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.

A. Paoluzzi, V. Pascucci, M. Vicentino.
**“Un linguaggio di progettazione orientato al Solid Modeling (A Design Language oriented to Solid Modeling),”** In *Atti del convegno IcoGraphics '93*, Note: *In Italian*, Mondadori Informatica, Milano, Italy pp. 60--66. March, 1993.

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.

1992

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.
**“Towards Efficient D.A.E. Solvers for the Solution of Dynamic Simulation Problems,”** In *Proc of I.M.A. 1989 O.D.E. Conference*, Edited by I. Gladwell and J. Cash and A. Iserles, Oxford University Press, pp. 299--308. 1992.

ISBN: 0-19-853659-3

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.

M. Berzins, P.M. Dew, S. Hillen.
**“Exploiting Parallelism for Adaptive CFD Software,”** In *Parallelogram*, pp. 14--16. February, 1992.

K.W. Brodlie, M. Berzins, P.M. Dew, A. Poon, H. Wright.
**“Visualization and its Use in Scientific Computation,”** In *Programming Environments for High-Level Scientific Problem Solving*, Elsevier, pp. 293--303. 1992.

D. Forslunk, P. Hinker, C.D. Hansen, W.St. John, S. Tenbrink, J. Brewton.
**“High-speed Networks, Visualization and Massive Parallelism in the Advanced Computing Laboratory,”** In *Computing Systems in Engineering*, Vol. 3, No. 1-4, 1992.

C.D. Hansen, P. Hinker.
**“Massively Parallel Isosurface Extraction,”** In *Visualization 1992*, Boston, Ma., pp. 77--83. October, 1992.

C.D. Hansen, D. Butler.
**“Visualization '91 Workshop Report: Scientific Visualization Environments,”** In *Computer Graphics Quarterly*, Vol. 26, No. 3, pp. 213--216. August, 1992.

C.R. Johnson, R.S. MacLeod, P.R. Ershler.
**“A Computer Model for the Study of Electrical Current Flow in the Human Thorax,”** In *Computers in Biology and Medicine*, Vol. 22, No. 5, Elsevier BV, pp. 305--323. 1992.

Electrocardiography has played an important role in the detection and characterization of heart function, both in normal and abnormal states. In this paper we present an inhomogeneous, anisotropic computer model of the human thorax for use in electrocardiography with emphasis on the calculation of transthoracic potential and current distributions. Knowledge of the current pathways in the thorax has many applications in electrocardiography and has direct utility in studies pertaining to cardiac defibrillation, forward and inverse problems, impedance tomography, and electrode placement in electrocardiography.

**Keywords:** scalar field methods, vector field methods, tensor field methods, cardiac heart, scientific visualization