Institution
Korea Institute of Science and Technology Information
Facility•Daejeon, South Korea•
About: Korea Institute of Science and Technology Information is a facility organization based out in Daejeon, South Korea. It is known for research contribution in the topics: Gravitational wave & LIGO. The organization has 1152 authors who have published 2319 publications receiving 93849 citations. The organization is also known as: Korea Institute of Science and Technology Information & KISTI.
Topics: Gravitational wave, LIGO, KEKB, Grid, Grid computing
Papers published on a yearly basis
Papers
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TL;DR: In this article, the authors reported a new measurement of the e+e−→ ϒ(nS)π+π− (n = 1, 2, 3) cross sections at energies from 10.52 to 11.02 GeV using data collected with the Belle detector at the KEKB asymmetric-energy e−e− collider.
Abstract: We report a new measurement of the e+e−→ ϒ(nS)π+π− (n = 1, 2, 3) cross sections at energies from 10.52 to 11.02 GeV using data collected with the Belle detector at the KEKB asymmetric-energy e+e− collider. We observe a new structure in the energy dependence of the cross sections; if described by a Breit-Wigner function its mass and width are found to be $$ M=\left(10752.7\pm {5.9}_{-1.1}^{+0.7}\right)\mathrm{MeV}/{c}^2 $$
and $$ \Gamma =\left({35.5}_{-11.3\kern0.5em -3.3}^{+17.6+3.9}\right) $$
MeV, where the first error is statistical and the second is systematic. The global significance of the new structure including systematic uncertainty is 5.2 standard deviations. We also find evidence for the e+e−→ ϒ (1S)π+π− process at the energy 10.52 GeV, which is below the B
$$ \overline{B} $$
threshold.
24 citations
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TL;DR: Adopting commercial software (3D-DOCTOR, Maya), an advanced surface reconstruction technique was applied to create a surface model of extensive lumbosacral structures which can be used in medical simulation systems.
Abstract: Unlike volume models, surface models representing hollow, three-dimensional images have a small file size; allowing them to be displayed, rotated, and modified in real time. Therefore, surface models of lumbosacral structures can be effectively used for interactive simulation of, e.g., virtual lumbar puncture, virtual surgery of herniated lumbar discs, and virtual epidural anesthesia. In this paper, we present surface models of extensive lumbosacral structures which can be used in medical simulation systems. One-hundred and thirty-eight chosen structures included the spinal cord, lumbar and sacral nerves, vertebrae, intervertebral discs, ligaments, muscles, arteries, and skin. The structures were outlined in the sectioned images from the Visible Korean. From these outlined images, serial outlines of each structure were stacked. Adopting commercial software (3D-DOCTOR, Maya), an advanced surface reconstruction technique was applied to create a surface model of the structure. In the surface models, we observed the anatomical relationships of the lumbosacral structures (e.g., cauda equina and ligaments) in detail. Additionally, the portions of some spinal nerves that could not be outlined were drawn and added to the surface models. These constructed models will hopefully facilitate development of high quality medical simulation of the lumbosacral region.
24 citations
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01 Jul 2004TL;DR: A new passage-level or passage-based text categorization model is proposed, which segments a test document into several passages, assigns categories to each passage, and merges the passage categories to the document categories.
Abstract: Researches in text categorization have been confined to whole-document-level classification, probably due to lack of full-text test collections. However, full-length documents available today in large quantities pose renewed interests in text classification. A document is usually written in an organized structure to present its main topic(s). This structure can be expressed as a sequence of subtopic text blocks, or passages. In order to reflect the subtopic structure of a document, we propose a new passage-level or passage-based text categorization model, which segments a test document into several passages, assigns categories to each passage, and merges the passage categories to the document categories. Compared with traditional document-level categorization, two additional steps, passage splitting and category merging, are required in this model. Using four subsets of the Reuters text categorization test collection and a full-text test collection of which documents are varying from tens of kilobytes to hundreds, we evaluate the proposed model, especially the effectiveness of various passage types and the importance of passage location in category merging. Our results show simple windows are best for all test collections tested in these experiments. We also found that passages have different degrees of contribution to the main topic(s), depending on their location in the test document.
24 citations
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TL;DR: In this article, the authors investigated the near-field rocket plume-lunar surface interaction and subsequent regolith erosion and particle dispersal, and the effect of surface erosion on flow characteristics, in conjunction with the finite volume method of plume impingement of a rocket nozzle.
24 citations
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TL;DR: This approach applies an aging theory-based EDT algorithm to online product reviews to detect the creation of customer-stated events as groups of similar reviews and track their growth and extinction and uses sentiment analysis and an opportunity algorithm to evaluate time-evolving events.
24 citations
Authors
Showing all 1155 results
Name | H-index | Papers | Citations |
---|---|---|---|
Hyun-Chul Kim | 176 | 4076 | 183227 |
Yang Yang | 164 | 2704 | 144071 |
Yongsun Kim | 156 | 2588 | 145619 |
Jongmin Lee | 150 | 2257 | 134772 |
Teruki Kamon | 142 | 2034 | 115633 |
G. Bauer | 131 | 1147 | 83657 |
Jung-Hyun Kim | 113 | 1195 | 56181 |
Jin Yong Lee | 107 | 757 | 55220 |
U. K. Yang | 103 | 782 | 54135 |
Sang Un Ahn | 82 | 391 | 22067 |
G. Kang | 81 | 210 | 50549 |
Y. D. Oh | 80 | 553 | 24043 |
M. K. M. Bader | 79 | 182 | 52738 |
H. J. Jang | 73 | 194 | 32564 |
Chunglee Kim | 71 | 156 | 17096 |