• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.6-7
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• 2021

Vegetation development in rivers is one of the important issues not only in academic fields such as geomorphology, ecology, hydraulics, etc., but also in river management practices. The problem of river vegetation is directly connected to the harmony of conflicting values of flood management and ecosystem conservation. In Korea, since the 2000s, the issue of river vegetation and land formation has been continuously raised under various conditions, such as the regulating rivers downstream of the dams, the small eutrophicated tributary rivers, and the floodplain sites for the four major river projects. In this background, this study proposes a method for classifying the distribution of vegetation in rivers based on remote sensing data, and presents the results of applying this to the Naeseong Stream. The Naeseong Stream is a representative example of the river landscape that has changed due to vegetation development from 2014 to the latest. The remote sensing data used in the study are images of Sentinel 1 and 2 satellites, which is operated by the European Aerospace Administration (ESA), and provided by Google Earth Engine. For the ground truth, manually classified dataset on the surface of the Naeseong Stream in 2016 were used, where the area is divided into eight types including water, sand and herbaceous and woody vegetation. The classification method used a random forest classification technique, one of the machine learning algorithms. 1,000 samples were extracted from 10 pre-selected polygon regions, each half of them were used as training and verification data. The accuracy based on the verification data was found to be 82~85%. The model established through training was also applied to images from 2016 to 2020, and the process of changes in vegetation zones according to the year was presented. The technical limitations and improvement measures of this paper were considered. By providing quantitative information of the vegetation distribution, this technique is expected to be useful in practical management of vegetation such as thinning and rejuvenation of river vegetation as well as technical fields such as flood level calculation and flow-vegetation coupled modeling in rivers.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.595-601
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• 2008

The purpose of this study is to investigate the trends and patterns of various kind of water uses in a household by metering in Korea. Water use components are classified by toilet, washbowl, bathing, laundry, kitchen, miscellaneous. Flow meters are installed in 140 household selected by sampling in all around Korea. The data are gathered by web-based data collection system from the year 2002 to 2006, considering pre-investigated data such as occupation, revenue, family members, housing types, age, floor area, water saving devices, education, miscellaneous. Reliable data are selected by upper fence method for each observed water use component and statistical characteristics are estimated for each residential type to determine liter per capita per day. Estimated domestic per capita day show an indoor water use with the range from 150 lpcd to 169 lpcd for each housing type as the order of high rise apartment, multi-house, and single house. As the order of consuming amount among water use components, it is investigated that toilet (38.5 lpcd) is the first, and the second is laundry water (30.8 lpcd), the third is kitchen (28.4 lpcd), the fourth is bathtub (24.7 lpcd), the next is washbowl (15.4 lpcd). The results are compared with water uses in U.K. and U.S. As life style has been changed into western style, pattern of water use in Korea is tend to be similar with the U.S. water use pattern. Compared with the surveying results by Bradley, on 1985. Thirty liter of total use increased with the advancement of economic level, and a little change of water use pattern can be found. Especially, toilet water take almost half part of total water use and laundry water shows lowest as 11% in surveying at the year of 1985. But, this study shows that 39 liter, 28% of toilet water, has been decreased by the spread of saving devices and campaign. It is supposed that the spread large sized laundry machine make by-hand laundry has been decreased and water use increased. Unit water amount of each end-use in household can be applied to design factor for water and wastewater facilities, and it play a role as information in establishing water demand forecasting and conservation policy.

• The Journal of Korean Academy of Sensory Integration
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• v.21 no.1
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• pp.47-58
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• 2023

Objective : This study aimed to investigate the current status and actual use of assessment tools by institutions in the field of occupational therapy with children in Korea. Methods : The study was conducted with 67 occupational therapists working with children in Korea. To investigate the use of evaluation tools by area, knowledge of the evaluation tools, and desire to participate in further education, the questionnaires used in studies by Lee, Hong, and Park (2018) and Kim (2015) were modified and supplemented according to the child evaluation tools currently in usein institutions in Korea. For data collection, we distributed Google questionnaires to child occupational therapists for 3 weeks using convenience sampling. Excel was used to analyze the use of the evaluation tools according to institution. Technical statistics and frequency analyses were used to verify the general characteristics, evaluation-related information, status of evaluation tool use, knowledge levels relating to evaluation tools, and desire to participate in education. A t-test was used for the evaluation tool status. Results : Welfare centers used the most evaluation tools, with an average of 11.1, followed by university hospitals, rehabilitation hospitals, clinics, and daycare centers. There were differences in the choice of tools used, hospital with the Jebsen-Taylor hand function test and the Wee-FIM (Functional Independence Measure) being the most frequently applied. Centers, daycare centers, and welfare center the Sensory Profile test and clinical observation were also used often. Regarding the level of knowledge of evaluation tools and the desire to participate further in education, 30 (44.8%) of the respondents had not completed their education, and 42 (62.7%) rated their knowledge level as generally low. When asked about the importance of using a manual to guide them in their use of evaluation tools, 66 (98.6%) answered positively, and 66 (98.6%) answered that they needed specialized training in the use of evaluation tools. Conclusion : This study makes it possible to understand the use and status of evaluation tools as used by different institutions in Korea in the field of child occupational therapy It is anticipated that it will provide the basis for introducing existing evaluation tools and preparing new evaluation tools to be used in this field in Korea.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.4
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• pp.297-306
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• 2023

Saemangeum Lake is the largest artificial lake in Korea. The continuous deterioration of lake water quality necessitates the introduction of novel water quality management strategies. Therefore, this study aims to identify the spatiotemporal water quality characteristics of Saemangeum Lake using data from the National Water Quality Measurement Network and provide basic information for water quality management. In the water quality parameters of Saemangeum Lake, water temperature and total phosphorous content were correlated, and salt, total nitrogen content, pH, and chemical oxygen demand were significantly correlated. Other parameters showed a low correlation. The spatial principal component analysis of Saemangeum Lake showed the characteristics of its four zones. The mid-to-downstream section of the river affected by freshwater inflow showed a high nutrient salt concentration, and the deep-water section of the drainage gate and the lake affected by seawater showed a high salt concentration. Two types of water qualities were observed in the intermediate water area where river water and outer sea water were mixed: waters with relatively low salt and high chemical oxygen demand, and waters with relatively low salt and high pH concentration. In the principal component analysis by time, the water quality was divided into four groups based on the observation month. Group I occurred during May and June in late spring and early summer, Group II was in early spring (March-April) and late autumn (November-December), Group III was in winter (January-February), and Group IV was in summer (July-October) during high temperatures. The water quality characteristics of Saemangeum Lake were found to be affected by the inflow of the upper Mangyeong and Dongjin rivers, and the seawater through the Garuk and Shinshi gates installed in the Saemangeum Embankment. In order to achieve the target water quality of Saemangeum Lake, it is necessary to establish water quality management measures for Saemangeum Lake along with pollution source management measures in the upper basin.

• Korean small business review
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• v.31 no.1
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• pp.73-88
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• 2009

This study examines the characteristics of 24 Korean hidden champions such as key success factors, core competences, strategic problems, and desirable future directions. The study categorized them into 8 types with Danny Miller's four trajectories and top manager's decision making style(rationality and passion). Danny Miller argued in his book, Icarus paradox, that outstanding firms will extend their orientations until they reach dangerous extremes and their momentum will result in common trajectories of decline. He suggested four very common success types: Craftsmen, Builders, Pioneers, Salesmen. He also suggested common trajectories of decline:Focusing(from Craftsmen to Tinkers), Venturing(from Builders to Imperialists), Inventing(from Pioneers to Escapists), Decoupling(from Salesmen to Drifts). In Korea, successful startups appear to possess three kinds of drive: Technology-drive, Vision-drive, Market-drive. Successful technology-driven firms tend to grow as craftsmen or pioneers. Successful vision-driven and market-driven ones tend to grow as builders and salesmen respectively. Korean top managers or founders seem to have two kinds of decision making style: Passion-based and Rationality-bases. Passion-based(passionate) entrepreneurs are biased towards action or proactiveness in competing and getting things done. Rationality- based ones tend to emphasis the effort devoted to scanning and analysing information to better understand a company's threats, opportunities and options. Consequently this study suggested 4*2 types of Korean hidden champions: (1) passionate craftsmen, (2) rational craftsmen, (3) passionate builders, (4) rational builders, (5) passionate pioneers, (6) rational pioneers, (7) passionate salesmen, (8) rational salesmen. These 8 type firms showed different success stories and appeared to possess different trajectories of decline. These hidden champions have acquired competitive advantage within domestic or globally niche markets in spite of the weak market power and lack of internal resources. They have maintained their sustainable competitiveness by utilizing three types of growth strategy; (1) penetrating into the global market, (2) exploring new service market, (3) occupying the domestic market. According to the types of growth strategy, these firms showed different financial outcomes and possessed different issues for maintaining their competitiveness. This study found that Korean hidden champions were facing serious challenges from the transforming economic structure these days and possessed the decline potential from their success momentum or self-complacence. It argues that they need to take a new growth engine not to decline in the turbulent environment. It also discusses how firms overcome the economic crisis and find a new business area in promising industries for the future. It summarized the recent policy of Korean government called as "Green Growth" and discussed how small firms utilize such benefits and supports from the government. Other implications for firm strategies and governmental policies were discussed.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.427-435
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• 2023

Changes in flowering time due to weather fluctuations impact plant growth and ecosystem dynamics. Accurate prediction of flowering timing is crucial for effective forest ecosystem management. This study uses a process-based model to predict flowering timing in 2023 for five major tree species in Korean forests. Models are developed based on nine years (2009-2017) of flowering data for Abeliophyllum distichum, Robinia pseudoacacia, Rhododendron schlippenbachii, Rhododendron yedoense f. poukhanense, and Sorbus commixta, distributed across 28 regions in the country, including mountains. Weather data from the Automatic Mountain Meteorology Observation System (AMOS) and the Korea Meteorological Administration (KMA) are utilized as inputs for the models. The Single Triangle Degree Days (STDD) and Growing Degree Days (GDD) models, known for their superior performance, are employed to predict flowering dates. Daily temperature readings at a 1 km spatial resolution are obtained by merging AMOS and KMA data. To improve prediction accuracy nationwide, random forest machine learning is used to generate region-specific correction coefficients. Applying these coefficients results in minimal prediction errors, particularly for Abeliophyllum distichum, Robinia pseudoacacia, and Rhododendron schlippenbachii, with root mean square errors (RMSEs) of 1.2, 0.6, and 1.2 days, respectively. Model performance is evaluated using ten random sampling tests per species, selecting the model with the highest R². The models with applied correction coefficients achieve R² values ranging from 0.07 to 0.7, except for Sorbus commixta, and exhibit a final explanatory power of 0.75-0.9. This study provides valuable insights into seasonal changes in plant phenology, aiding in identifying honey harvesting seasons affected by abnormal weather conditions, such as those of Robinia pseudoacacia. Detailed information on flowering timing for various plant species and regions enhances understanding of the climate-plant phenology relationship.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.7-7
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• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.

• Korean Journal of Ichthyology
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• v.35 no.4
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• pp.224-235
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• 2023

South Korea is the only divided nation globally, marked by a military demarcation line establishing demilitarized and civilian control zones, ensuring national security. Consequently, these areas exhibit relatively minimal ecological disruption compared to other regions. However, the threat to safety persists due to the presence of unexploded ordnances and landmines, imposing significant constraints on ecological research. To address this, we conducted a comparative study utilizing eDNA analysis as a supplementary and alternative approach within three points of the "Road of Peace" - Inje, Yanggu, and Hwacheon courses, located within the civilian control zone. Direct surveys and indirect eDNA sampling were carried out in May, July, and September of 2022. Genetic material obtained from the samples underwent amplification, library preparation, MiSeq sequencing, and subsequent ASV generation for indirect analysis. These results were then compared with the findings of direct surveys. Our findings revealed the detection of eDNA for both observed species at the Yanggu-1 point, and for two out of four species at Yanggu-2. Hwacheon-1 displayed the detection of eDNA for one out of one observed species, whereas Hwacheon-2 yielded seven out of twelve, Hwacheon-3 showed four out of six, and all one observed species at Hwacheon-4 exhibited eDNA detection. Consequently, approximately 69% of the fish species identified through direct surveys were confirmed by indirect eDNA analysis. It is necessary to verify if certain fish species, such as the continental trout and catfish, have genetic information registered in the NCBI database. Additionally, it is believed that further marker development research utilizing different genetic sequences is essential. Given the limitations imposed by the hazardous nature of the surveyed civilian control zone, eDNA analysis proves to be a suitable supplement for fish research in the area.

• Journal of the Korean Society of Radiology
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• v.18 no.3
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• pp.187-201
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• 2024

Osteoporosis is a major health issue globally, often remaining undetected until a fracture occurs. To facilitate early detection, deep learning (DL) models were developed to classify osteoporosis using abdominal computed tomography (CT) scans. This study was conducted using retrospectively collected data from 3,012 contrast-enhanced abdominal CT scans. The DL models developed in this study were constructed for using image data, demographic/clinical information, and multi-modality data, respectively. Patients were categorized into the normal, osteopenia, and osteoporosis groups based on their T-scores, obtained from dual-energy X-ray absorptiometry, into normal, osteopenia, and osteoporosis groups. The models showed high accuracy and effectiveness, with the combined data model performing the best, achieving an area under the receiver operating characteristic curve of 0.94 and an accuracy of 0.80. The image-based model also performed well, while the demographic data model had lower accuracy and effectiveness. In addition, the DL model was interpreted by gradient-weighted class activation mapping (Grad-CAM) to highlight clinically relevant features in the images, revealing the femoral neck as a common site for fractures. The study shows that DL can accurately identify osteoporosis stages from clinical data, indicating the potential of abdominal CT scans in early osteoporosis detection and reducing fracture risks with prompt treatment.