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정영준(Jung, Yung joon),고현우(Goh, Hyun woo) 한국전시산업융합연구원 2015 한국과학예술융합학회 Vol.20 No.-
물류운영비의 효율을 높이기 위한 국내·외 표준에 대한 연구가 진행되어 오고 있다. 파렛트, 콘테이너등의 기기를 사용하여 물류를 표준화 할 수 있는 ULS(Unit Load System) 물류표준의 도입비율은 여전히 낮다. 특히, 상온 제품에 대한 ULS에 대한 연구는 많으나 냉동 및 냉장 제품에 대한 연구는 거의 없는 실정이다. 본 연구에서는 국내 아이스크림 산업에 대한 ULS 도입에 관한 연구를 A기업을 대상으로 진행한다. 그래서 포장, 보관, 하역, 운송 그리고 정보화의 물류기능별 도입 방안을 제시하고 그 결과로 개선 효과를 보임으로서 냉동식품 물류의 ULS 도입의 타당성을 보인다. The progress of the national and international standards for the efficiency of logistics costs and the operation is being studied and established. The ratio of logistics standards is still low and it is emphasized to use the unit load system using a pallet so far. Previous studies are usually studied about room temperature products. It is needed to study about the unit load system in a sub-zero temperature. In this study, it is conducted an improvement study about the unit load system based on a domestic ice cream manufacturer and distributor of the "A" company. So, packaging, storage, handling, transport and logistics function presents Introduction of computerization and show the feasibility of the introduction of frozen food logistics as ULS show the improvement in the results.
유승목,이경희,박재복,윤석진,조창식,정영준,조일연,Yoo, Seung-mok,Lee, Kyung Hee,Park, Jaebok,Yoon, Seok Jin,Cho, Changsik,Jung, Yung Joon,Cho, Il Yeon 한국전자통신연구원 2019 전자통신동향분석 Vol.34 No.4
Deep learning is a hot topic in both academic and industrial fields. Deep learning applications can be categorized into two areas. The first category involves applications such as Google Alpha Go using interfaces with human operators to run complicated inference engines in high-performance servers. The second category includes embedded applications for mobile Internet-of-Things devices, automotive vehicles, etc. Owing to the characteristics of the deployment environment, applications in the second category should be bounded by certain H/W and S/W restrictions depending on their running environment. For example, image recognition in an autonomous vehicle requires low latency, while that on a mobile device requires low power consumption. In this paper, we describe issues faced by embedded applications and review popular inference engines. We also introduce a project that is being development to satisfy the H/W and S/W requirements.