• Journal of Chest Surgery
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• v.15 no.2
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• pp.259-265
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• 1982

We have designed a new type of bubble oxygenator (KOREA-KIM VENOTHERM OXYGENATOR) made of PVC sheet and deforming mesh incorporated in the heat exchanger, and evaluated in experimental animal for the analysis of it`s efficiency. The Oxygenator has low priming volume with high flow rate up to 6 L/rain, and efficiency of heat exchanger was excellent as 1-$1.5^{\circ}C.$ using total cardiopulmonary bypass method under moderate to deep hypothermia. Average priming volume of 1317 ml with 30% hemodilution method was perfused with an average of 1.1-3.0 L/min.$M^2$of arterial blood and pure oxygen at a rate of 2-3.4 L/min for 49.6 minutes continuously in average. During total cardiopulmonary bypass, average $PaO_2$ was $159.8{\pm}60$mmHg, $PaCO_2$ $41.0{\pm}3$mmHg respectively under $SaO_2$ over 96% with systolic arterial pressure of 70 mmHg and CVP of 5-10 cm$H_2O$. Plasma free Hemoglobin was $7.0{\pm}4$ mg/dl with 25% drop of hemoglobin and hematocrit at the end of cardiopulmonary bypass. This KKV Oxygenator was observed to have excellent capabillty of oxygen and carbon dioxide gas transfer with small amount of blood trauma, and the efficiency of heat exchanger was satisfactory during cooling and rewarming of the bubbled blood. Disadvantages have included the somewhat poor deforming effect due to loose PVC fiber mesh, the extracompact character of Teflon filters, and the rough inner surface of the heat exchanger copper pipes.

• Journal of Soil and Groundwater Environment
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• v.15 no.4
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• pp.39-45
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• 2010

In order to treat paddy soils contaminated by Pb, Cd, and As near the abandoned mine, $H_2PO_4$ was used for stabilization of Pb ($PO_4$/Pb mole ratio of 2/1). In addition, $CaCO_3$ and $FeSO_4$ were used as stabilizers for treating Cd and As (2% w/w), respectively. Leaching tests were conducted with artificial rain in the column to assess the heavy metal stabilization efficiency. The mass of heavy metals in the effluents passed through the columns were analyzed. The remaining heavy metals in the soils were also analyzed as Korean soil standard method, phytoavailability test and sequential extraction test. Lead in the effluent was not detected when $H_2PO_4$ was used as a stabilizer. This result suggests that $H_2PO_4$ is efficient for Pb stabilization. In addition results of sequential extraction scheme suggest that heavy metals are present as residual forms which is not easily extracted.

• Asian Journal of Atmospheric Environment
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• v.11 no.3
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• pp.176-183
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• 2017

Although it is well known that rain plays an important role in capturing air pollutants, its quantitative evaluation has not been done enough. In this study, the effect of raindrop size on pollutant scavenging was investigated by clarifying the chemical nature of individual size-resolved raindrops and their residual particles. Raindrops as a function of their size were collected using the raindrop collector devised by our oneself in previous study (Ma et al., 2000) during high atmospheric loading for $PM_{2.5}$. Elemental analyses of solid residues and individual residual particles in raindrops were subsequently analyzed by Particle Induced X-ray Emission (PIXE) and Scanning Electron Microscopy (SEM) with Energy Dispersive X-Ray Analysis (EDX), respectively. The raindrop number concentration ($m^{-2}h^{-1}$) tended to drastically decrease as the drop size goes up. Particle scavenging rate, $R_{sca.}$ (%), based on the actual measurement values were 38.7, 69.5, and 80.8% for the particles with 0.3-0.5, 0.5-1.0, and $1.0-2.0{\mu}m$ diameter, respectively. S, Ca, Si, and Al ranked relatively high concentration in raindrops, especially small ones. Most of the element showed a continuous decrease in concentration with increasing raindrop diameter. The source profile by factor analysis for the components of residual particles indicated that the rainfall plays a valuable role in scavenging natural as well as artificial particles from the dirty atmosphere.

• Korean Journal of Environmental Biology
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• v.26 no.3
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• pp.203-213
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• 2008

Benthic macro invertebrate communities were collected at six different sampling sites in the Musucheon stream in Korea from July 2006 to July 2007, and ecological exergy values were calculated based on five different functional feeding groups (collector-gatherer, collector-filterer, predator, scrapper, and shredder) of benthic macro invertebrates. Each sampling site was categorized to three stream types (perennial, intermittent and drought) based on the water flow condition. Exergy values were low at all study sites right after a heavy rain and relatively higher in the perennial stream type than in the intermittent or the drought stream type. Self-Organizing Map (SOM), unsupervised artificial neural network, was implemented to pattern spatial and temporal dynamics of ecological exergy of the study sites. SOM classified samples into four clusters. The classification reflected the effects of floods and droughts on benthic macroinvertebrate communities, and was mainly related with the stream types of the sampling sites. Exergy values of each functional feeding group also responded differently according to the different stream types. Finally, the results showed that exergy is an effective ecological indicator, and patterning changes of exergy using SOM is an effective way to evaluate target ecosystems.

• Journal of Korean Society of Water and Wastewater
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• v.27 no.2
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• pp.197-206
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• 2013

Recently, climate change causes climatic anomaly such as global warming, the typhoon and severe rain storm etc. and it brings damage frequently. Climate change and global warming are prevalent all over the world in this century and many researchers including hydrologists have studied on the climate change. In this study, Seonakdong river watershed in the Nakdong river basin was selected as a study area. Real-time monitoring system was used to draw the rating curves, which has 0.78 to 0.96 of $R^2$. To predict runoff change in Seonakdong river watershed caused by climate change, the change in hydrologic runoff were predicted using the watershed model, SWAT. As a result, the runoff from the Seonakdong river watershed was increased by up to 45 % in summer. Because of the non-point sources from the farmland and the urban area, the water quality will be affected by the climate change. In this study, the operating plan of the water gates in Seonakdong river will be suggested by considering the characteristics of the watershed runoff due to the climate change. The optimal watergate opening plan will solve the water pollution problems in the reservoir-like river.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1996.11a
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• pp.117-120
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• 1996

In this paper, It is tested by spraying the spoiled liquids on the materials to prove the process of tracking under the various environments. Our experiments ware examined by setting the materials in the spray chamber, and by spraying the distilled water(DW), the city water(CW), the underground water(UW), the artificial acid rain(AR) and the salt water(SW) in applied voltage 3-6[KV]. As the result, the time of tracking breakdown became shorter in the order of DW < CW < UW < AR < SW. XLPE was eroded and its anti-bracking property was very strong, but that of PVC sheath was week. Especially it was confirmed that spraying by AR and SW on the PVC sheath had a serious effect on the lifetime of cable by the tracking breakdown.

• Journal of Soil and Groundwater Environment
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• v.17 no.5
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• pp.31-39
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• 2012

Chemical and isotopic variations of snowmelt provide important clues for understanding snowmelt processes and the timing and contribution of snowmelt to catchment or watershed in spring. The newly developed model includes a hydraulic exchange between mobile and immobile water (${\omega}$), and isotopic exchanges between both mobile water and ice ($f_1$) and immobile water and ice ($f_2$). Since the new model is based on the mobile-immobile water conceptualization, which is widely used for describing chemical tracer transport in snow, it allows simultaneous calculations of chemical as well as isotopic variations in snowpack discharge. We compare the model results with a study of solute transport and isotopic evolution of snowmelt in snow, using artificial rain-on-snow experiments with conservative anion ($Br^-$). These observations are used to test the newly developed model and to better understand physical processes in a seasonal snowpack where our model simulates the chemical and isotopic variations.

• Journal of Ocean Engineering and Technology
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• v.30 no.5
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• pp.341-348
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• 2016

The fatigue damage caused by wide band loadings has generally been predicted using fatigue damage models in the frequency domain rather than a rain-flow counting method in the time domain because of its computation cost. This study showed that these fatigue damage models can be simplified in the form of normalized fatigue damage as a function of the S-N curve slope and bandwidth parameters. Based on numerical simulations of various wide band spectra, it was found that fatigue damage models in the form of normalized fatigue damage with one S-N curve slope and two bandwidth parameters( α₁ , α₂ ) provided less reasonable fatigue damage. Therefore, an additional bandwidth parameter needs to be considered based on a sensitivity study using various neural networks, which proved that α_1-5 would be the dominant factor of a fatigue damage model as an additional bandwidth parameter.

• International Journal of Advanced Culture Technology
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• v.10 no.2
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• pp.300-306
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• 2022

Currently, Korea is building traffic infrastructure using Intelligent Transport Systems (ITS), but the pedestrian traffic accident rate is very high. The purpose of this paper is to prevent the risk of traffic accidents by jaywalking pedestrians. The development of this study aims to detect pedestrians who trespass using the public data set provided by the Artificial Intelligence Hub (AIHub). The data set uses training data: 673,150 pieces and validation data: 131,385 pieces, and the types include snow, rain, fog, etc., and there is a total of 7 types including passenger cars, small buses, large buses, trucks, large trailers, motorcycles, and pedestrians. has a class format of Learning is carried out using YOLOv5 as an implementation model, and as an object detection and edge detection method of an input image, a canny edge model is applied to classify and visualize human objects within the detected road boundary range. In this study, it was designed and implemented to detect pedestrians using the deep learning-based YOLOv5 model. As the final result, the mAP 0.5 showed a real-time detection rate of 61% and 114.9 fps at 338 epochs using the YOLOv5 model.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.120-120
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• 2020

Spatial precipitation data is one of the essential components in modeling hydrological problems. The estimation of these data has achieved significant achievements own to the recent advances in remote sensing technology. However, there are still gaps between the satellite-derived rainfall data and observed data due to the significant dependence of rainfall on spatial and temporal characteristics. An effective approach based on the Convolutional Neural Network (CNN) model to correct the satellite-derived rainfall data is proposed in this study. The Mekong River basin, one of the largest river system in the world, was selected as a case study. The two gridded precipitation data sets with a spatial resolution of 0.25 degrees used in the CNN model are APHRODITE (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks). In particular, PERSIANN-CDR data is exploited as satellite-based precipitation data and APHRODITE data is considered as observed rainfall data. In addition to developing a CNN model to correct the satellite-based rain data, another statistical method based on standard deviations for precipitation bias correction was also mentioned in this study. Estimated results indicate that the CNN model illustrates better performance both in spatial and temporal correlation when compared to the standard deviation method. The finding of this study indicated that the CNN model could produce reliable estimates for the gridded precipitation bias correction problem.