• 대한약학회:학술대회논문집
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• 대한약학회 2001년도 Proceedings of International Convention of the Pharmaceutical Society of Korea
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• pp.298.1-298.1
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• 2001

• 한국환경과학회:학술대회논문집
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• 한국환경과학회 2020년도 정기학술대회 발표논문집
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• pp.121-121
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• 2020

• 한국환경과학회:학술대회논문집
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• 한국환경과학회 2020년도 정기학술대회 발표논문집
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• pp.128-128
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• 2020

• 인포메이션 디스플레이
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• 제24권4호
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• pp.3-11
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• 2023

• 한국콘텐츠학회논문지
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• 제11권3호
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• pp.108-115
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• 2011

대학 연구기관 등의 연구실에서 감전, 전기화재 등 전기사고방지를 위해 수행하는 전기분야 정기점검에 대한 문제점을 파악하고 명확한 기준이 없는 점검항목에 대해 실제 효율적으로 적용 가능하도록 구체적인 기준을 제시한다. 그래서 연구실 전기안전취약요인을 개선하도록 체계적이고 능률적인 정기점검 실시를 위한 표준모델을 마련하고자 한다. 또한, 모든 연구실의 전기안전환경을 중심으로 객관적인 평가가 가능하도록 공통으로 적용될 수 있는 점검항목을 도출하여 연구실 전기안전관리에 부합하도록 연구실 정기점검 전기분야 체크리스트를 개발 한다. 본 연구에서 개발된 전기분야 체크리스트는 실제 필요한 점검 항목에 대한 명확한 기준을 설정하여 모든 연구실에 공통으로 적용할 수 있도록 개발하여 정기점검 수행시 바로 실행 가능하도록 하였다. 이는 연구실의 전기사고 방지를 위한 효율적인 점검뿐만 아니라, 연구실안전수준을 전반적으로 상승시킬 것이다.

• 전자통신동향분석
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• 제34권4호
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• pp.55-64
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• 2019

In this study, we introduce trends in neural-network-based deep learning research applied to dialogue systems. Recently, end-to-end trainable goal-oriented dialogue systems using long short-term memory, sequence-to-sequence models, among others, have been studied to overcome the difficulties of domain adaptation and error recognition and recovery in traditional pipeline goal-oriented dialogue systems. In addition, some research has been conducted on applying reinforcement learning to end-to-end trainable goal-oriented dialogue systems to learn dialogue strategies that do not appear in training corpora. Recent neural network models for end-to-end trainable chit-chat systems have been improved using dialogue context as well as personal and topic information to produce a more natural human conversation. Unlike previous studies that have applied different approaches to goal-oriented dialogue systems and chit-chat systems respectively, recent studies have attempted to apply end-to-end trainable approaches based on deep neural networks in common to them. Acquiring dialogue corpora for training is now necessary. Therefore, future research will focus on easily and cheaply acquiring dialogue corpora and training with small annotated dialogue corpora and/or large raw dialogues.

• 전자통신동향분석
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• 제34권4호
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• pp.43-54
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• 2019

Currently, a majority of artificial intelligence is used to secure big data; however, it is concentrated in a few of major companies. Therefore, automatic data augmentation and efficient learning algorithms for small-scale data will become key elements in future artificial intelligence competitiveness. In addition, it is necessary to develop a technique to learn meanings, correlations, and time-related associations of complex modal knowledge similar to that in humans and expand and transfer semantic prediction/knowledge inference about unknown data. To this end, a neural memory model, which imitates how knowledge in the human brain is processed, needs to be developed to enable knowledge expansion through modality cooperative learning. Moreover, declarative and procedural knowledge in the memory model must also be self-developed through human interaction. In this paper, we reviewed this essential methodology and briefly described achievements that have been made so far.

• 전자통신동향분석
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• 제34권5호
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• pp.81-90
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• 2019

The data rate for transmission through fiber-optic cables has increased to 400 Gbps in single-wavelength channels. However, speeds up to 1 Tbps are required now to meet the ever-increasing bandwidth demand driven by the diverse requirements of contemporary applications for high-quality on-demand video streaming, cloud services, various social media, and emerging 5G-enabled applications. Because the data rates of the per-channel optical interfaces depend strongly on the operational speed of the optoelectronic devices used in optical transceivers, ultrahigh-speed photonic devices and components, and eventually, chip-level transmitter and receiver technologies, are essentially required to realize futuristic optical transceivers with data rates of 1 Tbps and beyond. In this paper, we review the recent progress achieved in high-speed optoelectronic devices, such as laser diodes, optical modulators, photodiodes, and the transmitter-receiver optical subassembly for optical transceivers in data centers and in metro/long-haul transmission.

• 전자통신동향분석
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• 제36권1호
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• pp.43-53
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• 2021

Super-realistic content technology has recently attracted attention as a core of the "new normal" that can overcome the spatial constraints caused by pandemics. It is moreover the core that allows users in remote locations to meet and engage in various social, cultural, and economic activities based on a network. Content technology is rapidly spreading beyond the existing entertainment area to various industries as an innovative tool that can be used to overcome space-time constraints and improve the productivity of industrial sites, because reality and virtual reality are now super-connected with ultra-low latency. However, existing services such as teleconferencing and tele-collaboration do not provide a level of realism that replaces face-to-face services, and various technical requirements have been proposed to overcome this. The trends in core technologies such as XR twins, hyper-realistic reproduction, sensory interaction, and emotional recognition technology, which are necessary for interactive realistic content that leads to feelings, from reproduction to experience and emotion, are explained. In this article, our aim is to present the future of realistic content that enables human care and can even overcome psychological difficulties such as the "Corona blues".

• 전자통신동향분석
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• 제36권3호
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• pp.12-22
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• 2021

Since the technical realization of self-aligned planar complementary metal-oxide-semiconductor field-effect transistors in 1960s, semiconductor manufacturing has aggressively pursued scaling that fruitfully resulted in tremendous advancement in device performances and realization of features sizes smaller than 10 nm. Due to many intrinsic material and technical obstacles, continuing the scaling progress of semiconductor devices has become increasingly arduous. As an effort to circumvent the areal limit, stacking devices in a three-dimensional fashion has been suggested. This approach is commonly called monolithic three-dimensional (M3D) integration. In this work, we examined technical issues that need to be addressed and overcome to fully realize energy efficiency, short latency and cost competency. Full-fledged M3D technologies are expected to contribute to various new fields of artificial intelligence, autonomous gadgets and unknowns, which are to be discovered.