• 제목/요약/키워드: Park Classification

검색결과 4,160건 처리시간 0.028초

Kano 모델의 품질속성 분류를 위한 질문서 연구 (Comparing the Questionnaires for Classifying Quality Attributes in the Kano Model)

  • 김만호;송해근;박영택
    • 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.

Brainwave-based Mood Classification Using Regularized Common Spatial Pattern Filter

  • Shin, Saim;Jang, Sei-Jin;Lee, Donghyun;Park, Unsang;Kim, Ji-Hwan
    • 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.

흉부 CT 영상에서 폐기종질환진단을 위한 폐기종영역 사전 탐지 기법 (Emphysema Region Pre-Detection Method for Emphysema Disease Diagnosis using Lung CT Images)

  • 뮤잠멜;팽소호;박민욱;김덕환
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2010년도 한국컴퓨터종합학술대회논문집 Vol.37 No.1(C)
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    • pp.447-451
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    • 2010
  • In this paper, we propose a simple but effective algorithm to increase the speed of Emphysema region classification. Emphysema region classification method based on CT image consumes a lot of time because of the large number of subregions due to the large size of CT image. Some of the sub-regions contain no Emphysema and the classification of these regions is worthless. To speed up the classification process, we create an algorithm to select Emphysema region candidates and only use these candidates in the Emphysema region classification instead of all of the sub-regions. First, the lung region is detected. Then we threshold the lung region and only select the dark pixels because Emphysema only appeared in the dark area of the CT image. Then the thresholded pixels are clustered into a region that called the Emphysema pre-detected region or Emphysema region candidate. This region is then divided into sub-region for the Emphysema region classification. The experimental result shows that Emphysema region classification using predetected Emphysema region decreases the size of lung region which will result in about 84.51% of time reduction in Emphysema region classification.

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주성분 분석과 동적 분류체계를 사용한 자동 이메일 분류 (Automatic e-mail classification using Dynamic Category Hierarchy and Principal Component Analysis)

  • 박선;김철원;이양원
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2009년도 춘계학술대회
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    • pp.576-579
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    • 2009
  • 인터넷 사용의 보편화로 이메일의 양이 급속히 증가하고 있다. 따라서 수신 메일을 효율적이면서 정확하게 분류할 필요성이 점차 증가하고 있다. 현재의 이메일 분류는 베이지안, 규칙 기반 등을 이용하여 스팸 메일을 필터링하기 위한 이원 분류가 주를 이루고 있다. 클러스터링을 이용한 다원 분류 방법은 분류의 정확도가 떨어지는 단점이 있다. 본 논문에서는 주성분 분석(PCA, Principal Component Analysis)을 기반으로 한 자동 카테고리 생성 방법과 동적 분류 체계 방법을 결합한 새로운 자동 이메일 분류 방법을 제안한다. 이 방법은 수신되는 이메일을 자동으로 분류하여 대량의 메일을 효율적으로 관리할 수 있으며, 메일을 동적으로 재분류 하여 분류 정확률을 높일 수 있다.

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미디어 분류를 위한 온톨로지 스키마 자동 생성 (Automated Modelling of Ontology Schema for Media Classification)

  • 이남기;박현규;박영택
    • 정보과학회 논문지
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    • 제44권3호
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    • pp.287-294
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    • 2017
  • UCC와 SNS 등을 통해 개인 미디어가 다양한 방식으로 생성됨에 따라 미디어를 분석하고 인지하는 기술에 대한 연구가 진행되고 있으며, 이를 통해 객체 인지의 수준이 향상되었다. 그 결과 기존의 제목, 태그 및 스크립터 정보를 이용한 추론 방식과 달리 미디어에서 인지되는 객체를 활용하는 영상 분류 추론 연구가 수행되고 있다. 하지만 추론을 위한 미디어 온톨로지 모델링을 사람이 직접 수행해야 하기 때문에 많은 시간과 비용이 발생하는 단점이 있다. 따라서 본 논문에서는 미디어 분류를 위한 온톨로지 스키마 모델링의 자동화 방법을 제안한다. 영상에서 인지되는 객체의 빈도에 따른 OWL-DL 공리의 특성을 고려하여 온톨로지 모델 생성의 자동화 방안에 대하여 설명한다. 유튜브에서 수집한 15가지의 카테고리에 대한 영상으로부터 온톨로지 모델을 자동 생성하여 추론을 통해 미디어 분류의 정확도에 대한 실험을 수행하였다. 실험결과 15가지 영상 이벤트의 행위 약 1500개에 대하여 영상 분류를 수행한 결과, 86%의 정확도를 얻었고, 온톨로지 모델링의 자동화 방법에 대한 타당한 성능을 보였다.

Clinical Relevance of the Tumor Location-Modified Lauren Classification System of Gastric Cancer

  • Choi, Jang Kyu;Park, Young Suk;Jung, Do Hyun;Son, Sang Yong;Ahn, Sang Hoon;Park, Do Joong;Kim, Hyung Ho
    • Journal of Gastric Cancer
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    • 제15권3호
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    • pp.183-190
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    • 2015
  • Purpose: The Lauren classification system is a very commonly used pathological classification system of gastric adenocarcinoma. A recent study proposed that the Lauren classification should be modified to include the anatomical location of the tumor. The resulting three types were found to differ significantly in terms of genomic expression profiles. This retrospective cohort study aimed to evaluate the clinical significance of the modified Lauren classification (MLC). Materials and Methods: A total of 677 consecutive patients who underwent curative gastrectomy from January 2005 to December 2007 for histologically confirmed gastric cancer were included. The patients were divided according to the MLC into proximal non-diffuse (PND), diffuse (D), and distal non-diffuse (DND) type. The groups were compared in terms of clinical features and overall survival. Multivariate analysis served to assess the association between MLC and prognosis. Results: Of the 677 patients, 48, 358, and 271 had PND, D, and DND, respectively. Their 5-year overall survival rates were 77.1%, 77.7%, and 90.4%. Compared to D and PND, DND was associated with significantly better overall survival (both P<0.01). Multivariate analysis showed that age, differentiation, lympho-vascular invasion, T and N stage, but not MLC, were independent prognostic factors for overall survival. Multivariate analysis of early gastric cancer patients showed that MLC was an independent prognostic factor for overall survival (odds ratio, 5.946; 95% confidence intervals, 1.524~23.197; P=0.010). Conclusions: MLC is prognostic for survival in patients with gastric adenocarcinoma, in early gastric cancer. DND was associated with an improved prognosis compared to PND or D.

욕창 분류체계교육프로그램이 병원간호사의 욕창 분류체계와 실금관련 피부염에 대한 지식과 시각적 감별 능력에 미치는 효과 (Effects of Pressure Ulcer Classification System Education Program on Knowledge and Visual Discrimination Ability of Pressure Ulcer Classification and Incontinence-Associated Dermatitis for Hospital Nurses)

  • 이윤진;박승미
    • Journal of Korean Biological Nursing Science
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    • 제16권4호
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    • pp.342-348
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    • 2014
  • Purpose: The purpose of this study was to examine the effects of pressure ulcer classification system education on hospital nurses' knowledge and visual discrimination ability of pressure ulcer classification system and incontinence-associated dermatitis. Methods: One group pre- and post-test was used. A convenience sample of 96 nurses participating in pressure ulcer classification system education, were enrolled in single institute. The education program was composed of a 50-minute lecture on pressure ulcer classification system and case-studies. The pressure ulcer classification system and incontinence-associated dermatitis knowledge test and visual discrimination tool, consisting of 21 photographs including clinical information were used. Paired t-test was performed using SPSS/WIN 18.0. Results: The overall mean difference of pressure ulcer classification system knowledge (t=4.67, p<.001) and visual discrimination ability (t=10.58, p<.001) were statistically and significantly increased after pressure ulcer classification system education. Conclusion: Overall understanding of pressure ulcer classification system and incontinence-associated dermatitis after pressure ulcer classification system education was increased, but tended to have lack of visual discrimination ability regarding stage III, suspected deep tissue injury. Differentiated continuing education based on clinical practice is needed to improve knowledge and visual discrimination ability for pressure ulcer classification system, and comparison experiment research is required to evaluate its effects.

토지피복분류에 관한 이론적 연구 - 자연환경관리를 중심으로 - (A Theoretical Study on Land Cover Classification - Focused on Natural Environment Management -)

  • 전성우;김귀곤;박종화;이동근
    • 한국환경복원기술학회지
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    • 제2권1호
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    • pp.29-37
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    • 1999
  • Land cover classification is an essential basic information in natural environment management; however, land cover classification studies in Korea have not yet been proceeded to a sufficient level. At the present, only a limited number of the precedent studies that only cover definite city area has been conducted. Furthermore, there is almost no research conducted on the land cover classification schemes that could accurately classify the Korea's land cover conditions. This study primarily focuses on the land cover classification scheme which carries the most urgent priority in order to classify and to map out the Korean land cover conditions. In order to develop the most suitable land cover classification scheme, many foreign land cover classification cases and projects that are being carried out were reviewed in depth. The land cover classification scheme this study proposes comprises 3 levels : The first level consists of 7 different classes; the second level consists of 22 different classes; and the third level is made up of 50 classes. The land cover classification map will serve many important roles in natural environment management, such as the conjecture of natural habitats and estimation of oxygen production or carbon dioxide absorption capability of a forest. In water pollution modelling, the land cover classification data can be used to estimate and locate non-point sources of water pollution. If applied to a watershed, modelling it will allow to estimate the total amount of pollution from non-point sources of pollution in the water shed. The land cover classification data will also be good as a barometer data that determines defusion of air pollutants in air pollution modelling.

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한국 한의학 질병사인분류 체계에 관한 연구 (The research on the disease classifications of the traditional medicine in Korea)

  • 최선미;박경모;신민규;신현규
    • 대한예방한의학회지
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    • 제4권2호
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    • pp.93-107
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    • 2000
  • Korea follows the Korea standard classification of disease and causes of death according to the ICD(international classification of disease) Oriental medicine began to of officially follow the classification of disease for using the Korean classification of diseases in 1972. The classification of OM(oriental medicine) has changed in shape experiencing two amendments. The largest difficulty was to overcome the different names of diseases between OM and ICD. A one-to-one correspondence of the name of a disease between OM and ICD is impossible So in the primary stage one-to-one and one-to-many correspondence was made. During the first amendment the international disease names were re-classified on the oriental medicine disease name's basis and at the same time the classification of OM was corresponded on a one-to-one basis to the ICD . During the second amendment this changed to many-to-many correspondence . Analyzing the history of classification of OM during the first and second amendments, it was discovered that establishment of the standards of classification, the unification of oriental medical terms, and overcoming the difference of disease names between the OM and ICD is necessary Also th classification and standardazation of OM must not stop as a single round. It must go on for a long time. The hosts of this project Korean oriental medical society and AKOM(association of korean oriental medicine) need to build a independant department which will supervise the classification project and monitor any problems to come up. Also a route through which suggestions can be taken in and new solutions can be brought up needs to be secured and an atmosphere in which studies can take place about the basis of classifications needs to be developed.

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RapidEye 위성영상의 시계열 NDVI 및 객체기반 분류를 이용한 북한 재령군의 논벼 재배지역 추출 기법 연구 (Extraction of paddy field in Jaeryeong, North Korea by object-oriented classification with RapidEye NDVI imagery)

  • 이상현;오윤경;박나영;이성학;최진용
    • 한국농공학회논문집
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    • 제56권3호
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    • pp.55-64
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    • 2014
  • While utilizing high resolution satellite image for land use classification has been popularized, object-oriented classification has been adapted as an affordable classification method rather than conventional statistical classification. The aim of this study is to extract the paddy field area using object-oriented classification with time series NDVI from high-resolution satellite images, and the RapidEye satellite images of Jaeryung-gun in North Korea were used. For the implementation of object-oriented classification, creating objects by setting of scale and color factors was conducted, then 3 different land use categories including paddy field, forest and water bodies were extracted from the objects applying the variation of time-series NDVI. The unclassified objects which were not involved into the previous extraction classified into 6 categories using unsupervised classification by clustering analysis. Finally, the unsuitable paddy field area were assorted from the topographic factors such as elevation and slope. As the results, about 33.6 % of the total area (32313.1 ha) were classified to the paddy field (10847.9 ha) and 851.0 ha was classified to the unsuitable paddy field based on the topographic factors. The user accuracy of paddy field classification was calculated to 83.3 %, and among those, about 60.0 % of total paddy fields were classified from the time-series NDVI before the unsupervised classification. Other land covers were classified as to upland(5255.2 ha), forest (10961.0 ha), residential area and bare land (3309.6 ha), and lake and river (1784.4 ha) from this object-oriented classification.