• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.367-373
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• 2023

Aircrews and passengers are exposed to radiation from cosmic rays and secondary scattered rays generated by reactions with air or aircraft. For aircrews, radiation safety management is based on the exposure dose calculated using a space-weather environment simulation. However, the exposure dose varies depending on solar activity, altitude, flight path, etc., so measuring by route is more suggestive than the calculation. In this study, we developed an instrument to measure the cosmic radiation dose using a general-purpose Si sensor and a multichannel analyzer. The dose calculation applied the algorithm of CRaTER (Cosmic Ray Telescope for the Effects of Radiation), a space radiation measuring device of NASA. Energy and dose calibration was performed with Cs-137 662 keV gamma rays at a standard calibration facility, and good dose rate dependence was confirmed in the experimental range. Using the instrument, the dose was directly measured on the international line between Dubai and Incheon in May 2023, and it was similar to the result calculated by KREAM (Korean Radiation Exposure Assessment Model for Aviation Route Dose) within 12%. It was confirmed that the dose increased as the altitude and latitude increased, consistent with the calculation results by KREAM. Some limitations require more verification experiments. However, we confirmed it has sufficient utilization potential as a cost-effective measuring instrument for monitoring exposure dose inside or on personal aircraft.

• Journal of the Korean earth science society
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• v.44 no.1
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• pp.62-78
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• 2023

The purpose of this study is to analyze the field of Earth science at a science fair. For this purpose, 566 pieces of data spanning 21 years (2000 to 2020), acquired from entries in the Earth Science section on the science fair website, were analyzed using the semantic network method. As a result, geoscience topics have been actively explored in works submitted for the Earth Science section of the science fair. Fossils from the Cretaceous period of the Mesozoic Era were particularly predominant. Together with these, keywords corresponding to astronomy, space science, and atmospheric science formed a small-scale network. Astronomy and space science mainly dealt with the dynamic characteristics of asteroids, Venus, and Jupiter. Other subjects included the solar system, sunspots, and lunar phases. Atmospheric science has focused on atmospheric physics, atmospheric observation and analysis technology, atmospheric dynamics, air quality monitoring, while marine science has been limited to physical oceanography and geologic oceanography. This study, is expected to help select Earth Science topics and conduct inquiry activities in schools.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.245-257
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• 2023

The representative crop in the Republic of Korea, rice, is cultivated over extensive areas every year, which resulting in reduced resistance to pests and diseases. One of the major rice diseases, rice blast disease, can lead to a significant decrease in yields when it occurs on a large scale, necessitating early detection and effective control of rice blast disease. Drone-based crop monitoring techniques are valuable for detecting abnormal growth, but frequent image capture for potential rice blast disease occurrences can consume significant labor and resources. The purpose of this study is to early detect rice blast disease using remote sensing data, such as drone and satellite images, along with weather data. Satellite images was helpful in identifying rice cultivation fields. Effective detection of paddy fields was achieved by utilizing vegetation and water indices. Subsequently, air temperature, relative humidity, and number of rainy days were used to calculate the risk of rice blast disease occurrence. An increase in the risk of disease occurrence implies a higher likelihood of disease development, and drone measurements perform at this time. Spectral reflectance changes in the red and near-infrared wavelength regions were observed at the locations where rice blast disease occurred. Clusters with low vegetation index values were observed at locations where rice blast disease occurred, and the time series data for drone images allowed for tracking the spread of the disease from these points. Finally, drone images captured before harvesting was used to generate spatial information on the incidence of rice blast disease in each field.

• Journal of Venture Innovation
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• v.5 no.2
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• pp.85-99
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• 2022

Dryers becoming commercially available for experimental and industrial use are classified to general drying oven, hot-air dryer, vacuum dryer, freezing dryer, etc. and kinds of them are various from the function, size and volume, etc. But the moisture measurement is not applied although it is important factor for the quality control and the performance improvement of products, and then now is very passive because the weight is weighed arbitrarily after dry-end. Generally the method for measuring moisture is divided by a direct measurement method and a indirect measurement method, and the former such as the change of weight or volume on the front and rear of separation of moisture, etc. is mainly used. Relatively a indirect measurement is very limited to apply due to utilize measurement apparatuses using temperature conductivity and micro-wave etc. In this research, we easily designed the moisture measurement system using the open-source based Arduino, and monitored moisture fluctuations and weight profiles in the real-time without the effect of external environment. Concretely the temperature-humidity and load cell sensors were packaged into a drying oven and the various change values were measured, and their sensors capable to operate 60℃ and 80℃ were selected to suitable for the moisture sensitive materials and the food dry. And also the performance safety using the organic samples of banana, pear, sawdust could be secured because the changes of evaporation rate as the dry time and temperature, and the measurement values of load cell appeared stable response characteristics through repeated experiments. Hereafter we judge that the reliability can be improved increasingly through the expansion of temperature-humidity range and the comparative analysis with CFD(Computational Fluid Dynamics) program.

• Journal of Mushroom
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• v.21 no.4
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• pp.266-269
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• 2023

This study aimed to address the increasing demand for technologies preventing mushroom fly damage. By monitoring the annual occurrence patterns of pests over several years and accumulating data, we conducted an analysis to evaluate the efficacy of preventive measures applied before the surge in mushroom fly infestation, typically observed in May. For preemptive control, physical measures involved installing air curtains at cultivation facility entrances and placing sticky traps and insect traps around entry points to block external entry and reduce internal insect density. Additionally, we applied an organic agricultural material, Dalmatian chrysanthemum extract, weekly alongside chemical control measures. To assess the reduction in mushroom fly populations, yellow sticky traps (15×25 cm) were placed at three locations within the mushroom cultivation facility, and the occurrence patterns before and after implementing preventive measures were compared. Compared to conventional practices, the application of preventive techniques resulted in a significant reduction, with a 60% decrease from 15 levels of mushroom flies/m² to 6 levels of mushroom flies/m² in May and a 40% decrease from 10 levels of mushroom flies/m² to 6 levels of mushroom flies/m² in June. While achieving over 50% efficacy during the peak mushroom fly season with preventive measures, we identified complementary actions such as blocking external sources (gaps in cultivation facility doors) and maintaining cleanliness around cultivation facilities (proper disposal of spent substrate) for further improvement. Comprehensive analysis and safety studies, including correlation analysis with contaminants and pathogens, are recommended to ensure the widespread adoption of mushroom fly preventive techniques for safe and stable mushroom production in the agricultural sector.

• Journal of Environmental Health Sciences
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• v.50 no.1
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• pp.16-24
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• 2024

Background: Indoor PM_2.5 concentrations in residential houses can be affected by various factors depending on the season. This is because not only do the climate characteristics depend on the season, but the activity patterns of occupants are also different. Objectives: The purpose of this study is to compare factors affecting indoor PM_2.5 concentrations in apartments and detached houses in Daegu according to seasonal changes. Methods: This study included 20 households in Daegu, South Korea. The study was conducted during the summer (from July 10 to August 10, 2023) and the autumn (from September 11 to October 9, 2023). A sensor-based instrument for PM_2.5 levels was installed in the living room of each residence, and measurements were taken continuously for 24 hours at intervals of one minute during the measurement period. Based on the air quality monitoring system data in Daegu, outdoor PM_2.5 concentrations were estimated using ordinary kriging (OK) in Python. In addition, the indoor activities of the occupants were investigated using a time-activity pattern diary. The affecting factors of indoor PM_2.5 concentration were analyzed using multiple regression analysis. Results: Indoor and outdoor PM_2.5 concentrations of the residences during summer were 15.27±11.09 ㎍/m³ and 11.52±7.56 ㎍/m³, respectively. Indoor and outdoor PM_2.5 concentrations during autumn were 13.82±9.61 ㎍/m³ and 9.57±5.50 ㎍/m³, respectively. The PM_2.5 concentrations were higher in summer compared to autumn both indoors and outdoors. The primary factor affecting indoor PM_2.5 concentration in summer was occupant activity. On the other hand, during the autumn season, the primary affecting factor was outdoor PM_2.5 concentration. Conclusions: Indoor PM_2.5 concentration in residential houses is affected by occupant activity such as the inflow of outdoor PM_2.5 concentration, cooking, and cleaning, as found in previous studies. However, it was revealed that there were differences depending on the season.

• Journal of Environmental Health Sciences
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• v.50 no.1
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• pp.6-15
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• 2024

Background: People's activities have been restricted due to the COVID-19 pandemic. These changes in activity patterns may lead to a decrease in fine particulate matter (PM_2.5) concentrations. Additionally, the level of population exposure to PM_2.5 may be changed. Objectives: This study aimed to analyze the impact of population movement and meteorological factors on the distribution of PM_2.5 concentrations before and after the outbreak of COVID-19. Methods: The study area was Guro-gu in Seoul. The research period was selected as January to March 2020, a period of significant population movement changes caused by COVID-19. The evaluation of the dynamic population was conducted by calculating the absolute difference in population numbers between consecutive hours and comparing them to determine the daily average. Ambient PM_2.5 concentrations were estimated for each grid using ordinary kriging in Python. For the population exposure assessment, the population-weighted average concentration was calculated by determining the indoor to outdoor population for each grid and applying the indoor to outdoor ratio to the ambient PM_2.5 concentration. To assess the factors influencing changes in the ambient PM_2.5 concentration, a statistical analysis was conducted, incorporating population mobility and meteorological factors. Results: Through statistical analysis, the correlation between ambient PM_2.5 concentration and population movement was positive on both weekends and weekdays (r=0.71, r=0.266). The results confirmed that most of the relationships were positive, suggesting that a decrease in human activity can lead to a decrease in PM_2.5 concentrations. In addition, when population-weighted concentration averages were calculated and the exposure level of the population group was compared before and after the COVID-19 outbreak, the proportion of people exceeding the air quality standard decreased by approximately 15.5%. Conclusions: Human activities can impact ambient concentrations of PM_2.5, potentially altering the levels of PM_2.5 exposure in the population.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.2
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• pp.1-15
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• 2002

Atmospheric aerosols interact with sunlight and affect the global radiation balance that can cause climate change through direct and indirect radiative forcing. Because of the spatial and temporal uncertainty of aerosols in atmosphere, aerosol characteristics are not considered through GCMs (General Circulation Model). Therefor it is important physical and optical characteristics should be evaluated to assess climate change and radiative effect by atmospheric aerosols. In this study GMS-5 satellite data and surface measurement data were analyzed using a radiative transfer model for the Yellow Sand event of April 7~8, 2000 in order to investigate the atmospheric radiative effects of Yellow Sand aerosols, MODTRAN3 simulation results enable to inform the relation between satellite channel albedo and aerosol optical thickness(AOT). From this relation AOT was retreived from GMS-5 visible channel. The variance observations of satellite images enable remote sensing of the Yellow Sand particles. Back trajectory analysis was performed to track the air mass from the Gobi desert passing through Korean peninsular with high AOT value measured by ground based measurement. The comparison GMS-5 AOT to ground measured RSR aerosol optical depth(AOD) show that for Yellow Sand aerosols, the albedo measured over ocean surfaces can be used to obtain the aerosol optical thickness using appropriate aerosol model within an error of about 10%. In addition, LIDAR network measurements and backward trajectory model showed characteristics and appearance of Yellow Sand during Yellow Sand events. These data will be good supporting for monitoring of Yellow Sand aerosols.

• Journal of Korean Society of Forest Science
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• v.83 no.4
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• pp.460-472
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• 1994

This study has been conducted to give some ideas for reasonable ecological management of Taejon city and its adjacent forest ecosystem against the effect of acid rain. Rain monitoring points to analyse its components represented 1 point in industrial area, 4 points in commercial area, 4 points in residential area, and 5 points in suburban area and forest survey was done in 7 forest sites adjacent to rain monitoring points. Transformed vegetation index(TVI) based on Landsat TM data was analysed for forest area. Taejon area was seriously contaminated by air pollutants and average concentration of anions in precipitation were 20.16mg/l for $SO_4{^{2-}}$, 3.65mg/l for $NO_3{^-}$, and 3.09mg/l for $Cl^-$. Anion in precipitation were $1.09mg/m^2/month$ for $SO_4{^{2-}}$, $0.23mg/m^2/month$ for $NO_3{^-}$, and $0.20mg/m^2/month$ for $Cl^-$. Cation in precipitation were $0.14mg/m^2/month$ for $Ca^{2+}$, $0.10mg/m^2/month$ for $NH_4{^+}$, $0.08mg/m^2/month$ for $Na^+$, $0.07mg/m^2/month$ for $K^+$, and $0.08mg/m^2/month$ for $Mg^{2+}$. The region with the highest concentration of $SO_4{^{2-}}$, $NO_3{^-}$, and $Cl^-$ in rain was industrial area. $SO_4{^{2-}}$, $NO_3{^-}$, and $Cl^-$ concentrations in industrial area were 43.08, 3.88, and 3.64ppm, respectively. Forest soil showed strongly acidic ranging pH4.16-4.94. Transformed vegetation index(TVI) were 3.11 in Dangsan, 4.00 in Kyechoksan, 4.13 in Bomunsan, 4.18 in Kabhasan, 3.34 in Bongsan, 4.13 in Sikchangsan, and 4.20 in Seongchisan. Dangsan forest located near in industrial area showed the lowest TVI.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1037-1051
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• 2020

The accurate monitoring and forecasting of the intensity of tropical cyclones (TCs) are able to effectively reduce the overall costs of disaster management. In this study, we proposed a multi-task learning (MTL) based deep learning model for real-time TC intensity estimation and forecasting with the lead time of 6-12 hours following the event, based on the fusion of geostationary satellite images and numerical forecast model output. A total of 142 TCs which developed in the Northwest Pacific from 2011 to 2016 were used in this study. The Communications system, the Ocean and Meteorological Satellite (COMS) Meteorological Imager (MI) data were used to extract the images of typhoons, and the Climate Forecast System version 2 (CFSv2) provided by the National Center of Environmental Prediction (NCEP) was employed to extract air and ocean forecasting data. This study suggested two schemes with different input variables to the MTL models. Scheme 1 used only satellite-based input data while scheme 2 used both satellite images and numerical forecast modeling. As a result of real-time TC intensity estimation, Both schemes exhibited similar performance. For TC intensity forecasting with the lead time of 6 and 12 hours, scheme 2 improved the performance by 13% and 16%, respectively, in terms of the root mean squared error (RMSE) when compared to scheme 1. Relative root mean squared errors(rRMSE) for most intensity levels were lessthan 30%. The lower mean absolute error (MAE) and RMSE were found for the lower intensity levels of TCs. In the test results of the typhoon HALONG in 2014, scheme 1 tended to overestimate the intensity by about 20 kts at the early development stage. Scheme 2 slightly reduced the error, resulting in an overestimation by about 5 kts. The MTL models reduced the computational cost about 300% when compared to the single-tasking model, which suggested the feasibility of the rapid production of TC intensity forecasts.