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Energy and infrequent fluctuations of temperature related to atmospheric mechanisms for various climate change scenarios (2021)
Conference Proceeding
Danaila, L., Chun, K., & Massei, N. (2021). Energy and infrequent fluctuations of temperature related to atmospheric mechanisms for various climate change scenarios. In Bulletin of the American Physical Society

Understanding, modeling, and predicting complex systems such as climate require coupling distinct phenomena, acting at different space/temporal scales: wavelike features, and turbulent cascade, with different regimes, crucial for mixing and dissipat... Read More about Energy and infrequent fluctuations of temperature related to atmospheric mechanisms for various climate change scenarios.

Efficient shapelet discovery for time series classification (extended abstract) (2021)
Conference Proceeding
Li, G., Choi, B. K. K., Xu, J., Bhowmick, S. S., Chun, K. P., & Wong, G. L. (2021). Efficient shapelet discovery for time series classification (extended abstract). In 2021 IEEE 37th International Conference on Data Engineering (ICDE) (2336-2337). https://doi.org/10.1109/ICDE51399.2021.00254

Time-series shapelets are discriminative subsequences, recently found effective for time series classification (TSC). It is evident that the quality of shapelets is crucial to the accuracy of TSC. However, major research has focused on building accur... Read More about Efficient shapelet discovery for time series classification (extended abstract).

Shapenet: A shapelet-neural network approach for multivariate time series classification (2021)
Conference Proceeding
Li, G., Choi, B., Xu, J., Bhowmick, S. S., Chun, K., & Wong, G. L. (2021). Shapenet: A shapelet-neural network approach for multivariate time series classification. In Proceedings of the AAAI Conference on Artificial Intelligence (8375-8383)

Time series shapelets are short discriminative subsequences that recently have been found not only to be accurate but also interpretable for the classification problem of univariate time series (UTS). However, existing work on shapelets selection can... Read More about Shapenet: A shapelet-neural network approach for multivariate time series classification.

Visualet: Visualizing shapelets for time series classification (2020)
Conference Proceeding
Li, G., Choi, B., Bhowmick, S. S., Wong, G. L., Chun, K. P., & Li, S. (2020). Visualet: Visualizing shapelets for time series classification. In Proceedings of the 29th ACM International Conference on Information \& Knowledge Management (3429-3432). https://doi.org/10.1145/3340531.3417414

Time series classification (TSC) has attracted considerable attention from both academia and industry. TSC methods that are based on shapelets (intuitively, small highly-discriminative subsequences have been found effective and are particularly known... Read More about Visualet: Visualizing shapelets for time series classification.

Ice jam flood hazard assessment and mapping of the Peace River at the Town of Peace River (2015)
Conference Proceeding
Lindenschmidt, K., Das, A., Rokaya, P., Chun, K., & Chu, T. (2015). Ice jam flood hazard assessment and mapping of the Peace River at the Town of Peace River. In 18th Workshop on the Hydraulics of Ice Covered Rivers (18-21)

Efforts are underway in Canada to develop, update and extend flood risk assessments and mapping for river sections prone to flooding. However, most of these previous works are limited to the open-water case. Very little has been done to include flood... Read More about Ice jam flood hazard assessment and mapping of the Peace River at the Town of Peace River.