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GANSO
GANSO is a programming library which implements several methods of global and nonsmooth, nonlinear optimization. It is written in C/C++, and is distributed in compiled form (as binary library files) for several platforms, including Windows, Linux and other Unix flavours.
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DLNLP@dmirg
DLNLP@dmirg is a library of Language Technology resources developed at the Centre for Informatics and Applied Optimization (CIAO).
This library can make useful information, software code and related research outcomes available to those with specific interest and skills in the domain of Natural Language Processing (NLP).
Academic and industrial researchers in NLP and related areas are invited to provide feedback, to facilitate further development of the library. Collaboration on current and future research and development projects is also very welcome.
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Hub Network Algorithm
HubNetwork Algorithm is developed as a PhD project to enhance discovery of Gene Regulatory Networks (GRN) by using heuristic information.
We developed an approach for GRN discovery which integrates heuristic information into the process. Heuristics were used to define a function that measures the degree of association between genes, a procedure for post-processing associated genes, and an algorithm to build the backbone of the network that we call a Hub Network. The pairwise dependency between genes is first calculated using the co-regulation function. This function not only calculates the measure of association based on the regulatory nature of the relationships but also provides us with visualization. In the second step the heuristic post processing procedure is applied to remove some of the false positives. Finally, the Hub Network is applied to build the structure of the network using the output of the previous steps.
HubNetwork algorithms along with benchmark datasets are freely available. The code is written in Python 2.5 and Eclipse 3.3 and Pydev 1.4.4.2636. In addition, you need to install R version 2.9.1 and Bioconductor package, Rpy version 1.0.3, Numpy 1.1.0 and statlib.
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Water Allocation Project
Water Allocation Project.
Water Allocation Project Information
Ballarat Incremental Knowledge Engine (BIKE)
The Ballarat Incremental Knowledge Engine (BIKE) is a comprehensive and extendable knowledge engineering platform developed in C++. It is available to researchers, developers, students and the general public through a GNU Affero General Public License.
BIKE is designed specificatly around the Ripple Down Rules (RDR) family of methodologies, but is also extendable to other approaches to knowledge engineering. BIKE's use of RDR makes it capable of of building sophisticated and easly maintainable knowledge based solutions.
BIKE Home | BIKE Downloads
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