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전문조작원 유무에 따른 사상체질 음성진단의 신뢰성 분석
박현준,김종열,장준수,Park, Hyun Jun,Kim, Jong-Yeol,Jang, Jun-Su 사상체질의학회 2016 사상체질의학회지 Vol.28 No.4
Objectives This study was aimed to analyze the reliability of vocal features and probabilities for being in Sasang constitutional types calculated from Sasang constitutional voice diagnosis system according to operator presence. Methods We acquired 96 voice recordings from one male and one female for 4 days. For the first 2 days, the subjects recorded their voice by themselves. For the last 2 days, they recorded according to the instruction of an operator following the standard operating procedure. We analyze the standard deviations of vocal features, probabilities for being three constitutional types, Tae-Eum (TE), So-Yang (SY), and So-Eum (SE) Results In the case of the female, coefficients of variations of the voice variables and the probabilities for being each constitutional type were all within 20%. In the case of the male, coefficients of variations were all within 20% except one variable. Even if there was no instruction from the operator, standard deviations of the probability did not increase for both genders. When recorded without the operator, for male, the probability for being SE decreased by 3.2%. For female, the probability for being TE increased by 5.438%, and that of SE decreased by 3.057%, and that of SY decreased by 2.394%. Conclusions When recorded without operators, for men, there was a significant difference in the probability for being SE. And for women, there were significant differences in the probabilities for all constitutional types.
靑小年犯罪의 動向과 對策 : Juvenile Delinquency and Its Prevention in Korea
朴鉉俊 경주대학교 창의력개발연구소 2000 創意力開發硏究 Vol.- No.4
The major purpose of the present study is finding out an integrated model which can be applied to explain Korean juvenile delinquency adequately. The present study especially focuses upon criminal direction which is peculiar to Korea these days on the juvenile delinquency. The variables employed in the model are borrowed from several sociological theories of juvenile delinquency. The model expects that a Korean youth may feel the pressure to study if he(or she) fails to meet the expectation of his parents in his academic achievements. The guilty feeling results from the pressure may lead th the separation of the child from his parents, as a result he may get along with another juvenile who experiences the same misfortune. Failure in the entering to the major universities of Korea means failure in one's life. Having almost no hope for the future, the students may indulge in the trivial and minor delinquencies such as smoking, drinking, etc(status offens). and may yield themselves to the more serious crimes like gang fighting, robbery, etc. Detailed analyses of the trends of youth's violent crime in Korea further show a number of points interest, based on the findings of detailed analyses of the trends and recidivism in juvenile delinquency in Korea, it is strongly suggested here that truly comprehensive, systematic, and organized efforts should be made to deter and control violence in Korea in general and Youth's violent grime in particular. As a result, any remedy to the problems of juvenile delinquency can not be proposed by the present study, it can be suggested that we may confront the more serious problem of youths in the near future unless an immediate and effective alternative ways to success other than college degree is provided to the Korean adolescents.
디지털 영상 객체의 불투명도 추정을 위한 SOM Matting
박현준,차의영,Park, Hyun-Jun,Cha, Eui-Young 한국정보통신학회 2009 한국정보통신학회논문지 Vol.13 No.10
본 논문은 인공신경망을 이용한 새로운 매팅 기법을 제안한다. 매팅이란 영상에서 객체의 불투명도를 추정하는 기술이다. 매팅 기법을 이용하면 객체를 자연스럽게 추출할 수 있다. 먼저 trimap을 이용하여 영상을 배경 영역, 전경 영역, 미지 영역으로 구분한다. 배경 영역과 전경 영역의 정보를 이용하여 미지 영역 화소의 불투명도를 추정한다. 제안하는 알고리즘은 배경 영역과 전경 영역의 정보를 SOM을 이용하여 학습하고 그 결과를 이용하여 미지 영역의 각 화소의 불투명도를 추정한다. 본 논문에서는 배경 영역과 전경 영역의 정보를 학습하는 방법에 따라서 전역적 SOM matting과 지역적 SOM matting으로 구별한다. 제안하는 알고리즘의 성능을 평가하기 위하여 영상에 적용해보았다. 이를 통해 제안하는 알고리즘이 객체를 영상에서 분리 가능함을 확인 할 수 있다. This paper presents new matting techniques. The matting is an alpha estimation technique of object in an image. We can extract the object in an image naturally using the matting technique. The proposed algorithms begin by segmenting an image into three regions: definitely foreground, definitely background, and unknown. Then we estimate foreground, background, and alpha for all pixels in the unknown region. The proposed algorithms learn the definitely foreground and definitely background using self-organizing map(SOM), and estimate an alpha value of each pixel in the unknown region using SOM learning result. SOM matting is distinguished between global SOM matting and local SOM matting by learning method. Experiment results show the proposed algorithms can extract the object in an image.