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ISMB
1993
15 years 7 months ago
Knowledge-Based Generation of Machine-Learning Experiments: Learning with DNA Crystallography Data
Thoughit has been possible in the past to learn to predict DNAhydration patterns from crystallographic data, there is ambiguity in the choice of training data (both in terms of th...
Dawn M. Cohen, Casimir A. Kulikowski, Helen Berman
CLUSTER
2009
IEEE
15 years 9 months ago
Using a cluster as a memory resource: A fast and large virtual memory on MPI
—The 64-bit OS provides ample memory address space that is beneficial for applications using a large amount of data. This paper proposes using a cluster as a memory resource for...
Hiroko Midorikawa, Kazuhiro Saito, Mitsuhisa Sato,...
MICCAI
2004
Springer
16 years 7 months ago
A Data Clustering and Streamline Reduction Method for 3D MR Flow Vector Field Simplification
Abstract. With the increasing capability of MR imaging and Computational Fluid Dynamics (CFD) techniques, a significant amount of data related to the haemodynamics of the cardiovas...
Bernardo Silva Carmo, Yin-Heung Pauline Ng, Adam P...
FSS
2010
147views more  FSS 2010»
15 years 5 months ago
A divide and conquer method for learning large Fuzzy Cognitive Maps
Fuzzy Cognitive Maps (FCMs) are a convenient tool for modeling and simulating dynamic systems. FCMs were applied in a large number of diverse areas and have already gained momentu...
Wojciech Stach, Lukasz A. Kurgan, Witold Pedrycz
CA
2003
IEEE
15 years 11 months ago
Bottom-Up Visual Attention for Virtual Human Animation
We present a system for the automatic generation of bottom-up visual attention behaviours in virtual humans. Bottom-up attention refers to the way in which the environment solicit...
Christopher Peters, Carol O'Sullivan