• Geotechnical Engineering
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• v.4 no.2
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• pp.15-24
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• 1988

To identify the stability of cantilever retaining wall in safe state by the deterministic method, these potential modes of such geotechnical failures as bearing capacity, horizontal sliding and overturning are analysed using Advanced First Order Second Moment (AFOSM) method. All design variables are assumed of the normal distribution and to be statistically independent. Considering the correlations between the single modes, structural system reliability index is 2. 05. Even if the safety factors are larger than the required value in the codes' by the conventional deterministic method, the system reliability of this structure may not be Judged to be safe state since the system reliability index is much lower than general value of 3.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.122-124
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• 2000

이 논문에서는 보다 효과적이고 편리한 서비스를 제공할 수 잇는 전자상거래를 위한 다중 에이전트 기반의 확장된 비교 쇼핑 시스템을 제안한다. 이 시스템은 웹 크로울링(web crawling)을 통해 비교 쇼핑 시스템의 대상이 되는 웹사이트들의 페이지 추출 정보를 입수한다. 각 쇼핑 사이트에서는 정보 추출을 위한 중심이 되는 랩퍼(wraper) 기술은 먼저 정보가 있는 페이지를 가려내고, 정보가 있다고 판명되는 페이지들에서 상품 정보의 위치 즉, 반복되는 패턴(pattern)을 추출하여 필요한 상품 기술 단위 정보를 뽑아내는 학습 알고리즘이며, 각 사이트에 맞게 만들어진 랩퍼 에이전트(wrapper agent)에 대해 유효성을 검사하는 방법론을 제시한다. 또한, 학습 시 필요한 지식(knowledge)으로서의 디렉토리(directory) 구성은 미리 만들어진 표준 카테고리(category)와 용어(terminology) 존재하에 제한적이나마 새로운 디렉토리 요소에 대해 자동으로 확장할 수 있는 방법론을 제안한다.

• Journal of Information Technology and Architecture
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• v.9 no.2
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• pp.167-176
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• 2012

In Korean military measuring systems interoperability is based on LISI (Level of Information System Interoperability) model at the requirement generation and acquisition process. However, LISI model cannot be used for interoperability measurement of system of systems (SoS) because LISI model is focused on interoperability measurement of a given system or system pair. Also, LISI model cannot provide quantitative information for interoperability decision because of qualitative rather than quantitative approach. This paper proposes a quantitative interoperability measurement methodology of SoS. At the proposed methodology, mission threads and supporting systems are identified using architecture approach, and Interoperability of SoS is measured with systems multiplicity and resemblance coefficient. Finally, a case study is presented to show the usefulness of the methodology.

• Korean Journal of Remote Sensing
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• v.31 no.3
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• pp.205-214
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• 2015

In this study, a novel land-cover classification framework for multi-temporal SAR data is presented that can combine multiple features extracted through data transforms and multiple classifiers. At first, data transforms using principle component analysis (PCA) and 3D wavelet transform are applied to multi-temporal SAR dataset for extracting new features which were different from original dataset. Then, three different classifiers including maximum likelihood classifier (MLC), neural network (NN) and support vector machine (SVM) are applied to three different dataset including data transform based features and original backscattering coefficients, and as a result, the diverse preliminary classification results are generated. These results are combined via a majority voting rule to generate a final classification result. From an experiment with a multi-temporal ENVISAT ASAR dataset, every preliminary classification result showed very different classification accuracy according to the used feature and classifier. The final classification result combining nine preliminary classification results showed the best classification accuracy because each preliminary classification result provided complementary information on land-covers. The improvement of classification accuracy in this study was mainly attributed to the diversity from combining not only different features based on data transforms, but also different classifiers. Therefore, the land-cover classification framework presented in this study would be effectively applied to the classification of multi-temporal SAR data and also be extended to multi-sensor remote sensing data fusion.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.360-360
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• 2022

토양수분과 유출 간 관계를 정량화하는 것은 수문 기작 및 유출 발생 과정의 이해를 위한 중요한 정보를 제공한다. 특히, 유출과정의 특성화는 수문 사상에 따른 불포화대 내 토양수 및 토사 손실 제어와 산사태 및 비점오염원 발생 예측을 위해 필수적이다. 유출과정과 관련된 비선형성과 복잡성을 확인하기 위해 토양수분과 유출 사이의 이력 거동이 조사되었다. 특히, 수문 과정 내 이력 현상 구체화를 위해 정성적인 시각적 분류 및 정량적 평가를 위한 이력 지수들이 개발되었다. 정성적인 시각적 분류는 시간에 따라 시계 및 반시계방향으로 다중 루프 형상을 나누는 방식으로 진행되었고, 정량적 평가의 경우 이력 고리(Hysteretic loop) 내 상승 고리(Rising limb)와 하강 고리(Falling limb)의 차이를 기준으로 한 지수로 이력 현상을 특성화하였다. 이전에 제안된 방법론들은 연구자의 판단이 들어가기 때문에 보편적이지 않고 이력 현상을 개발된 지수에 맞춤에 따라 자료 손실이 나타나는 한계가 존재한다. 자료의 손실 없이 불포화대 내 발생 가능한 대표 이력 현상을 자동으로 추출하기 위해 적합한 비지도 학습기반 기계학습 방법론의 제안이 필요하다. 우리 연구에서는 국내 산지 사면에서 강우 사상 동안 다중 깊이(10, 30, 60cm)로 56개의 토양수분 측정지점에서 확보된 토양수분 시계열 자료와 산지 사면 내 위어를 통해 확보된 유출 시계열 자료를 사용하였다. 먼저, 기존에 분류 방법을 기반으로 계절 및 공간특성에 따라 지배적으로 발생하는 토양수분-유출 간 이력 현상을 특성화하였다. 다음으로, 토양수분-유출 간 이력 패턴을 자료 손실 없이 형상화하여 자동으로 데이터베이스화하는 알고리즘을 개발하였다. 마지막으로, 비지도 학습방법을 이용하여 데이터베이스화된 실제 발현 이력 현상 내 확률분포를 최대한 가깝게 추정하는 은닉층을 반복적인 재구성 학습을 통해 구현함으로써 대표 이력 현상 패턴을 추출하였다.

• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.83-97
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• 2019

As society develops, the dissemination of microdata has increased to respond to diverse analytical needs of users. Analysis of microdata for policy making, academic purposes, etc. is highly desirable in terms of value creation. However, the provision of microdata, whose usefulness is guaranteed, has a risk of exposure of personal information. Several methods have been considered to ensure the protection of personal information while ensuring the usefulness of the data. One of these methods has been studied to generate and utilize synthetic data. This paper aims to understand the synthetic data by exploring methodologies and precautions related to synthetic data. To this end, we first explain muptiple imputation, Bayesian predictive model, and Bayesian bootstrap, which are basic foundations for synthetic data. And then, we link these concepts to the construction of fully/partially synthetic data. To understand the creation of synthetic data, we review a real longitudinal synthetic data example which is based on sequential regression multivariate imputation.

• The Journal of Society for e-Business Studies
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• v.12 no.4
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• pp.99-125
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• 2007

Recently, as the development of Ubiquitous Smart Space (USS) such as U-City is proliferating, preparing a development methodology dedicated to USS characteristics has become one of the crucial issues to increase the productivity of the USS projects. However, since the legacy development methodologies such as traditional UML do not consider the critical components of ubiquitous computing space such as context-awareness, service oriented architecture and multi-agent communication, they are not optimized for USS analysis and design. Hence, the purpose of this paper is to propose a USS-sophisticated development methodology. To do so, a hybrid approach, BPR-USS for space reengineering and UML-USS by amending UML with corresponding toolkit based on StarUML has been implemented. To show the feasibility of the approach described in this paper, an illustrative example with an actual USS development project for a multiplex space in Seoul is shown.

• Fire Science and Engineering
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• v.30 no.4
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• pp.20-26
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• 2016

When the fire takes place in Nuclear Powr Plants(NPPs), the reactor should achieve and maintain safe shut-down conditions and minimize the radioactive material released to the environment. The U.S. Nuclear Regulatory Commission (NRC) has issued numerous generic communications related to fire protection over the past 20 years, after it issued its requirements in the Fire Protection Rule set forth in Title 10, Section 50.48 of the Code of Federal Regulations (10 CFR 50.48) and Appendix R to the 10 CFR 50. The and Nuclear Energy Institute (NEI) has developed a Methodology for Risk Informed Fire Safe-Shutdown Analysis, which is related to the Deterministic Method for Multiple Spurious Operations solutions. The aim of this study was to identify, achieve, and maintain Post-Fire Safe-Shutdown of the Main Control Room (MCR) of the CANDU reactor, even though one train of the multiple Safety Structures, Systems, and Components (SCCs) fail by the technical specification and analysis method.

• Journal of The Geomorphological Association of Korea
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• v.20 no.4
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• pp.85-99
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• 2013

The objective of this paper is to analyze the spatial distribution of errors in the DEM generated using waterlines from multi-temporal remote sensing data and to assess flood vulnerability. Unlike conventional research in which only global statistics of errors have been generated, this paper tries to quantitatively analyze the spatial distribution of errors from a probabilistic viewpoint using geostatistical simulation. The initial DEM in Baramarae tidal flats was generated by corrected tidal level values and waterlines extracted from multi-temporal Landsat data in 2010s. When compared with the ground measurement height data, overall the waterline-based DEM underestimated the actual heights and local variations of the errors were observed. By applying sequential Gaussian simulation based on spatial autocorrelation of DEM errors, multiple alternative error distributions were generated. After correcting errors in the initial DEM with simulated error distributions, probabilities for flood vulnerability were estimated under the sea level rise scenarios of IPCC SERS. The error analysis methodology based on geostatistical simulation could model both uncertainties of the error assessment and error propagation problems in a probabilistic framework. Therefore, it is expected that the error analysis methodology applied in this paper will be effectively used for the probabilistic assessment of errors included in various thematic maps as well as the error assessment of waterline-based DEMs in tidal flats.

• Annual Conference on Human and Language Technology
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• 2011.10a
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• pp.143-147
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• 2011

본 논문에서는 한국어로 입력된 문장을 분석한 결과로부터 그에 해당하는 영어 대역문을 생성하는 과정에서, 어떻게 한국어의 보조용언을 영어 대역문에 반영 할 것인가를 다룬다. 특히 대화체 분야를 다루는 한영 자동번역 시스템에서는 한국어의 보조용언 생성이 대역문의 품질을 향상시키는데 중요한 위치를 차지하기 때문에, 한영 자동 번역에서의 자연스러운 영어 보조용언 생성을 위한 방법론을 제안한다. 첫째, 기존 패턴 기반 한영 자동 번역 엔진과 한국어 말뭉치를 형태소 분석한 결과를 살펴보고, 자연스러운 보조 용언 대역어 생성의 어려움을 살펴본다. 둘째, 자연스러운 보조용언 생성에 필요한 양상을 규칙화 한 지식을 기반으로 자연스러운 단일 보조용언 생성을 위한 방법을 제시한다. 셋째, 두 개 이상의 보조용언이 연속해서 나타나는 다중 보조용언의 생성 방법을 제시한다. 마지막으로, 실험과 결론을 통하여 본 논문이 제안하는 방법론을 사용했을 때, 자동 번역 엔진의 성능 평가 지표 중 하나인 BLEU와 NIST점수의 변화를 나타내봄으로 그 성능을 보인다.