academics

Highlights, Special Features and Opportunities

Below is just a sample of some of the exciting research happening in our department, and a few of our faculty’s related publications:

Bioinformatics: Modern medical treatment relies more on targeting treatment towards a patient’s genome in order to improve the effectiveness of treatment. The primary focus of this study could help in developing future personalized medicine tests for the treatment of cancer.

Dan Day and Daniel L. Swets, “Finding Gene Patterns in Cancer Patients and Linking Biological Databases Together,” Council on Undergraduate Research Posters on the Hill, 2008.

Satellite Image Processing: Satellite imagery provides a unique vantage point for observing seasonal dynamics of the landscape that have implications for global change issues. This project helps to more efficiently reduce contamination in satellite signals from the National Oceanic and Atmospheric Administration.

Stuart Ness and Daniel Swets, “Heritage and Future: Transitioning from AVHRR to MODIS,” in Proceedings of the South Dakota Academy of Science, Vol. 85, 2006.

Paul Marshall and Daniel Swets, “Statistical Software for Satellite Image Processing,” in Proceedings of the South Dakota Academy of Science, Vol. 85, 2006.

B. C. Reed, D. Swets, L. Bard, J. Brown, J. Rowland, “Interactive visualization of vegetation dynamics,” in Proceedings, International Geoscience and Remote Sensing Symposium (IGARSS), 2001.

High-Performance Computing: The advent of parallel processing has opened new frontiers in the ability for computers to solve previously intractable problems.

Paul Marshall and Daniel Swets, “Developing Parallel Algorithms for Seasonal Metrics Extraction,” in Proceedings of the South Dakota Academy of Science, Vol. 84, 2005.

Paul Marshall, Andrew Reinartz, and Daniel L. Swets, “Developing Parallel Algorithms for Seasonality Analysis,” Council on Undergraduate Research Posters on the Hill, 2005.

Daniel L. Swets, Tim Stavenger, and Jeri Peterson, “Parallel NDVI Smoothing Algorithm Comparison: A Study using a Windows-based PVM cluster and a multithreaded implementation,” in Proceedings, 30th International Symposium on Remote Sensing of the Environment (ISRSE), 2003.