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Rouplex-Niossl is a java SPI (service provider interface) for secure (SSL/TLS), selectable, socket channels. Some of the classes in the java.nio.channels package have been extended by secure counterparts that can be used side by side, or replace existing instances of the plain implementations. This package contains just the entry point calls for instantiating such instances, as well as a non-functional, default implementation. For a concrete implementation of these classes you can take a look at Rouplex-Niossl-Spi, which would be included as a separate dependency to your applications. More specifically this library defines SSLSocketChannel class to inherit from SocketChannel, SSLServerSocketChannel to inherit from ServerSocketChannel and SSLSelector to inherit from SSLSelector. One or more instances of SSLSocketChannel can be registered with an (or more) instance of SSLSelector to be selected upon, with the same exact semantics a SocketChannel would expect from registering with a Selector. Further, a mixture of SocketChannels and SSLSocketChannels can be registered simultaneously with an SSLSelector. The secure counterparts abide to the same API and semantics defined for plain channels at https://docs.oracle.com/javase/8/docs/api/java/nio/channels/package-summary.html. This way, the existing products can be easily updated to provide secure communication and new products can achieve security of data in transit by using the already proven and excellent patterns for communication such as nio.

Rouplex-Niossl is a java SPI (service provider interface) for secure (SSL/TLS), selectable, socket channels. Some of the classes in the java.nio.channels package have been extended by secure counterparts that can be used side by side, or replace existing instances of the plain implementations. This package contains just the entry point calls for instantiating such instances, as well as a non-functional, default implementation. For a concrete implementation of these classes you can take a look at Rouplex-Niossl-Spi, which would be included as a separate dependency to your applications. More specifically this library defines SSLSocketChannel class to inherit from SocketChannel, SSLServerSocketChannel to inherit from ServerSocketChannel and SSLSelector to inherit from SSLSelector. One or more instances of SSLSocketChannel can be registered with an (or more) instance of SSLSelector to be selected upon, with the same exact semantics a SocketChannel would expect from registering with a Selector. Further, a mixture of SocketChannels and SSLSocketChannels can be registered simultaneously with an SSLSelector. The secure counterparts abide to the same API and semantics defined for plain channels at https://docs.oracle.com/javase/8/docs/api/java/nio/channels/package-summary.html. This way, the existing products can be easily updated to provide secure communication and new products can achieve security of data in transit by using the already proven and excellent patterns for communication such as nio.

JUNG the Java Universal Network/Graph Framework--is a software library that provides a common and extendible language for the modeling, analysis, and visualization of data that can be represented as a graph or network. It is written in Java, which allows JUNG-based applications to make use of the extensive built-in capabilities of the Java API, as well as those of other existing third-party Java libraries. The JUNG architecture is designed to support a variety of representations of entities and their relations, such as directed and undirected graphs, multi-modal graphs, graphs with parallel edges, and hypergraphs. It provides a mechanism for annotating graphs, entities, and relations with metadata. This facilitates the creation of analytic tools for complex data sets that can examine the relations between entities as well as the metadata attached to each entity and relation. The current distribution of JUNG includes implementations of a number of algorithms from graph theory, data mining, and social network analysis, such as routines for clustering, decomposition, optimization, random graph generation, statistical analysis, and calculation of network distances, flows, and importance measures (centrality, PageRank, HITS, etc.). JUNG also provides a visualization framework that makes it easy to construct tools for the interactive exploration of network data. Users can use one of the layout algorithms provided, or use the framework to create their own custom layouts. In addition, filtering mechanisms are provided which allow users to focus their attention, or their algorithms, on specific portions of the graph.

Includes 2 main parts: - Path finding through 2D polygons using the A star algorithm and navigation-mesh generation Field of vision / shadows / line of sight / lighting. The basic polygon and point classes are the KPolygon and KPoint. KPolygon contains a list of KPoints for vertices as well as a center (centroid), area, and radius (circular bound or distance from center to furthest point). KPolygon was born out of the need for a more game-oriented and flexible polygon class than the Path2D class in the standard Java library. KPolygon implements java.awt.geom.Shape so it can be easily drawn and filled by Java2D's Graphics2D object. - This API provides path-finding and field-of-vision. For other complex geometric operations such as buffering (fattening and shrinking) and constructive area geometry (intersections and unions) it is recommended to use the excellent Java Topology Suite (JTS). The standard Java2D library also provides the Area class which can be used for some constructive area geometry operations. Note that there is a utility class PolygonConverter that can quickly convert KPolygons to JTS polygons and vice versa.

MassBank of America (MoNA), is an auto curating repository for storing, comparing and querying mass spectra of chemical compounds. It is metadata centric and it was designed to allow easy integration into other tools by utilize its REST based application programming interface. At the current time it contains over 200k predicted and 40k unique experimental mass spectra and their associated metadata. The predicted spectra were obtained by utilizing the lipid blast library and the experimental spectra were acquired from 30 different facilities all over the world, including several major research facilities in the United States and Japan. MoNA is utilizing the InChI Key as unique identifier for chemicals and is designed for easy scalability and expendability. This is realized by utilizing common applications like nginx, grails, AngularJS, postgresSQL and tomcat. MoNA is currently integrated in applications like MSDial, BinBase, MZMine and the statistics package R. This was accomplished by utilizing its REST based API, which is also utilized by its main AngularJS based web interface. We consider MoNA to be highly useful for crosslinking mass spectra in publications, identification of unknowns and integration in data acquisition software. This package provides you with access to the REST api of the main MoNA installation.

DICTIONARY-BASED COMPOUND SPLITTER FOR GERMAN BananaSplit is a compound splitter for German that uses a dictionary resource. The dictionary can be either a simple word list, or a word list equipped with POS values, or an XML based dictionary. The original version was able to use GermaNet as a dictionary. This is useful in applications that rely on GermaNet anyway: no additional lexicon needs to be generated and held in memory. This was also the original purpose of BananaSplit. It served as a compound splitter for a tool called BananaRelation. BananaRelation cannot be published here as it makes heavy use of unpublished code by EML Research, Heidelberg. BananaSplit can either be used as a standalone application or it can be integrated into other Java programs (as a library). This program emerged from the seminar Lexical Semantic Processing in NLP (winter term 2005/2006) taught by Iryna Gurevych at the Seminar für Sprachwissenschaft, Tübingen. Both BananaSplit and BananaRelation were introduced to the seminar participants on 17th of December, 2005. The key algorithm for compound splitting is based on Langer (1998). The program came to use in Müller and Gurevych (2006). Please note that the program splits compounds into two parts only. Details are given in the documents linked below.

JUNG the Java Universal Network/Graph Framework--is a software library that provides a common and extendible language for the modeling, analysis, and visualization of data that can be represented as a graph or network. It is written in Java, which allows JUNG-based applications to make use of the extensive built-in capabilities of the Java API, as well as those of other existing third-party Java libraries. The JUNG architecture is designed to support a variety of representations of entities and their relations, such as directed and undirected graphs, multi-modal graphs, graphs with parallel edges, and hypergraphs. It provides a mechanism for annotating graphs, entities, and relations with metadata. This facilitates the creation of analytic tools for complex data sets that can examine the relations between entities as well as the metadata attached to each entity and relation. The current distribution of JUNG includes implementations of a number of algorithms from graph theory, data mining, and social network analysis, such as routines for clustering, decomposition, optimization, random graph generation, statistical analysis, and calculation of network distances, flows, and importance measures (centrality, PageRank, HITS, etc.). JUNG also provides a visualization framework that makes it easy to construct tools for the interactive exploration of network data. Users can use one of the layout algorithms provided, or use the framework to create their own custom layouts. In addition, filtering mechanisms are provided which allow users to focus their attention, or their algorithms, on specific portions of the graph.