• 한국문헌정보학회지
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• 제49권1호
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• pp.319-340
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• 2015

이 연구는 국립아시아문화전당 아시아문화정보원의 수집대상 문화자원을 효율적으로 관리하기 위한 분류체계를 제시하기 위하여 시도되었다. 아시아문화정보원의 목적과 수집정책 방향을 알아보고 문화자원의 특성과 범주를 파악하였다. 그리고 현재 실제로 사용하고 있는 HRAF 분류체계, UNESCO 문화지표, 민속아카이브의 분류검색, 한국향토문화전자대전의 콘텐츠목차 등 4개의 분류체계를 비교분석하였다. 이를 토대로 아시아정보원의 문화자원 분류체계의 원칙과 기준을 제시하고, 분류체계의 주제 전개는 문화적, 사회적, 자연적 영역 순으로 전개하였고, 주류는 16개의 항목으로 설정되었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권7호
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• pp.2261-2280
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• 2014

Recently, network traffic has become more complex and diverse due to the emergence of new applications and services. Therefore, the importance of application-level traffic classification is increasing rapidly, and it has become a very popular research area. Although a lot of methods for traffic classification have been introduced in literature, they have some limitations to achieve an acceptable level of performance in real-time application-level traffic classification. In this paper, we propose a novel application-level traffic classification method using payload size sequence (PSS) signature. The proposed method generates unique PSS signatures for each application using packet order, direction and payload size of the first N packets in a flow, and uses them to classify application traffic. The evaluation shows that this method can classify application traffic easily and quickly with high accuracy rates, over 99.97%. Furthermore, the method can also classify application traffic that uses the same application protocol or is encrypted.

• 한국도서관정보학회지
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• 제29권
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• pp.241-272
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• 1998

The purpose of this paper is to examine the analytic-assembling(faceted analysis) methods applied in enumerative-hierarchical classification schemes. (mainly in KDC) The methods are summarized as follows : 1. For the enumerative-hierarchical classification schemes, in principle the subjects are divided into subdivisions by only one facet at the same level, and step by step. However some subjects, for example 'library and information science' 'education' and others in KDC, are divided into subdivisions by multiple facets at same level like Colon Classification. 2. Most of enumerative-hierarchical classification schemes have various kinds of auxiliary tables, such as standard subdivisions, areas, periods, and languages. Each of them is considered as foci by a facet applied to subdivide all kinds of subjects or some special subjects into lower level. 3. To classify the compound subjects with phase relation, KDC provides ready-made classification numbers or notes that says 'divide by 001-999'(whole subjects) of 'divide by xxx-xxx'(limited scope of subjects). The ready-made compound subjects, or subdividing by whole or limited scope of subjects are similar to representation of phase relation in Colon Classification. Yet these analytic-assembling methods in KDC are needed to be supplemented and amended. Subdividing methods for faceted analysis have to be unified through the whole schedule. The auxiliary tables should be enlarged and subdivided more specifically. And for representation of phase relation, the linking signs can be useful in KDC as well as UDC and other analytic-assembling classification schemes like Colon Classification.

• 품질경영학회지
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• 제41권2호
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• pp.209-220
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• 2013

Purpose: This paper compares and discusses the influence on the quality classification of Kano's questionnaire which is used for the Kano model(Kano et al., 1984), the 3-point Likert-scale newly proposed by Kano and the 5-point Likert-scale presented in this study. Methods: For the comparison, the current study conducts a survey of 631 television viewers. The classification results of the three methods are then compared with those of direct classification which is adopted as a standard for classification of quality attributes. Results: The agreement rates between the results using conventional Kano's questionnaire and the results using direct classification is higher than the results using 3-point and 5-point Likert-scales. In addition, the attributes grouped as must-be or attractive in the direct classification appear to be classified as one-dimensional attributes in the Likert-scales. Conclusion: In comparison with the convensional Kano's questionnaire, the Likert-scale questions highly tend to classify the quatity attributes as one-dimensional. Although the classification results of the 3-point and 5-point Likert-scales are the same, the 5-point Likert-scale has the advantage to classify quality attributes in more detail.

• 한국화재소방학회논문지
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• 제21권3호
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• pp.84-90
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• 2007

UN에서는 위험물의 분류, 표지, 제조, 수송, 저장, 사용과 폐기에 관한 통합된 시스템(GHS, Globally Harmonized System of Classification and Labelling of Chemicals, 화학물질의 분류와 표지에 관한 세계조화시스템)을 구축하고 이 사항을 OECD에 가입한 모든 나라들에게 자국에 도입하여 실시하도록 권고하고 있다. GHS는 위험물분류와 운송부분에 관하여 물리 화학적 위험성과 급성독성의 분류와 표지사항을 기본으로 출발하였으므로 기존의 UN 시행방법과 큰 차이는 없다. 본 연구에서는 UN에서 권고하고 있는 GHS와 위험물안전관리법의 위험물분류와 위험물표지사항 및 위험물판정시험방법을 비교 검토하였다.

• 대한원격탐사학회지
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• 제34권4호
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• pp.671-680
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• 2018

Compared to the imagery produced by traditional satellites, PlanetScope satellite imagery has made it possible to easily capture remotely-sensed imagery every day through dozens or even hundreds of satellites on a relatively small budget. This study aimed to detect changed areas and update a land cover map using a PlanetScope image. To generate a classification map, pixel-based Random Forest (RF) classification was performed by using additional features, such as the Normalized Difference Water Index (NDWI) and the Normalized Difference Vegetation Index (NDVI). The classification result was converted to vector data and compared with the existing land cover map to estimate the changed area. To estimate the accuracy and trends of the changed area, the quantitative quality of the supervised classification result using the PlanetScope image was evaluated first. In addition, the patterns of the changed area that corresponded to the classification result were analyzed using the PlanetScope satellite image. Experimental results found that the PlanetScope image can be used to effectively to detect changed areas on large-scale land cover maps, and supervised classification results can update the changed areas.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권2호
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• pp.807-824
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• 2016

In this paper, a method of mood classification based on user brainwaves is proposed for real-time application in commercial services. Unlike conventional mood analyzing systems, the proposed method focuses on classifying real-time user moods by analyzing the user's brainwaves. Applying brainwave-related research in commercial services requires two elements - robust performance and comfortable fit of. This paper proposes a filter based on Regularized Common Spatial Patterns (RCSP) and presents its use in the implementation of mood classification for a music service via a wireless consumer electroencephalography (EEG) device that has only 14 pins. Despite the use of fewer pins, the proposed system demonstrates approximately 10% point higher accuracy in mood classification, using the same dataset, compared to one of the best EEG-based mood-classification systems using a skullcap with 32 pins (EU FP7 PetaMedia project). This paper confirms the commercial viability of brainwave-based mood-classification technology. To analyze the improvements of the system, the changes of feature variations after applying RCSP filters and performance variations between users are also investigated. Furthermore, as a prototype service, this paper introduces a mood-based music list management system called MyMusicShuffler based on the proposed mood-classification method.

• 산업공학
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• 제25권2호
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• pp.170-177
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• 2012

Process control is essential to operate the semiconductor process efficiently. This paper consider fault classification of semiconductor based cyclic signal for process control. In general, process signal usually take the different pattern depending on some different cause of fault. If faults can be classified by cause of faults, it could improve the process control through a definite and rapid diagnosis. One of the most important thing is a finding definite diagnosis in fault classification, even-though it is classified several times. This paper proposes the method that one-class classifier classify fault causes as each classes. Hotelling T2 chart, kNNDD(k-Nearest Neighbor Data Description), Distance based Novelty Detection are used to perform the one-class classifier. PCA(Principal Component Analysis) is also used to reduce the data dimension because the length of process signal is too long generally. In experiment, it generates the data based real signal patterns from semiconductor process. The objective of this experiment is to compare between the proposed method and SVM(Support Vector Machine). Most of the experiments' results show that proposed method using Distance based Novelty Detection has a good performance in classification and diagnosis problems.

• 한국통신학회논문지
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• 제35권9B호
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• pp.1322-1329
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• 2010

As body sensor network (BSN) research becomes mature, the need for managing power consumption of sensor nodes has become evident since most of the applications are designed for continuous monitoring. Real time Electrocardiograph (ECG) analysis on sensor nodes is proposed as an optimal choice for saving power consumption by reducing data transmission overhead. Smart sensor nodes with the ability to categorize lately detected ECG cycles communicate with base station only when ECG cycles are classified as abnormal. In this paper, ECG classification algorithms are described, which categorize detected ECG cycles as normal or abnormal, or even more specific cardiac diseases. Our Euclidean distance (ED) based classification method is validated to be most power efficient and very accurate in determining normal or abnormal ECG cycles. A close comparison of power efficiency and classification accuracy between our ED classification algorithm and generalized linear model (GLM) based classification algorithm is provided. Through experiments we show that, CPU cycle power consumption of ED based classification algorithm can be reduced by 31.21% and overall power consumption can be reduced by 13.63% at most when compared with GLM based method. The accuracy of detecting NSR, APC, PVC, SVT, VT, and VF using GLM based method range from 55% to 99% meanwhile, we show that the accuracy of detecting normal and abnormal ECG cycles using our ED based method is higher than 86%.

• 한국기록관리학회지
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• 제5권2호
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• pp.73-101
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• 2005

본 연구는 시민단체 기록의 분류방안을 마련해 보는 데에 연구의 목적을 두고, 환경운동연합을 사례로 환경연합기록의 분류체계 및 처리일정표 개발 과정을 제시해 보았다. 환경연합 기록의 분류원칙으로 기능분류에 주제분류를 결합한 형태의 분류원칙을 적용하였으며, 기능분류체계 개발을 위해 기록관리 업무분석 표준인 AS 5090와 DIRKS 방법론을 활용하였다. 연구 방법으로는 문헌연구, 자료조사, 인터뷰, 업무분석, 설문조사 등을 활용하였다.