This paper explains how the R Framework (http : //www. wessa .net) and a newly developed Compendium Platform (http : //www. freestatistics. org) allow us to create, use, and maintain documents that contain empirical research results which can be recomputed and reused in derived work. It is illustrated that this technological innovation can be used to create educational applications that can be shown to support effective learning of statistics and associated analytical skills. It is explained how a Compendium can be created by anyone, without the need to understand the technicalities of scientific word processing (MgX) or statistical computing (R code). The propo&sd Reproducible Computing system allows educational researchers to objectively measure key aspects of the actual learning process based on individual and constructivist activities such as: peer review, collaboration in research, computational experimentation, etc. The system was implemented and tested in three statistics courses in which the use of Compendia was used to create an interactive e-leaming environment that simulated the real-world process of empirical scientific research.

mng@maths.hku.hk.

The need for complex and accurate three dimensional (3-D) microcomponents is increasing rapidly for many industrial and consumer products. Electrochemical machining process (ECM) has the potential of generating desired crack-free and stress-free surfaces of microcomponents. This paper reports a study of pulse electrochemical micromachining (PECMM) using ultrashort (nanoseconds) pulses for generating complex 3-D microstructures of high accuracy. A mathematical model of the microshaping process with taking into consideration unsteady phenomena in electrical double layer has been developed. The software for computer simulation of PECM has been developed and the effects of machining parameters on anodic localization and final shape of machined surface are presented.

PrefaceThere are many reasons to analyze the time series data, for example, to understand the underlying generating mechanism better, to achieve optimal control of the system, or to obtain better forecasting of future values. Applied time series analysis consists of empirical models for analyzing time series in order to extract meaningful statistics and other properties of the time series data. With the advances in computer technology, nowadays huge amounts of time series data are stored in data warehouses. Different innovative computing techniques are needed to extract information from these datasets. Innovative computing paradigms can extract the patterns from the time series and to present it in such a way that can better our understanding of the structure, relation, and function of the subjects. The purpose of this book is to illustrate how to apply innovative computing paradigms for the applied time series analysis, with frontier application studies of the time series problems based on the recent works at the

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Summary:We have developed an online program, WCLUSTAG, for tag SNP selection that allows the user to specify variable tagging thresholds for different SNPs. Tag SNPs are selected such that a SNP with user-specified tagging threshold C will have a minimum R2 of C with at least one tag SNP. This flexible feature is useful for researchers who wish to prioritize genomic regions or SNPs in an association study. Availability: The online WCLUSTAG program is available at http:// bioinfo.hku.hk/wclustag/ Contact: mng@math.hkbu.edu.hk

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