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Researchers at the National Institute of Standards and Technology (NIST) have developed a new statistical tool that they have used to predict protein function.
Have you ever wondered what it is about a smart city or community that makes it ‘smart?’ In an international collaboration with Dr. Martin Serrano of the
Part quality in additive manufacturing (AM) is highly variable due to inadequate dimensional tolerances, surface roughness, and defects, thereby limiting its
Payam Aminpour Mohammadabadi, Jennifer Helgeson, Paul Ferraro
Background To reduce the negative health effects from wildfire smoke exposure, effective risk and health communication strategies are vital. We estimated the
Zhuo Yang, Yan Lu, Milica Perisic, Yande Ndiaye, Adnan Gujjar, Fan-Tien Cheng, Haw-Ching Yang
In-situ measurements provide vast information for additive manufacturing process understanding and real-time control. Data from various monitoring techniques
Andrew Madison, John S. Villarrubia, Kuo-Tang Liao, Craig R. Copeland, Joshua Schumacher, Kerry Siebein, Robert Ilic, James Alexander Liddle, Samuel M. Stavis
This tool uses techniques from ASTM E3200 for evaluating manufacturing investments from the perspective of environmentally sustainable manufacturing by pairing
This tool calculates metrics for investment analysis documented in NIST Advanced manufacturing Series 200-5. It calculates net present value, internal rate of
The Engineering Laboratory has an established long-term collaboration with the NIST Statistical Engineering Division in the analysis of extreme wind speeds and