• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1681-1686
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• 1991

In robotics and other fields of engineering, techniques for artificial reality or virtual reality are focused on and studied extensively, e.g., virtual existence for tele-operator systems in robotics, and virtual reality of designed objects in architecture. In order to realize the system we should create physical stimulations according to internal models created by experiences in a human brain. The internal model does not have to have direct connections to the real world, however, the stimulation must be signals such that the internal model are retrieved in a human brain. In this paper we propose a technique for tele-virtual reality of dynamic mechanical models, which means that one dynamic mechanical model can be shared by peoples in distant places. Since a stability issue due to time delays arises in the system, we employed a scattering technique developed for a tele-operator system and a kind of passive adaptive controllers. Furthermore, restrictions due to a simple digital implementation of the scattering transformation are discussed and some conditions for stability are shown. The proposed method is applied to a remote tug of war system and the effectiveness is verified.

• Journal of Korea Multimedia Society
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• v.14 no.9
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• pp.1210-1220
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• 2011

In this paper, we suggest a haptic mouse system as an immersive interface between virtual environment and a human operator. The proposed haptic mouse creates vibrotacitle and thermal sensation to increase the immersion. The vibrotactile module is composed of eccentric motors and a solenoid actuator, and the thermal module consists of a thin-film resistance temperature detector and a Peltier thermoelectric heat pump. In order to evaluate the proposed haptic mouse system, we develop a simple racing game and conduct an experiment. The result of the experiment shows that the proposed haptic mouse system can improve the sense of reality in virtual environment and can be used as an effective interface between virtual environment and a human operator.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.1129-1134
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• 1989

In this paper, we propose a neural network for learning to control semi-linear dynamical systems. The network is a composite system of four three-layer backpropagation subnetworks, and is able to control inverted pendulums better than systems based on modern control theory at least in some ranges of parameters. Three of the four subnetworks in our network system process angles, velocities, and positions of a moving inverted pendulum, respectively. The outputs from those three subnetworks are input to the remaining subnetwork that makes control decisions. Each of the four subnetworks learns connection weights independently by backpropagation algorithms. Teaching signals are given by the human operator. Also, input signals are generated by the human operator, but they are converted by preprocessors to actual input data for the three subnetworks except for the network for control decisions. The whole system is implemented on both of 16 bit personal computers and 32 bit workstations. First, we briefly provide the research background and the inverted pendulum problem itself, followed by the description of our composite neural network model. Next, some results from the simulation are given, which are subsequently compared with the results from a control system based on modern control theory. Then, some discussions and conclusion follow.

• Journal of Biomedical Engineering Research
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• v.17 no.1
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• pp.109-120
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• 1996

Cardiac function is evaluated quantitatively using angiographic images via the analysis of the shape change or the heart wall boundaries. To kin with, boundary defection or ESLV(End Systolic Lert Ventricular) and EDLV(End Diastolic Left Ventricular) is essential for the quantitative analysis of cardiac function. The boundary detection methods proposed in the past were almost semi-automatic. Intervention by a knowledgeable human operator was still required Of con, manual tracing of the boundaries is currently used for subsequent analysis and diagnosis. This method would not cut excessive time, labor, and subjectivity associated with manual intervention by a human operator. EDLV images have noncontiguous and ambiguous edge signal on some boundary regions. In this paper, we propose a new method for automated detection of boundaries in noncontiguous and ambiguous EDLV images. The boundary detection scheme which based on a priori knowledge information is divided into two steps. The first step is to detect the candidate edge points of EDLV using ESLV boundaries. The second step is to correct detected boundaries of EDLV using the LV shape. We developed the algorithm of modifying EDLV boundaries defined adaptive modifier. We experimented the method proposed in this paper and compared our proposed method with the manual method in detecting boundaries of EDLV. In the areas within estimated boundaries of EDLV, the percentage of error was about 1.4%. We verified the useflilness and obtained the satisfying results througll the experiments of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.877-882
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• 2016

Disaster robots have accepted tele-operation in order to share the intelligence of human operators and robot systems. Virtual wall is one of the tele-operation technology to support recognition of human operator. If the virtual wall can block the robot from dangers, the operator will feel comfortable and can concentrate on fundamental missions. In this paper, we proposes and compares three methods for virtual wall visualization in tele-operation using 3D reconstruction. First is a virtual wall visualized only with edges. A wall filled with transparent color is the second method. Finally, third method is a texture-mapped virtual wall. In the experiments, we discuss their merits and demerits in view of robot tele-operation.

• Journal of the Korea Safety Management & Science
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• v.25 no.3
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• pp.17-22
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• 2023

As the importance of artificial intelligence grows rapidly and emerges as a leader in technology, it is becoming an important variable in the next-generation industrial system along with the robot industry. In this study, a safety system was developed using deep learning technology to provide worker safety in a robot workplace environment. The implemented safety system has multiple cameras installed with various viewing directions to avoid blind spots caused by interference. Workers in various scenario situations were detected, and appropriate robot response scenarios were implemented according to the worker's risk level through IO communication. For human detection, the YOLO algorithm, which is widely used in object detection, was used, and a separate robot class was added and learned to compensate for the problem of misrecognizing the robot as a human. The performance of the implemented system was evaluated by operator detection performance by applying various operator scenarios, and it was confirmed that the safety system operated stably.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.1
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• pp.20-27
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• 2024

Determining the number of operators who set up the machines in a human-machine system is crucial for maximizing the benefits of automated production machines. A man-machine chart is an effective tool for identifying bottlenecks, improving process efficiency, and determining the optimal number of machines per operator. However, traditional man-machine charts are lacking in accounting for idle times, such as interruptions caused by other material handling equipment. We present an adjusted man-machine chart that determines the number of machines per operator, incorporating idleness as a penalty term. The adjusted man-machine chart efficiently deploys and schedules operators for the hole machining process to enhance productivity, where operators have various idle times, such as break times and waiting times by forklifts or trailers. Further, we conduct a simulation validation of traditional and proposed charts under various operational environments of operators' fixed and flexible break times. The simulation results indicate that the adjusted man-machine chart is better suited for real-world work environments and significantly improves productivity.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.32 no.1
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• pp.1-9
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• 2024

The unmanned aerial vehicle industry has developed a lot, but the possibility of accidents is increasing due to potential risks. In this study, SHELL models and HFACS were used to analyze unmanned aerial vehicle accidents in the UK and to identify the main causes and characteristics of accidents. The main cause analyzed by the SHELL model was identified as an abnormality in the alarm system. The main cause of the accident analyzed by HFACS was identified as the technical environment. The common cause identified by the SHELL model and HFACS was identified as a mechanical problem of unmanned aerial vehicles. This is due to the lack of accurate information or functionality of the alarm system in the operator interface, which often prevents the operator from responding to sensitive information. Therefore, in order to prevent civil UAV accidents, the stability and reliability of the system must be secured through regular inspections of the UAV system and continuous software updates. In addition, an ergonomic approach considering human interfaces is needed when developing technologies.

• Journal of the Ergonomics Society of Korea
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• v.21 no.3
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• pp.13-24
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• 2002

Reduction and prevention of human error is one of the major interests for the enhancement of system safety and availability in Nuclear Power Plants (NPPs). As human beings have become the weak point in the system safety, a systematic evaluation on human performance during emergency situation should be performed in advance to identify the potential vulnerability of human tasks. Though the data gathering and analysis from real field is an important precondition, there were no available data in nuclear field of korea. This paper presents the result of human performance analysis on emergency tasks in NNPs. Firstly, a task analysis was performed to identify the characteristics of operator tasks during emergency condition and to classify them into a set of generic emergency tasks. Secondly, simulation data were collected and analyzed for the emergency tasks using the full scope simulator of Younggwang NPPs. The analyzed human performance information cover the event diagnosis time, the execution time of each procedural step, observation parameters, typer of irrelevant response, pattern of communication among staffs, and so on. These performance data would be used for human reliability analysis and the research of human error as technical bases.

• Nuclear Engineering and Technology
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• v.41 no.3
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• pp.247-270
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• 2009

This paper reviews studies on information searching behavior in process control systems and discusses some implications learned from previous studies for use in human factors studies on nuclear power plants (NPPs) main control rooms (MCRs). Information searching behavior in NPPs depends on expectancy, value, salience, and effort. The first quantitative scanning model developed by Senders for instrument panel monitoring considered bandwidth (change rate) of instruments as a determining factor in scanning behavior. Senders' model was subsequently elaborated by other researchers to account for value in addition to bandwidth. There is also another type of model based on the operator's situation awareness (SA) which has been developed for NPP application. In these SA-based models, situation-event relations or rules on system dynamics are considered the most significant factor forming expectancy. From the review of previous studies it is recommended that, for NPP application, (1) a set of symptomatic information sources including both changed and unchanged symptoms should be considered along with bandwidth as determining factors governing information searching (or visual sampling) behavior; (2) both data-driven monitoring and knowledge-driven monitoring should be considered and balanced in a systematic way; (3) sound models describing mechanisms of cognitive activities during information searching tasks should be developed so as to bridge studies on information searching behavior and design improvement in HMI; (4) the attention-situation awareness (A-SA) modeling approach should be recognized as a promising approach to be examined further; and (5) information displays should be expected to have totally different characteristics in advanced control rooms. Hence much attention should be devoted to information searching behavior including human-machine interface (HMI) design and human cognitive processes.