• Ecology and Resilient Infrastructure
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• v.9 no.1
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• pp.24-35
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• 2022

For water quality management, it is necessary to continuously improve the forecasting by analyzing the past water quality, and a Data-driven model is emerging as an alternative. Because the Data-driven model is built based on a wide range of data, it is essential to apply the correlation analysis method for the combination of input variables to obtain more reliable results. In this study, the Gamma Test was applied as a preceding step to build a faster and more accurate data-driven water quality prediction model. First, a physical-based model (HSPF, EFDC) was operated to produce daily water quality reflecting the complexity of the watershed according to various hydrological conditions for Paldang Dam. The Gamma Test was performed on the water quality at the water quality prediction site (Paldangdam2) and major rivers flowing into the Paldang Dam, and the method of selecting the optimal input data combination was presented through the analysis results (Gamma, Gradient, Standar Error, V-Ratio). As a result of the study, the selection criteria for a more efficient combination of input data that can save time by omitting trial and error when building a data-driven model are presented.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.407-415
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• 2013

Recently, Interest variety of IT services and computing resources are increasing. As a result, the interest in the security of cloud environments is also increasing. Cloud environment is stored that to provide services to a large amount of IT resources on the Cloud. Therefore, Cloud is integrity of the stored data and resources that such as data leakage, forgery, etc. security incidents that the ability to quickly process is required. However, the existing developed various solutions or studies without considering their cloud environment for development and research to graft in a cloud environment because it has been difficult. Therefore, we proposed wire-wireless integrated Security management Model in cloud environment.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.210-214
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• 2008

It is actually impossible to model and store all objects which exist in real home environment into robot's database in advance. To resolve this problem, this paper proposes new object modeling method that can be available for robot self-modeling, which is capable of estimating whole model's shape from partial surface data using Generic Model. And this whole produce is conducted to cylindrical objects like cup, bottles and cans which can be easily found at indoor environment. The detailed process is firstly we obtain cylinder's initial principle axis using points coordinates and normal vectors from object's surface after we separate cylindrical object from 3D image. This 3D image is obtained from 3D sensor. And second, we compensate errors in the principle axis repeatedly. Then finally, we do modeling whole cylindrical object using cross sectional principal axis and its radius To show the feasibility of the algorithm, We implemented it and evaluated its accuracy.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.23 no.1
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• pp.11-17
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• 2011

A major source of durability problems in concrete structures is the corrosion of steel by the damage of passivity layer around steel bars. As chloride ion penetration is major cause of the destruction of passivity layer, evaluation of depth and concentration profile of chloride ion is the essential factor for the service-life estimation of concrete structure. To estimate chloride ion penetration characteristics, this paper on the basis of in-situ experimental data investigated the depth and concentration profile of chloride ion penetration. The core specimens are obtained at air-zone, splash zone, and tidal zone in Wando, Masan, Incheon, Gwangyang, and donghae harbors. Colorimentric method measured the chloride ion penetration depth and ASTM C 114 evaluated the concentration profile of chloride ion. Based on experimental data, the influence of harbor location and exposure condition on chloride ion penetration is evaluated.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.4
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• pp.961-974
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• 2015

With the advancement of SIEM from ESM, it allows deep correlated analysis using huge amount of data. By collecting software's vulnerabilities from assessment with certain classification measures (e.g., CWE), it can improve detection rate effectively, and respond to software's vulnerabilities by analyzing big data. In the phase of monitoring and vulnerability diagnosis Process, it not only detects predefined threats, but also vulnerabilities of software in each resources could promptly be applied by sharing CCE, CPE, CVE and CVSS information. This abstract proposes a model for effective detection and response of software vulnerabilities and describes effective outcomes of the model application.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.310-311
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• 2015

Ships' tracking data are being monitored and collected by vessel traffic service center in real time. In this paper, we intend to contribute to vessel traffic service operators' decision making through extracting ships' tracking patterns and models based on these data. Support Vector Machine algorithm was used for vessel track modeling to handle and process the data sets and k-fold cross validation was used to select the proper parameters. Proposed data processing methods could support vessel traffic service operators' decision making on case of anomaly detection, calculation ships' dead reckoning positions and etc.

• The KIPS Transactions:PartB
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• v.9B no.6
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• pp.827-834
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• 2002

In this paper, we proposed the formation of Korean-Roman alphabet notation conversion table for the generation of Korean-Roman alphabet notation that also meets revised Roman alphabet notation. Introduced a mathematical analyzing method of the natural language which used a petrinet model so that a base of Roman alphabet notation analyzed standard pronunciation and Roman alphabet notation to work mathematically. It display the practical example through a petrinet modeling of a plan and Roman alphabet notation to create a Korean Roman alphabet notation conversion table with the method of the analysis that used a petrinet model, and present a mathematical modeling plan and application method of Korean. We developed application program based on window in order to verify a created Korean-Roman alphabet notation conversion table, and compared the result of an application program with Roman alphabet notation of an Roman alphabet notation example dictionary.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.55-57
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• 2001

강화학습은 한 에이전트가 자신이 놓여진 환경으로부터의 보상을 최대화할 수 있는 최적의 행동 전략을 학습하는 것이다. 따라서 강화학습은 입력(상태)과 출력(행동)의 쌍으로 명확한 훈련 예들이 제공되는 교사 학습과는 다르다. 특히 Q-학습과 같은 비 모델 기반(model-free)의 강화학습은 사전에 환경에 대한 별다른 모델을 설정하거나 학습할 필요가 없으며 다양한 상태와 행동들을 충분히 자주 경험할 수만 있으면 최적의 행동전략에 도달할 수 있어 다양한 응용분야에 적용되고 있다. 하지만 실제 응용분야에서 Q-학습과 같은 강화학습이 겪는 최대의 문제는 큰 상태 공간을 갖는 문제의 경우에는 적절한 시간 내에 각 상태와 행동들에 대한 최적의 Q값에 수렴할 수 없어 효과를 거두기 어렵다는 점이다. 이런 문제점을 고려하여 본 논문에서는 로봇 축구 시뮬레이션 환경에서 각 선수 에이전트의 동적 위치 결정을 위해 효과적인 새로운 Q-학습 방법을 제안한다. 이 방법은 원래 문제의 상태공간을 몇 개의 작은 모듈들로 나누고 이들의 개별적인 Q-학습 결과를 단순히 결합하는 종래의 모듈화 Q-학습(Modular Q-Learning)을 개선하여, 보상에 끼친 각 모듈의 기여도에 따라 모듈들의 학습결과를 적응적으로 결합하는 방법이다. 이와 같은 적응적 중재에 기초한 모듈화 Q-학습법(Adaptive Mediation based Modular Q-Learning, AMMQL)은 종래의 모듈화 Q-학습법의 장점과 마찬가지로 큰 상태공간의 문제를 해결할 수 있을 뿐 아니라 보다 동적인 환경변화에 유연하게 적응하여 새로운 행동 전략을 학습할 수 있다는 장점을 추가로 가질 수 있다. 이러한 특성을 지닌 AMMQL 학습법은 로봇축구와 같이 끊임없이 실시간적으로 변화가 일어나는 다중 에이전트 환경에서 특히 높은 효과를 볼 수 있다. 본 논문에서는 AMMQL 학습방법의 개념을 소개하고, 로봇축구 에이전트의 동적 위치 결정을 위한 학습에 어떻게 이 학습방법을 적용할 수 있는지 세부 설계를 제시한다.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.412-420
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• 2010

With increased complexity of product and market, the phenomenon that a consumer get paradoxical attitude toward marketing object has been increased. And this phenomenon eventually affects the relationship between consumer and product. In this study we tried to find more paradoxical phenomenon and understand consumer behavior confronting these situations when they buy agro-product based on ground theory methodology. According to the results, consumer's expectation and purchase experience can promote quality paradox experience during confronting various marketing activities such as price, product, promotion, place. Also these experience can cause quality paradox related interaction and communication even though there could be differences in their experience according to demographic characteristics, personal preference, and risk perception. Consumer will develop multiple strategies against quality paradox to manage the uncomfortable paradox experiences.

• Information Systems Review
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• v.14 no.2
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• pp.103-115
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• 2012

Improvement of the capability to cope with risk based on prior preventive management is very important for efficient operation of financial information system. In order to do this, understanding, analysis, and countermeasures for the risk that happened already in the past is essential. In this study, the defect data which happened in the financial information system including account system, business system and data feeding system during 4 years and 5 months were categorized and analyzed by the domain, defect factors, period, day of the week, phases of software development, and defect cause. As a result, it was identified that the defect data had characteristics and trends along the phase of software development, day of the week, and the cause, also that building risk prediction model was necessary for the risk management of whole financial domain due to the relation of the information systems.