• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.434-434
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• 2023

다양한 지면 모형은 대기 강제력 데이터 세트에 의해 구동되며 육지의 물, 에너지 및 생지화학적 순환의 해석에 활용된다. 그 중 에너지 플럭스 교환을 추정하는 것은 극심한 가뭄, 폭염, 물 부족 등 극한 기후 현상에서 중요한 역할을 한다. 에너지 플럭스는 기상기후조건과 토지피복의 변화에 따른 영향을 받고 있는데 그 영향을 구체적으로 조사하는 것은 생태계 프로세스의 매커니즘을 구성하는 데 필수적이다. 본 연구에서는 최신버전인 Community Land Model 버전 5.0 (CLM5)를 이용하여 동북아시아 지역의 에너지 플럭스의 시공간분포를 분석하였다. CLM5의 시뮬레이션은 1991년부터 2010년까지 2.5° × 2.5° 그리드에서 실행되었고 주요 에너지 인자인 순복사량, 현열, 잠열을 모의하였으며, 실행결과는 FLUXNET의 동북아시아 사이트의 관측자료를 이용하여 모델을 검증 및 평가하였다. 대기 강제력 변수의 차이는 모의 결과에 영향을 미치기 때문에 수문인자와 토지피복유형에 따른 에너지 플럭스의 변동성을 분석하였고 잠열을 식생 증발산열과 지면 증발열로 파티션하여 연구지역에 따른 각 구성요소의 비율을 산정하였다. 20년간의 순복사열, 잠열과 온도의 시공간적 변동성의 연 추세를 분석한 결과 동북아시아의 대부분 지역에서 잠열과 온도는 소폭 증가되였고 순복사열은 중국 내륙과 몽골지역에서 감소되였다. 본 연구는 지표와 대기 사이의 에너지 교환에 대해 분석하였으며 이후 증발산 및 물 플럭스와의 연동성과 관계성 분석에 활용하여 기후변화를 이해하는 데 기여할수 있을 것으로 사료된다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.3
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• pp.183-192
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• 2013

As a worldwide trend, the spatial information that is established by country, institution and purpose is integrated into the data with a single spatial reference to improve the data connectivity and usability. In this study, a new national single origin plane rectangular coordinate system was studied to efficiently respond to the changes in the spatial reference according to the introduction of a new national geodetic standard and to the demand of seamless data service in the spatial information sector. For this purpose, the Korean Peninsula was set as the projection region and the projection distortion in the projection region was analyzed. The projection parameters were defined to homogenize and minimize the projection distortion, and their standardization and registration on the international organizations were conducted. The study on the required optimal projection equation resulted in the Hooijberg projection equation and projection parameters (${\Phi}$, ${\lambda}$, K, N, E) resulted in $38^{\circ}N$ and $128^{\circ}E$ projection origin, and a scale factor of 0.99924. The proper false northing and easting were 700,000m N and 400,000m E, respectively, considering the introduction of country station index system.

• Journal of Digital Convergence
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• v.18 no.1
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• pp.301-307
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• 2020

In recent years, a recommendation system is introduced in many different fields with the beginning of the 5G era and making a considerably prominent appearance mainly in books, movies, and music. In such a recommendation system, however, the preference degrees of users are subjective and uncertain, which means that it is difficult to provide accurate recommendation service. There should be huge amounts of learning data and more accurate estimation technologies in order to improve the performance of a recommendation system. Trying to solve this problem, this study proposed a movie recommendation system based on Fuzzy-AHP and Word2vec. The proposed system used Fuzzy-AHP to make objective predictions about user preference and Word2vec to classify scraped data. The performance of the system was assessed by measuring the accuracy of Word2vec outcomes based on grid search and comparing movie ratings predicted by the system with those by the audience. The results show that the optimal accuracy of cross validation was 91.4%, which means excellent performance. The differences in move ratings between the system and the audience were compared with the Fuzzy-AHP system, and it was superior at approximately 10%.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.65-75
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• 2011

Power Line Communication (PLC) is a system for carrying data on a conductor used for electric power transmission. Recently, PLC has received much attention due to connection efficiency and possibility of extension. It can be used for not only alternative communication, in which communication line is not sufficient, but also for communication between home appliances. Korea Electronic Power Cooperation (KEPCO) is constructing the system, which automatically collects values of power consumption of every household. Due to the randomness and complicated physical characteristics of PLC protocol (KS X4600-1), it has been believed that the current PLC is secure in the sense that it is hard that an attacker guesses or modifies the value of power consumption. However, we show that the randomness of the protocol is closely related to state of the communication line and thus anyone can easily guess the randomness by checking the state of the communication line. In order to analyze the security of PLC, we study the protocol in detail and show some vulnerability. In addition, we suggest that PLC needs more secure protocol on higher layers. We expect that the study of PLC help in designing more secure protocol as well.

• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.9-16
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• 2021

In the past, there have been various studies on predicting the stock market by machine learning techniques using stock price data and financial big data. As stock index ETFs that can be traded through HTS and MTS are created, research on predicting stock indices has recently attracted attention. In this paper, machine learning models for KOSPI's up and down predictions are implemented separately. These models are optimized through a grid search of their control parameters. In addition, a hybrid machine learning model that combines individual models is proposed to improve the precision and increase the ETF trading return. The performance of the predictiion models is evaluated by the accuracy and the precision that determines the ETF trading return. The accuracy and precision of the hybrid up prediction model are 72.1 % and 63.8 %, and those of the down prediction model are 79.8% and 64.3%. The precision of the hybrid down prediction model is improved by at least 14.3 % and at most 20.5 %. The hybrid up and down prediction models show an ETF trading return of 10.49%, and 25.91%, respectively. Trading inverse×2 and leverage ETF can increase the return by 1.5 to 2 times. Further research on a down prediction machine learning model is expected to increase the rate of return.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.195-211
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• 2014

Cloud computing services provide IT resources as services on demand. This is considered a key concept, which will lead a shift from an ownership-based paradigm to a new pay-for-use paradigm, which can reduce the fixed cost for IT resources, and improve flexibility and scalability. As IT services, cloud services have evolved from early similar computing concepts such as network computing, utility computing, server-based computing, and grid computing. So research into cloud computing is highly related to and combined with various relevant computing research areas. To seek promising research issues and topics in cloud computing, it is necessary to understand the research trends in cloud computing more comprehensively. In this study, we collect bibliographic information and citation information for cloud computing related research papers published in major international journals from 1994 to 2012, and analyzes macroscopic trends and network changes to citation relationships among papers and the co-occurrence relationships of key words by utilizing social network analysis measures. Through the analysis, we can identify the relationships and connections among research topics in cloud computing related areas, and highlight new potential research topics. In addition, we visualize dynamic changes of research topics relating to cloud computing using a proposed cloud computing "research trend map." A research trend map visualizes positions of research topics in two-dimensional space. Frequencies of key words (X-axis) and the rates of increase in the degree centrality of key words (Y-axis) are used as the two dimensions of the research trend map. Based on the values of the two dimensions, the two dimensional space of a research map is divided into four areas: maturation, growth, promising, and decline. An area with high keyword frequency, but low rates of increase of degree centrality is defined as a mature technology area; the area where both keyword frequency and the increase rate of degree centrality are high is defined as a growth technology area; the area where the keyword frequency is low, but the rate of increase in the degree centrality is high is defined as a promising technology area; and the area where both keyword frequency and the rate of degree centrality are low is defined as a declining technology area. Based on this method, cloud computing research trend maps make it possible to easily grasp the main research trends in cloud computing, and to explain the evolution of research topics. According to the results of an analysis of citation relationships, research papers on security, distributed processing, and optical networking for cloud computing are on the top based on the page-rank measure. From the analysis of key words in research papers, cloud computing and grid computing showed high centrality in 2009, and key words dealing with main elemental technologies such as data outsourcing, error detection methods, and infrastructure construction showed high centrality in 2010~2011. In 2012, security, virtualization, and resource management showed high centrality. Moreover, it was found that the interest in the technical issues of cloud computing increases gradually. From annual cloud computing research trend maps, it was verified that security is located in the promising area, virtualization has moved from the promising area to the growth area, and grid computing and distributed system has moved to the declining area. The study results indicate that distributed systems and grid computing received a lot of attention as similar computing paradigms in the early stage of cloud computing research. The early stage of cloud computing was a period focused on understanding and investigating cloud computing as an emergent technology, linking to relevant established computing concepts. After the early stage, security and virtualization technologies became main issues in cloud computing, which is reflected in the movement of security and virtualization technologies from the promising area to the growth area in the cloud computing research trend maps. Moreover, this study revealed that current research in cloud computing has rapidly transferred from a focus on technical issues to for a focus on application issues, such as SLAs (Service Level Agreements).

• Journal of Korea Water Resources Association
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• v.55 no.6
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• pp.393-404
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• 2022

Reliable terrestrial rainfall observations from satellites at finer spatial resolution are essential for urban hydrological and microscale agricultural demands. Although various traditional "top-down" approach-based satellite rainfall products were widely used, they are limited in spatial resolution. This study aims to assess the potential of a novel "bottom-up" approach for rainfall estimation, the parameterized SM2RAIN model, applied to the C-band SAR Sentinel-1 satellite data (SM2RAIN-S1), to generate high-spatial-resolution terrestrial rainfall estimates (0.01° grid/6-day) over Central South Korea. Its performance was evaluated for both spatial and temporal variability using the respective rainfall data from a conventional reanalysis product and rain gauge network for a 1-year period over two different sub-regions in Central South Korea-the mixed forest-dominated, middle sub-region and cropland-dominated, west coast sub-region. Evaluation results indicated that the SM2RAIN-S1 product can capture general rainfall patterns in Central South Korea, and hold potential for high-spatial-resolution rainfall measurement over the local scale with different land covers, while less biased rainfall estimates against rain gauge observations were provided. Moreover, the SM2RAIN-S1 rainfall product was better in mixed forests considering the Pearson's correlation coefficient (R = 0.69), implying the suitability of 6-day SM2RAIN-S1 data in capturing the temporal dynamics of soil moisture and rainfall in mixed forests. However, in terms of RMSE and Bias, better performance was obtained with the SM2RAIN-S1 rainfall product over croplands rather than mixed forests, indicating that larger errors induced by high evapotranspiration losses (especially in mixed forests) need to be included in further improvement of the SM2RAIN.

• JOURNAL OF ELECTRICAL WORLD
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• s.451
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• pp.22-31
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• 2014

온실가스 다량 배출로 인한 지구온난화 현상은 많은 분야에서의 변화를 요구하고 있다. 특히 온실가스 배출의 주원인으로 꼽히고 있는 발전 등 에너지산업 분야의 경우 그 요구는 매우 거세다. 과거에는 경제성장이라는 측면만 고려하면 됐지만, 지금은 기후변화 대응을 위해 환경을 최우선적으로 고려할 것을 주문하고 있기 때문이다. 문제는 현재 전 세계적으로 약 20%에 이르는 인구가 전기 에너지를 사용하지 못하고 있다는 점이다. 즉 향후 에너지를 사용하고자 하는 신규 소비자는 더욱 늘 것이고, 산업의 발전으로 인한 에너지 소비 역시 큰 폭으로 증가할 수밖에 없다. 문제가 굉장히 어렵지만 해결책도 분명 존재한다. 결론적으로 말해 온실가스 배출을 최소화하면서도 에너지 효율은 높인 기술을 개발하면 되는 것이다. 그리고 이미 세계 각국은 청정에너지 기술개발을 위해 다각도의 노력을 펼치고 있는 상황이다. 그렇다면 세계 각국은 미래 에너지시장을 선도할 청정에너지 기술로 어떤 것을 꼽고 있을까. 이 질문에 대한 대답은 지난 5월 서울에서 개최된 '제5차 클린에너지장관회의(CEM, Clean Energy Ministerial)'에서 제시된 바 있다. CEM은 한국, 미국, 영국, 독일, 중국, 일본 등 세계 에너지의 70%를 사용하는 주요 국가의 관계 장관들이 모여 클린에너지 공급 확대와 에너지효율 향상을 위한 구체적 액션플랜을 논의하는 자리다. 2010년 미국에서 첫 회의가 열렸고 아랍에미리트, 영국, 인도에 이어 한국은 5번째로 CEM을 개최했다. 특히 이번 CEM에서는 회원국들의 의견을 모아 10대 청정에너지 혁신기술을 최초로 선정, 발표했다. CEM은 "향후 10년 간 에너지 시장의 변화를 선도할 유망 기술을 선정한 것으로 IEA 등 국제기구와 주요국 기술 로드맵을 기준으로 해 23개 회원국 회람을 거쳐 최종 확정하게 됐다"고 배경을 설명했다. 이번에 선정된 10대 청정에너지 혁신기술은 ${\triangle}$초고압직류송전 ${\triangle}$에너지저장장치 ${\triangle}$바이오연료 ${\triangle}$마이크로 그리드 ${\triangle}$탄소포집 및 저장 ${\triangle}$초고효율 태양광 발전 ${\triangle}$해상풍력 ${\triangle}$신재생에너지 하이브리드시스템 ${\triangle}$빅데이터 에너지관리시스템 ${\triangle}$지열 시스템이다. 이와 관련해 산업통상자원부 윤상직 장관은 "이번에 선정된 10개의 기술은 최근의 기술적 정책적 추세가 잘 반영된 결과"라고 평가했다. 특히 윤 장관은 "중앙집중형 공급원에서 분산형 전원으로의 변화, 에너지 효율향상의 중요성, ICT와 융 복합 추세 등 우리나라의 상황에서 시사하는 바가 크다"며 "현재 수립하고 있는 '제3차 국가에너지기술 개발계획'에 이러한 기술적 추세를 반영하겠다"는 의사를 표명했다. 향후 10년 간 에너지시장의 변화를 선도할 10대 청정에너지 유망기술을 자세히 소개한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.571-576
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• 2002

There have been a lot of considerations dealing with improving the performance of neuro-fuzzy system. The studies on the neuro-fuzzy modeling have largely been devoted to two approaches. First is to improve performance index of system. The other is to reduce the structure size. In spite of its satisfactory result, it should be noted that these are difficult to extend to high dimensional input or to increase the membership functions. We propose a novel neuro-fuzzy system based on the efficient clustering method for initializing the parameters of the premise part. It is a very useful method that maintains a few number of rules and improves the performance. It combine the various algorithms to improve the performance. The Expectation-Maximization algorithm of Gaussian mixture model is an efficient estimation method for unknown parameter estimation of mirture model. The obtained parameters are used for fuzzy clustering method. The proposed method satisfies these two requirements using the Gaussian mixture model and neuro-fuzzy modeling. Experimental results indicate that the proposed method is capable of giving reliable performance.

• Journal of Internet Computing and Services
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• v.12 no.4
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• pp.157-172
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• 2011

The latest active studies on distributed OLAP to adopt a distributed environment are mainly focused on DHT P2P OLAP and Grid OLAP. However, these approaches have its weak points, the P2P OLAP has limitations to multidimensional range queries in the cloud computing environment due to the nature of structured P2P. On the other hand, the Grid OLAP has no regard for adjacency and time series. It focused on its own sub set lookup algorithm. To overcome the above limits, this paper proposes an efficient central managed P2P approach for a cloud computing environment. When a multi-level hybrid P2P method is combined with an index load distribution scheme, the performance of a multi-dimensional range query is enhanced. The proposed scheme makes the OLAP query results of a user to be able to reused by other users' volatile cube search. For this purpose, this paper examines the combination of an aggregation cube hierarchy tree, a quad-tree, and an interval-tree as an efficient index structure. As a result, the proposed cloud P2P OLAP scheme can manage the adjacency and time series factor of an OLAP query. The performance of the proposed scheme is analyzed by a series of experiments to identify its various characteristics.