• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.387-398
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• 2023

The COVID-19 outbreak has significantly impacted human lifestyles and patterns. It was recommended to avoid face-to-face contact and over-crowded indoor places as much as possible as COVID-19 spreads through air, as well as through droplets or aerosols. Therefore, if a person who has contacted a COVID-19 patient or was at the place where the COVID-19 patient occurred is concerned that he/she may have been infected with COVID-19, it can be fully expected that he/she will search for COVID-19 symptoms on Google. In this study, an exploratory data analysis using deep learning models(DNN & LSTM) was conducted to see if we could predict the number of confirmed COVID-19 cases by summoning Google Trends, which played a major role in surveillance and management of influenza, again and combining it with data on the number of confirmed COVID-19 cases. In particular, search term frequency data used in this study are available publicly and do not invade privacy. When the deep neural network model was applied, Seoul (9.6 million) with the largest population in South Korea and Busan (3.4 million) with the second largest population recorded lower error rates when forecasting including search term frequency data. These analysis results demonstrate that search term frequency data plays an important role in cities with a population above a certain size. We also hope that these predictions can be used as evidentiary materials to decide policies, such as the deregulation or implementation of stronger preventive measures.

• Journal of Life Science
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• v.33 no.8
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• pp.639-650
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• 2023

The levels of harmful components in aerosols from heated tobacco products (HTPs) have been reported to be significantly lower than in cigarette smoke. However, it remains unclear whether the use of HTPs can mitigate the cardiovascular risks associated with cigarette smoking (CS). The objective of this study was to investigate the effects of a short-term switch from CS to HTP use on cardiac autonomic regulation (CAR). Seven healthy male smokers completed an open-label, randomized, cross-over trial consisting of five days of CS, use of three different HTPs (IQOS use, IQ; lil SOLID use, LS; lil HYBRID use, LH), or non-smoking (NS). Each session was separated by a one-week washout period, and levels of exhaled carbon monoxide (CO) and carboxyhemoglobin (COHb), systolic (SBP) and diastolic blood pressure (DBP), and heart rate variability (HRV) reflecting CAR were assessed before use of the product assigned to each session and at 24, 48, 72, 96, and 120 hr after use. Levels of exhaled CO and COHb were statistically significantly reduced only during NS. There were no statistical changes in SBP and DBP within any session. However, in HRV spectral analysis, log-transformed high frequency (lnHF) increased statistically significantly in IQ, LS, and NS, respectively. Normalized HF (HFnu) was significantly increased in NS and LH, respectively. lnHF and HFnu showed significant interaction effects. The findings of this study suggest that a short-term switch to HTPs instead of CS may lead to different distribution patterns of CAR, primarily driven by enhanced cardiac vagal tone.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.319-341
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• 2024

The utilization of multispectral imaging systems (MIS) in remote sensing has become crucial for large-scale agricultural operations, particularly for diagnosing plant health, monitoring crop growth, and estimating plant phenotypic traits through vegetation indices (VIs). However, environmental factors can significantly affect the accuracy of multispectral reflectance data, leading to potential errors in VIs and crop status assessments. This paper reviewed the complex interactions between environmental conditions and multispectral sensors emphasizing the importance of accounting for these factors to enhance the reliability of reflectance data in agricultural applications.An overview of the fundamentals of multispectral sensors and the operational principles behind vegetation index (VI) computation was reviewed. The review highlights the impact of environmental conditions, particularly solar zenith angle (SZA), on reflectance data quality. Higher SZA values increase cloud optical thickness and droplet concentration by 40-70%, affecting reflectance in the red (-0.01 to 0.02) and near-infrared (NIR) bands (-0.03 to 0.06), crucial for VI accuracy. An SZA of 45° is optimal for data collection, while atmospheric conditions, such as water vapor and aerosols, greatly influence reflectance data, affecting forest biomass estimates and agricultural assessments. During the COVID-19 lockdown,reduced atmospheric interference improved the accuracy of satellite image reflectance consistency. The NIR/Red edge ratio and water index emerged as the most stable indices, providing consistent measurements across different lighting conditions. Additionally, a simulated environment demonstrated that MIS surface reflectance can vary 10-20% with changes in aerosol optical thickness, 15-30% with water vapor levels, and up to 25% in NIR reflectance due to high wind speeds. Seasonal factors like temperature and humidity can cause up to a 15% change, highlighting the complexity of environmental impacts on remote sensing data. This review indicated the importance of precisely managing environmental factors to maintain the integrity of VIs calculations. Explaining the relationship between environmental variables and multispectral sensors offers valuable insights for optimizing the accuracy and reliability of remote sensing data in various agricultural applications.

• Journal of the Korean earth science society
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• v.29 no.2
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• pp.128-139
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• 2008

Intercomparison among the three radiative transfer models (RTMs) which have been used in the studies for COMS, was carried out on the condition of aerosol-laden atmospheres. Also the role of aerosols in the atmospheric radiation budget was analyzed. The results (hereafter referred to as H15) from Halthore et al.'s study (2005) were used as a benchmark to examine the models. Aerosol Radiative Forcing (ARF) values from the three RTMs, calculated under two conditions of Aerosol Optical Thickness (AOT=0.08, 0.24), were systematically underestimated in comparison to H15 in the following shortwave components; 1) direct and diffuse irradiance at the surface, 2) diffuse upward fluxes at the surface and the top of the atmosphere, and 3) atmospheric absorbance. The ARF values for the direct and diffuse fluxes at the surface was $-10{\sim}-40Wm^{-2}$. The diffuse upward values became larger with increasing both AOT and Solar Zenith Angle (SZA). Diffuse upward/downward fluxes at the surface were more sensitive to the SZA than to the atmospheric type. The diffuse downward values increased with increasing AOT and decreasing SZA. The larger AOT led to surface cooling by exceeding the reduction of direct irradiance over the enhancement of diffuse one at the surface. The extinction of direct solar irradiance was due mainly to water vapor in tropical atmospheres, and to both ozone and water vapor in subarctic atmospheres. The effect of water vapor in the tropics was $3{\sim}4$ times larger than that of the ozone. The absorbance values from the three RTMs agree with those from H15 within ${\pm}10%$.

• Atmosphere
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• v.25 no.1
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• pp.185-191
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• 2015

Ambient measurements of aerosol light absorption (${\sigma}_a$) and scattering coefficients (${\sigma}_s$) were done at Gosan climate observatory during summer 2008 using a 3-wavelength photoacoustic soot spectrometer (PASS). PASS was deployed photoacoustic method for light absorption and integrated nephelometry for light scattering measurements. The ${\sigma}_a$ and ${\sigma}_s$ from PASS were compared with those from co-located aethalometer and nephelometer measurements. The aethalometer measurements of ${\sigma}_a$ correlated reasonably well with photoacoustic measurements, but the slope of the linear fitting line indicated the PASS measurement values of ${\sigma}_a$ were larger by a factor of 1.53. The nephelometer measurement values of ${\sigma}_s$ correlated very well with PASS measurements of ${\sigma}_s$, with a slope of 1.12 and a small offset. Comparing to the aethalometer measurements, the photoacoustic measurements of ${\sigma}_a$ didn't exhibit a significant (i.e., the ratio between aethalometer and PASS increased) change with increasing relative humidity (RH). The ratio of ${\sigma}_s$ between nephelometer and PASS increased with increasing RH, especially when the RH increased beyond 80%. This apparent increase in ${\sigma}_s$ with RH may be due to the contribution of hygroscopic growth of aerosols.

• Journal of the Korean earth science society
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• v.37 no.7
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• pp.434-447
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• 2016

This study analyzed mass concentrations of PM10 and PM2.5, as measured at Tae-ahn and Gang-nae, Cheongju in central Korea over the period from 2011 to 2015. Higher mass concentrations of PM10, with the exception of dustfall cases during the period of winter and spring, reflected the influence of a prevailing westerly airflow, while the level of PM10 stayed at a low level in summer, reflecting the influence of North Pacific air mass and frequent rainfall. Accordingly, cases where a daily PM10 average of $81{\mu}gm^{-3}$ or over (exceeding the status of fine dust particles being 'a little bit bad') were often observed during the period of winter and spring, with more cases occurring in parts of Tae-ahn that are located close to the sources of pollutant emission in eastern China. Dustfall usually originated from dust storms made up of particles $2.5{\mu}m$ or over in diameter. However, anthropogenic haze displayed a high composition ratio of particulate less than $2.5{\mu}m$ in diameter. Accordingly, brightness temperature difference (BTD) values from the Communication, Ocean and Meteorological Satellite (COMS) were $-0.5^{\circ}K$ or over in haze with fine particulate. PM10 mass concentrations and NOAA 19 satellite BTD for haze cases were analyzed. Though PM10 mass concentrations were found to be lower than $200{\mu}g\;m^{-3}$, the mass concentration ratio of PM2.5/PM10 was measured as higher than 0.4 and BTD was found to be distributed in the range from -0.3 to $0.5^{\circ}K$. However, the BTD of dustfall cases exceeding $190{\mu}g\;m^{-3}$, were found to be less than 0.4 and BTD was found to be distributed in the range less than $-0.7^{\circ}K$. The result of applying BTD threshold values of the large-scale transport of haze proved to fall into line with the range over which aerosols of MODIS AOD and OMI AI were distributed.

• Journal of the Korean earth science society
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• v.35 no.1
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• pp.1-18
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• 2014

The purpose of this study was to analyze the sensitivity of meteorological fields and the variation of concentration of particulate matters (PMs) due to aerosol schemes and dust options within the WRF-Chem model to estimate Asian dusts affected on 29 May 2008 in the Korean peninsula. The anthropogenic emissions within the model were adopted by the $0.5^{\circ}{\pm}0.5^{\circ}$ RETRO of the global emissions, and the photolysis option was by Fast-J photolysis. Also, three scenarios such as the RADM2 chemical mechanism and MADE/SORGAM aerosol, the MOSAIC 8 section aerosol, and the GOCART dust erosion were simulated for calculating Asian dust emissions. As a result, the scenario of the RADM2 chemical mechanism & MADE/SORGAM aerosol depicted higher concentration than the others' in both Asian dusts and the background concentration of PMs. By comparing of the daily mean of PM10 measured at each air quality monitoring site in Seoul with the scenario results, the correlation coefficient was 0.67, and the root mean square error was $44{\mu}gm^{-3}$. In addition, the air temperature, the wind speed, the planetary boundary layer height, and the outgoing long-wave radiation were simulated under conditions of no chemical option with these three scenarios within the WRF or WRF-Chem model. Both the spatial distributions of the PBL height and the wind speed of u component among the meteorological factors were similar to those of the Asia dusts in range of 1,800-3,000 m and $2-16ms^{-1}$, respectively. And, it was shown that both scenarios of the RADM2 chemical mechanism and MADE/SORGAM aerosol and the GOCART dust erosion were interacted on-line between meteorological factors and Asian dusts or aerosols within the model because the outgoing long-wave radiation was changed to lower than the others.

• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.119-131
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• 2016

Descriptions are provided of the automated aerosol-type classification and mass concentration calculation algorithm for real-time data processing and aerosol products in Korea Aerosol Lidar Observation Network (KALION, http://www.kalion.kr). The KALION algorithm provides aerosol-cloud classification and three aerosol types (clean continental, dust, and polluted continental/urban pollution aerosols). It also generates vertically resolved distributions of aerosol extinction coefficient and mass concentration. An extinction-to-backscatter ratio (lidar ratio) of 63.31 sr and aerosol mass extinction efficiency of $3.36m^2g^{-1}$ ($1.39m^2g^{-1}$ for dust), determined from co-located sky radiometer and $PM_{10}$ mass concentration measurements in Seoul from June 2006 to December 2015, are deployed in the algorithm. To assess the robustness of the algorithm, we investigate the pollution and dust events in Seoul on 28-30 March, 2015. The aerosol-type identification, especially for dust particles, is agreed with the official Asian dust report by Korean Meteorological Administration. The lidar-derived mass concentrations also well match with $PM_{10}$ mass concentrations. Mean bias difference between $PM_{10}$ and lidar-derived mass concentrations estimated from June 2006 to December 2015 in Seoul is about $3{\mu}g\;m^{-3}$. Lidar ratio and aerosol mass extinction efficiency for each aerosol types will be developed and implemented into the KALION algorithm. More products, such as ice and water-droplet cloud discrimination, cloud base height, and boundary layer height will be produced by the KALION algorithm.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.11-19
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• 2012

Air-borne pollen, biogenically created aerosol particle, influences Earth's radiative balance, visibility impairment, and human health. The importance of pollens has resulted in numerous experimental studies aimed at characterizing their dispersion and transport, as well as health effects. There is, however, limited scientific information concerning the optical properties of airborne pollen particles contributing to total ambient aerosols. In this study, for the first time, optical characteristics of pollen such as aerosol backscattering coefficient, aerosol extinction coefficient, and depolarization ratio at 532 nm and their effect to the atmospheric aerosol were studied by lidar remotes sensing technique. Dual-Lidar observations were carried out at the Gwangju Institute of Science & Technology (GIST) located in Gwagnju, Korea ($35.15^{\circ}E$, $126.53^{\circ}N$) for a spring pollen event from 5 to 7 May 2009. The pollen concentration was measured at the rooftop of Gwangju Bohoon hospital where the building is located 1.0 km apart from lidar site by using Burkard trap sampler. During intensive observation period, high pollen concentration was detected as 1360, 2696, and $1952m^{-3}$ in 5, 6, and 7 May, and increased lidar return signal below 1.5km altitude. Pollen optical depth retrieved from depolarization ratio was 0.036, 0.021, and 0.019 in 5, 6, and 7 May, respectively. Pollen particles mainly detected in daytime resulting increased aerosol optical depth and decrease of Angstrom exponent.

• Journal of Korean Society of Environmental Engineers
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• v.29 no.1
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• pp.113-125
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• 2007

To know the differences in ionic compositions in rain and snow as well as snow influence on the chemical characteristics of winter precipitation, precipitation samples were collected by the wet-only automatic precipitation sample, in winter(November-February) in the Iksan located in the northwest of Chonbuk from 1995 to 2000. The samples were analyzed for concentrations of water-soluble ion species, in addition to pH and electrical conductivity. The mean pH of winter precipitation was 4.72. According to the type of winter precipitation, the mean pH of rain was 4.67 and lower than 5.05 in snow. The frequencies of pH below 5.0 in rain were about 73%, while those in snow were about 30%. Snow contained 3 times higher concentrations of sea salt ion components originated from seawater than did rain in winter, mainly $Cl^-,\;Na^+$, and $Mg^{2+}$. Neglecting sea salt ion components, $nss-SO_4^{2-}$ and $NO_3^-$ were important anions and $NH_4^+$ and $nss-Ca^{2+}$ were important cations in both of rain and snow. Concentrations of $nss-SO_4^{2-}$ was 1.3 times higher in rain than in snow, while those of $nss-Ca^{2+}$ and $NO_3^-$ were 1.5 and 1.3 times higher in snow, respectively. The mean equivalent concentration ratio of $nss-SO_4^{2-}/NO_3^-$ in winter precipitation were 2.4, which implied that the relative contribution of sulfuric and nitric acids to the precipitation acidity was 71% and 29%, respectively. The ratio in rain was 2.7 and higher than 1.5 in snow. These results suggest that the difference of $NO_3^-$ in rain and snow could be due to the more effective scavenging of $HNO_3$ vapor than particulate sulfate or nitrate by snow. The lower ratio in snow than rain is consistent with the measurement results of foreign other investigators and with scavenging theory of atmospheric aerosols. Although substantial $nss-SO_4^{2-}$ and $NO_3^-$ were observed in both of rain and snow, the corresponding presence of $NH_4^+,\;nss-Ca^{2+},\;nss-K^+$ suggested the significant neutralization of rain and snow. Differences in chemical composition of non-sea salt ions and neutralizing rapacity of $NH_4^+,\;nss-Ca^{2+}$, and $nss-K^+$ between rain and snow could explain the acidity difference of rain and snow. Snow affected that winter precipitation could be less acidic due to its higher neutralizing rapacity.