Peak-tracking BOTDA with dynamic ternary search.

We propose a peak-tracking BOTDA (PT-BOTDA) equipped with an efficient dynamic Brillouin frequency shift (BFS) searching scheme based on ternary search. The proposed scheme establishes a feedback loop between the selected frequency and the corresponding Brillouin gain to reduce the required number of scanning frequencies in one measurement. We also demonstrate the performance evaluation of the proposed scheme under scenarios with different searching granularities and dynamic sensing ranges. Experimental results indicate that in all situations, the proposed PT-BOTDA can achieve at least 85% and 97% reduction in the number of scanning frequencies for 1-MHz and 0.1-MHz frequency steps, respectively, with a 3-meter spatial resolution, while maintaining a convincing BFS searching accuracy under sufficient SNR condition using a smaller searching interval.

Real-time forecast of multiphase outbreak.

We used a single equation with discrete phases to fit the daily cumulative case data from the 2003 severe acute respiratory syndrome outbreak in Toronto. This model enabled us to estimate turning points and case numbers during the 2 phases of this outbreak. The 3 estimated turning points are March 25, April 27, and May 24. The estimated case number during the first phase of the outbreak between February 23 and April 26 is 140.53 (95% confidence interval [CI] 115.88-165.17) if we use the data from February 23 to April 4; and 249 (95% CI: 246.67-251.25) at the end of the second phase on June 12 if we use the data from April 28 to June 4. The second phase can be detected by using case data just 3 days past the beginning of the phase, while the first and third turning points can be identified only approximately 10 days afterwards. Our modeling procedure provides insights into ongoing outbreaks that may facilitate real-time public health responses.