• Journal of the Korean Institute of Landscape Architecture
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• v.26 no.2
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• pp.269-282
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• 1998

The visual preference of interiors focusing on lobbies was investigated as a function of six predictor variable on the base of the Informational Approach: complexity, coherence, mystery, spaciousness, brightness, plant. The Common Fcator Analysis of preference ratings yielded six common factors which helped to account for 22.3 percent of the variance in preference response to the scene. Among these factors, the factor defined as 'bright with many plants' was the most preferred and the factor defined as 'simple and closed' was the least preferred. The environmental attributes reflected in six groups of scenes were colour, resting place, window and the six predictors. In the commercial building scenes, complexity, spaciousness, coherence, brightness and mystery out of six predictors accounted for 74 percent of preference variance as the significant contributors. In the business building scenes, three predictors which are brightness, complexity, spaciousness accounted for 84 percent of preference variance. 'The amount of plant' not only influenced the preference indirectly through the intervening variable, complexity, but also was moderately correlated with brightness. The overall pattern of the resulted confirmed the usefulness of the Informational Approach to predict the preference in interiors focusing on lobbies.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.659-668
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• 2007

Collaborative filtering approach for recommender systems are now widely applied in e-commerce to assist customers to find their needs from many that are frequently available. this approach makes recommendations for users based on the opinions to similar users in the system. But this approach is opened to users who present their preference to items or acquire the preference information form other users, noise in the system makes significant problem for accurate recommendation. In this paper, we analyze the relationship between the standard deviation of preference ratings for each user and the estimated ratings of them. The result shows that the possibility of the pre-filtering condition which detecting the factor of bad effect on the prediction of user's preference. It is expected that using this result will reduce the possibility of bad effect on recommender systems.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.103-112
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• 2021

The purpose of this study was to identify motivation factors of marathon crew members using Q methodology. Four distinct factors were emerged throughout the analysis: the first factor is 'the major event participation preference' who is seeking mega or big marathon events to enjoy festival atmosphere. The second factor is 'special meaningful event participation preference' who prefers to participate marathon events to help disabled people or childeren. The third factor is 'the tourism type marathon event participation preference' who is seeking to participate marathon event with tourism. The last factor is 'the preference type for record breaking ' who is seeing the place is accessability, a good season and running course to break personal record.

• Journal of the Korean Institute of Landscape Architecture
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• v.28 no.3
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• pp.88-96
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• 2000

The objective of this study is to evaluate the preference and visual characteristic of users according to the location of benches at urban community parks. The types of benches are separated into four patterns and located in four representative places at urban community parks. Each relations between visual preference and adjective related factors are calibrated by the estimated results of Pearson correlation coefficient. Moreover, the factors which affect the visual preference are obtained by multiple regression analysis and to calibrate the each factors significant level, the method of multivariate variance analysis is applied. The results of this study are summzrized as belows: 1. Four types of factors which consist the visual characteristic are classified as emotional factor of visual images(aesthetic factor(F1), texture related factor(F2)) and physical factor(physical factor(F3), transformable factor(F4)). Each factor's eigenvalue is appears as 5.27∼1.78 and the eigenvalue of emotional factor of visual images is more higher than the physical factor. 2. The correlation coefficient between visual preference according to the location of benches(X21) and aesthetic factor(f1) is estimated as 0.79, which is highest value among the four factors. And the correlation coefficient of texture related factor(f2), physical factor(F3) and transformable factor(F4) is estimated as 0.14, 0.04 and 0.08 respectively. 3. The visual preference of users according to the location of benches is greatly affected by the emotional factor of visual images(F1, F2) and the physical factor(F3, F4) are poorly related. The results of this study suggest the effective guidelines for the location of leisure facilities. Moreover the design and planning of leisure facilities at the urban community park have to be reexamined. What must be examined from now on is as follows: First, the preference research of rest facilities in the urban park through the multiple approach must be carried out continuously. Second, the research about the visual quality of the environmental sight observed in sitting on the bench as well as the visual quality of the showed object and place needs to be supported. Nevertheless, through this study the utilization into the useful data of the plan and the design for the systematic disposition of landscape architecture equipments centered on the users can be expected.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.5
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• pp.415-422
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• 2017

Finding influential factors from given clustering result is a typical data science problem. Genetic Algorithm based method is proposed to derive influential factors and its performance is compared with two conventional methods, Classification and Regression Tree (CART) and Chi-Squared Automatic Interaction Detection (CHAID), by using Dunn's index measure. To extract the influential factors of preference towards political parties in South Korea, the vote result of $18^{th}$ presidential election and 'Demographic', 'Health and Welfare', 'Economic' and 'Business' related data were used. Based on the analysis, reverse engineering was implemented. Implementation of reverse engineering based approach for influential factor analysis can provide new set of influential variables which can present new insight towards the data mining field.

• Journal of the Korean Institute of Landscape Architecture
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• v.29 no.1
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• pp.1-10
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• 2001

The purpose of this thesis is to classify landscape-type of golf course, and t provide a better understanding of landscape of existing golf courses, seek a developed method for landscape, and other useful knowledge. In order to classify landscape type of the golf course, and analyze the preference for the determinants, we have selected 4 golf courses in Yongin, Kyonggi Province. The analysis in this study shows that a variable, 'familiarity' is the most potent influence of visual preference, (Sig 0.01), and it can be divided into five classes of landscape-type in golf course. More specifically, we conducted the analysis of the image of views and visual preference to bring out major factors which could decide visual preference in golf courses. The results between visual preference and physical variable are as follows; 1. It implies that a factor for a image of the view in golf course is analyzed by 4 districts from factor 1 to factor 4. An ability explaining those factors in the whole of variable quantity is 51.742%, implying factors for the image of the scene in golf courses are appeared as familiarity, changeableness, spaciousness, and naturalness. Among those factors, since familiarity(C.V.; 26.783%) and changeableness(C.V.; 112.200%) took high rank, this represents the fact that familiarity or changeableness highly affects the forming of image. 2. Defending on degree of image ability in golf course, we could classify as five types such as Type I, Type II, Type II, Type IV, and Type V. 3. As a result of calculating type of factor score, Type I had the lowest ranking in naturalness, and rather lower than others such as organization and spaciousness. The II is a top-ranked one in familiarity and naturalness, while it has the lowest ranking in spaciousness. Type III has the highest ranking in organization and preference. Type IV is the lowest-ranked one in familiarity and preference. Type IV is the lowest-ranked one is familiarity and preference. Type V has the highest ranking in spaciousness, but the lowest ranking in organization. 4. As a result of preference, Type III, Type II, Type V, Type I, and Type IV come out in order. That water-seen place type charges the highest rank shows the importance of changeable materials. 5. These factors-familiarity, organization, spaciousness and naturalness- are the major materials of the scene of view in golf courses. The possibility of how to use those for designing and making enhanced golf courses should be reinvestigated through these factors. Especially, it is acknowledged that the duction of changeableness, which is not mentioned in the study of informational approach, is much stimulating for the designing use. A further research on this theme should be made in the future, not limiting to the golf courses in Yongin.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.383-393
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• 2020

The purpose of this research is to identify factors affecting consumer's brand preference toward environment-friendly products like electric vehicles in Bangkok, Thailand. The researcher conducted the study based on a quantitative approach and adapted a nonprobability sampling as a convenience sampling method. The data were collected from 400 respondents living in Bangkok, who are 18 years old and above, with significant knowledge of electric vehicles. This study adapted the Structural Equation Model (SEM) and Confirmatory Factor Analysis (CFA) to examine the model accuracy, reliability and verification influence of various variables. The results revealed that social influence has significant effect on environment concern as well as a positive effect on attitude. The initial significance of environment concern leads to a positive effect on fuel efficiency, followed by brand preference. Lastly, attitude has a significant effect on brand preference as attitude of consumers toward environment-friendly products affects the encouragement of brand preference, which largely depends on individual opinion. From an environmental concern, the researchers identified fuel efficiency and attitude having a positive and significant effect on brand preference toward environment-friendly products for electric vehicles. The authors also found that environmental concern and social influences on green purchasing behavior were significantly interrelated.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.412-418
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• 2021

This study aims to investigate the influence of emotional engineering factors on brand preference and loyalty in smartphone product design. The emotional engineering factor was divided into color, performance, usability, value, and reliability, and the relationship between brand preference and loyalty was empirically analyzed. As a result of the analysis, the emotional engineering factor in the smartphone product design has a positive effect on the brand preference, and the factors having the greatest influence are the performance and color factors. In smartphone product design, the emotional engineering factor has a static effect on loyalty, and the factors that have the greatest influence are reliability and performance factors. The higher the brand preference in product design, the greater the affect on loyalty. It is necessary to approach product design that fits the characteristics of consumers by identifying the influential factors among the product design emotional engineering factors.

• Journal of the Korean Institute of Landscape Architecture
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• v.30 no.3
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• pp.64-72
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• 2002

The purpose of this paper is to examine the effects of interior landscape that influence preference at a department store in order to answer the research question; What are the effective factors of interior landscape that affect preference at a department store. After review of the effect of interior landscape, and the interior landscape at a department store, we constructed a literature framework and have formulated the hypothesis of this research. We have analyzed the data which surveyed 108 visitors about the interior landscape in a department store, using factor analysis, Pearson's correlation analysis, and the multiple linear regression method. We found that; 1) eleven variables can be selected for the effects of interior landscape at department store: accessibility, image, stay, distinction, comfort, complexity, cleanness, mystery, purification of atmosphere, noise and harmony. Among the 11 independent variables used to study the effect of interior landscape at a department store, the image and purification of atmosphere highly affect preference. 2) These 11 variables are grouped by factor analysis as effects of amenity, attractiveness and identity. 3) As a result of multiple regression analysis, independent variables influencing preference were proved statistically significant at one percent level. 4) Regarding their relative contribution of interior landscape effect at a department store, the effects of amenity was the most important and it showed a level of importance 1.4 times higher than the effect of identity, and 1.25 times higher than the effect of attractiveness. The research results suggest the need for guidelines for the creation of interior landscape at department stores. The approach and analysis method adopted by this research is highly useful for the evaluation of interior landscape criteria at a department store. It is recommended that more practical study on factors affecting user's preference be performed in the future.

• Proceedings of the IEEK Conference
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• summer
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• pp.395-399
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• 2004

We present modality conversion as an effective means for QoS management. We show that modality conversion, in combination with content scaling, would give a wider range of adaptation to support QoS at media level. Here, we consider modality conversion with respect to resource constraint and human factor. To represent modality conversion as well as content scaling, we present the overlapped content value (OCV) model that relates the content value of different modalities with resources. The specification of user preference on modality conversion is divided into qualitative and quantitative levels. The user preference is then integrated into the OCV model so that modality conversion correctly reflects the user's wishes. For the conversion of multiple contents, an optimization problem is formulated and solved by dynamic programming. The experiments show that the proposed approach is efficient to be applied in practice.