Detecting flaws and intruders with visual data analysis.
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Computer Communication Networks↗
Biomedical subjects
T J Jankun-Kelly
Publications and source records attributed to T J Jankun-Kelly.
Detection and visualization of defects in 3D unstructured models of nematic liquid crystals.
A method for the semi-automatic detection and visualization of defects in models of nematic liquid crystals (NLCs) is introduced; this method is suitable for unstructured models, a previously unsolved problem. The detected defects-also known as disclinations-are regions were the alignment of the liquid crystal rapidly changes over space; these defects play a large role in the physical behavior of the NLC substrate. Defect detection is based upon a measure of total angular change of crystal orientation (the director) over a node neighborhood via the use of a nearest neighbor path. Visualizations based upon the detection algorithm clearly identifies complete defect regions as opposed to incomplete visual descriptions provided by cutting-plane and isosurface approaches. The introduced techniques are currently in use by scientists studying the dynamics of defect change.
Journal Article↗
Superellipsoid-based, real symmetric traceless tensor glyphs motivated by nematic liquid crystal alignment visualization.
A glyph-based method for visualizing the nematic liquid crystal alignment tensor is introduced. Unlike previous approaches, the glyph is based upon physically-linked metrics, not offsets of the eigenvalues. These metrics, combined with a set of superellipsoid shapes, communicate both the strength of the crystal's uniaxial alignment and the amount of biaxiality. With small modifications, our approach can visualize any real symmetric traceless tensor.
Journal Article↗
A model and framework for visualization exploration.
Visualization exploration is the process of extracting insight from data via interaction with visual depictions of that data. Visualization exploration is more than presentation; the interaction with both the data and its depiction is as important as the data and depiction itself. Significant visualization research has focused on the generation of visualizations (the depiction); less effort has focused on the exploratory aspects of visualization (the process). However, without formal models of the process, visualization exploration sessions cannot be fully utilized to assist users and system designers. Toward this end, we introduce the P-Set Model of Visualization Exploration for describing this process and a framework to encapsulate, share, and analyze visual explorations. In addition, systems utilizing the model and framework are more efficient as redundant exploration is avoided. Several examples drawn from visualization applications demonstrate these benefits. Taken together, the model and framework provide an effective means to exploit the information within the visual exploration process.
Algorithms↗