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Argonne: Where AI research meets education and training
Last September, in the Chicago suburb of Lemont, Ill., Argonne National Laboratory hosted its first AI STEM Education Summit. More than 180 educators from high schools, community colleges, and universities; STEM administrators; and experts in various disciplines convened at “One Ecosystem, Many Pathways–Building an AI-Ready STEM Workforce” to discuss how artificial intelligence is reshaping STEM-related industries, including the implications for the nuclear engineering classroom and workforce.
A. Notea, Y. Segal
Nuclear Technology | Volume 24 | Number 1 | October 1974 | Pages 73-80
Technical Paper | Instrument | doi.org/10.13182/NT74-A31462
Articles are hosted by Taylor and Francis Online.
A procedure has been developed for characterization and optimization of gauges, based on nuclear or atomic radiation. It provides a logical and organized method to obtain the optimal design parameters of the gauge, limits of detection, resolving power, etc. The dominant concept in the procedure is a characterization function which correlates the variables that have to be measured, the design parameters of the gauge, its response and uncertainty. Gauges with linear and exponential responses were analyzed to demonstrate the generality of the approach and the use of the concepts.