• Journal of Environmental Impact Assessment
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• v.30 no.5
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• pp.271-296
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• 2021

Since the thermal stratification in a reservoir inhibits the vertical mixing of the upper and lower layers and causes the formation of a hypoxia layer and the enhancement of nutrients release from the sediment, changes in the stratification structure of the reservoir according to future climate change are very important in terms of water quality and aquatic ecology management. This study was aimed to develop a data-driven inflow water temperature prediction model for Daecheong Reservoir (DR), and to predict future inflow water temperature and the stratification structure of DR considering future climate scenarios of Representative Concentration Pathways (RCP). The random forest (RF)regression model (NSE 0.97, RMSE 1.86℃, MAPE 9.45%) developed to predict the inflow temperature of DR adequately reproduced the statistics and variability of the observed water temperature. Future meteorological data for each RCP scenario predicted by the regional climate model (HadGEM3-RA) was input into RF model to predict the inflow water temperature, and a three-dimensional hydrodynamic model (AEM3D) was used to predict the change in the future (2018~2037, 2038~2057, 2058~2077, 2078~2097) stratification structure of DR due to climate change. As a result, the rates of increase in air temperature and inflow water temperature was 0.14~0.48℃/10year and 0.21~0.41℃/10year,respectively. As a result of seasonal analysis, in all scenarios except spring and winter in the RCP 2.6, the increase in inflow water temperature was statistically significant, and the increase rate was higher as the carbon reduction effort was weaker. The increase rate of the surface water temperature of the reservoir was in the range of 0.04~0.38℃/10year, and the stratification period was gradually increased in all scenarios. In particular, when the RCP 8.5 scenario is applied, the number of stratification days is expected to increase by about 24 days. These results were consistent with the results of previous studies that climate change strengthens the stratification intensity of lakes and reservoirs and prolonged the stratification period, and suggested that prolonged water temperature stratification could cause changes in the aquatic ecosystem, such as spatial expansion of the low-oxygen layer, an increase in sediment nutrient release, and changed in the dominant species of algae in the water body.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.316-328
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• 2021

In this study, the leaf Na content prediction model for spring potato was established using 400-1000 nm hyperspectral sensor to develop the multispectral sensor for the salinity monitoring in reclaimed land. The irrigation conditions were standard, drought, and salinity (2, 4, 8 dS/m), and the irrigation amount was calculated based on the amount of evaporation. The leaves' Na contents were measured 1st and 2nd weeks after starting irrigation in the vegetative, tuber formative, and tuber growing periods, respectively. The reflectance of the leaves was converted from 5 nm to 10 nm, 25 nm, and 50 nm of FWHM (full width at half maximum) based on the 10 nm wavelength intervals. Using the variance importance in projections of partial least square regression(PLSR-VIP), ten band ratios were selected as the variables to predict salinity damage levels with Na content of spring potato leaves. The MLR(Multiple linear regression) models were estimated by removing the band ratios one by one in the order of the lowest weight among the ten band ratios. The performance of models was compared by not only R2, MAPE but also the number of band ratios, optimal FWHM to develop the compact multispectral sensor. It was an advantage to use 25 nm of FWHM to predict the amount of Na in leaves for spring potatoes during the 1st and 2nd weeks vegetative and tuber formative periods and 2 weeks tuber growing periods. The selected bandpass filters were 15 bands and mainly in red and red-edge regions such as 430/440, 490/500, 500/510, 550/560, 570/580, 590/600, 640/650, 650/660, 670/680, 680/690, 690/700, 700/710, 710/720, 720/730, 730/740 nm.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.63-75
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• 2023

Due to the development of industry, interest in air pollutants has increased. Air pollutants have affected various fields such as environmental pollution and global warming. Among them, environmental diseases are one of the fields affected by air pollutants. Air pollutants can affect the human body's skin or respiratory tract due to their small molecular size. As a result, various studies on air pollutants and environmental diseases have been conducted. Asthma, part of an environmental disease, can be life-threatening if symptoms worsen and cause asthma attacks, and in the case of adult asthma, it is difficult to cure once it occurs. Factors that worsen asthma include particulate matter and air pollution. Asthma is an increasing prevalence worldwide. In this paper, we study how air pollutants correlate with the number of emergency room admissions in asthma patients and predict the number of future asthma emergency patients using highly correlated air pollutants. Air pollutants used concentrations of five pollutants: sulfur dioxide(SO₂), carbon monoxide(CO), ozone(O₃), nitrogen dioxide(NO₂), and fine dust(PM₁₀), and environmental diseases used data on the number of hospitalizations of asthma patients in the emergency room. Data on the number of emergency patients of air pollutants and asthma were used for a total of 5 years from January 1, 2013 to December 31, 2017. The model made predictions using two models, Informer and LTSF-Linear, and performance indicators of MAE, MAPE, and RMSE were used to measure the performance of the model. The results were compared by making predictions for both cases including and not including the number of emergency patients. This paper presents air pollutants that improve the model's performance in predicting the number of asthma emergency patients using Informer and LTSF-Linear models.

• Journal of Biomedical Engineering Research
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• v.30 no.5
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• pp.401-411
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• 2009

In this paper, we correct pulse wave velocity(PWV) with heart-rate and derive regression equations to estimate intima-media thickness(IMT). Widely used methods for diagnosis of arteriosclerosis are IMT and PWV. Arterial wall stiffness determines the degree of energy absorbed by the elastic aorta and its recoil in diastole but there is not correlation between sclerosis and IMT in an existing study. In this study, we will correct PWV with heart-rate and get regression equation to estimate IMT using heart-rate correction index(HCI). We executed experiments for this study. Made up question of physical condition and measured electrocardiogram(ECG), photoplethysmogram (PPG) of finger-tip and toe-tip and ultrasound image of carotid artery. Calculated PWV and IMT using ECG, PPG and ultrasound image. We found that every p-value between PWV and IMT is not significant(<0.05). But p-value between IMT and HCI which is a corrected PWV using heart-rate is significant(>0.01). We use HCI and various measured parameter for estimating regression equation and apply backward estimation to select parameters for regression analysis. Result of backward estimation, found that only HCI is possible to derive proper regression equation of IMT. Relationship between PWV and IMT is the second order. Result of regression equation of E-H PWV is $R^2$=0.735, adj $R^2$=0.711. This is the best correlation value. We calculate error of its analysis for verification of earlobe PWV regression equation. Its result is RMSEP=0.0328, MAPE(%) = 4.7622. Like this regression analysis, we know that HCI is useful parameter and relationship between PWV, HCI and IMT. In addition, we are able to suggest possibility which is that we can get different parameter of prediction throughout just one measurement.

• Journal of Korea Port Economic Association
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• v.28 no.2
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• pp.75-93
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• 2012

The steel cargoes as the core raw materials for the manufacturing industry have important roles for increasing the handling volume of the port. In particular, steel cargoes are fundamental to vitalize Port of Incheon because they have recognized as the primary key cargo items among the bulk cargoes. In this respect, the IPA(Incheon Port Authority) ambitiously developed the port complex facilities including dedicated terminals and its hinterland in northern part of Incheon. However, these complex area has suffered from low cargo handling records and has faced operational difficulties due to decreased net profits. In general, the import and export steel cargo volumes are sensitively fluctuated followed by internal and external economy index. There is a scant of research for forecasting the steel cargo volume in Incheon port which used in various economy index. To fill the research gap, the aim of this research is to predict the steel cargoes of Port of Incheon using the well established methodology i.e. System Dynamics. As a result, steel cargoes volume dealt with in Incheon port is forecasted from about 8 million tons to about 10 million tons during simulation duration (2011-2020). The Mean Absolute Percentage Error (MAPE) is measured as 0.0013 which verifies the model's accuracy.

• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.19-29
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• 2011

A Blog provides commentary, news, or content on a particular subject. The important part of many blogs is interactive format. Sometimes, there is a heated debate on a topic and any article becomes a political or sociological issue. In this paper, we proposed a method to predict the popularity of an article in advance. First, we used hit count as a factor to predict the popularity of an article. We defined the saturation point and derived a model to predict the hit count of the saturation point by a correlation coefficient of the early hit count and hit count of the saturation point. Finally, we predicted the virtual temperature of an article using 4 types(explosive, hot, warm, cold). We can predict the virtual temperature of Internet discussion articles using the hit count of the saturation point with more than 70% accuracy, exploiting only the first 30 minutes' hit count. In the hot, warm, and cold categories, we can predict more than 86% accuracy from 30 minutes' hit count and more than 90% accuracy from 70 minutes' hit count.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.29-44
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• 2009

A variety of research efforts, using advanced wireless communication technologies, have been made to develop more reliable traffic information system. This study presents a novel decentralized traffic information system based on vehicle infrastructure integration (VII). A major objective of this study was also to devise a methodology for determining appropriate spacing of roadside equipment (RSE) to fully exploit the benefits of the proposed VII-based traffic information system. Evaluation of travel time estimation accuracy was conducted with various RSE spacings and the market penetration rates of equipped vehicle. A microscopic traffic simulator, VISSIM, was used to obtain individual vehicle travel information for the evaluation. In addition, the ANOVA tests were conducted to draw statistically significant results of simulation analyses in determining the RSE spacing. It is expected that the proposed methodology will be a valuable precursor to implementing capability-enhanced next generation traffic information systems under the forthcoming ubiquitous transportation environment.

• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.611-624
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• 2018

The percentage of moisture content in rice before harvest is crucial to reduce the economic loss in terms of yield, quality and drying cost. This paper discusses the application of artificial neural network (ANN) in developing a reliable prediction model using the low altitude fixed-wing unmanned air vehicle (UAV) based reflectance value of green, red, and NIR and statistical moisture content data. A comparison between the actual statistical data and the predicted data was performed to evaluate the performance of the model. The correlation coefficient (R) is 0.862 and the mean absolute percentage error (MAPE) is 0.914% indicate a very good accuracy of the model to predict the moisture content in rice before harvest. The model predicted values are matched well with the measured values($R^2=0.743$, and Nash-Sutcliffe Efficiency = 0.730). The model results are very promising and show the reliable potential to predict moisture content with the error of prediction less than 7%. This model might be potentially helpful for the rice production system in the field of precision agriculture (PA).

• International Journal of Highway Engineering
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• v.9 no.4
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• pp.1-9
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• 2007

To decide the number of road lane is very important and related to the 30th design hourly factor in the design of transportation facilities. But, as the quantitative division of road types is difficult, most planner and designer for deciding the 30th design hourly factors have used the fixed values in our country. In this study, we have analyzed the time series property of the design hourly factors in national highways and developed the model capable of estimating the 30th design hourly factors using real data. The presented model is a simple regression model(DHV = K*AADT), which is applied to the division of road lanes(2 or 4 lanes) and the level of AADT(3 levels). As a results, the simple regression model have better performance than the existing method with respect to MAPE and $R^2$. Also, the variations of the 30th design hourly factors are small. The more traffic volume increase, the more the factors decrease. But, the limitation of this study is to use the exiting method estimating the values of the factors, it is subject to study hereafter.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.70-70
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• 2015

하천에서의 수문/수리적 특성은 주수로의 다양한 지형학적 형태로 나타난다. 특히 흐름과 수반된 유사량의 변화는 하천의 지형학적, 수리기하적 특성을 지배하며, 하도의 물리적 시스템을 변화시켜 동적 평형에 이르게 된다. 하천에서 하도 형성에 지배적인 역할을 하는 수리특성은 하도형성유량으로 지배유량이며, 보통 만제유량을 사용한다. Dunne and Leopold(1978)는 만제유량을 유사의 이송, 하천의 사행, 유선형의 변화 등 하천의 일반적인 형태를 변화시키며, 주수로의 특성을 형성하는 유량으로 정의하였다. 이와 같이 수리 지형학적 특성을 반영하는 만제유량은 하천의 특성을 나타내는 중요한 요소이다. 따라서 본 연구에서는 한강 수계 20개 하천, 27개 수위 관측소의 최소 10년 이상의 실측 자료를 기반으로 다년간의 연평균 실측유량을 산정하였으며, McCandless(2003)가 제시한 지형학적 만제지표를 이용하여 추정한 만제유량과의 상관성을 분석하였다. 추정된 만제유량은 HEC-RAS model을 이용하여 만제하폭, 만제수심, 만제 시 평균유속을 산정하였다. 27개 지점의 실측유량과 만제유량의 상관성 분석결과 만제유량은 연평균 일유량의 7.7배로 나타났다. 따라서 만제유량을 7일 평균유량(1 week mean discharge)으로 정의하였으며, 수정된 7일 유량과 만제유량의 RMSE는 13.90 m/s, MAPE는 9.94 %로 상관성이 매우 높게 나타났다. 또한 만제유량과 만제하폭, 만제수심, 평균유량, 구간경사와 상관성 분석결과 개별적으로의 상관성은 나타나지 않았으나, 만제하폭, 수심, 평균유량과 만제유량에 대한 회귀 분석을 실시한 결과 $R^2$는 0.911로 매우 높게 나타났으며, 구간경사를 추가하여 분석한 결과 $R^2$가 0.914로 증가하였다. 따라서 만제유량은 수리 기하학적 특성이 모두 반영된 하천 특성을 나타내는 복합적인 지표임을 확인하였다. 아울러 만제유량을 통해 추정된 연평균 유량($48{\cdot}Q_{bf}$)을 우리나라의 월간 유출량 분포 비율을 이용하여 일유량으로 배분/생성하였으며, 생성된 일유량을 통해 CCHE2D model을 이용하여 하상변동 모의를 수행하였다. 대상 구간은 병성천 최하류로부터 상류로 7 km 구간이며, 2013년 1월과 12월 측량 자료를 통한 1년간의 실제 하상 변동 자료와 2013년 실측 유량자료에 따른 하상변동 모의 결과 및 만제유량에 의해 배분/생성된 일유량에 따른 하상변동 모의 결과를 비교하였다. 비교 분석 결과 7일 평균 유량으로 정의된 만제유량을 통해 배분/생성된 유량의 수치모의 결과는 실제 측량자료 및 실측유량자료에 따른 하상변동 결과와 매우 일치하는 것을 확인하였다.