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JSON is a light-weight, language independent, data interchange format. See http://www.JSON.org/ The files in this package implement JSON encoders/decoders in Java. It also includes the capability to convert between JSON and XML, HTTP headers, Cookies, and CDL. This is a reference implementation. There is a large number of JSON packages in Java. Perhaps someday the Java community will standardize on one. Until then, choose carefully. The license includes this restriction: "The software shall be used for good, not evil." If your conscience cannot live with that, then choose a different package. The package compiles on Java 1.2 thru Java 1.4.

MOCCA is the Message-Oriented Command and Context Architecture, providing a GLUE middle-ware that allows sending commands to a peer which are executed by state-less handlers in a specific context. In contrast to the Request-Response scheme the message flow is not fixed by the framework. This allows to implement different communication paradigms (including Request-Response). The whole system can be seen as an automaton with Messages that trigger state transitions in the local Contexts. This library contains the core components, including the GLUE-based implementation.

SSJ is a Java library for stochastic simulation, developed under the direction of Pierre L'Ecuyer, in the Département d'Informatique et de Recherche Opérationnelle (DIRO), at the Université de Montréal. It provides facilities for generating uniform and nonuniform random variates, computing different measures related to probability distributions, performing goodness-of-fit tests, applying quasi-Monte Carlo methods, collecting (elementary) statistics, and programming discrete-event simulations with both events and processes.

A tool to help visualise API differences between two different versions of a project. Jardiff takes two jar files and outputs all the public API changes as xml, html or plain text. Currently this is command line driven, though we are working on an ant plugin. It requires java 1.4 to run. <h2>Background</h2> At OSjava, we were using a shell script to work out API differences between our release versions. This unfortunately doesn't scale very well to larger projects, the main reason for jardiff was to do the same in a much shorter time (From memory it was taking minutes to get the API diff from two fairly small jars). In it's current state, jardiff can generate the api differences between rt.jar for java 1.4 and java 1.5 in under 20 seconds, so it should scale to even the largest of projects.

Stepping is a framework designed to ease the implementation of data processing solutions. In use cases where we need to implement data or data-streaming algorithms or any other processing on data, we need to first handle many different infrastructure issues. For example, we need to decide how to split the data processing logic into different steps, think about our threading policy, how to handle communication between the different steps, error handling etc. One of the most important subjects is the Threading Policy of our solution. For example, we need to think how many threads to open, have the option to distribute the processing of data to multiple 'executors' in parallel, have a thread-safe communication layer between the threads etc. On top of that we also care a lot about the performance of our solution, we want to make sure that the latency added by these infrastructures is minimal as possible. Stepping aims to handle many of these aspects so developers can spend their time on the business logic instead of solving these infrastructure and data flow issues issues over and over again.

Apache Spatial Information System (SIS) is a free software, Java language library for developing geospatial applications. SIS provides data structures for geographic features and associated metadata along with methods to manipulate those data structures. The library is an implementation of GeoAPI 3.0.2 interfaces and can be used for desktop or server applications. The SIS metadata module forms the base of the library and enables the creation of metadata objects which comply with the ISO 19115 international standard. The SIS referencing module enable the construction of geodetic data structures for geospatial referencing as defined by ISO 19111 standard, along with the associated operations which enable the transformation of coordinates between different reference systems. The SIS storage modules provide a common approach to the reading and writing of metadata, features and coverages applicable to simple imagery as to many dimensional data structures.

`Romaji` is a converter library to romanize Japanese hiragana/katakana string by standard and IME typing style. Even though [icu::Transliterator](http://userguide.icu-project.org/transforms/general) already has provided the same functions, and returns only one romanized string. However, there exists several different romanization systems, so one hiragana/katakana string has so many romanize string. For example, `"ちゃ"` can be romanized as `"cha"`, `"tya"`, `"chixya"`, `"tixya"`, `"chilya"`, or `"tilya"`. `Romaji` provides romanized strings as many as possible. If an input string contained non hiragana/katakana characters (includes kanji), `Romaji` return the characters as same as the input. For example, `Romaji` converts the input `"お茶の水"` to `"o茶no水"`. The mapping from hiragana/katakana to romaji is based on common IME's system to type Japanese on a computer. Therefor, `Romaji` does not directly implement the standard system like Hepburn, Nihon-shiki or Kunrei-shiki, but includes them.

This module defines the interface for AlignmentAlgorithms as well as some helper classes. An AlignmentAlgorithm computes an Alignment of two given input sequences, given a Comparator that works in these sequences. More details on the AlignmentAlgorithm can be found in the respective interface. More information on Comparators can be found in the comparators module. The resulting 'Alignment' may be just a real-valued dissimilarity between the input sequence or may incorporate additional information, such as a full Alignment, a PathList, a PathMap or a CooptimalModel. If those results support the calculation of a Gradient, they implement the DerivableAlignmentDistance interface. In more detail, the Alignment class represents the result of a backtracing scheme, listing all Operations that have been applied in one co-optimal Alignment. A classic AlignmentAlgorithm does not result in a differentiable dissimilarity, because the minimum function is not differentiable. Therefore, this package also contains utility functions for a soft approximation of the minimum function, namely Softmin. For faster (parallel) computation of many different alignments or gradients we also provide the ParallelProcessingEngine, the SquareParallelProcessingEngine and the ParallelGradientEngine.

--------------------------------------------------------------------------- Version for VIVO 1.8 This uses the source and test code from the Version for VIVO 1.10, edited to make it compatible with VIVO 1.8. It also borrows some code from VIVO 1.10 itself, changes the package name to avoid conflicts, and adds it here. * Vitro 1.8 uses Jena 2, not Jena 3, and Commons Lang 2, not 3, so modify the "import" statements in the Data Distribution code accordingly. * Vitro 1.8 does not have a "...webapp.utils.sparqlrunner" package, so borrow the source from Vitro 1.10, move it to a different package (just for compatibility with the 1.9 version), modify it to use Jena 2 and Commons Lang 2, and modify the Data Distribution API code to use this sparqlrunner package. * Vitro 1.9 has an earlier version of "...webapp.utils.configuration" package, so borrow the source from Vitro 1.10, move it to a different package so it won't conflict with the 1.9 version, modify it to use Jena 2 and Commons Lang 2, and modify the Data Distribution API code to use this configuration package. Make these modifications, compile, JAR it up, and deploy. --------------------------------------------------------------------------- Because VIVO 1.8 is not available as a Maven package, we have extracted the class files, JARed them up, and stored them in a file-based repository within this project. But that doesn't include any transitive dependencies, so any package that this code requires must be explicitly listed as a dependency. ---------------------------------------------------------------------------

The libswresample library performs highly optimized audio resampling, rematrixing and sample format conversion operations. Specifically, this library performs the following conversions: Resampling: is the process of changing the audio rate, for example from an high sample rate of 44100Hz to 8000Hz. Audio conversion from high to low sample rate is a lossy process. Several resampling options and algorithms are available. Format conversion: is the process of converting the type of samples, for example from 16-bit signed samples to unsigned 8-bit or float samples. It also handles packing conversion, when passing from packed layout (all samples belonging to distinct channels interleaved in the same buffer), to planar layout (all samples belonging to the same channel stored in a dedicated buffer or "plane"). Rematrixing: is the process of changing the channel layout, for example from stereo to mono. When the input channels cannot be mapped to the output streams, the process is lossy, since it involves different gain factors and mixing. Various other audio conversions (e.g. stretching and padding) are enabled through dedicated options.