• Communications for Statistical Applications and Methods
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• 제24권2호
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• pp.143-154
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• 2017

A variable selection method based on probabilistic principal component analysis (PCA) using penalized likelihood method is proposed. The proposed method is a two-step variable reduction method. The first step is based on the probabilistic principal component idea to identify principle components. The penalty function is used to identify important variables in each component. We then build a model on the original data space instead of building on the rotated data space through latent variables (principal components) because the proposed method achieves the goal of dimension reduction through identifying important observed variables. Consequently, the proposed method is of more practical use. The proposed estimators perform as the oracle procedure and are root-n consistent with a proper choice of regularization parameters. The proposed method can be successfully applied to high-dimensional PCA problems with a relatively large portion of irrelevant variables included in the data set. It is straightforward to extend our likelihood method in handling problems with missing observations using EM algorithms. Further, it could be effectively applied in cases where some data vectors exhibit one or more missing values at random.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권3호
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• pp.182-187
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• 2007

A fuzzy modeling method is proposed to build the dynamic model of a walking-beam reheating furnace from the recorded data. In the proposed method, the number of membership function on each variable is increased individually and the modeling accuracy is evaluated iteratively. When the modeling accuracy is satisfied, the membership functions on each variable are fixed and the structure of fuzzy model is determined. Because the training data is limited, in this process, as the number of membership function increase, it is highly possible that some rules are missing, i.e., no data in the training set corresponds to the consequent part of a missing rule. To complete the rulebase, the output of the model constructed at the previous step is used to generate the consequent part of the missing rules. Finally, in the real time application, a rolling update scheme to rulebase is introduced to compensate the change of system dynamics and fine tune the rulebase. The proposed method is verified by the application to the modeling of a reheating furnace.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.299-302
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• 1999

Generation of a Digital Elevation Model (DEM) in remote sensing is an important application. The process of DEM generation often requires interpolation. This paper is aimed to introduce a class of interpolation algorithms using spectral information, which is widely used in geophysical applications, and to examine the applicability of the method to DEM interpolation. The interpolation process can be explained in two steps. The first step is for finding spectral information from the known data and the second step is finding missing data so as to follow the spectral trend found in the previous step. The interpolation algorithm has been tested for a real DEM data and problems in the DEM interpolation are discussed.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.287-292
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• 2002

This paper presents a reverse engineering method for compound surfaces using vision system. A CNC machining center is used as a measuring station, which is equipped with slit beam generator and vision probe. Since obtained data using slit beam or laser scanner may have much data loss along the edge of compound surfaces, an algorithm is presented in this study to recover missing geometric data at such region. First, b-spline interpolation is applied to extract edge information of the surface, and as a next step, b-spline approximation is applied to recover the missing geometric data. Finally, b-spline skinning method is applied to regenerate the surface information. Appropriate simulation and experimental works are preformed to very the effectiveness of the proposed methods.

• 대기
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• 제24권3호
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• pp.445-456
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• 2014

A real-time quality control system for meteorological data (air temperature, air pressure, relative humidity, wind speed, wind direction, and precipitation) measured by an integrated meteorological sensor has been developed based on comparison of quality control procedures for meteorological data that were developed by the World Meteorological Organization and the Korea Meteorological Administration (KMA), using time series and statistical analysis of a 12-year meteorological data set observed from 2000 to 2011 at the Incheon site in Korea. The quality control system includes missing value, physical limit, step, internal consistency, persistence, and climate range tests. Flags indicating good, doubtful, erroneous, not checked, or missing values were added to the raw data after the quality control procedure. The climate range test was applied to the monthly data for air temperature and pressure, and its threshold values were modified from ${\pm}2{\sigma}$ and ${\pm}3{\sigma}$ to ${\pm}3{\sigma}$ and ${\pm}6{\sigma}$, respectively, in order to consider extreme phenomena such as heat waves and typhoons. In addition, the threshold values of the step test for air temperature, air pressure, relative humidity, and wind speed were modified to $0.7^{\circ}C$, 0.4 hPa, 5.9%, and $4.6m\;s^{-1}$, respectively, through standard deviation analysis of step difference according to their averaging period. The modified quality control system was applied to the meteorological data observed by the Weather Information Service Engine in March 2014 and exhibited improved performance compared to the KMA procedures.

• 한국CDE학회논문집
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• 제9권1호
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• pp.19-26
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• 2004

It is not possible to exchange parametric information of CAD models based on the current version of STEP (Standard for the Exchange of Product model data). The designer intents are lost during the transfer of CAD models. To resolve this problem, the macro-parametric approach had been proposed. To enable this approach, a set of standard modeling commands has been defined. Errors or missing elements of the standard modeling commands can be discovered by implementing macro-parametric translators. But there is a limit to discover problems only by using translators. This paper proposes a method to verify the standard modeling commands by implementing a geometric modeler. First, each argument of a modeling command is verified. Second, the set of the standard modeling commands is applied to geometric modeling of commercially available product parts. For the geometric modeling, nine test models have been selected.

• 한국CDE학회논문집
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• 제12권6호
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• pp.461-465
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• 2007

There have been 3E problems of energy, economy and environment since the earth has its history. Especially, the energy and environment problems have been getting serious after the modem industry revolution. Therefore, the demand of gas as an eco-friendly energy source is getting increased. With the demand of gas, the installation and use of gas boiler is also increased, so human life injury by the waste gas(CO) of boiler goes on increasing every year. It is the content about a life of the exhaust tube which is used at Gas boiler in this paper. We explain also the course to apply the 6SC(6 Step Creativity)of practical TRIZ and evaluate the resolution.

• ETRI Journal
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• 제42권5호
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• pp.761-772
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• 2020

This paper presents an automatic proficiency assessment method for a non-native Korean read utterance using bidirectional long short-term memory (BLSTM)-based acoustic models (AMs) and speech data augmentation techniques. Specifically, the proposed method considers two scenarios, with and without prompted text. The proposed method with the prompted text performs (a) a speech feature extraction step, (b) a forced-alignment step using a native AM and non-native AM, and (c) a linear regression-based proficiency scoring step for the five proficiency scores. Meanwhile, the proposed method without the prompted text additionally performs Korean speech recognition and a subword un-segmentation for the missing text. The experimental results indicate that the proposed method with prompted text improves the performance for all scores when compared to a method employing conventional AMs. In addition, the proposed method without the prompted text has a fluency score performance comparable to that of the method with prompted text.

• 대한전자공학회논문지SP
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• 제38권5호
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• pp.556-566
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• 2001

본 논문에서는 EBMF(Edge Based Median Filter)와 3-Step AMPDF(Adaptive Minimum Pixel Difference Filter) 기반의 움직임 적응 디인터레이싱 알고리즘을 제안 한다. 움직임 적응 방법에서 중요한 요소인 motion missing에 의한 에러를 방지하기 위해 입력 영상을 4 가지 유형으로 구분하여 각 영상에 따라 다른 임계 값을 사용하여 정확한 화소 값을 보간 하는 AMPDF를 사용하며 움직이는 대각선 에지의 효과적인 보간을 위하여 에지에 따라 가변적인 후보 픽셀을 선택하는 EBMF를 사용하여 성능을 향상시켰다. 또한 성능을 높이기 위해 입력되는 영상을 움직임 영역, 정지 영역, 경계 영역으로 나누어 적응적으로 보간 하였으며 모의 실험을 통해 기존의 방법들에 비해 성능이 우수함을 보였다.

• Genomics & Informatics
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• 제14권4호
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• pp.166-172
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• 2016

Although a large number of genetic variants have been identified to be associated with common diseases through genome-wide association studies, there still exits limitations in explaining the missing heritability. One approach to solving this missing heritability problem is to investigate gene-gene interactions, rather than a single-locus approach. For gene-gene interaction analysis, the multifactor dimensionality reduction (MDR) method has been widely applied, since the constructive induction algorithm of MDR efficiently reduces high-order dimensions into one dimension by classifying multi-level genotypes into high- and low-risk groups. The MDR method has been extended to various phenotypes and has been improved to provide a significance test for gene-gene interactions. In this paper, we propose a simple method, called accelerated failure time (AFT) UM-MDR, in which the idea of a unified model-based MDR is extended to the survival phenotype by incorporating AFT-MDR into the classification step. The proposed AFT UM-MDR method is compared with AFT-MDR through simulation studies, and a short discussion is given.