• Journal of Korean Society for Quality Management
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• v.42 no.3
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• pp.291-300
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• 2014

Purpose: The purpose of this study is to provide a statistical method from the data of ASRP's results and to apply to the reliability assessment of 155mm propelling charge, KM4A2. Methods: The accumulated data through ASRP for 155mm propelling charge were analyzed using regression analysis and MINITAB reliability analysis. The analysis methods used for this study were applied to statistical data types such as continuous data, binominal data. Results: The results of this study are as follows; The failure of 155mm propelling charge is mainly due to the broken charge bag, the decline of stabilizer content. The shelf-life(B5) regarding broken charge bag is 21.1years. The stabilizer content decrease with 0.0227%/year and safety storage period of propellant is 34.6years. Conclusion: The shelf-life of 155mm propelling charge determined by charge bag is estimated 21.1years.

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.155-165
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• 2018

Outliers and influential observations often distort many numerical measures for data analysis. Jang and Anderson-Cook (Quality and Reliability Engineering International, 30, 1409-1425, 2014) proposed a graphical firework plot method for exploratory analysis purpose to provide a possible visualization of the trace of the impact of the possible outlying and influential observations on the univariate/bivariate data analysis and regression. They developed 3-D plot as well as pairwise plot for the appropriate measures of interest. We use firework plots as a graphical exploratory data analysis tool to detect outliers and evaluate the impact of outliers in statistical inference.

• Journal of KSNVE
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• v.11 no.2
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• pp.257-264
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• 2001

In this research, piezoelectric smart structures are applied for SEA(Statistical Energy Analysis), which is well known approach for high frequency analysis. A new input power measurement based on piezoelectric electrical power measurement is proposed and compared with the conventional method in SEA. As an example, a simple aluminum beam on which piezoelectric actuator is attached is considered. By measuring the electrical impedance and electrical current of the piezoelectric actuator, the electrical power given on the actuator is found and this is In turn converted into the mechanical energy. From the measured value of the stored energy of the beam, the Internal loss factor is calculated and this value shows a good agreement with that given by the conventional method as well as the theoretical value. To compare the coupling loss factor, L-shape beam system which consists of a aluminum beam subsystem and a steel beam subsystem coupled by three pin is taken as second example. The input power and stored energy of each subsystem are found by the proposed approach. The coupling loss factor found by the electrical input power obtained from the piezoelectric actuator exhibits similar trend to the value found by the conventional method as well as the theoretical value. In conclusion, the use of SEA for high frequency application of piezoelectric smart structures is Possible. Especially, the input power that is essential for SEA can be found accurately by measuring the electrical input power of the piezoelectric actuator.

• The Korean Journal of Applied Statistics
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• v.31 no.2
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• pp.241-251
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• 2018

The analysis of gene sets in microarray has advantages in interpreting biological functions and increasing statistical powers. Many statistical methods have been proposed for detecting significant gene sets that show relations between genes and phenotypes, but there is no consensus about which is the best to perform gene sets analysis and permutation based tests are considered as standard tools. When many gene sets are tested simultaneously, a large number of random permutations are needed for multiple testing with a high computational cost. In this paper, several parametric approximations are considered as alternatives of the permutation distribution and the moment based gene set test has shown the best performance for providing p-values of the permutation test closely and quickly on a general framework.

• Nuclear Engineering and Technology
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• v.19 no.4
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• pp.249-265
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• 1987

For the probabilistic risk assessment of the high level radioactive waste repository, some methods have been proposed up to now. Since the system has highly uncertain input parameters, the evaluated risk for some input parameter values has high uncertainty. In this paper, methods of uncertainty and sensitivity analysis are devised to analyse systematically these factors and applied to a probabilistic risk assessment model of the high level waste repository, The statistical package SPUSA developed through this study can be used for any other fields, e.g., statistical thermal margin analysis, source term uncertainty analysis, etc.

• Journal of Technologic Dentistry
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• v.33 no.4
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• pp.391-402
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• 2011

Purpose: The purpose of this study was to investigate the factors affecting oral health impact profile. Methods: Subjects included elderly in the metropolitan areas of the cities of Daegu and Gyeong-buk. Statistical analysis was done using the Statistical Package for Social Sciences version 19.0 for Windows. We determined frequencies and percentage, calculating means, and standard deviations, and determining statistical significance using T-tests, analysis of variance, multiple regression analysis. Results: The results of multiple regression analysis between the oral health impact profile and the related factors indicated that Occupation, Economic status are the major component oral health impact profile in general characteristics and the Impediment of oral health promotion behavior is the major component that contribute the oral health impact profile in oral health belief. Conclusion: The comprehensive and reliable research which measures oral health impact profile of elderly is necessary.

• Journal of Fisheries and Marine Sciences Education
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• v.26 no.1
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• pp.156-165
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• 2014

The purpose of this study was to find research trends of smart learning. For this, we identified the research's characteristics such as the subject or keyword of research, method, data collection, and statistical analysis method. The 2,865 articles published from 1995 to 2013 were gathered from five Korean academic journals related to smart learning. Among them, research keyword, areas, research method, data collection method, and statistical analysis method were analyzed on 596 papers. The findings of this study were as follows: (a) Smart learning papers such keyword likes u-learning, m-learning, and smart-learning were emerging after 2006. Smart learning papers with ICT related topics were highly increased after 2000, but they were decreased after 2006. Smart learning papers with e-learning related keywords were steadily increased after 2000 through 2013. (b) The research field of deign had the highest portion in smart learning research, but managing had the lowest portion. (c) Development was mainly used as a research method. Both questionnaire and experiment were mainly used for collecting data methods. T-test and frequency analysis were mainly used as statistical analysis methods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.11
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• pp.1605-1611
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• 2017

In this study, the characteristic lifetime of power facilities such as power transformers and GIS were investigated as the basis of power facility asset management. It is difficult to obtain the operation and failure data of the facilities in Korea. Therefore, the number of failures of the electric power facilities was calculated from the operation data and hazard rate shown in the overseas literatures, and the statistical analysis was performed using the Weibull distribution function. As a result of extracting and analyzing the data of the UK National Grid for power transformers, the characteristic lifetime (scale parameter) of 116.45 years was considered to be a very appropriate value for power transformer management and can be used as a comparative data of the analysis of the domestic transformers. As for the GIS, based on the Bays and Bay-Years data and the hazard rate according to the operation years of the 123kV GIS in Germany, it is found out that the characteristic lifetime of GIS is not so meaningful. It is necessary to decide a maintenance strategy and lifetime expectancy considering the characteristics of the design, materials and manufacturing process of GIS.

• Journal of Biomedical Engineering Research
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• v.22 no.4
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• pp.369-375
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• 2001

The statistical regression model is one of the most frequently used clinical analysis methods. It has basic assumption of linearity, additivity and normal distribution of data. However, most of biological data in medical field are nonlinear and unevenly distributed. To overcome the discrepancy between the basic assumption of statistical model and actual biological data, we propose a new analytical method based on artificial neural network. The newly developed multilayer perceptron(MLP) is trained with 120 data set (60 normal, 60 patient). On applying test data, it shows the discrimination power of 0.76. The diabetic risk factors were also identified from the MLP neural network model and the logistic regression model. The signigicant risk factors identified by MLP model were post prandial glucose level(PP2), sex(male), fasting blood sugar(FBS) level, age, SBP, AC and WHR. Those from the regression model are sex(male), PP2, age and FBS. The combined risk factors can be identified using the MLP model. Those are total cholesterol and body weight, which is consistent with the result of other clinical studies. From this experiment we have learned that MLP can be applied to the combined risk factor analysis of biological data which can not be provided by the conventional statistical method.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.823-826
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• 2008

Statistical methods were used in the analysis of data, which are the SNR and SDNR in describing the various natures, and the methodology relating the results with the operation was developed. Multiple regression analysis based on the results of statistics of data were SNR = 0.0219 + 0.000044BOD lording - 0.00600C/N ratio and SDNR = 0.0226 + 0.000044BOD lording - 0.00602C/N ratio. It were concluded that the variability of the process performance should be reflected to the operation condition procedure through the analysis based on the statistics methods.