Download JAR files tagged by select with all dependencies

jBiDiB jbidibc USB POM Install the libusb drivers for using the libusb access. Under Windows OS you must install the Zadig driver as described here: https://github.com/libusb/libusb/wiki/Windows. Zadic can be downloaded from: http://zadig.akeo.ie/ In the Zadig UI you must check Options > List all devices and the select the 'USB-EPP /I2C... CH341A' device. Then select the target driver with the spinners (I used libusb-win32 (v1.2.6.0)) and click the 'Install driver' button.

jBiDiB jbidibc CH341A POM Install the libusb drivers for using the libusb access. Under Windows OS you must install the Zadig driver as described here: https://github.com/libusb/libusb/wiki/Windows. Zadic can be downloaded from: http://zadig.akeo.ie/ In the Zadig UI you must check Options > List all devices and the select the 'USB-EPP /I2C... CH341A' device. Then select the target driver with the spinners (I used libusb-win32 (v1.2.6.0)) and click the 'Install driver' button.

To use this update site locally: - Build the drools project with maven (including the eclipse stuff). - Open Eclipse. - Open the menu "Help", menu item "Install new software..." - Click on the button "Add..." to add a new software site. - Fill in the name "drools local update site" - Click on the button "Local..." and select "droolsjbpm-tools/drools-eclipse/org.drools.updatesite/target/repository/" - Select all the features. Click the buttons "Next" and "Finish".

App Configuration for flexible Scheduleviewer: Its manipulates the ScheduleViewerBasis-Example App in different Configurations: * show/hide/disable some Options * renaming the ScheduleSelector-Items (longname. shortname, Path) * Select/Deselect all ScheduleSelector Items * preselection of some Programm/Selectors/ Filterselectors / Schedules * Export as JSON and/or CSV * Save the SessionSelection in a JSON-String Resource

Beigesoft ORM library. This is simple lightweigt multiplatform (JDBC/Android) ORM library. It supports Postgresql, H2 and SQlite. Consist of ORM logic except platform dependent database access logic - e.g. JDBC or Android. It's configurable with standard Java Properties XML files. Standard SQL queries both DML(e.g. SELECT) and DDL(e.g. CREATE) are automatically generated and could be modified/replaced by Properties XML.

Village is a 100% Pure Java API that sits on top of the JDBC API. The purpose of this API is to make it easier to interact with a JDBC compliant relational database. By using Village, it is possible to execute and manage select/insert/update/delete SQL statements without having to actually write a single line of SQL. Village can use any valid JDBC Connection object, so it is possible to use Village with a JDBC Connection pool.

This module provides a convenient way to convert string case. <h3>Usage</h3> In the editor panel: <ol> <li>Select the text you want to change the case of</li> <li>Right-click to open the contextual menu</li> <li>Open the <code>Convert To...</code> submenu</li> <li>Click on the converter of your choice</li> </ol> Please note that if no text is selected, the menu is disabled. <h3>Available converters</h3> <ul> <li><b>camelCase</b>: first capitalized letter of each word, except for the first letter of the resulting word, no space</li> <li><b>hyphen-case</b>: lower case words separated with an hyphen</li> <li><b>lower case</b>: lower case words</li> <li><b>PascalCase</b>: first capitalized letter of each word, no space</li> <li><b>Sentence case.</b>: first capitalized letter of the first word, ends with a dot (capital letters within the sentence are preserved)</li> <li><b>snake_case</b>: lower case words separated with an underline character</li> <li><b>Title Case</b>: first capitalized letter of each word, one space between words</li> <li><b>UPPER CASE</b>: upper case words</li> </ul>

An empty artifact that Guava depends on to signal that it is providing ListenableFuture -- but is also available in a second "version" that contains com.google.common.util.concurrent.ListenableFuture class, without any other Guava classes. The idea is: - If users want only ListenableFuture, they depend on listenablefuture-1.0. - If users want all of Guava, they depend on guava, which, as of Guava 27.0, depends on listenablefuture-9999.0-empty-to-avoid-conflict-with-guava. The 9999.0-... version number is enough for some build systems (notably, Gradle) to select that empty artifact over the "real" listenablefuture-1.0 -- avoiding a conflict with the copy of ListenableFuture in guava itself. If users are using an older version of Guava or a build system other than Gradle, they may see class conflicts. If so, they can solve them by manually excluding the listenablefuture artifact or manually forcing their build systems to use 9999.0-....

The HTTP server module (ks-server-http) implements the Web API of the KnowledgeStore, which includes the two CRUD and SPARQL endpoints. The CRUD Endpoint supports the retrieval and manipulation of semi-structured data about resource, mention, entity and axiom records (encoded in RDF, possibly using JSONLD), and the upload / download of resource representation. The SPARQL Endpoint supports SPARQL SELECT, CONSTRUCT, DESCRIBE and ASK queries according to the W3C SPARQL protocol. The two endpoints are implemented on top of a component implementing the KnowledgeStore Java API (the Store interface), which can be either the the KnowledgeStore frontend (ks-frontend) or the Java Client. The implementation of the module is based on the Jetty Web sever (run in embedded mode) and the Jersey JAX-RS implementation. Reference documentation of the Web API is automatically generated using the Enunciate tool.

Extension of BestFirst. Takes a restricted number of k attributes into account. Fixed-set selects a fixed number k of attributes, whereas k is increased in each step when fixed-width is selected. The search uses either the initial ordering to select the top k attributes, or performs a ranking (with the same evalutator the search uses later on). The search direction can be forward, or floating forward selection (with opitional backward search steps). For more information see: Martin Guetlein (2006). Large Scale Attribute Selection Using Wrappers. Freiburg, Germany.