• 인간식물환경학회지
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• 제24권2호
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• pp.219-227
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• 2021

Background and objective: Urban street trees play an important role in carbon reduction in cities where greenspace is scarce. There are ongoing studies on carbon reduction by street trees. However, information on the carbon reduction capacity of street trees based on field surveys is still limited. This study aimed to quantify carbon uptake and storage by urban street trees and suggest a method to improve planting of trees in order to increase their carbon reduction capacity. Methods: The cities selected were Sejong, Chungju, and Jeonju among cities without research on carbon reduction, considering the regional distribution in Korea. In the cities, 155 sample sites were selected using systematic sampling to conduct a field survey on street environments and planting structures. The surveyed data included tree species, diameter at breast height (DBH), diameter at root collar (DRC), height, crown width, and vertical structures. The carbon uptake and storage per tree were calculated using the quantification models developed for the urban trees of each species. Results: The average carbon uptake and storage of street trees were approximately 7.2 ± 0.6 kg/tree/yr and 87.1 ± 10.2 kg/tree, respectively. The key factors determining carbon uptake and storage were tree size, vertical structure, the composition of tree species, and growth conditions. The annual total carbon uptake and storage were approximately 1,135.8 tons and 22,737.8 tons, respectively. The total carbon uptake was about the same amount as carbon emitted by 2,272 vehicles a year. Conclusion: This study has significance in providing the basic unit to quantify carbon uptake and storage of street trees based on field surveys. To improve the carbon reduction capacity of street trees, it is necessary to consider planning strategies such as securing and extending available grounds and spaces for high-density street trees with a multi-layered structure.

• 한국농공학회논문집
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• 제64권6호
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• pp.55-63
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• 2022

Odors emitted from pig houses have been a constant root of legal issues in pig farming. These gases are among the main causes of health and mental stresses to nearby communities, so policymakers and researchers continuously study to reduce the concentration of odorous gases from pig facilities. A continuous field experiment proved that the concentration of odor emissions inside the pig houses is highly dependent on ventilation rate, breeding details, and animal activities. However, the standard odor emission rate worldwide widely varies due to differences in pig house designs and ventilation requirements. Thus, this study aimed to measure the odor emission rates, considering the actual condition of selected Korean pig houses, through field measurement. The odor measurements were performed at three different pig production facilities without odor abatement technologies. The target experimental pig houses were buildings for weaning, growing, and fattening pigs. Results showed that the actual ventilation rate in target pig houses falls below the standard ventilation requirement of pigs, resulting in high odor concentrations inside the pig houses.

• Geomechanics and Engineering
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• 제31권6호
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• pp.545-556
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• 2022

Evaluation and optimization of tunnel wall convergence (TWC) plays a vital role in preventing potential problems during tunnel construction and utilization stage. When convergence occurs at a high rate, it can lead to significant problems such as reducing the advance rate and safety, which in turn increases operating costs. In order to design an effective solution, it is important to accurately predict the degree of TWC; this can reduce the level of concern and have a positive effect on the design. With the development of soft computing methods, the use of deep learning algorithms and neural networks in tunnel construction has expanded in recent years. The current study aims to employ the long-short-term memory (LSTM) deep neural network predictor model to predict the TWC, based on 550 data points of observed parameters developed by collecting required data from different tunnelling projects. Among the data collected during the pre-construction and construction phases of the project, 80% is randomly used to train the model and the rest is used to test the model. Several loss functions including root mean square error (RMSE) and coefficient of determination (R²) were used to assess the performance and precision of the applied method. The results of the proposed models indicate an acceptable and reliable accuracy. In fact, the results show that the predicted values are in good agreement with the observed actual data. The proposed model can be considered for use in similar ground and tunneling conditions. It is important to note that this work has the potential to reduce the tunneling uncertainties significantly and make deep learning a valuable tool for planning tunnels.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.141-141
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• 2022

Drought is a global phenomenon that affects almost all landscapes and causes major damages. Due to non-linear nature of contributing factors, drought occurrence and its severity is characterized as stochastic in nature. Early warning of impending drought can aid in the development of drought mitigation strategies and measures. Thus, drought forecasting is crucial in the planning and management of water resource systems. The primary objective of this study is to make improvement is existing drought forecasting techniques. Therefore, we proposed an improved version of Seasonal Autoregressive Integrated Moving Average (SARIMA) model (MD-SARIMA) for reliable drought forecasting with three years lead time. In this study, we selected four watersheds of Han River basin in South Korea to validate the performance of MD-SARIMA model. The meteorological data from 8 rain gauge stations were collected for the period 1973-2016 and converted into watershed scale using Thiessen's polygon method. The Standardized Precipitation Index (SPI) was employed to represent the meteorological drought at seasonal (3-month) time scale. The performance of MD-SARIMA model was compared with existing models such as Seasonal Naive Bayes (SNB) model, Exponential Smoothing (ES) model, Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend and Seasonal components (TBATS) model, and SARIMA model. The results showed that all the models were able to forecast drought, but the performance of MD-SARIMA was robust then other statistical models with Wilmott Index (WI) = 0.86, Mean Absolute Error (MAE) = 0.66, and Root mean square error (RMSE) = 0.80 for 36 months lead time forecast. The outcomes of this study indicated that the MD-SARIMA model can be utilized for drought forecasting.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.289-289
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• 2022

Waterlogging tolerance of corn is one of the important factor for cultivate in paddy soil condition to increase cultivation area and self-sufficiency of corn in Korea. In order to develop elite waterlogging tolerance corn, the new corn lines bred by crossing wild corn, Teosinte, and cultivated corn inbred lines. Five accessions among the 2 species, Zea mays sub spp. mexicana and Zea mays spp. parviglumis, of 81 Teosinte were selected through the waterlogging treatment. The waterlogging treatments were implemented for 7 days at the seedling(V3) stage. The inbred lines were developed by crossing 5 teosinte accessions and cultivated corn lines and they were estimated waterlogging tolerance. It was screened and analyzed the metabolites extracted from roots of 19KT-32(KS141 × teosinte) that was treated waterlogging. We selected 8 of 180 metabolites like as γ-aminobutyric acid(GABA), putrescine, citrulline, Gly, and Ala that expression was remarkably changed over 2.5-times, 7 metabolites increased and 1 metabolite decreased in waterlogging, respectively. Glutamate decarboxylase(GAD) catalyzing GABA accumulation gene have 10 haplotypes, and exon1 was highly conserved, but identified to 135 SNPs after the first intron. Among the 135 SNPs, the number of transversion mutations (52) surpassed the number of transition mutations (38). Most of metabolites were related to abiotic stress in plant that it regulated to pH, osmotic pressure K⁺/Ca⁺⁺ and ATPase activity. We are analyzing the association using these results for increase breeding efficiency.

• 농업과학연구
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• 제50권2호
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• pp.181-192
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• 2023

Appropriate fertilization methods are required according to species to supply necessary nutrients to plants and prevent soil environmental contamination in nurseries. In this study, the effects of nitrogen and phosphorus fertilization on the growth of Liriodendron tulipifera and soil characteristics were investigated. After 16 fertilization treatments (4 levels of nitrogen × 4 levels of phosphorus) were applied to one-year-old L. tulipifera seedlings at the Yongmun Nursery Station of the Korea Forest Service, height, root collar diameter (RCD), biomass, leaf nutrients, and soil characteristics were investigated. The height increased as the amount of nitrogen and phosphorus fertilization increased, and the RCD was the highest in the ×2 treatment. Biomass growth was on average 40.0% higher for the treatment with high nitrogen fertilization compared to the low nitrogen treatment. The seedling quality index was the highest with nitrogen and phosphorus ×2 treatment. Leaf phosphorus and magnesium concentrations decreased when nitrogen fertilization was applied, and leaf potassium concentrations decreased as nitrogen fertilization increased. Soil pH and exchangeable potassium decreased as the amount of phosphorus application increased, and exchangeable magnesium decreased as the amount of nitrogen application increased and increased as the amount of phosphorus application increased. Considering the growth of L. tulipifera seedlings and changes in the soil characteristics at the nursery stage, twice the standard fertilization amount is the appropriate fertilization amount for nursery of the Yongmun Nursery Station. It is expected that this study will contribute to improving nursery soil fertilization management technology for healthy seedling production.

• 한국농림기상학회지
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• 제21권4호
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• pp.238-249
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• 2019

기준증발산량은 기온, 풍속, 습도 등 기상요소를 바탕으로 추정하는 방법을 이용하고 있으며, Hargreaves 공식은 기온자료를 이용하여 기준증발산량을 산정할 수 있는 간단한 경험식이라 할 수 있다. 그러나 Hargreaves 공식은 풍속이 3 m s^-1 이상인 지역에서는 과소평가 되고, 상대습도가 높은 지역은 과대평가 되는 경향이 있다. 본 연구에서는 Hargreaves 공식을 우리나라에 적용하기 위해 보다 정확한 기준증발산량 추정이 가능하도록 계수 산정 연구를 수행하였다. 우리나라 종관기상관측지점(ASOS, Automated Synoptic Observing System)의 최근 11 년(2008-2018) 동안의 기상자료를 이용하여 Panman-Monteith 공식으로 기준증발산량을 추정하였고, 이 값을 기준으로 하여 각 지점별로 Hargreaves 공식의 계수를 보정하였다. 우리나라 82 개 지점에 대하여 지역별로 보정된 계수는 내륙지역이 50 개 지점이며, 0.00173~0.00232(평균0.00196)로 기본값인 0.0023 과 비슷하거나 낮게 산정되었다. 반면, 해안지역은 32 개 지점이며 지역별로 보정된 계수의 범위는 0.00185~0.00303(평균 0.00234)으로 동해안지역은 기본값과 비슷하거나 높게 산정된 반면, 서해안과 남해안지역은 지역별로 편차가 크게 나타났다. Hargreaves 공식의 계수를 보정하여 기준증발산량을 추정한 결과 RMSE(Root Mean Square Error)는 계수 보정 전 0.634~1.394(평균 0.857)에서 계수 보정 후 0.466~1.328(평균 0.701)로 낮아지고, NSC(Nash-Sutcliffe Coefficient)는 계수 보정 전 -0.159~0.837(평균 0.647)에서 계수 보정 후 -0.053~0.910(평균 0.755)로 높아짐에 따라 기준증발산량의 추정효율이 크게 향상되는 것으로 나타났다. 연구 결과, Hargreaves 공식을 그대로 이용할 경우 Penman-Monteith 공식에 비해 과대 또는 과소 산정될 수 있음을 확인하였으며, 계수를 보정하여 이용할 경우 정확도가 높은 기준증발산량을 추정할 수 있을 것으로 판단된다.

• 한국의학물리학회지:의학물리
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• 제23권2호
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• pp.81-90
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• 2012

방사선 치료에서 부정확한 환자 셋업이 표적에 전달되는 선량에 미치는 영향과 치료 마진과의 연관성을 몬테칼로 기법을 사용한 전산모사를 통하여 분석하였다. 실제 방사선 치료를 받은 직장암 환자에 대한 임상표적체적(CTV: Clinical Target Volume) 및 주요장기의 구조와 치료계획 시스템(Eclipse 8.9, USA)을 이용하여 수립된 세기조절 방사선치료계획에서의 선량분포에 대한 데이터를 전산모사에서 사용하였다. 전산모사 프로그램은 리눅스환경에서 오픈소스인 ROOT 라이브러리와 GCC를 기반으로 본 연구를 위하여 개발되었다. 환자셋업오차의 확률분포를 정규분포로 가정한 것에 따라 무작위로 생성된 크기만큼 셋업이 부정확한 경우를 모사하여 임상표적체적에서의 선량분포의 변화와 오차크기에 따른 마진크기를 3차원입체조형 방사선치료에 사용되는 마진공식과 비교분석 하였다. 셋업오차 생성에 사용된 정규분포의 표준편차 크기는 1 mm부터 10 mm까지 1 mm간격으로 두었으며 계통오차와 통계오차별로 2,000번 전산모사했다. 계통오차의 경우 전산모사에 사용된 표준편차가 커질수록 임상표적체적에 조사되는 최소선량 $D_{min}^{stat{\cdot}}$은 100.4%에서 72.50%로 감소하였고 평균선량 $\bar{D}_{syst{\cdot}}$도 100.45%에서 97.88%로 감소한 반면에 표준편차${\Delta}D_{sys}$는 0.02%에서 3.33%로 증가하였다. 통계오차의 경우 최소선량 $D_{min}^{rand{\cdot}}$은 100.45%에서 94.80%감소하였고 평균선량 $\bar{D}_{syst{\cdot}}$도 100.46%에서 97.87%로 감소하였으며 표준편차 ${\Delta}D_{rand}$는 0.01%에서 0.63%로 증가하였다. 그리고 마진공식으로부터 전산모사에 사용된 셋업오차에 해당되는 마진크기를 구하고 모집단비율(population ratio)을 정의하여 기존 마진공식의 목적이 세기조절방사선치료에 만족함을 확인했다. 개발된 전산모사 프로그램은 해당 환자의 치료계획 정보를 직접 사용하므로 직장암만 아니라 두경부암, 전립선암 등 여러 환부에 적용 가능하며 셋업오차 및 선량변화에 연관된 연구에도 사용할 수 있을 것으로 사료된다.

• 한국초지조사료학회지
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• 제40권4호
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• pp.227-235
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• 2020

본 연구는 옥수수 습해 저항성 계통과 감수성 계통의 지상부와 지하부 제형질과 뿌리의 형태적 특성을 알아보고자 수행되었다. 6개의 국내 자식 계통을 유묘기(V3)에 10일간 담수처리 한 후 엽노화 정도로 내습성을 평가 한 결과 KS85은 황화엽수 3.33개, 노화정도 5.54로 가장 피해가 커 습해 감수성을 보였으며, KS141은 황화엽수 1.33개, 노화정도 3으로 가장 피해가 적어 습해 저항성을 보였다. KS85와 KS141을 담수 처리 후 20일에 조사한 결과 KS85와 K141의 지상부 건물중은 무처리구 대비 각각 86.1%, 77.0%가 감소되었고, 지하부 건물중은 KS85와 K141이 무처리구 대비 각각 77.6%, 65.0% 감소하여 습해 저항성인 KS141이 감수성인 KS85에 비해 건물중 감소량이 적었다. 두 계통의 지하부 nodal root의 SEM 촬영 결과 피층의 두께가 KS141이 KS85보다 더 현저히 두꺼웠으며 담수 처리 후 KS85는 KS141에 비해 피층의 뒤틀림이 심하여 피층의 두께가 내습성과 관련이 있는 것으로 사료되어진다.

• 한국자원식물학회지
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• 제26권2호
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• pp.169-177
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• 2013

울릉도 민속식물 31분류군 49점 추출물을 대상으로 최종농도 $50{\mu}g/mL$로 LPS에 의해 유도된 RAW 264.7 대식세포의 NO 생성량을 조사하였다. 그 결과, 다래(Actinidia arguta) 잎 가지, 헛개나무(Hovenia dulcis) 잎, 동백나무(Camellia japonica) 잎 가지, 말오줌나무(Sambucus sieboldiana var. pendula) 잎 가지, 왕호장근(Fallopia sachalinensis) 뿌리 순으로 항염 활성이 우수하게 나타났다. 이 중에서 다래 잎 가지, 헛개나무 잎, 동백나무 잎 가지 추출물을 LPS로 유도된 Raw 264.7 대식세포에서 최종농도가 10, 20, 40, $50{\mu}g/mL$로 처리하여 NO 생성량과 세포생존율, $PGE_2$ 생성량을 측정하였다. 그 결과 다래 잎 가지($IC_{50}=29.21{\mu}g/mL$), 헛개나무 잎($IC_{50}=27.34{\mu}g/mL$), 동백나무 잎 가지($IC_{50}=45.68{\mu}g/mL$) 모두 NO 생성을 농도 의존적으로 유의성 있게 억제하였다. 또한 $PGE_2$ 측정결과 다래 잎 가지($IC_{50}=21.06{\mu}g/mL$), 헛개나무 잎($IC_{50}=33.47{\mu}g/mL$), 동백나무 잎 가지($IC_{50}=43.90{\mu}g/mL$)에서도 유의성 있는 억제효과를 보였다. 본 연구결과 다래 잎 가지, 헛개나무 잎, 동백나무 잎 가지의 추출물은 염증 유발의 중요 인자인 NO 및 $PGE_2$ 생성을 저해하여 우수한 항염증 효과를 보였다. 이들 소재에 대한 염증억제 유효성분 규명 및 그 작용기전을 추가적으로 연구함으로써 만성 염증질환의 예방과 치료에 효과적으로 사용할 수 있을 것으로 기대된다.