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Kim, Seog-Gyu;Kim, Jae-Hyun
- Journal of the Korea Society of Computer and Information
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- v.26 no.1
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- pp.103-110
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- 2021
In this paper, we compare two access control mechanisms for D2D(Device-to-Device) systems in 5G wireless networks and propose an effective access control for 5G D2D networks. Currently, there is no specified access control for 5G D2D networks but there can be two access control approaches for 5G D2D networks. One is the UE-to-Network Relay based access control and the other is the Remote UE(User Equipment) based access control. The former is a UE-to-Network Relay carries out the access control check for 5G D2D networks but the latter is a Remote UE performs the access control check for 5G D2D networks. Through simulation and evaluation, we finally propose the Remote UE based access control for D2D systems in 5G wireless networks. The proposed approach minimizes signalling overhead between the UE-to-Network Relay and the Remote UE and more efficiently performs the access control check, when the access control functionalities are different from the UE-to-Network Relay in 5G D2D networks.
https://doi.org/10.9708/jksci.2021.26.01.103 인용 PDF KSCI HTML

Lee, Moung-Jin;Lee, Won-Jin;Lee, Seung-Kuk;Jung, Hyung-Sup
- Korean Journal of Remote Sensing
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- v.38 no.6_2
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- pp.1581-1587
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- 2022
Recently, deep learning has become more important in remote sensing data processing. Huge amounts of data for artificial intelligence (AI) has been designed and built to develop new technologies for remote sensing, and AI models have been learned by the AI training dataset. Artificial intelligence models have developed rapidly, and model accuracy is increasing accordingly. However, there are variations in the model accuracy depending on the person who trains the AI model. Eventually, experts who can train AI models well are required more and more. Moreover, the deep learning technique enables us to automate methods for remote sensing applications. Methods having the performance of less than about 60% in the past are now over 90% and entering about 100%. In this special issue, thirteen papers on how deep learning techniques are used for remote sensing applications will be introduced.
https://doi.org/10.7780/kjrs.2022.38.6.2.1 인용 PDF KSCI HTML

Kim, Junwoo;Kim, Duk-jin;Sohn, Hong-Gyoo;Choi, Jinmu;Im, Jungho
- Korean Journal of Remote Sensing
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- v.38 no.5_2
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- pp.661-667
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- 2022
As remote sensing and GIS have been considered to be essential technologies for disasters information production, researches on developing methods for analyzing spatial data, and developing new technologies for such purposes, have been actively conducted. Especially, it is assumed that the use of remote sensing and GIS for disaster management will continue to develop thanks to the launch of recent satellite constellations, the use of various remote sensing platforms, the improvement of acquired data processing and storage capacity, and the advancement of artificial intelligence technology. This spatial issue presents 10 research papers regarding ship detection, building information extraction, ocean environment monitoring, flood monitoring, forest fire detection, and decision making using remote sensing and GIS technologies, which can be applied at the disaster prediction, monitoring and response stages. It is anticipated that the papers published in this special issue could be a valuable reference for developing technologies for disaster management and academic advancement of related fields.
https://doi.org/10.7780/kjrs.2022.38.5.2.1 인용 PDF KSCI HTML

Park, Min-Chul;Cheoi, Kyung-Joo
- 한국정보디스플레이학회:학술대회논문집
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- 2007.08b
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- pp.1737-1738
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- 2007
An intelligent remote controller for 3-D TV interface exploits an artificial system of human visual attention for an easy interaction.
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