• Journal of the Society of Cosmetic Scientists of Korea
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• v.29 no.1
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• pp.135-150
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• 2003

This study is described the stabilizing technology of water-in-oil (w/o) emulsion and the mechanism of emulsification with quaternium-18 hectorite (Q-18 HTRT) by swelling action. When Q-18 HTRT is dispersed in oil, it swells and constructs card-house structure adding ethanol, and formation of water phase is caused by hydrogen bonding. The gelling activities of Q-18 HTRT were excellent such as mineral oil, squalane, cetostearyl isononanoate, isostearic acid, cetyl octanoate, octyl dodecanol and so on. Especially, when oil gel containing Q-18 HTRT passed one to three times by Roll mill. It made the W/O emulsion cream (W/O-ECRM) having 2.0 w/w% of Q-18 HTRT and also produced the control sample (control) including 3.0 w/w% of cetyl PEG/PPG- l0/l dimethicone. The stability of after 24 weeks, Hardness of W/O-ECRM dropped 7.48%, whereas hardness of control went down 57 71%. As a result of these test emulsification of W/O-ECRM is superior compared with control. In cosmetic, 0-18 HTRT can use as suspending agent, oil adsorbent, emulsifying agent, dispersing agent, viscosifier and pigment.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.234-238
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• 2005

유비쿼터스 컴퓨팅과 유비쿼터스 네트워크를 통해 새롭고 다양한 서비스가 창출되고 있다. 특히, 언제 어디서나 사람과 사물 같은 객체의 위치를 인식하고 이를 기반으로 유용한 서비스를 제공하는 유비쿼터스 위치기반 서비스(Ubiquitous Location Based Services: u-LBS)가 중요한 서비스로 대두되고 있다. 이와 같이 유비쿼터스 환경에서 유용한 많은 응용 기술들이 개발되고 있다. 본 논문에서는 개발한 eCRM 모바일 콜센터는 기존에 기업들이 eCRM을 이용하여서 고객 마케팅하는데, 이를 보다 더 효율적으로 하기 위해서 u-LBS 기반 기술을 이용하여 eCRM 모바일 콜센터를 개발하였다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.301-321
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• 2024

Generative artificial intelligence is currently developing rapidly and expanding industrially. The development of generative AI is expected to improve productivity in most industries. However, there is a probability for exploitation of generative AI, and cases that actually lead to crime are emerging. Compared to the fast-growing AI, there is no legislation to regulate the generative AI. In the case of Korea, the crimes and risks related to generative AI has not been clearly classified for legislation. In addition, research on the responsibility for illegal data learned by generative AI or the illegality of the generated data is insufficient in existing research. Therefore, this study attempted to classify crimes related to generative AI for domestic legislation into generative AI for target crimes, generative AI for tool crimes, and other crimes based on ECRM. Furthermore, it suggests technical countermeasures against crime and risk and measures to improve the legal system. This study is significant in that it provides realistic methods by presenting technical countermeasures based on the development stage of AI.