Results 241 to 250 of about 4,040,361 (305)

WaterRAG: A Multiagent Retrieval-Augmented Generation Framework to Support Water Industry Transitions to Net-Zero. [PDF]

Environ Sci Technol
Zhai M, Zeng Q, Qiu R, Li J, Zhu Q, Waite TD, Ni BJ, Duan H.   +7 more
europepmc   +1 more source

Design and Implementation of an IoT-Based Low-Power Wearable EEG Sensing System for Home-Based Sleep Monitoring. [PDF]

Sensors (Basel)
Wang Y, Chen JB, Chen YT.
europepmc   +1 more source

Machine learning models for smart grid stability prediction: a comparative analysis. [PDF]

Sci Rep
Ali AM, Dawoud OK, Ghoneim OA, Abdel-Basset M.   +3 more
europepmc   +1 more source

Correlation analysis and prediction models for loess compressibility in Ili region, Xinjiang. [PDF]

PLoS One
Liu Z, Chen L, Chen K, Zhang Z, Chang J.
europepmc   +1 more source

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Introducing Model-Based System Engineering Transforming System Engineering through Model-Based Systems Engineering

2014
Abstract : In 2013, Naval Air Systems Command (NAVAIR) at the Naval Air Station, Patuxent River, Maryland initiated a research task (RT-48) to assess the technical feasibility of creating/leveraging a more holistic Model-Based Systems Engineering (MBSE) approach to support Mission-based Analysis and Engineering in order to achieve a 25% reduction in ...
Eirik Hole, Gary Witus, Rob Cloutier, Mark Blackburn   +3 more
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Smart Model Based Systems Engineering

SAE Technical Paper Series, 2018
<title>ABSTRACT</title> <p>Model Based Systems Engineering (MBSE) has been a dominant methodology for defining and developing complex systems; however, it has not yet been paired with cutting-edge digital engineering transformation. MBSE is constrained to
Alejandro Ayala, Jonathan Weaver, Jenifer Fuentes, Ruben Ochoa   +3 more
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Model-Based Systems Engineering Uptake in Engineering Practice

IEEE Transactions on Engineering Management, 2020
Modeling is ubiquitous in engineering, but data on model use and user sophistication in engineering-driven firms are remarkably sparse. Some authors have predicted a sea change in engineering workflow through model-based systems engineering. Despite benefits, the prevalence of effective modeling techniques in industry is an open question.
Bruce Cameron, Daniel Mark Adsit
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Model-Based Systems Engineering

2015
Today, we expect our systems to be highly sophisticated, intelligent, intuitive, robust, adaptive, and reliable. As technology, especially computational technology, has increased, so has our ability to imagine and develop even more capable and complex systems. This has progressed to the point where it is rare for an individual to understand all aspects
openaire   +2 more sources