TY - GEN
T1 - PEAKSEEK
T2 - 21st IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2009
AU - Forsberg, P.
AU - Agarwal, V.
AU - Perry, J.
AU - Gao, R.
AU - Tsoukalas, L. H.
AU - Jevremovic, T.
PY - 2009
Y1 - 2009
N2 - An accurate analysis of radiation data is essential in many nuclear related applications. In the intelligent Model Assisted Sensing System (iMASS) development, nuclear resonance florescence (NRF) spectra of radioactive isotopes are used for detection of nuclear material in cargo containers at US ports. The NRF spectrum of a particular radioactive isotope has a unique signature at unique energy levels. This paper presents a statistical processing algorithm, Peakseek, developed to identify radiation peaks in NRF spectra with a certain degree of confidence. The algorithm tracks the changes in the count rate ( fá) of the NRF spectrum and identifies the point of abrupt change in the count rate, i.e., energy level. Identification of abrupt changes in the count rate is performed on the basis of a generalized likelihood ratio statistical test.
AB - An accurate analysis of radiation data is essential in many nuclear related applications. In the intelligent Model Assisted Sensing System (iMASS) development, nuclear resonance florescence (NRF) spectra of radioactive isotopes are used for detection of nuclear material in cargo containers at US ports. The NRF spectrum of a particular radioactive isotope has a unique signature at unique energy levels. This paper presents a statistical processing algorithm, Peakseek, developed to identify radiation peaks in NRF spectra with a certain degree of confidence. The algorithm tracks the changes in the count rate ( fá) of the NRF spectrum and identifies the point of abrupt change in the count rate, i.e., energy level. Identification of abrupt changes in the count rate is performed on the basis of a generalized likelihood ratio statistical test.
UR - https://www.scopus.com/pages/publications/77949500456
U2 - 10.1109/ICTAI.2009.97
DO - 10.1109/ICTAI.2009.97
M3 - Conference contribution
AN - SCOPUS:77949500456
SN - 9781424456192
T3 - Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI
SP - 674
EP - 678
BT - ICTAI 2009 - 21st IEEE International Conference on Tools with Artificial Intelligence
PB - IEEE Computer Society
Y2 - 2 November 2009 through 5 November 2009
ER -