• Journal of Digital Contents Society
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• v.19 no.4
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• pp.821-827
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• 2018

Affective computing has gained increasing interest in the recent years with the development of potential applications in Human computer interaction (HCI) and healthcare. Although momentous research has been done on human emotion recognition, however, in comparison to speech and facial expression less attention has been paid to physiological signals. In this paper, Electroencephalogram (EEG) signals from different brain regions were investigated using modified wavelet energy features. For minimization of redundancy and maximization of relevancy among features, mRMR algorithm was deployed significantly. EEG recordings of a publically available "DEAP" database have been used to classify four classes of emotions with Multi class Support Vector Machine. The proposed approach shows significant performance compared to existing algorithms.

• Annual Conference on Human and Language Technology
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• 1999.10d
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• pp.99-105
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• 1999

한국어 정보처리를 위한 언어정보는 응용 분야에 따라 큰 차이를 보인다. 특히 말뭉치를 이용한 연구에서는 언어정보가 달라질 때마다 시스템을 새로 구성해야 하는 어려움이 있다. 본 논문에서는 이와 같은 어려움을 다소 완화시키기 위해 새로운 환경에 잘 적응할 수 있는 한국어 품사 태깅 시스템에 관해서 논한다. 본 논문에서는 이 시스템을 KTAG99라고 칭한다. KTAG99는 크게 실행부와 학습부로 구성되었다. 한국어 품사 태깅을 위한 실행부는 고유명사 추정기, 한국어 형태소 분석기, 통계기반 품사 태거, 품사 태깅 오류교정기로 구성되었으며, 실행부에서 필요한 언어정보를 추출하는 학습부는 고유명사 추정규칙 추출기, 형태소 배열규칙 추출기, 사전 추출기, 확률정보 추정기, 품사 태깅 오류수정 규칙 추정기로 구성되었다. KTAG99에서 필요한 언어정보의 대부분은 학습 말뭉치로부터 추출되거나 추정되기 때문에 아주 짧은 시간 내에 새로운 환경에 적응할 수 있다.

• Archives of design research
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• v.13 no.3
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• pp.49-58
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• 2000

We commonly use the computer interface a generalized form. However, the requirement of the user various and some users cannot apply the general circumstance. For these requirements, this research suggests the non-verbal communication. The suggestion is that Mewing with the mouth in human behavior applies to the interaction of the computer This was offered in three forms. First, drawing application: second, the arcade game: third, the interactive book. in condusion, we confirmed that the suggestion of this research could be effectively used for the development of the human computer interface.

• Journal of Distribution Science
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• v.22 no.2
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• pp.103-113
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• 2024

Purpose: With the popularity of artificial intelligence (AI) in the service industry and occurrence ofservice failures in AI-based services, understanding human-robot interaction issues in service failure situations is especially important. Some issues which deserve further empirical investigation are whether consumers can develop the same tolerance for chatbots after service failure as they have for human agents, and the relationship between agent type and tolerance is mediated by the mechanisms of perceived warmth and perceived competence. Research Design, Data, and Methodology: This research experimentally collected and analyzed data from 119 university students who had experienced chatbots service failures. Differences in tolerance towards human agents and chatbots after experiencing service failures were explored, with a further examination of the mediating pathways between this relationship via perceived warmth and perceived competence. Results: Consumers are more tolerant ofservice failure with chatbots compared to service failure with human agents. Significant mediation of the relationship between service agent and service failure tolerance by perceived competence, while perceived warmth has no significant mediating effect. Conclusions: This research enhances our understanding of AI-assisted services, human-computer interaction, improves the service functionality of existing smart devices, and deepens the understanding of the relationship between consumer responses and behaviors.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.531-536
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• 2016

This study highlights the effectiveness of analyzing the feelings children have when interacting with robots in a dramatic play setting using augmented reality in Human Robot Interaction (HRI). Existing dramatic play activities using robots by QR-markers were edited, and their weaknesses have been corrected so that children could interact more effectively with robots. Additionally, children's levels of interest and engagement in dramatic play activities, the accuracy of robotic props, and the smartness of robots were analyzed throughout children's interactions during such activities using augmented reality. Younger participants were more likely to find robots interesting and intelligent, and participants with no previous experience with robots had relatively higher levels of interest in robots and tended to notice changes in robots' costumes.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.110-119
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• 2021

The Coronavirus or COVID-19 is contagiousness virus that infected almost every single part of the world. This pandemic forced a major country did lockdown and stay at a home policy to reduce virus spread and the number of victims. Interactions between humans and robots form a popular subject of research worldwide. In medical robotics, the primary challenge is to implement natural interactions between robots and human users. Human communication consists of dynamic processes that involve joint attention and attracting each other. Coordinated care involves sharing among agents of behaviours, events, interests, and contexts in the world from time to time. The robotics arm is an expensive and complicated system because robot simulators are widely used instead of for rehabilitation purposes in medicine. Interaction in natural ways is necessary for disabled persons to work with the robot simulator. This article proposes a low-cost rehabilitation system by building an arm gesture tracking system based on a depth camera that can capture and interpret human gestures and use them as interactive commands for a robot simulator to perform specific tasks on the 3D block. The results show that the proposed system can help patients control the rotation and movement of the 3D arm using their hands. The pilot testing with healthy subjects yielded encouraging results. They could synchronize their actions with a 3D robotic arm to perform several repetitive tasks and exerting 19920 J of energy (kg.m².S^-2). The average of consumed energy mentioned before is in medium scale. Therefore, we relate this energy with rehabilitation performance as an initial stage and can be improved further with extra repetitive exercise to speed up the recovery process.

• Journal of Computing Science and Engineering
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• v.7 no.4
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• pp.211-219
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• 2013

Human-centered computing (HCC) as a field was defined several years ago. Since then, the Web has grown significantly, and so has its impact in society at every level, creating the grounds for a new Web science. In this paper, we examine the definitions of HCC and Web science, and discuss how they might be related. On the one hand, HCC can be viewed as a set of methodologies, and on the other hand, Web science can be viewed as a platform or repository, from which behavioral data can be drawn. We examine the relationship between the two, and summarize three different research approaches that in many ways show this intersection.

• Proceedings of the Korea Society for Simulation Conference
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• 1992.09a
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• pp.161-167
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• 1992

The spcaker will briefly summarized the current state of the art in commericial simulation tools as limited by soft ware and hardware technology. He will then discuss how recent and near-future advances in software and hardware tenilogy can be applied to the benefit of simulationists. Specifically, the following topics will be ciscussed : Simulation Languages vs Simulations ; Computer hardware platforms ; Performance liminting factors ; Performance assisting techniques ; Software architectures ; Human factors and model interaction.

• Journal of the Ergonomics Society of Korea
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• v.30 no.6
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• pp.705-713
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• 2011

Objective: The aim of this study is to compare results of emotion recognition by several algorithms which classify three different emotional states(happiness, neutral, and surprise) using physiological features. Background: Recent emotion recognition studies have tried to detect human emotion by using physiological signals. It is important for emotion recognition to apply on human-computer interaction system for emotion detection. Method: 217 students participated in this experiment. While three kinds of emotional stimuli were presented to participants, ANS responses(EDA, SKT, ECG, RESP, and PPG) as physiological signals were measured in twice first one for 60 seconds as the baseline and 60 to 90 seconds during emotional states. The obtained signals from the session of the baseline and of the emotional states were equally analyzed for 30 seconds. Participants rated their own feelings to emotional stimuli on emotional assessment scale after presentation of emotional stimuli. The emotion classification was analyzed by Linear Discriminant Analysis(LDA, SPSS 15.0), Support Vector Machine (SVM), and Multilayer perceptron(MLP) using difference value which subtracts baseline from emotional state. Results: The emotional stimuli had 96% validity and 5.8 point efficiency on average. There were significant differences of ANS responses among three emotions by statistical analysis. The result of LDA showed that an accuracy of classification in three different emotions was 83.4%. And an accuracy of three emotions classification by SVM was 75.5% and 55.6% by MLP. Conclusion: This study confirmed that the three emotions can be better classified by LDA using various physiological features than SVM and MLP. Further study may need to get this result to get more stability and reliability, as comparing with the accuracy of emotions classification by using other algorithms. Application: This could help get better chances to recognize various human emotions by using physiological signals as well as be applied on human-computer interaction system for recognizing human emotions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.559-575
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• 2023

3D human pose estimation is widely applied in various fields, including action recognition, sports analysis, and human-computer interaction. 3D human pose estimation has achieved significant progress with the introduction of convolutional neural network (CNN). Recently, several researches have proposed the use of multiview approaches to avoid occlusions in single-view approaches. However, as the number of cameras increases, a 3D pose estimation system relying on a CNN may lack in computational resources. In addition, when a single host system uses multiple cameras, the data transition speed becomes inadequate owing to bandwidth limitations. To address this problem, we propose a distributed real-time 3D pose estimation framework based on asynchronous multiple cameras. The proposed framework comprises a central server and multiple edge devices. Each multiple-edge device estimates a 2D human pose from its view and sendsit to the central server. Subsequently, the central server synchronizes the received 2D human pose data based on the timestamps. Finally, the central server reconstructs a 3D human pose using geometrical triangulation. We demonstrate that the proposed framework increases the percentage of detected joints and successfully estimates 3D human poses in real-time.