on an earlier version of this article and Pierre Provencher for his help in collecting the data. Correspondence concerning this article should be addressed to Robert J. Vallerand, Laboratoire de Recherche sur le Comportement Social, Departement de Psychologie, University du Quebec a Montreal, C.P. 8888, Station

This is the manual to the Statistical Data Viewer . The motivation for writing this application and an example of its actual use are discussed in my master's thesis [Nan03] on machine learning. If you simply want to get started and explore the application by yourself, read Section 2

theory; 03B35 [Mathematical logic and foundations]: Mechanization of proofs and logical operations; 68Q22 [Computer science]: Parallel and distributed algorithms; 68Q60 [Computer science]: Specification and verification of programs. CR Subject Classification (1991): C.2.2 [Computer systems

of the age at which each patient in a population develops carcinoma are known as age-incidence data; these provide a quantitative measure of human tumor initiation and dynamics. To test this hypothesis, we compared a mathematical model in which telomere loss is the rate limiting step during

: Data refinement is converting a program that uses one set of variables to an equally correct program that uses another set of variables, usually of different types. There have been a number of seemingly different mathematical definitions of data refinement. We present a unifying view of data

Stecke [21] has developed mathematical programming approaches for deter-mining, from a set of part type requirements, the production ratios (part types to be produced next, and their proportions) which maximize overall machine utiliza-tions by balancing machine workloads in a flexible manufacturing

gene classes regulated by similar mechanisms and accurately predict regulatory elements. Experiments are performed on several genomes including C. elegans, human chromosome 22, and Yeast. Index Terms-- database, data mining, complete genome, gene, transcription factor.

Abstract: Online learning initia-tives over the past decade have become increasingly comprehen-sive in their selection of courses and sophisticated in their presen-tation, culminating in the recent announcement of a number of consortium and startup activities that promise to make a university education on the internet, free of charge, a real possibility. At this pivotal moment it is appropriate to explore the potential for obtaining comprehensive bioinformatics training with currently existing free video resources. This article pre-sents such a bioinformatics curric-ulum in the form of a virtual course catalog, together with editorial commentary, and an assessment of strengths, weaknesses, and likely future directions for open online learning in this field. Online Learning Comes of Age Online academic ‘‘courseware’ ’ at the university level has now been available to the public for a decade, the earliest concerted effort having originated in 2002 with the Massachusetts Institute of Technology (MIT) and their OpenCour-seWare initiative

Abstract not found

this review are simulation methods such as Monte Carlo and response surface, and methods that use FEM to solve deterministic equations (Fokker-Planck) governing probability densities. The essential conclusion is that the second moment methods are mathematically identical to the second order (except