Zobrazeno 1 - 10
of 93
pro vyhledávání: '"Chau-chang Wang"'
Autor:
Ching-ren Lin, Yi-Chun Liao, Chau-chang Wang, Ban-Yuan Kuo, Hsin-Hung Chen, Jia-pu Jang, Po-chi Chen, Hsu-kuang Chang, Feng-Sheng Lin, Kun-Hui Chang
Publikováno v:
Terrestrial, Atmospheric and Oceanic Sciences, Vol 35, Iss 1, Pp 1-12 (2024)
Abstract This study focuses on developing and evaluating the broadband ocean bottom seismometer (Yardbird-BB OBS) in Taiwan. The Yardbird-BB OBS is a crucial instrument for recording seismic signals in deep-sea environments. Rigorous testing ensures
Externí odkaz:
https://doaj.org/article/e1db3be95216476aa8af1153274b5184
Autor:
Ching-Jer Huang, Hsin-Yu Chen, Chung-Ray Chu, Ching-Ren Lin, Li-Chen Yen, Hsiao-Yuen Yin, Chau-Chang Wang, Ban-Yuan Kuo
Publikováno v:
Sensors, Vol 22, Iss 23, p 9310 (2022)
A lab-fabricated ocean bottom seismometer was modified and deployed terrestrially to detect low-frequency (
Externí odkaz:
https://doaj.org/article/edc024fde51442a79fc90c43a7d84404
Publikováno v:
Terrestrial, Atmospheric and Oceanic Sciences, Vol 30, Iss 5, Pp 717-737 (2019)
This paper presents the seafloor survey results obtained in 2016 and 2017 using four deep-towed vehicles, developed by the Institute of Undersea Technology at National Sun Yat-sen University, for investigating mineral resource potential offshore nort
Externí odkaz:
https://doaj.org/article/ac5f3d7454ca421890cf333731f3c27f
Publikováno v:
2023 IEEE Underwater Technology (UT).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::96fabbb2dc1aa67e16c8986b35371bd1
https://doi.org/10.1109/ut49729.2023.10103400
https://doi.org/10.1109/ut49729.2023.10103400
Publikováno v:
2023 IEEE Underwater Technology (UT).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7636374eab15faa2e94093a30cf811cd
https://doi.org/10.1109/ut49729.2023.10103411
https://doi.org/10.1109/ut49729.2023.10103411
Publikováno v:
International Journal of Systematic and Evolutionary Microbiology. 70:5497-5502
A mesophilic, hydrogenotrophic methanogen, strain FWC-SCC2T, was isolated from deep-sea sediments collected by a real-time video multiple-corer at the C5-6 station near a cold seep at Four-Way Closure Ridge region during R/V Ocean Researcher III ORII
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ece9c8589e730af6c9f7f421a325f49e
https://doi.org/10.1099/ijsem.0.004440
https://doi.org/10.1099/ijsem.0.004440
Publikováno v:
AICAS
This paper presents an AUV with AI (artificial intelligence), which is able to perform real-time optical vision-based diver-following and forward looking altimeter-based obstacle avoidance. The AI AUV is equipped with thrusters and a standard navigat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1f65f83ff7c4f9a5bff976753cd8c4e2
https://doi.org/10.1109/aicas51828.2021.9458431
https://doi.org/10.1109/aicas51828.2021.9458431
Publikováno v:
Terrestrial, Atmospheric and Oceanic Sciences, Vol 30, Iss 5, Pp 717-737 (2019)
This paper presents the seafloor survey results obtained in 2016 and 2017 using four deep-towed vehicles, developed by the Institute of Undersea Technology at National Sun Yat-sen University, for investigating mineral resource potential offshore nort
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3e8254b107266b1d5b0963286c69f244
https://doi.org/10.3319/tao.2019.03.14.01
https://doi.org/10.3319/tao.2019.03.14.01
Publikováno v:
Global Oceans 2020: Singapore – U.S. Gulf Coast.
This paper presents the design of an automatic push coring device, the IUT APC-II, to be installed on an ROV. The purpose of designing the IUT APC-II is to improve the drawbacks of the prototype device, the IUT prototype APC. The volume of the new de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eccbc2a5783ed16e4f5f7b824b928ef9
https://doi.org/10.1109/ieeeconf38699.2020.9389294
https://doi.org/10.1109/ieeeconf38699.2020.9389294
Publikováno v:
OCEANS 2019 - Marseille.
An algorithm for estimating the displacement of an underwater vehicle was developed, which is based on detecting and matching features in seafloor images collected by the underwater vehicle itself. This feature-based algorithm consists of four main s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1bf2930435b58925ccb72ce5fa9c9ba6
https://doi.org/10.1109/oceanse.2019.8867051
https://doi.org/10.1109/oceanse.2019.8867051