• Transactions of the Korean Society of Mechanical Engineers
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• v.13 no.6
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• pp.1215-1222
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• 1989

본 논문의 목적은 공기 유동장내에 가스분류의 거동을 조사하고 실용 가스 기관의 설계시에 필요한 기초적 데이타를 제공하고자 하는데 있다.본 연구와 관련 된 후래의 연구를 보면 자문등은 열선농도프로브를 사용하여 정상분류중의 농도측정을 행하였고, 분류내의 내부구조를 상세히 조사하였다. 특히, 종래에는 일정하게 보였 던 분류코아 부의 농도변동값의 경향을 구체적으로 나타내었다.

• Journal of KIISE:Software and Applications
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• v.28 no.1
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• pp.64-72
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• 2001

결정트리 생성은 일련의 특징값으로 기술된 사례들로부터 분류 지식을 추출하는 학습 방법중의 하나이다. 현장에서 수집되는 사례들은 관측 오류, 주관적인 판단, 불확실성 등으로 인해서 애매하게 주어지는 경우가 많다. 퍼지숫자나 구간값을 사용함으로써 이러한 애매한 데이타의 수치 속성은 쉽게 표현될 수 있다. 이 논문에서는 수치 속성은 보통값 뿐마아니라 퍼지숫자나 구간값을 갖을 수 있고, 비수치 속서은 보통값을 가지며, 데이터의 클래스는 확신도를 기자는 학습 데이터들로 부터, 분류 규칙을 마이닝하기 위한 퍼지 결정트리 생성 방법을 제안한다. 또한 제안한 방법에 의해 생성된 퍼지 결정트리를 사용하여, 새로운 데이터에 대한 클래스를 결정하는 추론 방법을 소개한다. 한편, 제안된 방법의 유용성을 보이기 위해 수행한 실험의 결과를 보인다.

• Journal of KIISE:Information Networking
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• v.32 no.3
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• pp.339-349
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• 2005

For recent years, data broadcast technology has been recognized as a very effective data delivery mechanism in mobile computing environment with a large number of cli;ents. Especially, a hybrid broadcast algorithm in real-time environment, which integrates one-way broadcast and on-demand broadcast, has an advantage of adapting the requests of clients to a limited up-link bandwidth and following the change of data access pattern. However, previous hybrid broadcasting algorithms has a problem in the methods to get a grip on the change of data access Pattern. It is caused by the diminution of requests for the data items which are contained in periodic broadcasting schedule because they are already broadcasted. To solve this problem, existing researches may remove data items in periodic broadcasting schedule over a few cycles multiplying cooling factor or find out the requests of data items with extracting them on purpose. Both of them are the artificial methods not considering the property of data. In this paper, we propose a real-time adaptive hybrid broadcasting based on data type(RTAHB-DT) to broadcast considering data property and analysis the performance of our aigorithm through simulation study.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.6 no.2
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• pp.42-52
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• 1988

The main object of this study is to prove the effectiveness of Landsat data in detecting the stressed areas in forest by extracting these areas. And also to choose the effective bands for this type of survey and to reduce the effect of shadow in forest to improve the accuracy of classification are the other objects. In this study Landsat-5 TM data is used and image processing techniques such as spatial filtering and ratio are taken to reduce the effect of shadow and to improve the classification accuracy. As a result following conclusions are obtained. First, Landsat TM data is useful to detect the stressed areas in forest. Second, when detecting the stressed area, band 4 and 5 are the most effective. Third, spatial filtering and ratio are useful to reudce the effect of shadow and improve the classification accuracy. Especially, ratio has great effect on improving the classification accuracy between forest and other areas.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.9 no.4
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• pp.113-124
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• 1989

In this study, we tried to extract the land-use change information of Seoul city using the multiple date images of the same geographic area. Multiple date image set is MSS('72, '79, '81, '93) and TM('85), and we carried out geometric correction, digitizing(due to the administrative boundary) in pre-processing process. In addition, we performed land-use classification with MLC(Maximum Likelihood Classifier) after improving the predictive accuracy of classification by filtering technique. At the stage of classification, ground truth data, topographic maps, aerial photographs were used to select the training field and statistical data of that time were compared with the classification result to prove the accuracy. As a result, urban area in Seoul has been increased('72 : 25.8 %${\rightarrow}$'81 : 43.0 %${\rightarrow}$'85 : 51.9 %) and Forest area decreased ('72 : 39.0 %${\rightarrow}$'85 : 28.4 %) as we estimated. Finally, it is concluded that the utilzation of satellite imagery is very effective, economical and helpful in the urban land-use/land-cover monitoring.

• Geotechnical Engineering
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• v.10 no.1
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• pp.19-26
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• 1994

In this paper, the application of the rock classification method based on indicator kriging and the cost of errors, which can incorporate qualitative data, was presented. In particular, the binary classification of rock masses was considered. To this end, a simplified RMR system was used. Since most of subjectivity in this analysis occur during the estimation of loss functions, a sensitivity analysis of loss functions was performed. Through this research, it was found out that an expected cost of errors could successfully be used as an indication for how well a sampling plan was designed. In certain conditions, qualitative data can be more economical than quantitative data in terms of expected costs of errors and sampling costs. Therefore, an additional sampling should be carefully determined depending upon the surrounding geologic conditions and its sampling cost. The application method shown in this paper can be useful for more systematic rock classifications.

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.545-557
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• 2001

In this paper we propose a hierarchical classification algorithm based on rough membership function which can reason a new object approximately. We use the fuzzy reasoning method that substitutes fuzzy membership value for linguistic uncertainty and reason approximately based on the composition of membership values of conditional sttributes Here we use the rough membership function instead of the fuzzy membership function It can reduce the process that the fuzzy algorithm using fuzzy membership function produces fuzzy rules In addition, we transform the information system to the understandable minimal decision information system In order to do we, study the discretization of continuous valued attributes and propose the discretization algorithm based on the rough membership function and the entropy of the information theory The test shows a good partition that produce the smaller decision system We experimented the IRIS data etc. using our proposed algorithm The experimental results with IRIS data shows 96%~98% rate of classification.

• Proceedings of the Korea Database Society Conference
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• 1998.09a
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• pp.421-430
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• 1998

지식경영을 위한 다양한 대상 업무중에서 텍스트 데이터의 마이닝은 특히 중요하다. 그 이유는 텍스트 데이터가 양적인 면에서 가장 풍부하고, 또 발견할 수 있는 지식을 가장 많이 포함하고 있기 때문이다. 본 논문에서는 텍스트 데이터베이스에서 지식발견을 위한 한 과정으로 텍스트 데이터베이스 내의 텍스트들을 분류하는 기법을 기술한다. 특히 문서 분류 방법은 데이터베이스의 일부 데이터를 훈련, 예제로 간주하여 교사 학습 알고리즘을 통해 학습한 후 나머지 데이터를 이용해 분류 정확성을 검증 및 향상시킨다. 시험 데이터로는 인터넷의 뉴스그룹의 기사를 이용하였고, 시험 결과 분류의 정확성은 한글 및 영문 모두 최소 70% 이상으로 나타났다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.14 no.1
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• pp.39-47
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• 1996

This paper is to provide land cover classification techniques for large area ranged in different pathos by classifying Landsat TM data of Jeonnam province. The analyses proceeded by individual scene because acquired dates are not same in different pathes. In this processing, troubles had happened something like variation of classes can be classified in two scenes and choice problem about overlapped area. Since spatial effects in large area affect data values, it was difficult to make a selection of classes and training fields. we could present a solution about these problems by trial and error method, and found that Bayesian maximum likelihood classification and majority filtering were effective to improve classification accuracy.

• Geotechnical Engineering
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• v.9 no.3
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• pp.61-66
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• 1993

In this paper, the incorporation of qualitative(or soft) data, such as outputs of geophysical tests or construction experience which has so far been cumulated, was discussed for rock classsification. Geostatistics wart used for this research since the parameters for the design of tunnels are spatially correlated. In particular, indicator kriging technique, which is one of non -parametric approaches, was used. As a selection criteria for an optimal classification, the cost of errors was adopted and the binary classes were only considered for rock classification. In future, incorporating an appreciable amount of available qualitative data will be necessary in tunnelling projects in which quantitative data are scarce. In this respect, this research is of great significance.