• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.771-778
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• 2004

Recently, various applications of robot system become more popular in accordance with rapid development of computer hardware/software, artificial intelligence, and automatic control technology. Formerly robots mainly have been used in industrial field, however, nowadays it is said that the robot will do an important role in the home service application. To make the robot more useful, we require further researches on implementation of natural communication method between the human and the robot system, and autonomous behavior generation. The gesture recognition technique is one of the most convenient methods for natural human-robot interaction, so it is to be solved for implementation of intelligent robot system. In this paper, we describe the state-of-the-art of advanced gesture recognition technologies for intelligent robots according to three methods; sensor based method, feature based method, appearance based method, and 3D model based method. And we also discuss some problems and real applications in the research field.

• Journal of Mechanical Science and Technology
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• v.18 no.12
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• pp.2069-2079
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• 2004

This paper represents the description of a complex mathematical model of biomechanical interaction for human-rifle system during shooting. The model is developed by finite element method using bar elements. And three typical shooting positions, i.e. standing, kneeling and prone are used. Characteristics of interior/exterior ballistics and behaviors of human-rifle system are evaluated by this model, which takes into account the influence of environment, bullet, powder, barrel geometry parameters and anthropological parameters. The results of this study can be applied to anthropology, biomechanics, medical science, gait analysis, interior ballistics and exterior ballistics.

• Journal of Sensor Science and Technology
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• v.21 no.1
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• pp.28-33
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• 2012

The visual sensing of human hands plays an important part in many man-machine interaction/interface systems. Most existing visionbased hand detection techniques depend on the color cues of human skin. The RGB color image from a vision sensor is often transformed to another color space as a preprocessing of hand detection because the color space transformation is assumed to increase the detection accuracy. However, the actual effect of color space transformation has not been well investigated in literature. This paper discusses a comparative evaluation of the pixel classification performance of hand skin detection in four widely used color spaces; RGB, YIQ, HSV, and normalized rgb. The experimental results indicate that using the normalized red-green color values is the most reliable under different backgrounds, lighting conditions, individuals, and hand postures. The nonlinear classification of pixel colors by the use of a multilayer neural network is also proposed to improve the detection accuracy.

• Anxiety and mood
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• v.1 no.1
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• pp.3-6
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• 2005

Several contributing factors have been proposed for expression of excessive anxiety. Behavioral inhibition, activation of amygdala, and genetic vulnerability interchangeably affect each other. Only few studies have addressed the differences and similarities in anxiety between animal and human. The consensus is that individual vulnerability is a main factor for the expression of anxiety, although the interaction of environmental stressors and biological characteristics is involved in the presentation of anxiety. Further work is required to investigate how the interaction between stress and diathesis can affect responsiveness of stress and anxiety in animal and human. Here, the author reviews the findings regarding differences and similarities in both animal and human studies. Knowing the reciprocal relationship between the environment (stressors) and individual vulnerability or resilience, the proper understanding of anxiety and anxiety disorders would be possible.

• The Journal of Korea Robotics Society
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• v.5 no.3
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• pp.262-269
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• 2010

This paper presents a probabilistic head tracking method, mainly applicable to face recognition and human robot interaction, which can robustly track human head against various variations such as pose/scale change, illumination change, and background clutters. Compared to conventional particle filter based approaches, the proposed method can effectively track a human head by regularizing the sample space and sequentially weighting multiple visual cues, in the prediction and observation stages, respectively. Experimental results show the robustness of the proposed method, and it is worthy to be mentioned that some proposed probabilistic framework could be easily applied to other object tracking problems.

• Nuclear Engineering and Technology
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• v.36 no.5
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• pp.430-449
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• 2004

A quantitative model for a control system that integrates human operators, systems, and their interactions is developed based on discrete functions. After identifying the major entities and the key factors that are important to each entity in the control system, a quantitative analysis to estimate the recovery failure probability from an abnormal state is performed. A numerical analysis based on assumed values of related variables shows that this model produces reasonable results. The concept of 'relative sensitivity' is introduced to identify the major factors affecting the reliability of the control system. The analysis shows that the hardware factor and the design factor of the instrumentation system have the highest relative sensitivities in this model. T도 probability of human operators performing incorrect actions, along with factors related to human operators, are also found to have high relative sensitivities. This model is applied to an analysis of the TMI-2 nuclear power plant accident and systematically explains how the accident took place.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.152-158
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• 2022

As various mobile robots and manipulator robots have been commercialized, robots that can be used by individuals in their daily life have begun to appear. With the development of robots that support daily life, the interaction between robots and humans is becoming more important. Manipulator robots that support daily life must perform tasks such as pressing buttons or picking up objects safely. In many cases, this requires expensive multi-axis force/torque sensors to measure the interaction. In this study, we introduce a low-cost two-axis pressure sensor that can be applied to manipulators for education or research. The proposed system used three force sensitive resistor (FSR) sensors and the structure was fabricated by 3D printing. An experimental device using a load cell was constructed to measure the biaxial pressure. The manufactured prototype was able to distinguish the +-x-axis and the +-y-axis pressures.

• The Journal of Korea Robotics Society
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• v.18 no.2
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• pp.203-215
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• 2023

Social robots, which are mainly used by individuals, emphasize the importance of human-robot relationships (HRR) more compared to other types of robots. Emotional expression in robots is one of the key factors that imbue HRR with value; emotions are mainly expressed through the face. However, because of cultural and preference differences, the desired robot facial expressions differ subtly depending on the user. It was expected that a robot facial expression customization tool may mitigate such difficulties and consequently improve HRR. To prove this, we created a robot facial expression customization tool and a prototype robot. We implemented a suitable emotion engine for generating robot facial expressions in a dynamic human-robot interaction setting. We conducted experiments and the users agreed that the availability of a customized version of the robot has a more positive effect on HRR than a predefined version of the robot. Moreover, we suggest recommendations for future improvements of the customization process of robot facial expression.

• The Journal of Korea Robotics Society
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• v.18 no.4
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• pp.419-426
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• 2023

Assembly tasks are difficult to fully automate due to uncertain errors occurring in unstructured environments. When assembling parts such as electrical connectors, advances in grasping and assembling technology have made it possible for the robot to assemble the connectors without the aid of humans. However, some parts with tight assembly tolerances should be assembled by humans. Therefore, task sharing with human-robot interaction is emerging as an alternative. The goal of this concept is to achieve shared autonomy, which reduces the efforts of humans when carrying out repetitive tasks. In this study, a task-sharing robotic system for assembly process has been proposed to achieve shared autonomy. This system consists of two parts, one for robotic grasping and assembly, and the other for monitoring the process for robot-human task sharing. Experimental results show that robots and humans share tasks efficiently while performing assembly tasks successfully.

• Korean Journal of Human Ecology
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• v.16 no.6
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• pp.1169-1183
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• 2007

The purpose of this research is to explore the strategy of teacher and the strategy of child in teacher-child interaction according to related variables. The participants of this research are 2 classroom teachers and their 54 5-year-old kindergarten children(27 boys and 27 girls). To collect the data, child's classroom activities were observed and videotaped using event sampling 90 times(30 times per beginning, middle, and end). Repeated test, two-way ANOVA, Scheffe test used for data analysis. The results of this research were as followed; First, over time there were differences between strategies of teacher and strategies of child during teacher-child interaction. Second, in child variables there were differences in strategies of teacher and strategies of child during teacher-child interaction according to child's gender. Third, in environment variables there were differences between strategies of teacher and strategies of child according to play rules and play areas.