• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2003년도 봄 학술발표논문집 Vol.30 No.1 (B)
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• pp.178-180
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• 2003

EEG-based brain computer interface(BCI) provides a new communication channel between human brain and computer. EEG data is a multivariate time series so that hidden Markov model (HMM) might be a good choice for classification. However EEG is very noisy data and contains artifacts, so useful features mr expected to improve the performance of HMM. In this paper we addresses the usefulness of principal component features with Hidden Markov model (HHM). We show that some selected principal component features can suppress small noises and artifacts, hence improves classification performance. Experimental study for the classification of EEG data during imagination of a left, right up or down hand movement confirms the validity of our proposed method.

• Asia pacific journal of information systems
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• 제14권2호
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• pp.115-130
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• 2004

This paper proposes how to build an expert profile database in KMS, which provides the information of expertise that each expert possesses in the organization. To manage tacit knowledge in a knowledge management system, recent researches in this field have shown that it is more applicable in many ways to provide expert search mechanisms in KMS to pinpoint experts in the organizations with searched expertise so that users can contact them for help. In this paper, we develop a framework to automate expert classification using a text categorization technique called Vector Space Model, through which an expert database composed of all the compiled profile information is built. This approach minimizes the maintenance cost of manual expert profiling while eliminating the possibility of incorrectness and obsolescence resulted from subjective manual processing. Also, we define the structure of expertise so that we can implement the expert classification framework to build an expert database in KMS. The developed prototype system, "Knowledge Portal for Researchers in Science and Technology," is introduced to show the applicability of the proposed framework.

• KSTLE International Journal
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• 제1권1호
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• pp.34-42
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• 2000

A method and results of classification of four different metallic wear debris were presented by using their color features. The color image of wear debris was used far the initial data, and the color properties of the debris were specified by HSI color model. Particles were characterized by a set of statistical features derived from the distribution of HSI color model components. The initial feature set was optimized by a principal component analysis, and multidimensional scaling procedure was used fer the definition of a classification plane. It was found that five features, which include mean values of H and S, median S, skewness of distribution of S and I, allow to distinguish copper based alloys, red and dark iron oxides and steel particles. In this work, a method of probabilistic decision-making of class label assignment was proposed, which was based on the analysis of debris-coordinates distribution in the classification plane. The obtained results demonstrated a good availability for the automated wear particle analysis.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1470-1472
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• 2003

Hyperion, as hyperspectral data, is carried on NASA’s EO-1 satellite, can be used in more subtle discrimination on forest cover, with 224 band in 360 ?2580 nm (10nm interval). In this study, Hyperion image is used to investigate the effects of topography on the classification of forest cover, and to assess whether the topographic correction improves the discrimination of species units for practical forest mapping. A publicly available Digital Elevation Model (DEM), at a scale of 1:25,000, is used to model the radiance variation on forest, considering MSR(Mean Spectral Ratio) on antithesis aspects. Hyperion, as hyperspectral data, is corrected on a pixel-by-pixel basis to normalize the scene to a uniform solar illumination and viewing geometry. As a result, the approach on topographic effect normalization in hyperspectral data can effectively reduce the variation in detected radiance due to changes in forest illumination, progress the classification of forest cover.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 심포지엄 논문집 정보 및 제어부문
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• pp.62-64
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• 2004

P2P Systems have grown dramatically in recent years. Now many P2P systems have developed and been confronted by P2P technical challenges. We should consider how to efficiently locate desired resources. In this paper we integrated the existing pure P2P and hybrid P2P model. We try to keep roles of super peer in hybrid and concurrently use pure P2P model for searching resource. In order to improve the existing search mechanism, we present contents-based classification mechanism. Proposed system have the following features. This can forward only query to best peer using RI. Second, it is self-organization. A peer can reconfigure network that it can communicate directly with based on best peer. Third, peers can cluster each other through contents-based classification.

• 한국문헌정보학회지
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• 제42권4호
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• pp.181-199
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• 2008

본 연구는 실제 분류 시스템 개발자들의 행태를 이해하는 데 그 목적이 있다. 이를 위하여, 협력행태를 중심으로 협력의 유형, 협력에 영향을 미치는 요인, 협력이 분류 시스템 개발에 미치는 영향 등을 조사하였다. 또한 협력에 대한 이해가 분류 교육자, 연구자, 개발자에게 제공하는 의의를 논의하였다. 자료는 문헌조사, 현장인터뷰, 관찰법, 이메일의 방법을 통하여 수집되었다. 본 연구는 이미지 분류 시스템 개발팀을 대상으로 조사하였으며 사회과정모델을 연구의 프레임워크로 채택하였다.

• 반도체디스플레이기술학회지
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• 제21권1호
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• pp.108-113
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• 2022

The deep-learning-based measurement method with the through-focus scanning optical microscopy (TSOM) estimated the size of the object using the classification. However, the measurement performance of the method depends on the number of subdivided classes, and it is practically difficult to prepare data at regular intervals for training each class. We propose an approach to measure the size of an object in the TSOM image using the deep-learning regression model instead of using classification. We attempted our proposed method to estimate the top critical dimension (TCD) of through silicon via (TSV) holes with 2461 TSOM images and the results were compared with the existing method. As a result of our experiment, the average measurement error of our method was within 30 nm (1σ) which is 1/13.5 of the sampling distance of the applied microscope. Measurement errors decreased by 31% compared to the classification result. This result proves that the proposed method is more effective and practical than the classification method.

• 한국도서관정보학회지
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• 제49권4호
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• pp.265-294
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• 2018

최근 정보의 폭발적인 증가로 인해 사용자에게 적합한 정보를 제공하기 위한 정보의 필터링이 매우 중요시 되고 있다. 한국과학기술정보연구원에서 운영하고 있는 학술정보서비스인 NDSL은 방대한 자료를 보유함에도 불구하고 사용자들은 검색 외에 자료 획득이 쉽지가 않다. 본 논문은 사용자에게 적합한 정보를 제공하기 위하여 키워드 특성을 활용한 서비스인 PIN(Profiling service In NDSL)을 제안한다. PIN은 키워드만을 가지고 검색하는 것이 아닌 사용자 본인 및 유사 사용자가 등록한 관심 키워드, 동시이용 키워드, 검색 키워드로 분석된 워드 클라우드를 제공하고 이를 통하여 사용자에게 맞춤형 논문, 보고서, 특허, 동향의 콘텐츠를 추천한다. 또한 콘텐츠를 보다 쉽게 접근하기 위하여 중복분류가 가능한 학술연구분류체계 기반 분류를 제공한다. 이를 검증하기 위해 NDSL의 축적된 2016년도의 국내논문의 데이터를 기반으로 분류별로 키워드를 추출하고 이를 통해 매칭 기반의 분류 모델을 만든 후 트레이닝 및 테스트를 거쳐 결과를 도출한다.

• 한국전자거래학회지
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• 제7권3호
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• pp.49-60
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• 2002

Many researchers have studied component technologies with concept, methodology and implementation for partial business domain, however there are rarely researches for component classification to manage these systematically. In this paper, we suggest a component classification model, which can make component reusability higher and can derive higher productivity of software development. We take four focuses generalization, abstraction, technology and size. The generalization means which category a component belongs to. The abstraction means how specific a component encapsulates its inside. The technology means which platform for hardware environment a component can be plugged in. The size means the physical component volume.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.365-367
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• 2008

A digital city model represents a 3D environment of a city with various city object information such as 3D building model, road, and land cover. Usually, at least two satellite images with some image overlap are necessary and a complex satellite-related computation needs to be carried out to create a city model. This is an expensive technique, because it requires many resources and excessive computational cost. The authors propose a methodology to create a digital city model including 3D building model and land cover information from a single high resolution satellite image. The approach consists of image pan-sharpening, shadow recovery, building occlusion restoration, building model extraction, and land cover classification. We create a digital city model using a single KOMPSAT-2 image and review the result.