• Title, Summary, Keyword: 웃음

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만병통치약, 웃음 '한바탕 웃음으로' 건강해지세요

  • The Korean National Tuberculosis Association
    • 보건세계
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    • v.53 no.3
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    • pp.48-51
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    • 2006
  • 웃음을 '만병통치약' 혹은 '신비한 명약'이라고들 한다. 실제로 전문가들은 1번 웃으면 5분 동안 에어로빅을 한 것과 맞먹고 1분 동안 박장대소하면 10분 동안 조깅한 것이나 진배없다고 한다. 또 면역력을 높여주는 물질이 200배나 활발히 분비돼 각종 질병을 예방해 준다고도 한다. 웃음이 우리 몸에 어떤 영향을 미치는지 알아보고 웃는데 도움이 되는 정보를 모아보았다.

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마음의 힐링 - 웃음의 효능 웃음으로 극복하는 위기

  • Seon, An-Nam
    • 건강소식
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    • v.38 no.9
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    • pp.26-27
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    • 2014
  • 웃음에는 삶의 스트레스를 건너가게 해주는 유연한 힘이 있다. 아무리 힘들고 지치는 순간이라도 한번 활짝 웃고 나면 기분이 좋아지는 효과가 있다. 우리는 삶이 힘들고 지칠수록 우리를 웃게 해주는 무언가에 기대게 된다.

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Effects of Positive Attitude of Laughter Recreation Convergence Education on Psychological Happiness (웃음 레크리에이션 융합 교육에 대한 긍정적 태도가 심리적 행복감에 미치는 영향)

  • Lee, Sun Woo
    • Journal of the Korea Convergence Society
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    • v.6 no.3
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    • pp.37-49
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    • 2015
  • This study is to suggest the needs of laughter recreation convergence education as educational program to promote leisure use and happiness with the expectation that laughter recreation education will generate positive effect positive attitude and psychological happiness. So we prove that this education contributes to one's happy life through this study since it arouses positive changes on behavior. We included 108 Sampling targets and 216 copies of questionnaires to be done before and after education. As a result, partial factors of positive attitude on laughter recreation convergence education had a good influence on psychological happiness and there were differences between before and after the education. So this proves that it is meaningful to have laughter recreation convergence education.

Development of a Recognition System of Smile Facial Expression for Smile Treatment Training (웃음 치료 훈련을 위한 웃음 표정 인식 시스템 개발)

  • Li, Yu-Jie;Kang, Sun-Kyung;Kim, Young-Un;Jung, Sung-Tae
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.4
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    • pp.47-55
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    • 2010
  • In this paper, we proposed a recognition system of smile facial expression for smile treatment training. The proposed system detects face candidate regions by using Haar-like features from camera images. After that, it verifies if the detected face candidate region is a face or non-face by using SVM(Support Vector Machine) classification. For the detected face image, it applies illumination normalization based on histogram matching in order to minimize the effect of illumination change. In the facial expression recognition step, it computes facial feature vector by using PCA(Principal Component Analysis) and recognizes smile expression by using a multilayer perceptron artificial network. The proposed system let the user train smile expression by recognizing the user's smile expression in real-time and displaying the amount of smile expression. Experimental result show that the proposed system improve the correct recognition rate by using face region verification based on SVM and using illumination normalization based on histogram matching.

웃는 것도 운동 인류 최고의 명약 '웃음'

  • Lee, Jeong-Mi
    • 건강소식
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    • v.32 no.2
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    • pp.32-33
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    • 2008
  • 웃음은 세상에서 가장 아름다운 언어로 자신은 물론 다른 사람들까지 행복하게 한다. 더불어 건강에도 효과적이다. 여성의 평균수명이 남성보다 더 긴 이유 중 하나도 여자가 남자보다 더 수용적이고 긍정적이며 잘 웃기 때문이라고 한다. 여러 박사들은 논문이나 세미나를 통해 많이 웃을수록 건강하게 오래 살 수 있다고 말한다. 이런 시점에서 웃음이 질병 치료방법의 하나로 서서히 자리를 잡아가고 있다.

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Making Fun Strategy of Gag Concert (<개그콘서트>의 웃음생성 전략)

  • Hong, Kyung-Soo;Cho, Eui-Jin
    • The Journal of the Korea Contents Association
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    • v.12 no.1
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    • pp.138-145
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    • 2012
  • , Korea's popular television comedy program cast the strategy of making fun by word game interweaving meaning and nonmeaning and started to making fun by narrative game. So called Digital Narrative strategy seems to reflect the changes of social trends. Getting verisimilitude by detail description, parody realism, hierarchy of word body naked, anxiety for influence or star cameo seems to be principal strategy. With a minute realism strategy, new method of making meaning appropriate to digital era seems to appear.

Discrimination between spontaneous and posed smile: Humans versus computers (자발적 웃음과 인위적 웃음 간의 구분: 사람 대 컴퓨터)

  • Eom, Jin-Sup;Oh, Hyeong-Seock;Park, Mi-Sook;Sohn, Jin-Hun
    • Science of Emotion and Sensibility
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    • v.16 no.1
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    • pp.95-106
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    • 2013
  • The study compares accuracies between humans and computer algorithms in the discrimination of spontaneous smiles from posed smiles. For this purpose, subjects performed two tasks, one was judgment with single pictures and the other was judgment with pair comparison. At the task of judgment with single pictures, in which pictures of smiling facial expression were presented one by one, subjects were required to judge whether smiles in the pictures were spontaneous or posed. In the task for judgment with pair comparison, in which two kinds of smiles from one person were presented simultaneously, subjects were to select spontaneous smile. To calculate the discrimination algorithm accuracy, 8 kinds of facial features were used. To calculate the discriminant function, stepwise linear discriminant analysis (SLDA) was performed by using approximately 50 % of pictures, and the rest of pictures were classified by using the calculated discriminant function. In the task of single pictures, the accuracy rate of SLDA was higher than that of humans. In the analysis of accuracy on pair comparison, the accuracy rate of SLDA was also higher than that of humans. Among the 20 subjects, none of them showed the above accuracy rate of SLDA. The facial feature contributed to SLDA effectively was angle of inner eye corner, which was the degree of the openness of the eyes. According to Ekman's FACS system, this feature corresponds to AU 6. The reason why the humans had low accuracy while classifying two kinds of smiles, it appears that they didn't use the information coming from the eyes enough.

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