• Title/Summary/Keyword: Clustered heatmap

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Evaluation of temperature effects on brake wear particles using clustered heatmaps

  • Shin, Jihoon;Yim, Inhyeok;Kwon, Soon-Bark;Park, Sechan;Kim, Min-soo;Cha, YoonKyung
    • Environmental Engineering Research
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    • v.24 no.4
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    • pp.680-689
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    • 2019
  • Temperature effects on the generation of brake wear particles from railway vehicles were generated, with a particular focus on the generation of ultrafine particles. A real scale brake dynamometer test was repeated five times under low and high initial temperatures of brake discs, respectively, to obtain generalized results. Size distributions and temporal patterns of wear particles were analyzed through visualization using clustered heatmaps. Our results indicate that high initial temperature conditions promote the generation of ultrafine particles. While particle concentration peaked within the range of fine sized particles under both low and high initial temperature, an additional peak occurred within the range of ultrafine sized particles only under high initial temperature. The timing of peak occurrence also differed between low and high initial temperature conditions. Under low initial temperature fine sized particles were generated intensively at the latter end of braking, whereas under high initial temperature both fine and ultrafine particles were generated more dispersedly along the braking period. The clustered correlation heatmap divided particle sizes into two groups, within which generation timing and concentration of particles were similar. The cut-off point between the two groups was approximately 100 nm, confirming that the governing mechanisms for the generation of fine particles and ultrafine particles are different.

QCanvas: An Advanced Tool for Data Clustering and Visualization of Genomics Data

  • Kim, Nayoung;Park, Herin;He, Ningning;Lee, Hyeon Young;Yoon, Sukjoon
    • Genomics & Informatics
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    • v.10 no.4
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    • pp.263-265
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    • 2012
  • We developed a user-friendly, interactive program to simultaneously cluster and visualize omics data, such as DNA and protein array profiles. This program provides diverse algorithms for the hierarchical clustering of two-dimensional data. The clustering results can be interactively visualized and optimized on a heatmap. The present tool does not require any prior knowledge of scripting languages to carry out the data clustering and visualization. Furthermore, the heatmaps allow the selective display of data points satisfying user-defined criteria. For example, a clustered heatmap of experimental values can be differentially visualized based on statistical values, such as p-values. Including diverse menu-based display options, QCanvas provides a convenient graphical user interface for pattern analysis and visualization with high-quality graphics.