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`Romaji` is a converter library to romanize Japanese hiragana/katakana string by standard and IME typing style. Even though [icu::Transliterator](http://userguide.icu-project.org/transforms/general) already has provided the same functions, and returns only one romanized string. However, there exists several different romanization systems, so one hiragana/katakana string has so many romanize string. For example, `"ちゃ"` can be romanized as `"cha"`, `"tya"`, `"chixya"`, `"tixya"`, `"chilya"`, or `"tilya"`. `Romaji` provides romanized strings as many as possible. If an input string contained non hiragana/katakana characters (includes kanji), `Romaji` return the characters as same as the input. For example, `Romaji` converts the input `"お茶の水"` to `"o茶no水"`. The mapping from hiragana/katakana to romaji is based on common IME's system to type Japanese on a computer. Therefor, `Romaji` does not directly implement the standard system like Hepburn, Nihon-shiki or Kunrei-shiki, but includes them.

GroupDocs.Watermark for Java is a powerful document watermarking API to add image and text watermarks. Furthermore, API works to search and remove the watermarks which were already added to the documents by other third-party softwares. The watermarks added by this API are hard to remove by any third-party tools. It is straight-forward and self-descriptive for integration into the custom applications. The most notable features are: - Add text and image watermarks into documents and images - Search for possible watermarks in documents and remove them - Support various document formats: Pdf; MS Office: Word, Excel, PowerPoint, Visio - Support various image formats: png, bmp, jpeg, jpeg2000, gif, tiff, webp (including multiframe gif and tiff) - Process documents and images attached to stored email messages (msg, oft, eml, emlx formats are supported) - Add watermarks to images inside documents of all supported formats - Two ways of watermark adding/removing are supported: using generalized approach and working with supported format specifics

JCQL is a tool allowing to generate boilerplate java code from existing cassandra schema. It is intended to be used with Cassandra 2.1+ due to support of UDTs (User Defined Types)/Tuples/Collections. Cassandra's UDTs/Tuples/Collections and an ability to introspect schema through java driver make it possible to automatically generate POJOs and corresponding mappers between database and java models. Properly generated java code saves development efforts and is less error-prone compared to hand coding. Accompanied with proper CI and deployment it can also guarantee consistency between database and java models at any point of application lifecycle from development to production rollout. JCQL does not rely on java reflection or annotations which means all discrepancies between actual cassandra schema and what client code expects it to be will be identified during compilation not at runtime in the middle of the night right after production release. No need to worry about Cassandra client code performance implications due to use of reflection.

Module that defines the HttpChannel API. HttpChannels abstract complex download and upload steps into a simple and easy to use NIO Channel. NIO Channels can be wrapped into an InputStream or OutputStream and used in any way you may find possible to. Aside from that, Channels can be used natively in most next-gen libraries, meaning that you don't even need to wrap anything, just start writing or reading data to or from the channel wth a ByteBuffer. Anyone using the library should try to rely on code from this module only and, only if necessary, on configuration classes that are implementation specific. Relying on any other resource or class is considered an error and should NOT be done. One of the most interesting usages of channels for uploads and download is that you can easily copy data straight from one channel to the other, with less than 10 lines of code! Also, channels allows the implementation of a "tee" mechanism, in which data redden from a single channel can be copied to several other channels on the fly!

<p>PMD scans Java source code and looks for potential problems like:</p> <ul> <li>Possible bugs - empty try/catch/finally/switch statements</li> <li>Dead code - unused local variables, parameters and private methods</li> <li>Suboptimal code - wasteful String/StringBuffer usage</li> <li>Overcomplicated expressions - unnecessary if statements, for loops that could be while loops</li> <li>Duplicate code - copied/pasted code means copied/pasted bugs</li> </ul> <p>You can <b><a href="http://sourceforge.net/project/showfiles.php?group_id=56262">download everything from here</a></b>, and you can get an overview of all the rules at the <a href="rules/index.html">rulesets index</a> page.</p> <p>PMD is <a href="integrations.html">integrated</a> with JDeveloper, Eclipse, JEdit, JBuilder, BlueJ, CodeGuide, NetBeans/Sun Java Studio Enterprise/Creator, IntelliJ IDEA, TextPad, Maven, Ant, Gel, JCreator, and Emacs.</p>

<p>PMD scans Java source code and looks for potential problems like:</p> <ul> <li>Possible bugs - empty try/catch/finally/switch statements</li> <li>Dead code - unused local variables, parameters and private methods</li> <li>Suboptimal code - wasteful String/StringBuffer usage</li> <li>Overcomplicated expressions - unnecessary if statements, for loops that could be while loops</li> <li>Duplicate code - copied/pasted code means copied/pasted bugs</li> </ul> <p>You can <b><a href="http://sourceforge.net/project/showfiles.php?group_id=56262">download everything from here</a></b>, and you can get an overview of all the rules at the <a href="rules/index.html">rulesets index</a> page.</p> <p>PMD is <a href="integrations.html">integrated</a> with JDeveloper, Eclipse, JEdit, JBuilder, BlueJ, CodeGuide, NetBeans/Sun Java Studio Enterprise/Creator, IntelliJ IDEA, TextPad, Maven, Ant, Gel, JCreator, and Emacs.</p>

OpenIMAJ (Open Intelligent Multimedia in Java) is a collection of libraries and tools for multimedia analysis written in the Java programming language. OpenIMAJ intends to be the first truly complete multimedia analysis library and contains modules for analysing images, videos, text, audio and even webpages. The OpenIMAJ image and video analysis and feature extraction modules contain methods for processing visual content and extracting state-of-the-art features, including SIFT. The OpenIMAJ clustering and nearest-neighbour libraries contain efficient, multi-threaded implementations of clustering algorithms including Hierarchical K-Means and Approximate K-Means. The clustering library makes it possible to easily create visual-bag-of-words representations for images and video with very large vocabularies. The text-analysis modules contain implementations of a statistical language classifier and low-level processing pipeline. A number of modules deal with content creation, including interactive slideshows and animations. The hardware integration modules allow cross-platform integration with devices including webcams, the Microsoft Kinect, and even devices such as GPS's. OpenIMAJ also incorporates a number of tools to enable extremely-large-scale multimedia analysis using a distributed computing approach based on Apache Hadoop.

Races the cross validation error of competing attribute subsets. Use in conjuction with a ClassifierSubsetEval. RaceSearch has four modes: forward selection races all single attribute additions to a base set (initially no attributes), selects the winner to become the new base set and then iterates until there is no improvement over the base set. Backward elimination is similar but the initial base set has all attributes included and races all single attribute deletions. Schemata search is a bit different. Each iteration a series of races are run in parallel. Each race in a set determines whether a particular attribute should be included or not---ie the race is between the attribute being "in" or "out". The other attributes for this race are included or excluded randomly at each point in the evaluation. As soon as one race has a clear winner (ie it has been decided whether a particular attribute should be inor not) then the next set of races begins, using the result of the winning race from the previous iteration as new base set. Rank race first ranks the attributes using an attribute evaluator and then races the ranking. The race includes no attributes, the top ranked attribute, the top two attributes, the top three attributes, etc. It is also possible to generate a raked list of attributes through the forward racing process. If generateRanking is set to true then a complete forward race will be run---that is, racing continues until all attributes have been selected. The order that they are added in determines a complete ranking of all the attributes. Racing uses paired and unpaired t-tests on cross-validation errors of competing subsets. When there is a significant difference between the means of the errors of two competing subsets then the poorer of the two can be eliminated from the race. Similarly, if there is no significant difference between the mean errors of two competing subsets and they are within some threshold of each other, then one can be eliminated from the race.

This project aims to offer an easy-to-extend Java DAS server framework. It offers several advantages: * Implementing data sources is very easy but also flexible and powerful. * Data caching is built into the system, with access to the caching mechanism made available to the data sources. * All aspects of the server are highly configurable, including selecting options where the DAS 1.53 specification offers choices to the implementor. * The latest Java technologies have been used throughout the system to optimise performance and simplify data source development. * Wherever possible the same terminology is used in the API as in the DAS specification and XML - again, making data source development more easy. * The server allows XSLT transforms of the DAS XML to be configured to provide a simple DAS client view (limited to the single DAS source). More details of the DAS protocol, DAS servers and DAS clients can be found at http://www.biodas.org/wiki/Main_Page. The first version of this server is a complete implementation of Distributed Sequence Annotation System (DAS) Version 1.53. If you are interested in learning more about DAS 1.53, the specification is highly recommended as a concise and complete description of the DAS protocol that can be obtained from: http://biodas.org/documents/spec.html

# pact-jvm-consumer-java8 Provides a Java8 lambda based DSL for use with Junit to build consumer tests. # A Lambda DSL for Pact This is an extension for the pact DSL provided by [pact-jvm-consumer](../pact-jvm-consumer). The difference between the default pact DSL and this lambda DSL is, as the name suggests, the usage of lambdas. The use of lambdas makes the code much cleaner. ## Why a new DSL implementation? The lambda DSL solves the following two main issues. Both are visible in the following code sample: ```java new PactDslJsonArray() .array() # open an array .stringValue(&quot;a1&quot;) # choose the method that is valid for arrays .stringValue(&quot;a2&quot;) # choose the method that is valid for arrays .closeArray() # close the array .array() # open an array .numberValue(1) # choose the method that is valid for arrays .numberValue(2) # choose the method that is valid for arrays .closeArray() # close the array .array() # open an array .object() # now we work with an object .stringValue(&quot;foo&quot;, &quot;Foo&quot;) # choose the method that is valid for objects .closeObject() # close the object and we&apos;re back in the array .closeArray() # close the array ``` ### The existing DSL is quite error-prone Methods may only be called in certain states. For example `object()` may only be called when you&apos;re currently working on an array whereas `object(name)` is only allowed to be called when working on an object. But both of the methods are available. You&apos;ll find out at runtime if you&apos;re using the correct method. Finally, the need for opening and closing objects and arrays makes usage cumbersome. The lambda DSL has no ambiguous methods and there&apos;s no need to close objects and arrays as all the work on such an object is wrapped in a lamda call. ### The existing DSL is hard to read When formatting your source code with an IDE the code becomes hard to read as there&apos;s no indentation possible. Of course, you could do it by hand but we want auto formatting! Auto formatting works great for the new DSL! ```java array.object((o) -&gt; { o.stringValue(&quot;foo&quot;, &quot;Foo&quot;); # an attribute o.stringValue(&quot;bar&quot;, &quot;Bar&quot;); # an attribute o.object(&quot;tar&quot;, (tarObject) -&gt; { # an attribute with a nested object tarObject.stringValue(&quot;a&quot;, &quot;A&quot;); # attribute of the nested object tarObject.stringValue(&quot;b&quot;, &quot;B&quot;); # attribute of the nested object }) }); ``` ## Installation ### Maven ``` &lt;dependency&gt; &lt;groupId&gt;au.com.dius&lt;/groupId&gt; &lt;artifactId&gt;pact-jvm-consumer-java8_2.12&lt;/artifactId&gt; &lt;version&gt;${pact.version}&lt;/version&gt; &lt;/dependency&gt; ``` ## Usage Start with a static import of `LambdaDsl`. This class contains factory methods for the lambda dsl extension. When you come accross the `body()` method of `PactDslWithProvider` builder start using the new extensions. The call to `LambdaDsl` replaces the call to instance `new PactDslJsonArray()` and `new PactDslJsonBody()` of the pact library. ```java io.pactfoundation.consumer.dsl.LambdaDsl.* ``` ### Response body as json array ```java import static io.pactfoundation.consumer.dsl.LambdaDsl.newJsonArray; ... PactDslWithProvider builder = ... builder.given(&quot;some state&quot;) .uponReceiving(&quot;a request&quot;) .path(&quot;/my-app/my-service&quot;) .method(&quot;GET&quot;) .willRespondWith() .status(200) .body(newJsonArray((a) -&gt; { a.stringValue(&quot;a1&quot;); a.stringValue(&quot;a2&quot;); }).build()); ``` ### Response body as json object ```java import static io.pactfoundation.consumer.dsl.LambdaDsl.newJsonBody; ... PactDslWithProvider builder = ... builder.given(&quot;some state&quot;) .uponReceiving(&quot;a request&quot;) .path(&quot;/my-app/my-service&quot;) .method(&quot;GET&quot;) .willRespondWith() .status(200) .body(newJsonBody((o) -&gt; { o.stringValue(&quot;foo&quot;, &quot;Foo&quot;); o.stringValue(&quot;bar&quot;, &quot;Bar&quot;); }).build()); ``` ### Examples #### Simple Json object When creating simple json structures the difference between the two approaches isn&apos;t big. ##### JSON ```json { &quot;bar&quot;: &quot;Bar&quot;, &quot;foo&quot;: &quot;Foo&quot; } ``` ##### Pact DSL ```java new PactDslJsonBody() .stringValue(&quot;foo&quot;, &quot;Foo&quot;) .stringValue(&quot;bar&quot;, &quot;Bar&quot;) ``` ##### Lambda DSL ```java newJsonBody((o) -&gt; { o.stringValue(&quot;foo&quot;, &quot;Foo&quot;); o.stringValue(&quot;bar&quot;, &quot;Bar&quot;); }).build(); ``` #### An array of arrays When we come to more complex constructs with arrays and nested objects the beauty of lambdas become visible! ##### JSON ```json [ [&quot;a1&quot;, &quot;a2&quot;], [1, 2], [{&quot;foo&quot;: &quot;Foo&quot;}] ] ``` ##### Pact DSL ```java new PactDslJsonArray() .array() .stringValue(&quot;a1&quot;) .stringValue(&quot;a2&quot;) .closeArray() .array() .numberValue(1) .numberValue(2) .closeArray() .array() .object() .stringValue(&quot;foo&quot;, &quot;Foo&quot;) .closeObject() .closeArray(); ``` ##### Lambda DSL ```java newJsonArray((rootArray) -&gt; { rootArray.array((a) -&gt; a.stringValue(&quot;a1&quot;).stringValue(&quot;a2&quot;)); rootArray.array((a) -&gt; a.numberValue(1).numberValue(2)); rootArray.array((a) -&gt; a.object((o) -&gt; o.stringValue(&quot;foo&quot;, &quot;Foo&quot;))); }).build(); ``` `object` is a reserved word in Kotlin. To allow using the DSL without escaping, a Kotlin extension `newObject` is available: ```kotlin newJsonArray { rootArray -&gt; rootArray.array { a -&gt; a.stringValue(&quot;a1&quot;).stringValue(&quot;a2&quot;) } rootArray.array { a -&gt; a.numberValue(1).numberValue(2) } rootArray.array { a -&gt; a.newObject { o -&gt; o.stringValue(&quot;foo&quot;, &quot;Foo&quot;) } } }.build(); ```