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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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The RAIN scale: A good intention that falls short
Radiation protection specialists agree that clear communication of radiation risks remains a vexing challenge that cannot be solved solely by finding new ways to convey technical information.
Earlier this year, an article in Nuclear News described a new radiation risk communication tool, known as the Radiation Index, or, RAIN (“Let it RAIN: A new approach to radiation communication,” NN, Jan. 2025, p. 36). The authors of the article created the RAIN scale to improve radiation risk communication to the general public who are not well-versed in important aspects of radiation exposures, including radiation dose quantities, units, and values; associated health consequences; and the benefits derived from radiation exposures.
T. Tambouratzis, M. Antonopoulos-Domis, M. Marseguerra, E. Padovani
Nuclear Science and Engineering | Volume 130 | Number 1 | September 1998 | Pages 113-127
Technical Paper | doi.org/10.13182/NSE98-A1994
Articles are hosted by Taylor and Francis Online.
The use of artificial neural networks (ANNs) for transit time estimation is investigated. ANNs are proposed as an alternative to widely employed traditional techniques such as cross correlation and the cross spectrum, which are sensitive to the presence of noise and require a large volume of data for their calculation. The ANN employed is based on interactive activation and competition and has been found able to correctly estimate the current transit time from short records of signals generated by simulation, quickly follow changes in transit time, and detect when the transit time falls outside a predefined expected range. By appending a backpropagation ANN, the on-line estimation of decimated transit times is also allowed.