• Journal of Sasang Constitutional Medicine
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• v.4 no.1
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• pp.5-29
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• 1992

In this study, the author researched the process in which the philosophical basis of 'Sa Sang Medicine (四象醫學)' and its methodology build up the principles of Sa Sang Medicine, and then, examined how the principles were applied to the theoretical system of Sa Sang Medicine. The conclusion would be summarized as follows. 1. 'Nae Kyung Medicine (內經醫學)' was developed under the concept that the cosmos's order and its moving rule could be directly applied to that of human body, which corresponded to the 'Theory of Hwang-No (黃老之學)'. On the contrary, Sa Sang Medicine is a thoroughly human-oriented theory formed in the Confucianism system. 2. Lee Jae-Ma's Substantialism can be briefed into 'Mind 心' (Tae Keuk 太極), 'Mind-Body 心身' (Yang Eui 兩儀) and 'Activity-Mind-Body-Matter 事心身物' (Sa Sang 四象), which respectively represents one-elemented substance, two-elemented substance and four-elemented substance. Especially, Sa Sang was used as a basic framework in which he recognized all the objects and phenomena. So, most critical significance of his substantialism consists in the intention of Sa Sang type classifying. 3. By the method of Sa Sang type classifying, Lee Jae-Ma not only redefined the main concepts of confucianism and developed a unique philosophy of his own, but also, in the field of medical science, resystemized and re-explained the structure and function of human body. 4. From the recognition that Activity-Mind-body-Matter (Sa Sang) are four different existence forms of energy 氣 (or four variation types of energy), Yi Jae-Ma thinks that the viscera of human body have a vertical structure of 'four parts 四焦' (upper, mid-upper, mid-lower and lower parts) and its physiological function is operated by the rising and falling action of four energy presentations (sorrow 哀, anger 怒, joy 喜 and pleasure 樂). 5. In "Gyuk Chi Go 格致藁", Lee Jae-Ma understood the concept of joy, anger, sorrow and pleasure on the basis of nature-emotion theory 性情論 from the philosophical viewpoint. But, from the medical viewpoint of "Dong Eui Su Se Bo Won 東醫壽世保元", he understood them on the basis of vital energy theory. That is, sorrow, anger, joy and pleasure are expression of advance or reverse of nature vital-energy 性氣 and emotion vital-energy 情氣. 6. The rising and falling action principle of four energy presentations (sorrow, anger, joy and pleasure) which produces and helps each other is an identical principles of Sa Sang Medicine, distinguished from the Oh-Haeng 五行 circulating principle in Nae Kyung Medicine. Through this principle, Lee Jae-Ma explained the viscera physiology of human body, pathology & diagnosis and pharmacology.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.806-813
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• 2010

Human facial expression shows human's emotion most exactly, so it can be used as the most efficient tool for delivering human's intention to computer. For fast and exact recognition of human's facial expression on a 2D image, this paper proposes a new method which integrates an Discrete Adaboost classification algorithm and a neural network based recognition algorithm. In the first step, Adaboost algorithm finds the position and size of a face in the input image. Second, input detected face image into 5 Adaboost strong classifiers which have been trained for each facial expressions. Finally, neural network based recognition algorithm which has been trained with the outputs of Adaboost strong classifiers determines final facial expression result. The proposed algorithm guarantees the realtime and enhanced accuracy by utilizing fastness and accuracy of Adaboost classification algorithm and reliability of neural network based recognition algorithm. In this paper, the proposed algorithm recognizes five facial expressions such as neutral, happiness, sadness, anger and surprise and achieves 86~95% of accuracy depending on the expression types in real time.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.160-163
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• 2006

If an instruction system understood the interest and activeness of a learner in real time, it could provide some interesting factors when a learner is tired of learning. It could work as an adaptive tutoring system to help a learner to understand something difficult to understand. Currently the area of the facial expression recognition mainly deals with the facial expression of adults focusing on anger, hatred, fear, sadness, surprising and gladness. These daily facial expressions couldn't be one of expressions of a learner in e-Learning. They should first study the facial expressions of a learner in e-Learning to recognize the feeling of a learner. Collecting as many expression pictures as possible, they should study the meaning of each expression. This study, as a prior research, analyzes the feelings of learners and facial expressions of learners in e-Learning in relation to the feelings to establish the facial expressions database.

• Journal of KIISE:Software and Applications
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• v.32 no.6
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• pp.570-579
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• 2005

Facial expression recognition technology that has potentialities for applying various fields is appling on the man-machine interface development, human identification test, and restoration of facial expression by virtual model etc. Using sequential facial images, this study proposes a simpler method for detecting human facial expressions such as happiness, anger, surprise, and sadness. Moreover the proposed method can detect the facial expressions in the conditions of the sequential facial images which is not rigid motion. We identify the determinant face and elements of facial expressions and then estimates the feature regions of the elements by using information about color, size, and position. In the next step, the direction patterns of feature regions of each element are determined by using optical flows estimated gradient methods. Using the direction model proposed by this study, we match each direction patterns. The method identifies a facial expression based on the least minimum score of combination values between direction model and pattern matching for presenting each facial expression. In the experiments, this study verifies the validity of the Proposed methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.821-827
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• 2009

Human emotion can be reflected by their facial expressions. So, it is one of good ways to understand people's emotions by recognizing their facial expressions. General recognition system of facial expressions had selected interesting points, and then only extracted features without analyzing physical meanings. They takes a long time to find interesting points, and it is hard to estimate accurate positions of these feature points. And in order to implement a recognition system of facial expressions on real-time embedded system, it is needed to simplify the algorithm and reduce the using resources. In this paper, we propose a real-time recognition algorithm of facial expressions that project the grid points on an expression space based on Gabor wavelet feature. Facial expression is simply described by feature vectors on the expression space, and is classified by an neural network with its resources dramatically reduced. The proposed system deals 5 expressions: anger, happiness, neutral, sadness, and surprise. In experiment, average execution time is 10.251 ms and recognition rate is measured as 87~93%.

• Korean Journal of Culture and Social Issue
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• v.27 no.4
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• pp.475-503
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• 2021

The purpose of this study is to clarify the constructs of emotion suppression and help understanding on the multidimensional nature of emotion suppression by classifying constructs for suppression according to the KMW model. Also, this study examined the gender differences of emotion suppression. For this purpose, 657 adult male and female subjects were evaluated for attitude toward emotions, and difficulty in emotional regulation, as well as depression, state anger and daily stress scale. As a result of the exploratory factor analysis on the scales related to the emotion suppression factors, the emotion suppression factors corresponding to each stage of the KMW model were found to be 'distraction against emotional information, 'difficulty in understanding and interpretation of emotions', 'emotion control beliefs', 'vulnerability on emotional expression beliefs'. Next, the study participants were classified by performing a cluster analysis based on each emotion suppression factor. As a result, four clusters were extracted and named 'emotional control belief cluster', 'emotional expression cluster', 'emotional attention failure cluster', and 'general emotional suppression cluster'. As a result of examining the average difference of male depression, depression, state anger, and daily stress for each group, significant differences were found in all dependent variables. As a result of examining whether there is a difference in the frequency of emotional suppression clusters according to gender, the frequency of emotional suppression clusters was high in men, and the ratio of emotional expression clusters was high in women. Finally, it was analyzed whether there was a gender difference in the effect of the emotional suppression cluster on psychosocial adaptation, and the implications were discussed based on the results of this study.

• Journal of KIISE:Software and Applications
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• v.31 no.6
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• pp.799-807
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• 2004

In this paper, we deal with an emotion recognition method using facial images and speech signal. Six basic human emotions including happiness, sadness, anger, surprise, fear and dislike are investigated. Emotion recognition using the facial expression is performed by using a multi-resolution analysis based on the discrete wavelet transform. And then, the feature vectors are extracted from the linear discriminant analysis method. On the other hand, the emotion recognition from speech signal method has a structure of performing the recognition algorithm independently for each wavelet subband and then the final recognition is obtained from a multi-decision making scheme.

• Journal of Korea Multimedia Society
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• v.17 no.12
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• pp.1383-1392
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• 2014

In this paper, we proposed a method to automatically determine the optimal radius through multi-scale LBP operation generalizing the size of radius variation and boosting learning in facial emotion recognition. When we looked at the distribution of features vectors, the most common was $LBP_{8.1}$ of 31% and sum of $LBP_{8.1}$ and $LBP_{8.2}$ was 57.5%, $LBP_{8.3}$, $LBP_{8.4}$, and $LBP_{8.5}$ were respectively 18.5%, 12.0%, and 12.0%. It was found that the patterns of relatively greater radius express characteristics of face well. In case of normal and anger, $LBP_{8.1}$ and $LBP_{8.2}$ were mainly distributed. The distribution of $LBP_{8.3}$ is greater than or equal to the that of $LBP_{8.1}$ in laugh and surprise. It was found that the radius greater than 1 or 2 was useful for a specific emotion recognition. The facial expression recognition rate of proposed multi-scale LBP method was 97.5%. This showed the superiority of proposed method and it was confirmed through various experiments.

• Journal of Oriental Neuropsychiatry
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• v.25 no.3
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• pp.225-234
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• 2014

Objectives: The purpose of this study is to investigate the effects of M&L Self-Growth Meditation Program with Euro QOL-5 Dimension (EQ5D), Five Facet Mindfulness Questionnaire (FFMQ) and psychological test. Methods: 6 middle-age women have participated in the eight weeks of the M&L Self-Growth Meditation Program, and the program was executed once a week for about two hours. We evaluated EQ5D, FFMQ, Beck Depression Inventory (BDI), State-Trait Anxiety Inventory (STAI), and State-Trait Anger Expression Inventory (STAXI) before and after the program in order to analyze the effects of M&L Self-Growth Meditation Program. Results: 1) EQ5D scores increased significantly (p<0.05), and overall physical condition scale( VAS) increased. 2) In the FFQM scores, value of Nonreactivity increased significantly (p<0.05), and total score increased. 3) Scores of BDI and STAI-S decreased significantly (p<0.05), and STAI-T, STAXI-S, STAXI-T, STAXI-O, STAXI-Su, and STAXI-R decreased. Conclusions: The results suggested that M&L Self-Growth Meditation Program improves the quality of life and mindfulness skill and has a positive responses to psychological problems-depression, anxiety, and anger.

• Journal of Oriental Neuropsychiatry
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• v.26 no.2
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• pp.79-88
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• 2015

Objectives: The purpose of this study is to investigate the effects of the M&L Trauma Psychotherapy Program on: Impact of Event Scale - Revised (IES-R-K); Euro QOL-5 Dimension (EQ5D); Five-facet Mindfulness Questionnaire (FFMQ); and psychological tests. Methods: Eight middle-aged women subjected to domestic violence participated in the two-day M&L Trauma Psychotherapy Program. The Program was executed 5 times 2 days for about 3 hours. We evaluated IES-R-K, EQ5D, FFMQ, Beck Depression Inventory (BDI), State-Trait Anxiety Inventory (STAI), State-Trait Anger Expression inventory (STAXI) and SUDS before the Program and for four weeks afterwards, to analyze the effects of the M&L Trauma Psychotherapy Program. Results: The scores of IES-R-K, BDI, STAI-S, STAI-T, Hwa ST and Hwa CT decreased significantly (p<0.05). EQ5D scores increased significantly (p<0.05) and overall physical condition scale (VAS) increased. In the FFMQ scores, all five facet scores increased slightly. Scores of SUDS decreased significantly right after the program, and remained decreased four weeks later, rather than before the Program (p<0.05). Conclusions: The results suggested that the M&L Trauma Psychotherapy Program improved post-traumatic stress, quality of life and mindfulness skills, and had positive responses to psychological problems - depression, anxiety, anger and distress.