• International Journal of Highway Engineering
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• v.14 no.5
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• pp.189-199
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• 2012

PURPOSES: The purpose of this study is to propose a new methodology for developing statistical collision models and to show the validation results of the methodology. METHODS: A new modeling method of introducing variables into the model one by one in a multiplicative form is suggested. A method for choosing explanatory variables to be introduced into the model is explained. A method for determining functional forms for each explanatory variable is introduced as well as a parameter estimating procedure. A model selection method is also dealt with. Finally, the validation results is provided to demonstrate the efficacy of the final models developed using the method suggested in this study. RESULTS: According to the results of the validation for the total and injury collisions, the predictive powers of the models developed using the method suggested in this study were better than those of generalized linear models for the same data. CONCLUSIONS: Using the methodology suggested in this study, we could develop better statistical collision models having better predictive powers. This was because the methodology enabled us to find the relationships between dependant variable and each explanatory variable individually and to find the functional forms for the relationships which can be more likely non-linear.

• Journal of Astronomy and Space Sciences
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• v.28 no.1
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• pp.63-70
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• 2011

The needs for satellite formation flying are gradually increasing to perform the advanced space missions in remote sensing and observation of the space or Earth. Formation flying in low Earth orbit can perform the scientific missions that cannot be realized with a single spacecraft. One of the various techniques of satellite formation flying is the determination of the precise baselines between the satellites within the formation, which has to be in company with the precision validation. In this paper, the baseline of Gravity Recovery and Climate Experiment (GRACE) A and B was determined with the real global positioning system (GPS) measurements of GRACE satellites. And baseline precision was validated with the batch and sequential processing methods using K/Ka-band ranging system (KBR) biased range measurements. Because the proposed sequential method validate the baseline precision, removing the KBR bias with the epoch difference instead of its estimation, the validating data (KBR biased range) are independent of the data validated (GPS-baseline) and this method can be applied to the real-time precision validation. The result of sequential precision validation was 1.5~3.0 mm which is similar to the batch precision validation.

• Korean Journal of Pharmacognosy
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• v.40 no.2
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• pp.103-108
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• 2009

GCSB-5 preparation is a purified extract from a mixture of 6 medicinal plants(Acanthopanacis Cortex, Achyranthis Radix, Saposhnikoviae Radix, Cibotii Rhizoma, Glycine Semen Nigra, Eucommiae Cortex) that have been widely used for the treatment of various bone disorders. The aim of this study was to investigate HPLC analysis method and screening of standard compound on Saposhnikoviae Radix for quality standardization of a medicinal crude drug GCSB-5. Standard compound of Saposhnikoviae Radix was decided with cimifugin by isolation and instrumental analysis such as NMR. HPLC analysis method for the simultaneous determination of cimifugin was established for the quality control of the medicinal plants of Saposhnikoviae Radix species, GCSB-5 raw material and preparation. And validation of HPLC analysis methods were conformed for verification of HPLC methods by check to specificity, linearity, intra-day precision, inter-day precision and accuracy following ICH guideline.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.5
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• pp.541-547
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• 2010

The rigorous validation of the accuracy of metamodels is an important topic in research on metamodel techniques. Although a leave-k-out cross-validation technique involves a considerably high computational cost, it cannot be used to measure the fidelity of metamodels. Recently, the mean$_0$ validation technique has been proposed to quantitatively determine the accuracy of metamodels. However, the use of mean$_0$ validation criterion may lead to premature termination of a sampling process even if the kriging model is inaccurate. In this study, we propose a new validation technique based on the mean and variance of the response evaluated when sequential sampling method, such as maximum entropy sampling, is used. The proposed validation technique is more efficient and accurate than the leave-k-out cross-validation technique, because instead of performing numerical integration, the kriging model is explicitly integrated to accurately evaluate the mean and variance of the response evaluated. The error in the proposed validation technique resembles a root mean squared error, thus it can be used to determine a stop criterion for sequential sampling of metamodels.

• YAKHAK HOEJI
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• v.48 no.1
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• pp.60-64
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• 2004

Near-infrared (NIR) spectroscopy was used to determine rapidly and nondestructively the content of ambroxol in intact ambroxol tablets containing 30 mg (12.5％ m/m nominal concentration) by collecting NIR spectra in range 1100-1750 nm. The laboratory-made samples had 10.3∼15.9％ m/m nominal ambroxol concentration. The measurements were made by reflection using a fiber-optic probe and calibration was carried out by partial least square regression (PLSR) with autoscaling. Model validation was performed by randomly splitting the data set into calibration and validation data set (7 samples as a calibration data set and 5 samples as a validation data set). The developed NIR method gave results comparable to the known values of tablets in a laboratorial manufacturing Process, standard error of calibration (SEC) and standard error of prediction (SEP) being 0.49％ and 0.49％ m/m respectively. The method showed good accuracy and repeatability NIR spectroscopic determination in intact tablets allowed the potential use of real time monitoring for a running production process.

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.43-49
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• 2016

This paper presents a workflow validation method for data-intensive graphical workflow models using real-time workflow tracing mode on data-intensive workflow designer. In order to model and validate workflows, we try to divide as modes have editable mode and tracing mode on data-intensive workflow designer. We could design data-intensive workflow using drag and drop in editable-mode, otherwise we could not design but view and trace workflow model in tracing mode. We would like to focus on tracing-mode for workflow validation, and describe how to use workflow tracing on data-intensive workflow model designer. Especially, it is support data centered operation about control logics and exchange variables on workflow runtime for workflow tracing.

• Mass Spectrometry Letters
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• v.15 no.3
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• pp.149-157
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• 2024

The objective of the present study was to validate the analytical procedure for the quantitative determination of four trace metals (As, Cd, Pb, and Hg) in extracted fish lipids using Inductively Coupled Plasma-Mass Spectrometry, ICP-MS. The extracted lipids using Bligh and Dyer method were digested by means of microwave-assisted acid digestion and introduced into an optimized ICP-MS instrument. The validation of the analytical method was carried out in accordance with the international standards and guidelines outlined in the European Pharmacopeia (2022), which included specificity, selectivity, linearity, limit of detection, limit of quantification, precision, and accuracy. The linearity ranges of the calibration curves were R² > 0.999, while the relative standard deviation (%RSD) for precision was within 5%. All targeted trace metals have shown mean recoveries between 88.0%-114.9%. The obtained LOD and LOQ values for this analytical protocol indicated the ability to detect and quantify of As, Cd, Pb, and Hg at trace levels. The overall validation confirms the described analytical method was appropriate for routine analyses of As, Cd, Pb, and Hg in fish lipids.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.871-881
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• 2011

In this paper we propose a logistic regression method to estimate the survival function and the median survival time in interval-censored data. The proposed method is motivated by the data augmentation technique with no sacrifice in augmenting data. In addition, we develop a cross validation criterion to determine the size of data augmentation. We compare the proposed estimator with other existing methods such as the parametric method, the single point imputation method, and the nonparametric maximum likelihood estimator through extensive numerical studies to show that the proposed estimator performs better than others in the sense of the mean squared error. An illustrative example based on a real data set is given.

• The Korea Journal of Herbology
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• v.26 no.1
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• pp.103-110
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• 2011

Objective : For the standardization and quality control of eleutheroside E in Eleutherococcus species, HPLC analysis was performed and eleutherosdie E content was compared in 23 kinds of Eleutherococcus species collected from Korea and China. Methods : The content of eleutheroside E in stem bark of Eleutherococcus species collected from Korea and China were analyzed by HPLC. 0.5% phosphoric acid and acetonitrile was used as mobile solvent. Validation of HPLC analysis method was confirmed by analyzing specificity, linearity, precision and accuracy following ICH guideline. Results : Content of eleutheroside E was determined to be 1.0-1.6% and 0.5-0.8% in Korean and Chinese E. senticosus, respectively. Content of eleutheroside E in E. sessiliflorus was 0.7-1.1% and 0.2-0.4% respectively in Korean and Chinese origin. All calibration curves showed good linear regression. The method showed good precision and accuracy with intra-day and inter-day variations of 0.880-3.442% (RSD) and 0.606-3.328% (RSD), respectively, and average recovery was of 0.141-1.363% (RSD), for the eleutheroside E analyzed. Conclusion : These results might be used to establish a criterion of eleutheroside E in Eleutherococcus species.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.11
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• pp.485-491
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• 2006

In this paper, we study the problem of model selection for Support Vector Machine(SVM) predictor for short-term load forecasting. The model selection amounts to tuning SVM parameters, such as the cost coefficient C and kernel parameters and so on, in order to maximize the prediction performance of SVM. We propose that Cross-Validation method can be used as a model selection algorithm for SVM-based load forecasting technique. Through the various experiments on several data sets, we found that the difference between the prediction error of SVM using Cross-Validation and that of ideal SVM is less than 5%. This shows that SVM parameters for load forecasting can be efficiently tuned by using Cross-Validation.