• Electronics and Telecommunications Trends
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• v.39 no.5
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• pp.98-107
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• 2024

Applications such as artificial intelligence continue to grow in complexity and scale. Thus, the demand for scalable computing is increasing for achieving faster data processing and improved efficiency. This requirement has led to the development of memory-centric computing and high-speed fabric interconnection technologies. Memory-centric computing reduces the latency and enhances the system performance by shifting the focus from the central processing unit to the memory, whereas high-speed fabric interconnects enable efficient data transfer across various computing resources. Technologies such as Gen-Z, OpenCAPI, and CCIX have been integrated into the CXL (Compute Express Link) standard since 2019 to improve communication and cache coherence. Ethernet-based interconnects such as RoCE, InfiniBand, and OmniXtend also play a crucial role in providing high-speed data transfer and low latency. We explore the latest trends and prospects of these technologies, highlighting their benefits and applications.

• The Science & Technology
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• v.34 no.3 s.382
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• pp.78-79
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• 2001

전남대 잡초학연구실은 유전공학기술을 이용하여 수확량을 최고 26%까지 증산할 수 있는 다수확성 벼를 개발하는데 성공하여 화제를 모으고 있다. 이번에 개발된 다수확 형질전환 벼가 상용화되면서 현재 5백만톤 수준의 우리나라 벼 생산량이 7백만톤까지 늘어나게 된다. 구자옥교수가 1978년 부임하면서 개설된 잡초학연구실은 제초제연구, 제초제 저항성 잡초종의 생리생태에 대한 연구, 제초제 저항성 벼품종 개발사업 등을 진행하고 있다.

• The Science & Technology
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• v.29 no.6 s.325
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• pp.86-87
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• 1996

인하대의 채재우교수가 이끄는 연소공학연구실은 환경문제와 관련한 청정기술을 집중개발하는 연구실로 러시아 과학자 7명을 비롯해 총 28명의 연구원이 밤과 낮을 가리지 않고 연구에 열중하고 있다. 올해 열리는 한국산업기술대전에 개인연구팀으로는 이례적으로 디젤자동차, 봉고 등의 연료분사기를 임의로 조절해 매연을 막는 '전자분사장치'를 출품하기 위해 준비에 바쁘게 움직이고 있다.

• Proceedings of the Korean Society of Coastal and Ocean Engineers Conference
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• 1993.07a
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• pp.86-89
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• 1993

본인은 1992년 12월 7일 부터 1993년 3월 31일 까지 일본 성 산하 항만기술연구소에서 신형방파제의 실험에 참여할 기회를 가졌으며, 이 기간동안 일본의 북단 북해도(Hokkaido)에서 남단 Okinawa 까지 항만시설, 특히 신형방파제의 건설현장과 설치운영 현장에 초점을 두고 살펴보았다. 신형방파제에 관한 실험은 항만기술연구소 수공부 내파연구실(구 방파제연구실)에서 실시하였는데 이 연구실은 30년 가까이 방파제에 관한 연구와 실험을 수행한 곳으로 Goda, Tanimoto 등이 실장으로 있었던 세계적인 수준의 연구실이라 할 수 있다. (중략)

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2003.11a
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• pp.475-476
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• 2003

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2004.11a
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• pp.445-446
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• 2004

• Economic and Environmental Geology
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• v.47 no.3
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• pp.227-235
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• 2014

For technology level assessment of KIGAM World Class Laboratories (WCL) candidates, bibliometric and qualitative analysis was conducted on their research papers listed on the SCIE database during 2009-2012. For the six research areas of geoscience and mineral resources, a research excellence indicator was applied using a Modified Rank Normalized Impact Factor (mrnIF), which was introduced by Heo et al. (2008) and Cho (2013). The KIGAM research department in rare metals utilization had the highest score for Impact Factor (IF) per paper in 2012 but the groundwater department or the exploration geophysics department came first based on the position and the mrnIF. Applying the mrnIF, the KIGAM research department in groundwater achieved excellent results in 2009 and 2011 and the urban mine department or exploration geophysics department came first place in other years. In the groundwater area, the percentage of research papers over 80 or 90 mrnIF, using Cho (2013)'s research excellence index, was the highest in 2011. The Cho (2013)'s excellent research indicator, 20%, the ratio of over 90 mrnIF was matched in the urban mining area for the whole research period, 2009-2012, and in the groundwater area for several years except 2010. Qualitative analysis of research papers can show the technology level of research departments. KIGAM World Class Laboratories (WCL) candidates should focus on increasing the quality and the quantity of their research papers.

• Composites Research
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• v.15 no.2
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• pp.64-69
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• 2002

• Journal of the Korean Institute of Gas
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• v.23 no.2
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• pp.45-54
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• 2019

According to the Laboratory Safety Act, each laboratory in the field of science and technology must conduct safety inspections and diagnosis every year or every two years. At present, the relevant guidelines are not clear, so there is a high possibility that inspection and diagnosis will become ineffective. In the laboratory, there is a pre-risk factor analysis system for hazardous factors, but there are many difficulties in implementation due to lack of education and understanding of the researchers, excessive work, etc. For the analysis of the opinions of experts in the safety field using the Delphi technique, we analyzed the following items: 1. Consideration in applying the Lab Safety Act, 2. Consideration in Lab Safety inspection and diagnosis, and 3. Government policy necessary for Lab. safety. Through the investigation and analysis of the detailed items, we extracted for problems and alternatives in current laboratory safety diagnosis and current law.

• Electronics and Telecommunications Trends
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• v.34 no.4
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• pp.15-22
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• 2019

Recent technological advances in three-dimensional (3D) sensing devices and machine learning such as deep leaning has enabled data-driven 3D applications. Research on artificial intelligence has developed for the past few years and 3D deep learning has been introduced. This is the result of the availability of high-quality big data, increases in computing power, and development of new algorithms; before the introduction of 3D deep leaning, the main targets for deep learning were one-dimensional (1D) audio files and two-dimensional (2D) images. The research field of deep leaning has extended from discriminative models such as classification/segmentation/reconstruction models to generative models such as those including style transfer and generation of non-existing data. Unlike 2D learning, it is not easy to acquire 3D learning data. Although low-cost 3D data acquisition sensors have become increasingly popular owing to advances in 3D vision technology, the generation/acquisition of 3D data is still very difficult. Even if 3D data can be acquired, post-processing remains a significant problem. Moreover, it is not easy to directly apply existing network models such as convolution networks owing to the various ways in which 3D data is represented. In this paper, we summarize technological trends in AI-based 3D content generation.