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AutoTutor is an intelligent tutoring system developed by researchers at the Institute for Intelligent Systems at the University of Memphis, including Arthur C. Graesser that helps students learn Newtonian physics, computer literacy, and critical thinking topics through tutorial dialogue in natural language.
It refers to computing tools that help calculating the complex particle interactions as studied in high-energy physics, astroparticle physics and cosmology. The goal of the automation is to handle the full sequence of calculations in an automatic (programmed) way: from the Lagrangian expression describing the physics model up to the cross ...
VisSim - system simulation and optional C-code generation of electrical, process, control, bio-medical, mechanical and UML State chart systems. Vortex (software) - a complete simulation platform featuring a realtime physics engine for rigid body dynamics, an image generator, desktop tools (Editor and Player) and more. Also available as Vortex ...
Its interface can be used to create diagrams such as flowcharts, wireframes, UML diagrams, organizational charts, and network diagrams. [5] diagrams.net is available as an online web app, and as an offline desktop application for Linux, macOS, and Windows. [5] Its offline application is built using the Electron framework.
Generalized Intelligent Framework for Tutoring (GIFT) is an educational software designed for creation of computer-based tutoring systems. Developed by the U.S. Army Research Laboratory from 2009 to 2011, GIFT was released for commercial use in May 2012. [82] GIFT is open-source and domain independent, and can be downloaded online for free.
Physics-informed neural networks for solving Navier–Stokes equations. Physics-informed neural networks (PINNs), [1] also referred to as Theory-Trained Neural Networks (TTNs), [2] are a type of universal function approximators that can embed the knowledge of any physical laws that govern a given data-set in the learning process, and can be described by partial differential equations (PDEs).
Open Source Physics, or OSP, is a project sponsored by the National Science Foundation and Davidson College, whose mission is to spread the use of open source code libraries that take care of a lot of the heavy lifting for physics: drawing and plotting, differential equation solvers, exporting to animated GIFs and movies, etc., tools, and compiled simulations for physics and other numerical ...
For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...