• Journal of The Korean Astronomical Society
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• v.56 no.2
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• pp.293-299
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• 2023

The Wide-Angle Polarimetric Camera (PolCam) is installed on the Korea's lunar orbiter, Danuri, which launched on August 5, 2022. The mission objectives of PolCam are to construct photometric maps at a wavelength of 336 nm and polarization maps at 461 and 748 nm, with a phase angle range of 0°-135° and a spatial resolution of less than 100 m. PolCam is an imager using the push-broom method and has two cameras, Cam 1 and Cam 2, with a viewing angle of 45° to the right and left of the spacecraft's direction of orbit. We conducted performance tests in a laboratory setting before installing PolCam's flight model on the spacecraft. We analyzed the CCD's dark current, flat-field frame, spot size, and light flux. The dark current was obtained during thermal / vacuum test with various temperatures and the flat-field frame data was also obtained with an integrating sphere and tungsten light bulb. We describe the calibration method and results in this study.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.487-495
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• 2022

This paper describes the design and development of a high-power transmit receive module(TRM) for mounting on X-band synthetic aperture radar(SAR) of the NEXTSat-2. The TRM generates a high-power pulse signal with a bandwidth of 100 MHz in the target frequency range of X-band and amplifies a low-noise on the received signal. Tx. path of the TRM has output signal level of more than 200 watts (53.01 dB), pulse droop of 0.35 dB, signal strength change of 0.04 dB during transmission signal output, and phase change of 1.7 ˚. Rx. path has noise figure of 3.99 dB and gain of 37.38 ~ 37.46 dB. It was confirmed the TRM satisfies all requirements. The TRM mounted on the NEXTSat-2 flight model(FM) which will be launched using the KSLV-II (Nuri).

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.226-234
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• 2024

The frequent handover problem and playing ping-pong effects in 5G (5th Generation) ultra-dense networking cannot be effectively resolved by the conventional handover decision methods, which rely on the handover thresholds and measurement reports. For instance, millimetre-wave LANs, broadband remote association techniques, and 5G/6G organizations are instances of group of people yet to come frameworks that request greater security, lower idleness, and dependable principles and correspondence limit. One of the critical parts of 5G and 6G innovation is believed to be successful blockage the board. With further developed help quality, it empowers administrator to run many systems administration recreations on a solitary association. To guarantee load adjusting, forestall network cut disappointment, and give substitute cuts in case of blockage or cut frustration, a modern pursuing choices framework to deal with showing up network information is require. Our goal is to balance the strain on BSs while optimizing the value of the information that is transferred from satellites to BSs. Nevertheless, due to their irregular flight characteristic, some satellites frequently cannot establish a connection with Base Stations (BSs), which further complicates the joint satellite-BS connection and channel allocation. SF redistribution techniques based on Deep Reinforcement Learning (DRL) have been devised, taking into account the randomness of the data received by the terminal. In order to predict the best capacity improvements in the wireless instruments of 5G and 6G IoT networks, a hybrid algorithm for deep learning is being used in this study. To control the level of congestion within a 5G/6G network, the suggested approach is put into effect to a training set. With 0.933 accuracy and 0.067 miss rate, the suggested method produced encouraging results.

• Tunnel and Underground Space
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• v.25 no.5
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• pp.462-469
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• 2015

This study carried out a topographic survey at a small-scale open-pit limestone mine in Korea (the Daesung MDI Seoggyo office) using a popular rotary-wing unmanned aerial vehicle (UAV, Drone, DJI Phantom2 Vision+). 89 sheets of aerial photos could be obtained as a result of performing an automatic flight for 30 minutes under conditions of 100m altitude and 3m/s speed. A total of 34 million cloud points with X, Y, Z-coordinates was extracted from the aerial photos after data processing for correction and matching, then an orthomosaic image and digital surface model with 5m grid spacing could be generated. A comparison of the X, Y, Z-coordinates of 5 ground control points measured by differential global positioning system and those determined by UAV photogrammetry revealed that the root mean squared errors of X, Y, Z-coordinates were around 10cm. Therefore, it is expected that the popular rotary-wing UAV photogrammetry can be effectively utilized in small-scale open-pit mines as a technology that is able to replace or supplement existing topographic surveying equipments.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.5
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• pp.97-105
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• 2017

An air-burst munition is limited in space, so there is a limit on the size of the fuze and the amount of ammunition. In order to increase a firepower to a target with limited ammunition, it is necessary to concentrate the firepower on the ground instead of the omnidirectional explosion after flying to the target. This paper explores the design and verification of a ground-detection sensor that detects the direction of the ground and determines the flight-distance of an air-burst munition using a single axis geomagnetic sensor. Prior to the design of the ground detection sensor, a geomagnetic sensor model mounted on the spinning air-burst munition is analyzed and a ground-detection algorithm by simplifying this model is designed. A high speed rotating device to simulate a rotation environment is designed and a geomagnetic sensor and a remote-recording system are fabricated to obtain geomagnetic data. The ground detection algorithm is verified by post-processing the acquired geomagnetic data. Taking miniaturization and low-power into consideration, the ground detection sensor is implemented with analog devices and the processor. The output signal of the ground detection sensor rotating at an arbitrary rotation speed of 200 Hz is connected to the LED (Light Emitting Diode) in the high speed rotating device and the ground detection sensor is verified using a high-speed camera.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.1
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• pp.15-26
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• 2003

Ultrasonic inspection methods are widely used for detecting flaws in materials. The signal analysis step plays a crucial part in the data interpretation process. A number of signal processing methods have been proposed to classify ultrasonic flaw signals. One of the more popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classification of the signals in the feature space. This paper describes an alternative approach which uses the least mean square (LMS) method and expectation maximization (EM) algorithm with the model based deconvolution which is employed for classifying nondestructive evaluation (NDE) signals from steam generator tubes in a nuclear power plant. The signals due to cracks and deposits are not significantly different. These signals must be discriminated to prevent from happening a huge disaster such as contamination of water or explosion. A model based deconvolution has been described to facilitate comparison of classification results. The method uses the space alternating generalized expectation maximization (SAGE) algorithm In conjunction with the Newton-Raphson method which uses the Hessian parameter resulting in fast convergence to estimate the time of flight and the distance between the tube wall and the ultrasonic sensor Results using these schemes for the classification of ultrasonic signals from cracks and deposits within steam generator tubes are presented and showed a reasonable performances.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.1
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• pp.27-35
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• 2005

Ultrasonic inspection methods are widely used for detecting flaws in materials. The signal analysis step plays a crucial part in the data interpretation process. A number of signal processing methods have been proposed to classify ultrasonic flaw signals. One of the more popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classification of the signals in the feature spare. This paper describes an alternative approach which uses the least mean square (LMS) method and exportation maximization (EM) algorithm with the model based deconvolution which is employed for classifying nondestructive evaluation (NDE) signals from steam generator tubes in a nuclear power plant. The signals due to cracks and deposits are not significantly different. These signals must be discriminated to prevent from happening a huge disaster such as contamination of water or explosion. A model based deconvolution has been described to facilitate comparison of classification results. The method uses the space alternating generalized expectation maximiBation (SAGE) algorithm ill conjunction with the Newton-Raphson method which uses the Hessian parameter resulting in fast convergence to estimate the time of flight and the distance between the tube wall and the ultrasonic sensor. Results using these schemes for the classification of ultrasonic signals from cracks and deposits within steam generator tubes are presented and showed a reasonable performances.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.458-468
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• 2019

This research attempted to estimate monthly sales of food and beverage at the passenger terminal of Incheon int'l airport from June of 2015 to December 2020. This paper used ARIMA-Intervention model which can estimate the change of the sales amount suggesting the predicted monthly food and beverage sales revenue. The intervention variable was travel-ban policy against south Korea from P.R. China since July 2016 to December 2017 due to THAAD in south Korea. According to ARIMA, it was found normal predicted sales amount showed the slow growth increase rate until 2020 due to the effect of intervened variable. However, the monthly food sales in July and August 2019 was 20.3 and 21.2 billion KRW respectively. Each amount would increase even more in 2020 and the amount would increase to 21.4 and 22.1 billion KRW. The sales amount in 2019 would be 7.7 and 8.1 billion KRW and climb up 7.9 and 8.2 billion KRW in 2020. It was expected LCC passengers tend to spend more money for F&B at airport due to no meal or drink service of LCC or the paid-in meal and beverage service of LCC. The growth of sales of food and beverate will be accompanied with the growth of LCC according to estimated data.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.7
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• pp.445-454
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• 2022

Ice accretion on the aircraft components, such as wings, fuselage, and empennage, can occur when the aircraft encounters a cloud zone with high humidity and low temperature. The prevention of ice accretion is important because it causes a decrease in the aerodynamic performance and flight stability, thus leading to fatal safety problems. In this study, a shape design optimization of a multi-element airfoil is performed to minimize the amount of ice accretion on the high-lift device including leading-edge slat, main element, and trailing-edge flap. The design optimization framework proposed in this paper consists of four major parts: air flow, droplet impingement and ice accretion simulations and gradient-free optimization algorithm. Reynolds-averaged Navier-Stokes (RANS) simulation is used to predict the aerodynamic performance and flow field around the multi-element airfoil at the angle of attack 8°. Droplet impingement and ice accretion simulations are conducted using the multi-physics computational analysis tool. The objective function is to minimize the total mass of ice accretion and the design variables are the deflection angle, gap, and overhang of the flap and slat. Kriging surrogate model is used to construct the response surface, providing rapid approximations of time-consuming function evaluation, and genetic algorithm is employed to find the optimal solution. As a result of optimization, the total mass of ice accretion on the optimized multielement airfoil is reduced by about 8% compared to the baseline configuration.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.6
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• pp.97-118
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• 2021

This study empirically examines the effect of the psychological empowerment of airline cabin crews on customer-focused job performance attitude, service behavior by CSM, and service behavior beyond CSM. The research model and associated hypotheses were verified with the structural equation model. The findings of the study reveal that psychological empowerment has a effect on customer-focused job performance attitude and service behavior by CSM, but no effect on service behavior beyond CSM. And it is also shown that customer-focused job performance attitude has an effect on service behavior by CSM but no effect on service behavior beyond CSM. In addition, customer-focused job performance attitude shows a mediating effect between psychological empowerment and service behavior by CSM. On the other hand, it is analyzed that there is no mediating effect between psychological empowerment and service behavior beyond CSM. This study implies that the psychological empowerment and customer-focused job performance attitude of cabin crews are important at point of contact with customers to improve service quality, and psychological empowerment reinforces service behavior by CSM on the premise of customer-focused job performance attitude.