SCI Publications

2009


R. Archibald, A. Gelb, R. Saxena, D. Xiu. “Discontinuity Detection in Multivariate Space for Stochastic Simulations,” In Journal of Computational Physics, Vol. 228, No. 7, pp. 2676--2689. 2009.
DOI: 10.1016/j.jcp.2009.01.001

ABSTRACT

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Edge detection has traditionally been associated with detecting physical space jump discontinuities in one dimension, e.g. seismic signals, and two dimensions, e.g. digital images. Hence most of the research on edge detection algorithms is restricted to these contexts. High dimension edge detection can be of significant importance, however. For instance, stochastic variants of classical differential equations not only have variables in space/time dimensions, but additional dimensions are often introduced to the problem by the nature of the random inputs. The stochastic solutions to such problems sometimes contain discontinuities in the corresponding random space and a prior knowledge of jump locations can be very helpful in increasing the accuracy of the final solution. Traditional edge detection methods typically require uniform grid point distribution. They also often involve the computation of gradients and/or Laplacians, which can become very complicated to compute as the number of dimensions increases. The polynomial annihilation edge detection method, on the other hand, is more flexible in terms of its geometric specifications and is furthermore relatively easy to apply. This paper discusses the numerical implementation of the polynomial annihilation edge detection method to high dimensional functions that arise when solving stochastic partial differential equations.

Keywords: Stochastic partial differential equations, Multivariate edge detection, Generalized polynomial chaos method


T.J. Badger, R.S. Oakes, M. Daccarett, N.S. Burgon, N. Akoum, E.N. Fish, J.J. Blauer, S.N. Rao, Y. Adjei-Poku, E.G. Kholmovski, S. Vijayakumar, E.V. Di Bella, R.S. MacLeod, N.F. Marrouche. “Temporal Left Atrial Lesion Formation After Ablation of Atrial Fibrillation,” In Heart Rhythm, Vol. 6, No. 2, pp. 161--168. February, 2009.


T.J. Badger, Y.A. Adjei-Poku, N.S. Burgon, S. Kalvaitis, A. Shaaban, D.N. Sommers, J.J.E. Blauer, E.N. Fish N. Akoum, T.S. Haslem, E.G. Kholmovski, R.S. MacLeod, D.G. Adler, N.F. Marrouche. “Initial Experience of Assessing Esophageal Tissue Injury and Recovery Using Delayed-Enhancement MRI After Atrial Fibrillation Ablation,” In Circulation: Arrhythmia and Electrophysiology, Vol. 2, pp. 620--625. 2009.


M. Berzins. “Data Bounded Polynomials and Preserving Positivity in High Order ENO and WENO Methods,” SCI Technical Report, No. UUSCI-2009-003, SCI Institute, University of Utah, 2009.


E.W. Bethel, C.R. Johnson, S. Ahern, J. Bell, P.-T. Bremer, H. Childs, E. Cormier-Michel, M. Day, E. Deines, P.T. Fogal, C. Garth, C.G.R. Geddes, H. Hagen, B. Hamann, C.D. Hansen, J. Jacobsen, K.I. Joy, J. Krüger, J. Meredith, P. Messmer, G. Ostrouchov, V. Pascucci, K. Potter, Prabhat, D. Pugmire, O. Rubel, A.R. Sanderson, C.T. Silva, D. Ushizima, G.H. Weber, B. Whitlock, K. Wu. “Occam's Razor and Petascale Visual Data Analysis,” In Journal of Physics: Conference Series, Journal of Physics: Conference Series, Vol. 180, No. 012084, pp. (published online). 2009.
DOI: 10.1088/1742-6596/180/1/012084

ABSTRACT

One of the central challenges facing visualization research is how to effectively enable knowledge discovery. An effective approach will likely combine application architectures that are capable of running on today's largest platforms to address the challenges posed by large data with visual data analysis techniques that help find, represent, and effectively convey scientifically interesting features and phenomena.


J. Brouillat, C. Bouville, B. Loos, C.D. Hansen, K. Bouatouch. “A Bayesian Monte Carlo Approach to Global Illumination,” In Computer Graphics Forum Journal, Early View, Vol. 28, No. 8, pp. 2315--2329. October, 2009.


M. Callahan, M.J. Cole, J.F. Shepherd, J.G. Stinstra, C.R. Johnson. “A Meshing Pipeline for Biomedical Models,” In Engineering with Computers, Vol. 25, No. 1, SpringerLink, pp. 115-130. 2009.
DOI: 10.1007/s00366-008-0106-1


A.N.M. Imroz Choudhury, S.G. Parker. “Ray Tracing NPR-Style Feature Lines,” In Proceedings of the 7th International Symposium on Non-Photorealistic Animation and Rendering (NPAR) 2009, pp. 5--14. 2009.


J.D. Daniels, C.T. Silva, E. Cohen. “Semi-Regular Quadrilateral-only Remeshing from Simplified Base Domains,” In Computer Graphics Forum, Computer Graphics Forum, Vol. 28, No. 5, Wiley-Blackwell, pp. 1427--1435. July, 2009.
DOI: 10.1111/j.1467-8659.2009.01519.x


J.D. Daniels, C.T. Silva, E. Cohen. “Localized Quadrilateral Coarsening,” In Computer Graphics Forum, Vol. 28, No. 5, Wiley-Blackwell, pp. 1437--1444. July, 2009.
DOI: 10.1111/j.1467-8659.2009.01520.x


M. Datar, J. Cates, P.T. Fletcher, S. Gouttard, G. Gerig, R.T. Whitaker. “Particle Based Shape Regression of Open Surfaces with Applications to Developmental Neuroimaging,” In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009, Lecture Notes in Computer Science LNCS, Vol. 5762, pp. 167--174. 2009.
DOI: 10.1007/978-3-642-04271-3_21
PubMed ID: 20426109


C. Deitrich, C.E. Scheidegger, J. Schreiner, J. Comba, L.P. Nedel, C.T. Silva. “Edge Transformations for Improving Mesh Quality of Marching Cubes,” In IEEE Transactions on Visualization and Computer Graphics, Vol. 15, No. 1, pp. 150--159. Sept/Oct, 2009.


S. Durrleman, X. Pennec, A. Trouvé, G. Gerig, N. Ayache. “Spatiotemporal atlas estimation for developmental delay detection in longitudinal datasets,” In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009, Lecture Notes in Computer Science LNCS, Vol. 5761, pp. 297--304. 2009.
DOI: 10.1007/978-3-642-04268-3_37
PubMed ID: 20426000


T. Ellkvist, L. Stromback, L. Lins, J. Freire. “A First Study on Strategies for Generating Workflow Snippets,” In Proceedings of the ACM SIGMOD Intenational Workshop on Keyword Search on Structured Data (KEYS), pp. 15--20. 2009.
ISBN: 978-1-60558-570-3


T. Ellkvist, D. Koop, J. Freire, C.T. Silva, L. Stromback. “Using Mediation to Achieve Provenance Interoperability,” In Proceedings of the IEEE International Workshop on Scientific Workflows, 2009, pp. 291--298. 2009.
ISBN: 978-0-7695-3708-5


M. Ellisman, R. Stevens, M. Colvin, T. Schlick, E. Delong, G. Olsen, J. George, G. Karniakadis, C.R. Johnson, N. Sematova. “Scientific Grand Challenges: Opportunities in biology at the Extreme Scale of Computing,” Note: DOE Office of Advanced Scientific Computing Research, August, 2009.


T. Etiene, C.E. Scheidegger, L.G. Nonato, R. Kirby, C.T. Silva. “Verifiable Visualization for Isosurface Extraction,” In IEEE Transactions on Visualization and Computer Graphics, Proceedings of the 2009 IEEE Visualization Conference, Vol. 15, No. 6, pp. 1227--1234. Sept/Oct, 2009.


P.T. Fletcher PT, S. Venkatasubramanian, S. Joshi. “The geometric median on Riemannian manifolds with application to robust atlas estimation,” In Neuroimage, Vol. 45, No. 1, pp. S143--S152. March, 2009.
PubMed ID: 19056498


P.T. Fletcher, J. Moeller, J.M. Phillips, S. Venkatasubramanian. “Computing Hulls In Positive Definite Space,” In In Proceedings of the 19th Fall Workshop on Computational Geometry, November, 2009.


T. Fogal, J. Krüger. “Size Matters - Revealing Small Scale Structures in Large Datasets,” In Proceedings of the World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany, IFMBE Proceedings, Vol. 25/13, Springer Berlin Heidelberg, pp. 41--44. 2009.