• Journal of Applied Biological Chemistry
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• v.65 no.3
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• pp.195-202
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• 2022

Soybean (Glycine max L.) leaves have been researched as functional food stuff actively, but there is no validation method to control quality of soybean leaves (SL). In this study, we annotated seven kaempferol derivatives to confirm camelliaside A as index metabolite in SL using UHPLC-ESI-TOF-MS. HPLC-UVD validation method of camelliaside A in hot-water extract of SL was established according to validation guideline of functional foods from the Ministry of Food and Safety of Korea. The HPLC-UVD method was validated with reliable parameters for examining specificity, accuracy, precision, limit of detection and quantification and linearity. The established method gave the suitable ranges to qunatitate camelliaside A from the hot-water extract of soybean leaves.

• Geomechanics and Engineering
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• v.28 no.5
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• pp.437-454
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• 2022

The hydro-mechanical (HM) two-way sequential coupling in the TOUGH2-FLAC3D linking algorithm is validated completely and successfully in both M to H and H to M directions, which are initiated by mechanical surface loading for geomechanical validation and hydrological groundwater pumping for hydrogeological validation, respectively. For such complete and successful validation, a TOUGH2-FLAC3D linked numerical model is developed first by adopting the TOUGH2-FLAC3D linking algorithm, which uses the two-way (fixed-stress split) sequential coupling scheme and the implicit backward time stepping method. Two geomechanical and two hydrogeological validation problems are then simulated using the linked numerical model together with basic validation strategies and prerequisites. The second geomechanical and second hydrogeological validation problems are also associated with the Mandel effect and the Noordbergum and Rhade effects, respectively, which are three phenomenally well-known but numerically challenging HM effects. Finally, sequentially coupled numerical solutions are compared with either analytical solutions (verification) or fully coupled numerical solutions (benchmarking). In all the four validation problems, they show almost perfect to extremely or very good agreement. In addition, the second geomechanical validation problem clearly displays the Mandel effect and suggests a proper or minimum geometrical ratio of the height to the width for the rectangular domain to maximize agreement between the numerical and analytical solutions. In the meantime, the second hydrogeological validation problem clearly displays the Noordbergum and Rhade effects and implies that the HM two-way sequential coupling scheme used in the linked numerical model is as rigorous as the HM two-way full coupling scheme used in a fully coupled numerical model.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.949-954
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• 2009

The autoregressive process is applied in this paper to kernel regression in order to infer nonlinear models for predicting responses. We propose a kernel method for the autoregressive data which estimates the mean function by kernel machines. We also present the model selection method which employs the cross validation techniques for choosing the hyper-parameters which affect the performance of kernel regression. Artificial and real examples are provided to indicate the usefulness of the proposed method for the estimation of mean function in the presence of autocorrelation between data.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.1
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• pp.108-114
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• 2014

This paper describes a method to set an intensity-based initial validation gate for tracking filter while preserves the ability of tracking a target with maximum speed. First, we collected real data set of signal versus distance of an airplane target. And at each data point, we computed maximum distance the target can move. And a function is modeled to expect the maximum moving pixels on the lateral direction based on the intensity of the detected target in IR image sequence. The initial prediction error covariance can be computed using this function to decide the size of the initial validation gate. The simulation results show the proposed method can set the appropriate initial validation gates to track the targets with the maximum speed.

• 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.

• Journal of Microbiology and Biotechnology
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• v.21 no.1
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• pp.100-108
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• 2011

A method for the rapid detection and quantification of Newcastle disease virus (NDV) produced in an animal cell culture-based production system was developed to enhance the speed of the NDV vaccine manufacturing process. A SYBR Green I-based real-time RT-PCR was designed with a conventional, inexpensive RT-PCR kit targeting the F gene of the NDV LaSota strain. The method developed in this study was validated for specificity, accuracy, precision, linearity, limit of detection (LOD), limit of quantification (LOQ), and robustness. The validation results satisfied the predetermined acceptance criteria. The validated method was used to quantify virus samples produced in an animal cell culture-based production system. The method was able to quantify the NDV samples from mid- or late-production phases, but not effective on samples from the early-production phase. For comparison with other quantifiable methods, immunoblotting, plaque assay, and tissue culture infectious dose 50 ($TCID_{50}$) assay were also performed with the NDV samples. The results demonstrated that the real-time RT-PCR method is suitable for the rapid quantification of virus particles produced in an animal cell-culture-based production system irrespective of viral infectivity.

• Communications for Statistical Applications and Methods
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• v.15 no.2
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• pp.283-292
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• 2008

Smoothing parameter or bandwidth plays a key role in nonparametric classification based on kernel density estimation. We consider choosing smoothing parameter in nonparametric classification, which optimize the Bayes risk. Hall and Kang (2005) clarified the theoretical properties of smoothing parameter in terms of minimizing Bayes risk and derived the optimal order of it. Bootstrap method was used in their exploring numerical properties. We compare cross-validation and bootstrap method numerically in terms of optimal order of bandwidth. Effects on misclassification rate are also examined. We confirm that bootstrap method is superior to cross-validation in both cases.

• The KIPS Transactions:PartC
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• v.14C no.4
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• pp.313-320
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• 2007

In this paper, we propose a method to analyze security vulnerabilities of MS word-processor by checking the validation of its input files. That is, this study is to detect some vulnerabilities in the input file of the word processor by analyzing the header information of its input file. This validation test can not be conducted by the existing software fault injection tools including Holodeck and CANVAS. The proposed method can be also applied to identify the input file vulnerabilities of Hangul and Microsoft Excel which handle a data file with a header as an input. Moreover, our method can provide a means for assessing the fault tolerance and trustworthiness of the target software.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.190-194
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• 2023

By looking the importance of communication, data delivery and access in various sectors including governmental, business and individual for any kind of data, it becomes mandatory to identify faults and flaws during cyber communication. To protect personal, governmental and business data from being misused from numerous advanced attacks, there is the need of cyber security. The information security provides massive protection to both the host machine as well as network. The learning methods are used for analyzing as well as preventing various attacks. Machine learning is one of the branch of Artificial Intelligence that plays a potential learning techniques to detect the cyber-attacks. In the proposed methodology, the Decision Tree (DT) which is also a kind of supervised learning model, is combined with the different cross-validation method to determine the accuracy and the execution time to identify the cyber-attacks from a very recent dataset of different network attack activities of network traffic in the UNSW-NB15 dataset. It is a hybrid method in which different types of attributes including Gini Index and Entropy of DT model has been implemented separately to identify the most accurate procedure to detect intrusion with respect to the execution time. The different DT methodologies including DT using Gini Index, DT using train-split method and DT using information entropy along with their respective subdivision such as using K-Fold validation, using Stratified K-Fold validation are implemented.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1447-1448
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• 2011

The CSPE cables are used for three years in nuclear power plant. The accelerated thermal aging of chloro sulfonate polyethylene(CSPE) jacket of test cables were carried out for the period equal to 10, 20 and 30 years in air at 90 and $100^{\circ}C$, respectively. The electrical volume resistivity, density, XPS, FE-SEM, EDS and XRF of the accelerated thermal aging of CSPE were measured. The validation of condition monitering method of accelerated thermal aging CSPE was estimated by them. The best validation of condition monitoring method of accelerated aging CSPE is electrical volume resistivity because change thermal of the specimen showed distinction.