• Journal of the East Asian Society of Dietary Life
• /
• v.16 no.5
• /
• pp.623-633
• /
• 2006

This study surveyed the selection attributes and degree of satisfaction among Japanese restaurant customers by conducting frequency analysis on the data. Among all types of Japanese restaurants customers selected sushi bars the most (48.2%), and they considered taste (73.9%), price (34.8%), and service (22.2%) to be very important. When eating at Japanese restaurants, satisfaction differences among sanitation (p<0.05), price (p<0.05), and unique design (p<0.1) each had a significant difference with F values of 3.313, 3.208, and 2,702, respectively. factor analysis of the effect of selection attributes on Japanese restaurant performance revealed three factors; image, service, and food. Their combined satisfaction was 61.41%, and each of these three factors showed a Cronbach's ${\alpha}$ value of 0.744, 0.739, and 0.623 in the reliability analysis, respectively, thus demonstrating the overall level of reliability. Multiple regression analysis showed that increased overall satisfaction of Japanese food was related to the satisfaction levels of food and service, and not to that of surrounding satisfaction.

• Culinary science and hospitality research
• /
• v.16 no.4
• /
• pp.76-93
• /
• 2010

The hypothesis testing on the impact relationship of patterning, reliability, kindness and credibility, which are perceived as choice attributes in a coffee shop laid out in this study, showed that they are fit to the models of this study. They also bad a direct repercussion on customer satisfaction, and the customer satisfaction equally affected revisit and word-of-mouth intention. This results show that when the patterning and reliability, and employees' kindness and credibility based on the fresh image in the shop serve as the foundation, its customers also affect satisfaction-maximization, leading to the revisit of the satisfied customers and positive word-of-mouth.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.10
• /
• pp.3685-3707
• /
• 2021

In recent years, facial attribute editing has been successfully used to effectively change face images of various attributes based on generative adversarial networks and encoder-decoder models. However, existing models have a limitation in that they may change an unintended part in the process of changing an attribute or may generate an unnatural result. In this paper, we propose a model that improves the learning of the attention mask by adding a spatial attention mechanism based on the unified selective transfer network (referred to as STGAN) using semi-supervised learning. The proposed model can edit multiple attributes while preserving details independent of the attributes being edited. This study makes two main contributions to the literature. First, we propose an encoder-decoder model structure that learns and edits multiple facial attributes and suppresses distortion using an attention mask. Second, we define guide masks and propose a method and an objective function that use the guide masks for multiple facial attribute editing through semi-supervised learning. Through qualitative and quantitative evaluations of the experimental results, the proposed method was proven to yield improved results that preserve the image details by suppressing unintended changes than existing methods.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.16 no.1
• /
• pp.55-65
• /
• 2020

With the development of display hardware, image interpolation techniques have been used in various fields such as image zooming and medical imaging. Traditional image interpolation methods, such as bi-linear interpolation, bi-cubic interpolation and edge direction-based interpolation, perform interpolation in the spatial domain. Recently, interpolation techniques in the discrete cosine transform or wavelet domain are also proposed. Using these various existing interpolation methods and machine learning, we propose decision tree classification-based image interpolation methods. In other words, this paper is about the method of adaptively applying various existing interpolation methods, not the interpolation method itself. To obtain the decision model, we used Weka's J48 library with the C4.5 decision tree algorithm. The proposed method first constructs attribute set and select classes that means interpolation methods for classification model. And after training, interpolation is performed using different interpolation methods according to attributes characteristics. Simulation results show that the proposed method yields reasonable performance.

• Journal of Distribution Science
• /
• v.16 no.2
• /
• pp.67-81
• /
• 2018

Purpose - Recently the importance of green consumption and corporate social responsibility has been increasing, thereby enhancing the importance of green consumption space as well. The retail space, as a representative consumption space, is now consuming more energy by introducing bigger retail space, 24-hour operation, cutting-edge equipment, and manless checkout system. Especially for retailers, who are constantly interacting with consumers, not only the economic consideration but also the consumer experience via retail service and physical retail space is crucial for their success. Therefore, this study intends to understand the main factors of motivating consumer perception about green retail space. In addition, we further investigate the mediating and moderating variables to encourage revisit intention and green retail space image. Research design, data, and methodology - In order to test our hypotheses with two models, we conducted a survey using questionnaires. In model 1, 356 respondents were surveyed to determine whether consumers' green attitudes and behaviors enhance environmentally friendly perception on retail space properties. In model 2, a questionnaire survey was conducted on 69 consumers who have experience in green retail space. Questionnaire surveys were conducted with on-line panels in Korea and analyzed using regression model and Hayes' PROCESS macro. Results - We found that consumers with green attitude put more importance on the attributes of green retail space. Also, the utility of the green retail space was found to be significant in emotional and social benefits. And, the consumers, who perceived the importance of green retail space, show higher revisit intentions. The emotional and social utilities have significant positive effects on revisit intention through green retail space image. Conclusions - This study demonstrates that a green retail space can induce positive consumer utility, thereby increasing green retail space image and revisit intention. Thus, in order to increase the image and revisit, retailers should communicate green messages with consumers, enhance green attributes of retail space, and target green consumers. To do so, we suggest that various marketing efforts such as publicity and education are needed to appeal experiential green products and retail space to consumers.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.2
• /
• pp.166-172
• /
• 2014

Image classification is an important problem in computer vision. However, it is a very challenging problem due to the variability, ambiguity and scale change that exists in images. In this paper, we propose a method of a hypergraph based modeling can consider the higher-order relationships of semantic attributes of a scene image and apply it to a scene image classification. In order to generate the hypergraph optimized for specific scene category, we propose a novel search method based on a probabilistic subspace method and also propose a method to aggregate the expression values of the member semantic attributes that belongs to the searched subsets based on a linear transformation method via likelihood based estimation. To verify the superiority of the proposed method, we showed that the discrimination power of the feature vector generated by the proposed method is better than existing methods through experiments. And also, in a scene classification experiment, the proposed method shows a competitive classification performance compared with the conventional methods.

• Fashion & Textile Research Journal
• /
• v.16 no.3
• /
• pp.396-405
• /
• 2014

This study demonstrates how VM attributes and VM personality influence VM attitude based on regulatory focus and how VM attitude influences revisiting intention. We used 303 copies of the survey form for the analysis. SPSS 19.0 for Windows Package was used to perform frequency analysis, factor analysis, and regression analysis. The results of the study: First, direction and arrangement of VM attributes had a significantly positive (+) influence on VM attitude. Second, fervor and trust of VM personality had a significantly positive (+) influence on VM attitude, while unpleasantness had a negative (-) influence. Third, VM attitude had a significant influence on visiting intention. Fourth, in terms of promotion focus, direction, arrangement, and promotion of VM attributes had a significantly positive (+) influence on VM attitude. In regards to prevention focus, image of VM attributes had a significant influence on VM attitude. In promotion focus, fervor and trust of VM personality had a significantly positive (+) influence on VM attitude, while unpleasantness had a negative (-) influence. In prevention focus, refinement and fervor of VM personality had a statistically significant influence on VM attitude. Only promotion focus showed a significant influence of VM attitude on revisiting intention.

• The Research Journal of the Costume Culture
• /
• v.25 no.4
• /
• pp.433-447
• /
• 2017

This study reveals the components of college women's shopping orientations and compares the attributes of shoes accordingly. This study attempts to investigate the needs of consumers in the target market of young women by comparing the importance of shoe attributes with their shopping orientations and to provide basic data for efficient marketing strategies which could increase sales. Data was collected using a questionnaire survey. Of a total of 330 questionnaires, 319 were used for statistical analysis. The survey was carried out from July to August 2016. The 17 shopping orientation-related questions and 13 questions about shoe purchase attributes were measured using a five-point Likert Scale. SPSS 23 was used to carry out: descriptives, factor analysis, reliability analysis, cluster analysis, ANOVA, and Duncan's test. Shopping orientations were divided between brand orientation, pleasure orientation, trend orientation and utilitarian orientation. Shoe attributes were categorized into ostentation value, product value, economic value and aesthetic value. College women were divided into the following groups: active shopping, passive shopping, rational shopping and conforming shopping. According to the comparison of the importance of shoe attributes by consumer type among college women, a significant difference by group was found in ostentation value and aesthetic value only. Furthermore, the average scores on the importance of product value and economic value were very high without significant differences between groups. The study results would be available as basic data to help improving the visual image of shoes and product quality for brands targeting young women in the fashion industry.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2007.02a
• /
• pp.53-57
• /
• 2007

This paper presents the practice of multitexturing in the Internet for enhancing the image quality of 3D contents, where the attributes of objects such as textures are dynamically changed. We explain the empirical results of realizing the X3D nodes related with multitexturing in the recent X3D viewers, and discuss the directions for upgrading X3D viewers that satisfy the user requirements and the advanced graphics accelerators.

• Journal of the Korean Home Economics Association
• /
• v.38 no.10
• /
• pp.85-95
• /
• 2000

The purpose of this study was to identify brand loyally of women's wear and construct brand positioning maps by using multidimensional scaling(MDS). There were significant differences between brand loyal and indifferent group in ages, income, occupation status and level of education. Significant differences were found between groups in the degree of importance of attributes (design/color, fashion, quality, store image, salesperson's attitude and brand reputation) when evaluating brands. The positioning maps upon the similarity and preference of brand image were composed by use of MDS.