• Proceedings of the Korean Vacuum Society Conference
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• 2010.08a
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• pp.206-206
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• 2010

1차원 나노 소재 중 ZnO 나노선은 우수한 전기적, 광학적 특성으로 최근 센서, 디스플레이등 다양한 정보전자 소자에 활용 가능성이 높아지고 있다. 현재 보고된 ZnO 나노선 소자는 주로 단일선이나 랜덤 네트워크 형태로 제작되어 소자의 공정성, 재현성 및 균일성 확보가 매우 중요한 이슈가 된다. 본 연구에서는 화학기상증착법으로 성장한 ZnO 나노선을 슬라이딩 트랜스퍼 공정을 통하여 원하는 기판에 정렬된 형태로 전이하여 전계방출소자 (field effect transistor) 어레이를 제작하고 그 특성을 분석하였다. 또한, p-형으로 도핑된 Si 기판을 패터닝하여 정렬된 ZnO 나노선과 pn-정션 소자를 제작하여 정류특성과 electroluminescence 특성을 분석, 설명하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.323-327
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• 2004

우리나라의 경우 짧은 자료기간으로 인해 지점빈도해석에 의한 확률강우량 추정시 불확실성이 커지는 문제가 있어 지역빈도해석의 적용이 필요하다. 본 인구에서는 지역빈도해석 기법의 하나인 FORGEX 기법을 우리나라 강우자료에 적용하였다. 전국의 82개 기상청 산하 관측지점의 자료로부터 지속기간별 연최대 강우 자료를 추출하였으며, FORGEX 기법의 절차애 따라 확률강우량을 계산하고자 하는 지점을 중심으로 네트워크를 구성하였다 Netmax 계열을 이용하여 긴 재현기간에 내한 안정된 확률강우량을 추정할 수 있는 성장곡선을 유도할 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.228-230
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• 2019

일상생활에서 빈번히 사용되는 주변 생활 제품은 기술의 급속한 발전과 더불어 지능화 정도가 가속화 되고 있는 추세에 있다. 일반적으로 LED 조명이나 실내 에어컨을 자동으로 조정하거나 자동청소로봇 등은 이미 일반화된 제품들이다. 그럼에도 불구하고 우리 생활에서 가장 필요한 용품인 거울에 대한 지능적인 제품은 비교적 고가이어서 소비자가 쉽게 접근하기 어려운 생활용품이 되고 있어서 지능화 제품의 보급이 더딘편이다. 따라서 본 논문에서는 Raspberry Pi 3B+ 를 기반으로 하여 음성제어가 가능한 스마트 미러를 설계하고 구현하였다. 이를 위하여 저렴한 raspberry pi의 WiFi를 통해 네트워크에 연결하도록 하여 미러가 시간, 날씨 및 뉴스 정보 기능을 자동으로 업데이트 할 수 있도록 하였고 기상 조건, 사전 시간 또는 음악 재생과 같은 음성 제어가 가능하기 위하도록 Google Asistant 음성 인터페이스를 적용하였다. 본 논문에서 제안한 제품이 실용화될 경우 저가이면서 고기능 사양을 제공하고 있어서 스마트 미러 보급에 많은 기여가 예산된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.1077-1078
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• 2012

시계열 데이터는 기상데이터, 주식데이터, 센서 데이터, 네트워크 트래픽 데이터, 의료 데이터 등 다양한 분야에서 사용되고 있다. 그 중에서 서브시권스 매칭 방법은 시계열 데이터베이스 어플리케이션에서 많은 주목을 받고 있다. 기존의 서브시권스 매칭 방법은 단일 윈도우만을 비교하여 서브시권스 매칭을 수행하였으나, 착오해답을 줄이는 데에는 한계가 있었다. 따라서 다중 윈도우를 비교하여 착오해답을 줄이고 성능을 높일 수 있는 다중 윈도우를 이용한 서브시퀀스 매칭 방법을 구현하였다. 그 결과 단일 윈도우를 사용했을 때보다 약 4.8배까지 후보집합의 수가 줄어드는 것을 볼 수 있었다.

• Journal of Advanced Navigation Technology
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• v.21 no.4
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• pp.365-370
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• 2017

This study analyze correlation between weekdays data and special days data of different power demand patterns, and builds a separate data set, and suggests ways to reduce power demand prediction error by using deep learning network suitable for each data set. In addition, we propose a method to improve the prediction rate by adding the environmental elements and the separating element to the meteorological element, which is a basic power demand prediction elements. The entire data predicted power demand using LSTM which is suitable for learning time series data, and the special day data predicted power demand using DNN. The experiment result show that the prediction rate is improved by adding prediction elements other than meteorological elements. The average RMSE of the entire dataset was 0.2597 for LSTM and 0.5474 for DNN, indicating that the LSTM showed a good prediction rate. The average RMSE of the special day data set was 0.2201 for DNN, indicating that the DNN had better prediction than LSTM. The MAPE of the LSTM of the whole data set was 2.74% and the MAPE of the special day was 3.07 %.

• Journal of Korea Multimedia Society
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• v.16 no.6
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• pp.667-677
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• 2013

With the huge success of Social Network Services, studies on social network analysis to extract the current issues or to track the symptoms of epidemic disease are being carried out actively. On Twitter, tweets reflect people's reaction to an event and users' individual status well, so it is possible to detect an event regarding a tweet as a sensory value. Recently, social signals are used to detect the spread of illness like the flu as well as the occurrence of disaster event like an earthquake in early stages. In this paper, we set up a cold as a target event and regarded tweets as Cold Signals. To evaluate the reliability of Cold Signals, we analyzed correlations between weather factors and the cold index provided by Korea Meteorological Administration.

• Polymer(Korea)
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• v.31 no.2
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• pp.117-122
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• 2007

In this work, the mechanical and electrical properties, and thermal stability of vapor-grown carbon nanofibers/polyimide (VGCNFs/PI) composite film synthesized by in-situ polymerization were investigated in terms of tensile properties, volume resistivity and thermogravimetric analysis (TGA), respectively. From the results, the addition of VGCNFs with a certain amount into polyimide led to obvious improvement in tensile strength. The volume resistivity of the films was decreased with increasing the VGCNFs content and the electrical percolation threshold appeared between 1 and 3 wt% of VGCNFs content, which was probably caused by the formation of interconnective structures among the VGCNFs in a composite system. The thermal stability of the film was higher than that of pure PI one. This result indicated that the crosslinking of VGCNFs/PI Composites was enhanced by well-distribution of YGCNFs in PI resin, resulting in the increase of the thermal stability of the resulting composites.

• Proceedings of KOSOMES biannual meeting
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• 2008.05a
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• pp.191-195
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• 2008

In Ansan (the headquarter of KORDI ; Korea Ocean Research & Development Institute), KOSC(Korea Ocean Satellite Center) is being prepared for acquisition, processing and distribution of sensor data via L-band from GOCI(Geostationary Ocean Color Imager) instrument which is loaded on COMS(Communication, Ocean and Meteorological Satellite); it will be launched in 2009. The basis equipment of KOSC(Electric power, Network, Security) has been constructed in 2007. KOSC is being constructed data processing and management system, GOCI L-band reception system, etc. The final object of KOSC is that maximize the application of GOCI.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.1
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• pp.19-26
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• 2009

The standardization of eddy-covariance data processing is essential for the analysis and synthesis of vast amount of data being accumulated through continuous observations in various flux measurement networks. End users eventually benefit from the open and transparent standardization protocol by clear understanding of final products such as evapotranspiration and gross primary productivity. In this paper, we briefly introduced KoFlux efforts to standardize data processing methodologies and then estimated uncertainties of surface fluxes due to different processing methods. Based on our scrutiny of the data observed at Gwangneung KoFlux site, net ecosystem exchange and ecosystem respiration were sensitive to the selection of different processing methods. Gross primary production, however, was consistent within errors due to cancellation of the differences in NEE and Re, emphasizing that independent observation of ecosystem respiration is required for accurate estimates of carbon exchange. Nocturnal soil evaporation was small and thus the annually integrated evapotranspiration was not sensitive to the selection of different data processing methods. The implementation of such standardized data processing protocol to AsiaFlux will enable the establishment of consistent database for validation of models of carbon cycle, dynamic vegetation, and land-atmosphere interaction at regional scale.

• Polymer(Korea)
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• v.30 no.1
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• pp.85-89
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• 2006

The effect of vapor grown carbon fiber (VGCF) contents on electrical and rheological properties of VGCF filled polyphenylene sulfide (PPS) composites prepared through melt mixing using a twin screw exruder was studied. This method was proved to be quite effective to produce good dispersion of VGCF in the matrix even for highly filled PPS. From the dependence of the electrical conductivity on VGCF content, the percolation phenomena began to occur above $10\;wt\%$. While there is only a marginal increase of viscosity for 1 and $5\;wt\%$ VGCF filled PPS, the composites containing $10\;wt\%$. While VGCF showed abrupt increase in viscosity as well as flattening of frequency vs modulus curve, indicating a transition from a liquid-like to a solid-like behavior due to the creation of VGCF network. This result agrees well to the fact that the network formation in the composite can be composite by rheological property dependence on filler content as well as by electrical conductivity measurement.