• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2022년도 학술발표회
• /
• pp.446-446
• /
• 2022

본 연구에서는 MODIS(MODerate resolution Imaging Spectroradiometer) 다중 위성영상을 기반으로 전국 시공간 토양수분 및 토양수분 기반의 가뭄지수 SWDI(Soil Water Deficit Index)를 산정하였다. 시공간 토양수분의 산정을 위해 입력자료로 MODIS 위성의 지표면온도(Land Surface Temperature, LST), 증발산 및 식생(Enhanced Vegetation Index, EVI; Fraction of Photosynthetically Active Radiation, FPAR; Leaf Area Index, LAI; Normalized Difference Vegetation Index, NDVI) 관련 산출물 자료와 지상 관측자료인 일 단위 강수량 자료를 구축하였다. MODIS 위성영상은 산출물별로 제공되는 QC(Quality Control) 영상을 활용해 보정을 수행하였고, 공간 강수량 자료는 기상청에서 제공하는 전국 92개 지점의 종관기상관측자료를 구축하여 공간보간기법인 역거리가중법을 적용해 생성하였다. 실측 토양수분은 농촌진흥청에서 제공하는 76개 지점의 토양 깊이 10 cm에 설치된 TDR(Time Domain Reflectomerty) 센서에서 측정된 토양수분 자료를 활용하였으며, 토양수분 모의 시 토양 속성을 고려하기 위해 국립농업과학원에서 제공하는 토양도를 구축하여 활용하였다. 토양수분 산정 모형은 다중선형회귀모형(Multiple Linear Regression Model, MLRM)을 활용하였으며, 계절 및 토성에 따른 회귀식을 산정하였다. 회귀식 기반의 토양수분과 토성별 포장용수량 및 영구위조점 값을 이용하여 SWDI를 산정하고, 실제 가뭄 발생 시기 및 지역과의 비교하고자 한다.

• Journal of Korean Neurosurgical Society
• /
• 제57권6호
• /
• pp.455-459
• /
• 2015

Objective : A cost comparison of the surgical clipping and endovascular coiling of unruptured intracranial aneurysms (UIAs), and the identification of the principal cost determinants of these treatments. Methods : This study conducted a retrospective review of data from a series of patients who underwent surgical clipping or endovascular coiling of UIAs between January 2011 and May 2014. The medical records, radiological data, and hospital cost data were all examined. Results : When comparing the total hospital costs for surgical clipping of a single UIA (n=188) and endovascular coiling of a single UIA (n=188), surgical treatment [$mean{\pm}$standard deviation (SD) : \$8,280,000{\pm}1,490,000$] resulted in significantly lower total hospital costs than endovascular treatment ($mean{\pm}SD$ : \$11,700,000{\pm}3,050,000$, p<0.001). In a multi regression analysis, the factors significantly associated with the total hospital costs for endovascular treatment were the aneurysm diameter (p<0.001) and patient age (p=0.014). For the endovascular group, a Pearson correlation analysis revealed a strong positive correlation (r=0.77) between the aneurysm diameter and the total hospital costs, while a simple linear regression provided the equation, y (\)=6,658,630+855,250x (mm), where y represents the total hospital costs and x is the aneurysm diameter. Conclusion : In South Korea, the total hospital costs for the surgical clipping of UIAs were found to be lower than those for endovascular coiling when the surgical results were favorable without significant complications. Plus, a strong positive correlation was noted between an increase in the aneurysm diameter and a dramatic increase in the costs of endovascular coiling.

• 한국건설관리학회:학술대회논문집
• /
• 한국건설관리학회 2006년도 정기학술발표대회 논문집
• /
• pp.137-142
• /
• 2006

비용과 공기는 수익과 직접적인 상관관계를 갖는 중요한 요소로 성공적인 프로젝트를 위해서는 이들에 대한 정확한 예측이 이루어져야 한다. 현재 최종 공사비와 공기 예측을 목적으로 EVMS(Earned Value Management System)가 범용적으로 활용되고 있지만, 기존에 제시된 공사비 및 공기 예측모텔은 선형적인 예측방식을 사용하기 때문에 예측결과가 부정확하고 시공업체의 성향, 프로젝트의 특성, 진도율에 따른 변화 등을 고려하지 못하는 한계가 있었다. 본 연구에서는 건설산업의 다양한 특성이 반영될 수 있도록 PB-S curve와 다중회귀분석을 이용한 진행단계별 공사비 및 공기의 기울기 예측모델을 제안하고 이를 동해 최종 공사비 및 공기를 예측하고자 한다. 이를 위하여 국내 건설업체로부터 23건의 도로공사 EVMS 자료를 활용하여 공사 진행단계별 기울기 예측을 위한 회귀분석방정식을 도출하고, 활용성을 검증하였다.

• 한국작물학회지
• /
• 제54권1호
• /
• pp.29-35
• /
• 2009

The aim of the present study was to update the calibration that is used for the measurement of the total nitrogen content in the rice plant samples by using the visible and near infrared spectrum. Before the equation merge, correlation coefficient of calibration equation for nitrogen content on each rice parts was 0.945 (Leaf), 0.928 (Stem), and 0.864 (Whole plant), respectively. In the calibration models created by each part in the rice plant under the various regression method, the calibration model for the leaf was recorded with relatively high accuracy. Among of those, the calibration equation developed by Partial least squares (PLS) method was more accurate than the Multiple linear regression (MLR) method. The calibration equation was sensitive based on variety and location variations. However, we have merged and enlarged various of the samples that made not only to measure the nitrogen content more accurately, but also later sampling populations became more diversified. After merging, $R^2$ value becomes more accurate and significantly to 0.950 (L.), 0.974 (S.), 0.940 (W.). Also, after removal of outlier, R2 values increased into 0.998, 0.995, and 0.997. In view of the results so far achieved, Standard error of prediction (SEP) and SEP (C) were reduced in the stem and whole plant. Biases were reduced in the leaf, stem as well as whole plant. Slopes were high in the stem. Standard deviation reduced in the stem but $R^2$ was high in the stem and whole plant. Result was indicated that calibration equation make update, and updating robust calibration equation from merge function and multi-variate calibration.

• 의학교육논단
• /
• 제26권1호
• /
• pp.70-76
• /
• 2024

This study investigates whether personality characteristics and learning behaviors can predict medical students' academic achievement in Korea, specifically in terms of successfully completing medical school without delays or achieving a high grade point average (GPA) in their final year. In May 2018, 316 medical students took the Multi-Dimensional Learning Strategy Test, 2nd edition, which provided data on their personality and learning behavioral characteristics. Their final year's GPA and any delays in completing medical school were ascertained by reviewing all electronic academic records of each semester they had been enrolled. The combination of personality and learning behavioral characteristics was significantly associated with completing medical school without delays, even after adjusting for sex and admission path. A multiple logistic regression analysis showed that the adjusted odds ratios and 95% confidence intervals for completing medical school without delays were 1.52 (95% confidence interval [CI], 0.83-2.78) and 3.64 (95% CI, 1.70-7.82) for "others" and "both high" categories, respectively, when compared with the "both low" category. For 235 students who completed medical school without delays, their learning behavioral characteristics (scores) were significantly associated with their final year's GPA even after adjusting for sex, admission path, and personality characteristics (scores) as determined by the multiple linear regression analysis. This study suggests that individual personality and learning behavior characteristics are predictors of medical students' academic achievement. Therefore, interventions such as personalized counseling programs should be provided in consideration of such student characteristics.

• 한국농업기계학회:학술대회논문집
• /
• 한국농업기계학회 2017년도 춘계공동학술대회
• /
• pp.45-45
• /
• 2017

On-site monitoring of vegetable growth parameters, such as leaf length, leaf area, and fresh weight, in an agricultural field can provide useful information for farmers to establish farm management strategies suitable for optimum production of vegetables. Unmanned Aerial Vehicles (UAVs) are currently gaining a growing interest for agricultural applications. This study reports on validation testing of previously developed vegetable growth estimation models based on UAV-based RGB images for white radish and Chinese cabbage. Specific objective was to investigate the potential of the UAV-based RGB camera system for effectively quantifying temporal and spatial variability in the growth status of white radish and Chinese cabbage in a field. RGB images were acquired based on an automated flight mission with a multi-rotor UAV equipped with a low-cost RGB camera while automatically tracking on a predefined path. The acquired images were initially geo-located based on the log data of flight information saved into the UAV, and then mosaicked using a commerical image processing software. Otsu threshold-based crop coverage and DSM-based crop height were used as two predictor variables of the previously developed multiple linear regression models to estimate growth parameters of vegetables. The predictive capabilities of the UAV sensing system for estimating the growth parameters of the two vegetables were evaluated quantitatively by comparing to ground truth data. There were highly linear relationships between the actual and estimated leaf lengths, widths, and fresh weights, showing coefficients of determination up to 0.7. However, there were differences in slope between the ground truth and estimated values lower than 0.5, thereby requiring the use of a site-specific normalization method.

• Bulletin of the Korean Chemical Society
• /
• 제26권12호
• /
• pp.2007-2016
• /
• 2005

An artificial neural network (ANN) is successfully presented for prediction acidity constant (pKa) of various benzoic acids and phenols with diverse chemical structures using a nonlinear quantitative structure-property relationship. A three-layered feed forward ANN with back-propagation of error was generated using six molecular descriptors appearing in the multi-parameter linear regression (MLR) model. The polarizability term $(\pi_1)$, most positive charge of acidic hydrogen atom $(q^+)$, molecular weight (MW), most negative charge of the acidic oxygen atom $(q^-)$, the hydrogen-bond accepting ability $(\epsilon_B)$ and partial charge weighted topological electronic (PCWTE) descriptors are inputs and its output is pKa. It was found that properly selected and trained neural network with 205 compounds could fairly represent dependence of the acidity constant on molecular descriptors. For evaluation of the predictive power of the generated ANN, an optimized network was applied for prediction pKa values of 37 compounds in the prediction set, which were not used in the optimization procedure. Squared correlation coefficient $(R^2)$ and root mean square error (RMSE) of 0.9147 and 0.9388 for prediction set by the MLR model should be compared with the values of 0.9939 and 0.2575 by the ANN model. These improvements are due to the fact that acidity constant of benzoic acids and phenols in water shows nonlinear correlations with the molecular descriptors.

• 한국농공학회논문집
• /
• 제55권5호
• /
• pp.25-35
• /
• 2013

In swine house, dust generation comes from various sources and is known to be harmful both for the animals and the farmers because the dust contains biological and gaseous matters. When farmers are constantly exposed to the dusts, they can suffer chronic or acute respiratory symptoms and have high probability of manifesting various diseases. To address this problem, understanding of the mechanism of dust generation is very important. In this paper, the dust concentration of inhalable, respirable, TSP and $PM_{10}$ were monitored and analyzed according to the pig-activity level, ventilation quantity and feeding method in fattening pig house. From the measured results, in case of the concentration of TSP, an inverse-linear relation with ventilation rate ($R^2=0.88$) and linear relation with the installation height of feed supply pipe ($R^2=0.73$) were determined. However in case of the concentration of $PM_{10}$, no particular relationship with the variables was observed. Using the concentration of inhalable and respirable dust based on the pig-activity level, multi-variate regression analysis was conducted and results have shown that the movement of pigs can contribute to the dust generation (p＜0.05, $R^2=0.71$, 0.61). The relationship determined between dust generation and environmental variables investigated in this study is very significant and useful in conducting dust-reduction researches.

• 응용통계연구
• /
• 제26권3호
• /
• pp.441-452
• /
• 2013

국내 영화 산업은 투자 배급사 멀티플렉스로 수직 계열화된 대기업 중심으로 온라인 구전 마케팅이 활발히 진행되고 있다, 최근에는 대기업 계열의 멀티플렉스 영화관 중심으로 3D 4D 영화포맷 복합상영을 통해 up-selling을 통한 흥행성과 극대화를 도모하고 있다. 영화산업 기술진보와 흥행여건 변화에 따라, 기존 관객 수 대신 매출액을 흥행성과로 정의하고, 국내 개봉 상업영화를 대상으로 축소추정기법을 포함한 여러 회귀모형을 적용하였다. 특히 LASSO회귀의 경우, 교차타당성 방법을 이용한 예측오차가 가장 적고 흥행성과에 설명력이 높은 변수 순으로 의미 있는 독립변수들을 빠르고 효율적으로 선택할 수 있었다. 2013년도 1분기 개봉 영화를 대상으로 실증분석 결과, 개봉 후 온라인 평점과 빈도 모두 영향력이 높았으나, 개봉 전에는 온라인 평점만 효과적인 것으로 나타났다. 상영포맷 또한 흥행성과에 유의한 영향을 미치는 것으로 나타났다.

• The Journal of Asian Finance, Economics and Business
• /
• 제8권5호
• /
• pp.81-89
• /
• 2021

This study aimed to investigate the factors affecting Logistics capabilities for Logistics Service Providers in Vietnam. Researchers inherited and developed based on previous research to focus on analyzing and evaluating dynamics, measuring Logistics capabilities, and the factors affecting Logistics capabilities for Logistics Service Providers. The logistics capabilities Model is used based on three factors: customer demand management capability, innovation capability, and information management capability. The empirical analysis used data from the survey data of l90 managers of Logistics Service Providers in Hai Phong, Ho Chi Minh City, Da Nang, Hue, Hanoi with reliable tools (SPSS 26.0 software). The data were analyzed by frequencies, percentages, means, Pearson's Linear Correlation Coefficient, exploratory factor analysis, and multi-linear regression model based on the survey data. The research results identified the following factors affecting Logistics capabilities for Logistics Service Providers: innovation capability has the strongest impact on Logistics capabilities; customer demand management capability has the following strong effects on Logistics capabilities; and finally, information management capability that affects Logistics capabilities. There is also a positive relationship between all factors and Logistics capabilities. Several recommendations are further suggested to enhance to improve Logistics capabilities for Logistics Service Providers in Vietnam.