• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.193-205
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• 2023

A large amount of floating debris from land-based sources during heavy rainfall has negative social, economic, and environmental impacts, but there is a lack of monitoring systems for floating debris accumulation areas and amounts. With the recent development of artificial intelligence technology, there is a need to quickly and efficiently study large areas of water systems using drone imagery and deep learning-based object detection models. In this study, we acquired various images as well as drone images and trained with You Only Look Once (YOLO)v5s and the recently developed YOLO7 and YOLOv8s to compare the performance of each model to propose an efficient detection technique for land-based floating debris. The qualitative performance evaluation of each model showed that all three models are good at detecting floating debris under normal circumstances, but the YOLOv8s model missed or duplicated objects when the image was overexposed or the water surface was highly reflective of sunlight. The quantitative performance evaluation showed that YOLOv7 had the best performance with a mean Average Precision (intersection over union, IoU 0.5) of 0.940, which was better than YOLOv5s (0.922) and YOLOv8s (0.922). As a result of generating distortion in the color and high-frequency components to compare the performance of models according to data quality, the performance degradation of the YOLOv8s model was the most obvious, and the YOLOv7 model showed the lowest performance degradation. This study confirms that the YOLOv7 model is more robust than the YOLOv5s and YOLOv8s models in detecting land-based floating debris. The deep learning-based floating debris detection technique proposed in this study can identify the spatial distribution of floating debris by category, which can contribute to the planning of future cleanup work.

• Pediatric Infection and Vaccine
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• v.30 no.1
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• pp.20-32
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• 2023

Purpose: This study aimed to identify the etiology and risk factors of community-acquired pneumonia (CAP) requiring hospitalization in Korean children during the coronavirus disease 2019 (COVID-19) pandemic. Methods: Clinical information of children admitted with CAP to Seoul National University Children's Hospital (SNUCH) between January 1, 2021, and February 28, 2022, was retrospectively collected and analyzed. In addition, the etiologic diagnosis and demographic data of children with CAP who were discharged at the other seven hospitals between January and February 2022 were collected. Pneumonia was diagnosed using strict criteria comprising clinical symptoms, physical examination findings, and chest radiographic findings. Results: Among 91 children hospitalized with CAP at SNUCH during the 14-month period, 68.4% were aged <5 years and 79.1% had underlying diseases. Among the 95 CAP cases, respiratory assistance was required in 70.5%, and the use of a ventilator was required in 20.0%. A total of five patients expired, all of whom were either immunocompromised or had underlying neurological diseases. Neurological diseases and immunosuppression were significantly correlated with respiratory assistance (P=0.003) and death (P=0.014). A total of 55% of the detected respiratory pathogens were viruses, the most common of which was rhinovirus at 35.9%. Among the 169 children hospitalized for CAP at the eight institutions, ≥1 respiratory virus was detected in 92.3%, among which respiratory syncytial virus (79.8%) was the most prevalent. Conclusions: Even during the COVID-19 pandemic, Korean children were hospitalized with CAP caused by seasonal respiratory viral pathogens. Although atypical and pyogenic bacteria were not detected, continuous clinical monitoring and further prospective studies should be conducted.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3A
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• pp.297-307
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• 2010

Recently, maintenance engineering and technology for civil and building structures have begun to draw big attention and actually the number of structures that need to be evaluate on structural safety due to deterioration and performance degradation of structures are rapidly increasing. When stiffness is decreased because of deterioration of structures and member cracks, dynamic characteristics of structures would be changed. And it is important that the damaged areas and extent of the damage are correctly evaluated by analyzing dynamic characteristics from the actual behavior of a structure. In general, typical measurement instruments used for structure monitoring are dynamic instruments. Existing dynamic instruments are not easy to obtain reliable data when the cable connecting measurement sensors and device is long, and have uneconomical for 1 to 1 connection process between each sensor and instrument. Therefore, a method without attaching sensors to measure vibration at a long range is required. The representative applicable non-contact methods to measure the vibration of structures are laser doppler effect, a method using GPS, and image processing technique. The method using laser doppler effect shows relatively high accuracy but uneconomical while the method using GPS requires expensive equipment, and has its signal's own error and limited speed of sampling rate. But the method using image signal is simple and economical, and is proper to get vibration of inaccessible structures and dynamic characteristics. Image signals of camera instead of sensors had been recently used by many researchers. But the existing method, which records a point of a target attached on a structure and then measures vibration using image processing technique, could have relatively the limited objects of measurement. Therefore, this study conducted shaking table test and field load test to verify the validity of the method that can measure multi-point displacement responses of structures using image processing technique.

• 한국노년학
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• v.29 no.1
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• pp.149-175
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• 2009

The purpose of this research is to analyze the overall problems at the moment of October 2008, and then to find the improvements of home-help services of the Long-Term Care Insurance(LTCI), which has been revealed many problems since it was released in July 2008. The research uses the literature survey which analyzes 2nd-hand materials studied by other people already, and survey research was executed from active social workers in the area of LTCI. Based on the policy analysis framework of Gilbert and Specht, all the data are analyzed in the scopes of client·benefit(service)·finance·transferring system. This research has found the problems in each scope of home-help services of the LTCI. Firstly, the client system has some problems in mismatching between registered and service clients, estimating client number, and judging service levels. Secondly, the service system reveals deficiency in professionality of social workers, service quality lowering by loose qualification criteria on workers, non-reasonable limitation of service time available, and the same fare system applied to visiting-help service in spite of different levels. Thirdly, in financing system, clients need to pay additional money to get extra services such as meal, hair cutting, bathing etc., due to government financial support stopped, some organizations have to reduce services and replace full-time workers to part-time ones, which makes the service quality worse. Lastly, in the transferring system, the management system for service quality is not well prepared. There are too much competion because of allowing too many home-help service organizations and care worker academies. The suggestions that this research has found to improve the policy are as follows. ① It is desirable to make the registered clients the service ones as many as possible in the long term perspective. ② The LTCI organization requires more workers and higher professionality. ③ Many elderly people who are not eligible now require connection system to be more served. ④ Management system and service manual for care worker are to be developed. ⑤ Laws related to the service contents and process should be modified, the proportion of client charge needs to adjust. ⑥ Home-help service organization licensed by the LTCI needs to be financially supported publicly. ⑦ Monitoring system to home-help service organization needs to be strengthened. ⑧ Evaluation tools to home-help service organization and workers is required. ⑨ Specification to open the home-help service organization needs to be more strict.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.335-344
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• 2023

Brachydiplax chalybea flavovittata, a climate-sensitive biological indicator species, was first observed and recorded at Jeju Island in Korea in 2010. Overwintering was recently confirmed in the Yeongsan River area. This study was aimed to predict the potential distribution patterns for the larvae of B. chalybea flavovittata and to understand its ecological characteristics as well as changes of population under global climate change circumstances. Data was collected both from the Global Biodiversity Information Facility (GBIF) and by field surveys from May 2019 to May 2023. We used for the distribution model among downloaded 19 variables from the WorldClim database. MaxEnt model was adopted for the prediction of potential and future distribution for B. chalybea flavovittata. Larval distribution ranged within a region delimited by northern latitude from Jeju-si, Jeju Special Self-Governing Province (33.318096°) to Yeoju-si, Gyeonggi-do (37.366734°) and eastern longitude from Jindo-gun, Jeollanam-do (126.054925°) to Yangsan-si, Gyeongsangnam-do (129.016472°). M type (permanent rivers, streams and creeks) wetlands were the most common habitat based on the Ramsar's wetland classification system, followed by Tp type (permanent freshwater marshes and pools) (45.8%) and F type (estuarine waters) (4.2%). MaxEnt model presented that potential distribution with high inhabiting probability included Ulsan and Daegu Metropolitan City in addition to the currently discovered habitats. Applying to the future scenarios by Intergovernmental Panel on Climate Change (IPCC), it was predicted that the possible distribution area would expand in the 2050s and 2090s, covering the southern and western coastal regions, the southern Daegu metropolitan area and the eastern coastal regions in the near future. This study suggests that B. chalybea flavovittata can be used as an effective indicator species for climate changes with a monitoring of their distribution ranges. Our findings will also help to provide basic information on the conservation and management of co-existing native species.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.258-266
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• 2023

This study analyzed methodologies for estimating carbon stocks of perennial woody crops and the research cases in overseas countries. As a result, we found that Australia, Bulgaria, Canada, and Japan are using the stock-difference method, while Austria, Denmark, and Germany are estimating the change in the carbon stock based on the gain-loss method. In some overseas countries, the researches were conducted on estimating the carbon stock change using image data as tier 3 phase beyond the research developing country-specific factors as tier 2 phase. In South Korea, convergence studies as the third stage were conducted in forestry field, but advanced research in the agricultural field is at the beginning stage. Based on these results, we suggest directions for the following four future researches: 1) securing national-specific factors related to emissions and removals in the agricultural field through the development of allometric equation and carbon conversion factors for perennial woody crops to improve the completeness of emission and removals statistics, 2) implementing policy studies on the cultivation area calculation refinement with fruit tree-biomass-based maturity, 3) developing a more advanced estimation technique for perennial woody crops in the agricultural sector using allometric equation and remote sensing techniques based on the agricultural and forestry satellite scheduled to be launched in 2025, and to establish a matrix and monitoring system for perennial woody crop cultivation areas in the agricultural sector, Lastly, 4) estimating soil carbon stocks change, which is currently estimated by treating all agricultural areas as one, by sub-land classification to implement a dynamic carbon cycle model. This study suggests a detailed guideline and advanced methods of carbon stock change calculation for perennial woody crops, which supports 2050 Carbon Neutral Strategy of Ministry of Agriculture, Food, and Rural Affairs and activate related research in agricultural sector.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1341-1352
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• 2023

The normalized difference vegetation index (NDVI) derived from satellite images is a crucial tool to monitor forests and agriculture for broad areas because the periodic acquisition of the data is ensured. However, optical sensor-based vegetation indices(VI) are not accessible in some areas covered by clouds. This paper presented a synthetic aperture radar (SAR) based approach to retrieval of the optical sensor-based NDVI using machine learning. SAR system can observe the land surface day and night in all weather conditions. Radar vegetation indices (RVI) from the Sentinel-1 vertical-vertical (VV) and vertical-horizontal (VH) polarizations, surface elevation, and air temperature are used as the input features for an automated machine learning (AutoML) model to conduct the gap-filling of the Sentinel-2 NDVI. The mean bias error (MAE) was 7.214E-05, and the correlation coefficient (CC) was 0.878, demonstrating the feasibility of the proposed method. This approach can be applied to gap-free nationwide NDVI construction using Sentinel-1 and Sentinel-2 images for environmental monitoring and resource management.

• Korean Journal of Environment and Ecology
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• v.37 no.5
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• pp.327-336
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• 2023

This study aimed to propose an effective method for surveying wild birds by comparing the results of bioacoustic detection with those obtained through a field survey. The study sites were located at Dongbaek-dongsan and a 1100-altitude wetland in Jeju-do, South Korea. The bioacoustic detection was conducted over the course of 12 months in 2020. For the bioacoustic detection, a Song-meter SM4 device was installed at each study site, recording bird songs in 1-min per hour, .wav, and 44,100 Hz format. The findings of the field survey were taken from the 「Long-term trends of Bird Community at Dongbaekdongsan and 1100-Highland Wetland of Jeju Island, South Korea.」 by Banjade et al. (2019). The results of this study are as follows. First, the avifauna identified using bioacoustic detection comprised 29 families and 46 species in Dongbaek-dongsan, and 16 families and 25 species in the 1100-altitude wetland. Second, based on the song frequency, the dominant species in Dongbaek-dongsan were Hypsipetes amaurotis (Brown-eared Bulbul, 33.62%), Horornis diphone (Japanese Bush Warbler, 12.13%), and Zosterops japonicus (Warbling White-eye, 9.77%). In the 1100-altitude wetland the dominant species were Corvus macrorhynchos (Large-billed Crow, 27.34%), H. diphone (19.43%), and H. amaurotis (16.56%). Third, in the field survey conducted at Dongbaek-dongsan, the number of detected bird species was 39 in 2009, 51 in 2012, 35 in 2015, and 45 in 2018, while the bioacoustic detection identified 46 species. In the field survey conducted in the 1100-altitude wetland, the number of detected bird species was 37 in 2009, 42 in 2012, 34 in 2015, and 38 in 2018, while the bioacoustics detection identified 25 species. Overall, 43.6% of the 78 species detected in the field survey in Dongbaek-dongsan (34 species) were identified using bioacoustic detection, and 38.3% of the 47 species detected in the field survey in the 1100-altitude wetland (18 species) were identified using bioacoustic detection. Fourth, the bioacoustic detection identified 9 families and 12 species of birds in Dongbaek-dongsan, and 3 families and 7 species of birds in the 1100-altitude wetland. No results from field survey were available for these species. The identified birds were predominantly nocturnal, including Otus sunia (Oriental Scops Owl) and Ninox japonica (Northern Boobook), passage migrants, including Larvivora cyane (Siberian Blue Robin), L. sibilans (Rufous-tailed Robin), and winter visitors with a relatively small number of visiting individuals, such as Bombycilla garrulus (Bohemian Waxwing) and Loxia curvirostra (Red Crossbill). Fifth, the birds detected in the field survey but not through bioacoustic detection included 18 families and 48 species in Dongbaek-dongsan and 14 families and 27 species in the 1100-altitude wetland; the most representative families were Ardeidae, Accipitridae, and Muscicapidae. This study is significant as it provides essential data supporting the possibility of an effective survey combining bioacoustic detection with field studies, given the increasing use of bioacoustic devices in ornithological studies in South Korea.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.181-193
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• 2024

The increasing atmospheric imbalance caused by climate change leads to an elevation in precipitation, resulting in a heightened frequency of flooding. Consequently, there is a growing need for technology to detect and monitor these occurrences, especially as the frequency of flooding events rises. To minimize flood damage, continuous monitoring is essential, and flood areas can be detected by the Synthetic Aperture Radar (SAR) imagery, which is not affected by climate conditions. The observed data undergoes a preprocessing step, utilizing a median filter to reduce noise. Classification techniques were employed to classify water bodies and non-water bodies, with the aim of evaluating the effectiveness of each method in flood detection. In this study, the Otsu method and Support Vector Machine (SVM) technique were utilized for the classification of water bodies and non-water bodies. The overall performance of the models was assessed using a Confusion Matrix. The suitability of flood detection was evaluated by comparing the Otsu method, an optimal threshold-based classifier, with SVM, a machine learning technique that minimizes misclassifications through training. The Otsu method demonstrated suitability in delineating boundaries between water and non-water bodies but exhibited a higher rate of misclassifications due to the influence of mixed substances. Conversely, the use of SVM resulted in a lower false positive rate and proved less sensitive to mixed substances. Consequently, SVM exhibited higher accuracy under conditions excluding flooding. While the Otsu method showed slightly higher accuracy in flood conditions compared to SVM, the difference in accuracy was less than 5% (Otsu: 0.93, SVM: 0.90). However, in pre-flooding and post-flooding conditions, the accuracy difference was more than 15%, indicating that SVM is more suitable for water body and flood detection (Otsu: 0.77, SVM: 0.92). Based on the findings of this study, it is anticipated that more accurate detection of water bodies and floods could contribute to minimizing flood-related damages and losses.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.3
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• pp.147-158
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• 2007

To clarify the bloom pattern and species succession in phytoplankton community, the population dynamics with the determination of physico-chemical factors have been studies in Masan Bay, the south sea of Korea, for the periods November 2003-October 2004. Concentration of $NH_4-N$ was always higher than that of $NO_3-N$, which was similar level as compared to other costal areas. $PO_4-P$ concentration was lower than those in other coastal areas but similar to oligotrophic environments. Thus, phosphate seems the limiting nutrient rather than nitrogen. $SiO_2-Si$ concentration was also low as compared to other costal areas. Si:P ratio was low from autumn to winter, suggesting silicate and/or phosphate limitation during this period. The cell density of phytoplankton was high in winter 2003 and early autumn 2004. The carbon biomass was high in winter 2003 and summer 2004. And chlorophyll-a concentration was high in late autumn 2003 and summer 2004. Among 78 species of phytoplankton found in the bay during the investigated period, dominant species were two diatoms of Cylindrotheca closterium, Skeletonema costatum, and three dinoflagellates of Heterocapsa triquetra, Prorocentrum minimum, P. triestinum, and one raphidophyte of Heterosigma akashiwo. P. minimum dominated from late autumn to winter, but it was replaced by H. triquetra in late winter. P. triestinum dominated from late spring to early summer. Simultaneously, H. akashiwo cell density steadily increased, and it became dominant with C. closterium in late summer. With decreasing of H. akashiwo and C. closterium, S. costatum became the most dominant species in autumn. The canonical analyses showed that total phytoplankton cell density related to diatom cell density and it was affected by temperature, and concentrations of $NO_3-N\;and\;PO_4-P$. The carbon bio-mass and $chlorophyll-{\alpha}$ concentration related to diatom- and dinoflagellate cell densities and these were affected by flagellate cell density, salinity, and concentrations of $SiO_2-Si\;and\;PO_4-P$. Last six years monitoring data in Masan city obtained from Korean Meteorological Agency indicates gradual increase in air temperature. And the precipitation decreased especially in spring season. The winter bloom found in 2003 may be caused by the increase in the temperature and this bloom subsequently induced the nutrients depletion, which continued until next spring probably due to no precipitation. Therefore, the spring bloom, which had been usually observed in the bay, might disappear in 2004.