• Journal of Appropriate Technology
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• v.6 no.2
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• pp.238-255
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• 2020

As COVID-19, which occurred at the end of 2019, has become a global pandemic, it has emerged as an unprecedented event that quickly destroys a nation's medical and healthcare system in both developed and developing countries. In the 21st century, most of the civil society that aimed for hyperconnected society is facing a new crisis that has not been experienced so far. Indeed, lack of personal protective equipment, isolation of clustered communities, disruption of medical systems necessary for diagnosis and treatment, and disruption of educational and economic activities due to social isolation are emerging. Since the COVID-19 has occurred, many of the difficulties that have occurred in the past six months indicate the basic infrastructure a society should have particularly in a pandemic. These include personal protective equipment (PPE), decontamination and quarantine tools essential for effective response, rapid and precise large-scale diagnosis, medical devices required for patient care, and identification and fast and wide on-line networks that can be used in social isolation. In this first part, we would like to introduce some representative examples of 1) personal protective equipment, 2) prevention of personal and community health, 3) social response through big data and networks within the framework of appropriate technology.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.63-70
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• 2021

Generating a super-resolution meteological data by using a high-resolution deep neural network can provide precise research and useful real-life services. We propose a new technique of generating improved training data for super-resolution deep neural networks. To generate high-resolution meteorological data with domain specific knowledge, Lambert conformal conic projection and objective analysis were applied based on observation data and ERA5 reanalysis field data of specialized institutions. As a result, temperature and humidity analysis data based on domain specific knowledge showed improved RMSE by up to 42% and 46%, respectively. Next, a super-resolution generative adversarial network (SRGAN) which is one of the aritifial intelligence techniques was used to automate the manual data generation technique using damain specific techniques as described above. Experiments were conducted to generate high-resolution data with 1 km resolution from global model data with 10 km resolution. Finally, the results generated with SRGAN have a higher resoltuion than the global model input data, and showed a similar analysis pattern to the manually generated high-resolution analysis data, but also showed a smooth boundary.

• Korea Science and Art Forum
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• v.23
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• pp.149-162
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• 2016

Here are background, method, scope, main contents of this research. As the interests increased in recent about the construction in complex and diverse areas, construction is locally connected to human life like to coexistence of the technology and culture. The local development should not be fragmentary construction to improve local recycling ability. Local society should be inherited by modern cultural perspective through a variety of local culture and coexistence. Effective decision making analysis is necessary to build a livable area with a combination of high-tech industry. For this reason, this paper will study the political analysis for decision making at the planning stage of construction in point of fusion of technology and culture by using unstructured data analysis. Conclusion is as in the following. Local planning stage of construction describes diverse meanings of intangible and intangible factors as political factor. Technology factors have various qualitative and quantitative factors in construction field. Understanding decision making at the planning stage of construction means not only visible 'technology factor' such as structure, method, shape, and so on, but also invisible 'culture factor' such as spirit of age, religion, learning, and life-style reflected in formation process of space, and insight of brain power about art.

• The Journal of the Acoustical Society of Korea
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• v.37 no.6
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• pp.451-456
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• 2018

UAComm (Underwater Acoustic Communication) is an active research area, and many experiment has been performed to develop UAComm system. In this paper, we investigate the possibility of modifying and applying VirTEX (Virtual Time series EXperiment) to medium long range MIMO (Multiple-Input Multiple-Output) UAComm of about 20 km range for the analysis and performance prediction of UAComm system. Since VirTEX is a time-domain simulator, the generated time series can be used in HILS (Hardware In the Loop Simulation) to develop UAComm system. The developed package is verified through comparing with the sea-going FAF05 (Focused Acoustic Field 2005) experimental data. The developed simulator can be used to predict the performance of UAComm system, and even replace the expensive sea-going experiment.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.2
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• pp.88-99
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• 2019

This study presents the results of analysis for the wave data that were consecutively collected from February 2013 to November 2018 at the location of 1.6 km offshore from Namhangjin beach. The water depth at the location is 30.5 m and waves were measured by AWAC (Acoustic Wave And Current meter). By using wave-by-wave analysis and spectral analysis, wave heights and periods were evaluated and then the relationships between the quantities obtained by the two methods were proposed based on linear regression analysis. In addition, monthly and yearly variations of the significant wave height and period, and the peak wave direction were analyzed. Moreover, the relationship between the significant wave height and period was newly suggested. Variability and probability distribution of the significant wave period with respect to the significant wave height were also examined.

• Journal of Coastal Disaster Prevention
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• v.4 no.4
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• pp.189-196
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• 2017

Ocean Research Stations (ORSs) is the ocean platform type observation towers and measured oceanic, atmospheric and environmental data. These station located on the offshore area far from the coast, so they can produce the data without land effect. This study focused to improve the wave data quality of ORS station. The wave observations at ORSs are used by the C-band (5.8 GHz, 5.17 cm) MIROS Wave and Current Radar (MWR). MWR is convenient to maintenance and produce reliability wave data under bad weather conditions. MWR measured significant wave height, peak wave period, peak wave direction and 2D wave spectrum, so it's can provide wave information for researchers and engineers. In order to improve the reliability of MWR wave data, Datawell Waverider Buoy was installed near the one ORS (Socheoncho station) during 7 months and validate the wave data of MWR. This study found that the wave radar tend to be overestimate the low wave height under wind condition. Firstly, this study carried out the wave Quality Control (QC) using wind data, however the quality of wave data was limited. So, this study applied the four filters (Correlation Check, Direction Filter, Reduce White Noise and Phillips Check) of MWR operating software and find that the filters effectively improve the wave data quality. After applying 3 effective filters in combination, the RMSE of significant wave height decreased from 0.81m to 0.23m, by 0.58m and Correlation increased from 0.66 to 0.96, by 0.32, so the reliability of MWR significant wave height was significantly improved.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.2
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• pp.195-199
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• 2010

(255,223) RS(Reed-Solomon) code which is the CCSDS(Consultative Committee for Space Data Systems) standard was used in the STSAT-3 to correct errors during the downlink of payload data. The RS encoder developed by VHDL was implemented in MMU(Mass Memory Unit). Moreover, the RS decoder developed by C-language was implemented in the DRS(Data Receiving System) of ground station. In this paper, we reported the design and analysis results of RS(255,223) for STSAT-3. The BER(Bit Error Rate) performance from MMU to DRS was confirmed through the downlink test at 16 Mbps. Also, the error correction performance and capability of RS(255,223) was tested by the manual attenuation of the RF(Radio Frequency) signal in the X-band transmitter resulting in putting some errors in the communication line.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.306-306
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• 2019

전지구적 기온상승으로 인해 미래기후의 관한 연구가 중요시 되고 있다. 위와 같은 현상으로 인하여 다양한 기후변화 연구가 진행되고 있다. 미래기후 연구에는 GCM (General Circulation Model) 모의 결과가 이용된다. 격자 자료로 구성된 GCM은 연구 지점으로 지역적 상세화와 연구지역의 관측자료 사이의 편이 보정(bias correction)이 필수적이다. 위와 같은 근거로 편이 보정 방법의 선택은 매우 중요하며 편의 보정의 방법에 따라서 결과가 다르게 도출될 수 있다. 또한 국내외 연구에서는 다양한 상세화 기법과 편이 보정 기법을 분석 및 평가하는 연구가 진행되고 있으며, 편의 기법 중 대표적인 기법인 Quantile mapping과 Random Forest 기법이 있다. Quantile mapping 기법은 GCM의 과거 모의 데이터와의 편이 보정에 있어서 우수하게 나타났으나, GCM 데이터의 미래 예측 기간(2010년~2018년)까지의 데이터에서는 극한 강수를 정량적으로 분석 가능한 Random Forest 기법이 편이 보정 과정에서 성능이 우수할 것으로 판단된다. 본 연구에서는 우리나라 21개 관측소를 기준으로 총 4개의 GCM(GISS, CSIRO, CCSM4,MIROC5)의 과거 기간 자료(1970년~2005년)를 실제 관측소에서 관측된 강수량을 편의 보정하는 방법에 있어서 편의 보정 기법의 성능을 비교한 결과와 GCM 미래 예측 기간 자료(2010년~2018년)에서의 편의 보정 기법의 성능 결과를 비교하였다. 이를 토대로 편이 보정 기법의 결과를 6개의 평가지수를 이용하여 정량적으로 분석하였으며, 다기준의사결정기법인 TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution)를 이용하여 편이 보정기법들의 성능에 있어서 우선순위를 선정하였다. 본 연구에서 편이 보정 방법으로 Quantile mapping 방법을 사용했으며, Quantile mapping의 기법으로는 비모수 변환법(non-parametric transformation)과 분포기반 변환법(distribution derived transformation)이 사용되었다. 또한 머신러닝 방법 중 하나인 Random Forest 방법을 동시에 사용하여 결과를 비교하였다. 또한 GCM 자료가 격자식으로 제공하고 있기 때문에 관측소 강수량도 공간적으로 환산하여야 하는데, 본 연구에서는 역거리 가중치법(inverse distance weighting, IDW) 방법을 이용하였다.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.759-766
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• 2020

In recent years, the maritime traffic environment has been changing in various ways, and the traffic volume has been increasing constantly. Accordingly, the requirements for maritime traffic analysis have become diversified. To this end, traffic characteristics must first be analyzed using vessel trajectory data. However, as the conventional method is mostly manual, it requires a considerable amount of time and effort, and errors may occur during data processing. In addition, ensuring the reliability of the analysis results is difficult, because this method considers the subjective opinion of analysts. Therefore, in this paper, we propose an automated method of traffic network generation for maritime traffic analysis. In the experiment, spatiotemporal features are analyzed using data collected at Mokpo Harbor over six months. The proposed method can automatically generate a traffic network reflecting the traffic characteristics of the experimental area. In addition, it can be applied to a large amount of trajectory data. Finally, as the spatiotemporal characteristics can be analyzed using the traffic network, the proposed method is expected to be used in various maritime traffic analyses.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.29-45
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• 2022

This study aims to analyze how the public perceive the climate change in South Korea. The climate change has been highlighted due to its social and environmental impact on future society during decades. In recent, the outbreak of COVID-19 alerted the causal relationship between diseases and the climate change and forced decision-makers to cope with possible future epidemics. Along with the social and political importance of the climate change, the perception and actions of the public also become significant. Thus, this study analyzes the trends in the public perception of climate change before and after the COVID-19, using social media big data from March 1, 2019 through February 28, 2022. The results show that the negative perception dominated the public's perception, but a little positive perception implies that numerous policies on the climate change may help the public convert their negative perception to the positive. This study may help the decision-makers develop future policies and strategies on the climate change and carbon neutrality by considering the demand-side perception, such as South Korean perception.