-VIS results and Lunar Prospector(LP) GRS results. The retrieved volume FTAs enable us to re-evaluate the geological features of the lunar surface. Several important results are as follows. Firstly, very-low-Ti(<1.5 wt.%) basalts are the most spatially abundant, and the surfaces with TiO_2> 5 wt.% constitute less than 10% of the maria. Also, two linear relationships occur between the FeO abundance(FA) and the TiO_2 abundance before and after the threshold, 16 wt.% for FA. Secondly, a new perspective on mare volcanism is derived with the volume FTAs in several important mare basins, although this conclusion should be verified with more sources of data. Thirdly, FTAs in the lunar regolith change with depth to the uppermost surface,and the change is complex over the lunar surface. Finally, the distribution of volume FTAs hints that the highlands crust is probably homogeneous, at least in terms of the microwave thermophysical parameters.     

Cartograms for Use in Forecasting Weather-Driven Natural Hazards

This paper evaluates the potential of using cartograms for visualizing and interpreting forecasts of weather-driven natural hazards in the context of global weather forecasting and early warning systems. The use of cartograms is intended to supplement traditional cartographic representations of the hazards in order to highlight the severity of an upcoming event. Cartogrammetric transformations are applied to forecasts of floods, heatwaves, windstorms and snowstorms taken from the European Centre for Medium-range Weather Forecasts (ECMWF) forecast archive. Key cartogram design principles in standard weather forecast visualization are tested. Optimal cartogram transformation is found to be dependent on geographical features (such as coastlines) and forecast features (such as snowstorm intensity). For highly spatially autocorrelated weather variables used in analysing several upcoming natural hazards such as 2m temperature anomaly, the visualization of the distortion provides a promising addition to standard forecast visualizations for highlighting upcoming weather-driven natural hazards.     

不动产空间数据二三维一体化存储设计与应用探讨

通过对不动产空间数据和ArcGIS的GeoDatabase数据模型的分析,设计了不动产登记空间数据成果二三维数据统一存储的规则和方法,从而为不动产登记成果的二三维系统应用提供了数据支撑。     

深度学习GoogleNet模型支持下的中分辨率遥感影像自动分类

提出了一种基于深度学习技术的遥感分类方法,它能有效解决中分辨率影像在分类过程中出现的像元混分问题。研究选用2016年5月12日武汉市Landsat 7 ETM+遥感影像,基于GoogleNet模型中的Inception V3网络结构,借助迁移学习方法,构建出遥感分类模型,实现了对武汉市主城区4类典型地物（不透水层、植被、水体和其他用地）的自动分类提取,并将分类结果与传统最大似然分类（ML）结果进行了对比分析。研究表明：基于深度学习方法的遥感影像总体分类精度高达88.33%,Kappa系数为0.834 2,明显优于传统ML方法总体分类精度83%和Kappa系数0.755 0,而且有效抑制了地物在分类过程中出现的像元混分现象。     

粒子加速器中高精度丝线绝对位置测量技术研究

粒子加速器中采用振动线技术进行共架单元上多块磁铁的高精度预准直,需要将振动线代表的磁中心引出进行共架单元之间的相对准直。为了获取以振动线为代表的丝线高精度空间绝对位置,本文对采用近景摄影测量技术进行点、线位置求解的方法进行了研究。利用单相机多站位的方法进行拍摄,通过标定板提供的高精度控制点坐标,采用自标定光束法平差对相机进行标定,并提出将空间直线离散成空间2点进行直线整体精确求解。对标定板上由2点组成的模拟直线进行测量验证,并与标定板提供的理论值进行对比,结果显示空间直线位置获取精度优于5 μm。这表明了本文理论和方法的正确性,为进一步研究丝线高精度空间绝对位置测量打下了基础。     

融合GNSS和加速度计监测数据的超高建筑动态特性分析

GNSS和加速度计是目前动态监测超高建筑环境载荷变形的主要手段。GNSS具有无需通视、可直接获取三维位移等优点,但受精度和采样率的限制,其对微变形及高频振动信息不敏感;而加速度计具有高精度和高采样率等优点,但无法监测超高建筑低频的似静态变形。为充分发挥这两种传感器的各自优势,提出利用多速率Kalman滤波和RTS平滑方法对超高建筑GNSS和加速度计监测数据进行融合处理。试验结果表明,与单一的GNSS监测技术相比,该方法有利于削弱GNSS高频噪声的影响,提高位移数据的采样率,可有效识别超高建筑的低频和高频振动频率,提高对微变形振动的监测能力;与单一的加速度计监测技术相比,该方法可以准确监测超高建筑的低频变形信息,具有良好的工程应用价值。     

结合云计算与大数据的出租房消防安全监管GIS

我国城镇化进程和经济发展效果卓著,但消防建设规划与城市扩张发展之间并不协调。虽然现有研究已经运用GIS技术到消防安全监管当中,但依然存在信息联动性不强,可视化程度低的问题。为此,本文基于地理信息系统技术对城市开发区内地理信息数据、多源多时态遥感及航空影像、巡查数据、出租房数据等进行有效整合完善,以建立时空地理信息大数据。笔者利用虚拟化、云计算等技术建立出租房消防安全动态监管平台。此平台为管理部门提供了基于地理信息的决策支持,提升了出租房管理的高效性和科学性。系统的建成和应用对我国的出租房管理信息化工作的开展具有重要意义。     

基于图像的天体搜索研究与自动化集成软件开发

天体搜索是天文数据处理流程的一个重要环节,也是以平方公里阵列射电望远镜(Square Kilometre Array, SKA)为代表的下一代射电望远镜在面向海量数据处理中的挑战之一.现今天体自动搜索算法、软件已日趋成熟并投入应用,不过在自动化、兼容性等方面仍具有提升空间.以更自动化、更适应海量数据需求的天体搜索算法研究为宗旨,以现有算法为研究基础,天体自动搜索软件系统得到设计和开发.该系统包含友好的交互式用户操作界面,具备可视化输出数据显示、兼容不同数据输入和输出并包含为实际应用服务的文件管理功能.该系统对于大天区图以及图像集,均能够很好地进行自动化处理.测试结果显示,上述方法对于天体搜索的改进有一定成效.后续将在此基础上对该集成系统做进一步的改进开发,以适应更多的需求.     

大面积硅微条探测器在轨数据压缩算法的设计与实现

硅微条探测器具有位置分辨高、响应快、低噪声、低功耗等优点,广泛应用在各大加速器试验中,测量粒子径迹.新世纪以来,逐渐应用于空间探测领域.计划中的"悟空"2号暗物质粒子探测卫星的硅微条探测器将至数十万计,将产生海量的原始数据.如何实现探测器快速实时的数据压缩,是其需要解决的一大难题.立足于面向空间应用的硅微条探测器在轨实时压缩算法,算法采用FPGA (Field-programmable Gate Array)搭建流水线结构的方式实现,在提高系统集成度、节省逻辑资源的同时,批量数据处理时最高可将数据压缩率提升至38.4 M通道/s.算法结构具有通用性,设计思想和方案将为"悟空"2号的径迹探测器的研制提供参考.