• Journal of the Korean earth science society
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• v.40 no.1
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• pp.37-45
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• 2019

In spite of continued nourishments, Haeundae Beach in Busan has been suffering from erosion, this being caused by the increased wave energy due to global warming and intermittent typhoon reported by previous works. In the meantime, the typhoon Chaba hit Basan in October 2016. In order to investigate the effects of the typhoon in beach erosion and how fast the beach recovered after the typhoon, repeated beach profiling using a VRS-GPS system was carried out, and the grain size analyses for surface sediments sampled on the beach were conducted. Immediately after the typhoon invasion, Haeundae beach was eroded by 1.4 m in average height. The mean high tide lines were retreated back by 12 m, and beach slope became gentler from $3.8^{\circ}$ to $1.7^{\circ}$. The mean grain sizes of surface sediments became coarser from $1.6{\Phi}$ to $1.2{\Phi}$ after two months, and the sorting well sorted. After two months of typhoon landfall, the mean high tide lines have recovered by 85%, and the beach topography almost recovered. This suggests that the impact of typhoons on Haeundae beach erosion is negligible, and the relaxation time is shorter than that of other beaches.

• (The) Research of the performance art and culture
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• no.36
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• pp.255-287
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• 2018

This article deals with one of the pansori master's life and activities. Bak Songhui(1927~2017), who was the holder of National Intangible Cultural Asset No. 5 for pansori Heungboga. She had played a significant role through the modern history of pansori genre including Yeoseong Gukkeuk(Korean classical opera by women) and Changgeuk(Korean traditional opera in pansori style) as well as original pansori itself. In the article, the early stage of her learnings and the way she got involved to pansori from Gwonbeon period are offered, and the activities by group, solo recitals, and educational activity lists are also provided. Bak Songhui began to learn pansori, Geommu(dance), Seungmu(dance), Gayageum, Yanggeum, and Gagok genres at her age of 13 in Gwangju. She fulfilled 5 years of study in Gwangju Gwonbeon, and entered to a Hyeomnyulsa-travelling theater company, led by Gim Yeonsu at her age around 19. Later, Bak used to be an actress in Yeoseong Gugak Donghohoe(Female Korean music fans' club) led by Gim sohui as well as in Haennim Gukkeukdan, and Saehan Gukkeukdan at around her age of 30. She took the main actress' role in several performances. And thanks to her effort, the Yeoseong Gukkeuk can be one of the representative genre in history. As she entered to the National Changgeuk company, her brilliant talents worked well by leading the company's big hit with her talents of taking many different characters, devotions, and know-hows from her experience. After her 70s, she kept the pansori go on its right way to pass down. She unfolded pansori performances as well as her own students' public presentations, recordings, TV and radio broadcasting activities as the holder of National Intangible Cultural Asset. The activities that Bak Songhui showed us can become another chance to make her a great master of pansori, especially in Dongpyeonje style.

• Explosives and Blasting
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• v.37 no.3
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• pp.13-24
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• 2019

This paper was prepared to investigate the behavior of fragments in underwater torpedo explosion beneath a frigate or surface ship by using an explicit finite element analysis. In this study, a fluid-structure interaction (FSI) methodology, called the multi-material arbitrary Lagrangian-Eulerian (MM-ALE) approach in LS-DYNA, was employed to obtain the responses of the torpedo fragments and frigate hull to the explosion. The Euler models for the analysis were comprised of air, water, and explosive, while the Lagrange models consisted of the fragment and the hull. The focus of this modeling was to examine whether a worst-case fragment could penetrate the frigate hull located close (4.5 m) to the exploding torpedo. The simulation was performed in two separate steps. At first, with the assumption that the expanding skin of the torpedo had been torn apart by consuming 30% of the explosive energy, the initial velocity of the worst-case fragment was sought based on a well-known experimental result concerning the fragment velocity in underwater bomb explosion. Then, the terminal velocity of the worst-case fragment that is expected to occur before the fragment hit the frigate hull was sought in the second step. Under the given conditions, the possible initial velocities of the worst-case fragment were found to be very fast (400 and 1000 m/s). But, the velocity difference between the fragment and the hull was merely 4 m/s at the instant of collision. This result was likely to be due to both the tremendous drag force exerted by the water and the non-failure condition given to the frigate hull. Anyway, at least under the given conditions, it is thought that the worst-case fragment seldom penetrate the frigate hull because there is no significant velocity difference between them.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.1-27
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• 2021

The entire tourism industry is being hit hard by the COVID-19 as a global pandemic. Accommodation sharing services such as Airbnb, which have recently expanded due to the spread of the sharing economy, are particularly affected by the pandemic because transactions are made based on trust and communication between consumer and supplier. As the pandemic situation changes individuals' perceptions and behavior of travel, strategies for the recovery of the tourism industry have been discussed. However, since most studies present macro strategies in terms of traditional lodging providers and the government, there is a significant lack of discussion on differentiated pandemic response strategies considering the peculiarity of the sharing economy centered on peer-to-peer transactions. This study discusses the marketing strategy for individual hosts of Airbnb during COVID-19. We empirically analyze the effect of changes in listing descriptions posted by the Airbnb hosts on listing performance after COVID-19 was outbroken. We extract nine aspects described in the listing descriptions using the Attention-Based Aspect Extraction model, which is a deep learning-based aspect extraction method. We model the effect of aspect changes on listing performance after the COVID-19 by observing the frequency of each aspect appeared in the text. In addition, we compare those effects across the types of Airbnb listing. Through this, this study presents an idea for a pandemic crisis response strategy that individual service providers of accommodation sharing services can take depending on the listing type.

• Journal of Korean Society of Forest Science
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• v.100 no.4
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• pp.708-714
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• 2011

Wood store carbon that the forest absorbed until burned or decomposed over a long period. Such materials are most used in houses except in paper and pulp, and the use of wood in houses play an important role in reducing green-house gases. Therefore, we estimated the amount of carbon stocks in Korean houses, and analyzed how much contribution such stocks offers to green-house gas reduction. As the result, the carbon stocks amount of the wood products in Korean houses was 28.4 million $tCO_2$, which is 4.6% of the total annual green-house gas emission in Korea (620 million $tCO_2$ e), and 77.4% of forest sinks (LULUCF). Even though few wooden houses which use most wood in housing exist in Korea, the carbon stocks of wood products in houses in 2010 increased to 4.1 times that in 1975 (21.4 million $tCO_2$) because the carbon stocks increased due to apartment construction, which hit its stride from the last 1980's.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.391-404
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• 2021

This study developed a long-term prediction model for the potential yield of garlic based on a genetic algorithm (GA) by utilizing global climate reanalysis data. The GA is used for digging the inherent signals from global climate reanalysis data which are both directly and indirectly connected with the garlic yield potential. Our results indicate that both deterministic and probabilistic forecasts reasonably capture the inter-annual variability of crop yields with temporal correlation coefficients significant at 99% confidence level and superior categorical forecast skill with a hit rate of 93.3% for 2 × 2 and 73.3% for 3 × 3 contingency tables. Furthermore, the GA method, which considers linear and non-linear relationships between predictors and predictands, shows superiority of forecast skill in terms of both stability and skill scores compared with linear method. Since our result can predict the potential yield before the start of farming, it is expected to help establish a long-term plan to stabilize the demand and price of agricultural products and prepare countermeasures for possible problems in advance.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.315-320
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• 2022

This study discussed its implications for the meaning in life, which began to emerge through existential psychotherapy in the era of coronavirus infection 19 (COVID-19). In the midst of the COVID-19 pandemic, we are making efforts to live a meaningful life, and individuals and communities are making efforts to find meaning in how to live a meaningful life. Humanity has a premise for a peaceful life, and since the past, interest in the meaning in life has continued. The deadly virus called COVID-19, which hit the world in December 2019, created stress such as anxiety, alienation, and depression in people, endangering the lives of individuals and communities. Research on the meaning in life was active even before COVID-19, but I think it is necessary to look at the changes in people's meaning in life and how COVID-19 is affecting each individual amid the global pandemic of the virus. In other words, clarifying the meaning of our lives in the era of COVID-19 is a coping to reduce stress and a catalyst to improve the quality of life. This study aims to provide basic research to prepare ways to improve the quality of life in the era of COVID-19 by examining various perspectives and results on the meaning in life.

• Journal of the Korean Geotechnical Society
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• v.37 no.11
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• pp.51-60
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• 2021

River scour erodes the soil around the pier, reducing the lateral bearing capacity of the pier and lowering the stability of the structure. In this study, in order to examine the effect of scouring on the stability of the structure, an experiment was performed to measure the natural frequency of the pier according to the excavation of the surrounding ground. Impact vibration test was conducted on the pier with the caisson foundation of the Mangyeonggang Bridge, which is scheduled to be demolished. Accelerometers were attached to the top, center, and bottom of the pier and the acceleration responses were measured by hitting those three points. The experimental results showed that the top hit showed consistent and reasonable results of the acceleration responses according to the hitting position. The measured accelerations were converted to the frequency domain through Fast Fourier Transform (FFT), and then the natural frequency was determined. In addition, to analyze the scour effect on the natural frequency of the pier, the ground around the pier was excavated and the natural frequency change was analyzed. As a result, the natural frequency showed the decreasing tendency according to the excavation depth, but the decrease was small due to the large stiffness of the caisson foundation.

• Atmosphere
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• v.31 no.5
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• pp.577-592
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• 2021

This study evaluates the predictability of the number of days of heat and cold damages by growth stages of rice in South Korea using the hindcast data (1986~2020) produced by Pusan National University Coupled General Circulation Model-Weather Research and Forecasting (PNU CGCM-WRF) model chain. The predictability is accessed in terms of Root Mean Square Error (RMSE), Normalized Standardized Deviations (NSD), Hit Rate (HR) and Heidke Skill Score (HSS). For the purpose, the model predictability to produce the daily maximum and minimum temperatures, which are the variables used to define heat and cold damages for rice, are evaluated first. The result shows that most of the predictions starting the initial conditions from January to May (01RUN to 05RUN) have reasonable predictability, although it varies to some extent depending on the month at which integration starts. In particular, the ensemble average of 01RUN to 05RUN with equal weighting (ENS) has more reasonable predictability (RMSE is in the range of 1.2~2.6℃ and NSD is about 1.0) than individual RUNs. Accordingly, the regional patterns and characteristics of the predicted damages for rice due to excessive high- and low-temperatures are well captured by the model chain when compared with observation, particularly in regions where the damages occur frequently, in spite that hindcasted data somewhat overestimate the damages in terms of number of occurrence days. In ENS, the HR and HSS for heat (cold) damages in rice is in the ranges of 0.44~0.84 and 0.05~0.13 (0.58~0.81 and -0.01~0.10) by growth stage. Overall, it is concluded that the PNU CGCM-WRF chain of 01RUN~05RUN and ENS has reasonable capability to predict the heat and cold damages for rice in South Korea.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.543-552
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• 2022

When frost occurs, crops are directly damaged. When crops come into contact with low temperatures, tissues freeze, which hardens and destroys the cell membranes or chloroplasts, or dry cells to death. In July 2020, a sudden sub-zero weather and frost hit the Minas Gerais state of Brazil, the world's largest coffee producer, damaging about 30% of local coffee trees. As a result, coffee prices have risen significantly due to the damage, and farmers with severe damage can produce coffee only after three years for crops to recover, which is expected to cause long-term damage. In this paper, we tried to predict frost using frost generation data and weather observation data provided by the Korea Meteorological Administration to prevent severe frost. A model was constructed by reflecting weather factors such as wind speed, temperature, humidity, precipitation, and cloudiness. Using XGB(eXtreme Gradient Boosting), SVM(Support Vector Machine), Random Forest, and MLP(Multi Layer perceptron) models, various hyper parameters were applied as training data to select the best model for each model. Finally, the results were evaluated as accuracy(acc) and CSI(Critical Success Index) in test data. XGB was the best model compared to other models with 90.4% ac and 64.4% CSI, followed by SVM with 89.7% ac and 61.2% CSI. Random Forest and MLP showed similar performance with about 89% ac and about 60% CSI.