• Journal of Chest Surgery
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• v.39 no.4 s.261
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• pp.281-288
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• 2006

Background: Extracardiac pericardial-flap lateral tunnel Fontan operation has theoretical advantage of growth potentiality of the extracardiac tunnels. The mid-term results of this technique and morphologic change of the lateral tunnel were studied. Material and Method: Clinical data was reviewed in 42 patients who underwent extracardiac pericardial-flap lateral tunnel Fontan operation between November 1993 and December 2004. The age was $2.8{\pm}1.5$ years and the body weight was $12.3{\pm}3.2$ kg. Extracardiac tunnel was constructed using the pedicled pericardium with the base undetached. By reviewing the follow-up cardiac angiograms, the diameter and the cross-sectional area of the lateral tunnel was compared to those of inferior vena cava. Result: There were four operative mortality cases (9.8%) and the causes of death were low cardiac output for all four cases. Postoperatively, five patients had prolonged pleural effusion longer than two weeks and one patient required a permanent pacemaker due to complete heart block. Follow-up was possible in 37 patients and the follow up duration was $3.8{\pm}2.2$ years. During that period, one patient died, of upper gastrointestional bleeding combined with heart failure and one patient died a sudden death of unknown cause. Two patients required reoperation due to subaortic stenosis and anastomosis site stenosis between inferior vena cava and lateral tunnel. In one patient, bradyarrhythmia was anew but there was no thromboembolic complication. The lateral tunnel showed growth in proportion to the size of the inferior vena cava. Conclusion: Extracardiac pericardial-flap lateral tunnel Fontan operation is relatively simple and safe. The mid-term result was favorable and the extracardiac tunnel showed potential for growth.

• Journal of Chest Surgery
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• v.38 no.2 s.247
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• pp.110-115
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• 2005

Background: The aims of this paper were to review the mid term clinical results and to analyze the preoperative risk factors of isolated aortic valve replacement (AVR). Material and Method: Between January 1992 and February 2003, 80 patients underwent isolated AVR. 58 were male and 22 were female patients, raging from 12 to 75 years of age (mean :$46.8{\pm}13.0$ years). 74 patients except one early death and 5 follow-up loss were contacted by OPD or by telephone. The mean duration of follow-up was $44.2{\pm}29.7$ months and the total cumulative period was 272.8 patient-year. Result: The complications in hospital occurred in 35 cases : 12 wound problems (11 superficial, 1 deep), 11 arrhythmias (9 temporary, 2 persistent), 3 low cardiac output, and so forth. The late deaths were 4 cases : the heart-related deaths were 2 cases ($0.7\%$ patient-year). Conclusion: The risk factors that influenced the early mortality and morbidity were older age (> 60 years)(p=0.04), poor preoperative NYHA functional class (> 3) (p=0.048), high preoperative serum creatinin level (> 1.2 mg/100 ml)(p=0.031), long operation time (aortic clamping time>90 min)(p=0.042). The same factors influenced the late mortality and morbidity. Freedom from valve-related complication was $86.4{\pm}5.3\%,$ actuarial survival rate were $96.8{\pm}2.3\%$ at 3 years and $90.8{\pm}4.6\%$ at 10 years.

• Journal of Korea Water Resources Association
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• v.52 no.11
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• pp.917-929
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• 2019

Denitrification in streams is of great importance because it is essential for amelioration of water quality and accurate estimation of $N_2O$ budgets. Denitrification is a major biological source or sink of $N_2O$, an important greenhouse gas, which is a multi-step respiratory process that converts nitrate ($NO_3{^-}$) to gaseous forms of nitrogen ($N_2$ or $N_2O$). In aquatic ecosystems, the complex interactions of water flooding condition, substrate supply, hydrodynamic and biogeochemical properties modulate the extent of multi-step reactions required for $N_2O$ flux. Although water flow in streambed and residence time affect reaction output, effects of a complex interaction of hydrodynamic, geomorphology and biogeochemical controls on the magnitude of denitrification in streams are still illusive. In this work, we built a two-dimensional water flow channel and measured $N_2O$ flux from channel sediment with different bed geomorphology by using static closed chambers. Two independent experiments were conducted with identical flume and geomorphology but sediment with differences in dissolved organic carbon (DOC). The experiment flume was a circulation channel through which the effluent flows back, and the size of it was $37m{\times}1.2m{\times}1m$. Five days before the experiment began, urea fertilizer (46% N) was added to sediment with the rate of $0.5kg\;N/m^2$. A sand dune (1 m length and 0.15 m height) was made at the middle of channel to simulate variations in microtopography. In high- DOC experiment, $N_2O$ flux increases in the direction of flow, while the highest flux ($14.6{\pm}8.40{\mu}g\;N_2O-N/m^2\;hr$) was measured in the slope on the back side of the sand dune. followed by decreases afterward. In contrast, low DOC sediment did not show the geomorphological variations. We found that even though topographic variation influenced $N_2O$ flux and chemical properties, this effect is highly constrained by carbon availability.

• Korean Journal of Community Nutrition
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• v.26 no.5
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• pp.327-336
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• 2021

Objectives: This study was conducted to create a 3D printable snack dish model for the elderly with low food or fluid intake along with barriers towards eating. Methods: The decision was made by the hybrid-brainstorming method for creating the 3D model. Experts were assigned based on their professional areas such as clinical nutrition, food hygiene and chemical safety for the creation process. After serial feedback processes, the grape shape was suggested as the final model. After various concept sketching and making clay models, 3D-printing technology was applied to produce a prototype. Results: 3D design modeling process was conducted by SolidWorks program. After considering Dietary reference intakes for Koreans (KDRIs) and other survey data, appropriate supplementary water serving volume was decided as 285 mL which meets 30% of Adequate intake. To consider printing output conditions, this model has six grapes in one bunch with a safety lid. The FDM printer and PLA filaments were used for food hygiene and safety. To stimulate cognitive functions and interests of eating, numbers one to six was engraved on the lid of the final 3D model. Conclusions: The newly-developed 3D model was designed to increase intakes of nutrients and water in the elderly with dementia during snack time. Since dementia patients often forget to eat, engraving numbers on the grapes was conducted to stimulate cognitive function related to the swallowing and chewing process. We suggest that investigations on the types of foods or fluids are needed in the developed 3D model snack dish for future studies.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.275-290
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• 2021

Sulfur dioxide (SO2) in the atmosphere is mainly generated from anthropogenic emission sources. It forms ultra-fine particulate matter through chemical reaction and has harmful effect on both the environment and human health. In particular, ground-level SO2 concentrations are closely related to human activities. Satellite observations such as TROPOMI (TROPOspheric Monitoring Instrument)-derived column density data can provide spatially continuous monitoring of ground-level SO2 concentrations. This study aims to propose a 2-step residual corrected model to estimate ground-level SO2 concentrations through the synergistic use of satellite data and numerical model output. Random forest machine learning was adopted in the 2-step residual corrected model. The proposed model was evaluated through three cross-validations (i.e., random, spatial and temporal). The results showed that the model produced slopes of 1.14-1.25, R values of 0.55-0.65, and relative root-mean-square-error of 58-63%, which were improved by 10% for slopes and 3% for R and rRMSE when compared to the model without residual correction. The model performance by country was slightly reduced in Japan, often resulting in overestimation, where the sample size was small, and the concentration level was relatively low. The spatial and temporal distributions of SO2 produced by the model agreed with those of the in-situ measurements, especially over Yangtze River Delta in China and Seoul Metropolitan Area in South Korea, which are highly dependent on the characteristics of anthropogenic emission sources. The model proposed in this study can be used for long-term monitoring of ground-level SO2 concentrations on both the spatial and temporal domains.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• Korea Science and Art Forum
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• v.20
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• pp.147-158
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• 2015

This study made an approach to the industrial exhibition space, which is a medium of marketing communication, from the position of an enterprise and consumers through the output of Space Design, and conducted it with focus on B2B transactions among specialized exhibitions. In addition, this study inquired into what factors should be considered along with space design by interpreting the purpose of participating in the exhibition and space design of the enterprise which supply capital goods, elements, related technologies and materials, etc. This study aimed at drawing the direct/indirect effect, produced by space design, on the marketing by analyzing correlation between space design and participating enterprises' marketing. Despite the marketing effect of the exhibition, which was proved by preceding research results, the reality is that exhibition-participating expenses work as considerable burden on enterprises. Particularly, booth design, which is forming the most proportion among the participating expenses, was found to have insufficient influence on visitors due to the decline in its importance among diverse factors influencing visitor's decision to visit a booth. Regardless of the business category of participating enterprises in the exhibition, the standard of exhibits was ranked as the most important consideration factor in visiting a booth. Even by business category, the standard of booth design rarely had an influence on booth visit. Booth design had an affirmative influence on participating enterprise's preference, but its influence on product purchase or business talk & contact with a participating enterprise or price was found to be extremely low. It's difficult to judge marketing success or failure of an exhibition by the form and standard of booth design. Preferably, this study infers that it's necessary to put much weight on qualitative excellence of an exhibition, which consists of participation of an enterprise in possession of excellent technologies, exhibits with higher standards and high-quality visitors with purchasing power. This study suggests that it's more effective to set up the plan for expansion of participation in exhibition by optimally regulating the proportion of space design in participating expense to increase marketing effectiveness of an exhibition. The limitations of this study, analysis of which based on the visitors to an exhibition only, requires supplementation through the follow-up research work on participating enterprises in the exhibition.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.15 no.2
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• pp.51-61
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• 2010

Surface particulate organic carbon (POC) concentration was measured in the Northeastern Gulf of Mexico on 9 cruises from November 1997 to August 2000 to investigate the seasonal and spatial variability related to synchronous remote sensing data (Sea-viewing Wide Field-of-view Sensor (SeaWiFS), sea surface temperature (SST), sea surface height anomaly (SSHA), and sea surface wind (SSW)) and recorded river discharge data. Surface POC concentrations have higher values (>100 $mg/m^3$) on the inner shelf and near the Mississippi Delta, and decrease across the shelf and slope. The inter-annual variations of surface POC concentrations are relatively higher during 1997 and 1998 (El Nino) than during 1999 and 2000 (La Nina) in the study area. This phenomenon is directly related to the output of Mississippi River and other major rivers, which associated with global climate change such as ENSO events. Although highest river runoff into the northern Gulf of Mexico Coast occurs in early spring and lowest flow in late summer and fall, wide-range POC plumes are observed during the summer cruises and lower concentrations and narrow dispersion of POC during the spring and fall cruises. During the summer seasons, the river discharge remarkably decreases compared to the spring, but increasing temperature causes strong stratification of the water column and increasing buoyancy in near-surface waters. Low-density plumes containing higher POC concentrations extend out over the shelf and slope with spatial patterns and controlled by the Loop Current and eddies, which dominate offshore circulation. Although river discharge is normal or abnormal during the spring and fall seasons, increasing wind stress and decreasing temperature cause vertical mixing, with higher surface POC concentrations confined to the inner shelf.

• Korean Chemical Engineering Research
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• v.62 no.1
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• pp.36-43
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• 2024

Fishing net waste (FNW) constitutes over half of all marine plastic waste and is a major contributor to the degradation of marine ecosystems. While current treatment options for FNW include incineration, landfilling, and mechanical recycling, these methods often result in low-value products and pollutant emissions. Importantly, FNWs, comprised of plastic polymers, can be converted into valuable resources like syngas and pyrolysis oil through pyrolysis. Thus, this study presents a process for generating high-purity hydrogen (H₂) by catalytically pyrolyzing FNW in a CO₂ environment. The proposed process comprises of three stages: First, the pretreated FNW undergoes Ni/SiO₂ catalytic pyrolysis under CO₂ conditions to produce syngas and pyrolysis oil. Second, the produced pyrolysis oil is incinerated and repurposed as an energy source for the pyrolysis reaction. Lastly, the syngas is transformed into high-purity H₂ via the Water-Gas-Shift (WGS) reaction and Pressure Swing Adsorption (PSA). This study compares the results of the proposed process with those of traditional pyrolysis conducted under N₂ conditions. Simulation results show that pyrolyzing 500 kg/h of FNW produced 2.933 kmol/h of high-purity H₂ under N₂ conditions and 3.605 kmol/h of high-purity H₂ under CO₂ conditions. Furthermore, pyrolysis under CO₂ conditions improved CO production, increasing H₂ output. Additionally, the CO₂ emissions were reduced by 89.8% compared to N₂ conditions due to the capture and utilization of CO₂ released during the process. Therefore, the proposed process under CO₂ conditions can efficiently recycle FNW and generate eco-friendly hydrogen product.