• Korean Journal of Breeding Science
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• v.40 no.2
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• pp.164-167
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• 2008

A rose cultivar "Haedoji" developed at the Jeollanamdo Agricultural Research and Extention Services (JARES) is a standard type with deep Red flower. From 2000, two cultivars 'Vital' and 'Cardinal' were examined for horticultural characteristics and were included in cross-combination in 2003. Cultivar 'Vital', a vigorous standard type, first preference with red flower, was used as a mother plant and cultivar 'Cardinal', a red flower standard type with light color, was used as a pollen-donor plant. seventeen six breeding lines were selected in 2004 based on flower shape, flower color and abundance of petal numbers on the first selection. two breeding lines were selected in 2004 based on powderly mildew and vigor on the second selection. For three years, from 2005 till 2007, one breeding lines were selected and examined for their productivity, and then cultivar "Haedoji" was developed because of distinctive characters such as light red color flower, upright stem, long vase-life and Resistance to the Powderly Mildew. A standard type with intermediate sized flower, cultivar "Haedoji" shows in average 9.2 cm flower diameter, 62.0 cm flower stem length, and 9.5 days vase-life. The average productivity for three years was $167.3stems{\cdot}m^{-2}$ per year and increased 2% compare to cultivar 'Tiamo' with $163.9stems{\cdot}m^{-2}$ per year.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.2
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• pp.97-109
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• 2019

Degree days have been determined using temperature data measured at nearby weather stations to a site of interest to produce information for supporting decision-making on agricultural production. Alternatively, the data products of Moderate Resolution Imaging Spectroradiometer (MODIS) can be used for estimation of degree days in a given region, e.g., Korean Peninsula. The objective of this study was to develop a simple tool for processing the MODIS product for estimating cooling degree days (CDD), which would help assessment of heat stress conditions for a crop as well as energy requirement for greenhouses. A set of scripts written in R was implemented to obtain temperature profile data for the region of interest. These scripts had functionalities for processing spatial data, which include reprojection, mosaicking, and cropping. A module to extract air temperature at the surface pressure level was also developed using R extension packages such as rgdal and RcppArmadillo. Random forest (RF) models, which estimate mean temperature and CDD with a different set of MODIS data, were trained at 34 sites in South Korea during 2009 - 2018. Then, the values of CDD were calculated over Korean peninsula during the same period using those RF models. It was found that the CDD estimates using the MODIS data explained >74% of the variation in the CDD measurements at the weather stations in North Korea as well as South Korea. These results indicate that temperature data derived from the MODIS atmospheric products would be useful for reliable estimation of CDD. Our results also suggest that the MODIS data can be used for preparation of weather input data for other temperature-based agro-ecological models such as growing degree days or chill units.

• Journal of Environmental Impact Assessment
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• v.29 no.6
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• pp.430-440
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• 2020

The application contents, process, and its limitations are discussed for the setting of Korean legal guides & criteria for water cycle and ecological condition in development project of land use by thorough comparison and examination of prerequisites and credits of water cycle and soil+vegetation by USA's SITES (Sustainable Sites Initiative). In the case of SITES, due to the implementation procedure operated as a non-governmental independent assessment system by Green Business Certification, Inc, the natural condition of water cycle and soil-vegetation items-the key element of ecosystem services can be quantitatively assessed, well along with its legal and institutional guidelines and regulations. On the other hand, in the case of Korea, as a part of the national certification procedure for green building, the ecological area ratio system still have very limited role as an only amenity resource in the creation of artificial green spaces and insufficiency of management system for rain water. In conclusion, it was understood as an urgent situation in necessary for prompt establishment of site's sustainability certification system at the national level, based on management of water circulation and natural soil & vegetation in developed area with consideration of various land uses and types of development projects.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.184-192
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• 2022

Valve internal leakage is caused by damage to the internal parts of the valve, resulting in accidents and shutdowns of the piping system. This study investigated the possibility of a real-time leak detection method using the acoustic emission (AE) signal generated from the piping system during the internal leakage of a butterfly valve. Datasets of raw time-domain AE signals were collected and postprocessed for each operation mode of the valve in a systematic manner to develop a data-driven model for the detection and classification of internal leakage, by applying machine learning algorithms. The aim of this study was to determine whether it is possible to treat leak detection as a classification problem by applying two classification algorithms: support vector machine (SVM) and convolutional neural network (CNN). The results showed different performances for the algorithms and datasets used. The SVM-based binary classification models, based on feature extraction of data, achieved an overall accuracy of 83% to 90%, while in the case of a multiple classification model, the accuracy was reduced to 66%. By contrast, the CNN-based classification model achieved an accuracy of 99.85%, which is superior to those of any other models based on the SVM algorithm. The results revealed that the SVM classification model requires effective feature extraction of the AE signals to improve the accuracy of multi-class classification. Moreover, the CNN-based classification can be a promising approach to detect both leakage and valve opening as long as the performance of the processor does not degrade.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1245-1255
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• 2022

Terra Nova Bay polynya (TNBP) is a representative coastal polynya in East Antarctica, which is formed by strong katabatic winds. As the TNBP is one of the major sea ice factory in East Antarctica and has a great impact on regional ocean circulation and surrounding marine ecosystem, it is very important to analyze its area change and development characteristics. In this study, we detected the TNBP from synthetic aperture radar (SAR) and optical images obtained from April 2007 to April 2022 by visually analyzing the stripes caused by the Langmuir circulation effect and the boundary between the polynya and surrounding sea ice. Then, we analyzed the area change and development characteristics of the TNBP. The TNBP occurred frequently but in a small size during the Antarctic winter (April-July) when strong katabatic winds blow, whereas it developed in a large size in March and November when sea ice thickness is thin. The 12-hour mean wind speed before the satellite observations showed a correlation coefficient of 0.577 with the TNBP area. This represents that wind has a significant effect on the formation of TNBP, and that other environmental factors might also affect its development process. The direction of TNBP expansion was predominantly determined by the wind direction and was partially influenced by the local ocean current. The results of this study suggest that the influences of environmental factors related to wind, sea ice, ocean, and atmosphere should be analyzed in combination to identify the development characteristics of TNBP.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1643-1652
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• 2022

Deposited Marine Debris(DMD) can negatively affect marine ecosystems, fishery resources, and maritime safety and is mainly detected by sonar sensors, lifting frames, and divers. Considering the limitation of cost and time, recent efforts are being made by integrating underwater images and artificial intelligence (AI). We conducted a comparative study of You Only Look Once Version 5 (YOLOv5) and You Only Look Once Version 7 (YOLOv7) models to detect DMD from underwater images for more accurate and efficient management of DMD. For the detection of the DMD objects such as glass, metal, fish traps, tires, wood, and plastic, the two models showed a performance of over 0.85 in terms of Mean Average Precision (mAP@0.5). A more objective evaluation and an improvement of the models are expected with the construction of an extensive image database.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1031-1039
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• 2022

As one of the hydrological factors closely related to landslides, precipitation indirectly affects slope stability by generating external forces. Groundwater level fluctuations have attracted more attention lately as factors that directly affect slope stability have become more prominent. Therefore, this study attempted to analyze the relationship between variables through changes in precipitation, groundwater levels, and land displacement. A time series-based analysis was conducted using satellite-based precipitation and point-based groundwater levels in conjunction with the PSInSAR technique to simulate land displacement in urban and mountainous areas. There was a sharp rise in groundwater levels in both urban and mountain areas during heavy rainfall, and a continuous decrease in urban areas when rainfall was low. 6 mm of displacements was observed in the mountainous area as a results of soil outflow from the topsoil layer, which was accompanied by an increased groundwater level. Meanwhile, different results were found in urban area. In response to the rise in groundwater level, the land displacement increases due to the expansion of soil skeletons, while the decrease seems to be attributed to anthropogenic influences. Overall, there was no consistent relationship between groundwater levels and land displacement, which appears to be caused by factors other than hydrological factors. Additional consideration of environmental factors could contribute to a deeper understanding of the relationship between the two factors.

• Korean Journal of Culture and Social Issue
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• v.28 no.3
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• pp.513-527
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• 2022

This study was conducted to examining the socio-cultural impact of the COVID-19 pandemic that swept the world around 2020, and the transformation of norms and social problems due to COVID-19. For this, the characteristics of changes in the socio-cultural norms of the 14th century European Black Death, a representative example of the pandemic, were derived, and based on this, the COVID-19 pandemic was analyzed. The Black Death served as an opportunity to change social norms based on the existing religious authority and the power of the feudal system to the Enlightenment. The population declination and labor shortage also promoted commercialization and mechanization. Printing, which spread during this period, led to the popularization of knowledge, which raised the level of thinking and led to epochal scientific development. This became the foundation of the Industrial Revolution. Like the recent Black Death, COVID-19 has triggered changes in social norms. The technological environment of metaverse, a mixture of virtual and reality, has changed the norm of a consistent identity into free and open identities exerting various potentials through alternate characters. In addition, meme, which are about people being friendly to those with the same worldview as him on the metaverse, weakened the sense of isolation in non-face-to-face situations. Artificial intelligence (AI), which developed during the COVID-19 pandemic, has entered the stage of being used for creative activities beyond the function of assisting humans. Discussions were held on what new social problems would be created by the social norms changed due to the COVID-19 pandemic.

• Journal of Service Research and Studies
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• v.11 no.2
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• pp.1-19
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• 2021

This study was conducted to derive a model of a sustainable politics and administration system that will enhance human happiness. A new long-term sustainable development model has been established based on the experience of the politics and administration system over the past thousands of years. Currently, the democratic political system and the bureaucratic administrative system dominate, but they are facing many problems. In this study, we analyzed the politics and administration system experienced by human society, and derived a model of a politics and administration system that is ideal for the present and future societies and is sustainable in the long term. The necessary condition should be a model that can solve the problems of the current politics and administration system. It must be a model that is faithful to the characteristics and essence of modern society. And as a sufficient condition to ensure long-term sustainability, it must be based on the common principles of human society. After analyzing the problems of the current system and analyzing the conditions required for the new system, the axioms that are the basis of the politics and administration system were presented. Based on the axioms, the structure and operation model of a new politics and administration system were derived. The derived model was named as a servicism politics and administration system. It is a dynamic model in which two opposing opponents recognize each other's contradictions and balance them dialectically in the space-time dimension.