• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.35.4-35.4
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• 2019

We have conducted a 22 GHz very long baseline interferometry (VLBI) survey of 281 local (z < 0.05) active galactic nuclei (AGNs) selected from the Swift Burst Alert Telescope (BAT) 70-month ultra hard X-ray (14-195 keV) catalog. The main goal is to investigate the relation between the strengths of black hole accretion and the parsec-scale nuclear jet, which is expected to tightly correlate but has not been observationally confirmed yet. The BAT AGN Spectroscopic Survey (BASS) provides the least biased AGN sample against obscuration including both Seyfert types, hence it makes an ideal parent sample for studying the nuclear jet properties of an overall AGN population. Using the Korean VLBI Network (KVN), the KVN and VERA Array (KaVA), and the Very Long Baseline Array (VLBA), we observed 281 objects with a 22 GHz flux > 30 mJy, detecting 11 targets (~4% of VLBI detection rate). This implies that the fraction of X-ray AGNs which are currently ejecting a strong nuclear jet is very small. Although our 11 sources span a wide range of pc-scale morphological types, from compact to complex, they lie on a tight linear relation between accretion luminosity and nuclear jet luminosity. Our finding may indicate that the power of nuclear jet is directly responsible for the amount of black hole accretion. We also have probed the fundamental plane of black hole activity in VLBI scale (e.g., few milli-arcsecond). The results from our high-frequency VLBI radio study support that the change of jet luminosity and size follows what is predicted by the AGN evolution scenario based on the Eddington ratio (ƛ$_{Edd}$) - column density ($N_H$) plane, proposed by a previous study.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.146-152
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• 2019

This study discussed implications of the increase of single person households (SH) for high-tech industries especially focusing on artificial intelligence (AI) adopted products, based on critically reviewing the past researches on their characteristics including consumption trends; the improvement of AI technology; and its market potentiality in various industries. According to the results, SH spent more time with others like friends and neighbors more than couples. Younger people increasingly chose to live alone by their own free will for achieving their goals. 'Living alone' or 'going solo' is not thought negatively any more, but as a new market power in the future. Considering their value oriented consumption behaviors based on spirit of independence and individualism, they will need high-tech products more like AI adopted products than others because of their advantages for the value of single life. Thus, the rapid progress of AI technology is predicted to bring them satisfaction of their wants and it is suggested to prepare for the market segmentation of SH as AI end-users.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.657-665
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• 2021

Nondestructive evaluation methods play an important role in ensuring component integrity and safety in many industries. Operator fatigue can play a critical role in the reliability of such methods. This is important for inspecting high value assets or assets with a high consequence of failure, such as aerospace and nuclear components. Recent advances in convolution neural networks can support and automate these inspection efforts. This paper proposes using residual neural networks (ResNets) for real-time detection of corrosion, including iron oxide discoloration, pitting and stress corrosion cracking, in dry storage stainless steel canisters housing used nuclear fuel. The proposed approach crops nuclear canister images into smaller tiles, trains a ResNet on these tiles, and classifies images as corroded or intact using the per-image count of tiles predicted as corroded by the ResNet. The results demonstrate that such a deep learning approach allows to detect the locus of corrosion via smaller tiles, and at the same time to infer with high accuracy whether an image comes from a corroded canister. Thereby, the proposed approach holds promise to automate and speed up nuclear fuel canister inspections, to minimize inspection costs, and to partially replace human-conducted onsite inspections, thus reducing radiation doses to personnel.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.558-564
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• 2021

With the recent introduction of 5G, electromagnetic radiation sources are spreading throughout life, so it is necessary to establish a citizen-centered electromagnetic safety management system. In particular, the beamforming method of the 5G antenna increases the power density measurement of electromagnetic waves by more than 10 times when the wireless base station is installed, so it is unreasonable to determine the safety by physical measurement. Therefore, it is necessary to determine the presence or absence of electromagnetic wave safety in daily life through a predictive method by calculation through systematic model analysis. In this paper, in order to check the possibility of a 5G wireless base station using an electromagnetic wave numerical analysis tool as a way to solve this problem, we compared the measured values of the actual base stations and the predicted values through the prediction model to compare the reliability. A method of constructing a real-time base station electromagnetic wave strength prediction evaluation system combined with software was also proposed.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.17 no.1
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• pp.14-22
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• 2021

Drilling equipment is an essential part used in various fields such as construction, mining, etc., and it has drawn increasing attention in recent years. The drilling method is generally divided into three types. There are a top hammer method that strikes on the ground, a DTH (Down-The-Hole) method that directly strikes a bit in an underground area, and a rotary method that drills by using rotational force. Among them, the DTH method is most commonly used because it enables efficient drilling compared to other drilling methods. In the conventional DTH hammer, the valve between the piston and the bit is opened and closed using a face to face method. In order to improve the power of the DTH hammer, a DTH hammer with foot valve which is capable of instantaneous opening and closing is used in the drilling field. In this study, we designed a lab-scale DTH hammer with the foot valve, and manufactured an evaluation device for the experiment of the DTH hammer. In addition, we analyzed the performance of the DTH hammer adopted with foot valve according to the pressure range of 3-10 bar. As a result, the internal pressure distribution in the DTH hammer was experimentally analyzed, and then, the movement of the piston according to the pressure was predicted. We believe that this study provides the useful results to explain the performance characteristics of the DTH hammer with the foot valve.

• Journal of the wind engineering institute of Korea
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• v.22 no.4
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• pp.163-169
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• 2018

In this study, wind loads exerted on the offshore wind turbine rotor in parked condition were predicted with variations of wind speeds, yaw angles, azimuth angle, pitch angles, and power of the atmospheric boundary layer profile. The calculated wind loads using blade element theorem were compared with those of estimated aerodynamic loads for the simplified blade shape. Wind loads for an NREL's 5 MW scaled offshore wind turbine rotor were also compared with those of NREL's FAST results for more verification. All of the 6-component wind loads including forces and moments along the three axis were represented on a non-rotating coordinate system fixed at the apex of rotor hub. The calculated wind loads are applicable for the dynamic analysis of the wind turbine system, or obtaining the over-turning moment at the foundation of support structure for wind turbine system.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.552-560
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• 2021

With the recent development of the art distribution system, interest in art investment is increasing rather than seeing art as an object of aesthetic utility. Unlike stocks and bonds, the price of artworks has a heterogeneous characteristic that is determined by reflecting both objective and subjective factors, so the uncertainty in price prediction is high. In this study, we used LSTM Recurrent Neural Network deep learning model to predict the auction winning price by inputting the artist, physical and sales charateristics of the Korean artist. According to the result, the RMSE value, which explains the difference between the predicted and actual price by model, was 0.064. Painter Lee Dae Won had the highest predictive power, and Lee Joong Seop had the lowest. The results suggest the art market becomes more active as investment goods and demand for auction winning price increases.

• Journal of radiological science and technology
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• v.43 no.6
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• pp.503-509
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• 2020

This study aims to develop a patient-specific radiation exposure dose prediction model based on anthropometric data that can be easily measurable during CT examination, and to be used as basic data for DRL setting and radiation dose management system in the future. In addition, among the machine learning algorithms, the most suitable model for predicting exposure doses is presented. The data used in this study were chest CT scan data, and a data set was constructed based on the data including the patient's anthropometric data. In the pre-processing and sample selection of the data, out of the total number of samples of 250 samples, only chest CT scans were performed without using a contrast agent, and 110 samples including height and weight variables were extracted. Of the 110 samples extracted, 66% was used as a training set, and the remaining 44% were used as a test set for verification. The exposure dose was predicted through random forest, linear regression analysis, and SVM algorithm using Orange version 3.26.0, an open software as a machine learning algorithm. Results Algorithm model prediction accuracy was R^2 0.840 for random forest, R^2 0.969 for linear regression analysis, and R^2 0.189 for SVM. As a result of verifying the prediction rate of the algorithm model, the random forest is the highest with R^2 0.986 of the random forest, R^2 0.973 of the linear regression analysis, and R^2 of 0.204 of the SVM, indicating that the model has the best predictive power.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.29-39
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• 2021

As a means of solving traffic congestion in the downtown of large city, the interest in urban air mobility (UAM) using electric vertical take-off landing personal aerial vehicle (eVTOL PAV) is increasing. eVTOL configurations that will be used for UAM are classified by lift-and-cruise, tilt rotors, tilt-wings, tilted-ducted fans, multicopters, depending on propulsion types. This study tries to perform preliminary conceptual design for a given mission profile using reverse engineering techniques by taking the multicopter type Airbus's CityAirbus as a basic model. Wetted area, lift to drag ratio, drag coefficients were calculated using the OpenVSP which is an aerodynamic analysis software. The power required for each mission section of CityAirbus were calculated, and the corresponding battery and motor were selected. Also, total weight was predicted by estimating component weights of eVTOL.

• Journal of Ocean Engineering and Technology
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• v.35 no.4
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• pp.296-304
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• 2021

Research on the development of marine renewable energy is actively in progress. Various studies are being conducted on the development of wave energy converters. In this study, a numerical analysis of wave-energy extraction performance was performed according to the body shape and scale of the sloped oscillating water column (OWC) wave energy converter (WEC), which can be connected with the breakwater. The sloped OWC WEC was modeled in the time domain using a two-dimensional fully nonlinear numerical wave tank. The nonlinear free surface condition in the chamber was derived to represent the pneumatic pressure owing to the wave column motion and viscous energy loss at the chamber entrance. The free surface elevations in the sloped chamber were calculated at various incident wave periods. For verification, the results were compared with the 1:20 scaled model test. The maximum wave energy extraction was estimated with a pneumatic damping coefficient. To calculate the energy extraction of the actual size WEC, OWC models approximately 20 times larger than the scale model were calculated, and the viscous damping coefficient according to each size was predicted and applied. It was verified that the energy, owing to the airflow in the chamber, increased as the incident wave period increased, and the maximum efficiency of energy extraction was approximately 40% of the incident wave energy. Under the given incident wave conditions, the maximum extractable wave power at a chamber length of 5 m and a skirt draft of 2 m was approximately 4.59 kW/m.