• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1405-1423
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• 2021

Precipitation is one of the main factors that affect water and energy cycles, and its estimation plays a very important role in securing water resources and timely responding to water disasters. Satellite-based quantitative precipitation estimation (QPE) has the advantage of covering large areas at high spatiotemporal resolution. In this study, machine learning-based rainfall intensity models were developed using Himawari-8 Advanced Himawari Imager (AHI) water vapor channel (6.7 ㎛), infrared channel (10.8 ㎛), and weather radar Column Max (CMAX) composite data based on random forest (RF). The target variables were weather radar reflectivity (dBZ) and rainfall intensity (mm/hr) converted by the Z-R relationship. The results showed that the model which learned CMAX reflectivity produced the Critical Success Index (CSI) of 0.34 and the Mean-Absolute-Error (MAE) of 4.82 mm/hr. When compared to the GeoKompsat-2 and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN)-Cloud Classification System (CCS) rainfall intensity products, the accuracies improved by 21.73% and 10.81% for CSI, and 31.33% and 23.49% for MAE, respectively. The spatial distribution of the estimated rainfall intensity was much more similar to the radar data than the existing products.

• Journal of Korea Water Resources Association
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• v.52 no.3
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• pp.187-194
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• 2019

Intake ratio from river constitutes about 31% (8/26) that beings to "water stress country" as "Medium ~ High" with China, India, Italy, South Africa, etc. Therefore, the present study on a dam that is the most effective and direct for securing water resources has been performed. First of all, climate change scenarios were investigated and analyzed. RCP 4.5 and 8.5 with 12.5 km grid resolution presented in the IPCC (Intergovernmental Panel on Climate Change) 5th Assessment Report (AR5) were applied to study watershed using SWAT (Soil and Water Assessment Tool) and HEC-ResSim models that carried out co-operation. Based on the results of dam simulation, the reduction effects of floods and droughts were quantitatively presented. The procedures of dam projects of the USA, Japan and Korea were investigated. As a result, there are no estimating quantitative criteria, calculating methods or formulas. In the present study, therefore, indexes for selecting suitable dam site through literature investigation and analyzing dam watersheds were determined, Expert questionnaire for various indexes were performed. Based on the above mentioned investigation and expert questionnaire, a methodology assigning weight using AHP method were proposed. The function of suitable dam (FSDS) site was calibrated and verified for four medium-sized watersheds. Finally, automated model for suitable dam site was developed using FSDS and 'Model builder' of GIS tool.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.645-652
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• 2018

Recently, as South Korea has joined the OSJD, the rules of the OSJD need to be applied to South Korea. Therefore, the railways are connected to the continent railway in terms of software, but the railway systems in neighboring countries have been developed and operated for a long time, and are quite different with some restrictions in terms of hardware. Therefore, this study analyzed the current railway systems of neighboring countries' based on the TSI used in Europe for technical interoperability. A real operation with the operation models within the specific route was assumed and vector functions for the Infrastructure vector & Rolling stock vector were produced. The IOP value was calculated by working out the interfacing matrix value between the infrastructure vector and rolling stock vector. As a result of calculating the IOP in a specific route, which is from Busan South Korea to Vladivostok with the diesel locomotive hauling freight cars, the value was only 22%, which is fairly low in terms of the interoperability. In other words, there are 77.8% restricting items preventing their interoperability. Such restricted causes should be improved to increase the technical interoperability in the long term. Moreover, and when railway systems are constructed and manufactured, it is important to keep IOP 100% to increase the operating efficiency in continental railways.

• Korean Journal of Medicinal Crop Science
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• v.28 no.6
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• pp.395-411
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• 2020

Background: This study investigated the anti-obesity effect of the flavonoid rich fraction (FRF) and its constituent, rutin obtained from the leaf of Morus alba L., on the lipid accumulation mechanism in 3T3-L1 adipocyte and C57BL/6 mouse models. Methods and Results: In Oil Red O staining, FRF (1,000 ㎍/㎖) treatments showed inhibition rate of 35.39% in lipid accumulation compared to that in the control. AdipoRedTM assay indicated that the triglyceride content in 3T3-L1 adipocytes treated with FRF (1,000 ㎍/㎖) was reduced to 23.22%, and free glycerol content was increased to 106.04% that of the control. FRF and its major constituent, rutin affected mRNA gene expression. Rutin contributed to the inhibition of Sterol regulatory element binding protein-1c (SREBP-1c) gene expression, and inhibited the transcription factors SREBP-1c, peroxisome proliferator-activated receptor gamma (PPAR-γ), CCAAT/enhancer binding protein α (C/EBPα), fatty acid synthase (FAS) and acetyl-CoA carboxylase (ACC). In addition, the effect of FRF administration on obesity development in C57BL/6 mice fed high-fat diet (HFD) was investigated. FRF suppressed weight gain, and reduced liver triglyceride and leptin secretion. FRF exerted potential anti-inflammatory effects by improving insulin resistance and adiponectin levels, and could thus be used to help counteract obesity. The mRNA expressions of PPAR-γ, FAS, ACC, and CPT-1 were determined in liver tissue. Quantitative real-time PCR analysis was also performed to evaluate the expression of IL-1β, IL-6, and TNF-α in epididymal adipose tissue. Compared to the control group, mice fed the HFD showed the up-regulation in PPAR-γ, FAS, IL-6, and TNF-α genes, and down-regulation in CPT1 gene expression. FRF treatement markedly reduced the expression of PPAR-γ, FAS, IL-6, and TNF-α compared to those in HFD control, whereas increased the expression level of CPT1. Conclusions: These results suggest that the FRF and its major active constituent, rutin, can be used as effective anti-obesity agents.

• Journal of the Korean Society of Radiology
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• v.14 no.7
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• pp.965-973
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• 2020

The purpose of this study was to quantitatively correlate the change of flow velocity and signal voiding in TOF-MRA. We made our phantom to control the flow velocity, and changed the flow velocity in 16 steps from 8.0 to 127.3 mc/s. The TOF-MRA test was performed using a 3.0T MRI system and the signal intensity was measured by classifying the signal voiding length and image into the In flow, Mid flow, and Out flow. The length of signal voiding was the longest when the flow velocity was 127.3 cm/s and the signal intensity decreased with increasing flow velocity(p<0.05). In flow(-.547) and Mid flow(-.643) were negatively correlated with flow velocitys(p<0.05). In conclusion, it was confirmed that the increase in flow velocity was a major factor causing signal voiding in TOF-MRA. In the future, this study will provide basic data when studying sequences and parameters to reduce signal voiding in models with a high flow velocity.

• (The)Korea Educational Review
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• v.24 no.4
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• pp.247-286
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• 2018

The study aims to analyze the research trends according to 'characteristics of researchers' in the research papers published in "The Journal of Educational Administration" between last 10 years(2009 to 2018 first half). The study results are as follow. First, in terms of the researcher, more research was done by 'joint' researchers than a 'single' researcher. In addition, the number of studies in which the first author was male was higher than in women. Also, collaborative research between 'professors' and 'graduate students' was actively done. Second, the number of studies to develop and verify theories(or models) has increased. Third, in terms of research methods, more studies tend to utilize 'quantitative research' using advanced statistics and 'qualitative research' through interviews and observations to describe and explain Korea's educational administration phenomenon. Fourth, researchers showed high interest in 'School organization and management;', 'Higher education', 'Education policy and planning'. Fifth, according to each research area, there were some differences in the characteristics of the researchers who conducted the research, the nature of the research, and the research methods used mainly. Based on the results of this study, this study suggested the future trends of educational administration research in the era of the fourth industrial revolution.

• Journal of Korea Water Resources Association
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• v.55 no.3
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• pp.245-255
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• 2022

Evaluating the qualitative the qualitative process of water resources by using various indicators, as one of the most prevalent methods for optimal managing of water bodies, is necessary for having one regular plan for protection of water quality. In this study, zoning maps were developed on a yearly basis by collecting and reviewing the process, validating, and performing statistical tests on qualitative parameters҆ data of the Iranian aquifers from 1995 to 2020 using Geographic Information System (GIS), and based on Inverse Distance Weighting (IDW), Radial Basic Function (RBF), and Global Polynomial Interpolation (GPI) methods and Kriging and Co-Kriging techniques in three types including simple, ordinary, and universal. Then, minimum uncertainty and zoning error in addition to proximity for ASE and RMSE amount, was selected as the optimum model. Afterwards, the selected model was zoned by using Scholar and Wilcox. General evaluation of groundwater situation of Iran, revealed that 59.70 and 39.86% of the resources are classified into the class of unsuitable for agricultural and drinking purposes, respectively indicating the crisis of groundwater quality in Iran. Finally, for validating the extracted results, spatial changes in water quality were evaluated using the Groundwater Quality Index (GWQI), indicating high sensitivity of aquifers to small quantitative changes in water level in addition to severe shortage of groundwater reserves in Iran.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.7
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• pp.233-240
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• 2022

Most of the recent AI researches has focused on developing AI models. However, recently, artificial intelligence research has gradually changed from model-centric to data-centric, and the importance of learning data is getting a lot of attention based on this trend. However, it takes a lot of time and effort because the preparation of learning data takes up a significant part of the entire process, and the generation of labeling data also differs depending on the purpose of development. Therefore, it is need to develop a tool with various labeling functions to solve the existing unmetneeds. In this paper, we describe a labeling system for creating precise and fast labeling data of medical images. To implement this, a semi-automatic method using Back Projection, Grabcut techniques and an automatic method predicted through a machine learning model were implemented. We not only showed the advantage of running time for the generation of labeling data of the proposed system, but also showed superiority through comparative evaluation of accuracy. In addition, by analyzing the image data set of about 1,000 patients, meaningful diagnostic indexes were presented for men and women in the diagnosis of sarcopenia.

• Fisheries and Aquatic Sciences
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• v.25 no.5
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• pp.287-297
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• 2022

The objective of this study was to evaluate the probability of norovirus foodborne illness by raw oyster consumption. One hundred fifty-six oyster samples were collected to examine the norovirus prevalence. The oyster samples were inoculated with murine norovirus and stored at 4℃-25℃. A plaque assay determined norovirus titers. The norovirus titers were fitted with the Baranyi model to calculate shoulder period (h) and death rate (Log PFU/g/h). These kinetic parameters were fitted to a polynomial model as a function of temperature. Distribution temperature and time were surveyed, and consumption data were surveyed. A dose-response model was also searched through literature. The simulation model was prepared with these data in @RISK to estimate the probability of norovirus foodborne. One sample of 156 samples was norovirus positive. Thus, the initial contamination level was estimated by the Beta distribution (2, 156), and the level was -5.3 Log PFU/g. The developed predictive models showed that the norovirus titers decreased in oysters under the storage conditions simulated with the Uniform distribution (0.325, 1.643) for time and the Pert distribution (10, 18, 25) for temperature. Consumption ratio of raw oyster was 0.98%, and average consumption amount was 1.82 g, calculated by the Pert distribution [Pert {1.8200, 1.8200, 335.30, Truncate (0, 236.8)}]. ₁F₁ hypergeometric dose-response model [1 - (1 + 2.55 × 10^-3 × dose)^-0.086] was appropriate to evaluate dose-response. The simulation showed that the probability of norovirus foodborne illness by raw oyster consumption was 5.90 × 10^-10 per person per day. The annual socioeconomic cost of consuming raw oysters contaminated with norovirus was not very high.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1109-1124
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• 2022

This study proposes a marine debris monitoring methods using satellite and drone multispectral images. A multi-layer perceptron (MLP) model was applied to detect marine debris using Sentinel-2 satellite image. And for the detection of marine debris using drone multispectral images, performance evaluation and comparison of U-Net, DeepLabv3+ (ResNet50) and DeepLabv3+ (Inceptionv3) among deep learning models were performed (mIoU 0.68). As a result of marine debris detection using satellite image, the F1-Score was 0.97. Marine debris detection using drone multispectral images was performed on vegetative debris and plastics. As a result of detection, when DeepLabv3+ (Inceptionv3) was used, the most model accuracy, mean intersection over union (mIoU), was 0.68. Vegetative debris showed an F1-Score of 0.93 and IoU of 0.86, while plastics showed low performance with an F1-Score of 0.5 and IoU of 0.33. However, the F1-Score of the spectral index applied to generate plastic mask images was 0.81, which was higher than the plastics detection performance of DeepLabv3+ (Inceptionv3), and it was confirmed that plastics monitoring using the spectral index was possible. The marine debris monitoring technique proposed in this study can be used to establish a plan for marine debris collection and treatment as well as to provide quantitative data on marine debris generation.