Developed web-based system [1] that integrates data
management and visual analysis to facilitate access to large amounts of
observational data, supporting algorithm development for finding radiological
material.
Significance and Impact
Finding radiological material can help prevent nuclear and radiological
attacks. Reliable detection in uncontrolled environments requires effective
algorithms that take observations (e.g., background radiation) into account.
Downloading the data and exploring it on an analyst’s desktop using traditional
tools are impractical due to the size of the data.
Research and Details
Integration of data management techniques (SQL, FastBit), web server
backend and modern HTML5-based front end to support interactive analysis on
web browsers
Use of FastBit to perform histogram computation for spectra on-the-fly,
avoiding the need to store pre-computed histograms and supporting flexible
parameter choice (bin-size)
Contact
Gunther H. Weber
Bibliography
G. H. Weber, M. S. Bandstra, D. Chivers, H. H. Elgammal, V. Hendrix, J. Kua, J. Maltz, K. Muriki, Y. Ong, K. Song, M. Quinlan, L. Ramakrishnan, and B. J. Quiter, “Web-based Visual Data Exploration for Improved Radiological Source Detection,” Concurrency and Computation: Practice and Experience, vol. 29, no. 18, p. e4203, Sep. 2017.
@article{Weber:2017:ARESVis,
author = {Weber, Gunther H. and Bandstra, Mark S. and Chivers, Daniel and Elgammal, Hamdy H. and Hendrix, Valerie and Kua, John and Maltz, Jonathan and Muriki, Krishna and Ong, Yeongshnn and Song, Kai and Quinlan, Michael and Ramakrishnan, Lavanya and Quiter, Brian J.},
title = {Web-based Visual Data Exploration for Improved Radiological Source Detection},
journal = {Concurrency and Computation: Practice and Experience},
volume = {29},
number = {18},
issn = {1532-0634},
month = sep,
pages = {e4203},
year = {2017},
doi = {10.1002/cpe.4203},
escholarshipurl = {https://escholarship.org/uc/item/14z1h9gr}
}