On the Spectral Index－Flux Density Relation for Large Samples of Radio Sources     

W.Reich  P.Reich  R.Wielebinski 《中国天文和天体物理学报》2003,3(4):347-358

We present new statistical results on the spectral index-flux density relation for large samples of radio sources using archival data of the most sensitive surveys, such as 6C, Miyun, WENSS, B3, NVSS, GB87. Instrumental selection effects and the completeness of the catalogs are discussed. Based on the spectral indices calculated for about 200 000 sources from the WENSS (327 MHz) and NVSS (1.4 GHz) catalogs, we obtained (1) The median spectral index increases from amed --0.9 toαmed --0.8 (Svαvα), while S327 flux densities decrease from 0.1 Jy down to 25mJy. The median spectral indices nearly show no variation within the error bars when the flux density is larger than 0.1 Jy. (2) A dependence of the fraction of ultra-steep spectrum sources (USS, -1.5 <α<-1.0), steep spectrum sources (SSS, -1.0 <α< -0.5) and flat spectrum sources (FSS, -0.5≤α≤0.0) is partly responsible for the spectral flattening. Another contribution to the spectral flattening comes from the variation of αmed of steep spectrum so  相似文献   

Point source detection using the Spherical Mexican Hat Wavelet on simulated all-sky Planck maps     

P. Vielva  E. Martínez-González  J. E. Gallegos  L. Toffolatti  J. L. Sanz 《Monthly notices of the Royal Astronomical Society》2003,344(1):89-104

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Light-curve classification in massive variability surveys – I. Microlensing     

Vasily Belokurov  N. Wyn Evans  Yann Le Du 《Monthly notices of the Royal Astronomical Society》2003,341(4):1373-1384

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CORRESPONDENCE ANALYSIS ON IMAGES OF JIANGXI PROVINCE AS A TOURIST DESTINATION   总被引：4，自引：0，他引：4  

MAO Duan-qian ZHANG Jie BAO Hao-sheng 《中国地理科学(英文版)》2005,15(3):275-280

1IN T R O D U C T IO NAn image isa setofbelief,s ideasand impressionsthatapersonholdsaboutan object(KOTLER,1991).Similar-lydefinitionistheimage of a destinationas thesum ofbelief,sideasand impressionsthatpeoplehave ofa placeor destination(CROMPTON,1979;KO…  相似文献   

沉积物粒度分析在厦门市第四纪环境研究和地层划分对比中的应用   总被引：6，自引：0，他引：6  

张璞  陈建强  田明中  朱金芳  黄宗林  江春亮 《地球科学与环境学报》2005,27(1):88-94

采用MS2000型激光粒度分析仪进行测试，利用计算机粒度分析软件对数据进行整理和计算，绘制出样品的频率曲线、概率累积曲线以及粒度众数位值曲线等图件并进行沉积环境分析。厦门地区第四纪环境演化经历了中更新世同安组(含泥中粗砂、含泥细中砂、砂为主)海积一冲积一更新统上部龙海组(含泥粗中砂、含泥细中砂、含泥粗砂、粗砂、细中砂、含细砾中粗砂、中细砂等)冲积一洪冲积一更新世上部东山组(砂、砂砾、含泥中粗砂、粗砂、泥质中细砂、细砂、中粗砂等)冲洪积及部分海积(粉砂、细粉砂、含碳质泥、粘土、淤泥质粘土、粉砂质粘土等)一全新世长乐组(粉砂，淤泥质粘土、粉砂质粘土、碳质粘土、含砂淤泥质粘土，粉砂质亚粘土、粉细砂亚粘土等)海湾沉积。在解释环境变化的同时，说明粒度变化曲线在一定程度上可以作为地层划分的依据之一，并以此对研究区地层进行了详细划分。  相似文献   

Applications of seismic travel-time tomography     

R. Phillip Bording  Adam Gersztenkorn  Larry R. Lines  John A. Scales  Sven Treitel 《Geophysical Journal International》1987,90(2):285-303

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Numerical simulations of weak lensing measurements     

David J. Bacon  Alexandre Refregier  Douglas Clowe  Richard S. Ellis 《Monthly notices of the Royal Astronomical Society》2001,325(3):1065-1074

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'Hyper-parameters' approach to joint estimation: applications to Cepheid-calibrated distances and X-ray clusters     

Pirin Erdogdu  Stefano Ettori  Ofer Lahav 《Monthly notices of the Royal Astronomical Society》2003,340(2):573-579

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成都市冬季重污染日气象条件成因分析及预报     

张波  杨柏生 《成都信息工程学院学报》1992,(3)

本文通过对成都10个重污染日进行天气学分析,将污染浓度与气象要素进行聚类、研究了重污染日形成原因及污染浓度与气象要素的关系。在此基础上,建立了SO_2、TSP日平均浓度分级预报方程。  相似文献   

Automated Separation of Stars and Normal Galaxies Based on Statistical Mixture Modeling with RBF Neural Networks     

Dong-Mei Qin  Ping Guo  Zhan-Yi Hu  Yong-Heng ZhaoNational Laboratory of Pattern Recognition Laboratory  Institute of Automation  Chinese Academy of Sciences  Beijing  dmqin@nlpr.ia.ac.cnDepartment of Computer Sciences  Beijing Normal University  Beijing National Astronomical Observatories  Chinese Academy of Sciences  Beijing 《中国天文和天体物理学报》2003,3(3)

For LAMOST, the largest sky survey program in China, the solution of the problem of automatic discrimination of stars from galaxies by spectra has shown that the results of the PSF test can be significantly refined. However, the problem is made worse when the redshifts of galaxies are not available. We present a new automatic method of star/(normal) galaxy separation, which is based on Statistical Mixture Modeling with Radial Basis Function Neural Networks (SMM-RBFNN). This work is a continuation of our previous one, where active and non-active celestial objects were successfully segregated. By combining the method in this paper and the previous one, stars can now be effectively separated from galaxies and AGNs by their spectra-a major goal of LAMOST, and an indispensable step in any automatic spectrum classification system. In our work, the training set includes standard stellar spectra from Jacoby's spectrum library and simulated galaxy spectra of EO, SO, Sa, Sb types with redshift ranging from 0 to 1  相似文献