Less instrumentation. More insight. Physics-informed virtual sensors are shifting condition monitoring from isolated pilots ...
A key element to this paradigm shift is the deployment of a distributed sensor network that can continuously monitor water ...
Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...
Abstract: The development of rigorous theoretical tools, such as feasibility and stability analysis, for finite-control-set model predictive control (FCS-MPC) of electric drives, has lagged behind ...
OpenAI is finally rolling out a toggle that allows you to decide how hard the GPT-5-thinking model can think. This feature is rolling out to Plus and Pro subscribers. OpenAI has been testing the ...
Abstract: Model predictive control (MPC) achieves stability and constraint satisfaction for general nonlinear systems but requires computationally expensive online optimization. This brief studies ...
A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this research work authors have experimentally validated a blend of Machine ...
ABSTRACT: Objective: To develop and validate a machine learning-based risk prediction model for postoperative nausea and vomiting (PONV) following gynecological day hysteroscopy, providing ...
Center for Energy Informatics, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense, Denmark Building systems are dynamic and non-linear. In HVAC systems, independently ...
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