• Journal of the Korean housing association
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• v.22 no.2
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• pp.101-109
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• 2011

Until now, several comparative approaches were developed within the studies of Korean, Chinese, and Japanese traditional housings. In those studies, however, each space in the traditional houses was only treated in individual and fragmentary manners, and they lacked the interpretation of the topological attribute of each space within a holistic structure organized by unit spaces, and of the cultural-behavioral meaning of them within a holistic space-use pattern of the housing. The topological attribute and behavioral meaning can be analyzed and interpreted with the quantitative spatial analysis method such as Space Syntax. This study aims to analyze the traditional housings in Korea, China and Japan in the holistic aspect of spatial structure using Space Syntax, and to compare the analysis results with relating the structural attributes to the space-use pattern. In this study, the 'Banga' in Chosun era, the 'Siheyuan' in Ming-Ching era, and the 'Shoinzukuri' in Edo era were selected as the analysis subjects. The integration indices were calculated from the convex maps representing the subjects, and the common and different attributes of the three subjects were defined through comparative analyses.

• Journal of the Korean Institute of Landscape Architecture
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• v.23 no.2
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• pp.1-16
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• 1995

This study was carried out to suggest method which can be used to improve competitive power of theme parks. The characteristics of Hybrid Conjoint Analysis were described and its usefulness for identification of specific types of service theme parks have to provide was tested "Lotte World, " "Seoul land," and "farmland" were selected as study areas, and .7 attributes with 3 levels were utilized for analyses. Master design with 81 profiles was constructed to meet the requirement of ′Compromise Plan 1,′and data was collected by in-personal interviews on the study areas. Respondents were grouped by cluster analysis, and their characteristics were analyzed by discriminant analysis. Then, part-worth of each attribute . was estimated by stagewise estimation model Calibrated model of each group did not show part-worths of attributes clearly because both main effects and 2-way interaction effects were included in the models. Therefore, calibrated models′ coefficients were used to calculate utilities of all possible combinations of attributes levels. The results showed that managers of theme parks have several options for providing a new service: the combination of attribute levels with the highest utility is they however, they can choose the other combinations with next highest utlities is they can not afford it. Several suggestions were described to cope with the problems when Hybrid Conjoint Analysis is applied to landscape architectural study.

• The Korean Journal of Food & Health Convergence
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• v.8 no.4
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• pp.23-30
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• 2022

This study aims to analyze the premium hamburger market, which has recently become popular, the effect of the importance of the customer selection attribute of premium hamburgers on customer satisfaction, and the effect of customer satisfaction on repurchase intention. Existing research has focused on the importance of the selection attributes of premium hamburgers. Quality, convenience, experience, and presentation visuals were selected as customer selection attributes. This study analyzed 158 customers who had purchased and tasted premium hamburgers. To verify reliability and validity, a confirmatory factor analysis and discriminant validity analysis were performed, and a path analysis was carried out using structural equation modeling. The results showed that the quality, convenience, experience, and presentation visuals of premium hamburgers had a statistically significant effect on satisfaction. Moreover, satisfaction was verified to have a significant effect on repurchase intention. Customers' preference for premium burgers will continue to increase, thanks to the growth in national income, single-person families, and healthy food wellness. It was empirically proven that the selection attributes of premium burgers have a statistically significant effect on customer satisfaction and that satisfaction significantly affects repurchase intention. This study broadens the research horizon and has practical implications.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.7
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• pp.295-302
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• 2023

Software requirements written in natural language may have different meanings from the stakeholders' viewpoint. When designing an architecture based on quality attributes, it is necessary to accurately classify quality attribute requirements because the efficient design is possible only when appropriate architectural tactics for each quality attribute are selected. As a result, although many natural language processing models have been studied for the classification of requirements, which is a high-cost task, few topics improve classification performance with the imbalanced quality attribute datasets. In this study, we first show that the classification model can automatically classify the Korean requirement dataset through experiments. Based on these results, we explain that data augmentation through EDA(Easy Data Augmentation) techniques and undersampling strategies can improve the imbalance of quality attribute datasets, and show that they are effective in classifying requirements. The results improved by 5.24%p on F1-score, indicating that handling imbalanced data helps classify Korean requirements of classification models. Furthermore, detailed experiments of EDA illustrate operations that help improve classification performance.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.27 no.6
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• pp.407-416
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• 2014

Five factors are identified, which affect the performance of optical filter: 1) type of optical glass, 2) existence of Fe, 3) photo pic coating type, 4) coating form, and 5) coating thickness. If we consider all the levels of five factors, there are 360 possible candidates. We determined five evaluation criteria, which can be used to evaluate possible candidates. For the performance measures we selected white-state avearge voltage, black-state average voltage, and black-state error rate. And we added economic criterion and quality and maintenance criterion. Through the two-step statistical analysis of white-state avearge voltage, black-state average voltage, and black-state error rates, we selected final four candidates. Based on the five criteria we finally determined optimal optical filter using AHP.

• Spatial Information Research
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• v.11 no.4
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• pp.327-340
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• 2003

Quality elements and evaluation methods should be considered according to the characteristics of spatial database. The purpose of this study is to propose specific methods for quality evaluation focusing on land database which are an important parts of spatial database. Through the study, of quality evaluation for selected quality elements are specified, which are based on the construction processes of the topogaphical database, cadastral database, and zoning database. Position accuracy, attribute accuracy, consistency, completeness, temporal accuracy, believability, and lineage are selected as the quality elements of land database. A various statistical and mathematical skills are proposed for measurement and assesment methods of quality elements.

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.4
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• pp.452-459
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• 1998

The purpose of this study was to discover a conceptual framework and evaluation process of apparel quality by means-end chain theory. The theoretical study was conducted to find out a conceptual framework and build a hypothetical evaluation process model of apparel quality. Apparel quality was perceived associative network called a means-end chain and was evaluated in several stages. A conceptual framework of apparel quality evaluation was organized into hierarchical relationships among four different dimensions: physical attribute, physical function, instrumental performance, and expressive performance. The means-end structure linked tangible physical attributes and function to more abstract instrumental and expressive performance. A hypothetical evaluation process model linked dimensions of apparel quality to the selected means-end relationship. Different consumers had different means-end chains for the same apparel. Therefore different subjects are likely to have different evaluation paths. From this study we can suggest an evaluation process model of apparel quality.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.10
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• pp.42-49
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• 1993

In this paper, we evaluate the quality of synthesized speech by rule using the LPC CD as a objective measure, and then compare the test result with the subjective one. Speech used for the test consists of 108 words which are selected by word construction method using Korean attribute and frequency distribution, synthesized by demi-syllable rule. By evaluating the quality of synthesized speech by reule objectively, we have tried to resolve the problems such as lots of evaluation time, expansion of test scale, and variables of analysis result arised by subjective measure. We have, also, proved the validity of the objective test using the LPC CD, by comparing intelligibility which is the index for the subjective quality evaluation of synthesized speech by rule with MOS. From this results, we can provide a guide for quality assessment that would be useful in the R&D of synthesis method and the commercial products using synthesized speech.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.23-28
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• 2005

The high-dimensionality and insufficiency of gene expression profiles and proteomic profiles makes feature selection become a critical step in efficiently building accurate models for cancer problems based on such data sets. In this paper, we use a method, called Discrete Function Learning algorithm, to find discriminatory feature vectors based on information theory. The target feature vectors contain all or most information (in terms of entropy) of the class attribute. Two data sets are selected to validate our approach, one leukemia subtype gene expression data set and one ovarian cancer proteomic data set. The experimental results show that the our method generalizes well when applied to these insufficient and high-dimensional data sets. Furthermore, the obtained classifiers are highly understandable and accurate.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.219-223
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• 2001

Within a mechanical system such as an automotive the number of standard machine parts is increasing, so that the parts selection becomes more important than ever before. Selection of appropriate bearings in the preliminary design phase of a machine is also important. In this paper, three decision-making approaches are compared to find out a model that is appropriate to bearing selection problem. An artificial neural network, which is trained with real design cases, is used to select a bearing mechanism at the first step. Then, the subtype of the bearing is selected by the weighting factor method. Finally, types of peripherals such as lubrication methods are determined by a rule-based expert system.