• 한국통신학회논문지
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• 제41권11호
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• pp.1406-1409
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• 2016

본 논문에서는 송수신단 간 변조기법 및 채널 상태 값이 약속되지 않은 완벽한 블라인드 통신 상황에서 송신측의 변조방식을 알아내기 위해 성좌도 회전 및 확률밀도함수(probability density function : pdf)를 이용한 새로운 자율 변조 구분(Automatic modulation classification : AMC)기법과 경험적 신호 그룹화 알고리즘을 통해 채널 상태 값을 추정하는 방법을 제안한다. 평균제곱근 편차(Root mean square error : RMSE) 및 심볼 오류율(Symbol error rate : SER) 등의 모의실험을 통해 제안된 기법과 기존의 다른 기법간의 채널 상태와 변조 추정 능력을 비교 평가한다.

• Journal of Computing Science and Engineering
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• 제3권3호
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• pp.165-180
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• 2009

The HKIB, or Hankookilbo, test collections are two archives of Korean newswire stories manually categorized with semi-hierarchical or hierarchical category taxonomies. The base newswire stories were made available by the Hankook Ilbo (The Korea Daily) for research purposes. At first, Chungnam National University and KISTI collaborated to manually tag 40,075 news stories with categories by semi-hierarchical and balanced three-level classification scheme, where each news story has only one level-3 category (single-labeling). We refer to this original data set as HKIB-40075 test collection. And then Yonsei University and KISTI collaborated to select 20,000 newswire stories from the HKIB-40075 test collection, to rearrange the classification scheme to be fully hierarchical but unbalanced, and to assign one or more categories to each news story (multi-labeling). We refer to this modified data set as HKIB-20000 test collection. We benchmark a k-NN categorization algorithm both on HKIB-20000 and on HKIB-40075, illustrating properties of the collections, providing baseline results for future studies, and suggesting new directions for further research on Korean text categorization problem.

• 한국도서관정보학회지
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• 제33권1호
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• pp.143-167
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• 2002

이 연구는 외국의 문헌분류법이 중국의 문헌분류법에 끼친 영향을 DDC, ББK를 중심으로 파악하였다. 아울러 도서관을 국책 수행 상 중요 기관으로 인식하는 중국의 도서관에서 대표적으로 사용하고 있는 중국의 현대 3대 문헌분류법인 중국인민대학도서관도서분류법, 중국과학원도서관도서분류법, 중국 도서관분류법에 대하여 발전과정을 중심으로 분석하였다.

• Journal of Computing Science and Engineering
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• 제10권4호
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• pp.103-110
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• 2016

Emotion recognition is an important component of affective computing, and is significant in the implementation of natural and friendly human-computer interaction. An effective approach to recognizing emotion from text is based on a machine learning technique, which deals with emotion recognition as a classification problem. However, in emotion recognition, the texts involved are usually very short, leaving a very large, sparse feature space, which decreases the performance of emotion classification. This paper proposes to resolve the problem of feature sparseness, and largely improve the emotion recognition performance from short texts by doing the following: representing short texts with word cluster features, offering a novel word clustering algorithm, and using a new feature weighting scheme. Emotion classification experiments were performed with different features and weighting schemes on a publicly available dataset. The experimental results suggest that the word cluster features and the proposed weighting scheme can partly resolve problems with feature sparseness and emotion recognition performance.

• 한국도서관정보학회지
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• 제40권2호
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• pp.5-26
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• 2009

이 연구는, KDC 5판에서 문제점들이 다수 발견되어 시스템으로서의 문헌분류법에 부합하는 표준적인 조건을 제시한 다음, KDC 5판을 대상으로 각종 표준적인 조건에의 부합 여부를 자세하게 진단하여 발견된 구체적인 문제점들에 대한 합당한 처방을 마련 제시함으로써 향 후 KDC 발전에 일조하기 위한 것이다. 고찰대상으로는 기본적인 장치임에도 불구하고 제외된 것들(내부보조표, 우선순위표, 해설, 신 구대비표 등)을 비롯하여 본표, 조기표(공통보조표), 주기, 색인, 양자택일 등을 분석대상으로 삼았으며, 나아가 오류, 표기부적절, 누락, 표현일관성결여 및 삭제해야 할 부분 등도 바로 잡고자 한다.

• Journal of Information Technology Applications and Management
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• 제9권3호
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• pp.129-139
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• 2002

There exist a number of information systems planning (ISP) methodologies. Historically these methodologies have been evolving to reflect new technologies and business requirements. In fact, it is an uneasy task to select a methodology that fits a business need. Though there have been a number of studies proposing new ISP approaches, we are unable to find much research doing a comparative analysis on existing ISP methodologies. Our study, therefore, is to present a classification scheme for ISP approaches and to provide a guideline framework for selecting an approach most suitable to a particular firm's need. Our classification utilizes types of components covered in ISP deliverables and the peculiarity of these components. Such classification scheme and selection framework would help derive an IT-driven new enterprise model more effectively.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2004년도 GIS/RS 공동 춘계학술대회 논문집
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• pp.261-265
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• 2004

The purpose of this study is to present a standardized scheme for providing agriculture-related information at various spatial resolutions of satellite images including Landsat＋ETM, KOMPSAT-1 EOC, ASTER VNIR, and IKONOS panchromatic and multi-spectral images. The satellite images were interpreted especially for identifying agricultural areas, crop types, agricultural facilities and structures. The results were compared with the land cover/land use classification system suggested by Ministry of Construction & Transportation based on NGIS (National Geographic Information System) and Ministry of Environment based on satellite remote sensing data. As a result, high-resolution agricultural land cover map from IKONOS imageries was made out. The results by IKONOS image will be provided to KOMPSAT-2 project for agricultural application.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1995년도 추계학술대회 학술발표 논문집
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• pp.218-223
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• 1995

A new design scheme of a binary decision tree is proposed. In this scheme a binary decision tree is constructed by using genetic algorithm and FCM algorithm. At each node optimal or near-optimal feature or feature subset among all the available features is selected based on fitness function in genetic algorithm which is inversely proportional to classification error, balance between cluster, number of feature used. The proposed design scheme is applied to the handwtitten alphabetic characters. Experimental results show the usefulness of the proposed scheme.

• 한국대기환경학회지
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• 제14권4호
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• pp.321-332
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• 1998

Various meleorologlcal dada obtained by SODAR system in shoreline area surrounding Boryung power plant have been analysed to investigate atmospheric diffusibility. Important conclusion may be summarized as follows; (i) Stability classification scheme based on co (standard deviation of wind direction in degree for averaging time of 1 hour) appears to evaluate certain atmospheric velocity and : indicate horizontal mean wind speed. Thus different scheme for stability classification seems to be preferable in order to appropriately estimate lateral and vertical dispersion coefficients cy and cz, respectively. (ii) As a result of comparisons between 3 available schemes for estimating of mixing height, best one turned out to be the double height scheme where height corresponds to maximum cw.

• Management Science and Financial Engineering
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• 제12권2호
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• pp.71-85
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• 2006

Collaborative filtering, among other recommender systems, has been known as the most successful recommendation technique. However, it requires the user-item rating data, which may not be easily available. As an alternative, some collaborative filtering algorithms have been developed recently by utilizing the market basket data in the form of the binary user-item matrix. Viewing the recommendation scheme as a two-class classification problem, we proposed a new collaborative filtering scheme using a regularized discriminant analysis applied to the binary user-item data. The proposed discriminant model was built in terms of the major principal components and was used for predicting the probability of purchasing a particular item by an active user. The proposed scheme was illustrated with two modified real data sets and its performance was compared with the existing user-based approach in terms of the recommendation precision.