Non-redundant data clustering

Data clustering is a popular approach for automatically finding classes, concepts, or groups of patterns. In practice, this discovery process should avoid redundancies with existing knowledge about class structures or groupings, and reveal novel, previously unknown aspects of the data. In order to deal with this problem, we present an extension of the information bottleneck framework, called coordinated conditional information bottleneck, which takes negative relevance information into account by maximizing a conditional mutual information score subject to constraints. Algorithmically, one can apply an alternating optimization scheme that can be used in conjunction with different types of numeric and non-numeric attributes. We discuss extensions of the technique to the tasks of semi-supervised classification and enumeration of successive non-redundant clusterings. We present experimental results for applications in text mining and computer vision.     

扇形束投影域重建—再投影迭代法

本文所提出的投影域重建——再投影迭代算法可以恢复不完整的扇形束投影数据,从而实现从有限的投影数据重建图象。这种算法把滤波——反投影图象重建过程和再投影的过程纳入一个公式,仅在投影域上估算未知的投影数据,因此避免了重建过程和反投影过程中的插值运算,改善了收敛性,提高了计算精度,缩短了运算时间。模拟实验表明:即使有70％的投影数据丢失,经过两次迭代就能以令人满意的精度恢复丢失的投影数据。     

p,V, T and derived thermodynamic data for toluene,trichloromethane, dichloromethane,acetonitrile, aniline,and n-dodecane

Experimentally determined p,V,T data are reported for toluene, trichloromethane, dichloromethane, acetonitrile, aniline, and n-dodecane at 278, 288, 298, 313, and 323 K, except for dichloromethane, for which the highest temperature was 298 K. At each temperature, measurements were done at pressures up to about 280 MPa or (for aniline and n-dodecane) at a lower pressure slightly below the freezing pressure at the temperature of measurement. Values of the isobaric expansivity isothermal compressibility and (for toluene, trichloromethane, dichloromethane, and acetonitrile) internal pressure, derived from the p,V,T data, are presented.     

Income, Time Effects and Direct Preferences in a Multimodal Choice Context: Application of Mixed RP/SP Models with Non-Linear Utilities

Transport problems typically involve at least two types of constraints, on income and on time. Therefore, the indirect utility function depends either on the income available after having subtracted the cost of the discrete alternative and on the free time left after having worked and travelled by each competing option. In the typical linear-in-the-attributes and in-the-parameters specification, that represents the first grade approximation of the indirect utility function, the effect of income and time constraints cancel out and only the cost and time of the alternatives matter in the comparison between them. From a microeconomic point of view this is equivalent to assume that income and time effects could be disregarded; which is not always the case. To account for these effects the utility function should include second order attributes; however, in non-linear utility functions it may not be easy to distinguish among several effects that could be relevant: direct preferences for good and leisure, and simple interactions between attributes other than income and time effects. This paper analyses these effects from a theoretical point of view focusing on the possible confounding problem in detecting income and time effects. We use a dataset collected for a modal choice context and containing both revealed and stated preference data, and estimate several NL models examining the effect of the different second-order terms on detecting income and time effects. We compared specifications including square cost and time attributes, interactions between time and cost, cost divided by the income available to be spent on free time, and time multiplied by free time. Our results confirm the strong effect of direct preferences for goods and leisure time on choice, and the potential confounding effect between quadratic attributes and other non-linear omitted terms. Finally, we also found that care should be taken in highlighting income and time effects using mixed data sources, since confounding effects can occur when non-linearities are accounted for in both data sets.     

无线随钻测量技术的应用现状与发展趋势

目前,无线随钻测量技术是石油工程技术发展的一个主要方向。详细介绍了无线随钻测量仪器的传输方式、国内外无线随钻测量技术的主要进展和应用现状,指出了国内外无线随钻测量仪器的优缺点和应用范围,分析了无线随钻测量技术的发展趋势,并提出我国应在借鉴国外先进的无线随钻测量技术的基础上,研制具有自主知识产权的无线随钻测量仪器,以加快我国无线随钻测量技术的发展,缩短与国际先进水平的差距。     

Bayes estimators for reliability measures in geometric distribution model using masked system life test data

This paper presents Bayes estimators for the reliability measures of the individual components in a multi-component systems in the presence of masked system life test data. The life time distributions of the system components are assumed to be geometric with different parameters. Two-sided Bayesian probability intervals of the parameters are also derived. Numerical simulation study is given in order to: (i) explain how one can apply the theoretical results obtained, (ii) study the influence of the sample size and masking level on the accuracy of point estimates.     

Excel在大学物理实验中的应用

利用Excel的强大功能，对实验数据进行处理、分析，对实验过程及实验结果的监控。     

Analytic methods for modeling longitudinal data from rolling therapy groups with membership turnover.

Interventions for a variety of emotional and behavioral problems are commonly delivered in the context of treatment groups, with many using rolling admission to sustain membership (i.e., admission, dropout, and discharge from group are perpetual and ongoing). The authors present an overview of the analytic challenges inherent in rolling group data and outline commonly used (but flawed) analytic and design approaches to addressing (or sidestepping) these issues. Moreover, the authors propose use of latent class pattern mixture models (LCPMMs) as a statistically and conceptually defensible approach for modeling treatment data from rolling groups. The LCPMM approach is illustrated with rolling group data from a group-based alcoholism pilot treatment trial (N = 128). Different inferences were made with regard to treatment efficacy under LCPMM vs. the commonly used standard group-clustered latent growth model (LGM); coupled with other preliminary findings in this area, inferences from LGMs may be overly liberal when applied to data from rolling groups. Continued work on data analytic difficulties in groups with membership turnover is critical for furthering the ecological validity of research on behavioral treatments. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

钢样成分化验分析结果网络传输系统的开发与应用

钢样成分化验分析结果网络传输系统将碳硫分析仪、光谱分析仪和相应的计算机控制系统按以太网络结构组联,形成"炉前分析网络",采用分析网主服务器系统软件和网络分析系统软件实现网络传输。该系统可将炉前钢样化验分析结果实时传输到炉前大屏,具有传输速度快、准确率高的特点,提高了工作效率和产品合格率,降低了生产成本。     

大型堆浸金矿选厂自动化系统

对自动化在选矿工业中应用的意义进行了论述。结合堆浸选矿的工艺特点，介绍了金矿选厂自动化系统的构成和自动化系统实现的基本功能。