• Tribology and Lubricants
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• v.32 no.6
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• pp.207-211
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• 2016

To interpret the perception that originates from tactile sensibility during people touch and recognize the object surfaces, this study focuses on the development of a friction model that can describe the interaction of a stylus pen sliding over the counter surfaces. In addition, the study includes several other experimental factors such as the pressure, temperature, and topology of surface, which can have an effect on the emotional user experience concerning various surfaces; this research aims to suggest a method to quantitatively evaluate the relation between these experimental parameters and emotional user experience. Accordingly, the objective of research comprises the friction characteristic technology for measurement of fine tribological behavior and a standard to quantify the emotional feedback. Existing panels or input devices that provide interaction feedback about user actions simply operate with a single frequency vibration or sound response. On the contrary, this research investigates various interaction characteristics including friction force, frequency, and surface topology synthetically. Using the developed model, which can explain the relation between the friction parameters and emotional user experience, developers can design their product in order to provide the user with expected emotional sensibility. Consequently, it can contribute to reduce the development cost about sensitivity model.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.133-140
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• 2020

Emotional analysis is an application of opinion mining that analyzes opinions and tendencies of people appearing in unstructured text. Recently, emotional analysis of social media has attracted attention, but social media contains newly-created words and slang, so it is not easy to analyze with existing emotional analysis. In this study, I design a new emotional analysis system to solve these problems. The proposed system is possible to analyze various emotions as well as positive and negative in social media including newly-created words and slang. First, I collect newly-created words and slang related to emotions that appear in social media. Then, expand the existing emotional model and use it to quantify the degree of sentiment in emotional words. Also, a new sentiment dictionary is constructed by reflecting the degree of sentiment. Finally, I design an emotional analysis system that applies an sentiment dictionary that includes newly-created words and an extended emotional model.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.2
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• pp.185-190
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• 2015

The purpose of this study is developing the quantify the seat belt pulling Noise index and evaluation method. This paper presents the objective method to evaluate the emotional feeling about the pulling Noise of the seat belt. The physical quantification is required to objectively evaluate the emotional feeling of the pulling Noise. This is called the "Noise metric." The Noise metric is should correlated to the subjective rating of the pulling Noise. The pulling Noise index is developed throughout the linear regression of the Noise metric and the subjective rating. The developed index is used for the objective evaluation of the emotional feeling about the pulling Noise of a seat belt throughout the modification of seat belt components.

• Cartoon and Animation Studies
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• s.39
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• pp.393-412
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• 2015

See and feel the emotion recognition is the image of a person variously changed according to the environment, personal disposition. Thus, the image recognition has been focused on the emotional sensibilities computer you want to control the number studies. However, existing emotional computing model is numbered and the objective is clearly insufficient measurement conditions. Thus, through quantifiable image Emotion Recognition and emotion computing, is a study of the situation requires an objective assessment scheme. In this paper, the sensitivity was represented by numbered sizes quantified according to the image recognition calculation emotion. So apply the principal attributes of the color image emotion recognition as a configuration parameter. In addition, in calculating the color sensitivity by applying a digital computing focused research. Image color emotion computing research approach is the color of emotion attribute, brightness, and saturation reflects the weighted according to importance to the emotional scores. And free-degree by applying the sensitivity point to the image sensitivity formula (X), the tone (Y-axis) is calculated as a number system. There pleasure degree (X-axis), the tension and position the position of the image point that the sensitivity of the emotional coordinate crossing (Y-axis). Image color coordinates by applying the core emotional effect of Russell (Core Affect) is based on the 16 main representatives emotion. Thus, the image recognition sensitivity and compares the number size. Depending on the magnitude of the sensitivity scores demonstrate this sensitivity must change. Compare the way the images are divided up the top five of emotion recognition emotion emotions associated with 16 representatives, and representatives analyzed the concentrated emotion sizes. Future studies are needed emotional computing method of calculation to be more similar sensibility and human emotion recognition.

• The Journal of the Korea Contents Association
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• v.16 no.12
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• pp.327-345
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• 2016

The purpose of this study was to carry out cognitive movement therapy program for children with affective and behavioral disorder based on neuro science, psychology, motor learning, muscle physiology, biomechanics, human motion analysis, movement control and to quantify characteristic of expression and gestures according to change of facial expression by emotional change. We could observe problematic expression of children with affective disorder, and could estimate the efficiency of application of movement therapy program by the face expression change of children with affective disorder. And it could be expected to accumulate data for early detection and therapy process of development disorder applying converged measurement and analytic method for human development by quantification of emotion and behavior therapy analysis, kinematic analysis. Therefore, the result of this study could be extendedly applied to the disabled, the elderly and the sick as well as children.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.4
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• pp.421-430
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• 2006

This paper explores a new methodology of socio-statistical survey to classify environmental perception characteristics and to quantify atmospheric environmental sensitivity of neighboring people around a large industrial complex. In order to compensate intrinsic inclination against environmental problems, Atmospheric Environmental Sensitivity Index (AESI) is proposed as the weighted-summation of four representative questions asking the current status of the local air quality, which are chosen by the factor analysis of questionnaire. Atmospheric environmental perception is tried to be classified into interest/indifference characteristics and rational/emotional perception on environmental issues, positive/negative opinion on the solution of environmental problems. According to the chi-square cross-correlation and two-way layout analyses, it was clearly shown that environmental perception is categorized into two major groups, i.e., the positive-rational group having lower AESI and the negative-emotional group having higher AESI which means more seriously senses the status of local air quality.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.455-458
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• 1997

We are exposed to the various external stimuli input from the environment, which cause emotional changes based on the characteristics of the stimuli. Unfortunately, there are no quantitative results on relationship between human sensibility and the characteristics of physiological signals. The objective of this study was to quantify EEG signals evoked by visual stimulation based on the assumption that the analysis of the variability on the characteristics of the EEG waveform may provide the significant information regarding changes in psychological states of the subject. Seven university students were participated in this study. The experiment was devised with eleven experimental conditions, which are control and ten different types of visual stimulation based on IAPS (International Affective Picture Systems). Wavelet transformation was employed to analyze the EEG signals. Most positive and negative emotional response were compared in pairs. The results showed that the reconstructed signals at the decomposition level revealed the different energy value on the EEG signals. Also, general patterns of EEG signals in rest state compare with positive and negative stimulus were found. This study could be extended to establish an algorithm which distinguishes psychophysiological states of the subjects exposed to the visual stimulation.

• Proceedings of the ESK Conference
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• 1997.10a
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• pp.477-481
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• 1997

We are exposed to the various external stimuli input from the environment, which cause emotional changes based on the characteristics of the stimuli. Unfortunately, there are noquantitative results on relationship between human sensibility and the characteristics of physiological signals. The objective of this study was to quantify EEG signals evoked by visual stimulation based on the assumption that the analysis of the variability on the characteristics of the EEG waveform may provide the significant information regarding changes in psychological states of the subject. Seven university students were participated in this study. The experiment was devised with eleven experimental conditions, which are control and ten different types of visual stimulation based on IAPS(International Affective Picture Systems). Seven subjects were used to obtain EEGs while introducing visual stimulation. Wavelet transformation was employed to analyze the EEG signals. Most Positive and negative emotional response were pairely compared. The results showed that the reconstructed signals at the decomposition level revealed the different energy value on the EEG signals. Also, general patterns of EEG signals in rest state compare with negative and positive stimulus were found. This study could be extended to estabish an algorithm which distinguishes psychophysiological states of the subjects exposed to the visual stimulation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.166-175
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• 2017

This study examined children from two families exposed to domestic violence and had psychological counseling in July 2017 at KOVA, a support organization for crime victims. The subjects were exposed to family violence in excess of 10 years and was protected by the shelter with their mothers who had filed complaints with the local police. Victims of domestic violence often face difficulty in avoiding the source of aggression, and thus experience repetitive attacks. This research was conducted at the Buddhism Brain Research Facility, Seoul University, to identify and quantify the emotional characteristics of the affected children in which it is difficult to escape from their living conditions. Data was collected by BrainMaster, a 19-channel examination kit, and analyzed by NeuroGuide. As a result of analyzing the emotional characteristics of the affected children through Quantitative EEG and brain topographical map, we found an increase of slow wave and problems with abnormality of Alpha, High Beta in the left and right Frontal area asymmetry.

• Cartoon and Animation Studies
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• s.40
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• pp.477-496
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• 2015

Emotional awareness is the image of a person is represented by different tendencies. Currently, the emotion computing to objectively evaluate the emotion recognition research is being actively studied. However, existing emotional computing research has many problems to run. First, the non-objective in emotion recognition if it is inaccurate. Second, the correlation between the emotion recognition is unclear points. So to test the regularity of image sensitivity to the need of the present study is to control emotions in the computing system. In addition, the screen number of the emotion recognized for the purpose of this study, applying the method of objective image emotional computing system and compared with a similar degree of emotion of the person. The key features of the image emotional computing system calculates the emotion recognized as numbered digital form. And to study the background of emotion computing is a key advantage of the effect of the James A. Russell for digitization of emotion (Core Affect). Pleasure emotions about the core axis (X axis) of pleasure and displeasure, tension (Y-axis) axis of tension and relaxation of emotion, emotion is applied to the computing research. Emotional axis with associated representative sensibility very happy, excited, elated, happy, contentment, calm, relaxing, quiet, tired, helpless, depressed, sad, angry, stress, anxiety, pieces 16 of tense emotional separated by a sensibility ComputingIt applies. Course of the present study is to use the color of the color key elements of the image computing formula sensitivity, brightness, and saturation applied to the sensitivity property elements. Property and calculating the rate sensitivity factors are applied to the importance weight, measured by free-level sensitivity score (X-axis) and the tension (Y-axis). Emotion won again expanded on the basis of emotion crossed point, and included a representative selection in Sensibility size of the top five ranking representative of the main emotion. In addition, measuring the emotional image of a person with 16 representative emotional score, and separated by a representative of the top five senses. Compare the main representative of the main representatives of Emotion and Sensibility people aware of the sensitivity of the results to verify the similarity degree computing emotion emotional emotions depending on the number of representative matches. The emotional similarity computing results represent the average concordance rate of major sensitivity was 51%, representing 2.5 sensibilities were consistent with the person's emotion recognition. Similar measures were the degree of emotion computing calculation and emotion recognition in this study who were given the objective criteria of the sensitivity calculation. Future research will need to be maintained weight room and the study of the emotional equation of a higher concordance rate improved.