• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1998.04a
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• pp.304-308
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• 1998

Technical advances in computer networks and the Internet bring a new communication era and provide effective solutions for cooperative works and research. These technological advances introduced the concept of cyberspace that many people involve reseach and a project at different locations at the same time. In this paper, we present a fast and effective interaction protocol that is aeapted to the COLAB(COIIaborative LABoratory) Systems which use a high-speed ATM Network. The CCOLAB systems is developed for researchers those who are doing a large project on the collaborative research environment. The interaction protocol that we developed supports multi-session and multi-channel on the TCP/IP Network and provides more flexible solution to control multimedia data on the network.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.65-70
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• 2020

CNN's technologies that represent emotional detection include primitive CNN algorithms, deployment normalization, and drop-off. We present the methods and data of the three experiments in this paper. The training database and the test database are set up differently. The first experiment is to extract emotions using Batch Normalization, which complemented the shortcomings of distribution. The second experiment is to extract emotions using Dropout, which is used for rapid computation. The third experiment uses CNN using convolution and maxpooling. All three results show a low detection rate, To supplement these problems, We will develop a deep learning algorithm using feature extraction method specialized in image processing field.

• Journal of Korean Society of Transportation
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• v.31 no.6
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• pp.34-42
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• 2013

The reasons of traffic accidents can be classified into the vehicle, road environment and human factors. In development of vehicle and road technologies, the human factor is the most important. The emotion research recently carried out showed that emotions play an important role in human judgment and decision making. They are also expected to partly determine driving behavior. The purpose of this study was to investigate the effects of drivers' emotions on their driving behavior. The results of this study showed that positive emotions do not affect driving behavior. As for negative emotions, however, safe driving(SD) and comfort driving(CD) factors have a negative correlation, and violence driving(VD) and regulation violation(RO) factors have a positive correlation. This study is significant as a basic study for establishing and determining a policy for reducing traffic accidents and for educating drivers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1317-1324
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• 2016

Utilizing the Arduino platform to express the emotions that reflect the colors expressed the jewelry. Emotional color expression utilizes Plutchik's Wheel of Emotions model was applied to the similarity of emotions and colors. It receives the recognized value from the temperature, lighting, sound, pulse sensor and gyro sensor of a smart jewelery that can be easily accessible from your smartphone processes that recognize and process the emotion applied the rules of inference based on ontology. The emotional feelings color depending on the color looking for the emotion seen in context and applied to the smart LED jewelry. The emotion and the color combination of contextual information extracted from the recognition sensors are reflected in the built-in smart LED Jewelry depending on the emotions of the wearer. Take a light plus the emotion in a smart jewelery can represent the emotions of the situation, the doctor will be able to be a tool of representation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.603-610
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• 2021

In this paper, we extract the user's power consumption patterns, and model the optimal consumption patterns by applying the user's environment and emotion. Based on the comparative analysis of these two patterns, we present an efficient power consumption method through changes in the user's power consumption behavior. To extract significant consumption patterns, vector standardization and binary data transformation methods are used, and learning about the ensemble's ensemble with k-means clustering is applied, and applying the support factor according to the value of k. The optimal power consumption pattern model is generated by applying forced and emotion-based control based on the learning results for ensemble aggregates with relatively low average consumption. Through experiments, we validate that it can be applied to a variety of windows through the number or size adjustment of clusters to enable forced and emotion-based control according to the user's intentions by identifying the correlation between the number of clusters and the consistency ratios.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.503-508
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• 2023

The purpose of this study was to examine the impact of emotional intelligence and cognitive emotion regulation strategies on career maturity among university students during this period of increasing employment challenges. The study participants consisted of 348 students who attended general education courses at a 4-year N University located in Chungnam. The analysis was conducted using SPSS 26.0, and descriptive statistics, correlation analysis, and regression analysis were applied. The research findings indicated a significant correlation between emotional intelligence and cognitive emotion regulation strategies with career maturity among university students. The results suggested that positive thinking and motivation related to their emotions and feelings could enhance career maturity. Based on these findings, it is expected that various research and programs aiming to enhance career maturity will be promoted in the future. Additionally, the study aspires to serve as foundational data in devising concrete and achievable strategies for career and employment fields.

• Journal of IKEEE
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• v.22 no.4
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• pp.1140-1146
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• 2018

Recently, a methodology for analyzing complex bio-signals using a deep learning model has emerged among studies that recognize human emotions. At this time, the accuracy of emotion classification may be changed depending on the evaluation method and reliability depending on the kind of data to be learned. In the case of biological signals, the reliability of data is determined according to the noise ratio, so that the noise detection method is as important as that. Also, according to the methodology for defining emotions, appropriate emotional evaluation methods will be needed. In this paper, we propose a wavelet -based noise threshold setting algorithm for verifying the reliability of data for multimodal bio-signal data labeled Valence and Arousal and a method for improving the emotion recognition rate by weighting the evaluation data. After extracting the wavelet component of the signal using the wavelet transform, the distortion and kurtosis of the component are obtained, the noise is detected at the threshold calculated by the hampel identifier, and the training data is selected considering the noise ratio of the original signal. In addition, weighting is applied to the overall evaluation of the emotion recognition rate using the euclidean distance from the median value of the Valence-Arousal plane when classifying emotional data. To verify the proposed algorithm, we use ASCERTAIN data set to observe the degree of emotion recognition rate improvement.

• Science of Emotion and Sensibility
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• v.12 no.4
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• pp.373-380
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• 2009

This study tried to investigate how three levels of arousal affect performance of a 3-back task. Ten university male (age $25.7{\pm}1.5$) and ten female (age $24.5{\pm}1.8$) students participated in this experiment. Using pictures selected from a group test, three levels of arousal, i.e. tensed, neutral, and relaxed emotions, were induced. Each subject was run through the procedure three times, once for each arousal level. The procedure consisted of six phases for each arousal condition Rest 1(2 min), Picture 1(presenting emotion arousing photos for 2 min), 3-back task 1(2 min), Picture 2(presenting emotion arousing photos for 2 min), 3-back task 2(2 min), and Rest 2(2 min). Skin conductance level(SCL) of electrothermal activity was also measured during all phases of the experiment. The accuracy rate of 3-back task performance was the highest at a neutral emotional state, followed by relaxed and then tensed emotional state. There was no difference in reaction time(RT) among the three levels of arousal. SCL was the highest at a tensed emotional state, followed by neutral emotional state and then relaxed emotional state. Based on the results, it could be inferred that tension, induced by stimuli unrelated to cognitive tasks, decreases the ability to perform cognitive tasks.

• Science of Emotion and Sensibility
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• v.16 no.2
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• pp.157-166
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• 2013

There are few that evaluate tactile emotion as it pertains to car interior parts, while studies on visual evaluations of car interiors as well as usability tests in a visual sense are numerous. The purpose of this study is to determine typical in-vehicle tactile emotions so that they can be used to evaluate tactile impressions of car interior parts. 52 words related to tactile impressions of car interiors were gathered from a survey in conjunction with an in-vehicle test, interviews with the car salespersons, and an analysis of car reviews. After a factor analysis with 52 words, 10 categories of major tactile emotions were clustered. These were roughness, toughness, friction, comfortability, stiffness, softness, temperature, sleekness, familiarity, and flexibility. These representative tactile emotions regarding a car interior can be used to evaluate tactile impressions of surfaces such as leather, plastic, metal and wood when used as parts in car interiors.

• Korean Journal of Cognitive Science
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• v.21 no.1
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• pp.127-143
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• 2010

This study explores children's sex differences of emotion discrimination from facial expressions based on two dimensional model of emotion. The study group consisted of 92 children, of 40, 52, and 64 months of age, and the rate of male and female children was male children (50%) and female children (50%). Children of 92 were required to choose facial expressions related the twelve emotion terms. Facial expressions applied for experiment are used the photographs rated the degree of expression in each of the two dimensions (pleasure-displeasure dimension and arousal-sleep dimension) on a nine-point scale from 54 university students. The experimental findings appeared that the sex differences were distinctly the arousal-sleep dimension than the pleasure-displeasure dimension. In the arousal-sleep dimensionoussleepness, anger, comfort, and loneliness' emotions showed large sex differences over 1 value. Especially, while male children showed high arousal more than female children in the emotions like 'sleepiness, anger and loneliness', female children showed high arousal more than male children in 'comfort' emotion.