• Korean Journal of Mineralogy and Petrology
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• v.36 no.1
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• pp.73-94
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• 2023

We carried out the sensitive high resolution ion microprobe (SHRIMP) zircon U-Pb age dating and whole-rock geochemical analysis of granitoids and felsic porphyries in the Ssangyong Valley, Yongchu Valley, and Mungyeong Saejae geosites in the Mungyeong Geopark. The igneous rocks crop out in the western, northwestern and central parts of the Mungyeong city area, respectively, and intruded (meta)sedimentary successions of the Ogcheon Metamorphic Belt, Cambro-Ordovician Mungyeong Group and Jurrasic Daedong Group. The U-Pb isotopic compositions of zircon from two felsic porphyries and one granite samples in the Ssanyeong Valley yielded the Cretaceous intrusion ages of 93.9±3.3 Ma (tσ), 95.1±4.0 Ma (tσ) and 94.4±2.0 Ma (tσ), respectively. On the other hand, a felsic dike sample and a granite in the Yongchu Valley and a porphyritic granite in the Mungyeong Saejae had intrusion ages of 90.2±2.0 Ma (tσ), 91.0±3.0 Ma (tσ) and 88.6±1.5 Ma (tσ), respectively. Based on the average standard error calculated in combination with results of previous studies in this area (Lee et al., 2010; Yi et al., 2014; Aum et al., 2019), the geochronological results show that spatial variation in intrusion age of ~5 Myr between the Ssangyong (94.5±0.2 Ma) and Yongchu Valleys (89.7±0.4 Ma) is apparent. The geochemical compositions of major and trace elements in the samples showed an affinity of typical post-orogenic granite, indicating their petrogenesis during the late stage of Early Cretaceous magmatic activity possibly in association with subduction events of the Izanagi Plate.

• Korean Journal of Environment and Ecology
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• v.36 no.6
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• pp.582-591
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• 2022

This study was conducted to eliminate Myocastor coypusMolina, 1782 (Nutria) from Jeju Special Self-Governing Province, South Korea. Habitat identification and eradication were carried out from September to November 2013, and a survey was carried out until June 2022 to check whether the eradication was successful. The habitat was identified with unmanned cameras, interviews, and literature surveys, and the capture was performed using the trapping method with food to attract nutria to the habitat area. The study area for the follow-up survey, which was set relatively wide considering nutria's home range, included wetlands and rivers within 4.0 km² of the habitat area (eradication area). As a result, nutria's habitat was confirmed only at Songdang Ranch, Songdang-ri, of Jeju Island, with traces of habitat (footprints, excrement, and burrows) confirmed in waterways and ponds within the pasture. Eight individuals were captured, including four females, three males, and one individual in too advanced a state of decay to identify the sex. The follow-up survey thoroughly investigated the habitat and its surroundings, focusing on three areas with permanent water, Seongeup Reservoir, Cheonmi Creek, and Molsuni Pond, but no signs of habitat were identified. Therefore, it is determined that nutria inhabiting Jeju Island has been completely eradicated. It is believed that the successful eradication of nutria in the Jeju Special Autonomous Region was possible due to a synergy between 1) the eradication of nutria at the beginning of the settlement phase through rapid capture after confirming the nutria habitat and 2) the delayed expansion period because of rare presence of wetlands, where water is constantly stagnant, on Jeju Island. These results imply that quickly identifying the ecological characteristics of the species and preventing disturbances before they or at the beginning of the ecological disturbance through control and eradication at the initial stage of settlement before the expansion stage is an effective measure to cope with the influx of alien species.

• Journal of Korean Society of Forest Science
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• v.112 no.2
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• pp.157-172
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• 2023

Controlled pollination (CP) is an important method in tree breeding programs because CP quickly generates desirable genotypes and rapidly maximizes genetic gains. However, few studies have evaluated the efficiency and success rate of CP in the breeding program of Pinus densiflora. To evaluate CP and the management of control pollinated progenies, we used 159 individuals in CB2 × KW40 or KW40 × CB2 populations that were established in 2015. After genotyping microsatellite loci, we estimated whether the number of primers was sufficient or not. Then, we performed pedigree analysis. The result showed that the number of primers was sufficient. By pedigree analysis, we found out that 60 of 159 individuals had been generated by the mating between CB2 and KW40. In the maternity analysis, there was evidence to indicate the possibility of management problems. Therefore, we excluded 54 individuals and repeated the pedigree analysis. In the second analysis, 47 of 105 individuals were generated by the mating between CB2 and KW40. To increase the efficiency of CP in tree breeding programs, several precautions are required. It is necessary to identify the exact clone names of the mother and father trees. In addition, CP processes should be performed properly, including deciding on the schedule of CP and the isolation of female strobili or flowers. Finally, the monitoring of hybrid progenies management after mating is important. Molecular markers should be used to identify the clone names of the mother and father trees and for monitoring post hoc management. This study provides a reference for tree breeding programs for the future control pollination of pine species.

• Korean Journal of Ecology and Environment
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• v.55 no.1
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• pp.60-75
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• 2022

The Bayesian algorithm model is a model algorithm that calculates probabilities based on input data and is mainly used for complex disasters, water quality management, the ecological structure between living things or living-non-living factors. In this study, we analyzed the main factors affected Korean Estuary Trophic Diatom Index (KETDI) change based on the Bayesian network analysis using the diatom community and physicochemical factors in the domestic estuarine aquatic ecosystem. For Bayesian analysis, estuarine diatom habitat data and estuarine aquatic diatom health (2008~2019) data were used. Data were classified into habitat, physical, chemical, and biological factors. Each data was input to the Bayesian network model (GeNIE model) and performed estuary aquatic network analysis along with the nationwide and each coast. From 2008 to 2019, a total of 625 taxa of diatoms were identified, consisting of 2 orders, 5 suborders, 18 families, 141 genera, 595 species, 29 varieties, and 1 species. Nitzschia inconspicua had the highest cumulative cell density, followed by Nitzschia palea, Pseudostaurosira elliptica and Achnanthidium minutissimum. As a result of analyzing the ecological network of diatom health assessment in the estuary ecosystem using the Bayesian network model, the biological factor was the most sensitive factor influencing the health assessment score was. In contrast, the habitat and physicochemical factors had relatively low sensitivity. The most sensitive taxa of diatoms to the assessment of estuarine aquatic health were Nitzschia inconspicua, N. fonticola, Achnanthes convergens, and Pseudostaurosira elliptica. In addition, the ratio of industrial area and cattle shed near the habitat was sensitively linked to the health assessment. The major taxa sensitive to diatom health evaluation differed according to coast. Bayesian network analysis was useful to identify major variables including diatom taxa affecting aquatic health even in complex ecological structures such as estuary ecosystems. In addition, it is possible to identify the restoration target accurately when restoring the consequently damaged estuary aquatic ecosystem.

• Korean Journal of Heritage: History & Science
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• v.55 no.4
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• pp.118-135
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• 2022

The primary purpose of this study is to estimate the structure of Byeongpungsadaseok (屛風莎臺石) and Nanganseok (欄干石) in Geonwonneung (建元陵) and Heonneung (獻陵), which were built in the early of 15th century, based on the Annals of King Sejong. In addition, the ultimate purpose of this study is to reveal structural changes and their significance by comparing the differences with the contents of the dismantlement survey. Geonwonneung, Jereung(齊陵), and Heonneung were repaired at the same time in 1442, and the structural changes were the similar. The purpose of the repair in 1442 was to prevent water from flowing into the underground palace with smooth drainage. As a result of estimating the structure of Geonwonneung and Heonneung according to the records of the Annals of King Sejong, it was created in a very similar form to the Hyeonneung and Jeongneung of Goryeo. And it was clearly recognized that the Royal Tomb of Goryeo was followed. However, as the structure was improved in 1442, the unique characteristics of the Royal Tomb of the Joseon Dynasty were formed. First is the appearance of the Bokbuhyeong lime (覆釜形石灰, which is a convex roof on the Byeongpungsadaseok that serves to prevent rainwater from penetrating into the burial mound. It also plays a role in connecting and fixing the Manseok (滿石) and the Inseok (引石), which are the upper structures of the Sadaseok (莎臺石). Second, the Bakseok (薄石) between the nanganseok and the sadaseok has been transformed into the Sangseok (裳石) with a slope. This plays a role in protecting the inner stone chamber by expanding the length of the bakseok, which forms an overall slope, like the eaves of the roof. After both of these features were first attempted in 1442, they were applied to all Royal Tombs of the Joseon Dynasty and became unique features of these Royal Tombs.

• (The) Research of the performance art and culture
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• no.23
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• pp.63-103
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• 2011

This paper inquires closely into the background of pansori gosu(drummer) and his social position based on documents and oral materials and the performance features of gosu in the entire process of pansori performance, 'preparation', 'performance' and 'aftermath', focused on the relationship between the changja(singer)-gosu. In the past, some gosus were ex-tightrope performers. Their social position and working conditions were better than that of the ex-tightrope performers but were worse than that of the pansori singer. After 1910's, people formed some special sense about the gosu due to the change of the space for pansori performances and the technological advances on the media, and gosu's conditions improved. The theory of pansori drum gradually began to be established well. The function and the role of gosu in the whole process of pansori performance may be summarized as follows. To begin with, the training with various and a lot of singers is required in the 'preparation'. Rehearsals are divided into individual practices and joint practices, and the latter can be controlled by the level of the capacity of gosu and the degree of the experience between chanja-gosu. Next, bobiwi(flattering drumming) and chuimsae(encouraging remarks) are important in tbe 'process'. The gosu has to share the speed of one jangdan(rhythmic patterns) and the accent of the sori and adjust his enery. Besides, he has to acknowledge the naedeureum(beginning sign) and reply with changja's singing. In formal performances, working in harmony with changja and gosu and their joint experiences are necessary for the gosu; in pansori contests, giving chanja a stability; in contests for gosu, drumming skill, position, chuimsae; in small performances and new adaptation of pansori, cheap fees and positive response of the transformational play or ad-lib; in lecturer concerts, reacting quickly to rapidly changing situations. Chuimsae is way which gosus and audiences express their feeling together, however, its context and sound are different. Finally, 'aftermath' is a process the pair of chamgja and gosu mutually evaluates about performance or audiences estimate that.

• Korean small business review
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• v.39 no.1
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• pp.1-39
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• 2017

The first generation of the business that had been founded in 1960~1970s faces the situation to consider the succession of the family business developed by devotion of their whole lives in the critical timing to the next generation. In the process of selecting the party of family business succession, it is required to consider a variety of succession types including smooth transfer to the other family member or the employee of the company, selling the company, or hiring external specialist. Foreign countries acknowledge the importance of the succession in the family owned company to perform multiple studies on the influential factors to the succession, distinction, and types of family business succession; and they utilize the results for the related policy development and the support of family owned business succession. However, few studies have been conducted on the succession of the domestic family owned business and majority of them are related to the types of succession. Considering its share and influential power in the domestic economy, it is necessary to develop the guideline and the policies to solve many issues on the succession of the family owned business by systemic studies. Hence, the impact of the main characteristics in the family owned business on the types of its succession was analyzed in this study focusing on five domains of Socioemtional Wealth (SEW) in view of Behavioral Agency Theory by Gomez-Mejia et al. (2007) using the data from 540 family owned small-to-medium sized businesses so as to analyze the issues on their business succession. Upon the empirical analysis results, it was confirmed that they were influenced to the selection of succession type by family succession > internal employee succession > external succession, for the variables of social contribution which were non-financial characteristics, internal employee succession > family succession > external succession for the intellectual properties, and family succession > external succession for the management participation of the family. The distinction of social contribution were influenced the most to the selection of the succession types. Financial factors, business performance, and R&D investment variables were not significantly influenced to their selection of the succession types. In case of simultaneous management, the family succession rate was high and it showed the control effect to strengthen selecting family owned business with R&D investment, social contribution, and company history variables. The behavioral agency theory used in this study was confirmed with high explanation power on the family owned business succession. The family owned business showed the tendency to maintain SEW, and non-financial factors such as accumulated know-how and social contribution based on the long term history were significantly affected to the succession in the small-to-medium sized family owned businesses, unlike general large sized listed companies. The results of this study are expected to be helpful practically for the succession of the family owned business and to suggest the guideline for the development of governmental policy.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.306-314
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• 2023

Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and　industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1031-1042
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• 2023

In this study, a deep learning model was developed to predict the yield of cabbage and radish, one of the five major supply and demand management vegetables, using satellite images of Landsat 8. To predict the yield of cabbage and radish in Gangwon-do from 2015 to 2020, satellite images from June to September, the growing period of cabbage and radish, were used. Normalized difference vegetation index, enhanced vegetation index, lead area index, and land surface temperature were employed in this study as input data for the yield model. Crop yields can be effectively predicted using satellite images because satellites collect continuous spatiotemporal data on the global environment. Based on the model developed previous study, a model designed for input data was proposed in this study. Using time series satellite images, convolutional neural network, a deep learning model, was used to predict crop yield. Landsat 8 provides images every 16 days, but it is difficult to acquire images especially in summer due to the influence of weather such as clouds. As a result, yield prediction was conducted by splitting June to July into one part and August to September into two. Yield prediction was performed using a machine learning approach and reference models , and modeling performance was compared. The model's performance and early predictability were assessed using year-by-year cross-validation and early prediction. The findings of this study could be applied as basic studies to predict the yield of field crops in Korea.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1211-1224
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• 2023

Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.