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Dynamic Contaminant Identification in Water
Book chapter   Peer reviewed

Dynamic Contaminant Identification in Water

Craig C Douglas, J. Clay Harris, Mohamed Iskandarani, Chris R Johnson, Robert J Lodder, Steven G Parker, Martin J Cole, Richard Ewing, Yalchin Efendiev, Raytcho Lazarov, …
Computational Science – ICCS 2006, pp.393-400
Lecture Notes in Computer Science, Springer Berlin Heidelberg
2006

Abstract

Spectral Element Kalman Filter Approach Markov Chain Monte Carlo Spectral Element Method Hyperspectral Imaging
We describe how we plan to convert a traditional data collection sensor and ocean model into a DDDAS enabled system for identifying contaminants and then reacting with different models, simulations, and sensing strategies in a symbiotic manner. The sensor is just as useful in water as it would be on Mars for material identification. A successful terrestrial application of the sensor will lead to many new applications of the device and possible technology transfer to the private sector.

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