• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.706-709
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• 2006

Cancer is one of the major causes of death; however, the survival rate can be increased if discovered at an early stage for timely treatment. According to the statistics of the World Health Organization of 2002, breast cancer was the most prevalent cancer for all cancers occurring in women worldwide, and it account for 16.8% of entire cancers inflicting Korean women today. In order to classify the type of breast cancer whether it is benign or malignant, this study was conducted with the use of the discriminant analysis and the decision tree of data mining with the breast cancer data disclosed on the web. The discriminant analysis is a statistical method to seek certain discriminant criteria and discriminant function to separate the population groups on the basis of observation values obtained from two or more population groups, and use the values obtained to allow the existing observation value to the population group thereto. The decision tree analyzes the record of data collected in the part to show it with the pattern existing in between them, namely, the combination of attribute for the characteristics of each class and make the classification model tree. Through this type of analysis, it may obtain the systematic information on the factors that cause the breast cancer in advance and prevent the risk of recurrence after the surgery.

• 한국지반공학회지:지반
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• 제9권3호
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• pp.61-66
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• 1993

본 논문에서는 암반 분류를 위해 물리탐사 결과나 그동안 축적된 시공경험 등의 정성적 자료의 사용을 고려하였다. 터널 설계를 위한 요소(parameter)들이 공간적 상관관계를 갖기 때문에 지구 통계학(Geostatistics)을 이용하였으며, 특히, 비모수적 (non-parametric)방법 중의 하나인 지시 크리깅(indicator kriging) 기법을 사용했다. 최적 분류를 위한 선택 기준으로는 오차에 대응하는 비용(the cost of errors)을 사용했으며, 암반분류는 이분적 분류에 한정하였다. 앞으로, 정량적 데이타가 절대적으로 부족한 터널공사등에서 비교적 많은 양이 존재하는 정성적 데이타의 이용은 절실하며, 이러한 점에서 본 연구가 가지는 의미는 크다.

• 한국환경보건학회지
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• 제14권1호
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• pp.33-38
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• 1988

Natural mineral water is generally quite different from ordinary drinking water due to its original nature and various properties. The complexity of natural mineral water requires, therefore, not only to identify its nature and proper characteristics, but also to classify them by a reasonable scientific basis of comparison. The study was concentrated on a possible classification technique to natural mineral waters by their constitutions and physico-ehemical properties. The classification was carried out by the computation of such numerical parameters as ionic equivalent percentage, electrolytic conductance or mobility, ionic molecular weight, molecular concentration, equivalent conductivity and degree of ionization in consideration of the determinative criteria as follows -particular single element or molecule -major components of natural waters as bicarbonate, sulphate, chloride,caloride, calcium, magnesium, and sodium -moleculat concentration related to blood osmotic pressure -water temperature at emergence from spring -contents of free carbon dioxide (CO2) -pH value of water -total dissolved solids or salts (NaCl) The results obtained proved out to be clearly distinguhhable from ordinary drinking water as far as concern natural mineral water as an example on the subject -simple water -bicarbonate-predominating water -cold spring -carbonated-non gaseous water -weak alkaline water -non saline water Putting these various results together, the sample turned out to be a kind of natural mineral water that can be used as a drinking water if microbiologically safe.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.514-519
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• 1992

To make an accurate retrieval of the proportion of each category among mixed pixels (Mixel's) of a remotely sensed imagery, a maximum likelihood estimation method of category proportion is proposed. In this method, the observed multispectral vector is considered as probability variables along with the approximation that the supervised data of each category can be characterized by normal distribution. The results show that this method can retrieve accurate proportion of each category among Mixel's. And a index that can estimate the degree of error in each category is proposed. AS one of the application of the proportion estimation, a method for image classification based on category proportion estimation is proposed. In this method all pixel in a remotely sensed imagery are assumed to be Mixel's, and are classified to most dominant category. Among the Mixel's, there exists unconfidential pixels which should be categorized as unclassified pixels. In order to discriminate them, two types of criteria, Chi square and AIC, are proposed for fitness test on pure pixel hypothesis. Experimental result with a simulated dataset show an usefulness of proposed classification criterion compared to the conventional maximum likelihood criterion and applicability of the fitness tests based on Chi square and AIC,

• 한국안전학회지
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• 제15권4호
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• pp.139-149
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• 2000

This study aims to review and assess the existing postural classification schemes used for evaluating postural loads in industry. The schemes can be classified into three categories: self-report, observational and instrument-based techniques depending upon how to record working postures. Of the three techniques, this study was mainly focused on the observational methods. The observational technique is most widely used in the industrial sites because it does not interfere with work, and is easy and simple to use and cost-effective without requiring the use of expensive equipment for estimating the angular deviation of a body segment from the neutral position. In spite of the usefulness and applicability, the techniques have some problems: 1) The existing observational techniques lack the consistency in the class limits of the motion categories in each body segment; 2) Most of them do not provide the post-analysis criteria needed to judge whether or not any posture is acceptable in view point of the postural load; and 3) They can not precisely evaluate the postural load for a given posture because the external loads and dynamic factors including acceleration, moment and force were not taken into consideration.

• 대한치과교정학회지
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• 제2권1호
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• pp.35-40
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• 1971

Since malocclusion affects a large segment of the population, it is by definition a public health problem. The etiology ana treatment of malocclusions have been studied by clinicians; however epidemioloic aspect of tile problem have been neglected. This study was undertaken using Angle's classification to obtain and to evaluate epidemiologic data on the prevalence of malocclusion in a group of 2,378 Yonsei University students, 17 to 23 years of age. All freshmen were selected, except for those students receiving orthodontic treatment and those few with too many missing teeth which prohibits classification by Angle's method. The following results were obtained: 1) Almost $91\%$ of students had malocclusion of the teeth severe enough to require correction. 2) There was a statistically significant difference in malocclusion between males and females($93.66\%$ malocclusion in males, $79.13\%$ malocclusioa in females). 3) Crowding was most pravalent in class I malocclusion. 4) There appeared to be a specific association between the number of lost first molars and Angle's classification. 5) In this study, more class II, Div.2 malocclusion appeared than in Massier's and Frankel's study of Caucasians, which used similar criteria. Class III malocclusion was more prevalent than normal occlusion in the Korean students studied, but in Caucasians' normal occlusion was more prevalent.

• 정보관리학회지
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• 제18권2호
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• pp.203-230
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• 2001

본 연구에서는 문헌을 기반으로 한 지식의 자동분류를 위해 최적의 클러스터링 모형을 제시하고자 하였다. 클러스터링 실험을 위해서 신문기사 실험집단과 학술논문 초록 실험집단을 구축하였고, 분류 성능 평가 척도인 WACS를 개발하였다. 분류자질로 사용한 용어의 집합은 다양한 자질 축소 기준을 적용하여 생성하였으며, 다양한 용어 가중치를 사용하였다. 유사계수 공식으로는 코사인 계수와 자카드 계수를 적용하였으며, 클러스터링 알고리즘으로는 비계층적 기법인 완전연결 기법과 계층적 기법인 K-means기법을 각각 사용하였다. 실험 결과 신문기사 원문 집단에서의 성능이 좋았으며, 완전연결 기법의 성능이 K-means 기법보다 높게 나타났다. 역문헌빈도의 적용은 완전연결 클러스터링에서는 긍정적인 효과가 나타났으나, K-means 클러스터링에서는 그렇지 못했다. 분류자질은 전체의 7.66%만 사용하였을 경우에도 성능 저하가 크지 않았으며, K-means 클러스터링에서는 오히려 성능 향상 효과가 있었다.

• 대한간호학회지
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• 제46권3호
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• pp.375-389
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• 2016

Purpose: The aim of this study was to classify nursing management competencies and develop behavioral indicators for nurse managers in hospitals. Also, levels of importance and performance based on developed criteria were to be identified and compared. Methods: Using expert survey we classified nursing management competencies and behavioral indicators with data from 34 nurse managers and professors. Subsequently, data from a survey of 216 nurse managers in 7 cities was used to analyze the importance-performance comparison of the classified nursing management competencies and behavioral indicators. Results: Forty-two nursing management competencies were identified together with 181 behavioral indicators. The mean score for importance of nursing management competency was higher than the mean score for performance. According to the importance-performance analysis, 5 of the 42 nursing management competencies require further development: vision-building, analysis, change management, human resource development, and self-management competency. Conclusion: The classification of nursing management competencies and behavioral indicators for nurse managers in hospitals provides basic data for the development and evaluation of programs designed to increase the competency of nurse managers in hospitals.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 추계학술발표대회
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• pp.637-640
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• 2018

The paper proposes a new deep network-based model that rates periorbital wrinkles in order to alleviate the shortcomings of the evaluation by human experts as well as to facilitate the automation. Periorbital wrinkles still need to be classified by human experts. Furthermore, the classification results from experts are different from each other in many cases due to the inter-interpreter variability and the absence of quantification criteria. Unlike existing classification methods which classify original images, the proposed model consists of a cascade of two deep networks: U-Net for the enhancement of wrinkles on an input image and VGG16 for final classification based on the wrinkle information. Experiments of the proposed model are made with a data set that consists of 433 images rated by experts, showing the promising performance.

• 한국가스학회지
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• 제24권1호
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• pp.56-65
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• 2020

일반적으로 화재는 다양한 원인으로 발생하며 무작위로 보이기에 화재의 발생을 예측한다는 것은 매우 도전적인 문제이다. 하지만 모든 화재가 아닌 큰 피해를 주는 초대형 화재사고의 예측이 가능하다면, 선제적 대응을 통한 손실 최소화를 기대할 수 있다. 본 연구에서는 국가 전체를 대상으로 초대형 화재사고를 예측하기 위해 기계학습 기법인 k-평균 클러스터링을 이용하여 화재사고를 분류하고, 이를 인위적인 설정이 강한 비전문가 기준, 전문가 기준 분류 결과와 비교하여 예측에 적절한 분류 기준을 제안하였다. 비교 결과 기계학습을 이용한 분류가 일정한 피해규모와 비율로 분류되어, 예측에 적절한 분류 기준이라 판단하였다. 또한 초대형 화재사고의 주기성을 분석한 결과 일정한 패턴을 보였지만 높은 편차를 보였다. 따라서 단순 예측기법이 아닌 고급 예측기법을 사용하였을 때 초대형 화재사고의 발생 예측이 가능하다고 판단되었다.