Download JAR files tagged by models with all dependencies

This open source software is a reference implementation, consisting of software and related files, for the OMG specification called the Semantics of a Foundational Subset for Executable UML Models (fUML). The reference implementation is intended to implement the execution semantics of UML activity models, accepting an XMI file from a conformant UML model as its input and providing an execution trace of the selected activity model(s) as its output. The core execution engine, which is directly generated from the normative syntactic and semantic models for fUML, may also be used as a library implementation of fUML in other software.

Azure Video Analyzer provides a platform to build intelligent video applications that span the edge and the cloud. The platform offers the capability to capture, record, and analyze live videos along with publishing the results, video, and video analytics, to Azure services in the cloud or the edge. It is designed to be an extensible platform, enabling you to connect different video analysis edge modules such as Cognitive services containers, custom edge modules built by you with open-source machine learning models or custom models trained with your own data. You can then use them to analyze live video without worrying about the complexity of building and running a live video pipeline. Use the client library for Video Analyzer Edge to simplify interactions with the Microsoft Azure IoT SDKs (https://github.com/azure/azure-iot-sdks) and programmatically construct pipeline topologies and live pipelines.

The Systems Biology Simulation Core Library provides an efficient and exhaustive Java™ implementation of methods to interpret the content of models encoded in the Systems Biology Markup Language (SBML) and its numerical solution. This library is based on the JSBML project. It can be used on every operating system for which a Java Virtual Machine is available. Version 2.0 and beyond support simulation in three frameworks: constraint-based analysis, stochastic simulation, and ordinary differential equation systems. SBSCL supports SED-ML and COMBINE archives in OMEX format.