• Proceedings of the Korean Institute of Interior Design Conference
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• 2005.05a
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• pp.271-272
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• 2005

As regards of designing, I chose a simple wall design of repeating pattern of vertical windows, rather than making the building as a glamourous obzet. This kind of approach was intended to pursue strong image of construction company, interchanging and communicating with its confused surrounding. Therefore, I boldly removed parts that I considered needless from the facade, and used simple and easy words clearly implying the organization. Lobby is the face of the building, but since the space is deep and narrow and the reality of lease should be considered, there was limit to give original image to the lobby. Instead, high ceiling is the biggest feature of this space. Doorae Engineering-Construction Corp. is young and energetic company. I wanted to highlight the young and energetic image of the company by crossing tore oblique piece of boards. This doesn't just has a simple function as ceiling, but also work as a major subject in the space. In addition of this powerful space of oblique lines, indirect lighting is used to emphasize the character of territory, continuity and deepness of the space. Character of territory that divides main and supplementary function and main and supplementary moving line is expressed by flow of dimension, and continuity and deepness of space is emphasized by indirect lighting flowing linearly through the crack between the ceiling and the wall.

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.372-379
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• 2013

In this paper, we proposed a content-based image retrieval algorithm using local binary patterns and HSV color histogram. Images are retrieved using image input in image retrieval system. Many researches are based on global feature distribution such as color, texture and shape. These techniques decrease the retrieval performance in images which contained background the large amount of image. To overcome this drawback, the proposed method extract background fast and emphasize the feature of object by shrinking the background. The proposed method uses HSV color histogram and Local Binary Patterns. We also extract the Local Binary Patterns in quantized Hue domain. Experimental results show that the proposed method 82% precision using Corel 1000 database.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.152-159
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• 2014

In this paper, we introduce a run-length for wavelet coefficients and present a image splicing detection method using the statistical moments for the wavelet run-length. Various pre-processings for the suspicious image are performed to emphasize the discontinuous edges caused by the image splicing. The proposed scheme has the merit that can exploit the various statistical characteristics of the wavelet transform. We extracted up to 72 features, and performed training and testing using SVM(support vector machine). Experimental results showed that the proposed method generates similar detection results compared to the existing methods. In addition, we showed the wavelet domain run-length is useful to detect the spliced image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4439-4455
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• 2021

Compared with two-stage object detection algorithms, one-stage algorithms provide a better trade-off between real-time performance and accuracy. However, these methods treat the intermediate features equally, which lacks the flexibility to emphasize meaningful information for classification and location. Besides, they ignore the interaction of contextual information from different scales, which is important for medium and small objects detection. To tackle these problems, we propose an image pyramid network based on dual attention mechanism (DAIPNet), which builds an image pyramid to enrich the spatial information while emphasizing multi-scale informative features based on dual attention mechanisms for one-stage object detection. Our framework utilizes a pre-trained backbone as standard detection network, where the designed image pyramid network (IPN) is used as auxiliary network to provide complementary information. Here, the dual attention mechanism is composed of the adaptive feature fusion module (AFFM) and the progressive attention fusion module (PAFM). AFFM is designed to automatically pay attention to the feature maps with different importance from the backbone and auxiliary network, while PAFM is utilized to adaptively learn the channel attentive information in the context transfer process. Furthermore, in the IPN, we build an image pyramid to extract scale-wise features from downsampled images of different scales, where the features are further fused at different states to enrich scale-wise information and learn more comprehensive feature representations. Experimental results are shown on MS COCO dataset. Our proposed detector with a 300 × 300 input achieves superior performance of 32.6% mAP on the MS COCO test-dev compared with state-of-the-art methods.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.283-290
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• 2023

This study investigates the influential factors on online word-of-mouth (eWOM) intentions towards educational tourist destinations, primarily focusing on Korean universities and Chinese tourists. It reveals a positive correlation between eWOM intentions and the desire to enroll in these institutions. The significance of eWOM for attracting Chinese students elucidates the importance of establishing a strong brand image and ensuring high levels of tourist satisfaction. Moreover, social media users who travel for education purposes were found to emphasize self-image consistency and conspicuous self-expression. This research underscores the utility of leveraging social media to enhance the perception of educational tourist attractions, promoting these destinations, and stimulating eWOM, thereby enriching the understanding of the strategic use of social media in international student recruitment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1479-1486
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• 2011

In this paper, a simple and robust algorithm is proposed for detecting straight line segments in a steel plate image. Line detection from a steel plate image is a fundamental task for analyzing and understanding of the image. The proposed algorithm is based on small eigenvalue analysis. The proposed approach scans an input edge image from the top left comer to the bottom right comer with a moving mask. A covariance matrix of a set of edge pixels over a connected region within the mask is determined and then the statistical and geometrical properties of the small eigenvalue of the matrix are explored for the purpose of straight line detection. Before calculating the eigenvalue, each line segment is separated from the edge image where several line segments are overlapped to increase the accuracy of the line detection. Additionally, unnecessary line segments are eliminated by the number of pixels and the directional information of the detected line edges. The respects of the experiments emphasize that the proposed algorithm outperforms the existing algorithm which uses small eigenvalue analysis.

• Journal of Distribution Science
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• v.16 no.4
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• pp.75-82
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• 2018

Purpose - As the role of salespersons in retail stores has expanded from selling products to sharing brand experiences with customers, the importance of research on the effects of salesperson-brand relationships has grown. The purpose of this research is to investigate the influences of salespersons' brand identification on conceptual fluency and customers' service and brand evaluations. It was supposed that salespersons' brand identification is affected by brand knowledge, which is a core dimension of internal branding. Research design, data, and methodology - The author developed a structural model in which salespersons' brand knowledge influences brand identification, hence customers' perception of salesperson-brand image congruence. And it is hypothesized that salesperson-brand image congruence influences conceptual fluency which affects customers' satisfaction and brand evaluation. Data were collected from five department stores in Seoul. Results - First, salespersons' brand knowledge was found to have a significant effect on brand identification. The more a salesperson knows about the affiliated brand, the higher her level of brand identification. Second, salespersons' brand identification influenced salesperson-brand image congruence. Third, salesperson-brand image congruence had a significant effect on brand conceptual fluency. Customers who perceive salesperson-brand image congruent are more likely to process information easily. Finally, conceptual fluency was found to be a significant determinant of store loyalty and brand value evaluation. Conclusions - The results of this study verify importance of salesperson's brand identification on customers' service and brand evaluations. To enhance salespersons' brand identification, retailers should emphasize the importance of internal branding and communication, especially by sharing brand vision, values, and identity with employees at customer contact points. Also, as brand conceptual fluency is a significant determinant of customer responses, retailers need to deliver consistent messages through various components of store environments, including salespersons' attitudes, appearances, and manners, as well as physical store design. With a deeper understanding of the effects of salesperson-brand relationship and brand conceptual fluency, retailers will be able to create more effective brand strategies to enhance their performances. Future studies should consider data from various retail types, such as discount stores, to generalize the findings.

• Journal of the Korean Society for information Management
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• v.19 no.3
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• pp.123-143
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• 2002

Developing good methods for image description and indexing is fundamental for successful image retrieval, regardless of the content of images. Researchers and practitioners in the field of image indexing have developed a variety of image indexing systems and methods with the consideration of information types delivered by images. Such efforts in developing image indexing systems and methods include Panofsky's levels of image indexing and indexing systems adopting different approaches such as thesauri-based approach, classification approach. description element-based approach, and categorization approach. This study investigated users' perception of the objectiveness of image indexing, especially the iconographical analysis of image information advocated by Panofsky. One of the best examples of subjectiveness and conditional-dependence of image information is emotion. As a result, this study dealt with visual emotional information. Experiments were conducted in two phases : one was to measure the degree of agreement or disagreement about the emotional content of pictures among forty-eight participants and the other was to examine the inter-rater consistency defined as the degree of users' agreement on indexing. The results showed that the experiment participants made fairly subjective interpretation when they were viewing pictures. It was also found that the subjective interpretation made by the participants resulted from the individual differences in terms of their educational or cultural background. The study results emphasize the importance of developing new ways of indexing and/or searching for images, which can alleviate the limitations of access to images due to the subjective interpretation made by different users.

• Journal of the Korean Society of Costume
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• v.61 no.2
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• pp.116-130
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• 2011

Ethnic fashion and makeup were studied. 264 fashion designs from pret-$\`{a}$-porter collections in Milan and New York from 2001 S/S to 2005 F/W were analyzed. The major conclusions of the study are as the following: 1. The major types of ethnic fashion and makeup were Africa. American Indian. Japan, India. China and Inca. Makeup types expressed in ethnic fashion were soft smoky, smoky, retro, nature, avant-garde, eastern. 2. Makeup types expressed in ethnic fashion were used for the image for the designer's collections rather than ethnic features. Soft smoky and smoky makeup types were more used than others. 3. Soft smoky makeup types were more expressed in S/S seasons than in F/W seasons. In F/W seasons soft smoky and smoky makeup types were more expressed than other types. 4. Soft smoky and smoky makeup types were more expressed than others in Milan and New York collections commonly. 5. To emphasize the ethnic image for ethnic fashion, ethnic makeup arts like China, Japan, India, Africa, American Indian, Inca makeup arts and soft smoky, smoky makeup arts were represented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.918-920
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• 2011

In this paper, a simple edge pattern classification method is proposed for detecting straight line segments in an image corrupted by impulse noise. Corrupted images have complicated edge patterns. To detect straight line from an complicated edge pattern, it is needed to simplify the entire edge. The proposed algorithm separates the entire edge into 4 directional partial edge patterns. Each line segment is separated from the partial edge image where several line segments are overlapped, and then the straight line is detected. The results of the experiments emphasize that the proposed algorithm is simple but accurate.