New High-Speed Computing Devices

“One method of error analysis (not the one we will use) is based upon the principles of mathematical statistics. Unfortunately, statistical methods can only be meaningfully applied when one has large amounts of data for a given system. In many cases … these large quantities of data are not available … then statistical methods are not applicable, and some other methods must be devised.”     

The Consistent System

The Consistent System (CS) is an interactive computer system for researchers in the behavioral and policy sciences and in fields with similar requirements for data management and statistical analysis. The researcher is not expected to be a programmer. The system offers a wide range of facilities and permits the user to combine them in novel ways. In particular, tools for statistical analysis may be used in combination with a powerful relational subsystem for data base management. This paper gives an overview of the objectives, capabilities, status, and availability of the system.     

Data depth and correlation

Summary: We describe depth–based graphical displays that show the interdependence of multivariate distributions. The plots involve one–dimensional curves or bivariate scatterplots, so they are easier to interpret than correlation matrices. The correlation curve, modelled on the scale curve of Liu et al. (1999), compares the volume of the observed central regions with the volume under independence. The correlation DD–plot is the scatterplot of depth values under a reference distribution against depth values under independence. The area of the plot gives a measure of distance from independence. Correlation curve and DD-plot require an independence model as a baseline: Besides classical parametric specifications, a nonparametric estimator, derived from the randomization principle, is used. Combining data depth and the notion of quadrant dependence, quadrant correlation trajectories are obtained which allow simultaneous representation of subsets of variables. The properties of the plots for the multivariate normal distribution are investigated. Some real data examples are illustrated. *This work was completed with the support of Ca Foscari University.     

An efficient polynomial space and polynomial delay algorithm for enumeration of maximal motifs in a sequence

In this paper, we consider the problem of enumerating all maximal motifs in an input string for the class of repeated motifs with wild cards. A maximal motif is such a representative motif that is not properly contained in any larger motifs with the same location lists. Although the enumeration problem for maximal motifs with wild cards has been studied in Parida et al. (2001), Pisanti et al. (2003) and Pelfrêne et al. (2003), its output-polynomial time computability has been still open. The main result of this paper is a polynomial space polynomial delay algorithm for the maximal motif enumeration problem for the repeated motifs with wild cards. This algorithm enumerates all maximal motifs in an input string of length n in O(n ³) time per motif with O(n) space, in particular O(n ³) delay. The key of the algorithm is depth-first search on a tree-shaped search route over all maximal motifs based on a technique called prefix-preserving closure extension. We also show an exponential lower bound and a succinctness result on the number of maximal motifs, which indicate the limit of a straightforward approach. The results of the computational experiments show that our algorithm can be applicable to huge string data such as genome data in practice, and does not take large additional computational cost compared to usual frequent motif mining algorithms. This work is done during the Hiroki Arimura’s visit in LIRIS, University Claude-Bernard Lyon 1, France.     

Perceptions concerning research integrity and the practice of data audit in the biotechnology industry

A survey was conducted in order to evaluate the responses of biotechnology executives concerning their perceptions of the frequency of questionable R & D studies performed in their companies and to assess the extent to which their companies voluntarily conducted data audits. Data audit was found to be commonly practiced on a voluntary basis by biotechnology companies, in contrast to its almost lack of practice by universities. However, public companies were more likely to practice data auditing than privately held companies. Moreover, the likelihood that managers suspected or detected questionable studies in their companies was significantly increased if the company practiced data auditing.     

Ain't Behavin': Forecast Errors and Measurement Errors in Early GNP Estimates

Revisions of the early GNP estimates may contain elements of measurement errors as well as forecast errors. These types of error behave differently but need to satisfy a common set of criteria for well-behavedness. This article tests these criteria for U.S. GNP revisions. The tests are similar to tests of rationality and are based on the generalized method of moments estimator. The flash, 15-day, and 45-day estimates are found to be ill behaved, but the 75-day estimate satisfies the criteria for well-behavedness.     

THE CHOICE BETWEEN SETS OF REGRESSORS

This paper examines the choice of critical values for testing both non-sequential and nested sequential sets of constraints in the standard linear regression model. Modest increases in (e.g.) t-ratio critical values relative to their one-off values are often sufficient to maintain proper size. A Bayesian decision-theoretic approach, highlighted by the Schwarz (1978) criterion, provides a framework for deriving consistency and asymptotic local power properties of both forms of testing (data mining) algorithms.     

应用莫尔条纹法测定人体腰椎后关节三维位移量

应用莫尔条纹原理,测定人体离体腰椎三维运动时后关节的相对位移量,探索运动的角度、载荷和位移的相互关系,是直接研究关节运动学的一种简便有效方法。本文提供的实验结果对于研究腰椎后部结构的生理和病理功能具有重要的临床意义。     

.Net下基于GDI＋的数码照片信息提取

由于数码相机存储容量的限制,导致不同批次拍摄的照片命名相同而出现照片管理问题。利用GD I＋提供的关于位图操作的类,实现照片EX IF信息的提取并根据提取信息重命名照片,方便了数码照片的管理。