• Journal of the Korean Society of Safety
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• v.15 no.4
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• pp.134-138
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• 2000

Signal words such as DANGER, WARNING, CAUTION, etc. have been used in order to transmit a potential hazard easily and quickly. But they were applied to a number of the sites without consistency. Thus, this study took Quantification Method and Cluster Analysis in order to judge the signal words corresponding to the urgency of situations, and to analyze whether signal words are used properly or not. According to the result of Quantification Method II signal words were most affected by Understanding, Severity and Likelihood in both student group and industrial worker group. And in Quantification Method III CAUTION corresponded to Immediacy and Understanding whereas NOTICE did to Receptivity, WARNING, DEADLY and DANCER did to Likelihood, Dangerousness and Severity. Finally, Cluster Analysis showed that CAUTION and NOTICE were recognized as similar words.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.206-211
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• 2006

The quantification analysis problem is that how the m entities that have n characteristics can be linked to p-dimension space to reflect the similarity of each entity In this paper, the optimization approach for the quantification analysis problem using neural networks is suggested, and the performance is analyzed The computation of average variation volume by mean field theory that is analytical approximated mobility of a molecule system and the annealed mean field neural network approach are applied in this paper for solving the quantification analysis problem. As a result, the suggested approach by a mean field annealing neural network can obtain more optimal solution than the eigen value analysis approach in processing costs.

• The Transactions of the Korea Information Processing Society
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• v.2 no.3
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• pp.417-424
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• 1995

This paper describes MFT(Mean Field Theory) neural network with continuous with continuous variables is applied to quantification analysis problem. A quantification analysis problem, one of the important problems in statistics, is NP complete and arises in the optimal location of objects in the design space according to the given similarities only. This paper presents a MFT neural network with continuous variables for the quantification problem. Starting with reformulation of the quantification problem to the penalty problem, this paper propose a "one-variable stochastic simulated annealing(one-variable SSA)" based on the mean field approximation. This makes it possible to evaluate of the spin average faster than real value calculating in the MFT neural network with continuous variables. Consequently, some experimental results show the feasibility of this approach to overcome the difficulties to evaluate the spin average value expressed by the integral in such models.ch models.

• Journal of the Korean Statistical Society
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• v.25 no.4
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• pp.589-601
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• 1996

Geometric approach to extend the classical two-set theory of canonical correlation analysis to three or more sets is considered. It provides statistical graphs to represent the data in a low dimensional space. Procedures are developed for computing the canonical variables and the corresponding properties are investigated. The solution is equivalent to that of the usual problem in the case of two sets. Goodness-of-fit of the proposed plots is studied and a numerical example is included.

• Biomedical Science Letters
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• v.26 no.4
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• pp.275-287
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• 2020

Since its introduction in the forensic field, quantitative PCR (qPCR) has played an essential role in DNA analysis. Quality of DNA should be evaluated before short tandem repeat (STR) profiling to obtain reliable results and reduce unnecessary costs. To this end, various human DNA quantification kits have been developed. Among these kits, the PowerQunat® System was designed not only to determine the total amount of human DNA and human male DNA from a forensic evidence item, but also to offer data about degradation of DNA samples. However, a crucial limitation of the PowerQunat® System is its high cost. Therefore, to minimize the cost of DNA quantification, we evaluated kit performance using a reduced volume of reagents (1/2-volume) using DNA samples of varying types and concentrations. Our results demonstrated that the low-volume method has almost comparable performance to the manufacturer's method for human DNA quantification, human male DNA quantification, and DNA degradation index. Furthermore, using a reduced volume of regents, it is possible to run 2 times more reactions per kit. We expect the proposed low-volume method to cut costs in half for laboratories dealing with large numbers of DNA samples.

• Journal of the Korean Data and Information Science Society
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• v.15 no.3
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• pp.515-521
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• 2004

Categorical data are mostly found in oriental medical research. The nonlinear canonical correlation analysis does not assume an interval level of measurement. In this paper, we apply nonlinear canonical correlation analysis to quantification and explain how similar sets of variables are to one another for paralysis disease data.

• The Korean Journal of Applied Statistics
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• v.12 no.2
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• pp.517-525
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• 1999

본 논문에서는 정준판별분석에서 분석자의 사전지식을 고려한 조건부 계량화(partial quantification)를 제안하고 있다. 연관된 수식을 라그랑지 승수법으로 유도하였으며 SAS/IML을 이용한 프로그램과 예제를 간략히 설명하였다.

• Journal of Microbiology and Biotechnology
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• v.33 no.3
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• pp.348-355
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• 2023

Epifluorescence microscopy with image analysis was evaluated as a biofilm quantification method (i.e., quantification of surface area colonized by biofilms), in comparison with crystal violet (CV) staining. We performed different experiments to generate multispecies biofilms with natural and artificial bacterial assemblages. First, four species were inoculated daily in 16 different sequences to form biofilms (surface colonization, 0.1%-56.6%). Second, a 9-species assemblage was allowed to form biofilms under 10 acylase treatment episodes (33.8%-55.6%). The two methods comparably measured the quantitative variation in biofilms, exhibiting a strong positive relationship (R² ≥ 0.7). Moreover, the two methods exhibited similar levels of variation coefficients. Finally, six synthetic and two natural consortia were allowed to form biofilms for 14 days, and their temporal dynamics were monitored. The two methods were comparable in quantifying four biofilms colonizing ≥18.7% (R² ≥ 0.64), but not for the other biofilms colonizing ≤ 3.7% (R² ≤ 0.25). In addition, the two methods exhibited comparable coefficients of variation in the four biofilms. Microscopy and CV staining comparably measured the quantitative variation of biofilms, exhibiting a strongly positive relationship, although microscopy cannot appropriately quantify the biofilms below the threshold colonization. Microscopy with image analysis is a promising approach for easily and rapidly estimating absolute quantity of multispecies biofilms.

• Journal of the Korean Society of Safety
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• v.38 no.6
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• pp.72-78
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• 2023

The purpose of this paper is to derive a quantified approach for Operator Manual Actions (OMAs) based on the existing fire Human Reliability Analysis (HRA) methodology developed by the Korea Atomic Energy Research Institute (KAERI). The existing fire HRA method was reviewed, and supplementary considerations for OMA quantification were established through a comparative analysis with NUREG-1852 criteria and the review of the existing literature. The OMA quantification approach involves a timeline that considers the occurrence of Multiple Spurious Operations (MSOs) during a Main Control Room Abandonment (MCRA) determination and movement towards the Remote Shutdown Panel (RSP) in the event of a Main Control Room (MCR) fire. The derived failure probability of an OMA from the approach proposed in this paper is expected to enhance the understanding of its reliability. Therefore, it allows moving beyond the deterministic classification of "reliable" or "unreliable" in NUREG-1852. Also, in the event of a nuclear power plant fire where multiple OMAs are required within a critical time range, it is anticipated that the OMA failure probability could serve as a criterion for prioritizing OMAs and determining their order of importance.

• Mass Spectrometry Letters
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• v.4 no.2
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• pp.25-29
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• 2013

Proteomics for biomarker validation needs high throughput instrumentation to analyze huge set of clinical samples for quantitative and reproducible analysis at a minimum time without manual experimental errors. Sample preparation, a vital step in proteomics plays a major role in identification and quantification of proteins from biological samples. Tryptic digestion a major check point in sample preparation for mass spectrometry based proteomics needs to be more accurate with rapid processing time. The present study focuses on establishing a high throughput automated online system for proteolytic digestion and desalting of proteins from biological samples quantitatively and qualitatively in a reproducible manner. The present study compares online protein digestion and desalting of BSA with conventional off-line (in-solution) method and validated for real time sample for reproducibility. Proteins were identified using SEQUEST data base search engine and the data were quantified using IDEALQ software. The present study shows that the online system capable of handling high throughput samples in 96 well formats carries out protein digestion and peptide desalting efficiently in a reproducible and quantitative manner. Label free quantification showed clear increase of peptide quantities with increase in concentration with much linearity compared to off line method. Hence we would like to suggest that inclusion of this online system in proteomic pipeline will be effective in quantification of proteins in comparative proteomics were the quantification is really very crucial.