Selecting a reference frame

Reference frames are representations that parse space. In the case of spatial terms, reference frames mediate the mapping of linguistic expressions onto spatial configurations of objects. In the sentence ``The fly is above the cat,' ``above' is defined with respect to a reference frame that is imposed on the cat. Different types of reference frames can be used to define spatial terms, each based on a different source of information. For example, gravity, the orientation of objects in the scene or the orientation of the viewer can all be used to set the orientation of a reference frame. When these reference frames disagree (because the viewer is reclining or because the objects in the scene are overturned), there are competing definitions for the spatial term, resulting in the need for reference frame selection. The purpose of this paper is to review a line of research that examines reference frame selection in the context of spatial language. This work shows that all reference frames are initially active and assign a direction to a spatial term. Moreover, this activation is automatic, and is followed by the selection of a single reference frame, with selection accompanied by inhibition of the non-selected frames. Parallels between reference frame selection in language and in perception and attention are discussed.     

月球车视觉系统的一种匹配算法

针对月球车立体视觉系统对匹配速度和准确度要求较高的特点，提出了一种基于特征约束的区域匹配算法。该算法用多尺度小波变换实现边缘提取和降噪，采用多特征匹配、双向匹配、部分二次采样、选取图像子集等技术保证匹配的速度和精度。最后对匹配结果进行滤波，进一步提高匹配的准确性。     

Identification of uncatalogued LEO space objects by a ground-based EO array

A ground-based electro-optical (EO) array, deployed at the Jilin Space Tracking Base of Changchun Observatory, China, has been in operation since April 2017. The array has 8 small telescopes, each has an aperture of 15 cm and a field of view of 14° × 14°. On average, the array can collect angles data over 3–4 thousand Very Short Arcs (VSAs) of Low Earth Orbit (LEO) space objects each night. Correlation of the VSA angles data with the NORAD catalogue objects results in about 85% of all the VSAs being correlated to NORAD objects. The remaining 15% VSAs angles data could be supposed from uncatalogued objects. The Initial Orbit Determination (IOD) solutions of the VSAs with the range-search method and the association results of the IODs with the geometrical method are presented. The mean IOD success rate is about 91% and the True Positive (TP) rate is more than 86%. In addition, the classical Gauss, Laplace, Gooding and Double-r angles-only IOD methods are applied to process VSA angles data and their performance is assessed. The CBTA method is used to associate the IOD tracks and compared with the geometrical method. A set of procedures for identifying the uncatalogued objects based on the VSA angles data is designed. Processing of the VSA angles data from Aug 4 to Sep 30, 2017 reveals there are possibly 415 uncatalogued LEO objects.     

Feature selection for high-dimensional data in astronomy

With an exponentially increasing amount of astronomical data, the complexity and dimension of astronomical data are likewise growing rapidly. Extracting information from such data becomes a critical and challenging problem. For example, some algorithms can only be employed in the low-dimensional spaces, so feature selection and feature extraction become important topics. Here we describe the difference between feature selection and feature extraction methods, and introduce the taxonomy of feature selection methods as well as the characteristics of each method. We present a case study comparing the performance and computational cost of different feature selection methods. For the filter method, ReliefF and fisher filter are adopted; for the wrapper method, improved CHAID, linear discriminant analysis (LDA), Naive Bayes (NB) and C4.5 are taken as learners. Applied on the sample, the result indicates that from the viewpoints of computational cost the filter method is superior to the wrapper method. Moreover, different learning algorithms combined with appropriate feature selection methods may arrive at better performance.     

巴拉克·奥巴马胜选演说翻译的生态学视角

从生态学视角研究翻译的整合性。基于翻译适应选择论,分别从语言维、文化维和交际维分析奥巴马胜选演说三个中译本的适应性选择转换情况,指出应注重体现翻译生态系统的整体性,注意语言维、文化维和交际维等多维度的有机结合。在翻译过程中力求做出与翻译生态环境相适应的选择,达到兼顾原文原语、译语和译语读者之间平衡和协调的目的。     

基于主基底分析的变量筛选

利用Gram-Schmidt变换,提出一种主基底分析方法.解释并证明了Gram-Schmidt变换所删除的信息量.给出"主基底"的定义及构造方法,并提出"净信息含量比"的概念,用以测度所选基底包含的信息.该方法能在原始数据信息损失尽可能小的前提下,排除所有的冗余变量以及变量集合中的重叠信息,得到一个正交的主基底,从而更有效地对大规模变量集合中的信息进行筛选.多角度的理论分析指出,主基底在尽可能多地携带原始变量信息的同时,还可保证样本点间的相似性改变最小.实际案例分析说明了该方法的合理性和有效性.      

基于离散粒子群优化算法的直升机减速器齿轮故障特征选择

粒子群优化算法自提出以来,由于其容易理解、易于实现,所以发展很快,在很多领域得到了应用。本文针对机械故障特征选择问题,提出基于离散粒子群优化(PSO)算法的特征选择方法,并在直升机减速器齿轮故障诊断中进行了应用。实验结果表明,离散PSO算法可以快速、有效的求得优化特征集,是求解故障特征选择问题的一个较好方法。      

BUAA-SID1.0空间目标图像数据库

随着太空竞争的加剧,空间目标监视及目标识别受到越来越多国家的重视。而空间目标图像数据库的缺乏直接影响了空间目标识别技术的研究进展。针对这一问题,建立了BUAA-SID1.0空间目标图像数据库。文章在分析空间目标图像数据库建立的背景和意义的基础上,介绍了数据库的建立方法,指出了数据库共享版本BUAA-SID-share1.0的内容,给出了两种识别算法在共享数据库上的测试结果。     

完善党内选举制度推进党内民主建设

党内民主选举制度是党内民主建设的核心内容。发展党内民主最重要的是实现党内选举的科学化、民主化。党内选举制度的改革和完善，可以无情地斩断人身依附关系，彻底根治用人制度上的歪风，克服干部问题上的“近亲繁殖”弊病。完善党内选举制度需要健全和完善候选人提名方式，逐步扩大直接选举和差额选举，选举代表必须充分体现选举人的意志。其核心是把公平竞争引入党内选举，使党焕发青春和活力。     

模型的稀疏选择与参数辨识及应用

基于正则化技术的稀疏成分分析方法可同时完成模型选择和参数估计功能。现分别从迭代算法的设计和对应岭估计的构造两方面切入,研究正则化函数的选取及特点,并深入分析其模型参数辨识的机理,说明正则化参数与广义岭估计的最佳岭参数的耦合性。该方法可操作性强,可保证参数迭代的收敛性,对于正则化函数的构造和参数估计的统计特性分析均有规则可循。缺项多项式和制导工具误差系数求解的数值例子表明,该方法具有有效的一体化模型选择和参数估计功能。