Adaptive Assay

  • Yakov Ben-Haim
Part of the Mathematics and Its Applications book series (MAIA, volume 20)


The assay of material is comprised of four fundamental tasks: modelling, design, measurement and interpretation. These may be arranged as in figure 6.1.1. The model of the sample must provide all available information pertinent to the design process. The sample model constitutes the input upon which the design analysis is performed. The optimization of an assay-system design is based on a measure of performance: an index which quantitatively evaluates the performance of a proposed design, in the face of defined spatial, statistical or other uncertainties. For a given definition of the assay problem, including precise statement of the uncertainties involved, the measure of performance enables rational selection of the assay-system design. Data interpretation is based on a decision rule whereby information about the sample is extracted from measurements obtained by the assay system. The past four Chapters have been devoted to a thorough study of design-optimization and data-interpretation.


Statistical Uncertainty Design Algorithm Fisher Information Matrix Uranium Deposit Detector Position 
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  1. [1]
    See refs. [1.4] and [2.1] of Chapter 5. Also see Also see A. Wald, Sequential Analysis, John Wiley, 1947.Google Scholar
  2. [2]
    J. O. Berger, Statistical Decision Theory, Springer Verlag, 1980.zbMATHGoogle Scholar
  3. [3]
    Y. Ben‐Haim and A. Kushelevsky, Assay of Pu‐Aerosol in Human Lungs — Instrument Design and Data‐Interpretation, IAEA‐ WHO Internatl. Symp. on Assessment of Radioactive Contamination in Man, paper IAEA‐SM‐276/3, Paris, Nov. 1984.Google Scholar
  4. [4]
    Numerous papers in the Symposium of ref. [3] discuss various instrumental methods for assay of internal radioactive contamination. For examples, seeGoogle Scholar
  5. 1.
    R. C. Lane et. al., The Use of Six‐Element Arrays of Hyperpure Ge Detectors in Monitoring for Internal Actinide Contamination. Paper IAEA‐SM‐276/24.Google Scholar
  6. 2.
    T. Rahola et. al., The Advantage of Using A Semiconductor Detector for Determination of Internal Radioactive Contamination. Paper IAEA‐SM‐276/10.Google Scholar
  7. 3.
    C. Pomroy and H. Malm, Hyperpure Ge Detectors for In Vivo Measurements of U and Th. Paper IAEA-SM-276/49.Google Scholar
  8. 4.
    D. Hernandez, M. Righetti and J. Chagaray, Measurement of 239Pu and 241 Am with CsI(Tl) and I2Hg Detectors. Paper IAEA‐ SM‐276/64.Google Scholar
  9. An comparison of detector types may be found in:Google Scholar
  10. 5.
    S. Mizushita, Relative Sensitivity of Hyperpure Ge Detector Array and Phoswich Detectors in Assessment of Pu and Am in Lungs, J. Nucl. ScL Tech., 21: 775 – 85 (1984).CrossRefGoogle Scholar

Copyright information

© D. Reidel Publishing Company, Dordrecht, Holland 1985

Authors and Affiliations

  • Yakov Ben-Haim
    • 1
  1. 1.Department of Nuclear EngineeringTechnion-Israel Institute of TechnologyIsrael

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