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GridLAB-D is a new power system simulation tool that provides valuable information to users who design and operate electric power transmission and distribution systems, and to utilities that wish to take advantage of the latest smart grid technology. It incorporates advanced modeling techniques with high-performance algorithms to deliver the latest in end-use load modeling technology integrated with three-phase unbalanced power flow, and retail market systems.

This project describes a model of how the semantic human memory represents the information relevant to the objects of the world in text format. It provides a system and a GUI application capable of extracting and managing concepts and relations from English texts. https://aseryla2.sourceforge.io/

This project describes a model of how the semantic human memory represents the information relevant to the objects of the world in text format. It provides a system and a GUI application capable of extracting and managing concepts and relations from English texts. https://aseryla2.sourceforge.io/

This project is intended to provide Git access to the code of the original project, TA-Lib, which uses Subversion. It is intended for system integrators wishing to use TA-Lib in their Git-managed project through Git submodules or subtrees. No actual development is being done here; all development happens in the original project.

Development and support of OCFA have been discontinued. the code has moved to these github repositories: https://github.com/DNPA/OcfaLib https://github.com/DNPA/OcfaArch https://github.com/DNPA/OcfaJavaLib https://github.com/DNPA/OcfaModules https://github.com/DNPA/OcfaDoc If you are interested in contributing to ongoing work on the creation of a community maintained OCFA inspired computer forensic framework, please join the Mattock/MattockFS community page on...

SNNSraster is a utility for quick ANN analysis of raster GIS maps with the use of Stuttgart Neural Network Simulator trained network files. It was developed to read and write binary raster files. SNNSraster is a project of the Geography Laboratory of the University of Siena. The code was developed by Giancarlo Macchi Jánica between 2006 and 2007. SNNSraster's fundamental objective is to improve the ability to integrate the use of artificial neural networks in GIS environments.

Library dedicated to the parsing of network protocols and designed to be fast, auto-adaptive, asynchronous, modular and completely independent from client/server code.

Server/Client System for managing a Scientific Journal. Cross platform wxWidgets based.