• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.639-639
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• 2015

최근 지식정보 사회는 IT가 핵심 구성요소인 스마트 사회로 변모하고 있으며, 인간과 사물 간 의사소통에서 사물과 사물 간 의사소통까지 확장하고, IT간 융합에서 나아가 타 산업과 융합하는 지능형 사회로 나아가고 있다. '공간'에 대한 정보는 '시간'과 함께 인간이 생활하는데 있어 반드시 알아야 하는 가장 근본적인 정보로써, 공간에서 발생하는 정보를 기반으로 다른 사람들과 소통을 하고 목적을 충족함으로써 삶의 질을 향상시킨다. 현대 사회에서 공간정보는 중요한 인프라 가치를 증대시키므로 새로운 사회 패러다임 전환을 위한 필수적인 요소라 할 수 있다. 따라서 본 연구에서는 수재해 정보 플랫폼 구현에 앞서 사용자의 니즈를 만족시키고 효용가치 증대가 가능하도록 공간정보서비스 활용 방안 연구를 하고자 한다. 공간정보는 시대의 흐름에 따라 형태 및 생산?활용방법이 달라졌으나 항상 중요한 정보로 인식되어 왔으며, 미래 공간정보는 단순 콘텐츠 영역을 뛰어넘어 상황(Context)정보까지 범위를 확장하였다. (1)미국의 공간정보는 시설, 기록관리 및 지도와 같은 공공분야에서 현재는 업무통합관리, 의사결정지원 등에서 데이터 웨어하우스(Data Warehouse)로서의 역할 담당한다. (2)일본은 아시아 최고의 원천기술력을 보유하고 있으며, 높은 수준의 GIS, RS(위성항측), ITS(지능형 교통 시스템) 기술을 기반으로 하고 있다. (3)영국은 지리정보시스템과 공공서비스를 접목하여 시민의 요구에 부응하는 고객맞춤형서비스 제공을 국가정보화의 우선과제로 선정하고 있다. (4)우리나라는 초고속통신망과 모바일 기술 등 세계 최고 수준의 인프라를 확보하고 있어, 이러한 인프라 기반융 복합 공간정보서비스를 이용하는데 안정적인 기반을 확보하고 있다. 본 연구는 국내외 공간정보서비스의 패러다임 변화 및 추진 동향 등을 제시하였으며, 수재해정보 플랫폼 활용에 능동적 적극적으로 접근할 수 있는 기반을 마련하였다. 공간정보서비스를 활용하여 커뮤니케이션 강화, 수재해 정보 서비스의 효율성 증진, 재해부문 선진화 측면에서 발전적 영향을 미칠 수 있으며, 특히 각종 현안에 대한 미래 예측 및 대응에 기여할 것으로 판단된다.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.485-490
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• 2020

Recently, amid active research on domestic shipbuilding industry and IT convergence technology, with the development of satellite detection technology for ship safety operation, ships monitored the movement of ships with the mandatory long-range identification & tracking of vessels and automatic identification system. It is possible to help safe navigation, but it is necessary to develop safety device that alert the marine officer who rely on radar to correct conditions in case of weightlessness. Therefore, an ocean fog alarm system was developed to detect and inform using photo sensors. The fabricated ocean fog detect and alarm system consists of a small, low-power optical sensor transceiver and data sensing processing module. Through experiment, it is confirmed that the fabricated ocean fog detect and alarm system measure the corresponding concentration of ocean fog for fogless circumstance and fogbound circumstance, respectively. Furthermore, the fabricated system can control RPM of ship engine according to the concentration of ocean fog, and consequently, the fabricated system can be applied to assistant device for ship safety operation.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1677-1689
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• 2022

Air pollution is social issue that has long-term and short-term harmful effect on the health of animals, plants, and environments. Chimneys are the primary source of air pollutants that pollute the atmosphere, so their location and type must be detected and monitored. Power plants and industrial complexes where chimneys emit air pollutants, are much less accessible and have a large site, making direct monitoring cost-inefficient and time-inefficient. As a result, research on detecting chimneys using remote sensing data has recently been conducted. In this study, YOLOv5-based chimney detection model was generated using BUAA-FFPP60 open dataset create for power plants in Hebei Province, Tianjin, and Beijing, China. To improve the detection model's performance, data split and data augmentation techniques were used, and a training strategy was developed for optimal model generation. The model's performance was confirmed using various indicators such as precision and recall, and the model's performance was finally evaluated by comparing it to existing studies using the same dataset.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.200-209
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• 2022

Providing real-time location information is emerging as a major goal of the national industry. In order to provide such real-time location information (3D spatial information), it is essential to develop a technology for a satellite positioning method. Therefore, the country continues to make efforts to increase satisfaction with the needs of consumers by introducing the Network RTK GNSS method. In this study, among the Network RKT GNSS(Global Navigation Satellite System) methods provided by the National Geographic Information Service, continuous observation and single observation were measured at the integrated reference point using VRS(Virtual Reference Station) and FKP(Flӓachen-Korrektur Parameter) to evaluate accuracy. In addition, we aim to maximize efficiency by presenting accuracy on the rapidly increasing Network RTK GNSS method in the field.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.508-510
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• 2021

As the international standardization of 5G element technologies (e.g., 5G vertical satellite, direct communication functions between 5G NR (New Radio)-based devices) required not only in 5G verticals but also in autonomous navigation services is currently underway, it is expected to be utilized for autonomous navigation services while utilizing the economic size advantages of the scale of international standard-based solutions through 3GPP international standardization of marine communication services related to autonomous navigation vessels. In order to establish the ecosystem of ICT convergence market related to autonomous navigation vessels and to preoccupy core communication technology based on international standards, it is necessary to develop digital communication systems and gateways that have global compatibility, (2) secure core element technology based on next generation communication, and (3) promote international standardization for internationalization of related technologies. For this, data analysis and standard technology should be developed through service analysis by distance. Currently, the requirements for the operation of autonomous navigation vessels can be classified into three categories.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.114-114
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• 2021

본 연구에서는 Sentinel-1 SAR 센서 기반 이미지자료와 딥러닝기법을 이용하여 고해상도 토양수분을 산정하였다. 입력자료는 지표특성(모래함량, 점토함량, 경사도), 인공위성 기반의 강우와 LANDSAT 기반의 이미지자료(NDVI, LST, 공간분포 토양수분)를 사용하였다. 강우자료의 경우 GPM(Global Precipitation Measurement) 일강우 자료를 사용하였으며, 관측일 기준으로 5일전까지의 강우자료와 5일평균강우를 구분하여 사용하였다. LANDSAT 기반의 토양수분 이미지자료와 지점관측 토양수분을 이용하여 검·보정 이후 딥러닝 모형의 입력자료로 사용하였다. 입력자료는 30m × 30m 해상도로 Resample 하여 딥러닝 모형의 학습을 진행하였으며, 학습에 사용된 모형을 이용하여 Sentinel-1 기반의 고해상도(10m × 10m) 토양수분이미지를 산정하였다. 검증지점은 거창군 거창읍, 계룡시 두마면, 장수군 장수읍 및 무주군 무주읍 토양수분 관측지점을 선정하였다. 거창군 거창읍의 산정결과, LANDSAT 기반의 토양수분 이미지와 DNN 기반의 토양수분 이미지가 매우 유사하게 나타났으며, 모의값(DNN 기반 토양수분)이 실측값(LANDSAT 기반의 토양수분)을 잘 반영한 것(R: 0.875 ; RMSE: 0.013)으로 나타났다. 또한 학습모형을 토지피복이 유사한 지역에 적용하여 토양수분을 산정한 결과 검증지점 계룡시(R: 0.897 ; RMSE: 0.014), 장수군(R: 0.770 ; RMSE: 0.024) 및 무주군(R: 0.909 ; RMSE: 0.012)의 모의값이 실측값과 매우 유사한 것으로 나타났다. 이를 바탕으로 Seninel-1 SAR센서 이미지자료와 딥러닝기법을 연계한 고해상도 토양수분자료가 농업, 수문, 환경 등 다양한 분야에서 활용될 수 있을 것으로 판단된다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.667-669
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• 2021

Recently, RFID/USN technology has been applied in various fields such as logistics, environment, education, home network, disaster prevention, military, and medical care, but despite the remarkable development of RFID/USN technology, it is difficult to apply it to marine industry due to the characteristics of poor marine environment. Therefore, satellites are mainly used in the marine sector, and existing communication networks are used in the coast, so measures for forming a shelf-only short-range network in the ocean are being considered. In this paper, we consider the use of drones as mobile base stations of USN as a base station role using USN in existing PS-LTE and LTE networks.Since autonomous navigation vessels are aiming for the intelligent system, the number of crew and labor force should be reduced and the function of autonomous network formation in the form of more stable and intelligent ICT convergence technology should be strengthened.

• Progress in Superconductivity and Cryogenics
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• v.6 no.1
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• pp.12-17
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• 2004

High critical current density. $J_c$ over $1MA/cm^2$ at 77 K in a self field was successfully achieved from the YBCO film prepared on (100) $SrTiO_3$ single-crystal substrates by the TFA-MOD process. Unlike a normal TFA-MOD process, we prepared the TFA precursor solution by dissolving YBCO powder into the trifluoroacetic acid. A significant amount of the second phases, including $BaF_2$, was observed in the films fired at $700-725^{\circ}C$ for 2 h under $P(O_2)=10^{-3}$ atm and $P(H_2O)=4.2%$, most probably due to an insufficient reaction time, and hence $T_c$ was greatly degraded. However the films fired at $750-800^{\circ}C$ for 2 h were composed of strongly c-axis oriented YBCO grams without any second phases. and exhibited the $T_c$ values of 89.5 ~ 91 K with a sharp transition. With increasing the firing temperature from 750 to $800^{\circ}C$ average grain size of YBCO was increased and grain connectivity was enhanced. The highest $J_c$ value of $1.1MA/cm^2$ was obtained from the YBCO film fired at $800^{\circ}C$.

• Journal of the Korea Institute of Building Construction
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• v.24 no.1
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• pp.121-131
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• 2024

This research explores the potential of leveraging unstructured data from construction supervision documents, which contain detailed inspection insights from independent third-party monitors of building construction processes. With the evolution of analytical methodologies, such unstructured data has been recognized as a valuable source of information, offering diverse insights. The study introduces a framework designed to assess cost performance by applying advanced analytical methods to the unstructured data found in final construction supervision reports. Specifically, key phrases were identified using text mining and social network analysis techniques, and these phrases were then analyzed through binomial logistic regression to assess cost performance. The study found that predictions of cost performance based on unstructured data from supervision documents achieved an accuracy rate of approximately 73%. The findings of this research are anticipated to serve as a foundational resource for analyzing various forms of unstructured data generated within the construction sector in future projects.

• Korean Journal of Remote Sensing
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• v.35 no.6_3
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• pp.1173-1185
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• 2019

We, for the first time, retrieved sulfur dioxide (SO₂) vertical column density (VCD) in industrial and volcanic areas from TROPOspheric Monitoring Instrument (TROPOMI) using the Principle component analysis(PCA) algorithm. Furthermore, SO₂ VCDs retrieved by the PCA algorithm from TROPOMI raw data were compared with those retrieved by the Differential Optical Absorption Spectroscopy (DOAS) algorithm (TROPOMI Level 2 SO₂ product). In East Asia, where large amounts of SO₂ are released to the surface due to anthropogenic source such as fossil fuels, the mean value of SO₂ VCD retrieved by the PCA (DOAS) algorithm was shown to be 0.05 DU (-0.02 DU). The correlation between SO₂ VCD retrieved by the PCA algorithm and those retrieved by the DOAS algorithm were shown to be low (slope = 0.64; correlation coefficient (R) = 0.51) for cloudy condition. However, with cloud fraction of less than 0.5, the slope and correlation coefficient between the two outputs were increased to 0.68 and 0.61, respectively. It means that the SO₂ retrieval sensitivity to surface is reduced when the cloud fraction is high in both algorithms. Furthermore, the correlation between volcanic SO₂ VCD retrieved by the PCA algorithm and those retrieved by the DOAS algorithm is shown to be high (R = 0.90) for cloudy condition. This good agreement between both data sets for volcanic SO₂ is thought to be due to the higher accuracy of the satellite-based SO₂ VCD retrieval for SO₂ which is mainly distributed in the upper troposphere or lower stratosphere in volcanic region.