Download JAR files tagged by business with all dependencies

This project has a lot of business classes to work with genes and related named entities. Genes are part of a GeneDocument and may have gold IDs as well as mapped/predicted IDs. Another large part are species because most (all?) gene ID databases are species specific. So there are also classes or members to represent species mentions and the assignment of species IDs (taxonomy IDs) to genes. There is little to no business logic herein. This project is only useful as building block in other projects dealing with species assignment, gene ID mapping or similar efforts.

Concourse is a distributed database warehouse for transactions, search, and analytics across time. Developers use Concourse to quickly build mission critical software while also benefiting from real time insight into their most important data. With Concourse, end-to-end data management requires no extra infrastructure, no prior configuration and no additional coding–all of which greatly reduce costs and allow developers to focus on core business problems.

With distributed systems being developed as a part of the cloud age. With focus on performance associated with an application dependent on one DB instance, there is a need to bring down the dependency to a database to generate unique numbers for creating a private key when lots of data needs to be stored in the database tables. This library is intended to provide a way of generating unique numbers on the fly in a JAVA based distributed system. This is not a new concept but this library helps in keeping you focused on the business logic that you need to develop for your applications rather than spending time on how this is done. Typically applications powered by RDBMS can leverage the benefit as instant scalability might not be available for these setups when the load to the system spikes.

Rule Learner is an open source Java library for learning business rules from historical data. It supports supervised Machine Learning by incorporating well-known algorithms such as RIPPER and C4.5 provided by open source tools such as Weka. Rule Learner is implemented as a Machine Learning component of OpenRules Decision Manager. It allows business analysts to place their historical data in simple Excel tables and to automatically discover business rules that find certain pattern in this data. The generated rules are human readable and presented in Excel format executable by OpenRules Decision Manager.

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.

dyna4JDBC is a JDBC driver, that allows running alternative JVM language scripts (Groovy, JavaScript, Scala, Jython, Clojure, BeanShell, R (Renjin), JRuby etc.) or external console-oriented programs via the JDBC API. Mainly targeted at allowing JDBC-enabled business intelligence applications to run various scripts instead of SQL easily, dyna4JDBC captures and parses the output of scripts/external programs and presents that as a standard JDBC Result Set, allowing the output to be processed further for various purposes like building complex reports quickly and analysis with other tools.

This is an open source library that allows generating performance indicators easily for java based application. This library is configurable through an xml file (similar to log4j) in order to define the performance object types, dimensions, counters, the output format and statistics generation periodicity. Those statistics can be saved as a file (xml/json) or injected directly in a database. Then they can be correlated and analyzed through any Business Intelligence solution in order to check the application performance and quality: number of transactions, ratio of successful and failure ...