• The Korean Journal of Financial Management
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• v.9 no.2
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• pp.177-207
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• 1992

이 논문(論文)에서는 선도환시장(先渡換市場)에서의 위험(危險)프리미엄의 존재가설(存在假說)을 실증분석(實證分析)하기 위해 분석시간대(分析時間帶), 분석통화(分析通貨), 시계열(時系列) 자료(資料)들을 블럭처리(處理) 하고 시계열분석(時系列分析), 제한(制限) cointegration분석, 회귀모형분석(回歸模型分析) 등의 3가지 큰 범주(範疇)하의 12 가지 분석기법(分析技法)의 반복측정분석(反復測定分析)을 하였다. 검증결과(檢證結果) 각 통화(通貨)마다 분석기법(分析技法)에 대한 위험(危險)프리미엄의 민감도(敏感度)는 상당한 차이(差異)가 발견(發見)되었다. 위험(危險)프리미엄의 분석방법(分析方法)에 따른 결과치(結果値)의 변동리유(變動理由)는 크게 계량추정(計量推定)의 변동(變動)에 기인(基因)한 부분(部分)과 위험(危險)프리미엄 측정(測定)의 이론적(理論的) 모형(模型)의 상이(相異)에 의한 부분, 분석기법(分析技法)의 위험(危險)프리미엄 조건(條件)의 차이(差異)에 의한 변동(變動)부분으로 나누어 짐을 알 수 있었다. 이상의 발견점(發見点)이 시사(示唆)하는 바는 위험(危險)프리미험의 연구(硏究)에 있어서 상기(上記) 세가지 방향(方向)으로 더욱 깊은 연구(硏究)가 행하여 질수 있음을 알 수 있다. 각 연구(硏究) 방법(方法)의 비교(比較) 평가(評價)에서는 구체적인 실증분석(實證分析) 후 각 연구방법(硏究方法)들의 장단점(長短點)들이 논의(論議)되어진 바, 이들 방법(方法)이 서로 상호대체적(相互對替的)이 아니고 상호보완적(相互補完的)임을 알 수 있었다.

• Journal of the Korea Convergence Society
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• v.10 no.12
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• pp.17-22
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• 2019

Network attack analysis and visualization methods using network traffic session data detect network anomalies by visualizing the sender's and receiver's IP addresses and the relationship between them. The traffic flow is a critical feature in detecting anomalies, but simply visualizing the source and destination IP addresses symmetrically from up-down or left-right would become a problematic factor for the analysis. Also, there is a risk of losing timely security situation when designing a visualization interface without considering the temporal characteristics of time-series traffic sessions. In this paper, we propose a visualization interface and analysis method that visualizes time-series traffic data by using the radial axis, divide IP addresses into network and host portions which then projects on the cylindrical coordinate system that could effectively monitor network attacks. The proposed method has the advantage of intuitively recognizing network attacks and identifying attack activity over time.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.103-103
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• 2015

유류유출사고와 같이 하천 수표면의 흐름에 따라 이동 확산하는 부유성 오염물질의 혼합해석을 위해 많은 연구자들은 입자추적모형을 사용한 혼합모의를 수행해왔다. 입자추적모형에서 오염물질의 혼합은 평균 유속 분포에 의한 결정론적인 이동과 난류유동에 의한 무작위적인 혼합으로 나타내며, 난류혼합에 의한 수평확산은 난류확산계수로 조절한다. 따라서 표면흐름에 의한 난류확산계수의 산정을 위해 많은 연구자들은 부유성 입자를 이용한 실내실험을 수행하여 수평확산계수를 산정했고(Engelund, 1969; Cederwall, 1971), 최근에는 GPS의 발전으로 인해 해양영역에서 GPS를 장착한 표면부자를 활용한 확산실험을 통해 수평확산계수를 산정한 바 있다(Kjellson and $D{\ddot{o}}{\ddot{o}}s$, 2012; Alpers 등, 2013). 하천수질오염사고의 약 43.5%가 유류유출에 의한 것이며(환경부, 2013), 이에 따라 표면흐름에 의한 오염물질 혼합해석이 필요하나, 하천에서 수평확산계수 산정을 위한 현장실험연구는 부족한 상황이다. 따라서 본 연구에서는 낙동강 본류에서 GPS부자를 이용한 입자추적실험을 수행하여 표면흐름에 의한 확산계수를 산정했다. GPS부자를 이용한 입자추적실험은 낙동강의 강정고령보 하류와 구미보 하류의 각각 세 지점에서 수행되었다. GPS부자는 바람에 의한 교란을 최소화하기 위해 지름 10 cm의 구형으로 제작하였으며 시범테스트를 통해 입자의 주 궤적 변화가 크지 않은 지점에 GPS부자를 투입했다. GPS부자는 오염물질의 사고유출을 가정하여 한 지점에 투입했고 GPS부자 사이의 간섭을 최소화하기 위해 25 ~ 35개의 GPS부자를 이용했다. 표면흐름에 의해 이동하는 부자의 위치는 GPS에 시계열로 저장됐고 ADCP를 이용하여 실험당시의 수리량을 측정했다. 입자위치의 시계열자료로부터 GPS부자의 확산범위의 시간변화를 계산했고 단순 모멘트법을 이용하여 종, 횡 방향 확산계수를 계산했다. 그 결과, 종 방향 확산계수는 $0.003{\sim}0.041m^2/s$로 계산되었고 횡 방향 확산 계수는 $0.001{\sim}0.012m^2/s$로 계산되어, 흐름방향의 유속성분에 의한 확산이 지배적인 것으로 나타났다. 지류 합류부에서는 이송이 지배적인 혼합이 발생되었고(Pe>1) Pe의 증가에 따라 수평확산계수가 감소되었다. 25~35개 GPS부자 궤적의 앙상블 평균으로부터 계산한 Integral time scale은 모멘트법으로부터 계산한 종, 횡 방향 확산계수와 비례하는 것으로 나타나, Taylor(1921)의 이론과 일치했다. 또한 실험수로에서 수행된 기존연구결과와 비교한 결과, 하폭 대 수심비, 마찰항의 증가에 따라 수평확산계수가 증가하는 경향을 나타내었다.

• Journal of Korean Library and Information Science Society
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• v.49 no.4
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• pp.219-236
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• 2018

This study investigated the image of library in our society by analyzing newspaper articles related to libraries. A total of 3065 newspaper articles reported in Kyunghyang, Hankyoreh, Chosun, and Joongang from 2000 to 2017 were analyzed using time series analysis. The results of the time series analysis showed the number of newspaper articles related to library declined to a peak in 2009. Also, there were differences in the content of newspaper articles by year except for those content related to books. There were many articles about 'information' and 'use' in early 2000, about 'library operation and opening', 'culture' from 2006, and about 'residents of the area', 'culture' after 2012. These content of newspaper articles may reflects the image of library in our society. Finally, this study dis cussed practical ways of public library promotion.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.1
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• pp.83-95
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• 2021

In this study, major research trends at home and abroad were compared and analyzed in order to derive key research fields in the financial security field and to suggest directions. To this end, 689 domestic and 20,736 foreign data were collected from domestic and international academic journal DB, and major research fields related to financial security were extracted through LDA analysis. After that, hot & cold topics were derived through time series linear regression analysis. As a result of the analysis, studies related to government policy issues, personal information, and accredited certification were derived as promising research fields in Korea. In the case of foreign countries, related studies were drawn to develop advanced security systems such as cryptographic protocols and quantum security. Recently, it has become possible to apply various security technologies in Korea through the abolition of public certification. Accordingly, as changes in promising research fields are expected, the results of this study are expected to contribute to the establishment and development of a successful roadmap for domestic financial security.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.57-62
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• 2021

As the parallel computing capability for artificial intelligence improves, the field of artificial intelligence technology is expanding in various industries. In particular, artificial intelligence is being introduced to process data generated from IoT sensors that have enoumous data. However, the limitation exists when applying the AI techniques on IoT network because IoT has time series data, where the importance of data changes over time. In this paper, we propose time-weighted and user-state based artificial intelligence processing techniques to effectively process IoT sensor data. This technique aims to effectively classify IoT sensor data through a data pre-processing process that personalizes time series data and places a weight on the time series data before artificial intelligence learning and use status of personal data. Based on the research, it is possible to propose a method of applying artificial intelligence learning in various fields.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.11-18
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• 2023

In this paper, we evaluate deep learning time series forecasting models. Recent studies show that those models perform better than the traditional prediction model such as ARIMA. Among them, recurrent neural networks to store previous information in the hidden layer are one of the prediction models. In order to solve the gradient vanishing problem in the network, LSTM is used with small memory inside the recurrent neural network along with BI-LSTM in which the hidden layer is added in the reverse direction of the data flow. In this paper, we compared the performance of Informer by comparing with other models (LSTM, BI-LSTM, and Transformer) for real Nitrogen dioxide (NO2) data. In order to evaluate the accuracy of each method, mean square root error and mean absolute error between the real value and the predicted value were obtained. Consequently, Informer has improved prediction accuracy compared with other methods.

• Convergence Security Journal
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• v.24 no.2
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• pp.31-38
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• 2024

Recent expansion in cloud service usage has heightened the importance of cloud security. The purpose of this study is to analyze current research trends in the field of cloud security and to derive implications. To this end, R&D project data provided by the National Science and Technology Knowledge Information Service (NTIS) from 2010 to 2023 was utilized to analyze trends in cloud security research. Fifteen core topics in cloud security research were identified using LDA topic modeling and ARIMA time series analysis. Key areas identified in the research include AI-powered security technologies, privacy and data security, and solving security issues in IoT environments. This highlights the need for research to address security threats that may arise due to the proliferation of cloud technologies and the digital transformation of infrastructure. Based on the derived topics, the field of cloud security was divided into four categories to define a technology reference model, which was improved through expert interviews. This study is expected to guide the future direction of cloud security development and provide important guidelines for future research and investment in academia and industry.

• Journal of the Economic Geographical Society of Korea
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• v.22 no.4
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• pp.458-471
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• 2019

DMSP-OLS nighttime satellite imagery could be used to derive the sum of lights (SOL) and built-up area, and the two indices have been widely employed to make the estimation of socio-economic variables and the dynamics of urban developments. Considering it, this research investigated the spatiotemporal patterns of economic growth and urbanized area in Jilin Province, China, using DMSP-OLS data for a time span between 1992 and 2012. This study found the SOLs of both the province and most cities to tend to grow during the period. While SOL-weighted centroids' means moved towards northwestern direction, urban-area centroids' means followed the trend of south-eastern migration. These directional patterns could be associated with the Northeast Revitalization Plan of Chinese governments. Nonetheless, a future study will need to consider SNPP VIIRS DNB imagery in order to overcome temporal limitation of DMSP-OLS data. In addition, it is also necessary to estimate socio-economic indices, e.g., growth regional domestic product, using a regression model developed with correlation relationship between economic statistics ad SOL.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.2
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• pp.1-9
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• 2005

This study was performed to analyze time series landuse pattern of urban areas and the change of the areas by using remotely sensed multiple sensors. The results were as follows. First, according to the result of time series analysis, most agricultural land has been changed into built-up areas by development work such as the land development or land readjustment project, arrangement of science parks or military facilities, and location of public establishment like government buildings. Second, if the expansion of built-up areas maintains the present scale and speed, it seems that a lot of parts of land would be changed into built-up areas, especially centering around agricultural land, so it is necessary to establish the plan for urban space. Third, I have synthetically collected the data of the project of urban development and systematically monitored the process of in expansion the built-up areas up to now (from the past). I hereby could lay the foundation that makes us scientifically forecast the direction of expansion in the built-up areas by the urban development in the future.