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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.

This is CRUD interface based on standard JEE MVC servlet, JSP, JSTL. It renders forms and lists of any entity according XML settings (Beige-Settings). Database logic is handled by Beige-ORM. It also includes Mail-sender and database replicator through WEB-service. It is SQLite configured. Put WAR file into Tomcat7 webapps, make sure that Tomcat has libraries: HikariCP-2.4.3.jar, sqlite-jdbc-3.8.11.2.jar, slf4j-api-1.7.12.jar (versions may be different), for MS Windows change file separator in META-INF\context.xml connectionURL from "/" to "\" and reassemble WAR. Beigesoft-Accounting-Web extends it into very complex business application.

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.

ModelCC is a model-based parser generator (a.k.a. compiler compiler) that decouples language specification from language processing, avoiding some of the problems caused by grammar-driven parser generators. ModelCC receives a conceptual model as input, along with constraints that annotate it. It is then able to create a parser for the desired textual language and the generated parser fully automates the instantiation of the language conceptual model. ModelCC also includes a built-in reference resolution mechanism that results in abstract syntax graphs, rather than mere abstract syntax trees.

A collection of filters for manipulating multi-instance data. Includes PropositionalToMultiInstance, MultiInstanceToPropositional, MILESFilter and RELAGGS. For more information see: M.-A. Krogel, S. Wrobel: Facets of Aggregation Approaches to Propositionalization. In: Work-in-Progress Track at the Thirteenth International Conference on Inductive Logic Programming (ILP), 2003. Y. Chen, J. Bi, J.Z. Wang (2006). MILES: Multiple-instance learning via embedded instance selection. IEEE PAMI. 28(12):1931-1947. James Foulds, Eibe Frank: Revisiting multiple-instance learning via embedded instance selection. In: 21st Australasian Joint Conference on Artificial Intelligence, 300-310, 2008.

TagSoup is a SAX-compliant parser written in Java that, instead of parsing well-formed or valid XML, parses HTML as it is found in the wild: poor, nasty and brutish, though quite often far from short. TagSoup is designed for people who have to process this stuff using some semblance of a rational application design. By providing a SAX interface, it allows standard XML tools to be applied to even the worst HTML. TagSoup also includes a command-line processor that reads HTML files and can generate either clean HTML or well-formed XML that is a close approximation to XHTML.

Dhelm is a set of java-based open source libraries which can be used to develop software to perform technical analysis in stock market. The dhelm-indicator package includes APIs to calculate few common indicators. APIs for following indicators have been packaged into the v 1.0.0- 1. Simple Moving Average(SMA). 2. Exponential Moving Average(EMA). 3. Moving Average Convergence Divergence(MACD). 4. On Balance Volume(OBV). 5. Parabolic Stop and Reverse(PSAR). 6. Relative Strength Index(RSI). 7. Average Directional Index(ADX). 8. Bollinger Bands 9. Chaikin Money flow index. 10.Rate of Change(ROC). 11.Money Flow Index(MFI).

This project contains artifacts that provide utility functions for Cloud Bigtable client readers and writers in Google Cloud Dataflow. Dataflow includes a different version of the cloud bigtable client, resulting in a need to have a separation of concerns and an abstraction. More importantly, there is a need for shading and renaming of packages so that Dataflow nad bigtable-hbase-dataflow's two sets of shading (needed for a variety of reasons) don't clash with each other. This submodule does package renaming which is needed for bigtable-hbase-dataflow and alleviates some issues related to developing that module.