• Journal of the Ergonomics Society of Korea
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• v.16 no.3
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• pp.77-87
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• 1997

This paper describes the developement of a Design Issue Management System (DIMS). Although human factors engineering has been recognized as one of the critical activities in the design of man-machine system, it has been hardly successful nor effective in practice to cope with the hyman factors requirements by regulations. For supporting the human factors engineering in nuclear power plants, DIMS ahs three major modules : Design Requirements Data Base, Design Issue Tracking System, Issue Evaluation Support System. These modules function as formal verification architects that the licensing authority requests for verifying the safety of the equip- ment and facilities in nuclear power plants. An example application to an operator support system, named Critical Function Monitoring System, during its independent review of the human factors shows the usage and the benefit of DIMS.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.261-270
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• 1999

Sintering transforms powdered ore into lumped ore so that the latter can be used in a blast furnace. The powdered or combined with coke and other materials is loaded into a container and moved along by a pallet while the ignited coke burns. The speed by which the pallet moves determines how much sintering takes place. Since the process is complicated and lacks an accurate mathematical model, human operators manually control the speed by monitoring various factors in the plant. In this paper, we propose a neural network-based pallet speed controller which copies human operator knowledge. Actual process data were collected from a sintering plant for eight months and preprocessed to remove noisy and inconsistent data. A multilayer perceptron was trained using a back-propagation learning algorithm. In on-line testing at the sinter plant, the proposed model reliably controlled pallet speed during normal operation without the help of human operators. Moreover, the quality and productivity was as good as with human operators.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.5
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• pp.25-34
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• 2021

Increase in avian species richness is one of the important issues of urban biodiversity policies, since it can promote diverse ecosystem services such as seed dispersal, education, and pollination. However, though human disturbance can significantly affect avian species richness, there are limited studies on the way to reflect the dynamics of floating population. Therefore, this study analyzed the spatial relationship between avian species richness, floating population, and vegetation cover using telecommunications information to identify the areas that requiring targeted monitoring and restoration action. Bivariate Local Moran's I was applied to identify LISA cluster map that showing representative biotopes, which reflect significant spatial relationship between species richness and population distribution. Edge density and distribution of ndvi were identified for evaluating relative adequacy of selected biotopes to strengthen the robust biodiversity network. This study offers insight to consider human disturbance in spatial context using innovative big data to increase the effectiveness of urban biodiversity measures.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.683-691
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• 2019

In this paper, we propose a novel method to quantify the neural synchronization between subjects in the collaborative process through electroencephalogram (EEG) hyperscanning. We hypothesized that the neural synchronization in EEGs will increase when the communication of the operators is smooth and the teamwork is better. We quantified the EEG signal for multiple subjects using a representative EEG quantification method, and studied the changes in brain activity occurring during collaboration. The proposed method quantifies neural synchronization between subjects through bispectral analysis. We found that phase synchronization between EEGs of multi subjects increased significantly during the periods of collaborative work. Traditional methods for a human error analysis used a retrospective analysis, and most of them were analyzed for an unspecified majority. However, the proposed method is able to perform the real-time monitoring of human error and can directly analyze and evaluate specific groups.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.131-139
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• 2021

In current time, anomaly detection is the primary concern of the administrative authorities. Suspicious activity identification is shifting from a human operator to a machine-assisted monitoring in order to assist the human operator and react to an unexpected incident quickly. These automatic surveillance systems face many challenges due to the intrinsic complex characteristics of video sequences and foreground human motion patterns. In this paper, we propose a novel approach to detect anomalous human activity using a hybrid approach of statistical model and Genetic Programming. The feature-set of local motion patterns is generated by a statistical model from the video data in an unsupervised way. This features set is inserted to an enhanced Genetic Programming based classifier to classify normal and abnormal patterns. The experiments are performed using publicly available benchmark datasets under different real-life scenarios. Results show that the proposed methodology is capable to detect and locate the anomalous activity in the real time. The accuracy of the proposed scheme exceeds those of the existing state of the art in term of anomalous activity detection.

• Journal of Auto-vehicle Safety Association
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• v.14 no.3
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• pp.71-76
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• 2022

In autonomous driving cars, 3D pose estimation can be one of the effective methods to enhance safety control for OOP (Out of Position) passengers. There have been many studies on human pose estimation using a camera. Previous methods, however, have limitations in automotive applications. Due to unexplainable failures, CNN methods are unreliable, and other methods perform poorly. This paper proposes robust real-time multi-human 3D pose estimation architecture in vehicle using monocular RGB camera. Using particle filter, our approach integrates CNN 2D/3D pose measurements with available information in vehicle. Computer simulations were performed to confirm the accuracy and robustness of the proposed algorithm.

• 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.

• Analytical Science and Technology
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• v.15 no.5
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• pp.410-416
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• 2002

In this study, a new quantitative analytical method has been developed for the rapid determination of vancomycin in human plasma and urine using liquid chromatography/tandem mass spectrometry (LC - MS/MS). Chromatography was carried out on a $C_{18}$ XTerra MS column ($2.1{\times}30mm$) with a particle size of $3.5{\mu}m$. The mobile phase was 0.25% formic acid in 10% acetonitrile and the flow rate was $250{\mu}L/min$. Vancomycin and caffeine (internal standard) were detected by MS/MS using multiple reaction monitoring (MRM). Vancomycin gives a predominant doubly protonated precursor molecule ($[M+2H]^{2+}$) at m/z 725.0 and a corresponding product ion of m/z 100.0. Detection of vancomycin was good, accurate and precise, with a limit of detection of 1 nM in plasma. The calibration curves for vancomycin in human plasma was linear in a concentration range of $0.01{\mu}M$ - $100{\mu}M$ for plasma. This method has been successfully applied to determine the concentration of vancomycin in human plasma and urine from pharmacokinetic study and relative studies.

• Polymer(Korea)
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• v.30 no.6
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• pp.572-575
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• 2006

In this work, a variety of polymer based jelly phantoms suitable for the hyperthermia operations to human organs was synthesized in order to confirm the possibility of auxiliary cancer therapy. Specifically, using an appropriate material composition including polyethylene, Jelly phantoms for brain was prepared and characterized their electrical properties suitable for the monitoring the effect of electromagnetic wave from code division multiple access (CDMA) and personal communication service (PCS) on the human body. In the future, after injection of ferromagnetic nanoparticle into the jelly phantoms, new approach to propose the cancer therapy can be anticipated by monitoring the degree of temperature rise in human body using the photograph of Infrared camera.

• Journal of Sensor Science and Technology
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• v.31 no.6
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• pp.423-427
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• 2022

A pressure sensor that mimics the sensing ability of human skin has emerged as high-profile technology because it shows remarkable applications in numerous fields such as robotics, human health monitoring, and artificial prosthetics. Whereas recent pressure sensors have achieved high sensitivity similar to that of human skin, they still show limited detection bandwidth. Moreover, once these e-skin are fabricated, their sensitivity and stiffness are fixed; therefore, they can be used for only limited applications. Our study proposes a new adaptive pressure sensor built with uniform gallium microdroplet-elastomer composite. Based on the phase transition of gallium microdroplets, the proposed sensor undergoes mode transformation, enabling it to have a higher sensitivity and wider detection bandwidth compared with those of human skin. In addition, we succeeded in extending a single adaptive pressure sensor to sensor arrays based on its high uniformity, reproducibility, and large-scale manufacturability. Finally, we designed an adaptive e-skin with the sensor array and demonstrated its applications on health monitoring tasks including blood pulse and body weight measurements.