• Progress in Medical Physics
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• v.12 no.2
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• pp.141-146
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• 2001

It is well known that assurance of the radiation therapy needs for an accuracy of $\pm$ 5 % in the delivery of an absorbed dose to target volume. Therefore, the dose evaluation of brachytherapy source and/or linear accelerate beam must be a stability with accuracy. In an advanced country, they recommended to use the radioactive check source for reference air ionization chamber for a stable response of radiation field chamber. In this experiments, the radioactive source Sr-90 and PR-05 air ionization chamber were used for standard source and reference ion chamber. The response of reference ion chamber showed as an 1.000$\pm$ 0.010 uncertainty for 10 years long and the evaliuation f dose discrepancy of clinical field ion chamber showed as 0.997 $\pm$0.011 in a $^{60}$ Co brachytherapy soruce. In our experiments, we can assuarance the long halflife standard source is reliable to preserve the calibration factor of reference chamber in stability.

• Journal of the Ergonomics Society of Korea
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• v.36 no.4
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• pp.267-280
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• 2017

Objective: The aim of this study is to investigate key user experience factors of interactions for Head Mounted Display (HMD) devices in the Virtual Reality Environment (VRE). Background: Virtual reality interaction research has been conducted steadily, while interaction methods and virtual reality devices have improved. Recently, all of the virtual reality devices are head mounted display based ones. Also, HMD-based interaction types include Remote Controller, Head Tracking, and Hand Gesture. However, there is few study on usability evaluation of virtual reality. Especially, the usability of HMD-based virtual reality was not investigated. Therefore, it is necessary to study the usability of HMD-based virtual reality. Method: HMD-based VR devices released recently have only three interaction types, 'Remote Controller', 'Head Tracking', and 'Hand Gesture'. We search 113 types of research to check the user experience factors or evaluation scales by interaction type. Finally, the key user experience factors or relevant evaluation scales are summarized considering the frequency used in the studies. Results: There are various key user experience factors by each interaction type. First, Remote controller's key user experience factors are 'Ease of learning', 'Ease of use', 'Satisfaction', 'Effectiveness', and 'Efficiency'. Also, Head tracking's key user experience factors are 'Sickness', 'Immersion', 'Intuitiveness', 'Stress', 'Fatigue', and 'Ease of learning'. Finally, Hand gesture's key user experience factors are 'Ease of learning', 'Ease of use', 'Feedback', 'Consistent', 'Simple', 'Natural', 'Efficiency', 'Responsiveness', 'Usefulness', 'Intuitiveness', and 'Adaptability'. Conclusion: We identified key user experience factors for each interaction type through literature review. However, we did not consider objective measures because each study adopted different performance factors. Application: The results of this study can be used when evaluating HMD-based interactions in virtual reality in terms of usability.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.3
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• pp.232-241
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• 2017

This study was carried out to design the stable elements of the aerial work machinery used in the orchard and farmland which had been conducted in the previous research. A hydraulic lifting lift has been developed to work safely at irregular and inclined locations using an auto leveling system and a horizontal sensor. The development of a centralized controller including remote control has been carried out in order to control the elevated work platform. Through the developed module, we carried out on-site test run to check whether the control is stable in the elevation workbench. Through the structural analysis of the elevation workbench, the maximum load and the equal load amount that the worker can safely work on the workbench are presented.

• The Journal of Society for e-Business Studies
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• v.17 no.4
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• pp.1-16
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• 2012

Shieh and Wang [10] recently proposed an efficient mutual authentication scheme that combined the cost-effectiveness of operations of Lee et al. [6]. scheme and the security and key agreement of Chen and Yeh scheme. Shieh and Wang [10] scheme, however, does not satisfy the security requirements against a third party (the man-in the middle, attacker) that have to be considered in remote user authentication scheme using password-based smart cards. Shieh and Wang weaknesses are the inappropriateness that it cannot verify the forged message in 3-way handshaking mutual authentication, and the vulnerability that the system (server) secret key can easily be exposed. This paper investigates the problems of Shieh and Wang scheme in the verification procedure of the forged messages intercepted by the eavesdrop. An enhanced two-way remote user authentication scheme is proposed that is safe and strong against multiple attacks by adding the ability to perform integrity check on the server and proposed scheme is not expose user password information and the system's confidential information.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.117-124
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• 2011

This study was realized the home network system for home care by bio-physical sensor system, to convey for the remote physical signal. The composition condition has four functions of displacement point for a Vision, Somatosensory, Vestibular and CNS that the basic measurement used to a Heart Rate, Temperature, Weight. Physical signal are decided to search a max and min point with adjustment of 0.01 unit in the reference level. There were checked physical condition of body balance to compounded a physical neuroceptor of sensory organ for the measurement such as a Vision, Somatosensory, Vestibular, CNS, BMI. There are to check a health care condition through a combination of physical organ with a posturography of a exercise. The service of home network system can be used to support health care management system through health assistants in health care center and central health care system. It was expected to monitor a physical parameter for the remote control health management system.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.12
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• pp.297-304
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• 2019

The technological advances such as communication, sensor, and artificial intelligence lead smart factory construction. Smart factory aims at efficient process control by utilizing data from the existing automation process and intelligence technology such as machine learning. As a result of constructing smart factory, productivity increases, but costs increase. Therefore, small companies try to make a step-by-step transition from existing process to smart factory. In this paper, we have proposed a remote control system that support data collection, monitoring, and control for manufacturing equipment to support the construction of CNC cutting machine based small-scale smart factory. We have proposed the structure and design of the proposed system and efficient sensing data transmission scheme. To check the feasibility, the system was implemented for CNC cutting machine and functionality verification was performed. For performance evaluation, the web page access time was measured. The results means that the implemented system is available level.

• Journal of the Korean Society of Radiology
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• v.15 no.6
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• pp.795-801
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• 2021

The designed drone-based unmanned remote radiation detection module was developed according to the needs of the nuclear power plant decommissioning workshop. Using the Geiger-Mueller tube sensitive to low-level radiation measurement, It was manufactured to measure the amount of radiation leaking into and out of the containment vessel. The drone-based radiation detection module weighs less than 200g, It can be operated inside and outside the containment vessel of a nuclear power plant. To check the performance of the designed equipment, a performance evaluation test was conducted with reference to the international standard (IEC-60864). The stability of the radiation detection module designed to meet the needs of the field the statistical rate of change by repeated measurements in the rate of change experiment to evaluate the measurement accuracy was ±4.6%. The accuracy ±7.3% in the linearity experiment to evaluate the dose rate dependence, the linear The figure satisfies the international performance evaluation standard of ±3.5%. The radiation detection module developed in this study is a customized equipment for a nuclear power plant dismantling workshop. It will be helpful for accurate measurement of space dose rate and safety management of radiation worksites in sites with a lot of radiation dust.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.559-570
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• 2022

When a satellite image has low spatial resolution, it is difficult to detect small objects. In this research, we aim to check the effect of super resolution on object detection. Super resolution is a software method that increases the resolution of an image. Unpaired super resolution network is used to improve Sentinel-2's spatial resolution from 10 m to 3.2 m. Faster-RCNN, RetinaNet, FCOS, and S²ANet were used to detect vessels in the Sentinel-2 images. We experimented the change in vessel detection performance when super resolution is applied. As a result, the Average Precision (AP) improved by at least 12.3% and up to 33.3% in the ship detection models trained with the super-resolution image. False positive and false negative cases also decreased. This implies that super resolution can be an important pre-processing step in object detection, and it is expected to greatly contribute to improving the accuracy of other image-based deep learning technologies along with object detection.

• Korean Journal of Remote Sensing
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• v.39 no.4
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• pp.371-393
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• 2023

Crack detection in structures plays a vital role in ensuring their safety, durability, and reliability. Traditional crack detection methods sometimes need significant manual inspections, which are laborious, expensive, and prone to error by humans. Deep learning algorithms, which can learn intricate features from large-scale datasets, have emerged as a viable option for automated crack detection recently. This study presents an in-depth review of crack detection methods used till now, like image processing, traditional machine learning, and deep learning methods. Specifically, it will provide a comparative analysis of crack detection methods using deep learning, aiming to provide insights into the advancements, challenges, and future directions in this field. To facilitate comparative analysis, this study surveys publicly available crack detection datasets and benchmarks commonly used in deep learning research. Evaluation metrics employed to check the performance of different models are discussed, with emphasis on accuracy, precision, recall, and F1-score. Moreover, this study provides an in-depth analysis of recent studies and highlights key findings, including state-of-the-art techniques, novel architectures, and innovative approaches to address the shortcomings of the existing methods. Finally, this study provides a summary of the key insights gained from the comparative analysis, highlighting the potential of deep learning in revolutionizing methodologies for crack detection. The findings of this research will serve as a valuable resource for researchers in the field, aiding them in selecting appropriate methods for crack detection and inspiring further advancements in this domain.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.113-117
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• 2004

Such social structures as bridges, buildings, dams and towers have been transformed by their own load or fundamental ground. They have been behaved by other external causes. These regular or irregular behaviors threaten to do their users safety. Therefore, to monitor the load of the structures or reaction shown by them could help to verify their behaviors. RTK GPS allows the use of a static base station and remote rover unit to allow for data collection within several seconds and in real time. It is useful for monitoring the behaviors of massive structures like bridges. In this Study, Among GPS methods, we used RTK GPS to analyze the precision of monitoring and then on the basis of it, we developed a monitoring system using RTK GPS when measured the behavior of main tower of a suspension bridge by using RTK GPS. Comparing a deviation between observation values, X axis was 1mm, Y axis was 1mm and Z axis 2.2mm. It turned out that it was possible to monitor and measure structures by RTK GPS.