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...This repository is intended for contribution and collaborative development. If you have a new meshing algorithm or interested in contributing to cfMesh, do not hesitate to contact us. Please note that this code is not the same as CF-MESH+, which is a commercial product offered by Creative Fields Holding.

Track your Agility dog trial results. Multiple dogs can be tracked in a single file. Many venues are supported. Windows and Mac are supported. Please note: ARB moved to GitHub on 2017-12-27: https://github.com/dconnet/AgilityBook

...It simplifies the analysis of macromolecular structures, protein complexes, and molecular dynamics trajectories and offers a platform for the rapid integration of external programs. PLEASE NOTE: The Biskit source code as well as any later releases are now hosted on https://github.com/graik/biskit The sourceforge repo is only kept here for reference.

NOTE: as of April 24, 2015, libsharp development has moved to Github (https://github.com/dagss/libsharp). Libsharp is a collection of algorithms for efficient conversion between maps on the sphere and their spherical harmonic coefficients. It supports a wide range of pixelisations (including HEALPix, GLESP, and ECP). This library is a successor of libpsht (http://sourceforge.net/projects/libpsht).

NOTE: This project was moved to: https://github.com/eetorres The BPANNA is a flexible Back propagation neural network, which include the Conjugate Gradient and the Levenberg-Marquardt. You can change the number of inputs, number of layers, number of neurons per layer and outputs. It included an structure editor.

tXtFL is a strategy-based football simulator. Teams can be created from real stats on the web, built through custom designed plays, and then used to coach games or predict scores. Note that as of 2010, all new development is taking place at http://textflex.com/txtfl.

A MATLAB package to simulate sample paths of the solution of a Itô or Stratonovich stochastic differential equation (SDE), compute statistics and estimate the parameters from data. A note of caution: SDE Toolbox is no more developed but it's still downloadable. Its inferential capabilities can be considered surpassed (at best). Actually the parameter estimation methods were already far from the state-of-art when the project began in 2007 (!). The considered implemented parametric and non-parametric Monte Carlo likelihood methods were chosen for their ability to treat both one-dimensional and multivariate SDE systems, although the quality of the inferential results can't match those obtained using more advanced techniques. ...