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Effect of Accelerated Storage on the Microstructure and Water Absorption Characteristics of Korean Adzuki Bean (Vigna angularis L.) Cultivar (팥의 가속화 저장에 따른 미세구조 및 수분흡수 특성)

  • Jieun Kwak;Seon-Min Oh;You-Geun Oh;Yu-Chan Choi;Hyun-Jin Park;Suk-Bo Song;Jeong-Heui Lee;Jeom-Sig Lee
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.68 no.3
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    • pp.167-174
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    • 2023
  • This study investigated the microstructure and water absorption characteristics of the Korean adzuki bean (Vigna angularis L.) cultivar under accelerated storage. The germination rate, acid value, redness (a*), and yellowness (b*) values showed no significant differences after three months of storage compared to pre-storage under low temperatures (4℃). However, a statistically significant difference was observed under accelerated high temperatures (45℃). In particular, after storage for three months, the germination rate and acid value were 0% and 33.63 mg KOH/100g, respectively, under accelerated high temperatures. After storage for three months, the holes, hilum damage, and spaces between the seed coat and cotyledon shortened the time and speed of water absorption under accelerated high temperatures compared to that under low temperatures. Conversely, further research is required to investigate the reason for the low rate of parallel water absorption.

Derivation of Inherent Optical Properties Based on Deep Neural Network (심층신경망 기반의 해수 고유광특성 도출)

  • Hyeong-Tak Lee;Hey-Min Choi;Min-Kyu Kim;Suk Yoon;Kwang-Seok Kim;Jeong-Eon Moon;Hee-Jeong Han;Young-Je Park
    • Korean Journal of Remote Sensing
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    • v.39 no.5_1
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    • pp.695-713
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    • 2023
  • In coastal waters, phytoplankton,suspended particulate matter, and dissolved organic matter intricately and nonlinearly alter the reflectivity of seawater. Neural network technology, which has been rapidly advancing recently, offers the advantage of effectively representing complex nonlinear relationships. In previous studies, a three-stage neural network was constructed to extract the inherent optical properties of each component. However, this study proposes an algorithm that directly employs a deep neural network. The dataset used in this study consists of synthetic data provided by the International Ocean Color Coordination Group, with the input data comprising above-surface remote-sensing reflectance at nine different wavelengths. We derived inherent optical properties using this dataset based on a deep neural network. To evaluate performance, we compared it with a quasi-analytical algorithm and analyzed the impact of log transformation on the performance of the deep neural network algorithm in relation to data distribution. As a result, we found that the deep neural network algorithm accurately estimated the inherent optical properties except for the absorption coefficient of suspended particulate matter (R2 greater than or equal to 0.9) and successfully separated the sum of the absorption coefficient of suspended particulate matter and dissolved organic matter into the absorption coefficient of suspended particulate matter and dissolved organic matter, respectively. We also observed that the algorithm, when directly applied without log transformation of the data, showed little difference in performance. To effectively apply the findings of this study to ocean color data processing, further research is needed to perform learning using field data and additional datasets from various marine regions, compare and analyze empirical and semi-analytical methods, and appropriately assess the strengths and weaknesses of each algorithm.

Evaluation of the Effects of Hangover-Releasing Agent Containing Vinegar Extract in Common Buckwheat and Tartary Buckwheat on Alcohol Metabolism and Hangover Improvement (일반메밀과 쓴메밀의 식초 추출물의 알코올 대사 및 숙취개선 효능 평가)

  • Su Jeong Kim;Hwang Bae Sohn;A Hyun Park;Jong Nam Lee;Su Hyoung Park;Jung Hwan Nam;Do Yeon Kim;Dong Chil Chang;Yul Ho Kim
    • Korean Journal of Plant Resources
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    • v.36 no.5
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    • pp.435-445
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    • 2023
  • The aim of this study was to explore the effects of vinegar extract from seed of common buckwheat (Fagopyrum esculentum Moench) and seed of tartary buckwheat (F. tataricum Gaertner) on acute ethanol-induced hangover in Sprague-Dawley rats. Vinegar extract from buckwheat is rich choline, quercetin and its glycoside, rutin known as flavonoid antioxidants. The test extract containing buckwheat was proven to alleviate hangovers through a significant reduction in the concentration of alcohol and acetaldehyde in the context of an alcohol-induced hangover model. Hepatic alcohol dehydrogenase (ADH) and acetaldehyde dehydrogenase (ALDH) activities were significantly higher in buckwheat vinegar-treated rats than in ethanol-treated rats. Moreover, tartary buckwheat vinegar upregulated antioxidant enzyme such as superoxide dismutase and Catalase activities in liver tissues. These results suggest that buckwheat vinegar extract could alleviate ethanol-induced hangover symptoms by elevating activities related to hepatic ethanol-metabolizing enzymes against ethanol induced metabolites, and in particular, tartary buckwheat should be further developed to be a novel anti-hangover material.

Development of Cloud Detection Method Considering Radiometric Characteristics of Satellite Imagery (위성영상의 방사적 특성을 고려한 구름 탐지 방법 개발)

  • Won-Woo Seo;Hongki Kang;Wansang Yoon;Pyung-Chae Lim;Sooahm Rhee;Taejung Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1211-1224
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    • 2023
  • Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.

How Did the COVID-19 Pandemic Affect Mobility, Land Use, and Destination Selection? Lesson from Seoul, Korea

  • Lee, Jiwon;Gim, Tae-Hyoung Tommy;Park, Yunmi;Chung, Hyung-Chul;Handayani, Wiwandari;Lee, Hee-Chung;Yoon, Dong Keun;Pai, Jen Te
    • Land and Housing Review
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    • v.14 no.4
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    • pp.77-93
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    • 2023
  • The COVID-19 pandemic has brought about significant social changes through government prevention and control measures, changes in people's risk perceptions, and lifestyle changes. In response, urban inhabitants changed their behaviors significantly, including their preferences for transportation modes and urban spaces in response to government quarantine policies and concerns over the potential risk of infection in urban spaces. These changes may have long-lasting effects on urban spaces beyond the COVID-19 pandemic or they may evolve and develop new forms. Therefore, this study aims to explore the potential for urban spaces to adapt to the present and future pandemics by examining changes in urban residents' preferences in travel modes and urban space use due to the COVID-19 pandemic. This study found that overall preferences for travel modes and urban spaces significantly differ between the pre-pandemic, pandemic, and post-pandemic periods. During the pandemic, preferences for travel modes and urban spaces has decreased, except for privately owned vehicles and green spaces, which are perceived to be safe from transmission, show more favorable than others. Post-pandemic preferences for travel modes and urban spaces are less favorable than pre-pandemic with urban spaces being five times less favorable than transportation. Although green spaces and medical facilities that were positively perceived during the pandemic are expected to return to the pre-pandemic preference level, other factors of urban spaces are facing a new-normal. The findings suggest that the COVID-19 pandemic has had a significant impact on urban residents' preferences for travel modes and urban space use. Understanding these changes is crucial for developing strategies to adapt to present and future pandemics and improve urban resilience.

The Effect of Interest Rate Variability on Housing Prices (이자율 변동이 주택가격에 미치는 영향)

  • Han, Myung-hoon
    • Journal of Venture Innovation
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    • v.5 no.3
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    • pp.71-80
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    • 2022
  • The real estate market is an important part of a country's economy and plays a major role in economic growth through the growth of many related industries. Changes in interest rates affect asset prices and have a significant impact on housing prices. This study analyzed housing prices by dividing them into nationwide, local, and Seoul housing prices in order to analyze whether the effect of changes in interest rates on housing prices shows regional differences. The analysis was conducted from the first quarter of 2011 to the fourth quarter of 2021, and was analyzed using the DOLS model. The main analysis results are as follows. First, interest rates were found to have a significant negative effect on national housing prices, and a drop in interest rates significantly increased national housing prices and an increase in interest rates significantly lowered national housing prices. The consumer price index and loan growth rate also had a positive effect on housing prices nationwide, but statistical significance was not high. Second, interest rates had a negative effect on local housing prices, unlike national housing prices, but were not statistically significant. On the other hand, it was found that the consumer price index and loan growth rate had a larger and significant positive effect on local housing prices compared to national housing prices. Finally, it was found that the interest rate had the only significant negative effect on housing prices in Seoul. And this effect was greater and more significant than the effect on national and local housing prices. In the end, it was found that the effect of interest rates on Korean housing prices differs locally. Interest rates have a significant negative effect on national housing prices, and local housing prices, but they are not statistically significant. In addition, the interest rate was found to have the largest and most significant negative effect on housing prices in Seoul. In addition, it was found that there was a difference in the effect of macroeconomic variables on housing prices. This means that there are differences between regions with different factors influencing local and Seoul housing prices, and this point should be considered when drafting and implementing real estate policies.

Retrieval of Hourly Aerosol Optical Depth Using Top-of-Atmosphere Reflectance from GOCI-II and Machine Learning over South Korea (GOCI-II 대기상한 반사도와 기계학습을 이용한 남한 지역 시간별 에어로졸 광학 두께 산출)

  • Seyoung Yang;Hyunyoung Choi;Jungho Im
    • Korean Journal of Remote Sensing
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    • v.39 no.5_3
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    • pp.933-948
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    • 2023
  • Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R2=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.

Convergence of Remote Sensing and Digital Geospatial Information for Monitoring Unmeasured Reservoirs (미계측 저수지 수체 모니터링을 위한 원격탐사 및 디지털 공간정보 융합)

  • Hee-Jin Lee;Chanyang Sur;Jeongho Cho;Won-Ho Nam
    • Korean Journal of Remote Sensing
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    • v.39 no.5_4
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    • pp.1135-1144
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    • 2023
  • Many agricultural reservoirs in South Korea, constructed before 1970, have become aging facilities. The majority of small-scale reservoirs lack measurement systems to ascertain basic specifications and water levels, classifying them as unmeasured reservoirs. Furthermore, continuous sedimentation within the reservoirs and industrial development-induced water quality deterioration lead to reduced water supply capacity and changes in reservoir morphology. This study utilized Light Detection And Ranging (LiDAR) sensors, which provide elevation information and allow for the characterization of surface features, to construct high-resolution Digital Surface Model (DSM) and Digital Elevation Model (DEM) data of reservoir facilities. Additionally, bathymetric measurements based on multibeam echosounders were conducted to propose an updated approach for determining reservoir capacity. Drone-based LiDAR was employed to generate DSM and DEM data with a spatial resolution of 50 cm, enabling the display of elevations of hydraulic structures, such as embankments, spillways, and intake channels. Furthermore, using drone-based hyperspectral imagery, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were calculated to detect water bodies and verify differences from existing reservoir boundaries. The constructed high-resolution DEM data were integrated with bathymetric measurements to create underwater contour maps, which were used to generate a Triangulated Irregular Network (TIN). The TIN was utilized to calculate the inundation area and volume of the reservoir, yielding results highly consistent with basic specifications. Considering areas that were not surveyed due to underwater vegetation, it is anticipated that this data will be valuable for future updates of reservoir capacity information.

Attenuation of Oxidative Stress-Induced HepG2 Cellular Damage by Cirsiumjaponicum Root Extract (HepG2 세포에서 대계 추출물에 의한 산화적 스트레스 유발 세포 손상의 억제)

  • Da Jung Ha;Seohwi Kim;Byunwoo Son;Myungho Jin;Sungwoo Cho;Sang Hoon Hong;Yung Hyun Choi;Sang Eun Park
    • Journal of Life Science
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    • v.33 no.12
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    • pp.1002-1014
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    • 2023
  • The root of Cirsium japonicum var. maackii (Maxim.) has long been used in traditional medicine to prevent the onset and progression of various diseases and has been reported to exert a wide range of physiological effects, including antioxidant activity. However, research on its effects on hepatocytes remains scarce. This study used the human hepatocellular carcinoma HepG2 cell line to investigate the antioxidant activity of ethanol extract of C. japonicum root (EECJ) on hepatocytes. Hydrogen peroxide (H2O2) was used to mimic oxidative stress. The results showed that EECJ significantly reverted the decrease in cell viability and suppressed the release of lactate dehydrogenase in HepG2 cells treated with H2O2. Moreover, an analysis of changes in cell morphology, flow cytometry, and microtubule-associated protein light chain 3 (LC3) expression showed that EECJ significantly inhibited HepG2 cell autophagy induced by H2O2. Furthermore, it attenuated H2O2-induced apoptosis and cell cycle disruption by blocking intracellular reactive oxygen species and mitochondrial superoxide production, indicating strong antioxidant activity. EECJ also restored the decreased levels of intracellular glutathione (GSH) and enhanced the expression and activity of superoxide dismutase and GSH peroxidase in H2O2-treated HepG2 cells. Although an analysis of the components contained in EECJ and in vivo validation using animal models are needed, these findings indicate that EECJ is a promising candidate for the prevention and treatment of oxidative stress-induced liver cell damage.

Comparison of Spodoptera frugiperda Control Effects for Corn According to the Control Thresholds and Chemical Spraying Methods (열대거세미나방에 대한 옥수수의 요방제 수준 및 약제 살포방법에 따른 방제 효과 비교)

  • You Kyoung Lee;Hyun Ju Kim;Nak Jung Choi;Bo Yoon Seo;June Yeol Choi
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.25 no.3
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    • pp.142-150
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    • 2023
  • As global warming continues, the time of invasion of Spodoptera frugiperda has been advanced and the inflow rate has been increasing, leading to great increases in damage to crops. In this study, in order to minimize crop damage caused by S. frugiperda, the control period was set for corn fields through control thresholds, and the control effects according to the chemical spraying methods were investigated in forage corn filed. Even under the condition of 4% injury level during the corn silking stage, the damage rate of ear was 70%, showing an aspect of extensive damage. The economic injury level of S. frugiperda second instar larvae was shown to be 0.7 larvae per stalk, and the control threshold level was shown to be 0.6 larvae. The income was calculated by applying the corn wholesale unit price, and according to the result, even under the condition of injury level of 4%, there was a loss of KRW 895,221/10a, and the higher the injury level, the greater the decrease in income. To control S. frugiperda, the insecticidal effects of 10 single formulations registered for S. frugiperda were tested, and according to the results, four types(emamectin benzoate, chlorantraniliprole, indoxacarb, and spinetoram) showed high insecticidal activity not lower than 93.3%, and three types (chloran- traniliprole, spinetoram, and indoxacarb) were considered to be effective in controlling S. frugiperda as they showed high residual effects through insecticidal effect persistence tests. Therefore, conventional control and aerial control were conducted twice at 7-day intervals with indoxacarb SC and chlorantraniliprol WP, which show high activity against S. frugiperda, respectively, prior to the silking of forage corn. As a result, conventional control showed higher control values, 46.3%p in the case of indoxacarb SC and 21.7%p in the case of chlorantraniliprol WP, than aerial control through the primary control. In the secondary control too, higher control values of 26.7%p in the case of indoxacarb SC and 40.4%p in the case of chlorantraniliprol WP were found in conventional control than in aerial control. Therefore, it is considered necessary to prepare measures to improve the control effects in the recent situation where alternative methods for manpower control are widely used.