• Journal of Chest Surgery
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• v.30 no.9
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• pp.862-868
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• 1997

Shone's syndrome is a congenital cardiac malformation that consists of multiple levels of left heart obstruction including supravalvular mitral ring, congenital mitral stenosis(parachute mitral valve), subaortic stenosis, and coarctation of aorta. This syndrome is a very rare congenital anomaly and its prognosis is poor. We experienced 9 patients with Shone's syndrome between 1985 and 1994. There were 8 male and 1 female patients, and mean age was 33.0$\pm$31.0 months ranged from 2 months to 1 1 years. The congenital mitral, stenosis and coarctation of aorta existed in all patients and the supravalvular mitral ring and subaortic stenosis in 4 patients. Two patients had all four anatomic lesions. 3 patients underwent one stage total correction and the other 6 patients underwent two staged operation that was initial coarctoplasty with thoracotomy and later correction of intracardiac anomalies with median sternotomy. A third operation was performed in 2 patients. These procedures included reoperation for coarctation and replacement of mitral valve for persistent mitral stenosis. There was no operative death at the first operation but two operative deaths at the second operation. The cause of death in two cases was severe heart failure secondary to left ventricular hypoplasia. There was no operative death at the third operation. The seven survivors have beeli followed from 11 months to 12 years(mean follow-up 6.7 $\pm$ 3.6 years). There was no late death and the New York HeArt Association activity level was class I for all patients. We conclude that a food lone-term outcome can be expected by proper surgical treatment tailred to each individual's anatomy and pathophysiology although the operative mortality and morbidity of Shone's syndrome are high.

• Journal of Chest Surgery
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• v.42 no.1
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• pp.28-33
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• 2009

Background: Functional tricuspid regurgitation (TR) greater than or equal to a mild grade requires tricuspid valvuloplasty, and tricuspid valvuloplasty with ring annuloplasty has shown good outcomes. We report here on our early experience with the Edwards $MC^3$ annuloplasty system (Edwards LifeSciences, Irvine, CA). Material and Method: From November 2004 to July 2006, 72 patients with tricuspid annular dilatation and TR underwent tricuspid valvuloplasty with using the Edwards $MC^3$ annuloplasty ring. Sixty-eight patients were operated on via median sternotomy and four patients were operated on using robotic assisted minimal invasive thoracotomy. The patient population included 21 males and 51 females and their mean age was $53.9{\pm}12.3$. The mean grade of TR, as assessed by the preoperative echocardiography, was $2.2{\pm}1.0$. The mean NYHA functional class was $3.1{\pm}0.8$. The mean left ventricular ejection fraction was $57.0{\pm}9.9$%. Result: The TR and NYHA functional class, as assessed by postoperative echocardiography, was significantly reduced (mean=$0.4{\pm}0.6$ and $2.0{\pm}0.7$, respectively p<0.001). There was one case of hospital mortality. One patient required permanent pacemaker insertion for third degree atrioventricular block. Conclusion: Our study shows that the Edwards $MC^3$ remodeling ring is easy to implant and it effectively corrects functional TR with excellent clinical and echocardiographic outcomes. Further follow-up and a larger clinical series are required to establish the long-term stability of this repair technique.

• Korean Journal of Environment and Ecology
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• v.26 no.6
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• pp.892-901
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• 2012

The purpose of this research was to analyze fish fauna, distribution patterns, and fish community structures in the Juksan-Weir regions of upper weir(R-UW) and lower weir(R-LW), which was constructed in 2011 on Yeongsan River watershed. Our outcomes will provide valuable information in the impact analysis of weir constructions next decades, even if the current research is limited to distributions and fauna studies of fishes. The fishes observed were 8 family and 30 species in all the sites, and the number of the species in the regions of R-UW and R-LW was 23(938 individuals) and 27(1,680 individuals), respectively, indicating greater abundance in the lower region of Juksan-Weir. Most dominant species was Opsarichthys uncirostris amurensis with relative abundance of 42%, and this species had greater abundance in the R-LW(49%) than in the R-UW(30%). Coilia nasus, was the migratory fish sampled in this region and had no differences of abundance between the two regions. The extic species observed were Carassius cuvieri, Lepomis macrochirus, and Micropterus salmoides. The two formers of Carassius cuvieri(1.2%) and Lepomis macrochirus(3.7%) dominated in the R-UW, whereas Micropterus salmoides had greater dominance in the region of R-LW. According to tolerance guild analysis, the proportion of sensitive species ranged from 0.4 to 0.5%, and that of tolerant species ranged from 65% to 70%, implying a severe pollution of nutrients and organic matters in the water body. In the mean time, according to trophic guild analysis, the proportion of carnivores(57 - 77%) was evidently higher than that of insectivores(10 - 20%), indicating a dominance of the carnivores. Especially, high abundance of the bass, exotic species, may disturb the fish overall food chain, so the efficient ecosystem management may be required for the conservation of endemic species. When we examined fish data files of last 60 years, the species of Culter brevicauda, designated as endangered species, was observed firstly in our research area and the total number was 5 individuals(0.2% of the total). So, this region observed should be conserved as a protection zone and further monitoring studies should be done in the future.

• Journal of Wetlands Research
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• v.18 no.3
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• pp.301-312
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• 2016

This study has performed comparative analysis on characteristics of contaminated 35 tributaries on seasonal variation/point discharge load/pollutant distribution of water quality factors(8) in order to understand the effect of the watershed in Nakdong River Basin. As a results, the water quality of $BOD_5$(Biochemical Oxygen Demand), Chl-a(Chlorophyll a) and Fecal E. Coli shows II grade at tributaries of more than 50% without COD(Chemical Oxygen Demand), TP(Total Phosphate), TOC(Total Oxygen Carbon) and TN(Total Nitrogen) factors. The specific discharge(Q) were occupied about 54.4% (19 sites) as $0.05m^3/sec/km^2$ value. Among these results, the contaminant level of Dalseocheon, Hyeonjicheon, Seokkyocheon 1, Uriyeongcheon and Dasancheon was also high, which has to consider a discharged pollutant load(kg/day). The 35 major tributaries of Nakdong River were included in 7 mid-watershed, such as Nakdong Waegwan, Geumho River, Nakdong Goryung, Nakdong Changnyung, Nam River, Nakdong Milyang, Nakdong River Hagueon. Especially, the discharged pollutant load of Nam River and Geumho River also was high according to the amount of discharge such as Kachang dam, Gongsan dam and Nam river dam. Seasonal difference of the water quality factors such as $BOD_5$, TN, SS and Q was observed largely, on the other hand the TP and Chl-a was not. This is guessed due to the precipitation effect of site, biological and physicochemical degradation properties of pollutant and etc. The co-relationship between the seasonal difference and water quality factors was observed using a Pearson correlation coefficients. Besides, the Multiple Regression analysis using a Stepwise Regression method was conducted to understand the effect between seasonal difference and water quality factors/regression equations. As a result, the Multiple Regression analysis was adapted in the spring, summer and autumn without the winter, which was observed high at spring, summer and autumn in the order COD/TP, Chl-a/TOC, TOC/COD/$BOD_5$ water quality factors, respectively.

• Korean Journal of Environment and Ecology
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• v.32 no.1
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• pp.105-117
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• 2018

This study conducted health assessment and multivariate vegetation analysis using the riparian vegetation index in 30 sites of the Geumgang mainstream and Mihocheon to obtain practical data on the river management of the Geumgang. The result showed that the number of plant communities was 54. The flora was 75 families, 185 genera, 243 species, 2 subspecies, 21 varieties, 2 varieties, and 268 taxa. The riparian vegetation index was 38.3 (3.3; G-D1 ~ 66.7; G-U2, G-U4, and G-M3), and the health of the rivers in this area was evaluated as normal (grade C). The health of rivers was the highest in the upper stream of Geumgang mainstream and lowest in the downstream of Geumgang mainstream. The relationship between riparian vegetation index and chlorophyll-a content was low. The riparian vegetation was divided into five groups of Digitaria ciliaris colony group, Salix gracilistyla colony group, Erigeron annuus colony group, the group dominated by Humulus japonicus, Salix koreensis, Miscanthus sacchariflorus, and Phragmites japonica colonies, and the group dominated by Conyza canadensis and Echinochloa crusgalli var. echinata colonies. They had the similar health conditions. The CCA analysis showed that the environmental factors affecting the distribution of vegetation were physical factors such as vegetation area, artificial structure area, waterway area, branch width, channel width, and bank height and the biological factors such as the number of species. As such, it is necessary to maintain the health condition through continuous monitoring where the health condition is high and to apply active measures such as ecological restoration where the health condition is low.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.551-558
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• 2008

It is well known that the protein content of rice grain is an indicator of taste of cooked rice in the countries where people as the staple food. Ground-based optical sensing over the crop canopy would provide information not only on the mass of plant body which reflects the light, but also on the crop nitrogen content which is closely related to the greenness of plant leaves. The vegetation index has been related to crop variables such as biomass, leaf nitrogen, plant cover, and chlorophyll in cereals. The objective of this study was to investigate the correlation between GNDVI and NDVI values, and grain protein content at different dates and to estimate the grain protein content using G(NDVI) values. We measured Green normalized difference vegetation index [$GNDVI=({\rho}0.80{\mu}m-{\rho}0.55{\mu}m)/({\rho}0.80{\mu}m+{\rho}0.55{\mu}m)$] and [$GNDVI=({\rho}0.80{\mu}m-{\rho}0.68{\mu}m)/({\rho}0.80{\mu}m+{\rho}0.68{\mu}m)$] by using two different active sensors. The study was conducted during the rice growing season for three years from 2005 through 2007 at the experimental plots of National Institute of Agricultural Science and Technology. The experiments were carried out by randomized complete block design with the application of four levels of nitrogen fertilizers(0, 70, 100, 130kg N/ha) and the same amount of phosphorous and potassium content of the fertilizers. After heading stage, relationships between GNDVI of rice canopy and grain protein content showed the highly positive correlation at different dates for three years. GNDVI values showed higher correlation coefficients than that of NDVI during growing season in 2005-07. The correlation between GNDVI values at different dates and grain protein contents was highly correlated at early July. We attempted to estimate the grain protein content at harvesting stage using GNDVI values from early July for three years. The determination coefficients of the linear model by GNDVI values were 0.9l and the measured and estimated grain protein content at harvesting stage using GNDVI values highly correlated($R^2=0.96^{***}$). Results from this study show that GNDVI appeared very effective to estimate leaf nitrogen and grain protein content of rice canopy.

• Korean Journal of Remote Sensing
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• v.25 no.5
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• pp.423-434
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• 2009

The Arctic environment is sensitive to change of sea-ice distribution. The increase and decrease of sea ice work to an index of globe warming progress. In order to predict the progress of hereafter earth global warming, continuous monitoring regarding a change of the sea ice area in the Arctic should be performed. The remote sensing based on an artificial satellite is most effective on the North Pole. The sea ice observation using a passive microwave sensor has been continued from 1970's. The determination of sea ice extent and ice type is one of the great successes of the passive microwave imagers. In this paper, to investigate the seasonal and inter-annual variation of sea-ice distribution we used here the sea ice data from July 2002 to May 2009 around the Arctic within $60^{\circ}N$ for the AMSR-E 12.5km sea-ice concentration, a passive microwave sensor. From an early analysis of these data, the arctic sea-ice extent has been steadily decreasing at a rate of about 3.1%, accounting for about $2{\times}10^5\;km^2$, which was calculated for the sea-ice cover reaching its minimum extent at the end of each summer. It is also revealed that this trend corresponds to a decline in the multi-year ice that is affected mainly by summer sea surface and air temperature increases. The extent of younger and thinner (first-year) ice decreased to the 2007 minimum, but rapidly recovered in 2008 and 2009 due to the dramatic loss in 2007. Seasonal variations of the sea-ice extent show significant year-to-year variation in the seasons of January-March in the Barents and Labrador seas and August-October in the region from the East Siberian and Chukchi seas to the North Pole. The spatial distribution of multi-year ice (7-year old) indicates that the perennial ice fraction has rapidly shrunk recently out of the East Siberian, Laptev, and Kara seas to the high region of the Arctic within the last seven years and the Northeast Passage could become open year-round in near future.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.707-723
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• 2022

Although satellite-based sea surface temperature (SST) is advantageous for monitoring large areas, spatiotemporal data gaps frequently occur due to various environmental or mechanical causes. Thus, it is crucial to fill in the gaps to maximize its usability. In this study, daily SST composite fields with a resolution of 4 km were produced through a two-step machine learning approach using polar-orbiting and geostationary satellite SST data. The first step was SST reconstruction based on Data Interpolate Convolutional AutoEncoder (DINCAE) using multi-satellite-derived SST data. The second step improved the reconstructed SST targeting in situ measurements based on light gradient boosting machine (LGBM) to finally produce daily SST composite fields. The DINCAE model was validated using random masks for 50 days, whereas the LGBM model was evaluated using leave-one-year-out cross-validation (LOYOCV). The SST reconstruction accuracy was high, resulting in R² of 0.98, and a root-mean-square-error (RMSE) of 0.97℃. The accuracy increase by the second step was also high when compared to in situ measurements, resulting in an RMSE decrease of 0.21-0.29℃ and an MAE decrease of 0.17-0.24℃. The SST composite fields generated using all in situ data in this study were comparable with the existing data assimilated SST composite fields. In addition, the LGBM model in the second step greatly reduced the overfitting, which was reported as a limitation in the previous study that used random forest. The spatial distribution of the corrected SST was similar to those of existing high resolution SST composite fields, revealing that spatial details of oceanic phenomena such as fronts, eddies and SST gradients were well simulated. This research demonstrated the potential to produce high resolution seamless SST composite fields using multi-satellite data and artificial intelligence.

• Tunnel and Underground Space
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• v.33 no.4
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• pp.281-298
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• 2023

Continuous research efforts are being devoted to unmanned mobile platforms for lunar exploration. There is an ongoing demand for real-time information processing to accurately determine the positioning and mapping of areas of interest on the lunar surface. To apply deep learning processing and analysis techniques to practical rovers, research on software integration and optimization is imperative. In this study, a foundational investigation has been conducted on real-time analysis of virtual lunar base construction site images, aimed at automatically quantifying spatial information of key objects. This study involved transitioning from an existing region-based object recognition algorithm to a boundary box-based algorithm, thus enhancing object recognition accuracy and inference speed. To facilitate extensive data-based object matching training, the Batch Hard Triplet Mining technique was introduced, and research was conducted to optimize both training and inference processes. Furthermore, an improved software system for object recognition and identical object matching was integrated, accompanied by the development of visualization software for the automatic matching of identical objects within input images. Leveraging satellite simulative captured video data for training objects and moving object-captured video data for inference, training and inference for identical object matching were successfully executed. The outcomes of this research suggest the feasibility of implementing 3D spatial information based on continuous-capture video data of mobile platforms and utilizing it for positioning objects within regions of interest. As a result, these findings are expected to contribute to the integration of an automated on-site system for video-based construction monitoring and control of significant target objects within future lunar base construction sites.

• 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.