nicolas rolland

Welcome to Construct, a visual layout editor based on Blueprint & jQuery! This is version 1.0, finalized on March 5, 2010 and released for public consumption under the FreeBSD License. This project was built by Christian Montoya, and exists both as a useful tool for CSS designers and as proof that a visual layout editor is possible to acheive with clean CSS & semantic HTML. Read on for an explanation of the controls. - nicolas rolland

This is a CSS framework designed to cut down on your CSS development time. It gives you a solid foundation to build your own CSS on - nicolas rolland

Sax: Symbolic Aggregate approXimation -- SAX is the first symbolic representation for time series that allows for dimensionality reduction and indexing with a lower-bounding distance measure. In classic data mining tasks such as clustering, classification, index, etc., SAX is as good as well-known representations such as Discrete Wavelet Transform (DWT) and Discrete Fourier Transform (DFT), while requiring less storage space. In addition, the representation allows researchers to avail of the wealth of data structures and algorithms in bioinformatics or text mining, and also provides solutions to many challenges associated with current data mining tasks. One example is motif discovery, a problem which we recently defined for time series data. There is great potential for extending and applying the discrete representation on a wide class of data mining tasks. Source code has "non-commercial" license - nicolas rolland

Sax: Symbolic Aggregate approXimation -- SAX is the first symbolic representation for time series that allows for dimensionality reduction and indexing with a lower-bounding distance measure. In classic data mining tasks such as clustering, classification, index, etc., SAX is as good as well-known representations such as Discrete Wavelet Transform (DWT) and Discrete Fourier Transform (DFT), while requiring less storage space. In addition, the representation allows researchers to avail of the wealth of data structures and algorithms in bioinformatics or text mining, and also provides solutions to many challenges associated with current data mining tasks. One example is motif discovery, a problem which we recently defined for time series data. There is great potential for extending and applying the discrete representation on a wide class of data mining tasks. Source code has "non-commercial" license - nicolas rolland

a very efficient introduction to git in french - nicolas rolland