• 산업공학
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• 제19권2호
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• pp.117-123
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• 2006

Many products, such as gasoline, polymer plastics, alloys, and ceramics are manufactured by mixing two or more ingredients or components. When we are to develop new mixture products, we must deal with a long list of potentially important component variables. This paper introduces some mixture screening designs, analysis tools for screening important variables, and a guideline for applying these analysis tools. The results of this paper will be helpful to engineers who work in the research and development sector of mixture product industries.

• 대한기계학회논문집B
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• 제27권1호
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• pp.69-75
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• 2003

In this study, his technique was applied to a GDI spray in order to investigate the mixture distribution. In addition, the homogeneity degree and diffusion effect according to ambient temperature in the high pressure chamber were analyzed by using an entropy analysis method. From this experiment, we could find that entropy analysis is very effective method for the analysis of mixture formation, and the entropy values increase with the progress of uniformity in diffusion Process. we tried to provide the fundamental data for parameter which effects on the spray macroscopic characteristics with mixture ratio of diesel and gasoline. In addition, the mixture formation was analyzed by using entropy analysis. The entropy analysis is based on the concept of statistical entropy, and it identifies the degree of homogeneity in the fuel concentration. From the entropy analysis results we could find that the direct diffusion phenomena is a dominant factor in the formation of a homogeneous mixture at downstream of GDI spray especially in vaporizing conditions. As to increasing ambient temperature and increasing gasoline rate, the entropy intensity using the statistic thermodynamics method is increased because evaporation rate is higher gasoline than diesel.

• 한국의류학회지
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• 제26권11호
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• pp.1605-1614
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• 2002

The purpose of this study was to identify the consumers who use the level of price as the indicator of the product quality. In order to implement the purpose of this study, Jeans market had been segmented by the mixture regression model, and price response function was calibrated for each segment. Based on the types of price response function, segments were allocated into one of two groups; the group using the level of price as the quality indicator or the group not using the level of price as that. Then, characteristics of both groups were compared in terms of product attributes and demographic variables. Data were co]looted from the sample of the 23o undergraduate and graduate students in Seoul. For the data analysis, mixture regression model, conjoint analysis, and t-test were used. As a result, jeans market was divided into 5 segments. Segment 1,2,3 were allocated into the group not using the level of price as the quality indicator while segment 4,5 were done into the other group. Significant differences existed between two groups in product attributes, not in demographic variables. Mixture model and conjoint analysis were proved to be an effective set of tools in market segmentation.

• Communications for Statistical Applications and Methods
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• 제22권6호
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• pp.589-598
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• 2015

In longitudinal studies missing data are common and require a complicated analysis. There are two popular modeling frameworks, pattern mixture model (PMM) and selection models (SM) to analyze the missing data. We focus on the PMM and we also propose Bayesian pattern mixture models using generalized linear mixed models (GLMMs) for longitudinal binary data. Sensitivity analysis is used under the missing not at random assumption.

• 한국환경과학회지
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• 제24권11호
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• pp.1541-1546
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• 2015

The objective of this research was to evaluate the toxicity of the industial xenobiotic Aroclor 1248 (A) and natural origin substances~elemental sulfur (S80) and oleic acid (OA) and their binary mixtures to V. fischeri bioluminescence during the prolonged exposure time (up to 60 min). The bioluminescence quenching test was used to determine the toxic effects. Full factorial experiment design and multiple regression analysis and the comparison of binary mixture effect with the sum of effects of individual chemicals were used for the evaluation of combined effects of toxicants. The analysis of general trend of mixture toxicity to bioluminescence showed that mixture toxic effects were reversible up to 60 min. Data analysis revealed different joint effects, which were depended on mixture composition. S80 enhanced toxic effect of A and acted additively with synergistic interaction. Hydrophobic OA in mixture with A acted antagonistically and in mixture with sulfur caused an additive effect with antagonistic component of interaction. It was concluded that low concentrations of natural toxic substances present in environmental samples as mixtures of chemicals can define the toxicodynamic character of industrial xenobiotics.

• 보건행정학회지
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• 제12권2호
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• pp.1-22
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• 2002

Since the early 1980s scholars have applied latent structure and other type of finite mixture models from various academic fields. Although the merits of finite mixture model are well documented, the attempt to apply the mixture model to medical service has been relatively rare. The researchers aim to try to fill this gap by introducing finite mixture model and segmenting inpatients DB from one general hospital. In section 2 finite mixture models are compared with clustering, chi-square analysis, and discriminant analysis based on Wedel and Kamakura(2000)'s segmentation methodology schemata. The mixture model shows the optimal segments number and fuzzy classification for each observation by EM(expectation-maximization algorism). The finite mixture model is to unfix the sample, to Identify the groups, and to estimate the parameters of the density function underlying the observed data within each group. In section 3 and 4 we illustrate results of segmenting 4510 patients data including menial and ratio scales. And then, we show AHP can be identify the attractiveness of each segment, in which the decision maker can select the best target segment.

• 한국측량학회지
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• 제33권3호
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• pp.211-218
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• 2015

The analysis of remote sensing data depends on sensor specifications that provide accurate and consistent measurements. However, it is not easy to establish confidence and consistency in data that are analyzed by different sensors using various radiometric scales. For this reason, the cross-calibration method is used to calibrate remote sensing data with reference image data. In this study, we used an airborne hyperspectral image in order to calibrate a multispectral image. We presented an automatic cross-calibration method to calibrate a multispectral image using hyperspectral data and spectral mixture analysis. The spectral characteristics of the multispectral image were adjusted by linear regression analysis. Optimal endmember sets between two images were estimated by spectral mixture analysis for the linear regression analysis, and bands of hyperspectral image were aggregated based on the spectral response function of the two images. The results were evaluated by comparing the Root Mean Square Error (RMSE), the Spectral Angle Mapper (SAM), and average percentage differences. The results of this study showed that the proposed method corrected the spectral information in the multispectral data by using hyperspectral data, and its performance was similar to the manual cross-calibration. The proposed method demonstrated the possibility of automatic cross-calibration based on spectral mixture analysis.

• 한국연소학회:학술대회논문집
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• 한국연소학회 2015년도 제51회 KOSCO SYMPOSIUM 초록집
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• pp.169-172
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• 2015

This paper presents a numerical investigation on kerosene-air mixture detonation and behaviors of thermal elasto-plstic thin metal tube under detonation loading based on multi-material analysis. The detonation loading is modeled by the kerosene-air mixture detonation which is compared with CJ condition and experimental cell size. And the thermal softening effect on elasto-plstic model of metal tube is indicated by different dynamic response of detonation loaded tube in various temperature and tube thickness.

• ETRI Journal
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• 제43권1호
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• pp.74-81
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• 2021

The mixture model is a very powerful and flexible tool in clustering analysis. Based on the Dirichlet process and parsimonious Gaussian distribution, we propose a new nonparametric mixture framework for solving challenging clustering problems. Meanwhile, the inference of the model depends on the efficient online variational Bayesian approach, which enhances the information exchange between the whole and the part to a certain extent and applies to scalable datasets. The experiments on the scene database indicate that the novel clustering framework, when combined with a convolutional neural network for feature extraction, has meaningful advantages over other models.

• 대한기계학회논문집B
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• 제33권3호
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• pp.201-206
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• 2009

The focus of this work is placed on the analysis of the mixture formation process under the evaporative diesel-free spray conditions. In order to examine homogeneity of mixture within the vapor phase region of the injected spray, image analysis was carried out based on the entropy of statistical thermodynamics. As an experimental parameter, the injection pressure and ambient gas density were selected, and effects of the injection pressure and density variation of ambient gas on the mixture formation process in the evaporative diesel spray were investigated. In the case of application of the thermodynamic entropy analysis to evaporative diesel spray, the value of the dimensionless entropy always increases with increase in time from injection start. Consequently, the dimensionless entropy in the case of the higher injection pressure is higher than that of lower injection pressure during initial injection period.