• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.123-123
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• 2018

가뭄은 홍수와 달리 진행속도가 비교적 느리기 때문에 초기에 감지한다면 피해를 최소화 할 수 있다. 국내에서는 가뭄전망을 위해 물리적 기반의 기상-수문연계해석 시스템을 구축하여 월 내지 계절전망을 수행하고 있다. 물리적 기반의 가뭄전망은 수치예보모델의 불확실성을 가지고 있으므로 예보 정확도 개선의 측면에서는 통계적 모델을 같이 활용하는 것이 바람직하다. 최근 국외에서는 통계적 방법인 AI (Artificial Intelligence) 기술을 사용하여 가뭄을 전망하는 연구가 활발히 진행 중이나, 아직까지 국내에서는 관련연구가 미흡한 실정이다. 이에 본 연구에서는 ANFIS (Adaptive Neuro-Fuzzy Inference System) 기반의 댐 유입량 예측 모델을 구축하고 SRI (Standardized Runoff Index)를 활용하여 수문학적 가뭄전망을 수행하였다. 대상유역은 국내 주요 다목적댐이 위치한 충주댐 유역과 소양강댐 유역을 선정하였다. 수문 및 기상자료는 국토 교통부 및 기상청의 관측 댐 유입량, 관측 강수량, 관측 기온 및 장기기상예보 자료를 사용하였다. ANFIS 모델 구축을 위한 훈련 및 보정기간과 검정기간은 각각 1987~2010년과 2011~2016년을 선정하였다. 수문학적 가뭄전망은 지속기간 3개월의 1개월 전망 SRI3를 활용하였으며, SRI3는 관측유입량과 예측유입량을 결합하여 산정하였다. 댐 예측유입량 및 수문학적 가뭄전망의 정확도 평가를 위해 상관계수, 평균제곱근오차를 활용하였다. 댐 예측유입량 평가 결과 예측값과 관측값의 상관계수가 높게 나타났으며, 평균제곱근오차는 낮아 예측성이 뛰어났다. SRI3의 경우 관측값과 예측값의 가뭄발생시기가 유사하여 가뭄을 적절하게 반영하는 것으로 나타났다. 본 연구의 결과는 통계적 기반의 수문학적 가뭄전망기법을 개발하였다는 측면에서 의의가 있으며, 향후 물리적 기반의 가뭄전망정보와 결합한다면 보다 실효성이 향상될 것으로 기대된다.

• Journal of Climate Change Research
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• v.2 no.3
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• pp.143-159
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• 2011

Projects applying the CDM methodology AM0035 of the $SF_6$ Emission Reductions in Electrical Grids should provide direct monitoring of all the key parameters that are related to estimation of baseline and project emissions including detailed explanations of key operating conditions and procedures, and an explanation addressing uncertainty as the result of EB meeting 41. Through this study, recovery ratio during maintenance, purity of $SF_6$ before and after disposal, replacing, loss rate of $SF_6$ before and after reclamation, leakage emission from electricity consumption and fossil fuel combustion, considered conservatively the key parameter of various monitoring. Consequently, confirmed the reduction in the amount of reduction due to the baseline emission decrease, project emission increase.

• Journal of the Korea Computer Graphics Society
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• v.25 no.1
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• pp.23-32
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• 2019

Cybersickness is a symptom of dizziness that occurs while experiencing Virtual Reality (VR) technology and it is presumed to occur mainly by crosstalk between the sensory and cognitive systems. However, since the sensory and cognitive systems cannot be measured objectively, it is difficult to measure cybersickness. Therefore, methodologies for measuring cybersickness have been studied in various ways. Traditional studies have collected answers to questionnaires or analyzed EEG data using machine learning algorithms. However, the system relying on the questionnaires lacks objectivity, and it is difficult to obtain highly accurate measurements with the machine learning algorithms. In this work, we apply Deep Neural Network (DNN) deep learning algorithm for objective cybersickness measurement from EEG data. We also propose a data preprocessing for learning and network structures allowing us to achieve high performance when learning EEG data with the deep learning algorithms. Our approach provides cybersickness measurement with an accuracy up to 98.88%. Besides, we analyze video characteristics where cybersickness occurs by examining the video segments causing cybersickness in the experiments. We discover that cybersickness happens even in unusually persistent changes in the darkness such as the light in a room keeps switching on and off.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.443-452
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• 2021

One of the key technologies in edge computing is that it always provides services close to the user by moving data between edge servers according to the user's movements. As such, the movement of data between edge servers is frequent. As IoT technology advances and usage areas expand, the data generated also increases, requiring technology to accurately track and process each data to properly manage the data present in the edge computing environment. Currently, cloud systems do not have data disposal technology based on tracking technology for data movement and distribution in their environment, so users cannot see where it is now, whether it is properly removed or not left in the cloud system if users request it to be deleted. In this paper, we propose a tracking data server to create and manage the movement and distribution of data for each edge server and data stored in the central cloud in an edge computing environment.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.29-39
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• 2021

As a means of solving traffic congestion in the downtown of large city, the interest in urban air mobility (UAM) using electric vertical take-off landing personal aerial vehicle (eVTOL PAV) is increasing. eVTOL configurations that will be used for UAM are classified by lift-and-cruise, tilt rotors, tilt-wings, tilted-ducted fans, multicopters, depending on propulsion types. This study tries to perform preliminary conceptual design for a given mission profile using reverse engineering techniques by taking the multicopter type Airbus's CityAirbus as a basic model. Wetted area, lift to drag ratio, drag coefficients were calculated using the OpenVSP which is an aerodynamic analysis software. The power required for each mission section of CityAirbus were calculated, and the corresponding battery and motor were selected. Also, total weight was predicted by estimating component weights of eVTOL.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.17-28
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• 2021

Recently, eVTOL, the next-generation of eco-friendly transportation, has been in the spotlight due to global warming along with traffic jams in large cities of many countries. This study benchmark the external features of Hyundai Motors S-A1, a compound eVTOL combined fixed and tilt rotors among many types of eVTOLs, to create the basic configuration using reverse design techniques. Basic configurations were created using CATIA and aerodynamic analyses were performed using the aircraft design and aerodynamic analysis programs, OpenVSP, XFLR5, and the aircraft wetted area, drag, and lift were calculated after selecting the airfoil, incidence angle, and dihedral and anhedral angles through trade study. Also, required powers were estimated for completing the given mission profile and components weight and the total weight were predicted using the estimation formula and data survey.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.295-307
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• 2022

In this paper, we propose a novel compression method for scalable Fisher vectors (SCFV) which is used as a global visual feature description of individual video frames in MPEG CDVA standard. CDVA standard has adopted a temporal descriptor redundancy removal technique that takes advantage of the correlation between global feature descriptors for adjacent keyframes. However, due to the variable length property of SCFV, the temporal redundancy removal scheme often results in inferior compression efficiency. It is even worse than the case when the SCFVs are not compressed at all. To enhance the compression efficiency, we propose an asymmetric SCFV difference computation method and a SCFV reconstruction method. Experiments on the FIVR dataset show that the proposed method significantly improves the compression efficiency compared to the original CDVA Experimental Model implementation.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.369-379
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• 2022

With the deepening integration of technology and cultural industries, China's digital cultural industry has begun to rise. The digital culture industry has met new demands for cultural consumption and brought new experiences to consumers in the digital economy era. This paper uses the public data of 36 Chinese A-share listed companies in digital culture from 2018 to 2019 to construct a technical innovation efficiency evaluation index system for listed companies in China's digital cultural industry. Through the use of data envelopment analysis (DEA) method, the technical innovation efficiency of 36 listed companies in China's digital cultural industry was evaluated. The research results show that: (1) China's 36 listed companies have low technological innovation efficiency; (2) the allocation of R&D resources of listed companies is unreasonable; (3) there is a large difference in technological innovation efficiency among listed companies. Therefore, it is necessary to increase the efficiency of technology innovation of listed companies in China's digital culture industry by investing more R&D funds, distributing R&D resources, establishing effective dynamic incentive mechanism, promoting government-industrial-academic research.

• Journal of Korean Library and Information Science Society
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• v.53 no.4
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• pp.101-121
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• 2022

In this study, to expand and develop the policy information portal (POINT) of the National Library of Korea Sejong. This study conducted a survey and in-depth interview with government officials and policy researchers. The suggested ways to support the policy information portal (POINT) in the future. As a result of the analysis, the use of the current policy information portal service was found to be low, and it was found that improvement of information access, integrated search, and expansion of information provision data were more necessary. It was suggested that a one-stop service should be implemented to provide various information, systematic information on related data for each task, overseas trend data, core service data, promotion activation, data linkage by strengthening cooperation with various government ministries and research institutes, and easy information provision and menu composition.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.59-59
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• 2020

온실가스 증가로 전구평균기온은 지속적으로 상승하고 있으며, 이러한 지구시스템 변화는 수자원의 시·공간적인 변동을 증대시킬 것으로 전망된다. 보다 적극적인 기후변화 대응을 위해 2015년 파리협정이 채택됨에 따라 전 세계에서는 온실가스 감축을 실천하고 있으며, 선진국에서는 산업화 이전 대비 1.5℃ 및 2.0℃ 전구기온상승에 따른 분야별 영향평가 및 적응방안을 마련하고 있다. 그러나 국내의 경우 아직까지 전구기온 상승에 따른 수자원 영향평가가 미흡한 실정이다. 본 연구에서는 AR5 기후변화 시나리오를 기반으로 1.5℃ 및 2.0℃ 전구기온 상승으로 인한 국내 수자원 변화 특성을 분석하였다. 이를 위해 몬순특성을 고려하여 적정 5 GCMs을 선정하였으며, 시간샘플링 기법을 활용하여 1.5℃ 및 2.0℃ 전구기온 상승시기를 추정하였다. 통계적상세화 기법을 적용하여 상세 기후변화 시나리오를 생산하고, 수문모형(VIC)에 적용하여 미래 수문변화를 전망하였다. 과거 대비 1.5℃, 2.0℃ 전구기온 상승에 따른 수문기상인자의 변화를 분석한 결과 연평균 강수량 및 유출량은 전구기온상승에 따라 증가하며, 계절별 변동성은 심화될 것으로 전망되었다. 유출량의 변화는 강수량 변화경향과 대체로 일치하였으나, 강수량 대비 전망결과의 불확실성이 크게 나타났다. 한편, 수문순환은 전 지역에서 가속화되는 것으로 확인되었으며, 모든 GCM의 전망결과에서 동일한 경향을 보였다. 수문기상인자(강수량, 증발산량, 유출량)의 강도별 발생빈도 및 총량은 저강도 구간에서 감소, 고강도 구간에서 증가하는 것으로 분석되었다. 이러한 특성은 강수량 및 유출량의 극대값 증가에 기여하여 수자원 관리의 어려움을 가중시킬 것으로 예상된다.