Lian Jiang

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In this paper, we describe a feature extraction and tracking algorithm for AMR (Adaptive Mesh Refinement) datasets that operates within a distributed computing environment. Because features can span multiple refinement levels and multiple processors, tracking must be performed across time, across levels, and across processors. The resulting visualization is(More)
In this paper, we introduce the concept of rule-based visualization for a computational steering collaboratory and show how these rules can be used to steer the behaviors of the visualization subsystem. Rules define high-level policies and are used to autonomically select and tune the visualization routines based on application requirements and available(More)
In this paper, we introduce the concept of rule-based visu-alization for a computational steering collaboratory and show how these rules can be used to steer the behaviors of visualization subsystems. Feature-based visualization allows users to extract regions of interests, and then visualize, track and quantify the evolution of these features. Rules define(More)
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