Zobrazeno 1 - 10
of 84
pro vyhledávání: '"Sunghoon LIM"'
Publikováno v:
IEEE Access, Vol 11, Pp 66544-66567 (2023)
The clinical application of a real-time artificial intelligence (AI) image processing system to diagnose upper gastrointestinal (GI) malignancies remains an experimental research and engineering problem. Understanding these commonly used technical te
Externí odkaz:
https://doaj.org/article/9346fd69e7a548c9bb62a5924e3018d5
Publikováno v:
IEEE Access, Vol 10, Pp 56232-56248 (2022)
Cryptocurrency has recently attracted substantial interest from investors due to its underlying philosophy of decentralization and transparency. Considering cryptocurrency’s volatility and unique characteristics, accurate price prediction is essent
Externí odkaz:
https://doaj.org/article/d99a3fd3f91b41f696368ea10c13aed2
Autor:
Gyeongho Kim, Sunghoon Lim
Publikováno v:
IEEE Access, Vol 10, Pp 41313-41329 (2022)
Every year, maritime accidents cause severe damages not only to humans but also to maritime instruments like vessels. The authors of this work therefore propose a machine learning-based maritime accident prediction system that can be used to prevent
Externí odkaz:
https://doaj.org/article/e8116d4ce68248edab128fbfa0dd066d
Publikováno v:
IEEE Access, Vol 10, Pp 105702-105712 (2022)
This paper proposes a new coordinated control for multiple wind power plants (WPPs) based on two stepwise inertial control (SIC) methods to effectively release the kinetic energy of the permanent magnet synchronous generators (PMSGs) and improve thei
Externí odkaz:
https://doaj.org/article/d006627d6d7c4efa8beeddf3b96f863c
Publikováno v:
IEEE Access, Vol 10, Pp 11657-11668 (2022)
The high penetration of converter-based distributed generations (DGs) to power system can give rise to the lack of rotational inertia while replacing the conventional synchronous generators (SGs), which provide the primary frequency reserve (PFR) in
Externí odkaz:
https://doaj.org/article/9c45338e7dd04700a2a455dba54a2352
Publikováno v:
IEEE Access, Vol 10, Pp 34625-34636 (2022)
Detecting and preventing industrial machine failures are significant in the modern manufacturing industry because machine failures substantially increase both maintenance and manufacturing costs. Recently, state-of-the-art deep learning techniques th
Externí odkaz:
https://doaj.org/article/a4af1eb954e44b838caab905d6d93362
Autor:
Suppawong Tuarob, Poom Wettayakorn, Ponpat Phetchai, Siripong Traivijitkhun, Sunghoon Lim, Thanapon Noraset, Tipajin Thaipisutikul
Publikováno v:
Financial Innovation, Vol 7, Iss 1, Pp 1-32 (2021)
Abstract The explosion of online information with the recent advent of digital technology in information processing, information storing, information sharing, natural language processing, and text mining techniques has enabled stock investors to unco
Externí odkaz:
https://doaj.org/article/57c207756f5646f4b5677b277291440c
Publikováno v:
IEEE Access, Vol 9, Pp 132455-132467 (2021)
The authors of this work propose a deep learning-based fault detection model that can be implemented in the field of plastic injection molding. Compared to conventional approaches to fault detection in this domain, recent deep learning approaches pro
Externí odkaz:
https://doaj.org/article/f1e9e5b36c3a44818c54953bc09c383a
Autor:
Sujoy Chatterjee, Sunghoon Lim
Publikováno v:
IEEE Access, Vol 8, Pp 87647-87664 (2020)
Crowdsourcing has already been shown to be a promising tool in solving many real-life problems in time and cost-effective way. For example, in city planning, to install some specific facilities it is required to acquire knowledge about various factor
Externí odkaz:
https://doaj.org/article/e3401e7c497245829ab7d0cbd45411ef
Publikováno v:
Mechanical Engineering Journal, Vol 8, Iss 3, Pp 21-00052-21-00052 (2021)
This paper presents a new structural design framework that incorporates the concept of topology optimization and genetic algorithms to improve the manufacturability and structural robustness of the optimal structure. The level set function is employe
Externí odkaz:
https://doaj.org/article/269ce59711954b6e957711f9e5cbfa6f