Download JAR files tagged by %3Ehttps: with all dependencies

Kanbanery (https://kanbanery.com) is a simple but powerful Agile project management system, to be precise it focuses around the idea of Kanban, a somewhat near idea to SCRUM but with less strict rules. The heart of each Kanban flow is the Kanban board, IceBox and Archive - there are all easy accessible via this API. Janbanery wraps around the RESTful API delivered by Kanbanery while adding some more features like mass operations or filtering of results. In the end, it's very easy and pleasant to implement your own Kanbanery client be it on the desktop, mobile (android) or as for example Gradle / SBT script to take full advantage of kanbanery's features.

Javonet allows you to reference and use modules or packages written in (Java/Kotlin/Groovy/Clojure, C#/VB.NET, Ruby, Perl, Python, JavaScript/TypeScript) like they were created in your technology. It works on Linux/Windows and MacOS for applications created in JVM, CLR/Netcore, Perl, Python, Ruby, NodeJS, C++ or GoLang and gives you unparalleled freedom and flexibility with native performance in building your mixed-technologies products. Let it be accessing best AI or cryptography libraries, devices SDKs, legacy client modules, internal custom packages or anything from public repositories available on NPM, Nuget, PyPI, Maven/Gradle, RubyGems or GitHub. Get free from programming languages barriers today! For more information check out our guides at https://www.javonet.com/guides/v2/

This project is a collection of miscellaneous tools shared by a number of projects of the same author. There are **simple tuples** to use with Java Streams, **type-safe maps** ([inspired by the heterogeneous map pattern](https://www.informit.com/articles/article.aspx?p=2861454&seqNum=8)) described in Effective Java by Joshua Bloch, a **finder** that handles in a smart way queries to data sources, a facility to use the **DCI (Data, Context and Interactions) architectural pattern**, a simple **message bus** suitable for using the pub-sub pattern inside an application, some **test utilities**, an **experimental actor framework** and a few other small things. Yes, the project name is a tribute to the [jazz standard with the same name](https://en.wikipedia.org/wiki/These_Foolish_Things_(Remind_Me_of_You)) by Maschwitz and Strachey.

# geokey K Dimensional Z-Order curve utils. [](https://travis-ci.org/markrileybot/geokey) [](https://coveralls.io/github/markrileybot/geokey?branch=master) [](https://maven-badges.herokuapp.com/maven-central/io.github.markrileybot/geokey) ## Building ./gradlew build ## Gradle dependency See https://search.maven.org/artifact/io.github.markrileybot/geokey/ ## Using ### Use built in keys to make geohashes ```java import org.geokey.GeoKey; // Make a geo hash key String key = new GeoKey().setLatitude(48.669).setLongitude(-4.329).toString(); // "gbsuv7ztqzpts82uzfwq5e1bp" // parse a geo hash key GeoKey gk = new GeoKey("gbsuv7ztqzpts82uzfwq5e1bp"); ``` ### Make a special purpose K-Dimensional key ```java public class GeoTimeKey extends KDKey { private static final KDKeySpec spec = new KDKeySpec.Builder() .addDim(-180, 180, 1) .addDim(-90, 90, 1) .addDim(0, 1L << 62, 1) .setAlphabet(Alphabet.GEO_TIME_HASH) .build(); public GeoTimeKey() { super(spec); } public GeoTimeKey(String s) { super(spec, s); } public GeoTimeKey(byte[] s) { super(spec, s); } public GeoTimeKey setLatitude(double latitude) { set(1, latitude); return this; } public double getLatitude() { return super.get(1); } public GeoTimeKey setLongitude(double longitude) { set(0, longitude); return this; } public double getLongitude() { return super.get(0); } public GeoTimeKey setTime(long time) { set(2, time); return this; } public long getTime() { return (long) get(2); } } ```

relay-jdbc allows a JDBC connection to be relayed through an intermediate relay server: it is both a JDBC driver (client) and a JDBC relay server. It is a fork of https://github.com/AugeoSoftware/VJDBC project, where Aleksei Yu. Semenov has implemented a number of brilliant improvements of the orignal VJDBC project hosted on http://vjdbc.sourceforge.net Original Developers were: Hunter Payne ([email protected]) and Michael Link ([email protected]). For all pre-existing code, credits go to the original respective author. This product brings the original VJDBC concept further and (apart from code quality improvements and bug fixes) implements complete separation of the underlying transport mechanism, introducing support for connecting directly through a SSH pipe, where the relay server interacts with the client through standard I/O pipes. The re-designed transport architecture supports easy development of new transport implementations, allowing this JDBC relay to be quickly adapted to a variety of exotic environments.

RuSH is an efficient, reliable, and easy adaptable rule-based sentence segmentation solution. It is specifically designed to handle the telegraphic written text in clinical note. It leverages a nested hash table to execute simultaneous rule processing, which reduces the impact of the rule-base growth on execution time and eliminates the effect of rule order on accuracy. If you wish to cite RuSH in a publication, please use: Jianlin Shi ; Danielle Mowery ; Kristina M. Doing-Harris ; John F. Hurdle.RuSH: a Rule-based Segmentation Tool Using Hashing for Extremely Accurate Sentence Segmentation of Clinical Text. AMIA Annu Symp Proc. 2016: 1587. The full text can be found at: https://knowledge.amia.org/amia-63300-1.3360278/t005-1.3362920/f005-1.3362921/2495498-1.3363244/2495498-1.3363247?timeStamp=1479743941616 This version allows defining section scopes for sentence segmentation.

RuSH is an efficient, reliable, and easy adaptable rule-based sentence segmentation solution. It is specifically designed to handle the telegraphic written text in clinical note. It leverages a nested hash table to execute simultaneous rule processing, which reduces the impact of the rule-base growth on execution time and eliminates the effect of rule order on accuracy. If you wish to cite RuSH in a publication, please use: Jianlin Shi ; Danielle Mowery ; Kristina M. Doing-Harris ; John F. Hurdle.RuSH: a Rule-based Segmentation Tool Using Hashing for Extremely Accurate Sentence Segmentation of Clinical Text. AMIA Annu Symp Proc. 2016: 1587. The full text can be found at: https://knowledge.amia.org/amia-63300-1.3360278/t005-1.3362920/f005-1.3362921/2495498-1.3363244/2495498-1.3363247?timeStamp=1479743941616