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JARTs are Java-based Asynchronous Real Time sockets. JART uses JNA to build a pure Java TCP/IP stack upon Netmap. It is implemented in imperative style (no TCP state machine) using asynchronous programming with the help of ea-async. JART runs on both Linux (with the proper Netmap kernel module) and FreeBSD with Netmap enabled. FreeBSD 12.1+ has Netmap in the kernel by default so it works "out of the box". While JART has proven fairly robust in limited testing, it is still a work-in-progress and may not be suitable for production use. Pull requests welcome!

Mbassador is a fast and flexible event bus system following the publish subscribe pattern. It is designed for ease of use and aims to be feature rich and extensible while preserving resource efficiency and performance. It provides non-blocking iterators and minimal write contention with low memory footprint. Some features: declarative handler definition via annotations, sync and/or async event delivery, weak or strong references, configurable event filters,

Little Nanny is new type of Application to keep parents and their young children in touch. The idea is to reuse any old Smartphone (Android or iOS) as a high precision tracking device. After speaking with other parents, it was clear that there was a need for a really reliable App to help give children the freedom they need to explore and discover, while staying in touch with those who matter most. Little Nanny has a simple mission – to help kids be kids again, while giving parents an amazing new window into their children’s lives.

This class implements a single conjunctive rule learner that can predict for numeric and nominal class labels. A rule consists of antecedents "AND"ed together and the consequent (class value) for the classification/regression. In this case, the consequent is the distribution of the available classes (or mean for a numeric value) in the dataset. If the test instance is not covered by this rule, then it's predicted using the default class distributions/value of the data not covered by the rule in the training data.This learner selects an antecedent by computing the Information Gain of each antecendent and prunes the generated rule using Reduced Error Prunning (REP) or simple pre-pruning based on the number of antecedents. For classification, the Information of one antecedent is the weighted average of the entropies of both the data covered and not covered by the rule. For regression, the Information is the weighted average of the mean-squared errors of both the data covered and not covered by the rule. In pruning, weighted average of the accuracy rates on the pruning data is used for classification while the weighted average of the mean-squared errors on the pruning data is used for regression.

The Jeuron Application Platform is a lightweight framework to assemble software components intended to support multiple project and deployment scenarios while also providing an environment for testing and debugging. The platform is comprised of a set of packages which provide transport, messaging, configuration, and execution services designed to create a configurable, scalable, and distributed application environment. The low resource model permits the platform to be instantiated during each build cycle and to be deployed at all levels of the application hierarchy such as application servers, web servers, and mobile or wired workstations.

A Maven Mojo to download and "degenerate" non-maven projects into sources and binaries This MOJO is supposed to scrape and "de-generate" a zip file containing jars into a project's generated-sources folder, skipping items provided in the `src/` folder. It is intended to "mavenize-with-changes" an existing project and allow the user (of the Mojo) to replace classes which they do not have the ability/desire to recompile without setting up a full build. It can also be used to import non-maven projects by not changing anything. The itch I wanted to scratch was mostly to port libGDX to Maven, while replacing the native methods on Matrix4, without rebuilding the whole project. In essence - it's an alternative to patching someone else's project.

AODE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that have weaker (and hence less detrimental) independence assumptions than naive Bayes. The resulting algorithm is computationally efficient while delivering highly accurate classification on many learning tasks. For more information, see G. Webb, J. Boughton, Z. Wang (2005). Not So Naive Bayes: Aggregating One-Dependence Estimators. Machine Learning. 58(1):5-24.

JDOM is a Java-oriented object model which models XML documents. It provides a Java-centric means of generating and manipulating XML documents. While JDOM interoperates well with existing standards such as the Simple API for XML (SAX) and the Document Object Model (DOM), it is not an abstraction layer or enhancement to those APIs. Rather, it seeks to provide a robust, light-weight means of reading and writing XML data without the complex and memory-consumptive options that current API offerings provide. built July 23 2009

XBIS is an encoding format for XML documents that is fully convertible to and from text, with information set equivalence between the original document text and regenerated document text. It's intended for use in transmitting XML documents between application components, and is therefore designed for processing speed. The current Java language implementation offers several times the performance of SAX2 parsers working from text documents across a wide range of document types and sizes, and across JVMs tested, while also providing a substantial reduction in document size for most types of XML documents.