• Title/Summary/Keyword: Information Intensity

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Detection of Wildfire Smoke Plumes Using GEMS Images and Machine Learning (GEMS 영상과 기계학습을 이용한 산불 연기 탐지)

  • Jeong, Yemin;Kim, Seoyeon;Kim, Seung-Yeon;Yu, Jeong-Ah;Lee, Dong-Won;Lee, Yangwon
    • Korean Journal of Remote Sensing
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    • v.38 no.5_3
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    • pp.967-977
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    • 2022
  • The occurrence and intensity of wildfires are increasing with climate change. Emissions from forest fire smoke are recognized as one of the major causes affecting air quality and the greenhouse effect. The use of satellite product and machine learning is essential for detection of forest fire smoke. Until now, research on forest fire smoke detection has had difficulties due to difficulties in cloud identification and vague standards of boundaries. The purpose of this study is to detect forest fire smoke using Level 1 and Level 2 data of Geostationary Environment Monitoring Spectrometer (GEMS), a Korean environmental satellite sensor, and machine learning. In March 2022, the forest fire in Gangwon-do was selected as a case. Smoke pixel classification modeling was performed by producing wildfire smoke label images and inputting GEMS Level 1 and Level 2 data to the random forest model. In the trained model, the importance of input variables is Aerosol Optical Depth (AOD), 380 nm and 340 nm radiance difference, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), formaldehyde (HCHO), nitrogen dioxide (NO2), 380 nm radiance, and 340 nm radiance were shown in that order. In addition, in the estimation of the forest fire smoke probability (0 ≤ p ≤ 1) for 2,704 pixels, Mean Bias Error (MBE) is -0.002, Mean Absolute Error (MAE) is 0.026, Root Mean Square Error (RMSE) is 0.087, and Correlation Coefficient (CC) showed an accuracy of 0.981.

Comparison of Environment, Growth, and Management Performance of the Standard Cut Chrysanthemum 'Jinba' in Conventional and Smart Farms

  • Roh, Yong Seung;Yoo, Yong Kweon
    • Journal of People, Plants, and Environment
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    • v.23 no.6
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    • pp.655-665
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    • 2020
  • Background and objective: This study was conducted to compare the cultivation environment, growth of cut flowers, and management performance of conventional farms and smart farms growing the standard cut chrysanthemum, 'Jinba'. Methods: Conventional and smart farms were selected, and facility information, cultivation environment, cut flower growth, and management performance were investigated. Results: The conventional and smart farms were located in Muan, Jeollanam-do, and conventional farming involved cultivating with soil culture in a plastic greenhouse, while the smart farm was cultivating with hydroponics in a plastic greenhouse. The conventional farm did not have sensors for environmental measurement such as light intensity and temperature and pH and EC sensors for fertigation, and all systems, including roof window, side window, thermal screen, and shading curtain, were operated manually. On the other hand, the smart farm was equipped with sensors for measuring the environment and nutrient solution, and was automatically controlled. The day and night mean temperatures, relative humidity, and solar radiation in the facilities of the conventional and the smart farm were managed similarly. But in the floral differentiation stage, the floral differentiation was delayed, as the night temperature of conventional farm was managed as low as 17.7℃ which was lower than smart farm. Accordingly, the harvest of cut flowers by the conventional farm was delayed to 35 days later than that of the smart farm. Also, soil moisture and EC of the conventional farm were unnecessarily kept higher than those of the smart farm in the early growth stage, and then were maintained relatively low during the period after floral differentiation, when a lot of water and nutrients were required. Therefore, growth of cut flower, cut flower length, number of leaves, flower diameter, and weight were poorer in the conventional farm than in the smart farm. In terms of management performance, yield and sales price were 10% and 38% higher for the smart farm than for the conventional farm, respectively. Also, the net income was 2,298 thousand won more for the smart farm than for the conventional farm. Conclusion: It was suggested that the improved growth of cut flowers and high management performance of the smart farm were due to precise environment management for growth by the automatic control and sensor.

Mountain Meteorology Data for Forest Disaster Prevention and Forest Management (산림재해 방지와 산림관리를 위한 산악기상정보)

  • Keunchang, Jang;Sunghyun, Min;Inhye, Kim;Junghwa, Chun;Myoungsoo, Won
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.24 no.4
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    • pp.346-352
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    • 2022
  • Mountain meteorology in South Korea that is covered mountains with complex terrain is important for understanding and managing the forest disaster and forest ecosystems. In particular, recent changes in dryness and/or rainfall intensity due to climate change may cause an increase in the possibility of forest disasters. Therefore, accurate monitoring of mountain meteorology is needed for efficient forest management. Korea Forest Service (KFS) is establishing the Automatic Mountain Meteorology Observation Stations (AMOS) in the mountain regions since 2012. 464 AMOSs are observing various meteorological variables such as air temperature, relative humidity, wind speed and direction, precipitation, soil temperature, and air pressure for every minute, which is conducted the quality control (QC) to retain data reliability. QC process includes the physical limit test, step test, internal consistency test, persistence test, climate range test, and median filter test. All of AMOS observations are open to use, which can be found from the Korean Mountain Meteorology Information System (KoMIS, http://mtweather.nifos.go.kr/) of the National Institute of Forest Science and the Public Data Portal (https://public.go.kr/). AMOS observations with guaranteed quality can be used in various forest fields including the public safety, forest recreation, forest leisure activities, etc., and can contribute to the advancement of forest science and technology. In this paper, a series of processes are introduced to collect and use the AMOS dataset in the mountain region in South Korea.

Nature of the Interfacial Regions in the Antiferromagnetically-coupled Fe/Si Multilayered Films

  • Moon, J.C.;Y.V. Kudryavtsev;J.Y.Rhee;Kim, K.W.;Lee, Y.P.
    • Proceedings of the Korean Vacuum Society Conference
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    • 2000.02a
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    • pp.174-174
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    • 2000
  • A strong antiferromagnetic coupling in Fe/Si multilayered films (MLF) had been recently discovered and much consideration has been given to whether the coupling in the Fe/Si MLF system has the same origin as the metal/metal MLF. Nevertheless, the nature of the interfacial ron silicide is still controversial. On one hand, a metal/ semiconductor structure was suggested with a narrow band-gap semiconducting $\varepsilon$-FeSi spacer that mediates the coupling. However, some features show that the nature of coupling can be well understood in terms of the conventional metal/metal multilayered system. It is well known that both magneto-optical (MO) and optical properties of a metal depend strongly on their electronic structure that is also correlated with the atomic and chemical ordering. In this study, the nature of the interfacial regions is the Fe/Si multilayers has been investigated by the experimental and computer-simulated MO and optical spectroscopies. The Fe/Si MLF were prepared by rf-sputtering onto glass substrates at room temperature with the number of repetition N=50. The thickness of Fe sublayer was fixed at 3.0nm while the Si sublayer thickness was varied from 1.0 to 2.0 nm. The topmost layer of all the Fe/Si MLF is Fe. In order to carry out the computer simulations, the information on the MO and optical parameters of the materials that may constitute a real multilayered structure should be known in advance. For this purpose, we also prepared Fe, Si, FeSi2 and FeSi samples. The structural characterization of Fe/Si MLF was performed by low- and high -angle x-ray diffraction with a Cu-K$\alpha$ radiation and by transmission electron microscopy. A bulk $\varepsilon$-FeSi was also investigated. The MO and optical properties were measured at room temperature in the 1.0-4.7 eV energy range. The theoretical simulations of MO and optical properties for the Fe/Si MLF were performed by solving exactly a multireflection problem using the scattering matrix approach assuming various stoichiometries of a nonmagnetic spacer separating the antiferromagnetically coupled Fe layers. The simulated spectra of a model structure of FeSi2 or $\varepsilon$-FeSi as the spacer turned out to fail in explaining the experimental spectra of the Fe/Si MLF in both intensity and shape. Thus, the decisive disagreement between experimental and simulated MO and optical properties ruled out the hypothesis of FeSi2 and $\varepsilon$-FeSi as the nonmagnetic spacer. By supposing the spontaneous formation of a metallic ζ-FeSi, a reasonable agreement between experimental and simulated MO and optical spectra was obtained.

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An Improvement Study on the Hydrological Quantitative Precipitation Forecast (HQPF) for Rainfall Impact Forecasting (호우 영향예보를 위한 수문학적 정량강우예측(HQPF) 개선 연구)

  • Yoon Hu Shin;Sung Min Kim;Yong Keun Jee;Young-Mi Lee;Byung-Sik Kim
    • Journal of Korean Society of Disaster and Security
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    • v.15 no.4
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    • pp.87-98
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    • 2022
  • In recent years, frequent localized heavy rainfalls, which have a lot of rainfall in a short period of time, have been increasingly causing flooding damages. To prevent damage caused by localized heavy rainfalls, Hydrological Quantitative Precipitation Forecast (HQPF) was developed using the Local ENsemble prediction System (LENS) provided by the Korea Meteorological Administration (KMA) and Machine Learning and Probability Matching (PM) techniques using Digital forecast data. HQPF is produced as information on the impact of heavy rainfall to prepare for flooding damage caused by localized heavy rainfalls, but there is a tendency to overestimate the low rainfall intensity. In this study, we improved HQPF by expanding the period of machine learning data, analyzing ensemble techniques, and changing the process of Probability Matching (PM) techniques to improve predictive accuracy and over-predictive propensity of HQPF. In order to evaluate the predictive performance of the improved HQPF, we performed the predictive performance verification on heavy rainfall cases caused by the Changma front from August 27, 2021 to September 3, 2021. We found that the improved HQPF showed a significantly improved prediction accuracy for rainfall below 10 mm, as well as the over-prediction tendency, such as predicting the likelihood of occurrence and rainfall area similar to observation.

Changes in Stock Market Co-movements between Contracting Parties after the Trade Agreement and Their Implications

  • So-Young Ahn;Yeon-Ho Bae
    • Journal of Korea Trade
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    • v.27 no.1
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    • pp.139-158
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    • 2023
  • Purpose - The study of co-movements between stock markets is a crucial area of finance and has recently received much interest in a variety of studies, especially in international finance. Stock market co-movements are a major phenomenon in financial markets, but they are not necessarily independent of the real market. Several studies support the idea that bilateral trade linkages significantly impact stock market correlations. Motivated by this perspective, this study investigates whether real market integration due to trade agreements brings about financial market integration in terms of stock market co-movement. Design/methodology - Over the 10 free trade agreements (FTAs) signed by the United States, using a dynamic conditional correlations (DCC) multivariate GARCH (MGRACH) model, we empirically measure the degree of integration by finding DCCs between the US market and the partner country's market. We then track how these correlations evolve over time and compare the results before and after trade agreements. Findings - According to the empirical results, there are positive return spillover effects from the US market to eight counterpart equity markets, except Jordan, Morocco, and Singapore. Especially Mexico, Canada, and Chile have large return spillover effects at the 1% significance level. All partner countries of FTAs generally have positive correlations with the US over the entire period, but the size and variance are somewhat different by country. Meanwhile, not all countries that signed trade agreements with the United States showed the same pattern of stock market co-movement after the agreement. Korea, Mexico, Chile, Colombia, Peru, and Singapore show increasing DCC patterns after trade agreements with the US. However, Canada, Australia, Bahrain, Jordan, and Morocco do not show different patterns before and after trade agreements in DCCs. These countries generally have the characteristic of relatively lower or higher co-movements in stock markets with the US before the signing of the FTAs. Originality/value - To our knowledge, few studies have directly examined the linkages between trade agreements and stock markets. Our approach is novel as it considers the problem of conditional heteroscedasticity and visualizes the change of correlations with time variations. Moreover, analyzing several trade agreements based on the United States enables the results of cross-country pairs to be compared. Hence, this study provides information on the degree of stock market integration with countries with which the United States has trade agreements, while simultaneously allowing us to track whether there have been changes in stock market integration patterns before and after trade agreements.

Feasibility of Single-Shot Whole Thoracic Time-Resolved MR Angiography to Evaluate Patients with Multiple Pulmonary Arteriovenous Malformations

  • Jihoon Hong;Sang Yub Lee;Jae-Kwang Lim;Jongmin Lee;Jongmin Park;Jung Guen Cha;Hui Joong Lee;Donghyeon Kim
    • Korean Journal of Radiology
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    • v.23 no.8
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    • pp.794-802
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    • 2022
  • Objective: To evaluate the feasibility of single-shot whole thoracic time-resolved MR angiography (TR-MRA) to identify the feeding arteries of pulmonary arteriovenous malformations (PAVMs) and reperfusion of the lesion after embolization in patients with multiple PAVMs. Materials and Methods: Nine patients (8 females and 1 male; age range, 23-65 years) with a total of 62 PAVMs who underwent percutaneous embolization for multiple PAVMs and were subsequently followed up using TR-MRA and CT obtained within 6 months from each other were retrospectively reviewed. All imaging analyses were performed by two independent readers blinded to clinical information. The visibility of the feeding arteries on maximum intensity projection (MIP) reconstruction and multiplanar reconstruction (MPR) TR-MRA images was evaluated by comparing them to CT as a reference. The accuracy of TR-MRA for diagnosing reperfusion of the PAVM after embolization was assessed in a subgroup with angiographic confirmation. The reliability between the readers in interpreting the TR-MRA results was analyzed using kappa (κ) statistics. Results: Feeding arteries were visible on the original MIP images of TR-MRA in 82.3% (51/62) and 85.5% (53/62) of readers 1 and 2, respectively. Using the MPR, the rates increased to 93.5% (58/62) and 95.2% (59/62), respectively (κ = 0.760 and 0.792, respectively). Factors for invisibility were the course of feeding arteries in the anteroposterior plane, proximity to large enhancing vessels, adjacency to the chest wall, pulsation of the heart, and small feeding arteries. Thirty-seven PAVMs in five patients had angiographic confirmation of reperfusion status after embolization (32 occlusions and 5 reperfusions). TR-MRA showed 100% (5/5) sensitivity and 100% (32/32, including three cases in which the feeding arteries were not visible on TR-MRA) specificity for both readers. Conclusion: Single-shot whole thoracic TR-MRA with MPR showed good visibility of the feeding arteries of PAVMs and high accuracy in diagnosing reperfusion after embolization. Single-shot whole thoracic TR-MRA may be a feasible method for the follow-up of patients with multiple PAVMs.

A novel method for determining dose distribution on panoramic reconstruction computed tomography images from radiotherapy computed tomography

  • Hiroyuki Okamoto;Madoka Sakuramachi;Wakako Yatsuoka;Takao Ueno;Kouji Katsura;Naoya Murakami;Satoshi Nakamura;Kotaro Iijima;Takahito Chiba;Hiroki Nakayama;Yasunori Shuto;Yuki Takano;Yuta Kobayashi;Hironori Kishida;Yuka Urago;Masato Nishitani;Shuka Nishina;Koushin Arai;Hiroshi Igaki
    • Imaging Science in Dentistry
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    • v.54 no.2
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    • pp.129-137
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    • 2024
  • Purpose: Patients with head and neck cancer (HNC) who undergo dental procedures during radiotherapy (RT) face an increased risk of developing osteoradionecrosis (ORN). Accordingly, new tools must be developed to extract critical information regarding the dose delivered to the teeth and mandible. This article proposes a novel approach for visualizing 3-dimensional planned dose distributions on panoramic reconstruction computed tomography (pCT) images. Materials and Methods: Four patients with HNC who underwent volumetric modulated arc therapy were included. One patient experienced ORN and required the extraction of teeth after RT. In the study approach, the dental arch curve (DAC) was defined using an open-source platform. Subsequently, pCT images and dose distributions were generated based on the new coordinate system. All teeth and mandibles were delineated on both the original CT and pCT images. To evaluate the consistency of dose metrics, the Mann-Whitney U test and Student t-test were employed. Results: A total of 61 teeth and 4 mandibles were evaluated. The correlation coefficient between the 2 methods was 0.999, and no statistically significant difference was observed (P>0.05). This method facilitated a straightforward and intuitive understanding of the delivered dose. In 1 patient, ORN corresponded to the region of the root and the gum receiving a high dosage (approximately 70 Gy). Conclusion: The proposed method particularly benefits dentists involved in the management of patients with HNC. It enables the visualization of a 3-dimensional dose distribution in the teeth and mandible on pCT, enhancing the understanding of the dose delivered during RT.

The effect of R&D investment in Chinese private firms on firm performance and value: The moderating effect of ESG score (중국 민영기업의 R&D 투자가 경영성과와 기업가치에 미치는 영향: ESG 성과지수의 조절효과)

  • Youngsoo Park
    • Analyses & Alternatives
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    • v.8 no.2
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    • pp.87-115
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    • 2024
  • This study examines the effect of R&D investment on firm performance and value of Chinese private firms. Through R&D investment, firms aim to acquire knowledge and technological resources to create innovation and competitive advantage, which ultimately enhances firm performance and value. However, unlike other investments, R&D investments are characterized by high adjustment costs and risks, uncertainty and asymmetric information. In addition, the effect of R&D investment on firm performance and value has been shown to be mixed results due to various internal and external contextual factors. Therefore, this study intends to consider how the ESG activities of firms, which have recently attracted attention, act as a contextual factor in the results of R&D investment. This is because interaction with stakeholders through ESG activities is considered to be an important factor in securing competitive advantages and sustainable growth. In this context, this study measures the effect of a firm's R&D investment on its business performance by dividing it into financial performance and value, respectively, and examines the moderating effect of ESG score on the relationship. Based on empirical analysis of all Chinese private firms from 2010 to 2019, the results show that a firm's R&D investment has a negative impact on performance and a positive impact on value. Furthermore, a high ESG score of private firms positively moderates each relationship, emphasizing the importance of ESG activities.

Analysis of Parameter Optimization Reflecting the Characteristics of Runoff in Small Mountain Catchment (소규모 산지 유역의 유출특성을 반영한 매개변수 최적화 분석)

  • Joungsung Lim;Hojin Lee
    • Journal of the Korean GEO-environmental Society
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    • v.25 no.9
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    • pp.5-14
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    • 2024
  • In Korea, torrential rain frequency and intensity have surged over the past five years (2019-2023), breaking rainfall records. Due to insufficient observation facilities for rainfall and runoff data in small mountainous catchments, preparing for unexpected floods is challenging. This study examines the Bidogyo catchment in Goesan-gun, Chungcheongbuk-do, comparing design flood discharge calculated with optimized parameters versus standard guidelines. Using HEC-HMS and Q-GIS for model construction, five rainfall events were analyzed with data from the National Water Resources Management Information System. The time of concentration (Tc) and storage constant (K) were calculated using the Seokyeongdae formula and model optimization. Results showed that optimized parameters produced higher objective function values for flood events. The design flood discharge varied by -10.7% to 17.3% from the standard guidelines when using optimized parameters. Moreover, optimized parameters yielded flood discharges closer to observed values, highlighting limitations of the Seokyeongdae formula for all catchments. Further research aims to develop suitable parameter estimation methods for small mountainous catchments in Korea.