• Journal of KIISE:Software and Applications
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• v.37 no.10
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• pp.779-787
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• 2010

Since robots have been used widely recently, research about human-robot communication is in process actively. Typically, natural language processing or gesture generation have been applied to human-robot interaction. However, existing methods for communication among robot and human have their limits in performing only static communication, thus the method for more natural and realistic interaction is required. In this paper, an emotional gesture based dialogue management system is proposed for sophisticated human-robot communication. The proposed system performs communication by using the Bayesian networks and pattern matching, and generates emotional gestures of robots in real-time while the user communicates with the robot. Through emotional gestures robot can communicate the user more efficiently also realistically. We used behavior networks as the gesture generation method to deal with dialogue situations which change dynamically. Finally, we designed a usability test to confirm the usefulness of the proposed system by comparing with the existing dialogue system.

• The Journal of the Acoustical Society of Korea
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• v.25 no.6
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• pp.269-276
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• 2006

In this paper, we propose an emotion recognition system that can discriminate human emotional state into neutral or anger from the speech captured by a cellular-phone in real time. In general. the speech through the mobile network contains environment noise and network noise, thus it can causes serious System performance degradation due to the distortion in emotional features of the query speech. In order to minimize the effect of these noise and so improve the system performance, we adopt a simple MA (Moving Average) filter which has relatively simple structure and low computational complexity, to alleviate the distortion in the emotional feature vector. Then a SFS (Sequential Forward Selection) feature optimization method is implemented to further improve and stabilize the system performance. Two pattern recognition method such as k-NN and SVM is compared for emotional state classification. The experimental results indicate that the proposed method provides very stable and successful emotional classification performance such as 86.5%. so that it will be very useful in application areas such as customer call-center.

• Fashion & Textile Research Journal
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• v.21 no.4
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• pp.390-400
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• 2019

A major factor in making current hospital gowns is how to manage patients from the standpoint of hospitals. This shows that hospital gowns have not been considered as an apparel for a specific purpose with a design that considers the psychological composure of patients. This study, along with a meticulous analysis of the pattern design of domestic hospital gown suggests a design philosophy that can be of emotional help to patients. The analysis of hospital gowns in terms of motif is that the corporate identity of the hospital in question, along with the lettering symbolizing the hospital is conspicuous. The motif shown in the pattern also has a brightness contrast and two-way pattern. This study suggests hospital gown patterns as follows. First, on the basis of color dynamics, utilize repetition arrangement, camaieu arrangement and faux camaieu arrangement. Second, make use of warm colors in order to enhance trust between patients and medical staff. Last, use green color as a dominant color for the hospital to be felt of as a convenient space. Utilizing these three factors in the future design of hospital gowns will assist in the development of new hospital gowns that render a psychological composure.

• Journal of Korean Academy of Nursing
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• v.29 no.1
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• pp.61-71
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• 1999

Sleep is a necessity for survival. Disruption of sleep leads to numerous adverse physiological and psychological consequences. These could be particularly undesirable for older patients, who are subject to many additional factors. But there is limited research related to hospitalized elderly in Korea. The purpose of the study is to explore sleep patterns and disturbing factors of before and after hospitalization, in order to present basic information regarding elderly sleep to develop nursing intervention. The sample consisted of 32 elderly men and women between the ages of n and 87 years. Data collection was done from September to November 1997. Measures of sleep patterns and related factors were obtained from self-reported sleep questionnaires. Analysis of data was done by use of t-test, paired t-test, ANOVA, and Pearson Correlation Coefficient. The results of this study were summarized as follows : 1. In comparision between before and after admission of their sleep pattern, “sleep onset” tends to be delayed and nocturnal sleep time was significantly reduced. So, hospitalized elderly reported less total sleep time than before admission. 2. Regarding the sleep disturbing factors, medication(hypnotics ; 37.5%), physiological factor (snoring ; 59.4%) environmental factor (pillow ; 78.1%), emotional factor(anxiety related to disease ; 37.5%), and illness factor(fatigue ; 34.7%) were reported. 3. Significant differences in gender were found. Men had more disturbances in sleep than women owing to difficulty in falling a sleep and lack of nocturnal sleep. Women consumed more sleep inducing drugs. Significant increase was reported in napping during the day with increasing age. 4. Significant differences between good sleepers and poor sleepers were found for the following variables : nocturnal sleep time, total sleep time, bed time, sleep onset latency time, sleep latency time after nocturnal awakening, time spent in bed upon arousal, environmental factors, and emotional factors. In conclusion, it was found that the quantity and quality of sleep were significantly altered in hospitalized elderly, but adequate strategies for better sleep were not practiced. Further research is needed to develop Intervention strategies to promote sleep and to prevent sleep problems.

• Fashion & Textile Research Journal
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• v.15 no.3
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• pp.347-357
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• 2013

The nursery active-wear uniform designs of Internet shopping malls are simple and similar; however, the latest children's wear trends (mostly composed of training jumpers and pants) do not reflect these qualities. Children's folklore plays (widely used in child education) have an instructive value for the emotional and intellectual development of a child. Nursery active-wear uniform designs applied to children's folklore's plays could be positive for the emotional development and specialized cultural education of children. We designed three nursery active-wear uniforms with three different design concepts (casual, semi-formal and sporty) regardless of sex. The main color of the three nursery active-wear uniforms was yellow. We used three different chroma and values of yellow through three design concepts: Design I of a nursery active-wear uniform (a training suit style with a good activity), Design II of a nursery active-wear uniform (a semi suit style), and Design III of a nursery active-wear uniform (a sportswear style that reflected a sport wear trend). We expressed children's folklore plays in the pattern of a nursery active-wear uniform. The pattern was characterized as a pair of bears flying kites. This pattern was utilized in three nursery active-wear uniforms with the logo and name of the nursery. We modified the designs of active-wear nursery uniforms based on an evaluation of 33 special panels. We made three nursery active-wear uniforms for five-year olds.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.366-369
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• 2000

This paper examines three algorithms to recognize speaker's emotion using the speech signals. Target emotions are happiness, sadness, anger, fear, boredom and neutral state. MLB(Maximum-Likeligood Bayes), NN(Nearest Neighbor) and HMM (Hidden Markov Model) algorithms are used as the pattern matching techniques. In all cases, pitch and energy are used as the features. The feature vectors for MLB and NN are composed of pitch mean, pitch standard deviation, energy mean, energy standard deviation, etc. For HMM, vectors of delta pitch with delta-delta pitch and delta energy with delta-delta energy are used. We recorded a corpus of emotional speech data and performed the subjective evaluation for the data. The subjective recognition result was 56% and was compared with the classifiers' recognition rates. MLB, NN, and HMM classifiers achieved recognition rates of 68.9%, 69.3% and 89.1% respectively, for the speaker dependent, and context-independent classification.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.214-216
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• 2006

Expressive face and human body gestures are among the main non-verbal communication channels in human-human interaction. Understanding human emotions through body gesture is one of the necessary skills both for humans and also for the computers to interact with their human counterparts. Gesture analysis is consisted of several processes such as detecting of hand, extracting feature, and recognizing emotions. Skin color information for tracking hand gesture is obtained from face detection region. We have revealed relationships between paricular body movements and specific emotions by using HMM(Hidden Markov Model) classifier. Performance evaluation of emotional human body recognition has experimented.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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• pp.754-759
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• 2007

In this paper, we proposed the Bi-Modal Sensor Fusion Algorithm which is the emotional recognition method that be able to classify 4 emotions (Happy, Sad, Angry, Surprise) by using facial image and speech signal together. We extract the feature vectors from speech signal using acoustic feature without language feature and classify emotional pattern using Neural-Network. We also make the feature selection of mouth, eyes and eyebrows from facial image. and extracted feature vectors that apply to Principal Component Analysis(PCA) remakes low dimension feature vector. So we proposed method to fused into result value of emotion recognition by using facial image and speech.

• Korea Journal of Hospital Management
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• v.15 no.3
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• pp.17-32
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• 2010

The purpose of this study is to analyze the influence of DISC behavior pattern, stress-managing method, and the stress level on job attitude of hospital Employees, and to provide suggestions for effective human resources management in hospital settings. First, the research suggested emotional or aversive stress-managing method had significant influence to the stress level, whereas DISC behavior patterns did not. Second, to the job satisfaction, Influence, Compliance and Steadiness of DISC behavior patterns, challenging or aversive stress-managing method, and the stress level showed immediate meaningful effect. Third, for the system immersion, challenging or emotional ress-managing method as well as the job satisfaction showed direct influence. Especially, the challenging method had not only a direct but an indirect effect through mediating job satisfaction.

• Journal of Korean Medicine for Obesity Research
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• v.8 no.2
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• pp.63-72
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• 2008

Objectives We aimed to explore obesity pattern among overweight and obese Korean adult women using oriental obesity pattern identification questionnaire. Methods This survey was performed using data of 83 overweight and obese women aged from 20 to 55 yrs (BMI ${\geq}\;23\;kg/m^2$ : n=18, BMI ${\geq}\;25\;kg/m^2$ :ｎ=65) in Seoul, from 2007 to 2008. Subjects were given written consent and this study was performed under the permission of institutional review board of Kyung-Hee East-west Neo Medical Center. Results 1. The distribution of oriental obesity pattern identification did not show any differences between obese and overweight group(p>0.05). 2. The ratio of significantly-scored oriental pattern identification was ordered by Stagnation of the liver Qi(肝欝, 21.7%) > Indigestion(食積, 18.1%) > Spleen deficiency(脾虚, 16.9%) > Yang deficiency(陽虚, 14.5%) (n=83). 3. The frequency of top-scored oriental obesity pattern was ordered by Stagnation of the liver Qi(肝欝, 36.1%) > Indigestion(食積, 24.1%) > Yang deficiency (陽虚, 15.7%) (n=83). 4. The frequency of oriental obesity pattern identification was ordered by Stagnation of the liver Qi(肝欝, 41.7%) > Indigestion(食積, 29.2%) > Yang deficiency(陽虚, 12.5%) > Stagnation of the liver Qi and Yang deficiency(肝欝兼陽虚, 8.3%) (n=24). Conclusions In Korean adult overweight and obese women, Stagnation of the liver Qi(肝欝), Indigestion(食積), and Yang deficiency (陽虚) were found to be the main pathology based on oriental obesity pattern identification questionnaire. It suggests that not only physical status but also general condition and emotional problem should be concerned in treatment of obesity. This study could play a role as a preliminary data of oriental obesity pattern identification.