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A probabilistic chemical sensor model for data fusion
For a data fusion system, taking data from chemical sensors and making inference about the source parameters of a chemical release in real time, a reversible probabilistic sensor model is proposed.Expand
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Model-based inferences from adaptive cluster sampling
Abstract. Adaptive cluster sampling is useful for exploring populations of rareplant and animal species which cluster together because it allows sampling e ortto be concentrated in areas whereExpand
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Realtime sequential inference of static parameters with expensive likelihood calculations
A methodology is developed for making inference about parameters of a possible covert chemical or biological atmospheric release from sensor readings. The key difficulty in performing this inferenceExpand
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Biological Source Term Estimation Using Particle Counters and Immunoassay Sensors
Two simple probabilistic sensor models for detection of airborne biological agents are described. The first of these models contains a construct to account for the ambient atmospheric particleExpand
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