• Journal of the Korean Statistical Society
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• v.36 no.4
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• pp.457-469
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• 2007

Many procedures are available to identify a single outlier or an isolated influential point in linear regression and logistic regression. But the detection of influential points or multiple outliers is more difficult, owing to masking and swamping problems. The multiple outlier detection methods for logistic regression have not been studied from the points of direct procedure yet. In this paper we consider the direct methods for logistic regression by extending the $Pe\tilde{n}a$ and Yohai (1995) influence matrix algorithm. We define the influence matrix in logistic regression by using Cook's distance in logistic regression, and test multiple outliers by using the mean shift model. To show accuracy of the proposed multiple outlier detection algorithm, we simulate artificial data including multiple outliers with masking and swamping.

• The Research Journal of the Costume Culture
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• v.10 no.6
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• pp.601-616
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• 2002

Qualitative research is a method widely used in marketing research. However, the method has seldom been used in fashion marketing research in Korea. The purpose of this study was to prove that using both qualitative and quantitative research methods in main stage is much useful than using qualitative research method only in exploratory stage. Qualitative data were gathered by conducting Focus Group Interview(FGI) with 48 college students. Quantitative data were gathered by surveying college students, and 487 questionnaires were used in the statistical analysis. The data were analyzed using content analysis, mean, standard deviation, and t-test. As a result, FGI, one of the tools used in qualitative research methods, was proved to be useful in revealing consumers´deep emotional needs as well as purchase motives. FGI also revealed information which quantitative research method tools such as survey could have missed. Therefore, it is best to use multiple methods-simultaneous use of quantitative and qualitative methods-to understand fast changing consumers´needs and purchase motives.

• Geomechanics and Engineering
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• v.13 no.2
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• pp.237-254
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• 2017

Estimation of slope stability is a very important task in geotechnical engineering. However, its estimation using conventional and soft computing methods has several drawbacks. Use of conventional limit equilibrium methods for the evaluation of slope stability is very tedious and time consuming, while the use of soft computing approaches like Artificial Neural Networks and Fuzzy Logic are black box approaches. Multiple Regression (MR) analysis provides an alternative to conventional and soft computing methods, for the evaluation of slope stability. MR models provide a simplified equation, which can be used to calculate critical factor of safety of slopes without adopting any iterative procedure, thereby reducing the time and complexity involved in the evaluation of slope stability. In the present study, a multiple regression model has been developed and tested its accuracy in the estimation of slope stability using real field data. Here, two separate multiple regression models have been developed for dry and wet slopes. Further, the accuracy of these developed models have been compared and validated with respect to conventional limit equilibrium methods in terms of Mean Square Error (MSE) & Coefficient of determination ($R^2$). As the developed MR models here are not based on any region specific data and covers wide range of parametric variations, they can be directly applied to any real slopes.

• Journal of the Korean Society of Safety
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• v.19 no.1
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• pp.23-30
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• 2004

Modern production systems are very complex by request of automation, and failure modes that occur in thisautomatic system are very various and complex. The efficient fault diagnosis for these complex systems is essential for productivity loss prevention and cost saving. Traditional fault diagnostic system which perforns sequential fault diagnosis can cause catastrophic failure during diagnosis when fault propagation is very fast. This paper describes the Real-time Intelligent Multiple Fault Diagnosis System (RIMFDS). RIMFDS assesses current machine condition by using sensor signals. This system deals with multiple fault diagnosis, comprising of two main parts. One is a personal computer for remote signal generation and transmission and the other is a host system for multiple fault diagnosis. The signal generator generates various faulty signals and image information and sends them to the host. The host has various modules and agents for efficient multiple fault diagnosis. A SUN workstation is used as a host for multiple fault modules and agents for efficient multiple fault diagnosis. A SUN workstation is used as a host for multiple fault diagnosis and graphic representation of the results. RIMFDS diagnoses multiple faults with fast fault propagation and complex physical phenomenon. The new system based on multiprocessing diagnoses by using Hierarchical Artificial Neural Network (HANN).

• Bulletin of the Korean Mathematical Society
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• v.58 no.5
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• pp.1261-1278
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• 2021

Recently, a new kind of multiple zeta value of level two T(k) (which is called multiple T-value) was introduced and studied by Kaneko and Tsumura. In this paper, we define a kind of alternating version of multiple T-values, and study several duality formulas of weighted sum formulas about alternating multiple T-values by using the methods of iterated integral representations and series representations. Some special values of alternating multiple T-values can also be obtained.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.27-30
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• 1991

Recently, the phenomena of voltage instability have become major concern in power system, these phenomena are closely related to what are called multiple load flow solutions and calculation methods on these solutions have developed. The multiple solutions concerned with phenomena are pair solutions in heavy loaded contion. But conventional methods require much run time to find this pair solutions and unusual generation patten in the condition of multiple solutions. In this paper, by using concept of existence condition of multiple solutions, calculation method on the multiple load flow solutions is presented which find the pair solutions in light loaded condintion.

• Journal of Power Electronics
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• v.17 no.5
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• pp.1382-1390
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• 2017

This paper presents a power supply for gate drivers, which uses a magnetic resonance wireless power transfer system. Unlike other methods where multiple antennas are used to supply power for the gate drivers, the proposed method uses a single antenna in an insulated receiver to make multiple mutually isolated power supplies. The power transmitted via single antenna is distributed to multiple power supplies for gate drivers through resonant capacitors connected in parallel that also block DC bias. This approach has many advantages over other methods, where each gate driver needs to be supplied with power using multiple receiver antennas. The proposed method will therefore lead to a reduction in production costs and circuit area. Because the proposed circuit uses a high resonance frequency of 6.78 MHz, it is possible to implement a transmitter and a receiver using a small-sized spiral printed-circuit-board-type antenna. This paper used a single phase-leg circuit configuration to experimentally verify the performance characteristics of the proposed method.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.4
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• pp.435-441
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• 2012

This paper provides simulation-based results of effect analysis of sample size and sampling periods on accuracy of reliability estimation methods using multiple comparisons with analysis of variance. Sum of squared errors in estimated reliability measures were evaluated through applying seven estimation methods for one-shot systems to simulated quantal-response data. Analysis of variance was implemented to investigate change in these errors according to variations of sample size and sampling periods for each estimation method, and then the effect analysis on accuracy in reliability estimation was performed using multiple comparisons based on sample size and sampling periods. An efficient way to allocate both sample size and sampling periods for reliability estimation tests of one-shot systems is proposed in this paper from the effect analysis results.

• Communications for Statistical Applications and Methods
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• v.26 no.2
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• pp.131-148
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• 2019

Constant stress partially accelerated life tests are studied according to exponentiated Weibull distribution. Grounded on multiple censoring, the maximum likelihood estimators are determined in connection with unknown distribution parameters and accelerated factor. The confidence intervals of the unknown parameters and acceleration factor are constructed for large sample size. However, it is not possible to obtain the Bayes estimates in plain form, so we apply a Markov chain Monte Carlo method to deal with this issue, which permits us to create a credible interval of the associated parameters. Finally, based on constant stress partially accelerated life tests scheme with exponentiated Weibull distribution under multiple censoring, the illustrative example and the simulation results are used to investigate the maximum likelihood, and Bayesian estimates of the unknown parameters.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.1079-1086
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• 2005

Most discussions of single imputation methods and the EM algorithm concern point estimation of population quantities with missing values. A second concern is how to get standard errors of the point estimates obtained from the filled-in data by single imputation methods and EM algorithm. Now we focus on how to estimate standard errors with incorporating the additional uncertainty due to nonresponse. There are some approaches to account for the additional uncertainty. The general two possible approaches are considered. One is the jackknife method of resampling methods. The other is multiple imputation(MI). These two approaches are reviewed and compared through simulation studies.