GarlicSim is a platform for writing, running, and analyzing simulations. It is general enough to handle any kind of simulation: physics, game theory, epidemic spread, electronics, etc. GarlicSim aims to eliminate the need to write any boilerplate code that isn't directly related to the phenomenon you're simulating. GarlicSim defines a new format for simulations, called a simulation package and often abbreviated as simpack. The simpack contains all the code that define the simulated system, and is simply a Python package which defines a few special functions according to the GarlicSim simpack API. Simpack code may also be written in C. All of the tools that GarlicSim provides can be used to run simulations of all kinds of different domains.
Qt-based library with functionality to create highly efficient and fully graphical applications, oriented to computer vision, image processing, and scientific computation. The library features an homogeneous and well documented object-oriented API, with wrapping methods for high performance functionality from libraries such as OpenCV, GSL, CGAL, IPP, BLAS, LAPACK, or Octave library.
Thinknowlogy is grammar-based software, designed to utilize the Natural Laws of Intelligence in grammar, in order to create intelligence through natural language in software. This is demonstrated by programming in natural language, reasoning in natural language and drawing conclusions (more detailed than scientific solutions), making assumptions (with self-adjusting level of uncertainty), asking questions (about gaps in the knowledge), and detecting conflicts in the knowledge. It builds semantics autonomously (with no vocabularies or words lists), detecting some cases of semantic ambiguity. It is multi-grammar, proving that Natural Laws of Intelligence are universal.
Salad (short for Letter Salad) is an efficient and flexible implementation of the well-known anomaly detection method Anagram by Wang et al. (RAID 2006). Salad is based on n-gram models, that is, data is represented as all of its substrings of length n. During training these n-grams are stored in a Bloom filter. This enables the detector to represent a large number of n-grams in little memory and still being able to efficiently access the data. Salad extends Anagram by allowing various n-gram types, a 2-class version of the detector for classification, and various model analysis modes.