• International Journal of Knowledge Content Development & Technology
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• v.11 no.2
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• pp.77-105
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• 2021

In order to establish a digital-based use environment for the provision of new information services suitable for the 5G era, it is necessary to discuss the direction of service provision by the National Library of Children and Young Adults in the 5G era. Based on utilization services in other fields, library services in the 5G era, including the development and provision of employee education and training services, ultra-high-definition and 360-degree realistic contents and education on library use, provision of multi-dimensional realistic media streaming broadcasting services, provision of telepresence education programs, activation of virtual communities, implementation of hologram performance halls/exhibit centers, and provision of unmanned book delivery services, environment monitoring, safety monitoring, and customized services, were proposed. In addition, based on 5G service, 5G technology, and library application direction, advancing into a producing and supporting base for ultra-realistic and immersive contents in the 5G era, strengthening online and mobile services in the non-contact era, and establishing a smart library environment were proposed as the service provision direction for the National Library of Children and Young Adults in the 5G era.

• Journal of Environmental Science International
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• v.29 no.1
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• pp.33-44
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• 2020

Recently, a variety of modeling studies have been conducted to examine the air quality over South Korea during the Korea - United States Air Quality (KORUS-AQ) campaign period (May 1 to June 10, 2016). This study investigates the impact of different meteorological initializations on atmospheric modeling results. We conduct several simulations during the KORUS-AQ period using the Weather Research and Forecasting (WRF) model with two different initial datasets, which is FNL of NCEP and ERA5 of ECMWF. Comparing the raw initial data, ERA5 showed better accuracy in the temperature, wind speed, and mixing ratio fields than those of NCEP-FNL. On the other hand, the results of WRF simulations with ERA5 showed better accuracy in the simulated temperature and mixing ratio than those with FNL, except for wind speed. Comparing the nudging efficiency of temperature and wind speed fields, the grid nudging effect on the FNL simulation was larger than that on the ERA5 simulation, but the results of mixing ratio field was the opposite. Overall, WRF simulation with ERA5 data showed a better performance for temperature and mixing ratio simulations than that with FNL data. For wind speed simulation, however, WRF simulation with FNL data indicated more accurate results compared to that with ERA5 data.

• Journal of the Korean earth science society
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• v.41 no.2
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• pp.95-110
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• 2020

Comparisons between two different surface temperatures from high-resolution ECMWF ReAnalysis 5 (ERA5) and Automated Synoptic Observing System (ASOS) observations were performed to investigate the reliability of the new reanalysis data over South Korea. As ERA5 has been recently produced and provided to the public, it will be highly used in various research fields. The analysis period in this study is limited to 1999-2018 because regularly recorded hourly data have been provided for 61 ASOS stations since 1999. Topographic characteristics of the 61 ASOS locations are classified as inland, coastal, and mountain based on Digital Elevation Model (DEM) data. The spatial distributions of whole period time-averaged temperatures for ASOS and ERA5 were similar without significant differences in their values. Scatter plots between ASOS and ERA5 for three different periods of yearlong, summer, and winter confirmed the characteristics of seasonal variability, also shown in the time-series of monthly error probability density functions (PDFs). Statistical indices NMB, RMSE, R, and IOA were adopted to quantify the temperature differences, which showed no significant differences in all indices, as R and IOA were all close to 0.99. In particular, the daily mean temperature differences based on 1-hour-averaged temperature had a smaller error than the classical daily mean temperature differences, showing a higher correlation between the two data. To check if the complex topography inside one ERA5 grid cell is related to the temperature differences, the kurtosis and skewness values of 90-m DEM PDFs in a ERA5 grid cell were compared to the one-year period amplitude among those of the power spectrum in the time-series of monthly temperature error PDFs at each station, showing positive correlations. The results account for the topographic effect as one of the largest possible drivers of the difference between ASOS and ERA5.

• Journal of Internet of Things and Convergence
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• v.7 no.1
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• pp.27-34
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• 2021

Modern society is rapidly developing into the Internet of Things and Big Data, and there are industries that develop even in the Corona era. However, the church is not developing and responding enough to the Corona era, and it is shaking the existence of the church itself. The essence of the church consists of worship, evangelism, education, service, and companionship. In the era of Corona, where non-face-to-face safety is important, the essence does not change, but efforts to embody the essence of the church in a socially responsible manner are needed. This paper discusses the social responsibility of the church in this respect, focusing on the five essential elements of the church. To this end, we examine the essential elements of the church and study the implementation methods suitable for the Corona era.

• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.543-551
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• 2023

Snow is an essential climate factor that affects the climate system and surface energy balance, and it also has a crucial role in water balance by providing solid water stored during the winter for spring runoff and groundwater recharge. In this study, statistical analysis of Local Data Assimilation and Prediction System (LDAPS), Modern.-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and ERA5-Land snow depth data were used to evaluate the applicability in South Korea. The statistical analysis between the Automated Synoptic Observing System (ASOS) ground observation data provided by the Korea Meteorological Administration (KMA) and the reanalysis data showed that LDAPS and ERA5-Land were highly correlated with a correlation coefficient of more than 0.69, but LDAPS showed a large error with an RMSE of 0.79 m. In the case of MERRA-2, the correlation coefficient was lower at 0.17 because the constant value was estimated continuously for some periods, which did not adequately simulate the increase and decrease trend between data. The statistical analysis of LDAPS and ASOS showed high and low performance in the nearby Gangwon Province, where the average snowfall is relatively high, and in the southern region, where the average snowfall is low, respectively. Finally, the error variance between the four independent snow depth data used in this study was calculated through triple collocation (TC), and a merged snow depth data was produced through weighting factors. The reanalyzed data showed the highest error variance in the order of LDAPS, MERRA-2, and ERA5-Land, and LDAPS was given a lower weighting factor due to its higher error variance. In addition, the spatial distribution of ERA5-Land snow depth data showed less variability, so the TC-merged snow depth data showed a similar spatial distribution to MERRA-2, which has a low spatial resolution. Considering the correlation, error, and uncertainty of the data, the ERA5-Land data is suitable for snow-related analysis in South Korea. In addition, it is expected that LDAPS data, which is highly correlated with other data but tends to be overestimated, can be actively utilized for high-resolution representation of regional and climatic diversity if appropriate corrections are performed.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.465-480
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• 2020

Numerical simulations of the storm surge and the wave induced by the Typhoon Sanba incident on the south coast of Korea in 2012 are conducted using the JMA-MSM forecast weather field, NCEP-CFSR reanalysis weather field, ECMWF-ERA5 reanalysis weather field, and the pressure and wind fields obtained using the best track information provided by JTWC. The calculated surge heights are compared with the time history observed at harbors along the coasts of Korea. For the waves the calculated significant wave heights are compared with the data measured using the wave buoys and the underwater pressure type wave gauge. As a result the JMA-MSM and the NCEP-CFSR weather fields give the highest reliability. The ECMWF-ERA5 gives in general surge and wave heights weaker than the measured. The ECMWF-ERA5, however, reproduces the best convergence belt formed in front of the typhoon. The weather field obtained using JTWC best track information gives the worst agreement.

• Journal of information and communication convergence engineering
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• v.16 no.2
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• pp.93-98
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• 2018

The Internet of Things (IoT) is a form of the emerging 4th industry in the 5G era. IoT is expected to develop naturally in our daily life in the 5G era in which high-speed communication will be completed. Along with the rise of IoT, concerns about security and malicious attacks are also increasing. This paper examines DoS attacks, which are one of the representative security threats of IoT and proposes a local detection and blocking system that are suitable for response to such attacks. First, systems of the LoRaWAN type, which are most actively researched in the IoT system field and DoS attacks that can occur in such systems were examined. Then, the inverse order tree algorithm using regional characteristics was designed as a cluster analysis form. Finally, a system capable of defending denial-of-service attacks in the 5G IoT system using local detection and blocking with the Euclidean distance was designed.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.255-256
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• 2019

• Fashion & Textile Research Journal
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• v.24 no.5
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• pp.628-635
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• 2022

This study sought to investigate the relationship between perception, body awareness, and beauty management behavior in the untact era in their MZ generation's, and as a result of the study, it was confirmed that there is a causal relationship between variables. For the empirical analysis of the study, a survey was conducted online(Google questionnaire) in Seoul/Gyeonggi area from June 7 to 26, 2021. Of the 548 questionnaires, 512, excluding 36, were analyzed using SPSS V.21.0. Among the sub-factors of perception in the untact era, it was confirmed that the social environment perception and human relationship perception are key factors that negatively affect body consciousness and beauty management behavior, and so does self-awareness(p<.05). Next, it was confirmed that, among the sub-factors of body consciousness, appearance management awareness and appearance/body care effort were key factors that positively affected beauty management behavior, and that appearance confidence was also an important factor that positively affected beauty management behavior(p<.05). Therefore, through this study, we intend to provide basic data for product development, programs, and marketing strategies that can cope with changes in the beauty consumption market in preparation for the post-COVID era.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.289-289
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• 2023

4차산업 혁명이 도래한 이후로 전세계적으로 AI 기술이 유래 없는 속도로 발달 및 활용되고 있으며, 다양한 분야에서 AI 기법을 도입한 연구가 활발히 진행 중에 있다. 최근 수자원 분야에서는 단기 강우 예측, 댐 유입량 예측 및 하천 수위 예측 등의 분야에서 AI 기술이 접목되어 꾸준한 기술 개발이 이루어지고 있다. 그러나 단변량으로 축척된 자료를 활용하여 중·장기 모형 개발 연구가 다수 진행되고 있지만, 급격한 기후변화 현상과 복잡한 매커니즘을 보이고 있는 기상현상의 경우 단변량 분석으로서는 정확도가 저하 될 수 있는 우려가 있는 것이 현실이다. 이에 본 연구에서는 상기에 제시된 단점을 극복하고자 다양한 기상자료를 검증·예측인자로 활용함과 동시에 Deeplearning 모형과 결합하여 신뢰성 있는 단기 강수 예측이 가능한 모형을 개발하였다. 본 연구에서는 유럽중기예보센터(ECMWF, European Center for Medium-Range Weather Forecasts)에서 제공하고 있는 ERA5 재해석 자료를 활용하였으며, Deeplearning 모형과 결합하여 단기 강우 예측이 가능한 모형을 개발하였다. 1차적으로 격자자료(25km×25km)로 제공되고 있는 ERA5 자료를 상세화(downscaling) 모형에 적용하여 기상청 관측소와 비교·검증하였으며, Deeplearning 모형을 통해 단기 예측이 가능한 모형으로 확장하였다. 이때 Deeplearning의 다양한 모형 중 시계열 분석에 있어 예측 성능이 높은 LSTM 모형을 활용하였으며, 제공되고 있는 대기 변수의 상호관계를 노드간 연결을 통해 결과의 정확도와 신뢰성을 확보하였다. 본 연구 결과는 기관별로 제공하고 있는 예측 수준을 상회하는 결과를 도출하였으며, 홍수기에 집중되는 강우량을 예측하여 대비·대책을 선제적으로 마련할 수 있는 자료로써의 활용성이 높을 것으로 사료된다.