• Science of Emotion and Sensibility
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• v.5 no.3
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• pp.11-20
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• 2002

There are Two new models developed for objective evaluation of fabric color patterns by applying a multiple regression analysis and an adaptive foray-rule-based system. The physical features of fabric color patterns are extracted through digital image processing and the emotional features are collected based on the psychological experiments of Soen[3, 4]. The principle physical features are hue, saturation, intensity and the texture of color patterns. The emotional features arc represented thirteen pairs of adverse adjectives. The multiple regression analyses and the adaptive fuzzy system are used as a tool to analyze the relations between physical and emotional features. As a result, both of the proposed models show competent performance for the approximation and the similar linguistic interpretation to the Soen's psychological experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.558-566
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• 2015

LED, the next-generation light source, rapidly develops and has advantages of low power, high efficiency, and long life. Accordingly, an interest in lightings by using LED rises. If emotional lighting is implemented by using LED, all colors can be represented by using 3 primary colors of light, differently from the conventional single-color lighting. LED emotional lightings which can control human emotions continue to be developed thanks to these advantages. This study was conducted to design an algorithm for expressing LED emotional lighting in line with the situation and temperature by extracting colors for concentration and resting situations in indoor environment and mixing them with colors of the temperature felt by user. The LED emotional lighting designed with a neuro-fuzzy system was found to have effects on user's emotions during concentration and resting.

• Journal of the Korea Society of Computer and Information
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• v.20 no.10
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• pp.69-76
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• 2015

User's selection of music is largely influenced by private tastes as well as emotional states, and it is the unconsciousness projection of user's emotion. Therefore, we think user's emotional states to be music itself. In this paper, we try to grasp user's emotional states from music selected by users at a specific context, and we analyze the correlation between its context and user's emotional state. To get emotional states out of music, the proposed method extracts emotional words as the representative of music from lyrics of user-selected music through morphological analysis, and learns weights of linear classifier for each emotional features of extracted words. Regularities learned by classifier are utilized to calculate predictive weights of virtual music using weights of music chosen by other users in context similar to active user's context. Finally, we propose a method to recommend some pieces of music relative to user's contexts and emotional states. Experimental results shows that the proposed method is more accurate than the traditional collaborative filtering method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.7
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• pp.1105-1110
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• 2017

Speech with various emotions degrades the performance of the speaker recognition system. In this paper, a speaker recognition method using emotional adaptation has been proposed to improve the performance of speaker recognition system using affective speech. For emotional adaptation, emotional speaker model was generated from speaker model without emotion using a small number of training affective speech and speaker adaptation method. Since it is not easy to obtain a sufficient affective speech for training from a speaker, it is very practical to use a small number of affective speeches in a real situation. The proposed method was evaluated using a Korean database containing four emotions. Experimental results show that the proposed method has better performance than conventional methods in speaker verification and speaker recognition.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1099-1104
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• 2003

In this paper, the position control of a car-like mobile robot using neural network is proposed. The positional information of the mobile robot is given by a laser range finder located remotely through wireless communication. The heading angle is measured by a gyro sensor. Considering these two sensor information as references, the robot posture by localization is corrected by a cascaded controller. In order to improve the tracking performance, a neural network with a cascaded controller is used to compensate for any uncertainty in the robot. The remotely located neural network filter modifies the reference trajectories to minimize the positional errors by wireless communication. A car-like mobile robot is built as a test-bed and experimental studies of proposed several control algorithms are performed. It turns out that the best position control can be achieved by a cascaded controller with neural network.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.358-361
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• 2000

To reduce the leadtime for a new model according to the strict market requirements, automobile manufacturer begins to utilize 3-dimensional CAD based techniques such as DMU(Digital Mock-Up). RP(Rapid Prototyping), VE(Virtual Engineering). But, not so many satisfactory utilities have been introduced to deal with the emotional properties such as embossment on the surface of interior parts and touch from material characteristics in virtual environment. It is required to manufacture prototype parts to verify actual feeling of the passengers in real automobile. This paper suggests a methodology to enhance emotional property via embedding embossment on the surface of prototype car interior trim without deterioration of dimensional accuracy using RIM(Reaction Injection Molding) and vacuum forming method.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.193-198
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• 2021

The application of e-Voting plays an important role in order to support democracy activities in Indonesia, such as elections at different levels. E-Voting has the function of providing better service to people in order to participate in elections. This research attempts to develop the appearance of the user interface of e-Voting based on users' emotional preferences using Kansei Engineering. Kansei Engineering is used in this research to analyze emotional feelings regarding e-Voting applications' presented Kansei words and give a recommendation on the most suitable user interface to be considered in their development. This research observed two main users' emotional feelings ("calm" and "formal") selected from ten Kansei words. The final recommendation is a conceptual element designed for designing e-Voting applications based on the Kansei word "calm".

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1557-1564
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• 2010

In this paper, we propose a maximum entropy-based emotion recognition model using the individual average difference of emotional signal, because an emotional signal pattern depends on each individual. In order to accurately recognize a user's emotion, the proposed model utilizes the difference between the average of the input emotional signals and the average of each emotional state's signals(such as positive emotional signals and negative emotional signals), rather than only the given input signal. With the aim of easily constructing the emotion recognition model without the professional knowledge of the emotion recognition, it utilizes a maximum entropy model, one of the best-performed and well-known machine learning techniques. Considering that it is difficult to obtain enough training data based on the numerical value of emotional signal for machine learning, the proposed model substitutes two simple symbols such as +(positive number)/-(negative number) for every average difference value, and calculates the average of emotional signals per second rather than the total emotion response time(10 seconds).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1503-1510
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• 2016

In this study, we implemented the emotional light controlling system by using the wheel interface built in the smart-watch devices. Most previous light controlling systems have been adopted the direct switches or smart-phone applications for presenting individual emotion in lighting systems. However, in order to control color properties, these studies have some complicated user-interfaces in systems and limitation to present various color spectrums. Therefore, we need to user-friendly interfaces and functions for controlling properties of the lightning systems such as color, tone, color temperature, brightness, and saturation in detail with the wheel interface built in the smart-watch devices. The system proposed in the study is given to choose the user's selecting the emotional status information for providing the emotional lights. The selectable emotional status such as "stable", "surprise", "tired", "angry", etc. can be among 11 kinds of emotional states. In addition, the designed system processed the user's information such as user's emotional status information, local time, location information.

• Journal of the Ergonomics Society of Korea
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• v.30 no.1
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• pp.203-211
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• 2011

Objective: The aim of this study is to introduce a methodology to assess driver's emotion stability by using bio-signals. Background: Psychophysiological analysis of driver's behavior has been conducted to improve the driving safety and comfort. However, the variability of bio-signal and individual difference made it difficult to assess the psychophysiological status of drivers that can be expressed as emotional stability of drivers. Method: Two experimental studies were reviewed and summarized. New techniques assessing emotional stability of drivers were explained. Statistical concept and multidimensional space were used to identify the emotionally stable conditions. Conclusion: Psychophysiological approach can provide information of driver's emotional status. The experimental methodology and algorithm used in this study showed the possibility of parameterization of psychophysiological response. Application: Currently measured statistical and geometrical data can be further applied to develop an interactive device monitoring and reacting driver's emotion when driver experiences emotionally unstable or uncomfortable situation.