Conveners
Session 3: Sigma Data Challenge
- Adrian Bevan (Queen Mary University of London (GB))
Brief overview of the SIGMA data challenge, where it came from, who is involved and where it was intended to go.
The Poisson Functional Online Cumulative Sum (Poisson-FOCuS) method is a method for solving the likelihood ratio test of $\text{Poisson}( \lambda)$ null against $\text{Poisson}(\mu \lambda)$ alternative where $\mu > 1$, i.e. searching for an increase in count. This can be thought of as equivalent to testing all possible anomaly start points $\tau \leq T$ at each timestep $T$, giving a...
The threat from nuclear terrorism represents a complex challenge for global governments. Although current systems for detecting threats from illicit materials exist, each have inherent limitations. It is crucial that a system can detect material being transported with malicious intent which is likely to cause health risks and require extensive clean-up operations. One monitoring approach...
In order to reliably detect and identify weak radiological/nuclear sources in real-world environments while maintaining low probabilities of false alarm, it is necessary to employ algorithms that are able to account for temporally and spatially varying backgrounds, exploit the full information content of acquired spectra, and provide interpretable detection metrics.
Over the last several...
Overview of the GROUSE algorithm work done to date by AWE on the SIGMA
Data Challenge data.
Q&A from the Sigma Session, followed by Workshop conclusion
