• Journal of Korea Multimedia Society
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• v.20 no.10
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• pp.1646-1654
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• 2017

Pupil size variation can not be controlled intentionally by the user and includes various features such as the blinking frequency and the duration of a blink, so it is suitable for understanding the user's emotional state. In addition, an ocular feature based emotion classification method should be studied for virtual and augmented reality, which is expected to be applied to various fields. In this paper, we propose a novel emotion classification based on CNN with pupil size variation signals which include not only various ocular feature information but also time information. As a result, compared to previous studies using the same database, the proposed method showed improved results of 5.99% and 12.98% respectively from arousal and valence emotion classification.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.05a
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• pp.20-25
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• 2001

In recent years, the concern about a user center design in increasing, and it's needed to task a user's visual cognitive characteristics for information presentation. Then this study aims to grasp user's cognitive characteristics about the information presentation by analyzing the fixation points. In the experiment, actually subject operated a copy machine. Recorded the fixation point movement of the operation panel by the eye mark recorder. Analysis examined the screen interface of the operation panel from the field of a fixation point trace. The top down type fixation oder by experience or the context became clear as a result. Furthermore, the difference of the fixation order by skill level was also examined. In this study, it was assumed that to grasp the visual cognitive characteristics becomes the key of efficient information.

• 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 the Korean Society for Library and Information Science
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• v.32 no.4
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• pp.105-115
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• 1998

In this paper, we propose a document clustering and retrieval tool which allows users to manage their emotion based document access. This system name is ECRAS(Emotion based Clustering and Retrieval Agent System). Our system extract S emotion feature which like HAPPY, SAD, ANGRY, FEAR, DISGUST from various document. And, our system have retrieve documents for user query base on emotion feature.

• Journal of KIISE:Software and Applications
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• v.36 no.12
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• pp.986-995
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• 2009

Color affects people in their various combinations of hue, saturation and value. On the other hand, people may feel different emotion from the same color. If we can introduce these characteristics of color and people's emotion about color to emotion-based digital technologies and their contents, we can effectively draw users' interest and immersion to the contents. In this paper, we will show how people feel about color and present a method of image coloring that reflects the user's preference. First, we define basic templates that reflect the relationship between color and emotion, and then perform an image coloring. To reflect user's preference, we compute weights for hue, saturation and value through the experiments on each subject's preference about hue, saturation and value. The image coloring for each subject's taste will be drawn by updating the weights of hue, saturation and value. Through the results of experiments and surveys, we found that people were more satisfied with the transformation of the templates which reflected user's preference than the one that did not.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.39-43
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• 2002

Various electronic bulletin board systems (BBS) exist on the Internet. A user has to use two or more BBS. Because his/her interests may not be restricted to only one subject and BBS satisfying his/her interests may not be restricted to only one also. Furthermore, in each BBS, two or more subjects are parallel discussed while the newest contribution is always carried out. Therefore, when a user tries to keep on perusing about a specific subject, it is necessary for the user to remember in which BBS the subject exists and in the past what article of the subject was read. In this paper, we are aiming to construct an electronic bulletin board integrated management system. In this system, a user is able to use two or more BBS just like one BBS. In this paper, we present a framework of the electronic bulletin board integrated management system and implementation of a prototype system.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.528-531
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• 2021

Nowadays recommendation systems are so ubiquitous, where our many decisions are being done by the means of them. We can see recommendation systems in all areas of our daily life. Therefore the research of this sphere is still so active. So far many research papers were published for clothing recommendations as well. In this paper, we propose the clothing-recommendation system according to user emotion and weather information. We used social media to analyze users' 6 basic emotions according to Paul Eckman theory and match the colour of clothing. Moreover, getting weather information using visualcrossing.com API to predict the kind of clothing. For sentiment analysis, we used Emotion Lexicon that was created by using Mechanical Turk. And matching the emotion and colour was done by applying Hayashi's Quantification Method III.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.215-222
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• 2021

As the importance of human-computer interaction (Human Computer Interface) technology grows and research on HCI is progressing, it is inferred about the research emotion inference or the computer reaction according to the user's intention, not the computer reaction by the standard input of the user. Stress is an unavoidable result of modern human civilization, and it is a complex phenomenon, and depending on whether or not there is control, human activity ability can be seriously changed. In this paper, we propose an intelligent emotional recommendation system using music as a way to relieve stress after measuring heart rate variability (HRV) and acceleration photoplethymogram (APG) increased through stress as part of human-computer interaction. The differential evolution algorithm was used to extract reliable data by acquiring and recognizing the user's biometric information, that is, the stress index, and emotional inference was made through the semantic web based on the obtained stress index step by step. In addition, by searching and recommending a music list that matches the stress index and changes in emotion, an emotional recommendation system suitable for the user's biometric information was implemented as an application.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.05a
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• pp.15-19
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• 2001

This paper describes effectiveness and characteristics of 3 P(point) task analysis as a new Ergonomic and Kansei design method for extracting user demand especially. The key point in 3 P task analysis is to describe the flow of tasks and extract any problems in each task. A solution of a problem means a user demand. 3 P task analysis cal eliminate an oversight of check items by examining the users' information processing level. The suers' information processing level was divided into the following three stages for problem extraction: acquirement of information ---> understanding and judgment ---> operation. Three stages has fourteenth cues such as difficulty of seeing, no emphasis, mapping for extracting problems. To link analysis results to the formulation of a product concept. I added a column on the right side of the table for writing the requirements (user demand) to resolve the problems extracted from each task. The requirements are extracted by using seventh cues. Finally 3 P task analysis was compared with group interview to make the characteristics of 3 P task analysis, especially extracting user demand, clear.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.1
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• pp.45-51
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• 2012

In this paper, it's a system which recognize the user's emotions after obtaining the biological informations(pulse sensor, blood pressure sensor, blood sugar sensor etc.) about user's bio informations through wireless sensors in accordance of previously collected informations about user's stress index and classification the Colors & Music. This system collects the inputs, saves in the database and finally, classifies emotions according to the stress quotient by using multiple SVM(Support Vector Machine) algorithm. The experiment of multiple SVM algorithm was conducted by using 2,000 data sets. The experiment has approximately 87.7% accuracy.