Estimation for the number of components in a mixture model using stepwise split-and-merge EM algorithm

The main difficulty with EM algorithm for mixture model concerns the number of components, say g. This is the question of model selection, and the EM algorithm itself could not estimate g. On the contrary, the algorithm requires g to be specified before the remaining parameters can be estimated. To solve this problem, a new algorithm, which is called stepwise split-and-merge EM (SSMEM) algorithm, is proposed. The SSMEM algorithm alternately splits and merges components, estimating g and other parameters of components simultaneously. Also, two novel criteria are introduced to efficiently select the components for split or merge. Experimental results on simulated and real data demonstrate the effectivity of the proposed algorithm.     

Evaluation of passive microwave snow water equivalent algorithms in the depth hoar-dominated snowpack of the Kuparuk River Watershed, Alaska, USA

This research investigates the utility of passive microwave remote sensing instruments to accurately determine snow water equivalent (SWE) over large spatial extents. Three existing Special Sensor Microwave Imager (SSM/I) snow water equivalent algorithms produced by Chang, Tait and Goodison were evaluated for their ability to determine snow water equivalent in a snowpack containing substantial depth hoar, large faceted snow crystals. The Kuparuk River Watershed (8140 km²) test site on the North Slope of Alaska was chosen for its snowpack containing a think depth hoar layer and long history of ground truth data. A new regional snow water equivalent algorithm was developed to determine if it could produce better results than the existing algorithms in an area known to contain significant depth hoar. The four algorithms were tested to see how well they could determine snow water equivalent: (1) on a per pixel basis, (2) across swath-averaged spatial bands of approximately 850 km², and (3) on a watershed scale. The algorithms were evaluated to see if they captured the annual spatial distribution in snow water equivalent over the watershed. Results show that the algorithms developed by Chang and from this research are generally within 3 cm of the spatially averaged snow water equivalents over the entire watershed. The algorithms produced by Chang, Tait, and in this research were able to predict the basin-wide ground measured snow water equivalent value within a percent error range from −32.4% to 24.4% in the years with a typical snowpack. None of the algorithms produce accurate results on a pixel-by-pixel scale, with errors ranging from −26% to 308%.     

关于从旋涡炉渣回收铜的研究

介绍了用自然澄清法降低、回收旋涡炉渣中的铜的方法。该方法工艺简单。操作方便，不仅降低冶炼成本，同时提高了经济效益。     

提高信号设备运用质量 促进管理进步

本文运用全面质量管理的方法，对设备故障进行分析，提出预防措施，降低设备故障率，进而取消值班制实现减人增效、系统降本。     

烧结处理小矿山精矿的应用研究

研究小矿山精矿的性质，分析小矿山精矿对烧结过程的影响，提出了增加小矿山精矿配入量的途径及方法．     

2003 Gold Medal Award for Life Achievement in the Science of Psychology.

Presents the 2003 American Psychological Foundation's Gold Medal Award for Life Achievement in the Science of Psychology, which was presented to Robert Rosenthal. A biography of Rosenthal is provided, along with a selected bibliography and the text of the award citation: "For outstanding scientific contributions that have had a profound influence on research methods, empirical investigations, theory, and applications. Robert Rosenthal's seminal research on interpersonal expectancy inspired hundreds of studies with applications within and beyond psychology. His amplification of experimenter- and subject-related artifacts and his insights about ethical issues have improved the way that research is conducted. His statistical contributions are classic and wide ranging, including his body of work on meta-analysis and contrast analysis and his formulation of valuable procedures, such as the binomial effect-size display and counternull statistics. An exceptional scientist, teacher, mentor, and author, Rosenthal, with his generous and brilliant touch, has shaped the lives and work of countless others." (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Difference in Turbulent Diffusion between the Active and Passive Scalars in a Thermally Stably Stratified Medium

The difference in the turbulent diffusion between the active (heat) and passive (mass) scalars in a thermally stably stratified medium is investigated. The axisymmetric problem is treated on the formation of a turbulent circulation flow above a heated disk and on the turbulent diffusion of a passive scalar (impurity) from a continuous surface source in a stably stratified medium. The results indicate that the thermal stratification causes appreciable differences in the coefficients of turbulent transfer between the active (heat) and passive (mass) scalars. This means that the assumption of the identity of the coefficient of turbulent diffusion of heat and mass, employed in conventional models of turbulence, produces significant errors in estimating the heat and mass transfer in a thermally stably stratified medium.     

A simple approximation algorithm for the weighted matching problem

We present a linear time approximation algorithm with a performance ratio of 1/2 for finding a maximum weight matching in an arbitrary graph. Such a result is already known and is due to Preis [STACS'99, Lecture Notes in Comput. Sci., Vol. 1563, 1999, pp. 259-269]. Our algorithm uses a new approach which is much simpler than the one given by Preis and needs no amortized analysis for its running time.