Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Thurston Sexton"'
Publikováno v:
Applied AI Letters, Vol 2, Iss 3, Pp n/a-n/a (2021)
Abstract Despite recent dramatic successes, natural language processing (NLP) is not ready to address a variety of real‐world problems. Its reliance on large standard corpora, a training and evaluation paradigm that favors the learning of shallow h
Externí odkaz:
https://doaj.org/article/7c4f8018201a4dceb535b9e29ff8a19a
Publikováno v:
International Journal of Prognostics and Health Management, Vol 12, Iss 1 (2021)
Sensors and mathematical models have been used since the 1990’s to assess the health of systems and diagnose anomalous behavior. The advent of the Internet of Things (IoT) increases the range of assets on which data can be collected cost effectivel
Externí odkaz:
https://doaj.org/article/9888804a7b704b2692bc0885bb256543
Publikováno v:
Journal of Intelligent Manufacturing. 33:1859-1877
Optimizing maintenance practices is a continuous process that must take into account the evolving state of the equipment, resources, workers, and more. To help streamline this process, facilities need a concise procedure for identifying critical task
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c446df7e0f1eb3b866ef8aef3f4edce9
https://doi.org/10.1007/s10845-021-01772-5
https://doi.org/10.1007/s10845-021-01772-5
Publikováno v:
Manufacturing Letters. 27:42-46
Out-of-the-box natural-language processing (NLP) pipelines need re-imagining to understand and meet the requirements of engineering data. Text-based documents account for a significant portion of data collected during the life cycle of asset manageme
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3358dbf3afef4bf015656ca333c1c90e
https://doi.org/10.1016/j.mfglet.2020.11.001
https://doi.org/10.1016/j.mfglet.2020.11.001
Publikováno v:
Applied AI Letters, Vol 2, Iss 3, Pp n/a-n/a (2021)
Appl AI Lett
Appl AI Lett
Despite recent dramatic successes, natural language processing (NLP) is not ready to address a variety of real‐world problems. Its reliance on large standard corpora, a training and evaluation paradigm that favors the learning of shallow heuristics
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f650e30cb2b41f549fce12a765bacb80
https://doi.org/10.1002/ail2.33
https://doi.org/10.1002/ail2.33
Autor:
Alden Dima, Xiaoyu Zhang, Thurston Sexton, Senthil Chandrasegaran, Michael P. Brundage, Takanori Fujiwara, Kwan-Liu Ma
Publikováno v:
PacificVis
Analysis of large, high-dimensional, and heterogeneous datasets is challenging as no one technique is suitable for visualizing and clustering such data in order to make sense of the underlying information. For instance, heterogeneous logs detailing m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::31396cf8d74d919e80ac90e6a0f3875a
https://doi.org/10.1109/pacificvis52677.2021.00033
https://doi.org/10.1109/pacificvis52677.2021.00033
Publikováno v:
International Journal of Prognostics and Health Management, Vol 12, Iss 1 (2021)
Even as maintenance evolves with new technologies, it is still a heavily human-driven domain; multiple steps in the maintenance workflow still require human expertise and intervention. Various maintenance activities require multiple maintainers, all
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ff06f29636a8aba05304e55a36054b9
https://doi.org/10.36001/ijphm.2021.v12i1.2930
https://doi.org/10.36001/ijphm.2021.v12i1.2930
Publikováno v:
International Journal of Prognostics and Health Management, Vol 12, Iss 1 (2021)
Sensors and mathematical models have been used since the 1990’s to assess the health of systems and diagnose anomalous behavior. The advent of the Internet of Things (IoT) increases the range of assets on which data can be collected cost effectivel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3266b9365b66ec81509f8dff07674567
https://doi.org/10.36001/ijphm.2021.v12i1.2932
https://doi.org/10.36001/ijphm.2021.v12i1.2932
Publikováno v:
Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability.
The ASME 2020 Manufacturing Science and Engineering Conference (MSEC) is the 15th annual meeting organized by the Manufacturing Engineering Division (MED) of ASME. MED and ASME MSEC focuses on manufacturing sciences, technology, and applications, inc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::70b1cf1916c79d58c2dad44c85af6fb3
https://doi.org/10.1115/msec2020-8440
https://doi.org/10.1115/msec2020-8440
Autor:
Thurston Sexton, Mark Fuge
Publikováno v:
J Mech Des N Y
Recovering a system’s underlying structure from its historical records (also called structure mining) is essential to making valid inferences about that system’s behavior. For example, making reliable predictions about system failures based on ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::171d8d2240c5d5ce17c28809e5b5ad9f
https://doi.org/10.1115/1.4045686
https://doi.org/10.1115/1.4045686