• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.4
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• pp.441-447
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• 2015

This paper proposes a novel fuzzy-based multi-criteria decision making method and implements a footstep planner for humanoid robots with it. Humanoid robots require additional footstep planning process in addition to path planning for the autonomous navigation. Moreover, it is necessary to consider safety and energy consumption as well as path efficiency and multi-criteria decision making is indispensable. The proposed method can provide not only well- distributed and non-dominated, but also more preferable solutions for users. The planned footsteps by the proposed method were verified through simulation. The results indicate that the user's preference is properly reflected in optimized solutions maintaining solution quality.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2003.11a
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• pp.137-143
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• 2003

This study aimed to analyze the housing lifestyles of one person households (OPH) with the perspective of digital placemaking in order to suggest the planning criteria for OPH house. The structured questionnaire survey was accomplished by 145 OPH. The main findings were as follows. (1) OPH's housing lifestyles were classified into four types composed of ten factors. (2) The user preference for the space organization was varied by four types of housing lifestyles. (3) Most OPH required the informational appliances and their needs for other digital appliances were significantly differed by four types of housing lifestyles.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.1113-1116
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• 2005

PNS 시스템은 개인 휴대 단말기나 이동전화기로 제공되는 위치 지리 정보 서비스로 개인화된 서비스라 할 수 있다. 그러나 위치기반 PNS 서비스는 단순 위치 정보의 활용만이 아니라 위치 정보를 근간으로 POI(Poin of Interest)가 제공되어야 한다. 이를 위해서는 위치 및 위치에 부가되는 상황 정보를 바탕으로 개인의 개별화된 정보가 포함되어야 한다. 그러나 이러한 서비스에서 제공되는 위치 지리 정보는 개인의 성향이나 특성에 따른 정보를 포함하지 않기 때문에 개인 선호 특성 정보가 반영되지 않아 무분별한 POI 정보가 제공되고 있다. 본 논문에서는 사용자가 선 입력한 성향정보와 History 정보로부터 추출되는 사용자 선호 특성 정보를 데이터베이스로 구축하고, 개인 선호 특성 정보를 반영하여 웹 또는 모바일 기기를 통해 POI 서비스를 제공 받을 수 있는 PNS시스템을 제안하였다.

• The Journal of Information Technology and Database
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• v.4 no.2
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• pp.33-45
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• 1998

Database summarization is the procedure to obtain generalized and representative descriptions expressing the content of a large amount of database at a glance. We present a top-down summary refinement procedure to discover database summaries. The procedure exploits attribute concept hierarchies that represent ISA relationships among domain concepts. It begins with the most generalized summary and proceeds to find more specialized ones by stepwise refinements. This top-down paradigm reveals at least two important advantages compared to the previous bottom-up methods. Firstly, it provides a natural way of reflecting the user's own discovery preference interactively. Secondly, it does not produce too large intermediate result that makes it hard for the bottom-up approach to be applied in practical environment. The proposed procedure can also be easily extended for distributed databases. Information content measure of a database summary is derived in order to identify more informative summaries among the discovered results.

• Journal of Ginseng Research
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• v.13 no.1
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• pp.136-141
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• 1989

The purpose of this survey was to understand the attitudes, consumption patterns and preferences of domestic consumers relating to ginseng products in general. This study involved 1,305 people (420 agents, 742 ginseng farmer, 143 staff of Korea Tobacco and Ginseng Co.). The results obtained are summerized as follows. 1, Preferences for ginseng were very high for the majority of the respondents. 2. Most (80%) of the respondents had experience in taking ginseng. They expected ginseng to have efficacy as remidy for the hang-over syndrome, gastronil troubles and high blood pressure, in that order. 3. The patron of ginseng were, for the most part, men in the prime of manhood and old age. The favored products and the preferences regarding the organic condition of the ginseng products differed by sex and age. 4 To sum up the results of this study, we conclude that moderate priced ginseng products, not only easy to use and carry but also attractive to age and sex, should be developed without losing the efficacious components and characteristics.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.353-359
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• 2005

In this research, we propose a Unified Fuzzy rule-based knowledge Inference Systems (UFIS) to help the expert in cosmetic brand detection. Users' preferred cosmetic product detection is very important in the level of CRM. To this purpose, many corporations trying to develop an efficient data mining tool. In this study, we develop a prototype fuzzy rule detection and inference system. The framework used in this development is mainly based on two different mechanisms such as fuzzy rule extraction and RDB (Relational DB)-based fuzzy rule inference. First, fuzzy clustering and fuzzy rule extraction deal with the presence of the knowledge in data base and its value is presented with a value between 0 -1. Second, RDB and SQL (Structured Query Language)-based fuzzy rule inference mechanism provide more flexibility in knowledge management than conventional non-fuzzy value-based KMS (Knowledge Management Systems).

• Journal of the Korean Institute of Rural Architecture
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• v.7 no.3
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• pp.27-35
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• 2005

This study is about finding out characteristic of recognition individual housing in seaside of Donghae. To accomplish this purpose, we survey the 150 houses related to the landscape. Thus the major analysis is to take basic data, such as image(modern, western, traditional, etc) about exterior form of housing corresponding to the landscape. The result summarized as follows First, the elements for the characteristic of recognition were exterior material finish, exterior color, roof type, roof material finish, window size, roof slope, area of wall vs roof. Second, the image of traditional housing was very insufficient to plan landscape of housing with design elements. This research suggests that landscape housing of future is to be environmental landscape design and the proper design is to be various considering not only user's preference but also control of landscape.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.153-156
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• 2003

In this paper, we studied advanced audio/ voice information processing techniques, and trying to introduce more human friendly audio/voice. It is just in the beginning stage. Firstly, we approached in well-known time-domain methods such as moving average, differentiation, interpolation, and decimation. Moreover, some variation of them and envelope contour modification are utilized. We also suggested the MOS test to evaluate subjective listening factors. In the long term viewpoint, user's preference, mood, and environmental conditions will be considered and according to them, we hope our future technique can adapt speech and audio signals automatically.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.643-645
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• 2022

많은 온라인 쇼핑몰에서 색상 기반 필터링 서비스나 추천 시스템을 제공하지만, 수동 분류는 많은 시간이 들고 오류 위험이 있다. 본 연구의 실험에서는 먼저 분석할 의류 이미지를 실루엣 분석으로 수행한 경우와 수행하지 않는 경우의 k-평균 군집화 알고리즘으로 가장 우세한 색상 군집의 중심값을 도출하는데, 만약 군집 개수가 2개 이상이면 보다 큰 군집의 중심값만을 고려한다. 이 중심값을 이용해 사전 학습한 k-최근접 이웃 알고리즘으로 색상 클래스를 분류한다. 실험 결과 실루엣 분석을 수행하지 않은 k-평균 군집화 알고리즘을 사용한 분류 방식이 정확도와 수행 시간 모두 매우 준수하였으나, 배경색이 존재하여 의류 색 분석에 영향을 줄 수 있는 경우 잘못 분류한다는 문제도 있다.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.3
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• pp.135-148
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• 2003

In this paper we introduce the Internet-based purchase support systems using data mining and case-based reasoning (CBR). Internet Business activity that involves the end user is undergoing a significant revolution. The ability to track users browsing behavior has brought the vendor and end customer's closer than ever before. It is now possible for a vendor to personalize his product message for individual customers at massive scale. Most of former researchers, in this research arena, used data mining techniques to pursue the customer's future behavior and to improve the frequency of repurchase. The area of data mining can be defined as efficiently discovering association rules from large collections of data. However, the basic association rule-based data mining technique was not flexible. If there were no inference rules to track the customer's future behavior, association rule-based data mining systems may not present more information. To resolve this problem, we combined association rule-based data mining with CBR mechanism. CBR is used in reasoning for customer's preference searching and training through the cases. Data mining and CBR-based hybrid purchase support mechanism can reflect both association rule-based logical inference and case-based information reuse. A Web-log data gathered in the real-world Internet shopping mall is given to illustrate the quality of the proposed systems.