Herqq UPnP (HUPnP) is a software library for building UPnP devices and control points conforming to the UPnP Device Architecture version 1.1. It is designed to be simple to use and robust in operation. It is built using the Qt framework, following many of the design principles and programming practices used in the Qt framework. It integrates into Qt-based software smoothly and enables truly rapid UPnP development.
The GNU Autoconf Archive is a collection of more than 450 macros for GNU Autoconf. They can be re-used without imposing any restrictions on the licensing of the generated configure script. In particular, it is possible to use them in configure scripts that are meant for non-free software.
The minfx project is a Python package for numerical optimization. It provides a large collection of standard minimization algorithms, including the line search methods (steepest descent, back-and-forth coordinate descent, quasi-Newton BFGS, Newton, and Newton-CG), the trust-region methods (Cauchy point, dogleg, CG-Steihaug, and exact trust region), the conjugate gradient methods (Fletcher-Reeves, Polak-Ribiere, Polak-Ribiere +, and Hestenes-Stiefel), the miscellaneous methods (Grid search, Simplex, and Levenberg-Marquardt), and the augmented function constraint algorithms (logarithmic barrier and method of multipliers).
Bmrblib is a Python API abstracting the Biological Magnetic Resonance Data Bank (BioMagResBank or BMRB) NMR-STAR format. It allows the writing of NMR-STAR files for BMRB data deposition and the reading and easy extraction of data from files residing in the BMRB data bank, all without knowledge of the Self-Defining Text Archive and Retrieval (STAR) format.
CGAL, the Computational Geometry Algorithms Library, is a large C++ library of geometric data structures and algorithms such as Delaunay triangulations, mesh generation, Boolean operations on polygons, and various geometry processing algorithms. CGAL is used in various areas: computer graphics, scientific visualization, computer aided design and modeling, geographic information systems, molecular biology, medical imaging, robotics and motion planning, and numerical methods.
QSMM, the "QSMM State Machine Model", is a framework for development of non-deterministic intelligent state models and systems with spur-driven behavior. It includes low-level functions for generating optimal actions by the system and high-level functions for building multinode models. In a multinode model, nodes represent components of a system you develop which choose optimal actions using the framework and can correspond to entities external to the system and which behavior is to be learnt. A node can choose optimal actions based on a current node state which is either set manually by your program or is identified automatically by the framework. Probability profiles for a state transition matrix and an action emission matrix of the node can be specified using an assembler program with a user-defined instruction set.