• Journal of Digital Convergence
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• v.19 no.7
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• pp.87-94
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• 2021

The purpose of this study is to categorize tourists according to the types of Korean popular culture as travel motives and to explore their characteristics and behavior in the tourism-related decision-making process. A sample of 12,914 leisure tourists from the 2018 foreign tourist survey data was analyzed using MNL and ANOVA. The popular cultural tourists were categorized into K-food, K-fashion, and K-pop groups. They showed a higher percentage of female tourists, social media usage in the tourism information search, and visits from countries geographically close to Korea. K-pop tourists did not hesitate to choose Korea as the destination and visited Korea the most frequently. They showed the highest satisfaction, revisit intention and recommendation intention, suggesting loyalty and growth potential.

• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.118-127
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• 2021

This study aims to examine satisfaction of nursing students with online classes during first semester of 2020 after COVID-19 pandemic and the difference in satisfaction according to general and online-related characteristics. An online survey was conducted for all nursing students, and subsequently 627 responses were analyzed by t-test and ANOVA with SPSS WIN. Result reveals that students ability to use IT devices was above average, and most of them used laptop computers. Pre-recorded video lecture format was used the most, and improvement of online content was demanded the highest. Overall satisfaction with online classes was scored 3.0/5.0, with the highest satisfaction for anytime and anywhere learning, and the lowest satisfaction in recommending online classes to others. There were significant differences between self-evaluation on own grade, ability to use IT devices, format of online classes, and satisfaction about online classes. Through this study, it would be possible to suggest a plan to increase satisfaction of online class and basic data to establish university policy for online classes after COVID-19.

• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.212-224
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• 2022

This study aims to provide data on attitudes towards the use of Homecare beauty devices in correlation to narcissism of women between ages 30-59. Through statistical analysis of 563 survey questions, data displayed that respondents' age, level of education, marital status, economic status, and career status showed a strong correlation with implicit narcissism, while explicit narcissism only showed a correlation with age and career status. The most popular skincare location was shown to be 'self-provided at home', and the most popular item purchased being 'galvanic devices'. Secondly, attitudes towards the use of homecare beauty devices in correlation towards implicit narcissistic respondents were only to the consideration of its use, while explicit narcissists displayed a strong correlation between the purchase of a product and the recommendation of others. While this is the first study on attitudes towards homecare beauty devices in relation to a personality-based trait like narcissism and it displayed meaningful results, a more in-depth study in the future dealing with a larger region and respondent groups of a wider age and gender group should be undertaken.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.4
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• pp.60-73
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• 2011

Since Jeju Ollegil opened in September 2007 and attracted the sensation of popularity throughout the country, the interest in 'Walking Trails' has increased, and the central ministries and the local governments composite and assign various 'Walking Trails'. Walking trails are not tours on which people go to see one spot and move to another spot by vehicle, but a long linear journey that leads people to see, to feel and to experience a region's landscape and culture while walking on the trail. 'Walking Trails' are efficient routes to discover and to use a former way and to link the various ecological regions' histories and cultural resources, so it is most important to select a route. Although the routes were selected by considering the various planning factors and giving each route a specified theme, some problems like the inconvenience of visitors caused by lack of facilities have occurred. After designation and construction of the trails, they were not properly evaluated by visitors. Therefore, it is the purpose of this study to suggest a better way to construct the trails by surveying visitor satisfaction and by analyzing the impact of planning a route on visitor satisfaction at Bukhansan Dulegil which was completed. For this study, with a questionnaire based on the literature review to identify the important planning factors for selecting a route, a survey was conducted on visitor satisfaction for each section and their intention to revisit and to recommend that trail. Based on the characteristics of each section that was identified in the field research, the trails were classified into five types and satisfaction of each type and each type was analyzed. In addition, analyzing the impact of planning factors on satisfaction, the impact of satisfaction on revisiting and recommending and visitors' perception of the theme, further improvement for better construction of the trail was presented. Satisfaction of sectors with strong natural elements was higher; 'walking comfort' was the highest planning factor affecting satisfaction. In addition, satisfaction was surveyed to have high influence on revisiting and recommending.

• Culinary science and hospitality research
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• v.20 no.2
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• pp.165-182
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• 2014

This study has been carried out to provide marketing materials concerning recognition of parents and students for operators of private cooking education institutes and useful information for the parents who are to send their children to such training institutes, by identifying the effects of the quality of educational services and educational environment of cooking education institutes on satisfaction and positive recommendation intention of trainees. Especially, educational services and educational environment of cooking education institutes that provide education to foster skilled workforce in specialized culinary area were analyzed in detail to draw effective data. Firstly, it has been studied if educational services of cooking education institutes such as educational contents, service of instructors and educational service quality had positive effects on the level of satisfaction about the institutes. Secondly, looking into effects of satisfactory environmental service of cooking education institutes, such as educational environment and quality of administration, on behavioral intention, it has been surveyed that all factors affected satisfaction of students. Thirdly, as for the effect of use intention of action of cooking education institute on positive recommendation intention of trainees, it has been shown that satisfaction with educational services and environment had an effect on positive recommendation intention as well as on intention of reregistration. Therefore, it can be suggested that marketing strategies and management strategies need to be established in a way that quality of education services and educational environment provided by cooking education institutes can render positive behavioral intention to customers of cooking education and the education market through differentiated strategy establishment.

• Journal of Preventive Medicine and Public Health
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• v.27 no.2 s.46
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• pp.366-376
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• 1994

Patients' evaluation of hospital care is one of the most important aspects of quality assessment. Survey allows patients to judge sujectively the events that occur during their hospital visit if performed properly. This study describes the result of a research effort to develop outpatient questionnaire that has sufficient validity and reliability to be used to measure patients' perception of satisfaction in Korea and to investigate influencing factors on patients' satisfaction. Self-administered questionnaire was developed for outpatient and the survey was conducted covering 827 outpatients in a tertiary hospital. It was confirmed by factor analysis that patients evaluate several components of ambulatory care distinctly ; hospital environment, administration and ancillary services, and medical care. We found strong evidence of construct validity and internal consistency for the above three dimensions of hospital process. On the contrary, reliability of overall outcome measures was low. It suggests that three items concerning overall outcome measures have some different meanings in patients' perception. Using logistic regression analysis it was found that previous health status, cost evaluation, and improvement in health status have significant influences on the level of patients' overall satisfaction and that patient's sex, experience of previous visit, expectation for improvement, cost evaluation, and improvement in health status are strongly related with intention to recommend hospital. In spite of some limitations the results of this study can be used helpfully as baseline informations for developing self-administered questionnaire and for exploring the influencing factors on patients' satisfaction. Further comprehensive research efforts should be made on the measurement of ambulatory patients' satisfaction and its related factors in current Korean situation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.5
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• pp.385-393
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• 2013

In the past decade, a paradigm shift from machine-centered to human-centered and from technology-driven to user-driven has been witnessed. Consequently, Social search is getting more social and Social Network Service (SNS) is a popular Web service to connect and/or find friends, and the tendency of users interests often affects his/her who have similar interests. If we can track users' preferences in certain boundaries in terms of Web search and/or knowledge sharing, we can find more relevant information for users. In this paper, we propose a novel Topic Sensitive_Social Relationship Rank (TS_SRR) algorithm. We propose enhanced Web searching idea by finding similar and credible users in a Social Network incorporating social information in Web search. The Social Relation Rank between users are Social Relation Value, that is, for a different topics, a different subset of the above attributes is used to measure the Social Relation Rank. We observe that a user has a certain common interest with his/her credible friends in a Social Network, then focus on the problem of identifying users who have similar interests and high credibility, and sharing their search experiences. Thus, the proposed algorithm can make social search improve one step forward.

• Journal of Dental Rehabilitation and Applied Science
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• v.34 no.4
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• pp.270-279
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• 2018

Purpose: The aim of this study was to assess the patients' perception, acceptance, and preference of the difference between a conventional impression and digital impression through questionnaire survey. Materials and Methods: Thirteen (6 male, 7 female) subjects who experienced both digital and conventional impression at the same day were enrolled in this study. Conventional impression were taken with polyvinylsiloxane and digital impression were performed using a newly developed intra-oral scanner. Immediately after the two impressions were made, a survey was conducted with the standardized questionnaires consisting of the following three categories; 1) general dental treatment 2) satisfaction of conventional impression 3) satisfaction of digital impression. The perceived source of satisfaction was evaluated using Likert scale. The distribution of the answers was assessed by percentages and statistical analyses were performed with the paired t-test, and P < 0.05 was considered significant. Results: There were significant differences of the overall satisfaction between two impression methods (P < 0.05). Digital impression showed high satisfaction in less shortness of breath and odor to participants compared to conventional impression. The use of an oral scanner resulted in a discomfort of TMJ due to prolonged mouth opening and in lower score of the scanner tip size. Conclusion: It was confirmed that the preference for the digital impression using intraoral scanner is higher than the conventional impression. Most survey participants said they would recommend the digital impression to others and said they preferred it for future prosthetic treatment.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.179-196
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• 2019

Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.