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Documents authored by Hong, Yu Xuan

Found 2 Possible Name Variants:

Hong, Yu Xuan

Document
Multimedia Exposition
DOI: 10.4230/LIPIcs.SoCG.2018.76
Star Unfolding of Boxes (Multimedia Exposition)

Authors: Dani Demas, Satyan L. Devadoss, and Yu Xuan Hong

Published in: LIPIcs, Volume 99, 34th International Symposium on Computational Geometry (SoCG 2018)

Abstract
Given a convex polyhedron, the star unfolding of its surface is obtained by cutting along the shortest paths from a fixed source point to each of its vertices. We present an interactive application that visualizes the star unfolding of a box, such that its dimensions and source point locations can be continuously toggled by the user.
Cite as

Dani Demas, Satyan L. Devadoss, and Yu Xuan Hong. Star Unfolding of Boxes (Multimedia Exposition). In 34th International Symposium on Computational Geometry (SoCG 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 99, pp. 76:1-76:4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{demas_et_al:LIPIcs.SoCG.2018.76,
  author =	{Demas, Dani and Devadoss, Satyan L. and Hong, Yu Xuan},
  title =	{{Star Unfolding of Boxes}},
  booktitle =	{34th International Symposium on Computational Geometry (SoCG 2018)},
  pages =	{76:1--76:4},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-066-8},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{99},
  editor =	{Speckmann, Bettina and T\'{o}th, Csaba D.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2018.76},
  URN =		{urn:nbn:de:0030-drops-87890},
  doi =		{10.4230/LIPIcs.SoCG.2018.76},
  annote =	{Keywords: star unfolding, source unfolding, Voronoi diagram}
}

Hong, Seong-Yun

Document
Short Paper
DOI: 10.4230/LIPIcs.GISCIENCE.2018.24
Evaluating Efficiency of Spatial Analysis in Cloud Computing Platforms (Short Paper)

Authors: Changlock Choi, Yelin Kim, Youngho Lee, and Seong-Yun Hong

Published in: LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018)

Abstract
The increase of high-resolution spatial data and methodological developments in recent years has enabled a detailed analysis of individuals' experience in space and over time. However, despite the increasing availability of data and technological advances, such individual-level analysis is not always possible in practice because of its computing requirements. To overcome this limitation, there has been a considerable amount of research on the use of high-performance, public cloud computing platforms for spatial analysis and simulation. In this paper, we aim to evaluate the efficiency of spatial analysis in cloud computing platforms. We compared the computing speed for calculating the Moran's I index between a local machine and spot instances on clouds, and our results demonstrated that there could be significant improvements in terms of computing time when the analysis was performed parallel on clouds.
Cite as

Changlock Choi, Yelin Kim, Youngho Lee, and Seong-Yun Hong. Evaluating Efficiency of Spatial Analysis in Cloud Computing Platforms (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 24:1-24:5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

Copy BibTex To Clipboard

@InProceedings{choi_et_al:LIPIcs.GISCIENCE.2018.24,
  author =	{Choi, Changlock and Kim, Yelin and Lee, Youngho and Hong, Seong-Yun},
  title =	{{Evaluating Efficiency of Spatial Analysis in Cloud Computing Platforms}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{24:1--24:5},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Winter, Stephan and Griffin, Amy and Sester, Monika},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.24},
  URN =		{urn:nbn:de:0030-drops-93521},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.24},
  annote =	{Keywords: spatial analysis, parallel computing, cloud services}
}
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