• Journal of Fisheries and Marine Sciences Education
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• v.26 no.6
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• pp.1380-1391
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• 2014

The purpose of this study was to investigate realities and find vitalizing plan of ocean-related lifelong education in Busan area. 190 staff members of lifelong education institutes in Busan were participated in questionnaires for investigating this topic. The results of research were as follows. Firstly, staff members of lifelong education institutes recognized that citizens were needed to expand ocean consciousness. Secondly, they recognized that ocean-related lifelong education had to be conducted for inspiration of ocean consciousness. Thirdly, 65.8% of them had practice will to manage ocean-related lifelong education program in the future. Based upon these results, our suggestions for strategies to revitalize ocean-related lifelong education in Busan were as follows. Firstly, a customized program of ocean-related lifelong education for citizens of Busan, ocean city, has to be developed and come into wide use. Secondly, the regional characteristics of Busan have to be taken into consideration in utilizing learning material. Thirdly, systematic support plan for ocean-related lifelong education has to be needed. Lastly, participants' network for ocean-related lifelong education has to be established.

• Journal of the Korean Geophysical Society
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• v.9 no.3
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• pp.199-207
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• 2006

Fukuoka earthquake on March 20, 2005 showed the potential hazard of large events out of S. Korea. From the viewpoint of seismic hazard, seismic amplitude decrease Q-1 is very important. Related to the crustal cracks induced by the earthquakes, the value of Q-1- high Q-1 regions are more attenuating than low Q-1 regions - shows a correlation with seismic activity; relatively higher values of Q-1 have been observed in seismically active areas than in stable areas. For the southeastern and central S. Korea, we first simultaneously estimated QP-1 and QS-1 by applying the extended coda-normalization method to KIGAM and KNUE network data. Estimated QP-1 and QS-1 values are 0.009 f-1.05 and 0.004 f-0.70 for southeastern S. Korea and 0.003 f -0.54 and 0.003 f -0.42 for central S. Korea, respectively. These values agree with those of seismically inactive regions such as shield. The low QLg-1 value, 0.0018f -0.54 was also obtained by the coda normalization method. In addition, we studied QLg-1 by applying the source pair/receiver pair (SPRP) method to both domestic and far-regional events. The obtained QLg-1 for all Fc is less than 0.002, which is reasonable value for a seismically inactive region.

• Archives of Plastic Surgery
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• v.46 no.5
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• pp.470-474
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• 2019

Congenital absent sternum is a rare birth defect that requires early intervention for optimal long-term outcomes. Descriptions of the repair of absent sternum are limited to case reports, and no preferred method for management has been described. Herein, we describe the use of porcine acellular dermal matrix to reconstruct the sternum of an infant with sternal infection following attempted repair using synthetic mesh. The patient was a full-term male with trisomy 21, agenesis of corpus callosum, ventricular septal defect, patent ductus arteriosus, right-sided aortic arch, and congenital absence of sternum with no sternal bars. Following removal of the infected synthetic mesh, negative pressure wound therapy with instillation was used to manage the open wound and provide direct antibiotic therapy. When blood C-reactive protein levels declined to ${\leq}2mg/L$, the sternum was reconstructed using porcine acellular dermal matrix. At 21 months postoperative, the patient demonstrated no respiratory issues. Physical examination and computed tomography imaging identified good approximation of the clavicular heads and sternal cleft and forward curvature of the ribs. This case illustrates the benefits of negative pressure wound therapy and acellular dermal matrix for the reconstruction of absent sternum in the context of infected sternal surgical site previously repaired with synthetic mesh.

• Journal of IKEEE
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• v.23 no.1
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• pp.334-337
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• 2019

In response to the increasing demand for energy, research and development of next-generation energy is actively carried out around the world to replace fossil fuels. Among them, the specific gravity of solar power generation systems using infinity and pollution-free solar energy is increasing. However, solar power generation is so different from solar energy that it is difficult to provide stable power and the power production itself depends on the solar energy by region. To solve these problems in this paper, we have collected meteorological data such as actual regional solar irradiance, precipitation, temperature and humidity, and proposed a solar power output prediction system using logic-based fuzzy Neural Network.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.333-339
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• 2021

The study seeks to identify the determinants of the adoption of e-commerce by small and medium-sized enterprises (SMEs) in developing countries, in our case, in Indonesia. The aim of this study is to examine the factors influencing e-commerce adoption. This study uses the method of quantitative data collection based on a questionnaire survey of SMEs in Indonesia. The research relies on Regional Project stipulations regarding Business Development in Indonesia, to capture businesses with a range of 5 to 100 employees that are classified as SMEs. This study randomly chose 100 SMEs in Indonesia from the IndoNetwork database. Partial least square (PLS) structural model data processing was used for path coefficients analysis. Structural equation modeling is applied in this study to analyze the determinant factors on the e-commerce adoption. The study findings reveal that four factors, namely, perceived benefits, compatibility, technology readiness, and government support, significantly influence the adoption of e-commerce, whereas customer/supplier pressure does not have influence. So, this study concludes that perceived benefits, compatibility, technology readiness, and government support had a significant and positive relationship with e-commerce adoption. Meanwhile, customer/supplier pressure had no effect on the e-commerce adoption of by Indonesia SMEs.

• Journal of Hydrogen and New Energy
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• v.33 no.5
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• pp.591-597
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• 2022

Recently, technologies for efficient power grid operation have become important due to climate change. For this reason, predicting power demand using deep learning is being considered, and it is necessary to understand the influence of characteristics of each region, industrial structure, and climate. This study analyzed the power demand of New Jersey in US, with a high urbanization rate and a large service industry, and West Virginia in US, a low urbanization rate and a large coal, energy, and chemical industries. Using recurrent neural network algorithm, the power demand from January 2020 to August 2022 was learned, and the daily and weekly power demand was predicted. In addition, the power grid operation based on the power demand forecast was discussed. Unlike previous studies that have focused on the deep learning algorithm itself, this study analyzes the regional power demand characteristics and deep learning algorithm application, and power grid operation strategy.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.26-26
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• 2023

General circulation models (GCMs) are widely used in hydrological prediction, however their coarse grids make them unsuitable for regional analysis, therefore a downscaling method is required to utilize them in hydrological assessment. As one of the downscaling methods, convolutional neural network (CNN)-based downscaling has been proposed in recent years. The aim of this study is to generate the process of dynamic downscaling using CNNs by applying GCM output as input and RCM output as label data output. Prediction accuracy is compared between different input datasets, and model structures. Several input datasets with key atmospheric variables such as precipitation, temperature, and humidity were tested with two different formats; one is two-dimensional data and the other one is three-dimensional data. And in the model structure, the hyperparameters were tested to check the effect on model accuracy. The results of the experiments on the input dataset showed that the accuracy was higher for the input dataset without precipitation than with precipitation. The results of the experiments on the model structure showed that substantially increasing the number of convolutions resulted in higher accuracy, however increasing the size of the receptive field did not necessarily lead to higher accuracy. Though further investigation is required for the application, this paper can contribute to the development of efficient downscaling method with CNNs.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.230-230
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• 2023

딥러닝 알고리즘 중 과거의 정보를 저장하는 문제(장기종속성 문제)가 있는 단순 RNN(Simple Recurrent Neural Network)의 단점을 해결한 LSTM(Long short-term memory)이 등장하면서 특정한 유역의 강우-유출 모형을 구축하는 연구가 증가하고 있다. 그러나 하나의 모형으로 모든 유역에 대한 유출을 예측하는 지역화 강우-유출 모형은 서로 다른 유역의 식생, 지형 등의 차이에서 발생하는 수문학적 행동의 차이를 학습해야 하므로 모형 구축에 어려움이 있다. 따라서, 본 연구에서는 국내 12개의 유역에 대하여 LSTM 기반 분포형 지역화 강우-유출 모형을 구축한 이후 강우 이외의 보조 자료에 따른 정확도를 살펴보았다. 국내 12개 유역의 7년 (2012.01.01-2018.12.31) 동안의 49개 격자(4km²)에 대한 10분 간격 레이더 강우, MODIS 위성 이미지 영상을 활용한 식생지수 (Normalized Difference Vegetation Index), 10분 간격 기온, 유역 평균 경사, 단순 하천 경사를 입력자료로 활용하였으며 10분 간격 유량 자료를 출력 자료로 사용하여 LSTM 기반 분포형 지역화 강우-유출 모형을 구축하였다. 이후 구축된 모형의 성능을 검증하기 위해 학습에 사용되지 않은 3개의 유역에 대한 자료를 활용하여 Nash-Sutcliffe Model Efficiency Coefficient (NSE)를 확인하였다. 식생지수를 보조 자료를 활용하였을 경우 제안한 모형은 3개의 검증 유역에 대하여 하천 흐름을 높은 정확도로 예측하였으며 딥러닝 모형이 위성 자료를 통하여 식생에 의한 차단 및 토양 침투와 같은 동적 요소의 학습이 가능함을 나타낸다.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.73-81
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• 2023

Globalized cities are currently showing changes due to autonomous driving (AD). It is also maximizing globalization connections in cities where autonomous mobility is as complex as AD. The purpose of this study is to reveal that cities that realize AD and mobility will grow into globalized cities. Several cities, including New York and Shanghai, have attempted and are in progress, but failed cities are increasing. Although the technology of AD and the trust of citizens are prioritized, the city that has built the city's infrastructure is expected to be a city that has succeeded in AD. This is because commercialized cities or AVs will become hubs for mobility globalization, excluding rapid climate change or AV companies, and empirical analysis has been conducted that if AVs fail in metropolitan New York due to urban complexity (population density), urban economy size (GRDP), patents, number of consumers, infrastructure public EV chargers, and road quality. It examines whether the realization of AD by region and country affects overall national innovation. As a result, even if AV succeeds in large cities such as New York, Seoul, which has a higher population density (complexity), has a negative meaning, and a more similar Tokyo has a positive meaning. It can be seen that regional research on AV should also be prioritized in large cities such as Shanghai. This means that in order for AV to be realized in each city, the construction of AI infrastructure data must be actively changed to establish globalization of cities for economic growth as autonomous mobility.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.4
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• pp.499-513
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• 2022

This study targets the rechargeable battery industry, which has been rapidly growing recently. The rechargeable battery industry is closely related to the electric vehicle industry. However, other factors also influence it. Currently, rechargeable battery companies show a pattern of restructuring production space by various means. To determine the causes of these production spaces, the factors affecting regional and national scales were thoroughly examined. As a result, the location factors for rechargeable battery-related companies are determined by cooperative relationships with assembled car companies, government policy regulations, and the stability of supply of key materials. And a spatial strategy was implemented to make the most of these circumstances.