• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.583-584
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• 2010

• Journal of the Korean Society for Precision Engineering
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• v.17 no.2
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• pp.114-120
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• 2000

Fossil power plant availability is significantly affected by gradual degradations of equipment as operation of the plant continues. It is quite important to determine whether or not to replace some equipment and when to replace the equipment. Performance calculation and analysis can provide the information. Robustness in the performance calculation can be increased by using verification ＆ validation of measured input data. We suggest new algorithm in which estimation relation for validated measurement can be obtained using correlation between measurements. Input estimation model is obtained using design data and acceptance measurement data of domestic 16 fossil power plant. The model consists of finding mostly correlated state variable in plant state and mapping relation based on the model and current state of power plant.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.2
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• pp.9-15
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• 2014

'Visual segment surface' means a surface that extends from the missed approach point of non precision approaches (or the decision altitude location for approaches with vertical guidance and precision approaches) to the threshold to facilitate the identification of and protection from obstacles in this visual segment of the approach. Validation is the necessary final quality assurance step in the procedure design process, prior to publication. The purpose of validation is the verification of all obstacle and navigation data, and assessment of flyability of the procedure. This paper shows how to apply the protection for the visual segment of the approach procedure, and the results of the validation for visual segment surface conducted at an airport.

• Journal of Navigation and Port Research
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• v.39 no.1
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• pp.15-21
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• 2015

In high precision positioning systems based on GNSS, ambiguity resolution is an important procedure. Correct ambiguity leads to positioning results which have high precision between millimeters and centimeters. However, when the ambiguity is determined incorrectly, ensuring accuracy and precision of the positioning result is impossible. An ambiguity validation test is required to obtain correct ambiguity when ambiguity resolution is performed based on the ILS (Integer Least Squares), which shows the best performance in point of theory and experiment when compared with other methods such as IR (Integer Rounding) and IB (Integer Bootstrapping). Comparison between the candidates of the validation test is needed to judge ambiguity correctly, because ILS searches for candidates of integer ambiguity, unlike other methods which calculate only one integer ambiguity. We analyzed the experimental performance of ambiguity validation tests. R-ratio, F-ratio and W-ratio were adopted for analysis. The performance of validation tests was evaluated by classifying normal operation, detection, missed detection and false alarm. As a result, strengths and weaknesses of validation tests was showed to experimental. we concluded that validation tests must be selected according to environment.

• Korean Journal of Pharmacognosy
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• v.51 no.1
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• pp.78-85
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• 2020

In this study, we shortly introduced the HPLC method validation guideline for the analysis of functional food which was released from the Ministry of Food and Drug Safety of Korea in Dec 2018. The HPLC method validation was performed through the aforementioned HPLC method validation guideline in order to quantitate scopoletin content from the hot-water extract powder of Artemisia annua Linné. The HPLC method was validated by evaluating specificity, accuracy, precision, limit of quantitation and linearity. All parameters were in the suitable ranges which are designated in the guideline, which indicated the current HPLC method is reliable to quantitate the scopoletin content from the hot-water extract of A. annua.

• Journal of Digestive Cancer Research
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• v.11 no.3
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• pp.157-164
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• 2023

Prediction is a significant topic in clinical research. The development and validation of a prediction model has been increasingly published in clinical research. In this review, we investigated analytical methods and validation schemes for a clinical prediction model used in digestive cancer research. Deep learning and logistic regression, with split-sample validation as an internal or external validation, were the most commonly used methods. Furthermore, we briefly introduced and summarized the advantages and disadvantages of each method. Finally, we discussed several points to consider when conducting prediction model studies.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.547-548
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• 2008

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.259-260
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• 2012

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.10a
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• pp.130-130
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• 2003

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.1087-1088
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• 2010