C.D. Hansen, S. Tenbrink. The Impact of Gigabit Network Research on Scientific Visualization, In The Visual Computer, Vol. 9, No. 6, pp. 318--323. 1993.
C.D. Hansen, M. Krogh. Visualization on Massively Parallel Computers using CM/AVS, In AVS Users Conference, Orlando, Fl., pp. 129--137. May, 1993.
P. Hinker, C.D. Hansen. Geometric Optimization, In Visualization 1993, San Jose, Ca., pp. 189--195. October, 1993.
C.R. Johnson, R.S. MacLeod. Inverse Solutions for Electric and Potential Field Imaging, In Physiological Imaging, Spectroscopy, andEarlyDetection Diagnostic Methods, Vol. 1887, Edited by R.L. Barbour and M.J. Carvlin, SPIE, pp. 130--139. 1993.
C.R. Johnson, R.S. MacLeod, M.A. Matheson. Computational Medicine: Bioelectric Field Problems, In IEEE Computer, Vol. 26, No. 26, pp. 59--67. Oct, 1993.
C.R. Johnson, R.S. MacLeod. High Performance Computing in Medicine: Direct and Inverse Problems in Cardiology, In IEEE Engineering in Medicine and Biology Society 15th Annual International Conference, pp. 582--583. 1993.
C.R. Johnson, R.S. MacLeod, M.A. Matheson, C. Zimmerman. The Body Electric, In Discover Magazine, pp. 72--77. February, 1993.
S. Joshi, M. Miller. Maximum a Posteriori Estimation with Good's Roughness for Three-Dimensional Optical-Sectioning Microscopy, In J Opt Soc Am A, Vol. 10, No. 5, pp. 1078--1085. May, 1993.
K.L. Ma, J. Painter, C.D. Hansen, M. Krogh. A Data Distributed, Parallel Algorithm for Ray-Traced Volume Rendering, In Proceedings of the Parallel Rendering Symposium 1993, San Jose, Ca., pp. 15--22. October, 1993.
K.L. Ma, J.S. Painter, C.D. Hansen, M.F. Krogh. A Data Distributed Parallel Algorithm for Ray-Traced Volume Rendering, ICASE Report, Hampton, VA, Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, pp. 15--22. August, 1993.
R.S. MacLeod, C.R. Johnson, M.A. Matheson. Visualization of Bioelectric Fields, In IEEE Computer Graphics and Applications, Vol. 14, pp. 10--12. Jul, 1993.
R.S. MacLeod, C.R. Johnson. Map3d: Interactive Scientific Visualization for Bioengineering Data, In Proceedings of the IEEE Engineering in Medicine and Biology Society 15th Annual International Conference, IEEE Press, pp. 30--31. 1993.
F. Ortega, C.D. Hansen, J. Ahrens. Fast Data Parallel Polygon Rendering, In Supercomputing 1993, Portland, Or., pp. 709--718. November, 1993.
A. Paoluzzi, V. Pascucci, M. Vicentino. PLASM Functional Approach to Design: Representation of Geometry, In Proceedings of the Fifth International Conference on Computer-Aided Design Futures (CAAD Futures '93), Edited by U. Flemming and S. Van Wyk, North-Holland, pp. 127--141. 1993.
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J. Parker, M. Berzins, J.M. Cameron, K.A. Collins, C.M. Sawyer. Final Report on SERC/DTI Parallel Applications Programme Collaboration Between EPCC, Rolls Royce ands Leeds University, Edinburgh Parallel Computing Centre, September, 1993.
C. Walshaw, M. Berzins. Enhanced Dynamic Load Balancing of Adaptive Unstructured Meshes, In Proc. of 1993 SIAM Conference on Parallel Processing for Scientific Computing, Vol. 2, pp. 971--978. 1993.
D.R. Anderson, J.A. Weiss, S. Takai, K.J. Ohland, S.L-Y. Woo. Healing of the Medial Collateral Ligament Following a Triad Injury: A Biomechanical and Histological Study of the Knee in Rabbits, In Journal of Orthopaedic Research, Vol. 10, pp. 485--495. 1992.
M. Berzins, A.J. Preston, P.M. Dew, L.E. Scales.
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M. Berzins, R.M. Furzeland. An Adaptive Theta Method for the Solution of Stiff and Non-stiff Differential Equations, In Applied Numerical Mathematics, Vol. 9, pp. 1--19. 1992.
Berzins, M. and R.M. Furzeland, An adaptive theta method for the solution of stiff and nonstiff differential
equations, Applied Numerical Mathematics 9 (1992) 1-19.
This paper describes a new adaptive method that has been developed to give improved efficiency for solving
differential equations where the degree of stiffness varies during the course df the integration or is not known
beforehand. The method is a modification of the theta method, in which the new adaptive strategy is to
automatically select the value of theta and to switch between functional iteration and Newton iteration for the
solution of the nonlinear equations arising at each integration step. The criteria for selecting theta and for
switching are established by optimising the permissible step size.
The performance of the adaptive methods is demonstrated on a range of test problems including one arising
from the method of lines solution of a convectixr-dominated partial differential equation. In some cases the new
approach halves the amount of computational work.