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GroupDocs.Signature for Java allows developers to write applications with ability to significantly sign electronic docs and verify them. Signatures can be of different types. API supports multitude of file formats and includes Pdf, Microsoft Office documents, Open Office formats, PowerPoint presentations, Images etc. The quite captivating fact about the API is, its UI less and independent calls can be made. It also provides a useful features to verify signed documents with stored signatures. Signature Types: - Text Signature - Image Signature - Digital Signature - Barcode Signature - QR-Code Signature - Stamp Signature Verification Types: - Text Signature - Digital Signature - Barcode Signature - QR-Code Signature For more details on the library, please visit GroupDocs website at: http://groupdocs.com/products/signature/java Note: The library comes up with some limitations in the evaluation mode. In order to test full features of GroupDocs.Signature for Java library, please request a free 30-day temporary license.

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

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

ASV Toolbox is a modular collection of tools for the exploration of written language data. They work either on word lists or text and solve several linguistic classification and clustering tasks. The topics covered contain language detection, POS-tagging, base form reduction, named entity recognition, and terminology extraction. On a more abstract level, the algorithms deal with various kinds of word similarity, using pattern based and statistical approaches. The collection can be used to work on large real world data sets as well as for studying the underlying algorithms. The ASV Toolbox can work on plain text files and connect to a MySQL database. While it is especially designed to work with corpora of the Leipzig Corpora Collection, it can easily be adapted to other sources.

JSONXML project is library used to parse/format tree-like object structures in most popular text formats: XML and JSON. For parsing it accepts "java.io.Reader" and return java object. For formatting it accepts java object and "java.io.Writer". Object is generally structure that contains Map and/or List elements. Map is ordered set of named items. List is set of unnamed items. Reflection may be used to convert objects into set of maps/lists and vice versa. JSON parser is implemented explicitly. XML parser is based on SAX parser and applies only certain rules for result. Library is designed to allow various entry points for variable decisions depending on end use needs. 1. Formats - formats are used to enable locale-specific parsing/formatting of numbers and dates. 2. ReflectiveBuilder - enables reflection. Default implementation uses getters/setters only. 3. ObjectsRegistry - used to keep track of parsed or formatted objects and allow resolvable references in formatted (text) form.

The boilerpipe library provides algorithms to detect and remove the surplus "clutter" (boilerplate, templates) around the main textual content of a web page. The library already provides specific strategies for common tasks (for example: news article extraction) and may also be easily extended for individual problem settings. Extracting content is very fast (milliseconds), just needs the input document (no global or site-level information required) and is usually quite accurate. Boilerpipe is a Java library written by Christian Kohlschütter. It is released under the Apache License 2.0. The algorithms used by the library are based on (and extending) some concepts of the paper "Boilerplate Detection using Shallow Text Features" by Christian Kohlschütter et al., presented at WSDM 2010 -- The Third ACM International Conference on Web Search and Data Mining New York City, NY USA.

Show color codes preview per line in a sidebar area of an editor. <h2>Disable / Enable</h2> Check/Uncheck View > Show Colors <h2>Supported color patterns</h2> <ul> <li>Hex color code (e.g. #ffffff, #000)</li> <li>Css rgb/rgba values (e.g. rgb(0,0,0), rgba(255, 255, 255, 0.8))</li> <li>Css hsl/hsla values (e.g. hsl(0, 100%, 50%), hsla(120, 100%, 50%, 0.5))</li> <li>Named colors (e.g. red, blue)</li> <li>Java Color class (e.g. Color.black, new Color(100, 100, 100))</li> </ul> <h2>Multiple colors</h2> <ul> <li>Show top two colors in a sidebar if there are multiple colors in a line.</li> <li>If you want to check all colors, please click a specific rectangle. They will be shown as a list.</li> </ul> <h2>Change a color using the color chooser</h2> <ul> <li>Click a colored rectangle</li> <li>Click a color value of a list</li> <li>Select a new color in the color chooser</li> <li>An old color value will be changed to new one with the same format</li> </ul> <h2>Generate color codes</h2><p>You can generate color codes via a code generator(<kbd>Alt</kbd> + <kbd>Ins</kbd>).</p> <ol> <li>Run a code generator(Alt + Ins)</li> <li>Choose <code>Color...</code></li> <li>Choose format you expect (e.g. <code>new Color(r, g, b)</code>)</li> <li>Choose a color</li> <li>Click the OK button</li> <li>A color code is generated at the caret position</li> </ol> <h2>Options</h2> Tools > Options > Miscellaneous > Color Codes Preview <h3>Regex for enabled mime-types for Hex and CSS colors</h3> Default value is `^text/(x-)?(css|less|sass|scss)$`. If you would like to disable/enable some mime-types, please change the default regex. This pattern is used when the plugin checks a mime-type. <h3>Named Colors</h3> This option is `false` by default. If you would like to show named colors, please check it. <h2>NOTE</h2> <ul> <li>If you would like to show colors of `Color.decode(<hex>)` e.g. `Color.decode(#000000)`, Please add `java` to "Regex for enabled mime-types" of Hex and CSS e.g. (`^text/(x-)?(css|less|sass|scss|java)$`)</li> <li>Colors may be shown if they are not color codes. e.g. "#feature" contains #fea. This plugin recognizes it as a hex color code.</li> <li>If you use the GTK Look and Feel, you cannot change an alpha value in the color chooser.</li> <li>Hsl or hsla color values may not be changed correctly when you use the color chooser. (There may be 1% errors.)</li> </ul>

This plugin provides support for textlint. <h3>What&rsquo;s the textlint?</h3> <p>See <a href="https://github.com/textlint/textlint">https://github.com/textlint/textlint</a></p> <h3>Usage</h3> <h4>Install textlint and rules</h4> <p>Of course, it assumes that nodejs and npm are installed.</p> <p>e.g.</p> <pre><code>$ mkdir txtlint $ cd txtlint $ npm init $ npm install textlint --save-dev $ npm install textlint-rule-max-ten textlint-rule-spellcheck-tech-word textlint-rule-no-mix-dearu-desumasu --save-dev </code></pre> <h4>Create .textlintrc</h4> <pre><code>$ touch .textlintrc </code></pre> <pre><code class="json">{ &quot;rules&quot;: { &quot;max-ten&quot;: { &quot;max&quot;: 3 }, &quot;spellcheck-tech-word&quot;: true, &quot;no-mix-dearu-desumasu&quot;: true } } </code></pre> <p>You can also set parameters to Options (see below).</p> <h4>Set textlint and .textlintrc paths</h4> <p>Set paths to the Options (see below).</p> <p>e.g.</p> <ul> <li>textlint Path: /path/to/txtlint/node_modules/.bin/textlint (textlint.cmd in Windows)</li> <li>.textlintrc Path: /path/to/textlint/.textlintrc</li> </ul> <h4>Open Action Items window</h4> <ul> <li>Click Window > Action Items.</li> <li>Click &ldquo;Show action items for currently edited file only&rdquo; icon.</li> <li>Open your markdown or text file.</li> </ul> <h3>Options</h3> <p>Tools > Options > Editor > textlint</p> <ul> <li>textlint Path: Absolute path to textlint</li> <li>.textlintrc Path: Absolute path to .textlintrc</li> <li>Options : You can set options for the textlint command</li> <li>Enable in HTML files: To use the html plugin, you can check this</li> <li>Refresh on Save: To scan the document on save, you can check this (Checked by default)</li> <li>Show Annotations: To show annotations in the glyph gutter, you can check this (Checked by default)</li> </ul> <h3>Actions</h3> <h4>Fix</h4> <p>You have to save your file before you run this action.<br/> If there is a fixable rule&rsquo;s error, you can fix it. Right-click an item > Click <code>Fix</code>.<br/> To refresh items, your document is saved once.</p> <h4>Fix All</h4> <p>You have to save your file before you run this action.<br/> If there are fixable rule&rsquo;s errors, you can fix them. Right-click an item > Click <code>Fix All</code>.<br/> This action runs <code>textlint --fix</code> command.</p> <h4>Refresh</h4> <p>You can refresh results forcibly by the following action: Right-click your editor > Click "textlint Refresh".</p> <p>You can also set the shortcut key(Tools > Options > Keymap). </p> <h3>NOTE</h3> <ul> <li>The plugin scans only current file.</li> <li>The plugin does not refresh results automatically. Please save your file or run the refresh action.</li> <li>Use <code>UTF-8</code> as file encoding and <code>LF</code> as line endings.</li> <li>This plugin may not work properly in Windows. (Please try to check above.)</li> <li>If you cannot get expected results, just try to run the <code>textlint</code> commands once in your CLI.</li> </ul>

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.