• Korean Journal of Optics and Photonics
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• v.31 no.6
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• pp.274-280
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• 2020

In this paper, the effect of atmospheric turbulence is numerically modeled and analyzed via a phase-screen model, in regard to long-range optical energy transfer using coherent beam combination. The coherent-beam-combination system consists of three channel beams pointing at a target at a distance of 1-2 km. The phase and propagation direction of each channel beam are assumed to be corrected in an appropriate manner, and the atmospheric turbulence that occurs while the beam propagates through free space is quantified with a phase-screen model. The phase screen is statistically generated and constructed within the range of fluctuations of the structure constant Cn2 from 10-15 to 10-13 [m-2/3]. Particularly, in this discussion the shape, distortion, and combining efficiency of the 3-channel combined beam are calculated at the target plane by varying the structure constant used in the phase-screen model, and the effect of atmospheric turbulence on beam-combination efficiency is analyzed. Analysis with this numerical model verifies that when coherent beam combination is used for long-range optical energy transfer, the received power at the target can be at least three times the power obtainable by incoherent beam combination, even for maximal atmospheric fluctuation within the given range. This numerical model is expected to be effective for analyzing the effects of various types of atmospheric-turbulence conditions and beam-combination methods when simulating long-range optical energy transfer.

• Biomolecules & Therapeutics
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• v.29 no.2
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• pp.234-247
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• 2021

We used a heterozygous gene deletion library of fission yeasts comprising all essential and non-essential genes for a microarray screening of target genes of the antifungal terbinafine, which inhibits ergosterol synthesis via the Erg1 enzyme. We identified 14 heterozygous strains corresponding to 10 non-essential [7 ribosomal-protein (RP) coding genes, spt7, spt20, and elp2] and 4 essential genes (tif302, rpl2501, rpl31, and erg1). Expectedly, their erg1 mRNA and protein levels had decreased compared to the control strain SP286. When we studied the action mechanism of the non-essential target genes using cognate haploid deletion strains, knockout of SAGA-subunit genes caused a down-regulation in erg1 transcription compared to the control strain ED668. However, knockout of RP genes conferred no susceptibility to ergosterol-targeting antifungals. Surprisingly, the RP genes participated in the erg1 transcription as components of repressor complexes as observed in a comparison analysis of the experimental ratio of erg1 mRNA. To understand the action mechanism of the interaction between the drug and the novel essential target genes, we performed isobologram assays with terbinafine and econazole (or cycloheximide). Terbinafine susceptibility of the tif302 heterozygous strain was attributed to both decreased erg1 mRNA levels and inhibition of translation. Moreover, Tif302 was required for efficacy of both terbinafine and cycloheximide. Based on a molecular modeling analysis, terbinafine could directly bind to Tif302 in yeasts, suggesting Tif302 as a potential off-target of terbinafine. In conclusion, this genome-wide screening system can be harnessed for the identification and characterization of target genes under any condition of interest.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.6
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• pp.751-760
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• 2021

Most bridges in Korea are over 20 years old, and many problems linked to their deterioration are being reported. The current practice for bridge inspection mainly depends on expert evaluation, which can be subjective. Recent studies have introduced data-driven methods using building information modeling, which can be more efficient and objective, but these methods require manual procedures that consume time and money. To overcome this, this study developed an image-based automaticbridge component classification network to reduce the time and cost required for converting the visual information of bridges to a digital model. The proposed method comprises two convolutional neural networks. The first network estimates the type of the bridge based on the superstructure, and the second network classifies the bridge components. In avalidation test, the proposed system automatically classified the components of 461 bridge images with 96.6 % of accuracy. The proposed approach is expected to contribute toward current bridge maintenance practice.

• The Mathematical Education
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• v.60 no.4
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• pp.451-466
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• 2021

The interaction between student and school levels should be considered to understand and examine equity in education. For this reason, we included the socioeconomic composition of schools to scrutinize the equity related to students' socioeconomic status and mathematical literacy in Korea. We applied the hierarchical linear modeling approach to the Programme for International Student Assessment (PISA) 2015 data for binational comparison between Korea (5,548 students from 168 schools) and the U.S. (5,217 students from 161 schools). The findings show that school-level achievement and the socioeconomic composition of schools cannot be ignored to understand Korean students' achievement gap between high and low socioeconomic status. In addition, U.S. students from low socioeconomic status were likely to have similar mathematics literacy scores. These findings indicated that inequity in Korean mathematics education could be intertwined with the characteristics of Korean students like high demands for supplementary private education and school characteristics like curriculum selection. This research also reminds mathematics educators that people should not simply mimic other education systems to resolve education issues in their own system.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.299-306
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• 2022

In recent, sensors embedded in robots, equipment, and circuits have become common, and research for diagnosing device failures by learning measured sensor data is being actively conducted. This failure diagnosis study is divided into a classification model for predicting failure situations or types and a regression model for numerically predicting failure conditions. In the case of a classification model, it simply checks the presence or absence of a failure or defect (Class), whereas a regression model has a higher learning difficulty because it has to predict one value among countless numbers. So, the reason that regression modeling is more difficult is that there are many irregular situations in which it is difficult to determine one output from a similar input when predicting by matching input and output. Therefore, in this paper, we focus on input and output data with periodicity, analyze the input/output relationship, and secure regularity between input and output data by performing sliding window-based input data patterning. In order to apply the proposed method, in this study, current and temperature data with periodicity were collected from MMC(Modular Multilevel Converter) circuit system and learning was carried out using ANN. As a result of the experiment, it was confirmed that when a window of 2% or more of one cycle was applied, performance of 97% or more of fit could be secured.

• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.306-313
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• 2022

Purpose: The purpose of this study is suggested to improve upon current existing methods of ammonia chemical accident prevention and damage reduction. Method: Ammonia is one of the most common toxic substances that causes frequent chemical accidents. And it was selected as leakage materials according to statistics on chemical accident. Based on actual cases of chemical accidents, CARIS modeling was used to compare the damage impact range of Ammonia and HCl and Cl. Also, find out problems with the current systems. Result: As a result of find out the range of accident influence that spreads to the surroundings when an ammonia chemical accident, it was longer than the range of influence of hydrochloric acid and shorter than that of chlorine. In addition, it was found that when chemical accident by ammonia, hydrochloric acid, or chlorine, there are apartments and schools, which can have an effect. Conclusion: It is decided that it is necessary to determine whether or not chemical accident prevention management plans and statistical investigations are submitted for workplaces dealing with ammonia, and detailed guidelines and reviews are necessary. In addition, it is judged that it is necessary to establish a DB for ammonia handling plants, and it is considered that information sharing and joint inspection among related organizations should be pursued.

• 한국노년학
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• v.40 no.4
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• pp.747-760
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• 2020

The purpose of this study is to prepare basic data necessary for the development of services or systems that can enhance the accessibility of health and medical services or enhance the efficiency of health and medical use of senior citizens by identifying factors for predicting health and medical use behavior of senior citizens in Incheon Metropolitan City through the Korea health panel data(version 1.5). Through the structural equation model established through the SPSS and AMOS, it was confirmed that the predisposing factors, health behaviors and needs factors had significant direct and indirect effects on the use of health care services. Since the imbalance in demand and supply of health and medical services is more severe than in other regions, the results of this study can be used as basic data when checking whether the current health and medical system in Incheon Metropolitan City can operate effectively in an aged society and discussing how to provide health and medical services to the elderly in Incheon.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.367-372
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• 2022

With the recent advent of the New Normal era, realistic technologies and non-contact technologies are receiving social attention. However, the hair styling field focuses on the direction of the hair itself, individual movements, and modeling, focusing on hair simulation. In order to create an improved practice environment and demand of the times, this study proposed a non-contact hair styling VR system. In the theoretical review, we studied the existing cases of hair cut research. Existing haircut-related research tend to be mainly focused on force-based feedback. Research on the interactive haircut work in the virtual environment as addressed in this paper has not been done yet. VR controllers capable of finger tracking the movements necessary for beauty enable selection, cutting, and rotation of beauty tools, and built a non-contact collaboration environment. As a result, we conducted two experiments for interactive hair cutting in VR. First, it is a haircut operation for synchronization using finger tracking and holding hook animation. We made position correction for accurate motion. Second, it is a real-time interactive cutting operation in a multi-user virtual collaboration environment. This made it possible for instructors and learners to communicate with each other through VR HMD built-in microphones and Photon Voice in non-contact situations.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.967-977
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• 2022

The occurrence and intensity of wildfires are increasing with climate change. Emissions from forest fire smoke are recognized as one of the major causes affecting air quality and the greenhouse effect. The use of satellite product and machine learning is essential for detection of forest fire smoke. Until now, research on forest fire smoke detection has had difficulties due to difficulties in cloud identification and vague standards of boundaries. The purpose of this study is to detect forest fire smoke using Level 1 and Level 2 data of Geostationary Environment Monitoring Spectrometer (GEMS), a Korean environmental satellite sensor, and machine learning. In March 2022, the forest fire in Gangwon-do was selected as a case. Smoke pixel classification modeling was performed by producing wildfire smoke label images and inputting GEMS Level 1 and Level 2 data to the random forest model. In the trained model, the importance of input variables is Aerosol Optical Depth (AOD), 380 nm and 340 nm radiance difference, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), formaldehyde (HCHO), nitrogen dioxide (NO₂), 380 nm radiance, and 340 nm radiance were shown in that order. In addition, in the estimation of the forest fire smoke probability (0 ≤ p ≤ 1) for 2,704 pixels, Mean Bias Error (MBE) is -0.002, Mean Absolute Error (MAE) is 0.026, Root Mean Square Error (RMSE) is 0.087, and Correlation Coefficient (CC) showed an accuracy of 0.981.

• Ocean and Polar Research
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• v.44 no.4
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• pp.269-285
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• 2022

The interaction between ocean and ice shelf is a critical physical process in relation to water mass transformations and ice shelf melting/freezing at the ocean-ice interface. However, it remains challenging to thoroughly understand the process due to a lack of observational data with respect to ice shelf cavities. This is the first study to simulate the variability and circulation of water mass both overlying the continental shelf and underneath an ice shelf and an ice tongue in the Terra Nova Bay (TNB), East Antarctica. To explore the properties of water mass and circulation patterns in the TNB and the corresponding effects on sub ice shelf basal melting, we explicitly incorporate the dynamic-thermodynamic processes acting on the ice shelf in the Regional Ocean Modeling System. The simulated water mass formation and circulation in the TNB region agree well with previous studies. The model results show that the TNB circulation is dominated by the geostrophic currents driven by lateral density gradients induced by the releasing of brine or freshwater at the polynya of the TNB. Meanwhile, the circulation dynamics in the cavity under the Nansen Ice shelf (NIS) are different from those in the TNB. The gravity-driven bottom current induced by High Salinity Shelf Water (HSSW) formed at the TNB polynya flows towards the grounding line, and the buoyance-driven flow associated with glacial meltwater generated by the HSSW emerges from the cavity along the ice base. Both current systems compose the thermohaline overturning circulation in the NIS cavity. This study estimates the NIS basal melting rate to be 0.98 m/a, which is comparable to the previously observed melt rate. However, the melting rate shows a significant variation in space and time.