• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1998.11a
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• pp.189-194
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• 1998

Design factors are very important and deterministic in determining the first impression of products and environment. The final 30 number of channel button were chosen as a design factors at the Audio Unit. Then, we made the 8 types of prototype. with combining the design factors for experiment. Subjects rated the SD(Semantic Differential) evaluation sheets which have the 30 adjectives after watching each prototype. With the evaluated values, we simulated to identify the relation between the design factors and the adjectives using Neural Network. As a results, we could abstract the affective adjectives on each 8 types. Therefore, this research suggested the possibilities that we can infer the optimal design factors and types using Neural Network, if adjectives were given.

• Educational Technology International
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• v.8 no.1
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• pp.17-39
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• 2007

The purpose of this study was to identify the relationships among organizational commitment, job satisfaction, and learning organization culture. This study was conducted in five sub-organizations of one Korean conglomerate company. One thousand employees were randomly and proportionately selected, with 669 useable cases obtained, for a response rate of 67%. The organizational commitment instrument used from the "affective, continuance, and normative commitment" scale (ACNCS) of Allen and Meyer (1990). The "Dimensions of Learning Organization Questionnaire" of Watkins and Marsick (1997) was used to measure learning organization culture. The short form MSQ (Minnesota Satisfaction Questionnaire), developed by Weiss, Dawis, England, and Lofquist (1967), was the third instrument used. Descriptive statistics, correlational statistics, and inferential statistics (ANOVA and t-tests) were used. Organizational commitment (except for continuance) is moderately and positively related to job satisfaction and moderately and positively related to learning organization culture. In addition, learning organization culture is weakly to moderately and positively related to job satisfaction. No differences by age were found. Four-year college graduates are more likely to have higher creating continuous learning opportunities in learning organization culture than graduate school degree holders. Males are likely to have higher affective and continuance organizational commitment than females. Employees working in R&D, Engineering, and Manufacturing (REM) are likely to have higher continuance organizational commitment than do other types of jobs. Employees are more likely to have higher learning organization culture and job satisfaction than assistant managers. Assistant managers have higher continuance organizational commitment than managers. Managers generally have higher organizational commitment, learning organization culture, job satisfaction than assistant managers. They also have higher learning organization culture than employees. Employees who had worked for less than four years in their current job and organization have higher promoting inquiry and dialogue in learning organization culture than those who have worked for ten years or more. Employees in the insurance organization have higher affective organizational commitment, learning organization culture, and job satisfaction than those of the other organizations. Finally, employees of the electronic company have higher continuance organizational commitment in learning organization culture than those of other companies. In summary, this research enables CEOs and HRD and HRM practitioners to view organizational commitment, learning organization culture, and job satisfaction as important variables in exploring diverse ranges of topics related to the workplace. And then, they can diversely apply their management, interventions and practices to fit these diverse characteristics.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.555-558
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• 2006

감정을 포함하고 있는 음성은 청자로 하여금 화자의 심리상태를 파악할 수 있게 하는 요소 중에 하나이다. 음성신호에 포함되어 있는 감정을 인식하여 사람과 로봇과의 원활한 감성적 상호작용을 위하여 특징을 추출하고 감정을 분류한 방법을 제시한다. 음성신호로부터 음향정보 및 운율정보인 기본 특징들을 추출하고 이로부터 계산된 통계치를 갖는 특징벡터를 입력으로 support vector machine (SVM) 기반의 패턴분류기를 사용하여 6가지의 감정- 화남(angry), 지루함(bored), 기쁨(happy), 중립(neutral), 슬픔(sad) 그리고 놀람(surprised)으로 분류한다. SVM에 의한 인식실험을 한 경우 51.4%의 인식률을 보였고 사람의 판단에 의한 경우는 60.4%의 인식률을 보였다. 또한 화자가 판단한 감정 데이터베이스의 감정들을 다수의 청자가 판단한 감정 상태로 변경한 입력을 SVM에 의해서 감정을 분류한 결과가 51.2% 정확도로 감정인식하기 위해 사용한 기본 특징들이 유효함을 알 수 있다.

• Journal of the Korea Safety Management & Science
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• v.18 no.2
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• pp.65-71
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• 2016

This study was aimed to demonstrate how the analysis of the impact on confidence in the safety-conscious organizations target the clothing distribution center employees and organizational commitment. Safety awareness of employees of the clothing distribution center safety rules, safety education, road safety interests, divided into risk handling and trusted organization with the emotional trust and cognitive trust, organizational commitment was divided into affective, cognitive and normative commitment. Data collection was surveyed 185 people clothing distribution center workers, tested the hypothesis through regression analysis. The results are safety conscious exerts a positive effect on organizational trust, organizational trust was found to have a positive impact on organizational commitment.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.821-823
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• 2016

본 논문은 다차원 정서모델 기반 영상, 음성, 뇌파를 이용한 멀티모달 복합 감정인식 시스템을 제안한다. 사용자의 얼굴 영상, 목소리 및 뇌파를 기반으로 각각 추출된 특징을 심리학 및 인지과학 분야에서 인간의 감정을 구성하는 정서적 감응요소로 알려진 다차원 정서모델(Arousal, Valence, Dominance)에 대한 명시적 감응 정도 데이터로 대응하여 스코어링(Scoring)을 수행한다. 이후, 스코어링을 통해 나온 결과 값을 이용하여 다차원으로 구성되는 3차원 감정 모델에 매핑하여 인간의 감정(단일감정, 복합감정)뿐만 아니라 감정의 세기까지 인식한다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.203-210
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• 1999

We report on some of the preliminary results of the physiological responses resulting from vehicular speed changes. Healthy human subjects (n=5) were studied for the experiments. We measured the physiological responses of the subjects such as Heart Rate Variability (HRV), Galvanic Skin Response (GSR), and skin temperature for day and night vehicular speed change experiments, respectively. Before and after the tasks, we carried out a self-report for acquiring correlation with experiment results. Mean heart rate variability (HRV) and amplitude of GSR and skin temperature were calculated for 3 minutes duration in each state. The analysis of the physiological measures of ANS activity revealed that vehicle speed change-based affective state evoked arousal response pattern featured by HR acceleration, decrease of skin temperature, and increase of GSR amplitude. The obtained results show that despite some differences observed between each state, overall physiological responses show that the activity of the sympathetic nervous system increases as a result of the increase of speed.

• Journal of the Ergonomics Society of Korea
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• v.14 no.2
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• pp.63-73
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• 1995

An approach to quantitative evaluation of product usability during the design and implementation phases of the product life cycle is presented. The evaluation starts by defining a set of usability characteristics, viz. physical, cognitive and affective characteristic. Each of these characteristics is assessed by a set of usability criteria, such as functionality, visual clarity, learmability, etc. The usability criterion is then evaluated by a checklist consisting of a detailed questionnaire. The fuzzy weighted-checklist method with linguistic variables is used for quantitative analysis. Also, the method for quantifying usability improve- ments in iterative design processes is considered. This analysis procides a quantit- ative measure, which reflects the degree of excellence of product usability during the design and development phases.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.821-827
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• 2018

Affective computing has gained increasing interest in the recent years with the development of potential applications in Human computer interaction (HCI) and healthcare. Although momentous research has been done on human emotion recognition, however, in comparison to speech and facial expression less attention has been paid to physiological signals. In this paper, Electroencephalogram (EEG) signals from different brain regions were investigated using modified wavelet energy features. For minimization of redundancy and maximization of relevancy among features, mRMR algorithm was deployed significantly. EEG recordings of a publically available "DEAP" database have been used to classify four classes of emotions with Multi class Support Vector Machine. The proposed approach shows significant performance compared to existing algorithms.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.316-322
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• 2014

A movie recommendation system is proposed to learn a preference model of a viewer by using multimodal features of a video content and their evoked implicit responses of the viewer in synchronized manner. In this system, facial expression, body posture, and physiological signals are measured to estimate the affective states of the viewer, in accordance with the stimuli consisting of low-level and affective features from video, audio, and text streams. Experimental results show that it is possible to predict arousal response, which is measured by electrodermal activity, of a viewer from auditory and text features in a video stimuli, for estimating interestingness on the video.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.901-904
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• 2007

Nowadays, in many fields of medical treatment, we can make an observation and a diagnosis of inward disease without using a surgical operation. As one of them, ultra-sound diagnosis system can be available widely in its cost and size compared with other medical instruments. This system also make it possible for us to see the inner parts of the body in real time harmlessly for a long time. So it can be utilized to inspect the movement of heart or fetus and to diagnose an internal disease of the soft tissues. Ultra-sound images can be generated by the reflexive and scattered wave through the pulse generator and so in ultrasound images there exist inherently many affective noised signals. In this paper, we are to take an noise-restrained image and to extract a more affective regions of the images.