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SynapseGrid is a framework for constructing reactive real-time immutable data flow systems. -core contains everything to run a single-threaded system, -akka contains everything to run systems over Akka actors, -slf4j - enables logging, -concurrent - running systems directly over ExecutorContext without the need for Akka, -examples - a few test systems. Also there are -frames - a framework for type construction with meta information (see relations.scala). -typed-expressions - a framework for defining parsers and generators for natural language. The current version is 1.4.0

SynapseGrid is a framework for constructing reactive real-time immutable data flow systems. -core contains everything to run a single-threaded system, -akka contains everything to run systems over Akka actors, -slf4j - enables logging, -concurrent - running systems directly over ExecutorContext without the need for Akka, -examples - a few test systems. Also there are -frames - a framework for type construction with meta information (see relations.scala). -typed-expressions - a framework for defining parsers and generators for natural language. The current version is 1.4.0

Reco4j is an open source project aims at developing a recommendation framework based on graph data sources. We choose graph databases for several reasons. They are NoSQL databases, so "schemaless". This means that it is possible to extend the basic data structure with intermediate information, i.e. similarity value between item and so on. Moreover, since every information is expressed with properties, nodes and relations, the recommendation process can be customized to work on every graph. Reco4j can be used on every graph where "user" and "item" is represented by node and the preferences are modelled as relationship between them. Current implementation leverage on Neo4j as first graph database integrated in our framework.

A simple templating system for java codegen. This library includes an object-oriented, fluent source writing api, for a chained, intuitive codegen api. It also includes a template processor which can take java source files formatted with "magic comments", to allow simple mapping of GeneratorClass#generatorMethod() to inject dynamic source content. //@generateWith(GeneratorClass)// -Sets the current generator. You may use as many as you please //generatorMethod(arbitrary-string-data-you-may-want-to-parse)// -invokes the named method on the current injector, with any text (between brackets) sent as a string This allows you to markup default source with hooks where you may want to inject arbitrary code. It is especially useful for generating super-source in gwt compiles; changes to the default class are propagated to overrides.

The idea and motivation of the lindbergframework is to provide resources and simple solutions to problems based on the concept 'Plug and Use'. In the current version, the framework provides easy and simple solutions to the population of beans from SQL queries, abstraction of the complexities to access to stored procedures and stored functions , population of database cursors, transaction management, dependency injection, integration with Spring, JSF and Adobe Flex. The lindberg-persistence (LINP) solution, implements a important concept: separated repository of SQL commands. Among other resources.

This service implements the Indexer and Searcher interface of WebLab and connect to a remote SOLR engine in order to realize the functions. The connection is mandatory and thus the remote SOLR server should be started beforehand. Configuration of the SOLR server URL is found in src/main/webapp/WEB-INF/cxf-servlet.xml . See in particular "indexerServiceBean" and "searcherServiceBean". Moreover, the service implements several "Analyser" services that could be included in a complete search chain in order to: - enrich a ResultSet with metadata about Hits (see resultSetMetaEnricherServiceBean) - highlight snippet in ResultSet (see highlighterServiceBean) - provide facets related to the current results (see facetSuggestionServiceBean) - suggest spell correction of the original query (see spellSuggestionServiceBean)

JDOM is a Java-oriented object model which models XML documents. It provides a Java-centric means of generating and manipulating XML documents. While JDOM interoperates well with existing standards such as the Simple API for XML (SAX) and the Document Object Model (DOM), it is not an abstraction layer or enhancement to those APIs. Rather, it seeks to provide a robust, light-weight means of reading and writing XML data without the complex and memory-consumptive options that current API offerings provide. built July 23 2009

The Fuzzy Lattice Reasoning Classifier uses the notion of Fuzzy Lattices for creating a Reasoning Environment. The current version can be used for classification using numeric predictors. For more information see: I. N. Athanasiadis, V. G. Kaburlasos, P. A. Mitkas, V. Petridis: Applying Machine Learning Techniques on Air Quality Data for Real-Time Decision Support. In: 1st Intl. NAISO Symposium on Information Technologies in Environmental Engineering (ITEE-2003), Gdansk, Poland, 2003; V. G. Kaburlasos, I. N. Athanasiadis, P. A. Mitkas, V. Petridis (2003). Fuzzy Lattice Reasoning (FLR) Classifier and its Application on Improved Estimation of Ambient Ozone Concentration.

XBIS is an encoding format for XML documents that is fully convertible to and from text, with information set equivalence between the original document text and regenerated document text. It's intended for use in transmitting XML documents between application components, and is therefore designed for processing speed. The current Java language implementation offers several times the performance of SAX2 parsers working from text documents across a wide range of document types and sizes, and across JVMs tested, while also providing a substantial reduction in document size for most types of XML documents.

The Software Testing Automation Framework (STAF) is an open source, multi-platform, multi-language framework designed around the idea of reusable components, called services (such as process invocation, resource management, logging, and monitoring). STAF removes the tedium of building an automation infrastructure, thus enabling you to focus on building your automation solution. The STAF framework provides the foundation upon which to build higher level solutions, and provides a pluggable approach supported across a large variety of platforms and languages. This component contains the STAF Java API (http://staf.sourceforge.net/current/STAFJava.htm ) only. For more information see http://staf.sourceforge.net/ .