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notuvysingleapp from group com.notuvy (version 2.1)

A simple Java framework for making applications singletons. The underlying mechanism uses interprocess communication to that at most one application process is active at a time. A new application invocation either displaces a previous invocation, or it defers to the previous and terminates itself.

Group: com.notuvy Artifact: notuvysingleapp
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Artifact notuvysingleapp
Group com.notuvy
Version 2.1
Last update 16. July 2012
Organization not specified
URL http://labs.notuvy.com/projects/notuvysingleapp/
License Apache 2
Dependencies amount 4
Dependencies junit, log4j, commons-lang, jdom,
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rxtx-rebundled from group de.root1 (version 2.1-7r2-6)

rxtx-rebundled is a slightly modified version of the original rxtx 2.1-7r2. The only difference is: 1) It's a working mavenized library 2) There's just one JAR required. Nothing else. The native libs are bundled with the jar-file. 3) You don't have to care about "java.library.path". This version will on startup extract the correct native libs to system temp folder and loads them automatically. When JVM terminates, temp files will be removed.

Group: de.root1 Artifact: rxtx-rebundled
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2 downloads
Artifact rxtx-rebundled
Group de.root1
Version 2.1-7r2-6
Last update 09. May 2015
Organization not specified
URL http://dev.root1.de/projects/rxtx-rebundled/
License GNU LESSER GENERAL PUBLIC LICENSE Version 3, 29 June 2007
Dependencies amount 0
Dependencies No dependencies
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mrglvq from group de.cit-ec.ml (version 0.1.0)

This project contains a Java implementation of median relational generalized learning vector quantization as proposed by Nebel, Hammer, Frohberg, and Villmann (2015, doi:10.1016/j.neucom.2014.12.096). Given a matrix of pairwise distances D and a vector of labels Y it identifies prototypical data points (i.e. rows of D) which help to classify the data set using a simple nearest neighbor rule. In particular, the algorithm optimizes the generalized learning vector quantization cost function (Sato and Yamada, 1995) via an expectation maximization scheme where in each iteration one prototype 'jumps' to another data point in order to improve the cost function. If the cost function can not be improved anymore for any of the data points, the algorithm terminates.

Group: de.cit-ec.ml Artifact: mrglvq
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Artifact mrglvq
Group de.cit-ec.ml
Version 0.1.0
Last update 27. January 2018
Organization not specified
URL https://gitlab.ub.uni-bielefeld.de/bpaassen/median_relational_glvq
License The GNU General Public License, Version 3
Dependencies amount 1
Dependencies rng,
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