• Korean Journal of Heritage: History & Science
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• v.44 no.2
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• pp.4-25
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• 2011

This study was performed in 2010 to examine the flora and vegetation structure and chemical characteristics of soil in the growing community of Abeliophyllum distichum, located in the Byeonsanbando National Park. This Abeliophyllum distichum community has more individual numbers in Cheongrim-ni and Jungkye-ri, Byeonsan-myeon, and Buan-gun area, which is designated as a Natural Monument (No. 370), and also where the habitat conditions for Abeliophyllum distichum is more favorable. The authors recorded 100 taxa with 45 families, 82 genus, 93 species, 4 varieties, and 3 forms. Among them, species such as Abeliophyllum distichum (critically endangered), Asarum maculatum (near threatened) and Chionanthus retusa (near threatened), which are categorized as rare plants, were recorded. According to the list of Korean endemic plants, 4 taxa, particularly Philadelphus schrenckii, Abeliophyllum distichum, Weigela subsessilis, and Lonicera subsessili, were recorded. The community of Abeliophyllum distichum is located in the northwest slope of Baekcheon watershed and the community is comprised of healthy soil. The community structure was classified into three: the Castanea crenata community, Zelkova serrata community, and Quercus serrata community. The Castanea crenata community is composed of the Cornus walteri, Platycarya strobilacea, Zelkova serrata, Rhamnella frangulioides, arranged in terms of importance percentage. The Zelkova serrata community is composed of Celtis sinensis, Quercus aliena, Styrax japonica, and Acer pseudo-sieboldianum, also according to importance percentage. As for the Quercus serrata community, it is composed of Quercus variabilis, Castanea crenata, and Prunus sargentii, also arranged in terms of importance percentage. The importance percentage of Abeliophyllum distichum is 6.6% in the Castanea crenata community, 5.6% in the Zelkova serrata community and 5.1% in the Quercus serrata community. Moreover, in order of chemical characteristics of soil pH, electrical conductivity, available phosphoric, organic matter, and exchangeable cation (K, Ca, Mg) are analyzed. The No. 3 site was relatively higher than other districts of the same chemical characteristics of soil.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.2
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• pp.105-111
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• 2021

Rice lodging is an annual occurrence caused by typhoons accompanied by strong winds and strong rainfall, resulting in damage relating to pre-harvest sprouting during the ripening period. Thus, rapid estimations of the area of lodged rice are necessary to enable timely responses to damage. To this end, we obtained images related to rice lodging using a drone in Gimje, Buan, and Gunsan, which were converted to 128 × 128 pixels images. A convolutional neural network (CNN) model, a deep learning model based on these images, was used to predict rice lodging, which was classified into two types (lodging and non-lodging), and the images were divided in a 8:2 ratio into a training set and a validation set. The CNN model was layered and trained using three optimizers (Adam, Rmsprop, and SGD). The area of rice lodging was evaluated for the three fields using the obtained data, with the exception of the training set and validation set. The images were combined to give composites images of the entire fields using Metashape, and these images were divided into 128 × 128 pixels. Lodging in the divided images was predicted using the trained CNN model, and the extent of lodging was calculated by multiplying the ratio of the total number of field images by the number of lodging images by the area of the entire field. The results for the training and validation sets showed that accuracy increased with a progression in learning and eventually reached a level greater than 0.919. The results obtained for each of the three fields showed high accuracy with respect to all optimizers, among which, Adam showed the highest accuracy (normalized root mean square error: 2.73%). On the basis of the findings of this study, it is anticipated that the area of lodged rice can be rapidly predicted using deep learning.

• Journal of Service Research and Studies
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• v.13 no.2
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• pp.62-81
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• 2023

The purpose of this study is to propose policies to improve and revitalize rural bus services in Jeollabuk-do in the future by identifying the factors that affect service satisfaction and policy satisfaction and the relationship between them, targeting rural bus users in 4 cities and counties in Jeollabuk-do. In the four cities and counties in the study area, the number of rural bus users is continuously decreasing, and various transportation policies, such as unification of bus fares and demand-response transportation, are being piloted to promote bus use. In this study, three major service quality factors that affect rural bus service satisfaction and policy satisfaction were derived after a literature review. Modifying the research model presented in previous studies, we have presented a research model to verify the relationship between the three factors affecting service satisfaction and policy satisfaction, and the relationship between service satisfaction and policy satisfaction. For the verification of the research model, a total of 520 survey data collected from passengers near bus stops and bus terminals in four cities and counties, Gochang, Gimje, Buan, and Jeongeup, were used. As a result of the verification, it was found that the three factors of economic feasibility, convenience, and safety had a statistically positive (+) effect on service satisfaction, but only convenience and safety had a positive (+) effect on policy satisfaction. Contrary to the research hypothesis, it was found that there was no statistically significant relationship between service satisfaction and policy satisfaction. Although the result is different from the research hypothesis, it was a meaningful result that can make policy suggestions on the improvement of the unified fare system policy, service satisfaction, and policy satisfaction to Jeollabuk-do rural bus transportation policy makers and working-level officers. In conclusion, based on the results of research analysis, the unified fare system, and transportation policy, measures to improve service satisfaction and policy satisfaction were presented.