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JUNG provides a common and extendible language for the modeling, analysis, and visualization of data that can be represented as a graph or network.
New version now available on GitHub: https://github.com/jrtom/jung/releases/tag/jung-2.1
OpenDMAP (Open Source Direct Memory Access Parser) is a natural language processing (text mining) application: a semantic parser for information extraction.
QSAR is a project that aims to build a GUI that enables people to build quantitative structure activity (or property) relationship models. It will use parts of CDK (cdk.sf.net), JOELib (joelib.sf.net), R (www.r-project.org) and other projects.
SLEDRIDE: Simplified Learning about Expression Data Running in a Desktop Environment. To provide a general workbench for pipe-lining microarray gene expression data from supervised learning results into unsupervised learning methods.
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* Java classes for parsing text, conversion to XML or to evaluate in Java. The parser is textual-script-controlled with a syntax near Backus Naur Format, named ZBNF. * Some routines for conversion: C-Header or Java to XMI, XML-Documentation generation,
The aim of the project is the creation of an multiuser, webenabled, datahandling, processing and visualisation tool for engineering data from the real word - with Datacollection, Charting, Mapping, Alerting, Messaging and Reporting capabilities .....
Open extensible system analysis report tool for Java, based on numerous open source analysis initiatives. The XML/XSL batch-processing framework produces integrated HTML/SVG reports of the systems current state and the development over time.
Maximally flat (maxflat) digital filter design in Java, with arbitrary numbers of poles and zeros. "Maximally flat" means that the magnitude frequency response has the maximum number of vanishing derivatives at 0 and pi.
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Everyday Software for the Researcher of Restricted Means: This project is intended to offer scientists and students with small budgets advanced versions of aqua-built desktop-editing, graphics and statistical applications for MacOSX.
A very simple Equity Investment Stragety Analyser tool.
What it does :
- Maintain Stock portfolios
- Simulate Investment using NSE Historical bhav data files
- Analyze different investment strategies against index performance
- Graph the results
JMulTi is an interactive software designed for univariate and multivariate time series analysis. It has a Java graphical user interface that uses an external engine for statistical computations. It uses the framework JStatCom.
National University Community Research Institute's NU KEEPERRHHATT Algorithmic Framework is a series of meta-algorithms based upon the Longest Hamiltonian Path Problem for finding high level explanations to social, economic and political behaviour.
OpenBRR2 project focuses on the re-write of the original "OpenBRR - Data" (http://sourceforge.net/projects/openbrr) project. The aim is to develop a hosted data aggregation application for all F/LOSS projects.
VideoGrok is a set of applications for relating metadata to segments of video, and then locating and analysing these, with interfaces to technologies including SMIL, RSS and RDF. Currently based on Quicktime for Java. This restriction will be removed.
Projeny (Probablistic Networks Generator in Java) is a graphical (Java SWT) front-end to BNT (Bayes Net Toolbox for Matlab). Projeny requires BNT, JMatLink and a Matlab back-end. There is no installable release package, but source code is available on SVN - please check out from SVN to use Projeny. Projeny was started with BNJ as the base.
AlViz is a research prototype for visual ontology alignment implemented as multiple-view plug-in for Protege using J-Trees and Graphs. Based on similarity measures of an ontology matching algorithm AlViz helps to assess and optimize the alignment results
jIR is an open source project focused on building an open platform for image processing tasks. It is composed of individual algorithms whose task is to extract or compare information in a data set of images.
This proyect presents a system, which, from a corpus of documents, extracts information about a theme area, and a pedagogical components collection. This information is packed into fine granularity learning objects (metadata included).