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Biomedical Sector

Original Research Projects


  • The assessment and detection of global warming is of great concern to the world now. This project aimed to detect quantitative characteristics of observed climate changes and to develop a new mathematical theory for analyzing non-stationary and nonlinear remote-sensing signals. A key outcome was a master dataset for the latest version of the Alberta Agroclimatic Atlas. The dataset includes both digital data and map images. The agroclimatic changes over Alberta since 1901 to 2002 were quantitatively documented and the analysis shows that the Alberta agriculture has benefited from the changes. In addition, the team discovered internal upstream running solitons from satellite images over clouds, which can be used to predict severe weather. A major theoretical result was the establishment of the statistical confidence limit for the Hilbert-Huang Transform for analyzing nonlinear and non-stationary time series. An example was analyzed for the length-of-day data and the El Niño signals were detected from the data. All the results above have been published in refereed journals or books. This project was completed in 2004.

  • This project aimed to understand the behaviour of infectious disease process in a population in order to prevent its establishment, control its spread, and reduce its ability to persist. Hospital infection, pandemics and bio-terrorist attacks are becoming a global concern. Mathematical modeling is indispensable as infectious disease data are not the result of controlled experiments but are part of observational data arising from complex naturally occurring phenomena. This project completed in June 2002.