• 한국정보통신학회논문지
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• 제11권7호
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• pp.1359-1366
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• 2007

최근 광통신 용량은 VoIP, AUdio/Video 스트리밍의 멀티미디어 서비스 수요로 인한 정보통신 용량의 증가에 비례하여 증가하고 있다. 초고속 광통신망에서 추가적인 광섬유망과 고속장비 없이 이를 해결하기 위한 방법으로 DWDM(Dense Wavelength Division Multiplexing) 기법이 대두되고 있다. 따라서, 본 논문에서는 이러한 기능을 갖는 광필터를 설계하기 위하여 광섬유 한쪽의 클래드를 연마하여 다층 슬래브 도파로에 결합시킨 형태의 광섬유/다층 슬래브 결합구조의 광필터를 제안하였다. 제안된 광필터는 $1.5{\mu}m$ 통신창에서 분리간격이 $4.15{\mu}m$일 때 65nm의 편광 독립성, TM 모드와 TE 모드에 대해 중심파장이 각각 ${\lambda}_0=1.54946\;{\mu}m$와 ${\lambda}_0=1.6144\;{\mu}m$일 때 0.1 nm의 FWHM(Full Width at Half Maximun) 특성을 가진다.

• 대한원격탐사학회지
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• 제21권1호
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• pp.73-81
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• 2005

We construct improved geocentric digital elevation model (DEM), estimate tidal dynamics and ice stream velocity over Sulzberger Ice Shelf, West Antarctica employing differential interferograms from 12 ERS tandem mission Synthetic Aperture Radar (SAR) images acquired in austral fall of 1996. Ice, Cloud, and land Elevation Satellite (ICESat) laser altimetry profiles acquired in the same season as the SAR scenes in 2004 are used as ground control points (GCPs) for Interferometric SAR (InSAR) DEM generation. 20 additional ICESat profiles acquired in 2003-2004 are then used to assess the accuracy of the DEM. The vertical accuracy of the OEM is estimated by comparing elevations with laser altimetry data from ICESat. The mean height difference between all ICESat data and DEM is -0.57m with a standard deviation of 5.88m. We demonstrate that ICESat elevations can be successfully used as GCPs to improve the accuracy of an InSAR derived DEM. In addition, the magnitude and the direction of tidal changes estimated from interferogram are compared with those predicted tidal differences from four ocean tide models. Tidal deformation measured in InSAR is -16.7cm and it agrees well within 3cm with predicted ones from tide models. Lastly, ice surface velocity is estimated by combining speckle matching technique and InSAR line-of-sight measurement. This study shows that the maximum speed and mean speed are 509 m/yr and 131 m/yr, respectively. Our results can be useful for the mass balance study in this area and sea level change.

• 한국산업보건학회지
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• 제29권3호
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• pp.358-367
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• 2019

Objectives: This study aimed to review model algorithms and input parameters applied to some exposure models and to compare the simulated estimates using an exposure scenario from each model. Methods: A total of five exposure models which can estimate inhalation exposure were selected; the Korea Ministry of Environment(KMOE) exposure model, European Centre for Ecotoxicology and Toxicology of Chemicals Targeted Risk Assessment(ECETOC TRA), SprayExpo, and ConsExpo model. Algorithms and input parameters for exposure estimation were reviewed and the exposure scenario was used for comparing the modeled estimates. Results: Algorithms in each model commonly consist of the function combining physicochemical properties, use characteristics, user exposure factors, and environmental factors. The outputs including air concentration ($mg/m^3$) and inhaled dose(mg/kg/day) are estimated applying input parameters with the common factors to the algorithm. In particular, the input parameters needed to estimate are complicated among the models and models need more individual input parameters in addition to common factors. In case of CEM, it can be obtained more detailed exposure estimates separating user's breathing zone(near-field) and those at influencing zone(far-field) by two-box model. The modeled exposure estimates using the exposure scenario were similar between the models; they were ranged from 0.82 to $1.38mg/m^3$ for concentration and from 0.015 to 0.180 mg/kg/day for inhaled dose, respectively. Conclusions: Modeling technique can be used for a useful tool in the process of exposure assessment if the exposure data are scarce, but it is necessary to consider proper input parameters and exposure scenario which can affect the real exposure conditions.

• 문화기술의 융합
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• 제5권4호
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• pp.407-412
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• 2019

본 논문에서는 한글 단어 단위의 음성 인식 처리 기술을 제안한다. 음성 인식은 마이크와 같은 센서를 사용하여 얻은 음향학적 신호를 단어나 문장으로 변환시키는 기술이다. 대부분의 외국어들은 음성 인식에 있어서 어려움이 적은 편이다. 그에 반면, 한글의 모음과 받침 자음 구성이어서 음성 합성 시스템으로부터 얻은 문자를 그대로 사용하기에는 부적절하다. 기존 구조의 음성 인식 기술을 개선해야만 보다 정확하게 단어를 인식할 수 있다. 이러한 문제를 해결하기 위해 기존 방식의 음성 인식구조에 새로운 알고리즘을 추가하여 음성 인식률을 높이게 하였다. 먼저 입력된 단어를 전처리 과정을 수행한 후 결과를 토큰 처리한다. 레벤스테인 거리 알고리즘과 해싱 알고리즘에서 처리된 결과 값을 조합한 후 자음 비교 알고리즘을 거쳐 표준 단어를 출력한다. 최종 결과 단어를 표준화 테이블과 비교하여 존재하면 출력하고 존재하지 않으면 테이블에 등록하도록 하였다. 실험 환경은 스마트폰 응용 프로그램을 개발하여 사용하였다. 본 논문에서 제안된 구조는 기존 방식에 비해 인식률의 성능이 표준어는 2%, 방언은 7% 정도 향상되었음을 보였다.

• Geomechanics and Engineering
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• 제17권6호
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• pp.535-541
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• 2019

Combining the radial well drilling and hydraulic fracturing technique, the production capacity of the reservoirs with low-permeability can be improved effectively. Due to the existence of radial holes, the stress around the well is redistributed, and the initiation and propagation of hydraulic fractures are different with those in traditional hydraulic fracturing. Therefore, it is necessary to study the influences of radial horizontal wells on hydraulic fracturing. The laboratory experiment was conducted to simulate the hydraulic fracturing on the physical model with radial holes. The experimental results showed that, compared with the borehole without radial holes, the sample with radial hole in the direction of maximum horizontal stress was fractured with significantly lower pressure. As the angle between direction of the horizontal hole and the maximum horizontal stress increased, the breakdown pressure grew. While when the radial hole was drilled towards the direction of the minimum horizontal stress, the breakdown pressure increased to that needed in the borehole without radial holes. When the angle between the radial hole and the maximum horizontal stress increase, the pressure required to propagate the fractures grew apparently, and the fracture become complex. Meanwhile, the deeper the radial hole drilled, the less the pressure was needed for fracturing.

• 디지털융복합연구
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• 제17권9호
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• pp.343-347
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• 2019

본 연구는 민간에서 생산된 청화자기에 그려진 청화회화의 주제 및 기법 속에 민속성과 예술성이 어떻게 융합되었는가 하는 것을 다루고자 한다. 이에 경덕진을 중심으로 한 청화자기의 등장의 역사적 배경을 살펴보고 민간청화자기에서 드러나는 민속성과 예술성에 대해 살펴본다. 관요에서 시작한 청화자기는 명 청 시기를 거쳐 민간으로 확대된다. 민간청화회화는 그 소비자가 민중인 만큼 민속적인 소재들을 화제로 사용하였고, 개인의 감성을 투영한 자유분방한 선들이 도자기 위에 그려졌다. 그러므로 관요와는 다른 미감을 이루었다. 따라서 이와 같은 민간청화회화의 발전은 우리의 물질세계를 풍부하게 하였을 뿐 아니라, 중국 전통문화의 특수한 정신세계를 이루도록 하였다. 주제의 민속성과 예술성이 완미하게 결합함으로서 도자회화 발전과 민족문화 발전에 매우 중요한 작용을 하게 되었다.

• 산업경영시스템학회지
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• 제42권3호
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• pp.184-192
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• 2019

Focusing on the emerging influencer market of SNS (Social Network Service), This study attempts to clarify the priority of Influencer characteristics when the customer decided to purchase products through the promotion of influencers. Since the influencer marketing differs from the Online information source marketing, this study has an academic implication in that integrated the influence of the characteristics of the Online information sources and the characteristics of SNS contents. For this purpose, through the literature research on Information sources and Influencers, the characteristics of influencers were reconstructed and priorities were derived using the AHP (Analytic Hierarchy Process) technique. The upper layer of the AHP structure was set to expertise, trustworthiness, social attractiveness, and content attractiveness, and the lower layer structured the model with 13 subfactors. The results are summarized as follows. First, in the result of combining the importance of the $1^{st}$ and $2^{nd}$ classes, the detailed factors of expertise and trustworthiness, ranked from the top to six, are largely influenced in purchasing decisions in influencer marketing. Second, content attractiveness is the third rank in the $1^{st}$ layer. Influencer marketing shows that content is more important than social attractiveness. Besides, the $7^{th}$ to $9^{th}$ positions of the overall rankings accounted for visual information, storytelling, and external attractiveness, which are the details of content attractiveness, and it is confirmed that it is more effective for influencer marketing to emphasize content attractiveness than social attractiveness. Although the influencer marketing differs from the existing information marketing, this study has an academic implication in that integrated the influence of the characteristics of the source and the characteristics of the contents.

• Earthquakes and Structures
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• 제17권2호
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• pp.233-244
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• 2019

In this work, we have studied the effects of different soil thicknesses, haunch heights, reinforcement forms and construction technologies on the seismic performance of a composite precast fabricated utility tunnel by pseudo-static tests. Five concrete specimens were designed and fabricated for low-cycle reciprocating load tests. The hysteretic behavior of composite precast fabricated utility tunnel under simulated seismic waves and the strain law of steel bars were analyzed. Test results showed that composite precast fabricated utility tunnel met the requirements of current codes and had good anti-seismic performance. The use of a closed integral arrangement of steel bars inside utility tunnel structure as well as diagonal reinforcement bars at its haunches improved the integrity of the whole structure and increased the bearing capacity of the structure by about 1.5%. Increasing the thickness of covering soil within a certain range was beneficial to the earthquake resistance of the structure, and the energy consumption was increased by 10%. Increasing haunch height within a certain range increased the bearing capacity of the structure by up to about 19% and energy consumption by up to 30%. The specimen with the lowest haunch height showed strong structural deformation with ductility coefficient of 4.93. It was found that the interfaces of haunches, post-casting self-compacting concrete, and prefabricated parts were the weak points of utility tunnel structures. Combining the failure phenomena of test structures with their related codes, we proposed improvement measures for construction technology, which could provide a reference for the construction and design of practical projects.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제8권3호
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• pp.123-128
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• 2019

본 논문에서는 RCNN (recurrent convolution neural network) 계층 모델을 채택한 인공 지능에 기반을 둔 주가 예측을 제안한다. LSTM (long-term memory model) 기반 신경망은 시계열 데이터의 예측에 사용된다. 다른 한편, 컨볼루션 신경망은 데이터 필터링, 평균화 및 데이터 확장을 제공한다. 제안된 주가 예측에서는 위에서 언급 한 장점들을 RCNN 모델에서 결합하여 적용함으로써 다음날의 주가 종가를 예측한다. 그리고 최근의 시계열의 데이터를 강조하기 위해 커스텀 가중치 손실 함수가 채택되었다. 또한 시장의 상황을 반영하기 위해 주가 인덱스에 관련된 데이터를 입력으로 포함하였다. 제안된 주가 예측 방식은 실제 주가를 대상으로 한 실험에서 3.19%로 테스트 오차를 줄였으며, 다른 방법보다 약 19%의 성능 향상을 거둘 수 있었다.

• 한국컴퓨터정보학회논문지
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• 제24권5호
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• pp.149-156
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• 2019

The existing subtract image based intrusion detection system for CCTV digital images has a problem that it can not distinguish intruders from moving backgrounds that exist in the natural environment. In this paper, we tried to solve the problems of existing system by designing real - time intrusion detection system for CCTV digital image by combining subtract image based intrusion detection method and background learning artificial neural network technology. Our proposed system consists of three steps: subtract image based intrusion detection, background artificial neural network learning stage, and background artificial neural network evaluation stage. The final intrusion detection result is a combination of result of the subtract image based intrusion detection and the final intrusion detection result of the background artificial neural network. The step of subtract image based intrusion detection is a step of determining the occurrence of intrusion by obtaining a difference image between the background cumulative average image and the current frame image. In the background artificial neural network learning, the background is learned in a situation in which no intrusion occurs, and it is learned by dividing into a detection window unit set by the user. In the background artificial neural network evaluation, the learned background artificial neural network is used to produce background recognition or intrusion detection in the detection window unit. The proposed background learning intrusion detection system is able to detect intrusion more precisely than existing subtract image based intrusion detection system and adaptively execute machine learning on the background so that it can be operated as highly practical intrusion detection system.