| LDR | | 01896nam u200385 4500 |
| 001 | | 000000418892 |
| 005 | | 20190215163234 |
| 008 | | 181129s2017 |||||||||||||||||c||eng d |
| 020 | |
▼a 9780438098213 |
| 035 | |
▼a (MiAaPQ)AAI10901880 |
| 035 | |
▼a (MiAaPQ)OhioLINK:osu1512051705269695 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 004 |
| 100 | 1 |
▼a Wei, Tzu-Hsuan. |
| 245 | 10 |
▼a Query-Driven Analysis and Visualization for Large-Scale Scientific Dataset using Geometry Summarization and Bitmap Indexing. |
| 260 | |
▼a [S.l.]:
▼b The Ohio State University.,
▼c 2017. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2017. |
| 300 | |
▼a 158 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B. |
| 500 | |
▼a Adviser: Han-Wei Shen. |
| 502 | 1 |
▼a Thesis (Ph.D.)--The Ohio State University, 2017. |
| 520 | |
▼a The computational power of modern supercomputers grows rapidly, and it facilitates scientists to produce high-resolution datasets when simulating physical or weather models, which generate extreme scale data with multiple variables most of the t |
| 520 | |
▼a First, we focus on the problem of identifying salient features and evaluating selected features for creating a data summarization. To analyze a volumetric dataset, displaying isosurface is typically used to reveal the locations of values that th |
| 590 | |
▼a School code: 0168. |
| 650 | 4 |
▼a Computer science. |
| 690 | |
▼a 0984 |
| 710 | 20 |
▼a The Ohio State University.
▼b Computer Science and Engineering. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-12B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0168 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2017 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000306
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a ***1012033 |