• Journal of Institute of Control, Robotics and Systems
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• v.10 no.11
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• pp.1044-1051
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• 2004

This paper described a novel locomotion interface that can generate infinite floor for various surface, named as virtual walking machine. This interface allows users to participate in a life-like walking experience in virtual environments, which include various terrains such as plains, slopes and stair ground surfaces. The interface is composed of two three-DOF (X, Y, Yaw) planar devices and two four-DOF (Pitch, Roll, Z, and relative rotation) footpads. The planar devices are driven by AC servomotors for generating fast motions, while the footpad devices are driven by pneumatic actuators for continuous support of human weight. To simulate natural human walking, the locomotion interface design specification are acquired based on gait analysis and each mechanism is optimally designed and manufactured to satisfy the given requirements. The designed locomotion interface allows natural walking(step: 0.8m, height: 20cm, load capability: 100kg, slope:30deg) for various terrains.

• Tribology and Lubricants
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• v.36 no.6
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• pp.307-314
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• 2020

In this paper, studies on application cases of machine condition monitoring using oil sensors are reviewed. Owing to rapid industrial advancements, maintenance strategies play a crucial role in reducing the cost of downtime and improving system reliability. Consequently, machine condition monitoring plays an important role in maintaining operation stability and extending the period of usage for various machines. Machine condition monitoring through oil analysis is an effective method for assessing a machine's condition and providing early warnings regarding a machine's breakdown or failure. Among the three prevalent methods, the online analysis method is predominantly employed because this method incorporates oil sensors in real-time and has several advantages (such as prevention of human errors). Wear debris sensors are widely employed for implementing machine condition monitoring through oil sensors. Furthermore, various types of oil sensors are used in different machines and systems. Integrated oil sensors that can measure various oil attributes by incorporating a single sensor are becoming popular. By monitoring wear debris, machine condition monitoring using oil sensors is implemented for engines, automotive transmission, tanks, armored vehicles, and construction equipment. Additionally, such monitoring systems are incorporated in aircrafts such as passenger airplanes, fighter airplanes, and helicopters. Such monitoring systems are also employed in chemical plants and power plants for managing overall safety. Furthermore, widespread application of oil condition diagnosis requires the development of diagnostic programs.

• International Journal of Automotive Technology
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• v.7 no.5
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• pp.625-635
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• 2006

From a viewpoint of human factors, automated highway systems(AHS) can be defined as one of the newly developing human-machine systems that consist of humans(drivers and operators), machines(vehicles and facilities), and environments(roads and roadside environments). AHS will require a changed vehicle control process and driver-vehicle interface(DVI) comparing with conventional driving. This study introduces a fixed-based AHS simulator and provides questionnaire-based human factors evaluation results after three kinds of automated driving speed experiences in terms of road configuration, operation policies, information devices, and overall AHS use. In the simulator, the "shared space-at-grade" concept-based road configuration was virtually implemented on a portion of the Kyungbu highway in Korea, and heads-up display(HUD), AHS information display, and variable message signs(VMS) were installed for appropriate AHS DVI implementation. As the results, the subjects expressed positive opinions on the implemented road configuration, operation policies, and the overall use of AHS. The results of this study would be helpful in developing the road configuration and DVI design guideline as the basic human factors research for the future implementation of AHS.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.5
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• pp.434-441
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• 2004

In this paper, an exoskeleton-type motion capturing system is designed and implemented. The device is designed to have 12 degree-of-freedom entirely to represent human arm motions. Forward and inverse kinematics of the device are analyzed to make sure of its singular positions. With the designed model parameters, simulation studies are conducted to verify that the designed motion capturing system is effective to represent human motions within the workspace. As a counterpart of the exoskeleton system, a mobile robot is built to follow human motion restrictively. Experimental studies of teleoperation from the exoskeleton device to control the mobile robot are carried out to show feasible application of wireless man-machine interface.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.109-126
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• 2023

Early detection of forest fires is essential in preventing large-scale forest fires. Predicting forest fires serves as a vital early detection method, leading to various related studies. However, many previous studies focused solely on climate and geographic factors, overlooking human factors, which significantly contribute to forest fires. This study aims to develop forest fire prediction models that take into account human, weather and geographical factors. This study conducted a comparative analysis of four machine learning models alongside the logistic regression model, using forest fire data from Gangwon-do spanning 2003 to 2020. The results indicate that XG Boost models performed the best (AUC=0.925), closely followed by Random Forest (AUC=0.920), both of which are machine learning techniques. Lastly, the study analyzed the relative importance of various factors through permutation feature importance analysis to derive operational insights. While meteorological factors showed a greater impact compared to human factors, various human factors were also found to be significant.

• ICROS
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• v.20 no.2
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• pp.39-45
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• 2014

얼굴 표정 인식은 인간 중심의 human-machine 인터페이스의 가장 중요한 요소 중 하나이다. 현재의 얼굴 표정 인식 기술은 주로 얼굴 영상을 이용하여 특징을 추출하고 이를 미리 학습시킨 인식 모델을 통하여 각 감정의 범주로 분류한다. 본 논문에서는 이러한 얼굴 표정 인식 기술에 사용되는 표정 특징 추출 기법과 표정 분류 기법을 설명하고, 각 기법에서 많이 사용되고 있는 방법들을 간략히 정리한다. 또한 각 기법의 특징들을 나열하였다. 또한 실제적 응용을 위해서 고려해야할 사항들에 대하여 제시하였다. 얼굴 표정 인식 기술은 인간 중심의 human-machine 인터페이스를 제공할 뿐만 아니라 로봇 분야에서도 활용 가능할 것으로 전망한다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.653-659
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• 1994

Human experts have the various own knowledges to be applied in specialized domains. The fact that knowledge itself becomes more critical in the context of textile knowledge with rapid development of new fibers, automated equipments, processes and applications. Diversity of worsted spun yarns, lack of human expertise, and inconsistency among manually generated process plans in consequency of adjustment machine parameters owing to change up raw materials frequently increase the necessity of developing computer aided process planning(CAPP) systems for spinning process. Expert systems offer one of techniques to develop CAPP systems which would behave in a knowledgeable manner. Expert systems are the problem-solving computer program that can reach a level of performance comparable to that of a human expert in some specialized problem domain. This paper is described as job justification module. The job justification module performs to consult with users on which worsted spun yarn manufacturing process planning under the various factors, e.g., raw materials, machine parameters and required yarn counts. Also, the developed module informs the various knowledges relevant process planning. The job justification module offers the control parameters at each process and includes the various standard process plans as database. These knowledges are generated by facts and rules within rule bases.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.146-149
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• 2003

This paper proposes the concept of “Artificial Emotion”(AE). The goal of AE is simulation, extension and expansion of natural emotion, especially human emotion. The object of AE is machine emotion and emotion machine. The contents of AE are emotion recognition, emotion measurement, emotion understanding emotion representation emotion generation, emotion processing, emotion control and emotion communication. The methodology, technology, scientific significance and application value of artificial emotion are discussed

• Journal of the Ergonomics Society of Korea
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• v.12 no.1
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• pp.57-73
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• 1993

In this paper, methods of human figure representation in computer graphics are described. Many applications of the human figure representation are found in areas including industry, advertisement, and cartoon production and further research for the methods that show the human figure more realistically is ex- pected. Two analytic methods for human model, kinematics and dynamics, are ex- plained and the characteristics of the man-machine interface systems that include human figure representation are presented. Various techniques of the human figure representation based on kinematics or(and) dynamics are discussed and representation methods of human body segments such as hand, face, spine are introduced in this paper.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.12
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• pp.1186-1191
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• 2007

Human driver monitoring system is one of the most important systems for the safety in driving vehicles, and therefore driver assistance system has gained much attention during the last decade. This paper proposed an intelligent driver assistance system which monitors human driver's states from bio-signals such as ECG and Blood Pressure. The proposed system used mamdani fuzzy inference to evaluate the driver's mental strain and generated warning signals to the driver. The approach using bio-signals in driver assistance system is the main issue of the related systems and the preliminary results showed the possibility of further research topics in developing more intelligent embedded systems with bio-signal feedback.