TimeTubes
| Autor: | Issei Fujishiro, Hsiang-Yun Wu, Naoko Sawada, Makoto Uemura, Masanori Nakayama |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Fusion
Multivariate statistics Computer science Astrophysics::High Energy Astrophysical Phenomena 020207 software engineering Missing periods 02 engineering and technology Sensor fusion computer.software_genre 01 natural sciences 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Data mining Blazar 010303 astronomy & astrophysics computer |
| Zdroj: | CGI |
| DOI: | 10.1145/3095140.3095154 |
| Popis: | Astronomers have been observing blazars to solve the mystery of the relativistic jet. A technique called TimeTubes uses a 3D volumetric tube to visualize the time-dependent multivariate observed datasets and allows astronomers to interactively analyze the dynamic behavior of and relationship among those variables. However, the observed datasets themselves exhibit uncertainty due to their errors and missing periods, whereas periods interpolated by TimeTubes result in a different type of uncertainty. In this paper, we present a technique for ameliorating such data- and mapping-inherent uncertainties: visual fusion of datasets for the same blazar from two different observatories. Visual data fusion with Time-Tubes enables astronomers to validate the datasets in a meticulous manner. |
| Databáze: | OpenAIRE |
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