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The application Bio7 is an integrated development environment for ecological modelling and contains powerful tools for model creation, scientific image analysis and statistical analysis. The application itself is based on an RCP-Eclipse-Environment (Rich-Client-Platform) which offers a huge flexibility in configuration and extensibility because of its plug-in structure and the possibility of customization.
For monitoring and control of distributed generation and consumption
SolarNetwork started as a simple set of client and server tools to collect and analyse solar power information from a distributed network of solar power collectors.
SolarNetwork is now expanding into a set of tools to not only collect and analyse information, but to also control and influence behaviour of a distributed network of nodes where energy is being generated and/or consumed. The name implies it is for solar generated energy only, the SolarNetwork can in fact be used with any form...
SBSI (Systems Biology Software Infrastructure) is a suite of tools for systems biology, such as parallelized numerical algorithms, and a Java, Eclipse RCP based client for visualizing results, running simulations, and integrating SBML based plugins.
Virtual RTAI Lab is a project aimed to develop an educational platform for Control System Design. It is composed by a server running on linux rtai and a java client, which allow the user to better understand parameters changing in real-time control.
A Open Source 3D Immersive simulation environment, like the "second life", with some distribuited processing tools, to make the GRID power growup with every new node (client machine) attached.
Molevolve is a Java library for running a Genetic Algorithm to model the 3-dimensional structures of peptide chains from amino-acid sequences. Client code can specify its own peptide chain model, fitness functions and GA operations. Requires JDK 1.5.
A simulator for self-organizing video replication and more
... algorithm, which lets the content place itself where it is needed. It is robust, scalable and adaptive. The transport path of content is exploited to replicate content and limited storage space is handled by clean-up mechanisms.
We implemented a simulator to show the algorithm's performance and to test its behavior under real circumstances. It is easily extendable to support several new scenarios or changes to the algorithm (see replication and client models).