• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2015년도 춘계 학술논문 발표대회
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• pp.243-244
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• 2015

This paper presents a Stochastic Long-Term Maintenance Costs Estimating Method for the Apartment Housing (SLCE). A simulation approach is used for generating the stochastic long-term maintenance cost, and it is based on the defined variability in repair cycle of the individual maintenance elemental within the process. SLCE provides the probability distribution of the budget required to maintain the apartment housing. A case study is presented to demonstrate and to validate the system.

• International Journal of Quality Innovation
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• 제1권1호
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• pp.32-37
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• 2000

In an industrial process, the proper objective is to find the optimal operating conditions with minimum process variability around the target. Vining and Myers(1990) suggest to use the separate model for the mean response and the process varian linear predictor ${\tau}_i={\log}\;{\sigma}^2_i$ is unknown and should be estimated. Noting that the variance of $\hat{{\tau}_i}$ is heterogeneous, another appropriate D-optimality criterion $D_3$ based on the method of generalized least squares is proposed in this paper.

• Journal of the Korean Statistical Society
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• 제31권1호
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• pp.45-61
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• 2002

We consider the problem of estimating binomial proportions in the presence of nonignorable nonresponse using the Bayesian selection approach. Inference is sampling based and Markov chain Monte Carlo (MCMC) methods are used to perform the computations. We apply our method to study doctor visits data from the Korean National Family Income and Expenditure Survey (NFIES). The ignorable and nonignorable models are compared to Stasny's method (1991) by measuring the variability from the Metropolis-Hastings (MH) sampler. The results show that both models work very well.

• 대한원격탐사학회지
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• 제22권3호
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• pp.183-197
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• 2006

Combinations of visible and near-infrared (NIR) bands in an image are widely used for estimating vegetation vigor and productivity. Using this approach to understand within-field grain crop variability could allow pre-harvest estimates of yield, and might enable mapping of yield variations without use of a combine yield monitor. The objective of this study was to estimate within-field variations in crop yield using vegetation indices derived from hyperspectral images. Hyperspectral images were acquired using an aerial sensor on multiple dates during the 2003 and 2004 cropping seasons for corn and soybean fields in central Missouri. Vegetation indices, including intensity normalized red (NR), intensity normalized green (NG), normalized difference vegetation index (NDVI), green NDVI (gNDVI), and soil-adjusted vegetation index (SAVI), were derived from the images using wavelengths from 440 nm to 850 nm, with bands selected using an iterative procedure. Accuracy of yield estimation models based on these vegetation indices was assessed by comparison with combine yield monitor data. In 2003, late-season NG provided the best estimation of both corn $(r^2\;=\;0.632)$ and soybean $(r^2\;=\;0.467)$ yields. Stepwise multiple linear regression using multiple hyperspectral bands was also used to estimate yield, and explained similar amounts of yield variation. Corn yield variability was better modeled than was soybean yield variability. Remote sensing was better able to estimate yields in the 2003 season when crop growth was limited by water availability, especially on drought-prone portions of the fields. In 2004, when timely rains during the growing season provided adequate moisture across entire fields and yield variability was less, remote sensing estimates of yield were much poorer $(r^2<0.3)$.

• 한국토양비료학회지
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• 제47권3호
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• pp.217-224
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• 2014

Ground-based remote sensing can be used as one of the non-destructive, fast, and real-time diagnostic tools for predicting yield, biomass, and nitrogen stress during growing season. The objectives of this study were: 1) to assess biomass and nitrogen (N) status of tobacco (Nicotiana tabacum L.) plants under N stress using ground-based remote sensors; and 2) to evaluate the feasibility of spectral reflectance indices for estimating an application rate of N and predicting yield of tobacco. Dry weight (DW), N content, and N uptake at the 40th and 50th day after transplanting (DAT) were positively correlated with chlorophyll content and normalized difference vegetation indexes (NDVIs) from all sensors (P<0.01). Especially, Green NDVI (GNDVI) by spectroradiometer and Crop Circle-passive sensors were highly correlated with DW, N content and N uptake. The yield of tobacco was positively correlated with canopy reflectance indices measured at each growth stage (P<0.01). The regression of GNDVI by spectroradiometer on yield showed positively quadratic curve and explained about 90% for the variability of measured yield. The sufficiency index (SI) calculated from data/maximum value of GNDVI at the $40^{th}$ DAT ranged from 0.72 to 1.0 and showed the same positively quadratic regression with N application rate explaining 84% for the variability of N rate. These results suggest that use of reflectance indices measured with ground-based remote sensors may assist in determining application rate of fertilizer N at the critical season and estimating yield in mid-season.

• 대한지역사회영양학회지
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• 제28권5호
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• pp.414-422
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• 2023

Objectives: This study evaluated usual dietary intakes of total fat and fatty acids among the Korean population based on the revised Dietary Reference Intakes for Koreans 2020 (2020 KDRIs). Methods: This study utilized data from the eighth Korea National Health and Nutrition Examination Survey (KNHANES 2019-2021). We included 18,895 individuals aged 1 year and above whose 1-day 24-hour dietary recall data were available. To calculate the external variability using the National Cancer Institute 1-day method, data from the U.S. NHANES 2017-March 2020 Pre-pandemic dataset were employed. The total fat and fatty acid intake were evaluated based on the Acceptable Macronutrient Distribution Ranges (AMDRs) and Adequate intake (AI) of 2020 KDRIs for each sex and age groups. Results: Approximately 86% of the Korean population obtained an adequate amount of energy from total fat consumption (within the AMDRs), indicating an appropriate level of intake. However, the percentage of individuals consuming saturated fatty acids below the AMDR was low, with only 12% among those under 19 years of age and 52% aged 19 years and older. On a positive note, approximately 70% of the population showed adequate consumption of essential fatty acids, exceeding the AI. Nevertheless, monitoring the intake ratio of omega 3 (n-3) to omega 6 (n-6) fatty acids is essential to ensure an optimum balance. Conclusions: This study explored the possibility of estimating the distribution of nutrient intake in a population by applying the external variability ratio. Therefore, if future KNHANES conduct multiple 24-hour recalls every few years-similar to the U.S. NHANES-even for a subset of participants, this may aid in the accurate assessment of the nutritional status of the population.

• 대한의용생체공학회:의공학회지
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• 제16권3호
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• pp.289-300
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• 1995

지금까지는 혈관의 중심선을 구해서 혈관의 직경을 측정해 왔다. 혈관의 중심선을 구하는 방법은 2가지가 보고되어 있는데 그중 하나는 maunal로 중심선을 찾는 observer-defined 방법이다. 이 방법을 사용자에 따라 변화할 가능성이 잠재한다, 또 다른 방법은 자동으로 혈관의 중심을 찾아내는 것인데 대단히 복잡하다. 이 논문에서, 중심선을 찾지 않고 방향코드와 위치정보를 이용하여 직경을 구하는 새로운 방법을 제안한다. 이 방법은 경계선과 방향코드를 동시에 검출하기 때문에 절차가 간단해지고 처리속도도 빨라진다. 중앙선을 이용하여 자동으로 혈관직경을 구하는 방법과 비교해보면, 가지가 있거나 장애가 있는 혈관 이미지에 있어서 정확도가 개선된다. 또한 방향 코드는 3비트로 코드화되기 때문에 혈관정보를 압축 저장하는데 용이하다. 이 방법은 실험을 통하여 유용성이 있음을 확인하였다.

• Journal of Information Technology Applications and Management
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• 제26권6호
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• pp.47-63
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• 2019

The volatility of major crypto currencies was examined and they are diagnosed whether they have a systematic risk or not, by estimating market beta representing systematic risk using GARCH( Generalized Auto Regressive Conditional Heteroskedastieity) model. First, the empirical results showed that their prices are very volatile over time because of the existence of ARCH and GARCH effects. Second, in terms of efficiency, asymmetric GJR model was estimated to be the most appropriate model because the standard error of a market beta was less than that of the OLS model and GARCH model. Third, the estimated market beta of Bitcoin using GJR model was less than 1 at 0.8791, showing that there is no systematic risk. However, unlike OLS model, the market beta of Ethereum and Ripple was estimated at 1.0581 and 1.1222, showing that there is systematic risk. This result shows that bitcoin is less dangerous than Ripple and Ethereum, and ripple is the most dangerous of all three crypto currencies. Finally, the major cryptocurrency found that the negative impact caused greater variability than the positive impact, causing bad news to fluctuate more than good news, and therefore good news and bad news had a different effect on the variability.

• 한국지능시스템학회논문지
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• 제26권5호
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• pp.343-350
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• 2016

Remaining lifetime prediction of the underground gas pipeline plays a key role in maintenance planning and public safety. One of main causes in the pipeline failure is metal corrosion. This paper deals with estimating the pipeline reliability in the presence of corrosion defects. Because a pipeline has uncertainty and variability in its operation, probabilistic approximation approaches such as first order second moment (FOSM), first order reliability method (FORM), second order reliability method (SORM), and Monte Carlo simulation (MCS) are widely employed for pipeline reliability predictions. This paper presents a fuzzy inference based reliability method (FIRM). Compared with existing methods, a distinction of our method is to incorporate a fuzzy inference into quantifying degrees of variability in corrosion defects. As metal corrosion depends on the service environment, this feature makes it easier to obtain practical predictions. Numerical experiments are conducted by using a field dataset. The result indicates that the proposed method works well and, in particular, it provides more advisory estimations of the remaining lifetime of the gas pipeline.

• 한국수자원학회논문집
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• 제36권4호
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• pp.661-671
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• 2003

본 연구는 홍수위 계산에 있어서 도입되는 불확식성의 원인을 분석하고 정량화하여 확률론적 홍수위 계산을 실시함으로서 제방원류에 대한 제내지의 범람특성을 해석할 수 있는 모형을 개발하였다. 이를 위해서 홍수위에 영향을 미치는 각종 영향인자를 통계학적으로 분석하였고, 이들 인자를 부등류와 부정류 해석과정에 Monte Carlo 모의를 도입함으로써 홍수위에 미치는 영향을 정량화하였다. 개발된 모형의 검증을 위해 낙동강 유역의 현풍∼적포교구간에 적용하였다. 제내지로의 범람양상과 역류양상을 합리적으로 모의하였고 질량보존도 잘 모의하고 있는 것으로 나타났다. 또한 제내지 침수양상 모의시 붕괴폭, 붕괴시간 등의 불확실도를 고려하여 침수수심 및 침수면적을 산정하였다.