• 한국신뢰성학회지:신뢰성응용연구
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• 제14권2호
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• pp.93-96
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• 2014

RFID (Radio Frequency IDentification) system is recognition technology which can maintain various object's information. Reliability of RFID tags is the most important factor in RFID system. In this paper, we proposed ALT (Accelerated Life Test) method for UHF RFID tags. Temperature and humidity were adopted as stress factors and the accelerated life tests were conducted in three different conditions. We performed failure analysis for identifying failure mechanism and statistical analysis of test data. In the statistical analysis, we employed Inverse Power law for relationship between tag's life and stress. Through the statistical analysis, we proposed acceleration factor for several levels of temperature-humidity. The reliability qualification test plans were also designed for the tag's target reliability.

• 한국환경과학회지
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• 제14권2호
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• pp.251-258
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• 2005

Statistical analysis between operating parameters and effluent quality on advanced wastewater treatment plant was performed. Through factor analysis four factors derived varimax rotation were selected each plant. Four components explained $80\%,\;82\%$ of the total variance of the process, respectively. The components on MLE plant were identified in the following order: 1) HRT increase and BOD load decrease by influent decrease, 2) Biomass, 3) SVI increase by internal return increase, 4) Microbial diversity by SRT increase. On $A_2O$ plant, we defined them as follows: factor 1, high MLSS by return rate increase, HRT increase by influent decrease; factor 2, biomass; factor 3, BOD of influent; factor 4 was relate to DO.

• Communications for Statistical Applications and Methods
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• 제22권5호
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• pp.475-485
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• 2015

Similar to regression, many measures to detect influential data points in discriminant analysis have been developed. Many follow similar principles as the diagnostic measures used in linear regression in the context of discriminant analysis. Here we focus on the impact on the predicted classification posterior probability when a data point is omitted. The new method is intuitive and easily interpretable compared to existing methods. We also propose a graphical display to show the individual movement of the posterior probability of other data points when a specific data point is omitted. This enables the summaries to capture the overall pattern of the change.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 추계학술대회논문집 II
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• pp.1109-1113
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• 2001

Interior parts of a vehicle are getting important to reduce interior noise of car. Therefore, prior analysis of cabin noise related with interior parts are necessary at first design stage. Recently, Statistical Energy Analysis(SEA) has been suggested as a possible way for meddle of high frequency range analysis with interior parts. This article introduces an example of the application of SEA to predict air born noise of cabin of car.

• Communications for Statistical Applications and Methods
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• 제28권5호
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• pp.511-520
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• 2021

Over the last decade, Bitcoin has attracted a great deal of public interest and Bitcoin market has grown rapidly. One of the main characteristics of the market is that it often undergoes some events or incidents that cause outlying observations. To obtain reliable results in the statistical analysis of Bitcoin data, these outlying observations need to be carefully treated. In this study, we are interested in change point analysis for Bitcoin return series having such outlying observations. Since these outlying observations can affect change point analysis undesirably, we use a robust test for parameter change to locate change points. We report some significant change points that are not detected by the existing tests and demonstrate that the model allowing for parameter changes is better fitted to the data. Finally, we show that the model with parameter change can improve the forecasting performance of Value-at-Risk.

• Communications for Statistical Applications and Methods
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• 제30권6호
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• pp.561-575
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• 2023

Brain network analysis has attracted the interest of neuroscience researchers in studying brain diseases. Magnetoencephalography (MEG) is especially proper for analyzing functional connectivity due to high temporal and spatial resolution. The application of graph theory for functional connectivity analysis has been studied widely, but research on network modeling for MEG still needs more. Temporal exponential random graph model (TERGM) considers temporal dependencies of networks. We performed the brain network analysis, including static/temporal network statistics, on two groups of epilepsy patients who removed the left (LT) or right (RT) part of the brain and healthy controls. We investigate network differences using Multiset canonical correlation analysis (MCCA) and TERGM between epilepsy patients and healthy controls (HC). The brain network of healthy controls had fewer temporal changes than patient groups. As a result of TERGM, on the simulation networks, LT and RT had less stable state than HC in the network connectivity structure. HC had a stable state of the brain network.

• Communications for Statistical Applications and Methods
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• 제31권2호
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• pp.191-202
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• 2024

The goal of this paper is to show how multivariate regression analysis with high-dimensional responses is facilitated by the response dimension reduction. Multivariate regression, characterized by multi-dimensional response variables, is increasingly prevalent across diverse fields such as repeated measures, longitudinal studies, and functional data analysis. One of the key challenges in analyzing such data is managing the response dimensions, which can complicate the analysis due to an exponential increase in the number of parameters. Although response dimension reduction methods are developed, there is no practically useful illustration for various types of data such as so-called large p-small n data. This paper aims to fill this gap by showcasing how response dimension reduction can enhance the analysis of high-dimensional response data, thereby providing significant assistance to statistical practitioners and contributing to advancements in multiple scientific domains.

• 대한교통학회지
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• 제7권1호
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• pp.43-55
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• 1989

This study is to review the road traffics and its process by the type of business in annual Statistical Yearbook of Transportation published under the supervision of Ministry of Transport, and the main purpose of this study is to find out an recommendations for the result of the review. For this purpose, this study surveyed and analyzed actual results and its output process in Statistical Yearbook by vehicle and business types. The local survey is performed for the nationwide 23 cities to produce passenger (ton) number and passenger (ton)-㎞ number by vehicle and business types. The result of the local survey is compared with the road traffics in Statistical Yearbook of Transpotation. The result of the survey analysis reveals that road traffic in Statistical Yearbook is produced formally and there is remarkable differences between road traffic in Statistical Yearbook and local survey output. Conclusively, statistical output process of road traffics must be improved to solve th se problems mentioned above in respect to system and technic. Also it is recommended to publish its own road traffic statistics (tentatively named Statistical Yearbook of Road Transportation) just like Statistical Yearbook of Railroad for user's expediency and practicality.

• 품질경영학회지
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• 제28권1호
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• pp.175-195
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• 2000

In this study, we developed a statistical software for measurement systems analysis. This software is patterned after the Measurement Systems Analysis Reference Manual developed by the Automotive Industry Action Group (AIAG). This software includes stability analysis, bias and linearity analysis, and gage R&R studies. This software was developed by using Delphi(version 4.0) and can be implemented on MS Windows 95 or higher level.

• Journal of the Korean Statistical Society
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• 제30권1호
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• pp.139-151
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• 2001

Although lots of works are done in influence diagnostics, results in the multivariate analysis are quite rare. One of recent works done by Fung(1995) is about the single case influence diagnostics in the linear discriminant analysis. In this paper we extend Fung's results to the multiple cases diagnostics which are necessary in the linear discriminant analysis for two reasons among others; First, the masking effect cannot be detected by single case diagnostics and secondly two populations are concerned in the discriminant analysis, i.e., influential cases can occur in one or both populations.