• Journal of the Korean Geotechnical Society
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• v.35 no.1
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• pp.17-30
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• 2019

This study presents the application of the numerical and analytical technique to simulate the Load Distribution Ratio (LDR) and to define axial stiffness on reinforcing pile foundation ($K_{vr}$) in vertical extension remodeling structure. The main objective of this study was to investigate the LDR between existing piles and reinforcing piles. Therefore, to analyze the LDR, 3D FEM analysis was performed as variable for elastic modulus, pile end-bearing condition, raft contacts, and relative position of reinforcing pile in a group. Also, using the axial stiffness ($K_{ve}$) of existing piles, the axial stiffness of reinforcing pile was defined by 3D approximate computer-based method, YSPR (Yonsei Piled Raft). In addition $K_{vr}$ was defined by reducing the $K_{ve}$considering the degradation of the existing piles.

• Korean Journal of Construction Engineering and Management
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• v.6 no.6 s.28
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• pp.133-141
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• 2005

In the resent years, the importance of VE (value engineering) and LCC (life cycle cost) analysis for apartment building construction projects has been fully recognized. Accordingly theoretical models, guidelines, and supporting software systems were developed for the value engineering and life cycle cost analysis for construction management including large building systems. However, the level of consensus on VE and LCC analysis results is still low due to the lack of reliable data on maintenance. This paper presents time dependent LCC model based value analysis method for rational investment decision making and design alternative selection for construction of apartment building. The proposed method incorporates a time dependent LCC model and a performance evaluation technique by fuzzy logic theory to properly handle the uncertainties associated with statistics data and to analyze the value of alternatives more rationally. The presented time dependent VE and LCC analysis procedure were applied to a real world project, and this case study is discussed in the paper. The model and the procedure presented in this study can greatly contribute to design value engineering alternative selection, the estimation of the life cycle cost, and the allocation of budget for apartment building construction projects.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.39-49
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• 2017

As the Internet technology advances, data on the web is increasing sharply. Many research study about incremental learning for classifying effectively in data increasing. Web document contains the time-series data such as published date. If we reflect time-series data to classification, it will be an effective classification. In this study, we analyze the time-series variation of the words. We propose an efficient classification through dividing the dataset based on the analysis of time-series information. For experiment, we corrected 1 million online news articles including time-series information. We divide the dataset and classify the dataset using SVM and $Na{\ddot{i}}ve$ Bayes. In each model, we show that classification performance is increasing. Through this study, we showed that reflecting time-series information can improve the classification performance.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.2
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• pp.317-329
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• 2018

The study on the existing multi-utility tunnel has examined the general aspects related to the installation of multi-utility tunnel rather than the optimal design and feasibility analysis of accommodation facility in multi-utility tunnel. In the basic planning stage related to the introduction of multi-utility tunnel, it is difficult to determine accommodation facility due to lack of relevant indicators and data. In this paper, VE/LCC analysis method is suggested for the optimal alternative decision of accommodation facilities in multi-utility tunnel. The analysis of the items of individual accommodation facility and the value index for LCC costs were applied to the kind alternatives, and the priorities of each kind were analyzed. In addition, the domestic multi-utility tunnel and analysis result are compared. The result of this study will be helpful to shorten the time and convenience of the user in the process of determining accommodation facility including the first designers when introducing multi-utility tunnel.

• Korean Journal of Construction Engineering and Management
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• v.12 no.3
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• pp.42-52
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• 2011

As environmental issues are rising recently efforts to reduce environmental stress are emerging in all industry segments. Especially environmental impact of buildings occupy a critical portion, so each country is operating green building rating system for life cycle of buildings. Accordingly green building rating system for every facility is operating in Korea. And acquisition of grade I for building energy efficiency is mandatory for every new public buildings since 2010. To design green building efficiently and systematically eco-friendly elements should be considered and checked from the schematic design phase. But in many cases eco-friendly elements are checked at the end of constructed design phase. So applying eco-friendly elements at the value engineering process, which is performing through schematic and constructed design phase, could make a efficient and systematic green building design. Value engineering process is divided into pre workshop, workshop and post workshop stages. And subject selection in pre workshop stage is the step that finds out the subjects which has the great possibility to be improved to perform efficient value engineering workshop. So this study present the Green VE subject selection model to select the most considerable eco-friendly subjects in projects.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.627-630
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• 2007

XML is becoming a de facto standard for exchanging data in Internet data processing environments due to the inherent characteristics such as hierarchical self-describing structures. Nowadays the number of 3D VE(Virtural Environment) available on the internet is constantly increasing, most of them focused low-level geometric data that lack any semantic information. VRML is composed of simple science graph. X3D is constructed based on XML and has many advantage. However, previous researches can not apply various advantage of XML. This work proposes an alternate approach for association semantic information to X3D VE based on XML. These information use navigation to VE. Moreover, we study extraction method of sematic information to XML document. In this work, we study saving techniques for navigation processing.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.95-99
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• 2010

Social media refers to the content, which are created by users, such as blogs, social networks, and wikis. Recently, question-answering (QA) communities, in which users share information by questions and answers, are regarded as a kind of social media. Thus, QA communities have become a huge source of information for the past decade. However, it is hard for users to search the exact question-answer that is exactly matched with their needs as the number of question-answers increases in QA communities. This paper proposes an approach for classifying a question into three categories (information, opinion, and suggestion) according to the purpose of the question for more accurate information retrieval. Specifically, our approach is based on modified Na$\ddot{i}$ve Bayes classifier which uses structural characteristics of QA documents to improve the classification accuracy. Through our experiments, we achieved about 71.2% in classification accuracy.

• Journal of Digital Contents Society
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• v.4 no.1
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• pp.67-79
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• 2003

With the advent of digital age, we've come to have an affinity with multimedia, in our daily lives, which has the most visual images. Everyday, more than 90 percent of people watch television, and most of them spend their time watching television and use internet for their leisure time activity. Multimedia change and diversify rapidly and have powerful potential. However, it is true that there is a considerable limit in the use of and application for their function. In this study, I've aimed at supporting the potential of therapeutic function which visual images have as the most powerful brain-stimulating-media. In order to accomplish the purpose of this study, I've placed chroma therapy in the element of video production. Thus, I've produced functional videos which shall be the backbone of video therapy. For EEG and psychology test, 1 chose 25 employees as sample group, and testified the potential of it.

• Journal of KIISE:Software and Applications
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• v.33 no.10
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• pp.886-895
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• 2006

Fingerprint classification reduces the number of matches required in automated fingerprint identification systems by categorizing fingerprints into a predefined class. Support vector machines (SVMs), widely used in pattern classification, have produced a high accuracy rate when performing fingerprint classification. In order to effectively apply SVMs to multi-class fingerprint classification systems, we propose a novel method in which SVMs are generated with the one-vs-all (OVA) scheme and dynamically ordered with $na{\ddot{i}}ve$ Bayes classifiers. More specifically, it uses representative fingerprint features such as the FingerCode, singularities and pseudo ridges to train the OVA SVMs and $na{\ddot{i}}ve$ Bayes classifiers. The proposed method has been validated on the NIST-4 database and produced a classification accuracy of 90.8% for 5-class classification. Especially, it has effectively managed tie problems usually occurred in applying OVA SVMs to multi-class classification.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.727-729
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• 2005

나이브베이즈분류기($na\ddot{i}ve$ Bayes classifier)는 학습, 적용 및 계산자원 이용의 측면에서 매우 효율적인 모델이다. 또한, 그 분류 성능 역시 다른 기법에 비해 크게 떨어지지 않음이 다양한 실험을 통해 보여져 왔다. 특히, 데이터를 생성한 실제 확률분포를 나이브베이즈분류기가 정확하게 표현할 수 있는 경우에는 최대의 효과를 볼 수 있다. 하지만, 실제 확률분포에 존재하는 조건부독립성(conditional independence)이 나이브베이즈분류기의 구조와 일치하지 않는 경우에는 성능이 하락할 수 있다. 보다 구체적으로, 각 자질변수(feature variable)들 사이에 확률적 의존관계(probabilistic dependency)가 존재하는 경우 성능 하락은 심화된다. 본 논문에서는 이러한 나이브베이즈분류기의 약점을 효율적으로 해결할 수 있는 자질변수의 통합기법을 제시한다. 자질변수의 통합은 각 변수들 사이의 관계를 명시적으로 표현해 주는 방법이며, 특히 상호정보량(mutual information)에 기반한 통합 변수의 선정이 성능 향상에 크게 기여함을 실험을 통해 보인다.