• 대한한의학원전학회지
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• 제25권1호
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• pp.51-68
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• 2012

Objective : This paper is aimed at suggesting further tasks by checking and rectifying the errors of the ancieut Chinese-vernacular Korean translations of Park Ji-won(朴趾源)'s "Kumryosocho". Method : In order to correct the wrongly transcribed "Kumryosocho" was contrasted with the original "Xiangzubiji(香祖筆記)", of which the part is "Kumryosocho". And then the errors and mistakes are discovered in published ancient Chinese-to-vernacular Korean translations. Result : In the course of checking the existing translations of "Kumryosocho", this paper identified the following types of errors. 1. Errors attributable to unfamiliar names of medicinal herbs 2. Errors due to the unfamiliarity with the names of diseases or symptoms in Traditional Koreau Medicine(TKM). 3. Errors committed in hand transcription. These types of errors were committed as well in translating jargons routinely used in TKM books. To the surprise, the errors above have been repeated even in the latest version of its translation. This means that the medicine-related materials by Silhak scholars, including "Kumryosocho", were placed at a dead zone of the research between Chinese classic scholars and TKM scholars. Conclusion : To minimize errors and mistakes, it is needed to activate the cooperative work of heterogeneous experts in two academic fields.

• 한국지능시스템학회논문지
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• 제13권6호
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• pp.710-715
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• 2003

본 논문에서는 사람의 식별과 감정을 인식하기 위한 새로운 방법을 제안한다. 제안된 방법은 색차 정보에 의한 형판의 위치 인식과 형판 벡터 추출에 기반 한다. 단일 색차 공간만을 이용할 경우 피부색 영역을 정확히 추출하기 힘들다. 이를 보완하기 위해서 여러 가지 색차 공간을 병행하여 피부색 영역을 추출하며, 이를 응용하여 각각의 형판을 추출하는 방법을 제안한다. 그리고, 사람의 식별과 감정 인식을 위해서 추출된 형판에 대한 각각의 특징 벡터를 신경회로망을 이용하여 학습하여 사용한다. 마지막으로, 제안된 방법은 실제 실험을 통하여 그 가능성을 보인다.

• ETRI Journal
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• 제37권6호
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• pp.1231-1241
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• 2015

In this study, we investigate the relationship between emotions and the physiological responses, with emotion recognition, using the proposed fuzzy information granulation-based neural network (FIGNN) for boredom, pain, and surprise emotions. For an analysis of the physiological responses, three emotions are induced through emotional stimuli, and the physiological signals are obtained from the evoked emotions. To recognize the emotions, we design an FIGNN recognizer and deal with the feature selection through an analysis of the physiological signals. The proposed method is accomplished in premise, consequence, and aggregation design phases. The premise phase takes information granulation using fuzzy c-means clustering, the consequence phase adopts a polynomial function, and the aggregation phase resorts to a general fuzzy inference. Experiments show that a suitable methodology and a substantial reduction of the feature space can be accomplished, and that the proposed FIGNN has a high recognition accuracy for the three emotions using physiological signals.

• 한국CDE학회논문집
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• 제19권4호
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• pp.443-454
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• 2014

In this paper, an intuitive emotional expression of the 3D avatar is presented. Using the motion selection control of 3D avatar, an easy-to-use communication which is more intuitive than emoticon is possible. 12 pieces different emotions of avatar are classified as positive emotions such as cheers, impressive, joy, welcoming, fun, pleasure and negative emotions of anger, jealousy, wrath, frustration, sadness, loneliness. The combination of lower body motion is used to represent additional emotions of amusing, joyous, surprise, enthusiasm, glad, excite, sulk, discomfort, irritation, embarrassment, anxiety, sorrow. In order to get the realistic human posture, BVH format of motion capture data are used and the synthesis of BVH file data are implemented by applying the proposed emotional expression rules of the 3D avatar.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권1호
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• pp.27-32
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• 2006

Verbal communication is the most commonly used mean of communication. A spoken word carries a lot of informations about speakers and their emotional states. In this paper we designed a model to recognize emotional states in a speech, a first phase of two phases in developing a toy machine that recognizes emotional states in a speech. We conducted an experiment to extract and analyse the emotional state of a speaker in relation with speech. To analyse the signal output we referred to three characteristics of sound as vector inputs and they are the followings: frequency, intensity, and period of tones. Also we made use of eight basic emotional parameters: surprise, anger, sadness, expectancy, acceptance, joy, hate, and fear which were portrayed by five selected students. In order to facilitate the differentiation of each spectrum features, we used the wavelet transform analysis. We applied ANFIS (Adaptive Neuro Fuzzy Inference System) in designing an emotion recognition model from a speech. In our findings, inference error was about 10%. The result of our experiment reveals that about 85% of the model applied is effective and reliable.

• 천문학회보
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• 제39권1호
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• pp.29-29
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• 2014

A fundamental problem in space physics is to explain the origin of energetic charged particles in space close to the Earth and the significant temporal variations of their flux. The particles are primarily electrons and protons although energetic heavy ions such as O+ are sometimes non-negligible. By "energetic" we mean a rather broad energy range of particles from a few tens of keV to well above MeV. Drastic variations of the particle fluxes (by >3 orders of magnitude) occur over both a short time scale like a few minutes and a long time scale like the 11-year sunspot cycle. In this talk I will focus on relativistic energy electrons (~MeV) trapped within the Earth's magnetosphere. They are a primary element of the space weather since they can cause damage to satellites, so often called "killer electrons". Considering that the source particles in both the solar wind and the ionosphere are relatively cold (~eV), the quasi-permanent existence of these very energetic particles close to the Earth has been a surprise to space physicists for decades. Complex electromagnetic processes such as wave-particle interactions within the magnetosphere are believed to play a major role in generating these killer electrons. While detailed physics remains an active research area, for this lecture I will introduce a synthesized picture of how solar activities are related to wave-particle interaction physics inside the magnetosphere. This can be applied to other astrophysical systems.

• 한국지능시스템학회논문지
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• 제13권3호
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• pp.371-376
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• 2003

본 논문에서는 효과적인 정보를 표현하는 Independent Component Analysis(ICA)-factorial 표현방법을 이용하여 얼굴감정 인식을 수행한다. 얼굴감정인식은 두 단계인 특징추출 과정과 인식과정에 의해 이루어진다. 먼저 특징추출방법은 주성분 분석(Principal Component Analysis)을 이용하여 얼굴영상의 고차원 공간을 저차원 특징공간으로 변환한 후 ICA-factorial 표현방법을 통해 좀 더 효과적으로 특징벡터를 추출한다. 인식단계는 최소거리 분류방법인 유클리디안 거리에 근거한 K-Nearest Neighbor 알고리즘으로 얼굴감정을 인식한다. 6개의 기본감정(기쁨, 슬픔, 화남, 놀람, 공포, 혐오)에 대해 얼굴 감정 데이터베이스를 구축하고 실험해본 결과 기존의 방법보다 좋은 인식 성능을 얻었다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권2호
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• pp.105-110
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• 2008

Human being recognizes emotion fusing information of the other speech signal, expression, gesture and bio-signal. Computer needs technologies that being recognized as human do using combined information. In this paper, we recognized five emotions (normal, happiness, anger, surprise, sadness) through speech signal and facial image, and we propose to method that fusing into emotion for emotion recognition result is applying to multimodal method. Speech signal and facial image does emotion recognition using Principal Component Analysis (PCA) method. And multimodal is fusing into emotion result applying fuzzy membership function. With our experiments, our average emotion recognition rate was 63% by using speech signals, and was 53.4% by using facial images. That is, we know that speech signal offers a better emotion recognition rate than the facial image. We proposed decision fusion method using S-type membership function to heighten the emotion recognition rate. Result of emotion recognition through proposed method, average recognized rate is 70.4%. We could know that decision fusion method offers a better emotion recognition rate than the facial image or speech signal.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2036-2038
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• 2001

In this paper, we propose the neural network based emotion recognition method for intelligently recognizing the human's emotion using vision system. In the proposed method, human's emotion is divided into four emotion (surprise, anger, happiness, sadness). Also, we use R,G,B(red, green, blue) color image data and the gray image data to get the highly trust rate of feature point extraction. For this, we propose an algorithm to extract four feature points (eyebrow, eye, nose, mouth) from the face image acquired by the color CCD camera and find some feature vectors from those. And then we apply back-prapagation algorithm to the secondary feature vector(position and distance among the feature points). Finally, we show the practical application possibility of the proposed method.

• 보건의료산업학회지
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• 제7권1호
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• pp.133-144
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• 2013

The present study is aimed at assessing medical service quality as perceived by in-patients of geriatric hospitals and at analyzing the excitement factors by using revised IPA Applying the Kano's model for users' satisfaction. The data was collected from Nov. 5 to Dec. 7, 2012. Among a total of 503 cases of questionaries, only 419 cases were used. To data were analyzed by PASW statistics 18.0 and revised IPA applying Kano's model. The paired t-test results reveal that satisfaction was higher than the expectation level at a statistically significant level across all the medical service quality factors. The revised IPA results categorized facility convenience, hospitalization and care, and kindness as basic factors and medical reliability and access as excitement factors. In conclusion, medical reliability and access, which were identified as excitement factors of medical service quality, are essential opportunity factors for users and should accordingly be used as strategic factors to increase satisfaction with a geriatric hospital and induce customer surprise.