• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.341-343
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• 2022

온실가스 배출 문제가 세계적인 현안으로 부각되면서 수소를 에너지원으로 사용하는 수소경제가 주목받고 있다. 수소연료전지는 수소경제의 구성요소 중 하나로, 수소를 활용해 열과 전기를 생산하며 에너지 변환 효율이 높이는데 장점이 있다. 본 연구는 세계적인 온라인 커뮤니티인 레딧(Reddit)에서 수집한 수소연료전지와 관련된 소셜 데이터를 텍스트마이닝과 감성분석 기법으로 분석하였다. 분석 결과 9,211건의 댓글을 LDA(Latent Dirichlet Allocation)을 이용해 4개의 토픽 그룹으로 분류할 수 있었다. 이 중 수소연료전지와 관련이 높은 그룹을 선정해 STM(Structural Topic Model) 분석으로 10개 토픽을 추출하였고, 기후 환경, 수소 산업, 수소 차와 관련 있는 토픽 3개를 발견할 수 있었다. 이 연구 결과를 통해 수소연료전지의 세계적으로 실제적인 내용을 빠르고 효과적으로 파악하여 수소연료전지에 대한 예측하고, 우리나라의 수소연료전지 관련 국가R&D의 정책적 방향을 제시하고자 한다.

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1207-1216
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• 2018

Discharge or water level predictions at tidally affected river reaches are currently still a great challenge in hydrological practices. This research aims to predict water level of the tide dominated site, Jamsu bridge in the Han River downstream. Physics-based hydrodynamic approaches are sometimes not applicable for water level prediction in such a tidal river due to uncertainty sources like rainfall forecasting data. In this study, TensorFlow deep learning framework was used to build a deep neural network based LSTM model and its applications. The LSTM model was trained based on 3 data sets having 10-min temporal resolution: Paldang dam release, Jamsu bridge water level, predicted tidal level for 6 years (2011~2016) and then predict the water level time series given the six lead times: 1, 3, 6, 9, 12, 24 hours. The optimal hyper-parameters of LSTM model were set up as follows: 6 hidden layers number, 0.01 learning rate, 3000 iterations. In addition, we changed the key parameter of LSTM model, sequence length, ranging from 1 to 6 hours to test its affect to prediction results. The LSTM model with the 1 hr sequence length led to the best performing prediction results for the all cases. In particular, it resulted in very accurate prediction: RMSE (0.065 cm) and NSE (0.99) for the 1 hr lead time prediction case. However, as the lead time became longer, the RMSE increased from 0.08 m (1 hr lead time) to 0.28 m (24 hrs lead time) and the NSE decreased from 0.99 (1 hr lead time) to 0.74 (24 hrs lead time), respectively.

• Information and Communications Magazine
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• v.30 no.12
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• pp.17-24
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• 2013

본고에서는 세계전파통신회의(WRC: World Radio Conference)에서 IMT로 지정된 주파수 현황과 국내 이동통신 주파수 현황 및 계획을 알아본다. 또한 현재 시점에서 데이터 트래픽 증가 추세에 비추어 2020년 Beyond4G(5G)시대를 대비한 ITU(국제전기통신연합) 해당 표준화그룹의 소요량 예측 및 통신방식별 분담 율을 분석하였다. 주파수 수요예측에 따라 WRC-15에서 IMT 추가 주파수 지정 목적으로 진행하고 있는 위성, 방송, 과학 및 고정 등 기존업무와의 공유 연구 진행현황을 주파수 대역별로 살펴본다. 또한 도시 밀집 지역에서 대용량 데이터 전송을 위한 서비스 기술이 중요해진 시점에서 Beyond4G(5G) 시대를 위해 우리나라가 주도하고 있는 6GHz 이상 대역을 IMT로 활용하기 위한 활동을 소개한다. 마지막으로 WRC가 주파수를 분배 할당하는 방식인 '주파수 대역에 서비스 방식 지정'과 달리 '서비스 방식에 의한 주파수 대역 점유(예: LTE 기술표준(PS-LTE)을 PPDR대역에서 활용) 가능성'등 LTE 기술표준의 확산 추세에 대응하기 위해 5G시대에 준비할 사항에 대한 시사점을 언급하였다.

• Aerospace Engineering and Technology
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• v.10 no.2
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• pp.29-36
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• 2011

The Science and Technology Satellite-3 (STSAT-3) is based on the KITSAT-1, 2, 3 and STSAT-1, 2 which were Korea micro-satellites for the mission of space and earth science. The objectives of the STSAT-3 are to support earth and space sciences in parallel with the demonstration of spacecraft technology. The STSAT-3 carries an infrared (IR) camera for space & earth observation and an imaging spectrometer for earth observation. The IR payload instrument of the STSAT-3, Multi-purpose Infrared Imaging System (MIRIS), will observe the Galactic plane and North/South Ecliptic poles to research the origin of universe. The secondary payload instrument, Compact Imaging Spectrometer (COMIS), images the Earth's surface. The data acquired from COMIS are expected to be used for various application fields such as monitoring of disaster management, water quality studies, and farmland assessment. In this paper we present the operations concept of STSAT-3 which will be launched into a sun-synchronous orbit at a nominal altitude of 600km in late 2012.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.4
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• pp.567-574
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• 2019

Traditional project progress method(PPM) has been used for Korean defense research and development project management for the last 20 years. However, it is difficult to intuitively understand the performance in terms of the project schedule, because the PPM does not provide the function of managing and forecasting project schedule. Therefore, this paper proposes new schedule managing and forecasting function for the PPM using earned schedule management concept. We verify the effectiveness of the proposed functions through several defense projects and prove that it is possible to reinforce the schedule management function of the PPM.

• Journal of Korea Technology Innovation Society
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• v.15 no.2
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• pp.345-368
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• 2012

As science and technology are the core engines of economic and social affairs, it is becoming increasingly necessary to explore new promising technologies in order to secure competitiveness in science and technology with a view to helping upgrade the country's overall competitiveness and promoting industrial development. The governments of major advanced countries provide R&D support for promising future technologies. Even in South Korea, a study is being carried out to set up a model for forecasting future technologies and reinforcing the relevant survey system. This study intends to explore methods of identifying promising future technologies in the bio-science sector, which has emerged as a new growth engine. It will use a text-mining technique to collect and analyze theses in the bio science sector. It will identify key research sectors by analyzing thesis contour lines, and then review promising future key research subjects through in-depth study.

• Proceeding of EDISON Challenge
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• 2013.04a
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• pp.125-137
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• 2013

2012년 G 단백질 연결 수용체(G-Protein Coupled Receptors ; GPCR) 연구가 노벨 화학상을 받았다. 상당히 많은 병과 관련되어 있어 잠재력이 크고, 많은 연구가 진행 중이다. 현재 리간드와 단백질간의 정전기적 포텐셜 연구를 통한 예측 연구가 진행되고 있지만, GPCR과 리간드 간의 연구에서 아직 리간드의 전하를 통한 단백질과 리간드간의 상호작용 예측 연구가 되어 있지 않다. 그렇기 때문에 이번 연구에서는 8가지 방법으로 전하(charge)를 띠게 하여서 단백질과 리간드의 상호작용을 계산을 통하여 예측하여 보았다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.1094-1095
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• 2023

우리나라는 지리적 여건 상 대외무역에 대한 의존도가 높기 때문에, 해상운송에서의 물동량을 예측하여 항만시설을 개발하는 것이 매우 중요하다. 한편 우리나라 컨테이너 운송의 75%는 부산항을 통해 운송되고 있기 때문에 경기 회복을 위해서는 부산항의 경쟁력 강화가 급선무이다. [1] 물동량은 경제적 수입 뿐만 아니라, 지속가능성을 예측하는 측면에서도 가치가 있다. 본 연구에서는 물동량, 경제지수, 기후정보 등 다양한 입력변수와 LSTM 모델을 이용하여 보다 정확한 부산항 컨테이너 물동량 딥러닝 예측모델을 구현하였다.

• Convergence Security Journal
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• v.23 no.5
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• pp.57-64
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• 2023

In this study, we analyzed how to steal the target model without training data. Input data is generated using the generative model, and a similar model is created by defining a loss function so that the predicted values of the target model and the similar model are close to each other. At this time, the target model has a process of learning so that the similar model is similar to it by gradient descent using the logit (logic) value of each class for the input data. The tensorflow machine learning library was used as an experimental environment, and CIFAR10 and SVHN were used as datasets. A similar model was created using the ResNet model as a target model. As a result of the experiment, it was found that the model stealing method generated a similar model with an accuracy of 86.18% for CIFAR10 and 96.02% for SVHN, producing similar predicted values to the target model. In addition, considerations on the model stealing method, military use, and limitations were also analyzed.

• Journal of Korea Technology Innovation Society
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• v.11 no.1
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• pp.91-117
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• 2008

The relationships between science, technology, and industry are very complicated and vary according to time. Thus, it would be almost impossible to combine the three categories in a single model. However, the linking of science, technology, and industry, which are divided according to their respective classification standards, is a starting point from which to understand how science and technology, technology and industry, and further science, technology, and industry are related to each other. Studies have been carried out to analyze the relationship between science and technology and between technology and industry, whereas no study has been undertaken to get an overall view of science, technology, and industry. Since an appropriate methodology or an analytical model has not been suggested, this paper proposes a model for generally analyzing science, technology, and industry. More specifically, this paper examines the methodology for linking science, technology, and industry. This paper uses citation analysis to analyze knowledge flow such as absorption and utilization of given knowledge, looks at the provision of knowledge to create new knowledge, and examines the use of network analysis to analyze the complicated phenomenon of knowledge flow. This paper proposes an empirical study of trend analysis of technological innovation by looking into a linkage structure of knowledge flow among science, technology, and industry based on the classification linkage and analysis methodology using scientific paper and patents.