• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.999-1009
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• 2022

The Chuncheon Mullori area is an underprivileged area for water welfare that does not have a local water supply system. Here, water is supplied to the village by using a small-scale water supply facility that uses underground water and underground water as the source. To solve the problem of water shortage during drought and to prepare for the increasing water demand, a sand dam was installed near the valley river, and this facility has been operating since May 2022. In this study, in order to evaluate the reliability of water supply when a sand dam is assumed during a drought in the past, groundwater runoff simulation results using MODFLOW were used to generate inflow data from 2011 to 2020, an unmeasured period. After performing SWAT-K basin hydrologic modeling for the watershed upstream of the existing water intake source and the sand dam, the groundwater runoff was calculated, and the relative ratio of the monthly groundwater runoff for the previous 10 years to the monthly groundwater runoff in 2021 was obtained. By applying this ratio to the 2021 inflow time series data, historical inflow data from 2011 to 2020 were generated. As a result of analyzing the availability of water supply during extreme drought in the past for three cases of demand 20 m³/day, 50 m³/day, and 100 m³/day, it can be confirmed that the reliability of water supply increases with the installation of sand dams. In the case of 100 m³/day, it was analyzed that the reliability exceeded 90% only when the existing water intake source and the sand dam were operated in conjunction. All three operating conditions were evaluated to satisfy 50 m³/day or more of demand based on 95% reliability of water supply and 30 m³/day or more of demand based on 99% of reliability.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.375-384
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• 2022

The shipping industry is cyclically impacted by complex variables such as various economic indicators, social events, and supply and demand. The purpose of this study was to analyze the operating profit of 13 Korean liner companies over 30 years, including the financial crisis of the late 1990s, the global financial crisis of the late 2000s, and the COVID-19 global pandemic. This study was conducted to also identify factors that impacted the profit ratio of Korea's liner shipping companies according to economic conditions. It was divided into ocean-going and short-sea shipping, reflecting the characteristics of liner shipping companies, and was analyzed by hierarchical multiple regression analysis. The time series data are based on the Korean International Financial Reporting Standards (K-IFRS) and comprise seaborne trade volume, fleet evolution, and macroeconomic indicators. The outliers representing the economic downturn due to social events were separately analyzed. As a result of the analysis, the China Container Freight Index (CCFI) positively impacted ocean-going as well as short-sea liner shipping companies. However, the Korean container shipping volume only impacted ocean-going liners positively. Additionally, world and Korea's GDP, world seaborne trade volume, and fuel price are factored in the operating profit of short sea liner shipping. Also, the GDP growth rate of China, exchange rate, and interest rate did not significantly impact both groups. Notably, the operating profitability of Korea's liner shipping shows an exceptionally high rate during the recessions of 1998 and 2020. It is paradoxical, and not correlated with the classical economic indicators. Unlike other studies, this paper focused on the operating profit before financial expenses, considering the complexity as well as difficulty in forecasting the shipping cycle, and rendered conclusions using relatively long-term empirical analysis, including three economic shocks.

• The Journal of Engineering Geology
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• v.33 no.2
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• pp.275-291
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• 2023

Global warming has made the polar regions more accessible, leading to increased demand for the construction of new resource-development plants in oil-rich permafrost regions. The selection of locations of resource-development plants in permafrost regions should consider the surface displacement resulting from thawing and freezing of the active layer of permafrost. However, few studies have considered surface displacement in the selection of optimal locations of resource-development plants in permafrost region. In this study, Analytic Hierarchy Process (AHP) analysis using a range of geospatial information variables was performed to select optimal locations for the construction of oil-sands development plants in the permafrost region of southern Athabasca, Alberta, Canada, including consideration of surface displacement. The surface displacement velocity was estimated by applying the Small BAseline Subset Interferometric Synthetic Aperture Radar technique to time-series Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar images acquired from February 2007 to March 2011. ERA5 reanalysis data were used to generate geospatial data for air temperature, surface temperature, and soil temperature averaged for the period 2000~2010. Geospatial data for roads and railways provided by Statistics Canada and land cover maps distributed by the North American Commission for Environmental Cooperation were also used in the AHP analysis. The suitability of sites analyzed using land cover, surface displacement, and road accessibility as the three most important geospatial factors was validated using the locations of oil-sand plants built since 2010. The sensitivity of surface displacement to the determination of location suitability was found to be very high. We confirm that surface displacement should be considered in the selection of optimal locations for the construction of new resource-development plants in permafrost regions.

• Clean Technology
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• v.29 no.4
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• pp.255-261
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• 2023

Power semiconductors are semiconductors used for power conversion, transformation, distribution, and control. Recently, the global demand for high-voltage power semiconductors is increasing across various industrial fields, and optimization research on high-voltage IGBT components is urgently needed in these industries. For high-voltage IGBT development, setting the resistance value of the wafer and optimizing key unit processes are major variables in the electrical characteristics of the finished chip. Furthermore, the securing process and optimization of the technology to support high breakdown voltage is also important. Etching is a process of transferring the pattern of the mask circuit in the photolithography process to the wafer and removing unnecessary parts at the bottom of the photoresist film. Ion implantation is a process of injecting impurities along with thermal diffusion technology into the wafer substrate during the semiconductor manufacturing process. This process helps achieve a certain conductivity. In this study, dry etching and wet etching were controlled during field ring etching, which is an important process for forming a ring structure that supports the 3.3 kV breakdown voltage of IGBT, in order to analyze four conditions and form a stable body junction depth to secure the breakdown voltage. The field ring ion implantation process was optimized based on the TEG design by dividing it into four conditions. The wet etching 1-step method was advantageous in terms of process and work efficiency, and the ring pattern ion implantation conditions showed a doping concentration of 9.0E13 and an energy of 120 keV. The p-ion implantation conditions were optimized at a doping concentration of 6.5E13 and an energy of 80 keV, and the p+ ion implantation conditions were optimized at a doping concentration of 3.0E15 and an energy of 160 keV.

• Economic and Environmental Geology
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• v.57 no.3
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• pp.281-292
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• 2024

North Korea relies heavily on coal as the primary energy source, playing an important role in all energy demand sectors except for the transportation sector. Approximately half of the total electricity is generated through coal-fired power plants, and coal is used to produce heat and power for all industrial facilities. Furthermore, coal has been a significant contributor to earning foreign currency through long-term exports to China. Nevertheless, since the 1980s, indiscriminate mining activities have led to rapid depletion of coal production in most coal mines. Aging mine facilities, lack of investment in new equipment, shortages of fuel and electricity, difficulties in material supply, and frequent damage from flooding have collectively contributed to a noticeable decline in coal production since the late 1980s. North Korea's coal deposits are distributed in various geological formations from the Proterozoic to the Cenozoic, but the most critical coal-bearing formations are Ripsok and Sadong formations distributed in the Pyeongnam Basin of the Late Paleozoic from Carboniferous to Permian, which are called as Pyeongnam North and South Coal Fields. Over 90% of North Korea's coal is produced in these coal fields. The classification of coal in North Korea differs from the international classification based on coalification (peat, lignite, sub-bituminous coal, bituminous coal, and anthracite). North Korean classification based on industrial aspect is classified into bituminous coal, anthracite, and low-grade coal (Chomuyeontan). Based on the energy factor, it is classified into high-calorie coal, medium calorie coal, and low-calorie coal. In North Korea, the term "Chomuyeontan" refers to a type of coal that is not classified globally and is unique to North Korea. It is a low-grade coal exclusively used in North Korea and is not found or used in any other country worldwide. This article compares North Korea's coal classification and the international coal classification of coal and provides insights into the geological characteristics, reserves, utilization, and research trends of North Korean coal resources. This study could serve as a guide for preparing scientific and industrial agendas related to coal collaboration between North Korea and South Korea.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.1-23
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• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.