• Annual Conference on Human and Language Technology
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• 1996.10a
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• pp.75-84
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• 1996

인간의 가장 자연스러운 통신 수단은 자연언어이다. 본 논문에서는 자연언어 대화체를 사용한 인터네트 상에서의 정보 검색에 있어서 사용자 모델링 에이젼트 (User modeling Agent or User modeling system)의 모델 형성 기술 및 그의 역할을 서술하고 있다. 사용자 모델은 인간의 심성 모델 (Mental model)에 해당하며, 심성 모델이 사용자가 시스템에 대한 지식과 자신의 문제상황 또는 주변환경에 대하여 가지는 모델임에 반하여, 사용자 모델은 시스템이 사용자의 지식 및 문제 상황을 표상(Representation)하여 형성한 사용자에 대한 모델이다. 따라서 사용자 모델은 시스템의 지능적인 Human Computer Interaction (HCI)의 지원을 위하여 필수적이다. 본 논문에서는 사용자 모델 형성 기술 및 지능형 대화 모델의 지원을 위한 시스템 실례로써 사용자 모델 형성 시스템 $BGP-MS^2$ 와 사용자 모델의 형성을 위하여 구축된 지식베이스 구조를 설명하고 있다.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.8
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• pp.156-164
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• 1998

IMS is a more advanced manufacturing system than FMS. However, IMS do not have sufficient performance for the work in the various and uncertain environment, because of the difficulty of the work and occurrence of the unexpected condition. If IMS is hard to work properly, teleoperation system can support it by using the human's consideration and judgment. The master mechanism is a basic component of the teleoperation system and the development of the useful one is important for efficiency of the work. A master mechanism of exoskeleton type can increase the work efficiency, mobility and harmony between a working robot and an operator. This paper describes an arm-harness of exoskeleton type, which is able to drive a robot according to judgment. This device is applied to a robot system for evaluating the system performance through the experiment.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.57-62
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• 2002

This study described the specification and configuration of developed fixed-base AHS (Automated Highway System) simulator fur the human factors researches, and its usability evaluation results after riding 120, 140, and 160kph automated driving speed. As the results, this study suggested the subjects' preferences and opinions about simulator and AHS configurations that would help to establish the AHS R&D plan and driver-vehicle/road interface design guidelines as the basic researches of the AHS human factors.

• Proceedings of the KSPS conference
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• 2005.11a
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• pp.163-166
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• 2005

We propose a speech emotion recognition method for natural human-robot interface. In the proposed method, emotion is classified into 6 classes: Angry, bored, happy, neutral, sad and surprised. Features for an input utterance are extracted from statistics of phonetic and prosodic information. Phonetic information includes log energy, shimmer, formant frequencies, and Teager energy; Prosodic information includes pitch, jitter, duration, and rate of speech. Finally a patten classifier based on Gaussian support vector machines decides the emotion class of the utterance. We record speech commands and dialogs uttered at 2m away from microphones in 5different directions. Experimental results show that the proposed method yields 59% classification accuracy while human classifiers give about 50%accuracy, which confirms that the proposed method achieves performance comparable to a human.

• Journal of Information Management
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• v.33 no.2
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• pp.49-66
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• 2002

In this paper, the recent trends of user-centered information communication are reviewed, especially focused on Computer-Mediated Communication(CMC) based on internet, Human Factors Engineering, and Human-Computer Interaction(HCI). The result is that human-centered information communication process has influence on the extension of user interface.

• Annual Conference of KIPS
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• 2010.04a
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• pp.576-578
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• 2010

운전자 정보제공 HVI(Human-Vehicle Interface) 시스템은 운전자에게 보다 향상된 인터페이스를 제공하기 위한 시스템이다. 요즘에는 다양한 정보기기가 등장하면서 운전 중에 다양한 정보를 습득할 수 있고 유용한 정보로 활용할 수 있다. 반면 이러한 기기들이 통합되지 않음으로 인해 조작에 불편을 주고 때로는 유용한 정보가 운전에 방해를 주는 요인이 된다. 따라서 본 연구에서는 운전자에게 정보제공을 위한 HVI 통합 시스템을 설계하여 다양한 정보기기를 통해 수집되는 정보를 운전자에게 효과적으로 제공하고 운전 중에 운전자의 동작을 최소화기 위한 시스템을 설계한다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.5
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• pp.18-23
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• 2010

In this paper, we propose a computationally efficient method detecting the P300 wave for brain-machine interface. Electrophysiological researches have shown that the P300 wave's potential is decreased when human intention matches visual stimulation. Motivated by this fact, we can infer human intention for brain-machine interface by detecting the P300 wave's potential decrease. The P300 wave is recorded from EEG(electroencephalogram) electrodes attached on human brain skull after giving alphabetical stimulation. To detect the potential decrease in P300, firstly we statistically model the P300 wave's negative potential. Then we infer human intention based on maximum likelihood estimation. The proposed method was evaluated on the data recorded from three healthy human subjects. The method achieved an averaging accuracy of 98% from subject k, 90% from subject j and 79.8% from subject h.

• Journal of the Ergonomics Society of Korea
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• v.32 no.1
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• pp.9-16
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• 2013

Objective: The aim of this study is to investigate a trend of human error types observed in a series of verification and validation experiments for an Advanced Control Room(ACR) equipped with Lager Display Panel(LDP), Work Station Flat Panel Display(WS FPD), list type Alarm System(AS), Soft Control(SC) and Computerized Procedure System(CPS). Background: Operator behaviors in a fully computerized control room are quite different from those in a traditional hard-wired control room. Operators in an ACR all together monitor plant status and variables through their own interface system such as LDP and WS FPD, are notified of abnormal plant status through their own list type AS, control the plant through their own SC, and follow the structured procedure through their own CPS whereas operators in a traditional control room only separately do their duty directed by their supervisor. Especially the secondary task such as manipulating the user interface of ACR can be an extra burden to all the operators including the supervisor. Method: The Reason's human error classification method was applied to operators' behavioral data collected from a series of verification and validation experiments where operators showed their plant operational behaviors under a couple of harsh scenarios using the ACR simulator. Results: As operators accustomed to the new ACR system, knowledge or rule based mistakes appearing frequently in the early series of experiments decreased drastically in the latest stage of the series. Slip and lapse types of errors were observed throughout the series of experiments. Conclusion: Education and training can be one of the most important factors for the operators accustomed to the traditional control room to be adapted to the new system and to run the ACR successfully. Application: The results of this study implied that knowledge or rule based mistakes can be reduced by training and education but that lapse type errors might be reduced only through innovative improvement in human-system interface design or teamwork culture design including a new leadership style suitable for ACR.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.85-90
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• 2008

This paper describes the human body learning system using the multi-modal user interface. Through our learning system, students can study about human anatomy interactively. The existing learning methods use the one-way materials like images, text and movies. But we propose the new learning system that includes 3D organ surface models, haptic interface and the hierarchical data structure of human organs to serve enhanced learning that utilizes sensorimotor skills.

• Journal of the Ergonomics Society of Korea
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• v.23 no.4
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• pp.9-21
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• 2004

As menu structure of household appliance is complicated, user's cognitive workload frequently occurs errors. In existing studies, errors didn't present that interpretation for cognitive factors and alternatives, but are only considered as statistical frequency. Therefore, error classification and analysis in tasks is inevitable in usability evaluation. This study classified human error throughout information process model and navigation behavior. Human error is defined as incorrect decision and behavior reducing performance. And navigation is defined as unrelated behavior with target item searching. We searched and analyzed human errors and its causes as a case study, using mobile phone which could control appliances in near future. In this study, semantic problems in menu structure were elicited by SAT. Scenarios were constructed by those. Error analysis tests were performed twice to search and analyze errors. In 1st prototype test, we searched errors occurred in process of each scenario. Menu structure was revised to be based on results of error analysis. Henceforth, 2nd Prototype test was performed to compare with 1st. Error analysis method could detect not only mistakes, problems occurred by semantic structure, but also slips by physical structure. These results can be applied to analyze cognitive causes of human errors and to solve their problems in menu structure of electronic products.