send the data without any lost under the poor coverage of the mobile network in rural part in Fukushima. Result indicates that a combination of both energies has given best estimation due to a reduction in overall noise which helped in demarcating geological entities and litho-contacts. 5 IAEA, 2003, Guidelines for radioelement mapping using gamma ray spectrometry data, IAEA-TECDOC-1363. Figure 6: KURAMA-II under the eld test on a city bus. Uranium is estimated using above two energies individually and in combination, using multi-channel processing followed by standard corrections procedure. IAEA 1999 Generic procedures for monitoring in a nuclear or radiological emergency. Multi-channel processing is applied on this dataset to reduce the spectral noise and use of combined 1.12 MeV and 1.76 MeV has reduced the PoissonвЂ™s related statistical error.

IAEA-TECDOC-1363, Guidelines for radioelement mapping using gamma ray spectrometry data, IAEA, Vienna. As a case study, the AGRS data of northern part of Cuddapah Basin is considered. IAEA-CU-2007-03, World-wide open proficiency test. Present study examines the utility of gamma rays of energies 1.12 MeV and 1.76 MeV of uranium in estimation of uranium in airborne gamma ray spectrometric survey (AGRS) in comparison to the conventional 1.76 MeV alone used world wide. These cps values of 40K, 238U, and 232Th were compared to the activity. Furthermore, as these methods have become more practical during the past decade, it is foreseen that the popularity of learning-based methods in nuclear science and technology will increase consequently, understanding the benefits and barriers of implementing such methodologies can help create better research plans, and identify project risks and opportunities.Estimation of uranium from multichannel spectra in airborne gamma ray spectrometry using 1.12 MeV and 1.76 MeV photopeaks of 214Bi - An application to Cuddapah Basin Estimation of uranium from multichannel spectra in airborne gamma ray spectrometry using 1.12 MeV. cumulated gamma spectrum using the method described by the IAEA report TECDOC-13639. The principles of learning-based methods in these applications are explained and recent studies are explored. These are reactor health and monitoring, radiation detection, and optimization.

This paper focuses on applications related to three key subareas related to safety and decision-making.

Improvements are expected by:-Increasing counting statistics and-Construction of calibration pads facility. 2 American National Standard for calibration and use of Germanium Spectrometers for the measurement of Gamma-Ray emission rates of radionuclides. This survey presents an overview of the fundamentals of artificial intelligence and the state of development of learning-based methods in nuclear science and engineering to identify the risks and opportunities of applying such methods to nuclear applications. The calibration was performed based on FSA-NNLS method and standard spectra of K, U, Th, Cs and Bckgwere obtained. To do so, it is important to understand the fundamentals between the disciplines to effectively develop and deploy such systems. 22 INTERNATIONAL ATOMIC ENERGY AGENCY, Guidelines for Radioelement Mapping using Gamma Ray Spectrometry. Nuclear technology industries have increased their interest in using data-driven methods to improve safety, reliability, and availability of assets.

Iaea tecdoc 1363