Download JAR files tagged by considered with all dependencies

The Jadex application kernel provides application support for active components, whereby an application is itself considered as an active component. Applications are composed of subcomponents as well as spaces in various characteristics.

A java api and command line tool for scanning, reporting and fixing a git repository's InnerSource Readiness based on a supplied specification which defines the files and file contents necessary for a repository to be considered ready for InnerSource contribution.

Implementations of the core APIs, not including extension point implementations. This package contains implementations of the data access objects, translator infrastructure etc. The extension point implementations that can be considered as core functionality (files, URLs etc) are held in the taverna-reference-types module.

Apache Commons Lang, a package of Java utility classes for the classes that are in java.lang's hierarchy, or are considered to be so standard as to justify existence in java.lang. The code is tested using the latest revision of the JDK for supported LTS releases: 8, 11, 17 and 21 currently. See https://github.com/apache/commons-lang/blob/master/.github/workflows/maven.yml Please ensure your build environment is up-to-date and kindly report any build issues.

A plugin helping with installing ImageJ 1.x plugins and dependencies. In ImageJ 1.x, .jar files containing an underscore are automatically scanned for classes whose names contain underscores. Every such class is considered to be a plugin. That is not true, however, for jai_codec.jar's classes. Therefore, Fiji introduced the split between plugins/ and jars/, where third-party libraries are expected to live in jars/. ImageJ2 uses the same structure since it is backwards compatible.

A NSGA-II implementation using Java. This implementation of NSGA-II algorithm is in pure reference to the original published paper. This is not an effort to convert the originally implemented C code in Java. The original C code by the authors has not be referred to while writing this implementation. This is a fully customizable implementation of the NSGA-II algorithm, made as generic as possible. This documentation assumes you have basic understanding of the NSGA-II algorithm. Apart from the core concepts of the algorithm, everything else in this package can be implemented as per the user's choice and plugged into the algorithm dynamically. Since NSGA-II is more like a set of protocols to follow as an algorithm rather than a concrete implementation of every aspect, this package has been re-written from scratch keeping complete customizability in mind. Apart from the core concepts of the algorithm, everything is considered to be a plugin external to the algorithm that can be implemented by the user and dynamically plugged into the algorithm during runtime as needed. This opens up the possibility of the package to be used simply as a PoC or be converted into something much more complex according to the users needs.

Performs one-class classification on a dataset. Classifier reduces the class being classified to just a single class, and learns the datawithout using any information from other classes. The testing stage will classify as 'target'or 'outlier' - so in order to calculate the outlier pass rate the dataset must contain informationfrom more than one class. Also, the output varies depending on whether the label 'outlier' exists in the instances usedto build the classifier. If so, then 'outlier' will be predicted, if not, then the label willbe considered missing when the prediction does not favour the target class. The 'outlier' classwill not be used to build the model if there are instances of this class in the dataset. It cansimply be used as a flag, you do not need to relabel any classes. For more information, see: Kathryn Hempstalk, Eibe Frank, Ian H. Witten: One-Class Classification by Combining Density and Class Probability Estimation. In: Proceedings of the 12th European Conference on Principles and Practice of Knowledge Discovery in Databases and 19th European Conference on Machine Learning, ECMLPKDD2008, Berlin, 505--519, 2008.

Module that defines the HttpChannel API. HttpChannels abstract complex download and upload steps into a simple and easy to use NIO Channel. NIO Channels can be wrapped into an InputStream or OutputStream and used in any way you may find possible to. Aside from that, Channels can be used natively in most next-gen libraries, meaning that you don't even need to wrap anything, just start writing or reading data to or from the channel wth a ByteBuffer. Anyone using the library should try to rely on code from this module only and, only if necessary, on configuration classes that are implementation specific. Relying on any other resource or class is considered an error and should NOT be done. One of the most interesting usages of channels for uploads and download is that you can easily copy data straight from one channel to the other, with less than 10 lines of code! Also, channels allows the implementation of a "tee" mechanism, in which data redden from a single channel can be copied to several other channels on the fly!