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Dr. Marius P. Schamschula

Research Interests

Computational Physics: Artificial Neural Networks, Genetic Algorithms, Remote Sensing/GIS, Hydrology, Space Weather, and Computer Clusters
Optics: Compact Systems, Optical Information Processing and Database Management, Interconnections, Pattern Recognition, Time Delays, Panoramic Lenses, and Photorefractive Wave Mixing and Phase Conjugation

Contact
Office: 142 V. M. Chambers Bld.
Phone:(256) 372-8226 (Office), (256) 513-9859 (Google Voice)
E-Mail: marius@physics.aamu.edu
Home Page: http://optics.physics.aamu.edu/~marius/

Recent Publications
  1. R. Inguva, J. l. Johnson, and M. P. Schamschula, "Multifeature Fusion Using Pulse Coupled Neural Networks," Proc. SPIE 3719, 342-350 (1999)
  2. J. Fu, M. P. Schamschula, and H. J. Caulfield, "Optical parallel database management system for page oriented holographic memories," Opt. Express 5 #12273-285 (1999)
  3. M. P. Schamschula, J. L. Johnson, and R. Inguva, "Image Processing with Pulse Coupled Neural Networks," The Second International Forum on Multimedia and Image Processing, World Automation Congress, Maui (2000)
  4. H. J. Caulfield, J. L. Johnson, M. P. Schamschula, and R. Inguva, "A general model of primitive consciousness," Cognitive Systems Research 2, 263-272 (2001)
  5. W. L. Crosson, C. A. Laymon and M. P. Schamschula, "Disaggregation of microwave remote sensing data for estimating near-surface soil moisture using a neural network," Preprint Vol. of 16th Conf. on Hydrology (January 13-17, Orlando, FL), Amer. Meteor. Soc., Boston, MA, 85-90 (2002)
  6. W. L. Crosson, C. A. Laymon, R. Inguva and M. Schamschula, "Assimilating remote sensing data in a surface flux-soil moisture model," Hydrol. Proc. 16, 1645-1662 (2002)
  7. M. Schamschula, W. L. Crosson, C. A. Laymon, and R. Inguva, "Disaggrregation of Remotely Sensed Soil Moisture Using Neural Networks" World Automation Congress, Orlando, FL (2002)
  8. W. Crosson, C. Laymon, A. Limaye, W. Khairy, M. Schamschula, T. Coleman and R. Inguva, "Assimilation of remote sensing data in a hydrologic model to improve estimates of spatially distributed soil moisture," Proceedings of IGARSS, International Geoscience and Remote Sensing Symposium (June 24-28, Toronto, Canada), 1168-1170 (2002)
  9. T. D. Tsegaye, W. L. Crosson, C. A. Laymon, M. P. Schamschula, and A. B. Johnson, "Application of a Neural Network-Based Spatial Disaggregation Scheme for Addressing Scaling of Soil Moisture," in Scaling Methods in Soil Physics, Y. Pachepsky, D. E. Radcliffe, and H. M. Selim (Eds.), CRC Press, Boca Raton, 261-278 (2003)
  10. T. D. Tsegaye, R. Metzl, X. Wang, M. Schamschula, W. Tadesse, D. Clendenon, K. Golson, T. L. Coleman, and G. Schaefer, "A long-term near real time database of meteorological/soil profile data: The Alabama Mesonet (ALMNet)," International Symposium on Remote Sensing of Environment, Saint Petersburg, Russia (2005)