Lam merges several input files line-by-line. By changing the input or output line separators you can do fun things like interleaving lines from several files or making a simple template system. Lam can also pad or truncate input lines to given widths before merging. Lam is often distributed together with jot and rs (sometimes under the name bsd-utils).
Gamma is a dynamically-typed, object-oriented, interpreted programming language that has been designed and optimized to reduce the time required for building applications. It supports the QNX/Photon and Linux/GTK GUI environments, and has a built-in library of over 300 functions. It cuts development times and offers run-time debugging by wedding a C-like syntax to a Lisp interpreter that has been optimized specifically for performance and memory usage.
Jot is used to print out increasing, decreasing, random, or redundant data, usually numbers, one per line. It can be used to generate randomness fitting a certain pattern (eg, a random IP address) or number sequences (useful in shell programming). It is often distributed together with lam and rs, sometimes under the name bsd-utils.
Elfvector is a package for generating and using a transfer vector for subroutine linkage between an ELF executable and an ELF shared library under Linux on x86, in order to save space and application startup time. At runtime, only the name of the vector is looked up dynamically, no matter how many symbols are used from the vector. Elfvector also includes vectool for managing groups of shared libraries at fixed addresses.
php-msrpc is a PHP binding for MSRPC, which is Microsoft's proprietary protocol for managing Windows servers and the like. It uses the libraries provided by the Samba-TNG project, which is required for use. php-msrpc will enable you to write Web-based administration tools for Windows (such as a user manager) with a Web server running under Linux.
Torch is a machine learning library written in C++ that works on most Unix/Linux platforms. It can be used to train MLPs, RBFs, HMMs, Gaussian Mixtures, Kmeans, Mixtures of experts, Parzen Windows, KNN, and can be easily extended so that you can add your own machine learning algorithms.