• Korean Journal of Food Science and Technology
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• v.35 no.6
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• pp.1053-1059
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• 2003

This study aimed to determine the amount of vitamin C from vegetable & fruit juice by high performance liquid chromatograhy (HPLC). Components for estimation of measurement uncertainty associated with the analysis of vitamin C, such as standard weight, purity, molecular weight, dilution of standard solution, calibration curve, recovery, and precision, were importantly applied. The estimation of uncertainty obtained with systematic and random error based on the GUM (Guide to the expression of uncertainty in measurement) and EURACHEM document with mathematical calculation and statistical analysis. The components, evaluated ty either Type A or Type B methods, were combined to produce an overall value of uncertainty known as the combined standard uncertainty. An expanded uncertainty was obtained by multiplying the combined standard uncertainty with a coverage factor (k) calculated from the effective degree of freedom. The content of vitamin C from vegetable and fruit juice was 27.53 mg/100g and the expanded uncertainty by multiplying by the coverage factor (k, 2.06) was 0.63 mg/100g at a 95% confidence level. It was concluded that the main sources were, in order of recovery and precision, weight and purity of the reference material, dilution of the standard solution, and calibration curve. Careful experiments on other higher uncertainties is further needed in addition to better personal proficiency in sample analysis in terms of accuracy and precision.

• Journal of Chest Surgery
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• v.54 no.2
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• pp.88-98
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• 2021

Background: This study aimed to develop a new risk prediction model for operative mortality in a Korean cohort undergoing heart valve surgery using the Korea Heart Valve Surgery Registry (KHVSR) database. Methods: We analyzed data from 4,742 patients registered in the KHVSR who underwent heart valve surgery at 9 institutions between 2017 and 2018. A risk prediction model was developed for operative mortality, defined as death within 30 days after surgery or during the same hospitalization. A statistical model was generated with a scoring system by multiple logistic regression analyses. The performance of the model was evaluated by its discrimination and calibration abilities. Results: Operative mortality occurred in 142 patients. The final regression models identified 13 risk variables. The risk prediction model showed good discrimination, with a c-statistic of 0.805 and calibration with Hosmer-Lemeshow goodness-of-fit p-value of 0.630. The risk scores ranged from -1 to 15, and were associated with an increase in predicted mortality. The predicted mortality across the risk scores ranged from 0.3% to 80.6%. Conclusion: This risk prediction model using a scoring system specific to heart valve surgery was developed from the KHVSR database. The risk prediction model showed that operative mortality could be predicted well in a Korean cohort.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.4D
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• pp.511-518
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• 2011

Truck weight data are essential for road infrastructure design, maintenance and management. WIM (Weigh-In-Motion) system provides highway planners, researchers and officials with statistical data. Recently high speed WIM data also uses to support a vehicle weight regulation and enforcement activities. This paper aims at developing axle load estimating models with high speed WIM data collected from national highway. We also suggest a method to estimate axle load using simple regression model for WIM system. The model proposed by this paper, resulted in better axle load estimation in all class of vehicle than conventional model. The developed axle load estimating model will used for on-going or re-calibration procedures to ensure an adequate level of WIM system performance. This model can also be used for missing axle load data imputation in the future.

• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.835-845
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• 2013

Travel-time is considered the most typical and preferred traffic information for intelligent transportation systems(ITS). This paper proposes a real-time travel-time prediction method for a national highway. In this paper, the K-nearest neighbor(KNN) method is used for travel time prediction. The KNN method (a nonparametric method) is appropriate for a real-time traffic management system because the method needs no additional assumptions or parameter calibration. The performances of various models are compared based on mean absolute percentage error(MAPE) and coefficient of variation(CV). In real application, the analysis of real traffic data collected from Korean national highways indicates that the proposed model outperforms other prediction models such as the historical average model and the Kalman filter model. It is expected to improve travel-time reliability by flexibly using travel-time from the proposed model with travel-time from the interval detectors.

• Bulletin of the Korean Chemical Society
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• v.31 no.7
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• pp.1907-1914
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• 2010

A novel catalytic kinetic method is proposed for the determination of Se(IV), Se(VI) and total inorganic selenium in water based on the catalytic effect of Se(IV) on the reduction of bromate by p-nitrophenylhydrazine at pH 3.0. The generated bromine, $Br_2$ or $Cl_2$ plus $Br_2$ in 0.1 M NaCl (or NaBr) environment efficiently decolorized Calmagite and the reaction was monitored spectrophotometrically at 523 nm as a function of time. In this indicator reaction, bromide acted as an activator for the catalysis of selenium (IV) and a reducing agent for selenium (VI) at pH 3.0, which allowed the determination of total selenium. The fixed time method was adopted for the determination and speciation of inorganic selenium. Under the optimum conditions, the calibration graph are linear in the range 1 - 35 ${\mu}gL^{-1}$ of Se(IV) for the fixed time method at $25^{\circ}C$. The detection limit based on statistical $3S_{blank}$/m-criterion was 0.215 ${\mu}gL^{-1}$ for the fixed time method (7 min). All of the variables that affect the sensitivity at 523 nm were investigated, and the optimum conditions were established. The interference effect of various cations and anions on the Se (IV) determination was also studied. The selectivity of the selenium determination was greatly improved with the use of the strongly cation exchange resin such as Amberlite IR120 plus. The proposed kinetic method was validated statistically and through recovery studies in natural water samples. The RSDs for ten replicate measurements of 5, 15 and 25 ${\mu}gL^{-1}$ of Se(IV) and Se(VI) was changed between 2.1 - 4.85%. Analyses of a certified standard reference material (NIST SRM 1643e) for selenium using the fixed-time method showed that the proposed kinetic method has good accuracy. Se(IV), Se(VI) and total inorganic selenium in environmental water samples have been successfully determined by this method after selective reduction of Se(VI) to Se(IV).

• Journal of the Korea Concrete Institute
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• v.23 no.4
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• pp.495-501
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• 2011

The load combinations in current KCI Design Code are determined with reference to those in ACI 318-05, which adopts the LRFD (load and resistance factor design) format. The load and resistance factors in LRFD format should be determined to meet the required levels of reliability index or probability of failure for various predetermined failure modes, which are also based on the statistical data reflecting locality and contemporary situation. However, the current KCI Design Code has been written utilizing foreign data, because of insufficiency in accrued data in Korea. This study considered the current safety levels of KCI Code based on published domestic data to evaluate appropriateness of the current KCI regulations. Based on the calibrated reliability index of the existing Code, the new resistance factors are suggested. The results presented in this paper can be considered as a basic research for establishment of unique design format for future Korean Codes.

• Journal of Sensor Science and Technology
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• v.12 no.1
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• pp.34-43
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• 2003

In this study, we implemented the measurement of pH, $pO_2$, $pCO_2$ of the arterial blood on a portable blood gas analysis system. This system is consist of two parts of hardware and software. The hardware part is divided into a fluidic mechanism and an electronic circuit unit. The system program is composed of operating, washing, correcting, and measuring routines. Both of 1-point and 2-point calibration schemes were used to enhance the accuracy of the measurement. In order to evaluate the performance of the developed system, we measured and performed statistical analysis on the characteristics of the sensing electrode response. As a result, coefficient variation was within 1.12, and maximum error was within 1.298%. We confirmed development possibility of portable blood gas analyzer.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.281-290
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• 2007

Linear estimator, a weighted sum of the sample observation, is commonly adopted to estimate the finite population parameters such as population totals in survey sampling. The weight for a sampled unit is often constructed by multiplying the base weight, which is the inverse of the first-order inclusion probability, by an adjustment term that takes into account of the auxiliary information obtained throughout the population. The linear estimator using the weight adjustment is often more efficient than the one using only the bare weight, but its valiance estimation is more complicated. We discuss variance estimation for a general class of weight-adjusted estimator. By identifying that the weight-adjusted estimator can be viewed as a function of estimated nuisance parameters, where the nuisance parameters were used to incorporate the auxiliary information, we derive a linearization of the weight-adjusted estimator using a Taylor expansion. The method proposed here is quite general and can be applied to wide class of the weight-adjusted estimators. Some examples and results from a simulation study are presented.

• Journal of Biosystems Engineering
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• v.27 no.3
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• pp.259-266
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• 2002

It is crucial to know spatial soil variability for precision farming. However, it is time-consuming, and difficult to measure spatial soil properties. Therefore, there are needs fur sensing technology to estimate spatial soil variability, and for electronic mapping technology to store, manipulate and process the sampled data. This research was conducted to develop a real-time soil organic matter sensor and an electronic mapping system. A soil organic matter sensor was developed with a spectrophotometer in the 900∼1,700 nm range. It was designed in a penetrator type to measure reflectance of soil at 15cm depth. The signal was calibrated with organic matter content (OMC) of the soil which was sampled in the field. The OMC was measured by the Walkeley-Black method. The soil OMCs were ranged from 0.07 to 7.96%. Statistical partial least square and principle component regression analyses were used as calibration methods. Coefficient of determination, standard error prediction and bias were 0.85 0.72 and -0.13, respectively. The electronic mapping system was consisted of the soil OMC sensor, a DGPS, a database and a makeshift vehicle. An algorithm was developed to acquire data on sampling position and its OMC and to store the data in the database. Fifty samples in fields were taken to make an N-fertilizer dosage map. Mean absolute error of these data was 0.59. The Kring method was used to interpolate data between sampling nodes. The interpolated data was used to make a soil OMC map. Also an N-fertilizer dosage map was drawn using the soil OMC map. The N-fertilizer dosage was determined by the fertilizing equation recommended by National Institute of Agricultural Science and Technology in Korea. Use of the N-fertilizer dosage map would increase precision fertilization up to 91% compared with conventional fertilization. Therefore, the developed electronic mapping system was feasible to not only precision determination of N-fertilizer dosage, but also reduction of environmental pollution.

• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.855-866
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• 2008

Recently many small area estimation methods using the lattice data analysis have been studied and known that they have good performances. In the case of using the lattice data which is mainly used for small area estimation, the choice of better neighborhood information system is very important for the efficiency of the data analysis. Recently Lee and Shin (2008) compared and analyzed some neighborhood information systems based on GIS methods. In this paper, we evaluate the effect of various neighborhood information systems which were suggested by Lee and Shin (2008). For comparison of the estimators, MSE, Coverage, Calibration, Regression methods are used. The number of unemployment in Economic Active Population Survey(2001) is used for the comparison.