• Smart Media Journal
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• v.12 no.7
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• pp.43-51
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• 2023

As online transactions increase, the image of clothing has a great influence on consumer purchasing decisions. The importance of image information for clothing materials has been emphasized, and it is important for the fashion industry to analyze clothing images and grasp the materials used. Textile materials used for clothing are difficult to identify with the naked eye, and much time and cost are consumed in sorting. This study aims to classify the materials of textiles from clothing images based on deep learning algorithms. Classifying materials can help reduce clothing production costs, increase the efficiency of the manufacturing process, and contribute to the service of recommending products of specific materials to consumers. We used machine vision-based deep learning algorithms ResNet and Vision Transformer to classify clothing images. A total of 760,949 images were collected and preprocessed to detect abnormal images. Finally, a total of 167,299 clothing images, 19 textile labels and 20 fabric labels were used. We used ResNet and Vision Transformer to classify clothing materials and compared the performance of the algorithms with the Top-k Accuracy Score metric. As a result of comparing the performance, the Vision Transformer algorithm outperforms ResNet.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.10
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• pp.1701-1706
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• 2013

Domestic and overseas information with regard to harmful substances are analyzed. From the results, environmental-derived hazard chemicals, which show relatively low recognition, and hazard chemicals that occur unavoidably in food manufacturing process are selected as target harmful substances. Thus, educational leaflet contents were developed based on these substances. To find the effects of education with the above contents, this study surveyed 120 female college students living in Seoul. The purpose of the survey is to analyze the change in recognition, attitude and behavior on hazard chemicals in foods. The survey found that the recognition on harmful substance in foods increased; from 31.5~78.0% before education to 98.8% after education. It also indicates that vague anxiety in which the harmful substances may damage their health decreased by approx. 25.0%; from 77.8% before education to 52.8% after education. For the question of what they would do when government promotes to reduce harmful substances in foods, 12.3% of respondents said that they would actively follow the suggestions and 73.5% of them said that they would do their best before an education. However, 56.1% of them said that they would actively follow the suggestions after the education. It indicates that the ability to recognize harmful substances changed after the education. With regard to consumer behavior, when they knew about the harmful substances in foods, 49.6% of them said that they would select foods after investigating relevant information before the education, while 77.4% of them said that after the education; which is an increase of 27.8%. Further, 45.4% of them said that they would not purchase relevant foods before the education, while 20.9% of them said that after the education; which is a decrease of 24.5%. Therefore, it is considered that vague anxiety of consumers can be eliminated by providing persuasive information on harmful substances. To expand on the communication channel with consumers for food safety, contents development and educational promotion should be enhanced for providing food safety related information.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.127-133
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• 2021

In this study, an augmented reality-based make-up tool was built to analyze the user's face shape based on face-type reference model data and to provide virtual makeup by providing face-type makeup. To analyze the face shape, first recognize the face from the image captured by the camera, then extract the features of the face contour area and use them as analysis properties. Next, the feature points of the extracted face contour area are normalized to compare with the contour area characteristics of each face reference model data. Face shape is predicted and analyzed using the distance difference between the feature points of the normalized contour area and the feature points of the each face-type reference model data. In augmented reality-based virtual makeup, in the image input from the camera, the face is recognized in real time to extract the features of each area of the face. Through the face-type analysis process, you can check the results of virtual makeup by providing makeup that matches the analyzed face shape. Through the proposed system, We expect cosmetics consumers to check the makeup design that suits them and have a convenient and impact on their decision to purchase cosmetics. It will also help you create an attractive self-image by applying facial makeup to your virtual self.

• Journal of Korean Ophthalmic Optics Society
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• v.7 no.1
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• pp.45-50
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• 2002

The 'hands-on' craftsmanship of the 20th century has came and gone. Today, we are dealing with whole new, 'cerebral approach,' to concept and design with this new approach, design and function are very much dependant upon planning, sales, promotion, and the formative technique of the design industry. The innovative process of design constantly change as it reflects the needs and wants of society. It is and industry that constantly change as it reflects the needs and wants of society. It is and industry that constantly remakes and reshapes itself to suit current trend and outlook. The current idea being that consumers are looking for quality over quantity. Due to the 20th centuries dominant philosophy of functionalism, production intended to standardize the individual's purchasing choice. Aesthetic, or philosophic qualities played a second fiddle to the functional bias of a product, With production, Marketing, and research and development are integrated into the management process. This translates as good which include efficiency, quality, durability, and credibility an trademark and style. There is a definite 'post-modernist' movement and style in 21st century. Every possibility is available as the old boundaries of the 20th century are laid aside. There is a new, transformative quality to the current paradigm of design. The old "should" and "should not" of design no longerapplies. The integrated rative of design solves the usual disparity between aesthetic qualities and production. Design and profirability need not be stranger to one another. It can differentiate the image perceived of both enterprises and consumers by making use of integrated goods services. With an integrated system. both producers and designers win. While design gets full access to design in turn. All consumers make decisions based upon the evaluation of quality, service, and image ; even though it may not be a conscious decision to do so. Consumers are fully integrated human beings ; therefore producers who apply the new, integrated paradigmatic approach to concept, design, and production will reap the harvest of making a true relationship with individual buyer.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.55-78
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• 2021

Tosolve complex and diverse social problems and ensure the quality of life of individuals, social robots that can interact with humans are attracting attention. In the past, robots were recognized as beings that provide labor force as they put into industrial sites on behalf of humans. However, the concept of today's robot has been extended to social robots that coexist with humans and enable social interaction with the advent of Smart technology, which is considered an important driver in most industries. Specifically, there are service robots that respond to customers, the robots that have the purpose of edutainment, and the emotionalrobots that can interact with humans intimately. However, popularization of robots is not felt despite the current information environment in the modern ICT service environment and the 4th industrial revolution. Considering social interaction with users which is an important function of social robots, not only the technology of the robots but also other factors should be considered. The design elements of the robot are more important than other factors tomake consumers purchase essentially a social robot. In fact, existing studies on social robots are at the level of proposing "robot development methodology" or testing the effects provided by social robots to users in pieces. On the other hand, consumer emotions felt from the robot's appearance has an important influence in the process of forming user's perception, reasoning, evaluation and expectation. Furthermore, it can affect attitude toward robots and good feeling and performance reasoning, etc. Therefore, this study aims to verify the effect of appearance of social robot and consumer emotions on consumer's attitude toward social robot. At this time, a social robot design evaluation model is constructed by combining heterogeneous data from different sources. Specifically, the three quantitative indicator data for the appearance of social robots from the ABOT Database is included in the model. The consumer emotions of social robot design has been collected through (1) the existing design evaluation literature and (2) online buzzsuch as product reviews and blogs, (3) qualitative interviews for social robot design. Later, we collected the score of consumer emotions and attitudes toward various social robots through a large-scale consumer survey. First, we have derived the six major dimensions of consumer emotions for 23 pieces of detailed emotions through dimension reduction methodology. Then, statistical analysis was performed to verify the effect of derived consumer emotionson attitude toward social robots. Finally, the moderated regression analysis was performed to verify the effect of quantitatively collected indicators of social robot appearance on the relationship between consumer emotions and attitudes toward social robots. Interestingly, several significant moderation effects were identified, these effects are visualized with two-way interaction effect to interpret them from multidisciplinary perspectives. This study has theoretical contributions from the perspective of empirically verifying all stages from technical properties to consumer's emotion and attitudes toward social robots by linking the data from heterogeneous sources. It has practical significance that the result helps to develop the design guidelines based on consumer emotions in the design stage of social robot development.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.6
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• pp.197-211
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• 2021

In the service industry the types are diversifying and the scale of service companies is greatly improving. Such a phenomenon is caused by economic growth and technological development diversifying consumer needs creating demand for new services maturing the service industry and intensifying competition among companies in the form of global competition. It can be said that this is because it is necessary to improve competitiveness by utilizing the economy of scale. Research is needed on the impact of entrepreneurship on various outcome variables in order for service organization managers to respond quickly to diverse and rapidly changing environments and achieve organizational outcomes and corporate goals of management outcomes. The purpose of this study was to empirically analyze the relationship in which the entrepreneurial spirit of a manager influences the relationship between customer orientation, which is an organizational result, customer satisfaction, and financial result, which is a management result. In order to verify such research, the questionnaire was composed of one business owner questionnaire, two employee questionnaires, and two customer questionnaires. The questionnaire was distributed to a total of 400 companies, and the questionnaires of 340 companies were collected. Of these, 303 companies, excluding the questionnaires of 37 companies with many dishonest or missing values, were used for hypothesis testing. The results of this study can be summarized as follows. First, entrepreneurship had a positive (+) effect on customer orientation, supporting the hypothesis. Second, customer orientation showed a positive (+) effect on customer satisfaction, supporting the hypothesis. Third, customer satisfaction showed a positive (+) effect on financial outcomes, supporting the hypothesis. Fourth, it was found that entrepreneurship influences customer satisfaction through customer orientation, and customer satisfaction affects financial outcomes. It turns out that customer orientation between entrepreneurship and customer satisfaction is completely mediated, and customer satisfaction is completely mediated by customer orientation and financial outcomes. The relationship between entrepreneurship and management improved employee behavior and attitudes, which is an individual outcome, and this change was found to improve customer satisfaction, which is an organizational outcome. It makes frequent contact with customers in the process of servicing them. Employee roles are important at service contacts and influence service purchases. Employees facing customers through service contacts act as a decisive factor in maintaining a continuous relationship with customers. Within a beauty service company, it is necessary to create a customer-oriented environment among workers. It suggests that customer-oriented companies and employees can anticipate their desires and provide products or services of superior value to achieve greater customer satisfaction and a competitive advantage. In addition, it was clarified that customer satisfaction has an aspect relationship with financial management, which is a management result. Therefore, it is suggested that the entrepreneurial spirit is an important factor for the management of a beauty service company to secure competitiveness and improve results.