• Nuclear Engineering and Technology
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• v.37 no.2
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• pp.151-158
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• 2005

Advanced nuclear power plants are generally large complex systems automated by computers. Whenever a rare plant emergency occurs the plant operators must cope with the emergency under severe mental stress without committing any fatal errors. Furthermore, The operators must train to improve and maintain their ability to cope with every conceivable situation, though it is almost impossible to be fully prepared for an infinite variety of situations. In view of the limited capability of operators in emergency situations, there has been a new approach to preventing the human error caused by improper human-machine interaction. The new approach has been triggered by the introduction of advanced information systems that help operators recognize and counteract plant emergencies. In this paper, the adverse effect of automation in human-machine systems is explained. The discussion then focuses on how to configure a joint human-machine system for ideal human-machine interaction. Finally, there is a new proposal on how to organize technologies that recognize the different states of such a joint human-machine system.

• International Journal of Human Ecology
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• v.7 no.2
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• pp.85-95
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• 2006

The purpose of this study was to examine mothers' ideal and actual parenting behaviors toward their infants in three parenting domains; social, didactic, and limit setting. A total of 264 mothers of young children under age three from Seoul, Korea completed Parental Style Questionnaires (PSQ). Mothers' self report on their ideal and actual parenting were explored as a function of child sex, age, and birth order. As expected, there were significant differences between mothers' ideal and actual behaviors in all three parenting domains: Mothers' ideal behaviors such as social interaction, didactic interaction and limit setting were higher than those of their actual behaviors. For mothers' ideal parenting, results revealed neither significant main effects nor interaction effects. However, the Parenting Domain x Birth-Order 2-way interaction and the Parenting Domain x Child Age 2-way interaction were significant for mothers' actual behaviors. Specifically, mothers reported more social and didactic behaviors with their first-born than later born children, but not for limit setting behavior. It was also found that higher limit setting behaviors were apparent for their 2- and 3-year-old than 1-year old children whereas lower social interactions were found for 3-year-old than for 1-year-old. In light of universality and uniqueness, mothers' parenting behavior toward young children has been discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.2966-2986
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• 2023

Climate change is a constant threat to human life, and it is important to understand the public perception of this issue. Previous studies examining climate change have been based on limited survey data. In this study, the authors used big data such as news articles and social media data, within which the authors selected specific keywords related to climate change. Using these natural language data, topic modeling was performed for discourse analysis regarding climate change based on various topics. In addition, before applying topic modeling, sentiment analysis was adjusted to discover the differences between discourses on climate change. Through this approach, discourses of positive and negative tendencies were classified. As a result, it was possible to identify the tendency of each document by extracting key words for the classified discourse. This study aims to prove that topic modeling is a useful methodology for exploring discourse on platforms with big data. Moreover, the reliability of the study was increased by performing topic modeling in consideration of objective indicators (i.e., coherence score, perplexity). Theoretically, based on the social amplification of risk framework (SARF), this study demonstrates that the diffusion of the agenda of climate change in public news media leads to personal anxiety and fear on social media.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.849-857
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• 2015

Although human-sized bipedal humanoid robots have been developed as the ideal form of human-friendly robots, studies of humanoid robots from the user perspective and of actual interaction between humanoid robots and the public in daily environments are few. This paper presents a long-term public demonstration that encouraged interaction between a humanoid robot and unspecified individuals. We have collected a significant amount of subjective evaluation data from the public by performing a storytelling demonstration that enhanced people's empathy towards the robot. The evaluation model consists of the robot's human friendliness, which involves its impression on humans, interaction with humans, and imitation of human motions and the robot's human appearance which involves gender, age, height, and body type. This study shows that there is no significant difference in human-friendliness between gender groups (male and female), while there is a significant difference between age groups (children and adults). In human appearance, it appears that there is no significant difference between either gender groups or age groups, except for the case of the robot's height.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.186-192
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• 2009

In this paper, we represent the recognition method for human frontal upper body pose. In HCI(Human Computer Interaction) and HRI(Human Robot Interaction) when a interaction is established the human has usually frontal direction to the robot or computer and use hand gestures then we decide to focus on human frontal upper-body pose, The two main difficulties are firstly human pose is consist of many parts which cause high DOF(Degree Of Freedom) then the modeling of human pose is difficult. Secondly the matching between image features and modeling information is difficult. Then using Pictorial Model we model the human main poses which are mainly took the space of frontal upper-body poses and we recognize the main poses by making main pose database. using determined main pose we used the model parameters for particle filter which predicts the posterior distribution for pose parameters and can determine more specific pose by updating model parameters from the particle having the maximum likelihood. Therefore based on recognizing main poses and tracking the specific pose we recognize the human frontal upper body poses.

• BMB Reports
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• v.50 no.11
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• pp.535-536
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• 2017

A novel approach has been used to identify functional interactions relevant to human disease. Using high-throughput human-yeast genetic interaction screens, a first draft of disease interactome was obtained. This was achieved by first searching for candidate human disease genes that confer toxicity in yeast, and second, identifying modulators of toxicity. This study found potentially disease-relevant interactions by analyzing the network of functional interactions and focusing on genes implicated in amyotrophic lateral sclerosis (ALS), for example. In the subsequent proof-of-concept study focused on ALS, similar functional relationships between a specific kinase and ALS-associated genes were observed in mammalian cells and zebrafish, supporting findings in human-yeast genetic interaction screens. Results of combined analyses highlighted MAP2K5 kinase as a potential therapeutic target in ALS.

• Proceedings of the Korea Society of Design Studies Conference
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• 2001.10a
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• pp.41.2-41
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• 2001

• Smart Media Journal
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• v.11 no.6
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• pp.9-17
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• 2022

In the COVID-19 pandemic era, non-contact services were demanded and the use of extended reality and metaverse services increased rapidly in various applications. In this paper, we analyze Gather.town, ifland, Roblox, and ZEPETO metaverse platforms in terms of user interaction, avatar-based interaction, and virtual world authoring. Especially, we distinguish interactions among user input techniques that occur in the real world, avatar representation techniques to represent users in the virtual world, and interaction types that create a virtual world through user participation. Based on this work, we highlight the current trends and needs of human-metaverse interaction and forecast future opportunities and research directions.

• 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.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.2
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• pp.101-106
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• 2022

Recently, virtual human has been widely used in various fields such as education, training, information guide. In addition, it is expected to be applied to services that interact with remote users in metaverse. In this paper, we propose a novel method to make a virtual human' interaction to perceive the user's surroundings. We use the editing authoring tool to apply user's interaction for providing the virtual human's response. The virtual human can recognize users' situations based on fuzzy, present optimal response to users. With our interaction method by context awareness to address our paper, the virtual human can provide interaction suitable for the surrounding environment based on automatic adaptation.