Clustering large number of extragalactic spectra of galaxies and quasars through canopies

Abstract

Cluster analysis is the distribution of objects into different groups or more precisely the partitioning of a data set into subsets (clusters) so that the data in subsets share some common trait according to some distance measure. Unlike classification, in clustering one has to first decide the optimum number of clusters and then assign the objects into different clusters. Solution of such problems for a large number of high dimensional data points is quite complicated and most of the existing algorithms will not perform properly. In the present work a new clustering technique applicable to large data set has been used to cluster the spectra of 702248 galaxies and quasars having 1,540 points in wavelength range imposed by the instrument. The proposed technique has successfully discovered five clusters from this 702,248X1,540 data matrix.     

新型城镇化水平综合评价研究

新型城镇化是城市发展的目标,评价新型城镇化水平有助于提高市民生活质量和城市竞争力,因而对新型城镇化水平进行综合评价至关重要。将文化潜力要素加入改进的“星系”模型来构建新型城镇化水平评价体系,以成熟的专家意见法、相关分析法制定基于两步筛选法的新型城镇化水平评价指标体系技术路线,并采用融合了360度专家反馈法的模糊综合评价法对沈阳市进行新型城镇化水平综合评价。通过实例验证,沈阳市发展水平的综合评价真实有效,旨对新型城镇化发展提供参考。     

Bayesian finite mixtures with an unknown number of components: The allocation sampler

A new Markov chain Monte Carlo method for the Bayesian analysis of finite mixture distributions with an unknown number of components is presented. The sampler is characterized by a state space consisting only of the number of components and the latent allocation variables. Its main advantage is that it can be used, with minimal changes, for mixtures of components from any parametric family, under the assumption that the component parameters can be integrated out of the model analytically. Artificial and real data sets are used to illustrate the method and mixtures of univariate and of multivariate normals are explicitly considered. The problem of label switching, when parameter inference is of interest, is addressed in a post-processing stage.     

浅谈《故训汇纂》的价值

中国传统语言文字学的六种研究方法均与故训密切相关,而对现代的人来说,故训更是阅读古籍、研究汉语史和编纂字词典的不可或缺的资料,清代的《经籍诂》已经尝试汇唐以前的故训资料于一书,但今天的《故训汇纂》做得更好,它既扩大了资料收录范围,又对所收资料进行了全面系统的整理,在嘉惠学林的同时,也倡导了一种实事求是的学风。     

On Bayesian Analysis of Mixtures with an Unknown Number of Components (with discussion)

New methodology for fully Bayesian mixture analysis is developed, making use of reversible jump Markov chain Monte Carlo methods that are capable of jumping between the parameter subspaces corresponding to different numbers of components in the mixture. A sample from the full joint distribution of all unknown variables is thereby generated, and this can be used as a basis for a thorough presentation of many aspects of the posterior distribution. The methodology is applied here to the analysis of univariate normal mixtures, using a hierarchical prior model that offers an approach to dealing with weak prior information while avoiding the mathematical pitfalls of using improper priors in the mixture context.     

《故训汇纂》的语义研究价值

《故训汇纂》是传统语义训释的总汇,在汉语语义研究上具有重要作用。本文选取其中有代表性的"回"字,对它的168条训释作穷尽性的语义系统研究,归纳出11个义项,这些义项有的在词义发展过程中逐渐消失,有的成为语素构成现代汉语的双音词。这些内容充分显示了《故训汇纂》在汉语语言研究和辞书编撰上的重要作用。