• Journal of Information Processing Systems
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• v.12 no.1
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• pp.109-128
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• 2016

This paper presents a new combined forecasting method that is guided by the soft set theory (CFBSS) to predict business failures with different sample sizes. The proposed method combines both qualitative analysis and quantitative analysis to improve forecasting performance. We considered an expert system (ES), logistic regression (LR), and support vector machine (SVM) as forecasting components whose weights are determined by the receiver operating characteristic (ROC) curve. The proposed procedure was applied to real data sets from Chinese listed firms. For performance comparison, single ES, LR, and SVM methods, the combined forecasting method based on equal weights (CFBEWs), the combined forecasting method based on neural networks (CFBNNs), and the combined forecasting method based on rough sets and the D-S theory (CFBRSDS) were also included in the empirical experiment. CFBSS obtains the highest forecasting accuracy and the second-best forecasting stability. The empirical results demonstrate the superior forecasting performance of our method in terms of accuracy and stability.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.870-877
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• 2006

Recently, failures of equipments are linked directly to extensive damages of human lives or financial losses from the increasing uses of train control equipments utilizing computers. Then safety activities have to progress for guaranteeing safety during the system life-cycle. In this paper, we examine the methods for risk analysis and assessment of safety activities and propose optimized one method for risk assessment. There are original risk assessment methods; risk graph and risk matrix method under the qualitative analysis, IRF(Individual Risk Formula) calculations and statistical calculations method under the quantitative analysis. Best-Practice(BP) risk analysis method is proposed for combining advantages of the qualitative and the quantitative analysis. In the comparison of risk graph and risk matrix method for safety estimation, BP method has no applications published up to now, but we can expect that this method will be utilized widely for the risk assessment due to various strong points.

• Food Science and Biotechnology
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• v.17 no.3
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• pp.573-577
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• 2008

$^1H$-Nuclear magnetic resonance (NMR) spectrometry was applied to the quantitative analysis of coumarins in the roots of Angelica gigas without any chromatographic purification. The experiment was performed by the analysis of each singlet germinal methyl, which was well separated in the range of 1.0-2.0 ppm in the $^1H$-NMR spectrum. The quantity of the compounds was calculated by the ratio of the intensity of each compound to the known amount of internal standard (dimethyl terephthalate). These results were compared with the conventional gas chromatography (GC) method. The contents of decursin and decursinol angelate in A. gigas were determined $1.98{\pm}0.07$, $1.13{\pm}0.08%$ in quantitative $^1H$-NMR method and $2.06{\pm}0.24$, $1.17{\pm}0.24%$ in GC method, respectively. The advantages of quantitative $^1H$-NMR analysis are that can be analyzed to identify and quantify, and no reference compounds required for calibration curves. Besides, it allows rapid and simple quantification for coumarins with an analysis time for only 10 min without any preprocessing.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.10
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• pp.1291-1296
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• 2013

Risk-based inspection (RBI) is a well-known method that is used to optimize inspection activities based on risk analysis in order to identify the high-risk components of major facilities such as power plants. RBI, when implemented and maintained properly, improves plant reliability and safety while reducing unplanned outages and repair costs. Risk is given by the product of the probability of failure (POF) and the consequence of failure (COF). A semi-quantitative method is generally used for risk assessment. Semi-quantitative risk assessment complements the low accuracy of qualitative risk assessment and the high expense and long calculation time of quantitative risk assessment. The first step of RBI is to identify important failure modes and causes in the equipment. Once these are defined, the POF and COF can be assessed for each failure. During POF and COF assessment, an effective inspection method and range can be easily found. In this paper, the calculation of the POF is improved for accurate risk assessment. A modified semi-quantitative risk assessment was carried out for boiler facilities of thermal power plants, and the next maintenance schedules for the equipment were decided.

• Mass Spectrometry Letters
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• v.5 no.3
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• pp.63-69
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• 2014

In this study, we present a new isotope-coded carbamidomethylation (iCCM)-based quantitative proteomics, as a complementary strategy for conventional isotope labeling strategies, with providing the simplicity, ease of use, and robustness. In iCCM-based quantification, two proteome samples can be separately isotope-labeled by means of covalently reaction of all cysteinyl residues in proteins with iodoacetamide (IAA) and its isotope (IAA-$^{13}C_2$, $D_2$), denoted as CM and iCCM, respectively, leading to a mass shift of all cysteinyl residues to be + 4 Da. To evaluate iCCM-based isotope labeling in proteomic quantification, 6 protein standards (i.e., bovine serum albumin, serotransferrin, lysozyme, beta-lactoglobulin, beta-galactosidase, and alpha-lactalbumin) isotopically labeled with IAA and its isotope, mixed equally, and followed by proteolytic digestion. The resulting CM-/iCCM-labeled peptide mixtures were analyzed using a nLC-ESI-FT orbitrap-MS/MS. From our experimental results, we found that the efficiency of iCCM-based quantification is more superior to that of mTRAQ, as a conventional nonisobaric labeling method, in which both of a number of identified peptides from 6 protein standards and the less quantitative variations in the relative abundance ratios of heavy-/light-labeled corresponding peptide pairs. Finally, we applied the developed iCCM-based quantitative method to lung cancer serum proteome in order to evaluate the potential in biomarker discovery study.

• Journal of Korean Society for Quality Management
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• v.50 no.4
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• pp.831-842
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• 2022

Purpose: This study carried out the Quality by Design (QbD)6σ process to verify the effectiveness and equivalence of the finished D-antigen quantitative test method, and compared the OFAT-based method validation and test result acceptance criteria with the Analytical Quality by Design (AQbD)-based method validation and test method. This is a study on how to reduce the risk of delay in permit change by increasing the reliability of permit data in the existing method by statistically analyzing the results. Methods: With the QbD6σ process, the effectiveness and equivalence of the D-antigen quantitative test method were verified with the data of the existing test method and the new test method. Results: Method validation tests are performed based on AQbD. Critical Method Parameters are identified through risk assessment, and single/combined actions are verified by designing and performing tests for Critical Method Parameters (analysis of variance, full factorial design method). Method validation can be effectively accomplished with the QbD6σ process. Conclusion: The use of QbD6σ can be used to achieve satisfactory results for both pharmaceutical companies and regulators by using appropriate statistical analytical methods for method validation as required by regulatory agencies.

• Journal of Biomedical Engineering Research
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• v.16 no.3
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• pp.359-366
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• 1995

The parameter, B/A, quantifies nonlinearity of the pressure-density relationship of propagation medium. This study investigated quantitative evaluation technique for healing fractured bones using this ultrasonic nonlinear parameter, B/A, obtained by the second harmonic amplitude method. A series of fundamental experiments were performed on cylinder phantoms made of aluminium, which demonstrated potential capability of nonlinear parameter B/A in the diagnosis of healing fractured bones using ultrasound.

• Journal of the Korean Society of Food Science and Nutrition
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• v.1 no.1
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• pp.33-35
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• 1972

The curcumin method was adopted in this research for quantitative analysis of boron in plants. An experiment if this method is suitable to present conditions of our laboratory led us to the following conclusions. 1. In making ashes the addition of 0.5ml saturated $Ba(OH)_2$ solution to boron $1{\gamma}$. could completely prevent it from volatilizing. 2. The soft glass ware made in Korea was unfit for this experiment because of the differences in quality. The polyethylene cup was desirable for the quantitative analysis of boron.

• YAKHAK HOEJI
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• v.4 no.1
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• pp.47-49
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• 1959

Another application of the new quantitative analytical method of prussic acid by "Microdiffusion analysis" for the determination of prussic acid in human blood was studied. The blood containing potassium cyanide was dropped in outer room of unit, and then N-sulfuric acid was added. The liberated HCN gas was absorbed into nickel sulfate solution of inner room, afterward, absorbed prussic acid was determined with EDTA by residual titration. The result was coincided with the result of Liebig Denigs' method at ordinary temperature.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.428-432
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• 2003

Quantitative Feedback Theory (QFT) is one of most effective methods of robust controller design and can be considered as a suitable method for systems with parametric uncertainties. Particularly it allows us to obtain controllers less conservative than other methods like $H_{\infty}$ and ${\mu}$-synthesis. In QFT method, we transform all the uncertainties and desired specifications to some boundaries in Nichols chart and then we have to find the nominal loop transfer function such that satisfies the boundaries and has the minimum high frequency gain. The major drawback of the QFT method is that there is no effective and useful method for finding this nominal loop transfer function. The usual approach to this problem involves loop-shaping in the Nichols chart by manipulating the poles and zeros of the nominal loop transfer function. This process now aided by recently developed computer aided design tools proceeds by trial and error and its success often depends heavily on the experience of the loop-shaper. Thus for the novice and First time QFT user, there is a genuine need for an automatic loop-shaping tool to generate a first-cut solution. In this paper, we approach the automatic QFT loop-shaping problem by using an algorithm involving Linear Programming (LP) techniques and Genetic Algorithm (GA).