• Journal of Korea Water Resources Association
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• v.50 no.9
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• pp.587-595
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• 2017

Hydraulic characteristics affecting sediment transport capacity due to the weir operations were investigated and developed sediment rating curves for four gaging stations (Nakdong, Gumi, Waegwan, and Jindong) in Nakdong River. Analysis found that the sediment transportaion capability had been decreased and it could be proved from the field measurement records in 2013. Applicabilities of nine sediment transport prediction techniques, which are imbeded in GUIDE program, were examined and adopted for the four gaging stations. Analysis of sediment balance for Nakdong River, including 9 major tributaries, had been carried out with pseudo 2-D numerical model and found that: 1) sedimentation phenomena will be prevailed along the Nakdong River. 2) Engelund-Hansen technique shows the least error in estimation of sediment balance. 3) Engelund-Hansen technique most appropriately describes the sediment characteristics for four gaging stations. 4) Estimated error from the sediment balance for Nakdong River was smaller than the error caused by the estimation of sediment incomming from 9 tributries. Therefore, it is necessary to improve the accuracy of predicting the sediment incomming from the tributaties for better sediment balance analysis.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.2
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• pp.121-131
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• 2007

Despite the close linkage in changes between the ecological and hydrological processes in forest ecosystems, an integrative approach has not been incorporated successfully. In this study, based on the vegetation and hydrologic data of the Gwangneung headwater catchment with the Geographic Information System, we attempted such an integrated approach by employing the Regional Hydro-Ecologic Simulation System (RHESSys). To accomplish this, we have (1) constructed the input data for RHESSys, (2) developed an integrated calibration system that enables to consider both ecological and hydrological processes simultaneously, and (3) performed sensitivity analysis to estimate the optimum parameters. Our sensitivity analyses on six soil parameters that affect streamflow patterns and peak flow show that the decay parameter of horizontal saturated hydraulic conductivity $(s_1)$ and porosity decay by depth (PD) had the highest sensitivity. The optimization of these two parameters to estimate the optimum streamflow variation resulted in a prediction accuracy of 0.75 in terms of Nash-Sutcliffe efficiency (NSec). These results provide an important basis for future evaluation and mapping of the watershed-scale soil moisture and evapotranspiration in forest ecosystems of Korea.

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.197-207
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• 2010

Using a variety of data-mining methods on high-throughput cDNA microarray data, the level of gene expression in two different tissues can be compared, and DEG(Differentially Expressed Gene) genes in between normal cell and tumor cell can be detected. Diagnosis can be made with these genes, and also treatment strategy can be determined according to the cancer stages. Existing cancer classification methods using machine learning select the marker genes which are differential expressed in normal and tumor samples, and build a classifier using those marker genes. However, in addition to the differences in gene expression levels, the difference in gene-gene correlations between two conditions could be a good marker in disease diagnosis. In this study, we identify gene pairs with a big correlation difference in two sets of samples, build gene classification modules using these gene pairs. This cancer classification method using gene modules achieves higher accuracy than current methods. The implementing clinical kit can be considered since the number of genes in classification module is small. For future study, Authors plan to identify novel cancer-related genes with functionality analysis on the genes in a classification module through GO(Gene Ontology) enrichment validation, and to extend the classification module into gene regulatory networks.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.521-530
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• 2018

This paper proposes "The Agriculture Decision-making System(ADS) based on Deep Learning for improving crop productivity" that collects weather information based on location supporting precision agriculture, predicts current crop condition by using the collected information and real time crop data, and notifies a farmer of the result. The system works as follows. The ICM(Information Collection Module) collects weather information based on location supporting precision agriculture. The DRCM(Deep learning based Risk Calculation Module) predicts whether the C, H, N and moisture content of soil are appropriate to grow specific crops according to current weather. The RNM(Risk Notification Module) notifies a farmer of the prediction result based on the DRCM. The proposed system improves the stability because it reduces the accuracy reduction rate as the amount of data increases and is apply the unsupervised learning to the analysis stage compared to the existing system. As a result, the simulation result shows that the ADS improved the success rate of data analysis by about 6%. And the ADS predicts the current crop growth condition accurately, prevents in advance the crop diseases in various environments, and provides the optimized condition for growing crops.

• Korean Journal of Clinical Laboratory Science
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• v.53 no.4
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• pp.309-316
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• 2021

Sepsis is a physiological response to a source of infection that triggers mechanisms that compromise organ function, leading to death if not treated early. Biomarkers with high sensitivity, specificity, speed, and accuracy that could differentiate sepsis from non-infectious systemic inflammatory response syndrome (SIRS) could bring about a revolution in sepsis treatment. Given the limitations and time required for microbial verification of pathogens, the accurate diagnosis of infection before employing antibiotic therapy is important and clinically necessary. Procalcitonin (PCT), lactate, C-reactive protein (CRP), cytokines, and proadrenomedullin (ProADM) are the common biomarkers used for diagnosis. The procalcitonin (PCT)-guided antibiotic treatment in patients with acute respiratory infections effectively reduces antibiotic exposure and side effects while improving survival rates. The evidence regarding sepsis screening in hospitalized patients is limited. Clinicians, researchers, and healthcare decision-makers should consider these findings and limitations when implementing screening tools, future research, or policy on sepsis recognition in hospitalized patients. The use of biomarkers in pediatric sepsis is promising, although such use should always be correlated with clinical evaluation. Biomarkers may also improve the prediction of mortality, especially in the early phase of sepsis, when the levels of certain pro-inflammatory cytokines and proteins are elevated.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5A
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• pp.841-848
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• 2006

There is a complex variation of stress in PSC anchorage zones and box girder diaphragms because of large concentrated load by prestress. According to the AASHTO LFRD design code, three-dimensional effects due to concentrated jacking loads shall be investigated using three-dimensional analysis procedures or may be approximated by considering separate submodels for two or more planes. In this case, the interaction of the submodels should be considered, and the model loads and results should be consistent. However, box girder diaphragms are 3-dimensional disturbed region which requires a fully three-dimensional model, and two-dimensional models are not satisfactory to model the flow of forces in diaphragms. In this study, the strengths of the prestressed box girder diaphragms are predicted using the 3-dimensional grid strut-tie model approach, which were tested to failure in University of Texas. According to the analysis results, the 3-dimensional strut-tie model approach can be possibly applied to the analysis and design of PSC box girder anchorage zones as a reasonable computer-aided approach with satisfied accuracy.

• Korean Journal of Environmental Biology
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• v.33 no.4
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• pp.459-467
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• 2015

Understanding of a carbon storage in a regional scale ecosystem is a very important data for predicting change of global carbon cycle. Therefore, the real data collected in the various ecosystems are a very useful for enhancing accuracy of model prediction. We tried to estimate total accumulated ecosystem carbon in Deogyusan National Park (DNP) with naturally well preserved ecosystem. In DNP, vegetations were classified to four main communities with Quercus mongolica community (12,636.9 ha, 54.8%), Quercus variabilis community (2,987.0 ha, 13.0%), Pinus densiflora community (5,758.0 ha, 25.0%), and Quercus serrata community (402.9 ha,1.7%). Biomass and soil carbons were estimated by the biomass allometric equations based on the DBH and carbon contents of litter and soil (0~30 cm) layers collected in 3 plots ($30cm{\times}30cm$) in each community. The biomass and soil carbons were shown as high value as 1,759,000 tC and 7,776,000 tC, respectively, in Quercus mongolia community in DNP area. In Quercus mongolica, Quercus variabilis, Quercus serrata, Pinus densiflora communities, the accumulated ecosystem carbon were shown 9,536,000 tC, 1,405,000 tC, 147,000 tC, 346,000 tC, respectively. Also, the total ecosystem carbon was estimated with 11,434,000 tC in DNP.

• Spatial Information Research
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• v.20 no.2
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• pp.13-24
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• 2012

To prevent the damage to human health by climate change, vulnerability assessment should be conducted for establishment of adaptation strategies. In this study, vulnerability assessment was conducted to provide information about vulnerable area for making adaptation policy. vulnerability assessment for human health was divided into three categories; extreme heat, ozone, and epidemic disease. To assess vulnerability, suitable indicators were selected by three criteria; sensitivity, adaptive capacity, and exposure, spatial data of indicators were prepared and processed using GIS technique. As a result, high vulnerability to extreme heat was shown in the low land regions of southern part. And vulnerability to harmful ozone was high in the surrounding area of Dae-gu basin and metropolitan area with a number of automobiles. Vulnerability of malaria and tsutsugamushi disease have a region-specific property. They were high in the vicinity of the Dimilitarized zone and south-western plain, respectively. In general, vulnerability of human health was increased in the future time. Vulnerable area was extended from south to central regions and from plain to low mountainous regions. For assessing vulnerability with high accuracy, it is necessary to prepare more related indicators and consider weight of indicators and use climate prediction data based on the newly released scenario when assessing vulnerability.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.481-494
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• 2018

The accurate radiative transfer model simulation is essential for an accurate ozone profile retrieval using optimal estimation from backscattered ultraviolet (BUV) measurement. The input parameters of the radiative transfer model are the main factors that determine the model accuracy. In particular, meteorological parameters such as temperature and surface pressure have a direct effect on simulating radiation spectrum as a component for calculating ozone absorption cross section and Rayleigh scattering. Hence, a sensitivity of UV ozone profile retrievals to these parameters has been investigated using radiative transfer model. The surface pressure shows an average error within 100 hPa in the daily / monthly climatological data based on the numerical weather prediction model, and the calculated ozone retrieval error is less than 0.2 DU for each layer. On the other hand, the temperature shows an error of 1-7K depending on the observation station and altitude for the same daily / monthly climatological data, and the calculated ozone retrieval error is about 4 DU for each layer. These results can help to understand the obtained vertical ozone information from satellite. In addition, they are expected to be used effectively in selecting the meteorological input data and establishing the system design direction in the process of applying the algorithm to satellite operation.

• Journal of Astronomy and Space Sciences
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• v.24 no.3
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• pp.249-260
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• 2007

The crustal deformation due to Ocean Tide Loading (OTL) in the Korean peninsula reaches up to ${\sim}3cm$ in the vertical direction. Considering that the achievable positioning accuracy of current state-of-the-art space geodesy technologies is at the several millimeter level, the centimeter-level OTL effect should be precisely modelled and corrected for. This study begins with comparison of ocean tide models and validation of OTL-prediction softwares. Different ocean tide models caused about ${\sim}6mm$ RMS differences in the vertical deformation in the Kyung-gi Bay area. When we analyzed the OTL displacements in the Seoul, Ulsan, and Seogwipo areas where three VLBI observatories are planned to be installed, the maximum displacement of ${\sim}3.5cm$ was predicted in the Seogwipo area and ${\sim}2cm$ in the Seoul and Ulsan areas. When the OTL corrections were not applied in the GPS data processing, the OTL effect propagates into the Zenith Wet Delay (ZWD) estimates, and the scale factor between ZWD differences and OTL displacements was 3.72.