• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.861-869
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• 2023

This article proposes a novel approach to measure the performance of Safety-Critical Systems (SCS). Such systems contain multiple processing nodes that communicate with each other is modeled by a Petri nets (PN). The paper uses the PN for the performance evaluation of SCS. A set of ordinary differential equations (ODEs) is derived from the Petri net model that represent the state of the system, and the solutions can be used to measure the system's performance. The proposed method can avoid the state space explosion problem and also introduces new metrics of performance, along with their measurement: deadlock, liveness, stability, boundedness, and steady state. The proposed technique is applied to Shutdown System (SDS) of Nuclear Power Plant (NPP). We obtained 99.887% accuracy of performance measurement, which proves the effectiveness of our approach.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.213-220
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• 2024

Fall detection and prevention technologies play a pivotal role in ensuring the well-being of individuals, particularly those living independently, where falls can result in severe consequences. This paper addresses the challenge of accurate and quick fall detection by proposing a Bayesian probability-based measure applied to surface electromyography (sEMG) signals. The proposed algorithm based on a Bayesian filter that divides the sEMG signal into transient and steady states. The ratio of posterior probabilities, considering the inclusion or exclusion of the transient state, serves as a scale to gauge the dominance of the transient state in the current signal. Experimental results demonstrate that this approach enhances the accuracy and expedites the detection time compared to existing methods. The study suggests broader applications beyond fall detection, anticipating future research in diverse human-robot interface benefiting from the proposed methodology.

• Journal of the Korean Society for Heat Treatment
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• v.37 no.2
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• pp.73-78
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• 2024

This study presents a real-time method that uses Laser Absorption Spectroscopy (LAS) to measure exhaust gas temperatures in turbulent flow fields. It was possible to measure temperature by passing a laser beam through the exhaust gas in a grid pattern, and obtain a temperature distribution image through time series analysis at 0.1 second intervals. Temperature image resolution has been improved with CT reconstruction algorithms. Estimating maximum temperature values and locations enabled 2D temperature analysis, surpassing single-point methods like thermocouples. The accuracy of LAS measurements was evaluated by comparison with thermocouple measurements. This approach will contribute to automotive technology and environmental protection by providing reliable temperature data for interpreting turbulent temperature distributions.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.33-42
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• 2020

There has been difficulties in identifying objects by relying on the naked eye in various surveillance systems. There is a growing need for automated surveillance systems to replace soldiers in the field of military surveillance operations. Even though the object detection technology is developing rapidly in the civilian domain, but the research applied to the military is insufficient due to a lack of data and interest. Thus, in this paper, we applied one of deep learning algorithms, Convolutional Neural Network-based binary classification to develop an autonomous identification model of both friend and foe helicopters (AH-64, Mi-17) among the military weapon systems, and evaluated the model performance by considering accuracy, precision, recall and F-measure. As the result, the identification model demonstrates 97.8%, 97.3%, 98.5%, and 97.8 for accuracy, precision, recall and F-measure, respectively. In addition, we analyzed the feature map on convolution layers of the identification model in order to check which area of imagery is highly weighted. In general, rotary shaft of rotating wing, wheels, and air-intake on both of ally and foe helicopters played a major role in the performance of the identification model. This is the first study to attempt to classify images of helicopters among military weapons systems using CNN, and the model proposed in this study shows higher accuracy than the existing classification model for other weapons systems.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.527-534
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• 2017

The purpose of this study is to develop unmanned equipment that can automatically move to the desired point and measure water quality at the correct depth. For this purpose, we constructed a water sampling lift and water sampling container, an unmanned vessel equipped with a VRS-GPS, an acoustic echo sounder, and a water quality sensor. Also, we developed an automatic navigation algorithm and program, an automatic water sampling program, and a water quality map generation program. As a result of the experiment in the detention pond, the unmanned vessel sailed along the planned route with an accuracy of about 93% within the error range of 3m. In addition, the water quality sensor installed in the lift was able to acquire the water quality of the target area in real time and transmit it to the server via wireless Internet, and it was possible to monitor the water quality of each site in real time. Through field experiments, the water sampling lift was able to control the desired length with an accuracy of about 94%. The stretch length accuracy experiment of the water sampling lift was impossible to measure directly in the water, so it was replaced land-based experiment. We also found some unstable problems due to the weight of the water sampling lift and the weight of the air compressor to operate the water container. Except these two problems, we accomplished purpose of this study. An automated water quality measurement method using an unmanned vessel can be used to measure the quality of water in a difficult to access area and to secure the safety of the worker.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.4 no.1
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• pp.19-30
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• 1997

This study was to investigate the method for shortening the body temperature (BT) because it takes a long time and is impractical to measure axillary or oral BT with mercury thermometer, The first approach was to identify BT change according to the measuring time and determine the clinically not statistically avaiable and optimal BT measuring time. The second was to test the accuracy of tympanic thermometer. It can measure BT within a few seconds, so if it is approved accurate, we can save BT measuring time by substitute tympanic thermometer for mercury thermometer. This study was conducted from 1, to 30 June, 1996. The subjects were 12men students of medicalk college and 29 women students of nursing school. The results were as follows ; 1) The 3, 5, 7, 9, 11, 13minute-measured axillary BT and 3, 5, 7, minute-measured BT showed somewhat linear relationship with time. It was difficult to find the optimum measuring time which were clinically significant. 2) For axillary tempeiature, the measuring time which were not statistically different was 11 and 13minute. But the real BT difference between 3 and 13minute, or between 5 and 13minute were very small and was within the range of daily variation. 3) For oral temperature, there was no intervals which showed the statistically insignificant. But like as axillary temperature, the difference between 3 and 7, or 5 and 7 minute were trivial by $0.3^{\circ}C$ and by $0.1^{\circ}C$ respectively. 4) Tympanic temperatures were lower than oral BTs which were measured with mercury thermometer by $0.26^{\circ}C$ (with ear tug) and $0.15^{\circ}C$(without ear tug). 5) The reliability of repeated measure tympanic temperature was better than without ear tug. With above results, we can't determine the optimal and cilically significant oral and axillary measuring time using mercury thermometer. However, because the real differences between measuring times were very small, so we recommend further study for the aged, the infants and the febrile patients. And we can't sure the accuracy of tympanic temperature but the reliability was better with ear tug than without ear tug.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.8
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• pp.682-688
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• 2000

To improve the performance of a flexible robot arm one of the important things is the vibration displacement measurement of a flexible arm. Many types of sensors have been used to measure it, The most popular has been strain gauges which measures the deflection of the beam,. Photo sensors have also been for detecting beam displacement and accelerometers are often used to measure the beam vibration. But the vibration displacement can be obtained indirectly from these sensors. In this article a vision sensor is used as a displacement sensor to measure the vibration displacement of a flexible robot arm. Several schemes are proposed to reduce the image processing time and increase its accuracy. From the experimental results it is seen that the vision sensor can be an alternative sensor for measuring the vibration displacement and has a potential for on-line tip position control of flexible robot systems.

• Journal of Korea Multimedia Society
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• v.22 no.12
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• pp.1404-1414
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• 2019

Educational books commonly use some copyrighted images with various kinds of deformation for helping students understanding. When using several copyrighted images made by merging or editing distortion in legal, we need to pay a charge to original copyright holders for each image. In this paper, we propose an efficient matching algorithm by separating each copyrighted image with the merged and edited type including rotation, illumination change, and change of size. We use the Oriented FAST and Rotated BRIEF (ORB) method as a basic feature matching scheme. To improve the matching accuracy, we design a new MIN-MAX similarity in matching stage. With the distorted dataset, the proposed method shows up-to 97% of precision in experiments. Also, we demonstrate that the proposed similarity measure also outperforms compared to other measure which is commonly used.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1131-1135
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• 2010

The development of modern civilization result from the abundance of material. Yet modern people live with chronic mild stress. Excessive chronic mild stress leads to various diseases. From the risk of the disease in order to protect our bodies need to manage chronic mild stress. The purpose of this study is to inspection the effectiveness of detecting in chronic mild stress using the Multi-sensor system. The Multi-sensor system is designed that can be measure three kinds of vital signals of chronic mild stress for the detection. First Photoplethysmogram(PPG), second Electro Dermal Activity(EDA), third Skin Temperature(SKT). The ages and occupations exposed to chronic mild stress, people often use out of this system was applied to dairy products(Pen). In addition, vital signals that occur when the variety of noise was used to remove the accelerometer. Chronic mild stress by the analysis of measured vital signals from Multi-sensor system to the measurement information to a PC to a wireless transmission(Bluetooth). In this study, using Multi-sensor system writing conditions and a variety of situations in the movement to measure vital signals and measurement results verified the accuracy and reliability. Through this measure chronic mild stress in everyday life and managing to maintain will help more healthy lifestyle.

• Journal of Sensor Science and Technology
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• v.29 no.5
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• pp.283-292
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• 2020

Current sensors that use a Hall element and Hall IC to measure the magnetic fields generated in steel silicon core gaps do not distinguish between direct and alternating currents. Thus, they are primarily used to measure direct current (DC) in industrial equipment. Although such sensors can measure the DC when installed in expensive equipment, ascertaining problems becomes difficult if the equipment is set up in an unexposed space. The control box is only opened during scheduled maintenance or when anomalies occur. Therefore, in this paper, a method is proposed for facilitating the safety management and maintenance of equipment when necessary, instead of waiting for anomalies or scheduled maintenance. A Bluetooth 4.0 low-energy current-sensor system based on near-field communication is used, which compensates for the nonlinearity of the current-sensor output signal using a piecewise linear model. The sensor is controlled using its generic attribute profile. Sensor nodes and cell phones used to check the signals obtained from the sensor at 50-A input currents showed an accuracy of ±1%, exhibiting linearity in all communications within the range of 0 to 50 A, with a stable output voltage for each communication segment.