• 제목/요약/키워드: classification of class

검색결과 1,555건 처리시간 0.025초

Soft Independent Modeling of Class Analogy for Classifying Lumber Species Using Their Near-infrared Spectra

  • Yang, Sang-Yun;Park, Yonggun;Chung, Hyunwoo;Kim, Hyunbin;Park, Se-Yeong;Choi, In-Gyu;Kwon, Ohkyung;Yeo, Hwanmyeong
    • Journal of the Korean Wood Science and Technology
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    • 제47권1호
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    • pp.101-109
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    • 2019
  • This paper examines the classification of five coniferous species, including larch (Larix kaempferi), red pine (Pinus densiflora), Korean pine (Pinus koraiensis), cedar (Cryptomeria japonica), and cypress (Chamaecyparis obtusa), using near-infrared (NIR) spectra. Fifty lumber samples were collected for each species. After air-drying the lumber, the NIR spectra (wavelength = 780-2500 nm) were acquired on the wide face of the lumber samples. Soft independent modeling of class analogy (SIMCA) was performed to classify the five species using their NIR spectra. Three types of spectra (raw, standard normal variated, and Savitzky-Golay $2^{nd}$ derivative) were used to compare the classification reliability of the SIMCA models. The SIMCA model based on Savitzky-Golay $2^{nd}$ derivatives preprocessing was determined as the best classification model in this study. The accuracy, minimum precision, and minimum recall of the best model (PCA models using Savitzky-Golay $2^{nd}$ derivative preprocessed spectra) were evaluated as 73.00%, 98.54% (Korean pine), and 67.50% (Korean pine), respectively.

Semi-Supervised Recursive Learning of Discriminative Mixture Models for Time-Series Classification

  • Kim, Minyoung
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제13권3호
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    • pp.186-199
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    • 2013
  • We pose pattern classification as a density estimation problem where we consider mixtures of generative models under partially labeled data setups. Unlike traditional approaches that estimate density everywhere in data space, we focus on the density along the decision boundary that can yield more discriminative models with superior classification performance. We extend our earlier work on the recursive estimation method for discriminative mixture models to semi-supervised learning setups where some of the data points lack class labels. Our model exploits the mixture structure in the functional gradient framework: it searches for the base mixture component model in a greedy fashion, maximizing the conditional class likelihoods for the labeled data and at the same time minimizing the uncertainty of class label prediction for unlabeled data points. The objective can be effectively imposed as individual mixture component learning on weighted data, hence our mixture learning typically becomes highly efficient for popular base generative models like Gaussians or hidden Markov models. Moreover, apart from the expectation-maximization algorithm, the proposed recursive estimation has several advantages including the lack of need for a pre-determined mixture order and robustness to the choice of initial parameters. We demonstrate the benefits of the proposed approach on a comprehensive set of evaluations consisting of diverse time-series classification problems in semi-supervised scenarios.

다중 클래스 SVMs를 이용한 얼굴 인식의 성능 개선 (The Performance Improvement of Face Recognition Using Multi-Class SVMs)

  • 박성욱;박종욱
    • 대한전자공학회논문지SP
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    • 제41권6호
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    • pp.43-49
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    • 2004
  • 기존의 다중 클래스 SVMs은 클래스의 개수가 증가되면, 이진 클래스 SVMs의 수도 증가되어 분류를 위해 많은 시간이 요구된다. 본 논문에서는 분류 시간을 줄이기 위하여, PCA+LDA 특징 부 공간에서 NNR을 적용하여 클래스의 개수를 줄이는 방법을 제안한다. 제안된 방법은 PCA+LDA 특징 부 공간에서 간단한 NNR을 사용하여, 입력된 테스트 특징 데이터와 근접된 얼굴 클래스들을 추출함으로서 얼굴 클래스의 개수를 줄이는 방법이다. 클래스 개수를 줄임으로, 본 방법은 기존의 다중 클래스 SVMs에 비하여 훈련 횟수와 비교 횟수를 줄일 수 있고, 결과적으로 하나의 테스트 영상을 위한 분류 시간을 크게 줄일 수 있다. 또한 실험 결과, 제안된 방법은 NNC 기법보다 낮은 에러 율을 가지며, 기존의 다중 클래스 SVMs보다 동일한 에러 율을 갖지만, 보다 빠른 분류시간을 가짐을 확인할 수 있었다.

Dynamic Positioning System의 IMO Class 변경 요건에 관한 연구 (A Study on Dynamic Positioning System IMO class upgrade requirements)

  • 채종주
    • 한국항해항만학회지
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    • 제39권3호
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    • pp.165-172
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    • 2015
  • Dynamic Positioning System(DPS)은 그 신뢰성 및 redundancy(대체) 시스템에 따라 IMO 및 각 선급에서 3개의 class(등급)로 나누고 있다. IMO MSC/Circ 645에 의하면 DPS는 Class 1, 2, 및 3로 나누고 있으며 등급이 높을수록 좀 더 신뢰성 있고 안전하게 DP 선박을 운용할 수 있다. 국내에서 많은 DP Class 선박들이 건조되고 있는 상황에서 DP Class 1선박의 개조를 통해서 DP Class 2로 변경하거나 DP Class 2선박을 신조 또는 중고선으로 구입하는 경우 무엇을 검토하고 확인해야 하는지에 대한 구체적인 실무 자료가 부족하고, DP Class 1선박을 Class 2로 변경하여 다시 매도하는 새로운 산업분야의 개척에 있어 국내 사례를 바탕으로 한 연구가 필요할 것으로 판단된다. 이에 본 연구에서는 DP Class 1선박을 DP Class 2 선박으로 변경하기 위해서는 어떠한 IMO 및 선급의 DP class 요건의 충족이 필요하며 이를 위해서 어떠한 설비의 변경 및 추가가 필요한지를 국내에서 있었던 실제 사례를 통해서 연구해 보았다. DP 선박 Class 변경을 위해서는 FMEA를 통해서 파악되는 DP 선박의 동력 시스템, thruster 시스템 및 제어 시스템 3가지의 주요 시스템에 대체(redundancy)기능을 갖추어야 한다. 동력 시스템은 단일의 발전기, 배전반등에 문제가 발생해도 DP 기능을 유지할 수 있어야 하며, 더불어 PMS기능을 갖추고 있어야 한다. thruster 시스템은 단일의 고장이 발생하더라도 선박의 Surge, Sway 및 Yaw를 남은 thruster 시스템으로 자동 제어 할 수 있어야 한다. 각종 제어 시스템, PRS 및 센서는 여러개를 설치하여 단일의 장비고장에도 DP 기능을 유지 할 수 있어야 한다.

Five-year investigation of a large orthodontic patient population at a dental hospital in South Korea

  • Piao, Yongxu;Kim, Sung-Jin;Yu, Hyung-Seog;Cha, Jung-Yul;Baik, Hyoung-Seon
    • 대한치과교정학회지
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    • 제46권3호
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    • pp.137-145
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    • 2016
  • Objective: The purpose of this study was to investigate the characteristics of orthodontic patients at Yonsei Dental Hospital from 2008 to 2012. Methods: We evaluated Angle's classification from molar relationships, classification of skeletal malocclusion from the A point-nasion-B point angle, facial asymmetry, and temporomandibular joint disorders (TMDs) from the records of 7,476 patients who received an orthodontic diagnosis. The orthognathic surgery rate, extraction rate, and extraction sites were determined from the records of 4,861 treated patients. Results: The patient number increased until 2010 and gradually decreased thereafter. Most patients were aged 19-39 years, with a gradual increase in patients aged ${\geq}40years$. Angle's Class I, Class II divisions 1 and 2, and Class III malocclusions were observed in 27.7%, 25.6%, 10.6%, and 36.1% patients, respectively, with a gradual decrease in the frequency of Class I malocclusion. The proportion of patients with skeletal Class I, Class II, and Class III malocclusions was 34.3%, 34.3%, and 31.4%, respectively, while the prevalence of facial asymmetry and TMDs was 11.0% and 24.9%, respectively. The orthognathic surgery rate was 18.5%, with 70% surgical patients exhibiting skeletal Class III malocclusion. The overall extraction rate among nonsurgical patients was 35.4%, and the maxillary and mandibular first premolars were the most commonly extracted teeth. Conclusions: The most noticeable changes over time included a decrease in the patient number after 2010, an increase in the average patient age, and a decrease in the frequency of Angle's Class I malocclusion. Our results suggest that periodic characterization is necessary to meet the changing demands of orthodontic patients.

온라인 리뷰에서 평점의 분류 (Classification of ratings in online reviews)

  • 최동준;최호식;박창이
    • Journal of the Korean Data and Information Science Society
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    • 제27권4호
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    • pp.845-854
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    • 2016
  • 감성분석 (sentiment analysis) 혹은 오피니언 마이닝 (opinion mining)은 블로그, 리뷰, 신문기사나 소셜네트워크 등의 문서에서 개인의 주관적인 정보 혹은 의견을 알아보는데 사용되는 텍스트 마이닝의 기법이다. 평점이 있는 온라인 리뷰에서 리뷰 텍스트에 기반한 평점의 분류문제에 대한 선행연구에서는 이진 분류만을 고려하였다. 그러나 긍정과 부정 외에도 중립적인 의견도 있을 수 있기 때문에 이진 분류보다는 다범주 분류가 더 적합할 것이다. 본 연구에서는 리뷰 텍스트에 기반한 평점의 다범주 분류문제를 고려한다. 전처리에서는 카이제곱 통계량을 이용하여 평점과 연관된 단어들을 추출하고 이를 입력변수로 삼아 지지벡터기계 (support vector machines)와 비례오즈 모형 (proportional odds model) 등 다범주 분류기의 예측력을 비교한다.

군사학 분야 웹 문서 분류체계의 설계 (A Design of Classification System for Military Information Resources on the Internet)

  • 오동근;황재영;배영활
    • 한국도서관정보학회지
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    • 제32권2호
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    • pp.323-347
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    • 2001
  • 이 연구는 군사학 분야의 인터넷 학술정보자원을 효율적으로 조직, 활용하기 위한 청문서 분류체계의 모형을 제시하기 위해 시도된 것이다. 이를 위해, 우선 일반문헌분류표 가운데 군사정보에 관한 항목을 상세하게 전개하고 있는 LCC의 Class U(Military Science)와 Class V(Naval Class)를 상세히 분석하고, 웹 문서 분류체계 중 체계적 분류방식을 도입하고 있는 Yahoo!의 분류항목(처음/정부/군사)을 비교 분석하였다. 아울러 웹 문서 분류체계의 새로운 설계를 위해 기존의 Yahoo! Korea와 심마니, Yahoo! US를 종합적으로 비교 분석하였다. 이와 같은 비교 분석의 결과를 바탕으로, 실제적인 분류체계의 모형을 제시하였다.

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일 대학병원 호스피스 병동 입원 환자의 간호활동시간 측정과 원가산정 (Determination of Cost and Measurement of nursing Care Hours for Hospice Patients Hospitalized in one University Hospital)

  • 김경운
    • 간호행정학회지
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    • 제6권3호
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    • pp.389-404
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    • 2000
  • This study was designed to determine the cost and measurement of nursing care hours for hospice patients hostpitalized in one university hospital. 314 inpatients in the hospice unit 11 nursing manpower were enrolled. Study was taken place in C University Hospital from 8th to 28th, Nov, 1999. Researcher and investigator did pilot study for selecting compatible hospice patient classification indicators. After modifying patient classification indicators and nursing care details for general ward, approved of content validity by specialist. Using hospice patient classification indicators and per 5 min continuing observation method, researcher and investigator recorded direct nursing care hours, indirect nursing care hours, and personnel time on hospice nursing care hours, and personnel time on hospice nursing care activities sheet. All of the patients were classified into Class I(mildly ill), Class II (moderately ill), Class III (acutely ill), and Class IV (critically ill) by patient classification system (PCS) which had been carefully developed to be suitable for the Korean hospice ward. And then the elements of the nursing care cost was investigated. Based on the data from an accounting section (Riccolo, 1988), nursing care hours per patient per day in each class and nursing care cost per patient per hour were multiplied. And then the mean of the nursing care cost per patient per day in each class was calculated. Using SAS, The number of patients in class and nursing activities in duty for nursing care hours were calculated the percent, the mean, the standard deviation respectively. According to the ANOVA and the $Scheff{\'{e}$ test, direct nursing care hours per patient per day for the each class were analyzed. The results of this study were summarized as follows : 1. Distribution of patient class : class IN(33.5%) was the largest class the rest were class II(26.1%) class III(22.6%), class I(17.8%). Nursing care requirements of the inpatients in hospice ward were greater than that of the inpatients in general ward. 2. Direct nursing care activities : Measurement ${\cdot}$ observation 41.7%, medication 16.6%, exercise ${\cdot}$ safety 12.5%, education ${\cdot}$ communication 7.2% etc. The mean hours of direct nursing care per patient per day per duty were needed ; 69.3 min for day duty, 64.7 min for evening duty, 88.2 min for night duty, 38.7 min for shift duty. The mean hours of direct nursing care of night duty was longer than that of the other duty. Direct nursing care hours per patient per day in each class were needed ; 3.1 hrs for class I, 3.9 hrs for class II, 4.7 hrs for class III, and 5.2 hrs for class IV. The mean hours of direct nursing care per patient per day without the PCS was 4.1 hours. The mean hours of direct nursing care per patient per day in class was increased significantly according to increasing nursing care requirements of the inpatients(F=49.04, p=.0001). The each class was significantly different(p<0.05). The mean hours of direct nursing care of several direct nursing care activities in each class were increased according to increasing nursing care requirements of the inpatients(p<0.05) ; class III and class IV for medication and education ${\cdot}$ communication, class I, class III and class IV for measurement ${\cdot}$ observation, class I, class II and class IV for elimination ${\cdot}$ irrigation, all of class for exercise ${\cdot}$ safety. 3. Indirect nursing care activities and personnel time : Recognization 24.2%, house keeping activity 22.7%, charting 17.2%, personnel time 11.8% etc. The mean hours of indirect nursing care and personnel time per nursing manpower was 4.7 hrs. The mean hours of indirect nursing care and personnel time per duty were 294.8 min for day duty, 212.3 min for evening duty, 387.9 min for night duty, 143.3 min for shift duty. The mean of indirect nursing care hours and personnel time of night duty was longer than that of the other duty. 4. The mean hours of indirect nursing care and personnel time per patient per day was 2.5 hrs. 5. The mean hours of nursing care per patient per day in each class were class I 5.6 hrs, class II 6.4 hrs, class III 7.2 hrs, class IV 7.7 hrs. 6. The elements of the nursing care cost were composed of 2,212 won for direct nursing care cost, 267 won for direct material cost and 307 won for indirect cost. Sum of the elements of the nursing care cost was 2,786 won. 7. The mean cost of the nursing care per patient per day in each class were 15,601.6 won for class I, 17,830.4 won for class II, 20,259.2 won for class III, 21,452.2 won for class IV. As above, using modified hospice patient classification indicators and nursing care activity details, many critical ill patients were hospitalized in the hospice unit and it reflected that the more nursing care requirements of the patients, the more direct nursing care hours. Emotional ${\cdot}$ spiritual care, pain ${\cdot}$ symptom control, terminal care, education ${\cdot}$ communication, narcotics management and delivery, attending funeral ceremony, the major nursing care activities, were also the independent hospice service. But it is not compensated by the present medical insurance system. Exercise ${\cdot}$ safety, elimination ${\cdot}$ irrigation needed more nursing care hours as equal to that of intensive care units. The present nursing management fee in the medical insurance system compensated only a part of nursing car service in hospice unit, which rewarded lower cost that that of nursing care.

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최적화된 확률 모델을 이용한 다양한 품질의 지문분류 (Various Quality Fingerprint Classification Using the Optimal Stochastic Models)

  • 정혜욱;이지형
    • 한국시뮬레이션학회논문지
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    • 제19권1호
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    • pp.143-151
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    • 2010
  • 지문분류는 1:N 지문인식 시스템의 효율성을 높이는 단계로 지문의 매칭 시간 단축과 인식의 정확성을 높여주는 역할을 한다. 지문 각 클래스의 융선 패턴은 한 개 이상의 클래스와 중복되는 성질을 가지기 때문에 지문분류 작업은 어렵다. 또한 잡음을 많이 포함하거나 예외적인 입력 상태인 경우에도 분류 작업은 어려워진다. 본 논문에서는 다양한 품질의 지문을 효과적으로 분류하기 위해 지문의 방향특징을 이용해 확률 모델을 설계하고, 이를 최적화 하여 지문분류를 수행하는 방법을 제안하였다. 지문 융선을 픽셀단위로 탐색하여 방향 값을 산출하고, 산출된 방향 값을 일정 픽셀 단위로 병합하여 지문의 방향특징을 추출한다. 추출된 방향 특징을 이용해 확률론적 정보추출 및 인식 방식인 마코프 모델을 이용하여 지문의 클래스별 마코프 모델을 생성한다. 생성된 클래스별 마코프 모델의 상태전이 행렬을 분석하여 클래스별 분류 모델의 가중치 항목을 결정하고 유전자 알고리즘을 이용하여 지문분류 성능을 향상시킬 수 있는 최적의 수치를 찾아낸다. 유전알고리즘에 의해 최적화된 분류모델에 다양한 품질의 지문 데이터베이스를 적용하여 실험해 본 결과 최적화 되기 전의 분류 모델에 비해 우수한 분류성능을 보였다. 또한 실험에 사용한 다양한 품질의 데이터베이스를 분석해본 결과 제안한 방법은 특이점 유, 무 및 상태에 독립적으로 예외적인 입력상황의 지문에 대해 효율적으로 지분분류를 수행했다.

CLASSIFICATION OF SOLVABLE LIE GROUPS WHOSE NON-TRIVIAL COADJOINT ORBITS ARE OF CODIMENSION 1

  • Ha, Hieu Van;Hoa, Duong Quang;Le, Vu Anh
    • 대한수학회논문집
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    • 제37권4호
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    • pp.1181-1197
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    • 2022
  • We give a complete classification of simply connected and solvable real Lie groups whose nontrivial coadjoint orbits are of codimension 1. This classification of the Lie groups is one to one corresponding to the classification of their Lie algebras. Such a Lie group belongs to a class, called the class of MD-groups. The Lie algebra of an MD-group is called an MD-algebra. Some interest properties of MD-algebras will be investigated as well.