• Journal of The Korean Society of Grassland and Forage Science
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• v.42 no.2
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• pp.127-136
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• 2022

This study was conducted to estimate the damage of Whole Crop Maize (WCM) according to abnormal climate using machine learning and present the damage through mapping. The collected WCM data was 3,232. The climate data was collected from the Korea Meteorological Administration's meteorological data open portal. Deep Crossing is used for the machine learning model. The damage was calculated using climate data from the Automated Synoptic Observing System (95 sites) by machine learning. The damage was calculated by difference between the Dry matter yield (DMY)_normal and DMY_abnormal. The normal climate was set as the 40-year of climate data according to the year of WCM data (1978~2017). The level of abnormal climate was set as a multiple of the standard deviation applying the World Meteorological Organization(WMO) standard. The DMY_normal was ranged from 13,845~19,347 kg/ha. The damage of WCM was differed according to region and level of abnormal climate and ranged from -305 to 310, -54 to 89, and -610 to 813 kg/ha bnormal temperature, precipitation, and wind speed, respectively. The maximum damage was 310 kg/ha when the abnormal temperature was +2 level (+1.42 ℃), 89 kg/ha when the abnormal precipitation was -2 level (-0.12 mm) and 813 kg/ha when the abnormal wind speed was -2 level (-1.60 m/s). The damage calculated through the WMO method was presented as an mapping using QGIS. When calculating the damage of WCM due to abnormal climate, there was some blank area because there was no data. In order to calculate the damage of blank area, it would be possible to use the automatic weather system (AWS), which provides data from more sites than the automated synoptic observing system (ASOS).

• Nuclear Medicine and Molecular Imaging
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• v.41 no.3
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• pp.194-200
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• 2007

Purpose: $^{13}N$-ammonia is a well known radiopharmaceutical for the measurement of a myocardial blood flow (MBF) non-invasively using PET-CT. In this study, we investigated a correlation between MBF obtained from dynamic imaging and myocardial perfusion score (MPS) obtained from static imaging for usefulness of cardiac PET study. Methods: Twelve patients (11 males, 1 female, $57.9{\pm}8.6$ years old) with suspicious coronary artery disease underwent PET-CT scan. Dynamic scans (6 min: $5\;sec\;{\times}\;12,\;10\;sec\;{\times}\;6,\;20\;sec\;{\times}\;3,\;and\;30\;sec\;{\times}\;6$) were initiated simultaneously with bolus injection of 11 MBq/kg $^{13}N-ammonia$ to acquire rest and stress image. Gating image was acquired during 13 minutes continuously. Nine-segment model (4 basal walls, 4 mid walls, and apex) was used for a measurement of MBF. Time activity curve of input function and myocardium was extracted from ROI methods in 9 regions for quantification. The MPS were evaluated using quantitative analysis software. To compare between 20-segment model and 9-segment model, 6 basal segments were excluded and averaged segmental scores were used. Results: There are weak correlation between MBF (rest, 0.18-2.38 ml/min/g; stress, 0.40-4.95 ml/min/g) and MPS (rest 22-91%, stress, 14-90%), however the correlation coefficient between corrected MBF and MPS in rest state was higher than stress state (rest r=0.59; stress r=0.80). As a thickening increased, correlation between MBF and MPS also showed good correlation at each segments. Conclusions: Corrected and translated MPS as its characteristics using $^{13}N$-ammonia showed good correlation with absolute MBF measured by dynamic image in this study. Therefore, we showed MPS is one of good indices which reflect MBF. We anticipate PET-CT could be used as useful tool for evaluation of myocardial function in nuclear cardiac study.

• The Korean Journal of Air & Space Law and Policy
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• v.32 no.1
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• pp.225-285
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• 2017

In regard to the regulations related to the RPA(Remotely Piloted Aircraft), which is sometimes called in other countries as UA(Unmanned Aircraft), ICAO stipulates the regulations in the 'RPAS manual (2015)' in detail based on the 'Chicago Convention' in 1944, and enacts provisions for the Rules of UAS or RPAS. Other contries stipulates them such as the Federal Airline Rules (14 CFR), Public Law (112-95) in the United States, the Air Transport Act, Air Transport Order, Air Transport Authorization Order (through revision in "Regulations to operating Rules on unmanned aerial System") based on EASA Regulation (EC) No.216/2008 in the case of unmanned aircaft under 150kg in Germany, and Civil Aviation Act (CAA 1998), Civil Aviation Act 101 (CASR Part 101) in Australia. Commonly, these laws exclude the model aircraft for leisure purpose and require pilots on the ground, not onboard aricraft, capable of controlling RPA. The laws also require that all managements necessary to operate RPA and pilots safely and efficiently under the structure of the unmanned aircraft system within the scope of the regulations. Each country classifies the RPA as an aircraft less than 25kg. Australia and Germany further break down the RPA at a lower weight. ICAO stipulates all general aviation operations, including commercial operation, in accordance with Annex 6 of the Chicago Convention, and it also applies to RPAs operations. However, passenger transportation using RPAs is excluded. If the operational scope of the RPAs includes the airspace of another country, the special permission of the relevant country shall be required 7 days before the flight date with detail flight plan submitted. In accordance with Federal Aviation Regulation 107 in the United States, a small non-leisure RPA may be operated within line-of-sight of a responsible navigator or observer during the day in the speed range up to 161 km/hr (87 knots) and to the height up to 122 m (400 ft) from surface or water. RPA must yield flight path to other aircraft, and is prohibited to load dangerous materials or to operate more than two RPAs at the same time. In Germany, the regulations on UAS except for leisure and sports provide duty to avoidance of airborne collisions and other provisions related to ground safety and individual privacy. Although commercial UAS of 5 kg or less can be freely operated without approval by relaxing the existing regulatory requirements, all the UAS regardless of the weight must be operated below an altitude of 100 meters with continuous monitoring and pilot control. Australia was the first country to regulate unmanned aircraft in 2001, and its regulations have impacts on the unmanned aircraft laws of ICAO, FAA, and EASA. In order to improve the utiliity of unmanned aircraft which is considered to be low risk, the regulation conditions were relaxed through the revision in 2016 by adding the concept "Excluded RPA". In the case of excluded RPA, it can be operated without special permission even for commercial purpose. Furthermore, disscussions on a new standard manual is being conducted for further flexibility of the current regulations.

• The Korean Journal of Financial Management
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• v.24 no.2
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• pp.1-40
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• 2007

We test a model of investment-cashflow-growth opportunities relationship in order to estimate the sensitivities to investments. In this study, we use a new proxy variable for the value of growth opportunities(hereafter "VGO"), which is based on the seminal papers of M&M(1958:1961:1963) and Lee(2006;2007). The empirical findings on the sensitivities of cashflow and growth opportunities are as follows. First, when the traditional proxy variables for the growth opportunities such as Tobin's Q, MBR and sales growth are included with the new proxy VGO in the estimation, their coefficients are turned out to be insignificant. Second, only the new proxy variable VGO shows a statistically significant positive sensitibity to investment, which can be regarded that the growth opportunities hold the positive influences to investments. Third, the Tobin's Q can be decomposed into three factors such as the value of growth opportunities(VGO), the value of asset-in-place and valuation errors. It turns out that only the VGO shows a statistically significant positive relationship with investment among others. This means that the new variable VGO is a good proxy variable for the growth opportunities in the investment-cashflow sensitivity analysis. In sum, thanks to the above findings in this study, we can say that it will not be proper to choose a proxy variable for the growth opportunities from the traditional set of proxies such as Tobin's Q, MBR, or sales growth rate.

• The Korean Journal of Nuclear Medicine
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• v.32 no.1
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• pp.50-60
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• 1998

I-123 labelled fatty acids are suitable for investigation of regional myocardial metabolism, so they are on the clinical trial. However, the precise properties of these materials are not characterized yet. We have synthesized phenylpentadecanoic acid and labeled this compound with I-123. The purpose of this study was to examine the stability, biodistribution, metabolism and SPECT imaging of [I-123]15-(p-iodophenyl)pentadecanoic acid(I-123-IPPA) that we made. The stability test of I-123-IPPA in serum of rat, mouse and human showed no free I-123 after 1 hour. In biodistribution study in mice for various time intervals after injection(5, 10, 15, 30, 60 minutes), uptake in myocardium was 14.5%ID/g(5 min), and 1.9%ID/heart(5 min), while uptake in muscles was 2.6%ID/g(5 min). Myocardium to blood ratio and myocardium to lung ratio increased for 5 min after injection and then decreased rapidly. Chromatographic data of rat blood and urine showed that little PPA was found in blood and urine at 15-20 min after injection. The myocardial I-123-IPPA SPECT images of a dog with myocardial infarction showed defects similar to those of Tc-99m-MIBI and F-18-FDG. These data suggest that I-123-IPPA is quite stable in vitro and shows favorable biodistribution in mice. SPECT imaging with I-123-IPPA demonstrated infarct zone as photon defect in dog model of myocardial infarction. I-123-IPPA may be used for the evaluation of fatty acid metabolism in clinical trials in Korea.

• The Journal of the Petrological Society of Korea
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• v.25 no.3
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• pp.195-209
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• 2016

The understanding of geometric complexity of strike-slip Fault system can be an important factor to control fault reactivation and surface rupture propagation under the regional stress regime. The Kumamoto earthquake was caused by dextral reactivation of the Futagawa-Hinagu Fault system under the E-W maximum horizontal principal stress. The earthquakes are a set of earthquakes, including a foreshock earthquake with a magnitude 6.2 at the northern tip of the Hinagu Fault on April 14, 2016 and a magnitude 7.0 mainshock which generated at the intersection of the two faults on April 16, 2016. The hypocenters of the main shock and aftershocks have moved toward NE direction along the Futagawa Fault and terminated at Mt. Aso area. The intersection of the two faults has a similar configuration of ${\lambda}$-fault. The geometries and kinematics, of these faults were comparable to the Yansan-Ulsan Fault system in SE Korea. But slip rate is little different. The results of age dating show that the Quaternary faults distributed along the northern segment of the Yangsan Fault and the Ulsan Fault are younger than those along the southern segment of the Yansan Fault. This result is well consistent with the previous study with Column stress model. Thus, the seismic activity along the middle and northern segment of the Yangsan Fault and the Ulsan Fault might be relatively active compared with that of the southern segment of the Yangsan Fault. Therefore, more detailed seismic hazard and paleoseismic studies should be carried out in this area.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.149-155
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• 2021

Early warning systems for weather risk management in the agricultural sector have been developed to predict potential wind damage to crops. These systems take into account the daily maximum wind speed to determine the critical wind speed that causes fruit drops and provide the weather risk information to farmers. In an effort to increase the accuracy of wind risk predictions, an artificial neural network for binary classification was implemented. In the present study, the daily wind speed and other weather data, which were measured at weather stations at sites of interest in Jeollabuk-do and Jeollanam-do as well as Gyeongsangbuk- do and part of Gyeongsangnam- do provinces in 2019, were used for training the neural network. These weather stations include 210 synoptic and automated weather stations operated by the Korean Meteorological Administration (KMA). The wind speed data collected at the same locations between January 1 and December 12, 2020 were used to validate the neural network model. The data collected from December 13, 2020 to February 18, 2021 were used to evaluate the wind risk prediction performance before and after the use of the artificial neural network. The critical wind speed of damage risk was determined to be 11 m/s, which is the wind speed reported to cause fruit drops and damages. Furthermore, the maximum wind speeds were expressed using Weibull distribution probability density function for warning of wind damage. It was found that the accuracy of wind damage risk prediction was improved from 65.36% to 93.62% after re-classification using the artificial neural network. Nevertheless, the error rate also increased from 13.46% to 37.64%, as well. It is likely that the machine learning approach used in the present study would benefit case studies where no prediction by risk warning systems becomes a relatively serious issue.

• Journal of Life Science
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• v.32 no.1
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• pp.11-22
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• 2022

N-methyl-D-aspartate (NMDA) receptors have received considerable attention regarding their involvement in glutamate-induced neuronal excitotoxicity. Resveratrol has been shown to exhibit neuroprotective effects against this kind of overactivation, but the underlying cellular mechanisms are not yet clearly understood. In this study, HT-22 neuronal cells were treated with NMDA in Mg²⁺-free buffer and subsequently used as an experimental model of glutamate excitotoxicity to elucidate the mechanisms of resveratrol-induced neuroprotection. We found that NMDA treatment causes a drop in MTT reduction ability, disrupts inside-negative transmembrane potential of mitochondria, depletes cellular ATP levels, and stimulates intracellular ROS production. Double fluorescence imaging studies demonstrated an increased formation of mitochondrial permeability transition (MPT) pores accompanied by apoptotic cell death, while cobalt protoporphyrin and bilirubin showed protective effects against NMDA-induced mitochondrial injury. On the other hand, zinc protoporphyrin IX significantly attenuated the protective effects of resveratrol which was itself shown to enhance heme oxygenase-1 (HO-1) mRNA and protein expression levels. In cells transfected with HO-1 small interfering RNA, resveratrol failed to suppress the NMDA-induced effects on MTT reduction ability and MPT pore formation. The present study suggests that resveratrol may prevent mitochondrial injury in NMDA- treated HT-22 cells and that enhanced expression of HO-1 is involved in the underlying cellular mechanism.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Journal of Preventive Medicine and Public Health
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• v.32 no.2
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• pp.177-182
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• 1999

Objectives: To reexamine the association between air pollution and daily mortality in Seoul, Korea using a method of meta-analysis with the data filed for 1991 through 1995. Methods: A separate Poisson regression analysis on each district within the metropolitan area of Seoul was conducted to regress daily death counts on levels of each ambient air pollutant, such as total suspended particulates (TSP), sulfur dioxide $(SO_2)$, and ozone $(O_3)$, controlling for variability in the weather condition. We calculated a weighted mean as a meta-analysis summary of the estimates and its standard error. Results: We found that the p value from each pollutant model to test the homogeneity assumption was small (p<0.01) because of the large disparity among district-specific estimates. Therefore, all results reported here were estimated from the random effect model. Using the weighted mean that we calculated, the mortality at a $100{\mu}g/m^3$ increment in a 3-day moving average of TSP levels was 1.034 (95% Cl 1.009-1.059). The mortality was estimated to increase 6% (95% Cl 3-10%) and 3% (95% Cl 0-6%) with each 50 ppb increase for 9-day moving average of SO2 and 1-hr maximum O3, respectively. Conclusions: Like most of air pollution epidemiologic studies, this meta-analysis cannot avoid fleeing from measurement misclassification since no personal measurement was taken. However, we can expect that a measurement bias be reduced in a district-specific estimate since a monitoring station is hefter representative cf air quality of the matched district. The similar results to those from the previous studios indicated existence of health effect of air pollution at current levels in many industrialized countries, including Korea.