Processing Stamp Bags for Latent Prints: Impact of Rubric Selection and Gray-Scaling on Experimental Results

We report data on two open issues in our previous experimentation seeking an effective method for development of latent prints on glassine drug bags: (1) the choice of rubric to assess the quality of fingerprints and (2) the choice of whether to use color or gray-scale images. Two research projects were performed to evaluate the impact of the rubric choice and the color adjustments applied. The Dove rubric is preferable to the modified rubric previously used. Analysts report a more uniform application and a more thorough analysis resulting in an upward trend in scores. Although gray-scaling in experimentation is necessary to conceal which treatment was employed, native color images are preferable for casework. The results of this research quantitatively show the impact of native color as measured by the Dove rubric

Bayes linear kinematics in the analysis of failure rates and failure time distributions

Collections of related Poisson or binomial counts arise, for example, from a number of different failures in similar machines or neighbouring time periods. A conventional Bayesian analysis requires a rather indirect prior specification and intensive numerical methods for posterior evaluations. An alternative approach using Bayes linear kinematics in which simple conjugate specifications for individual counts are linked through a Bayes linear belief structure is presented. Intensive numerical methods are not required. The use of transformations of the binomial and Poisson parameters is proposed. The approach is illustrated in two examples, one involving a Poisson count of failures, the other involving a binomial count in an analysis of failure times

Computation of Carlson's Multiple Hypergeometric Function R for Bayesian Applications

1 online resource (PDF, 31 pages

Evaluation of elicitation methods to quantify Bayes linear models

The Bayes linear methodology allows decision makers to express their subjective beliefs and adjust these beliefs as observations are made. It is similar in spirit to probabilistic Bayesian approaches, but differs as it uses expectation as its primitive. While substantial work has been carried out in Bayes linear analysis, both in terms of theory development and application, there is little published material on the elicitation of structured expert judgement to quantify models. This paper investigates different methods that could be used by analysts when creating an elicitation process. The theoretical underpinnings of the elicitation methods developed are explored and an evaluation of their use is presented. This work was motivated by, and is a precursor to, an industrial application of Bayes linear modelling of the reliability of defence systems. An illustrative example demonstrates how the methods can be used in practice