• Journal of Nutrition and Health
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• v.40 no.6
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• pp.566-575
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• 2007

The purpose of this research was to understand how individuals reflect on the frequency and quantity of foods that they consume. Participants selected 5 males and 15 females aged 30 years or older were first interviewed on the frequency of their food consumption. Then based on this data, they were given a cognitive interview using the method of verbal proving. The individual cognitive interviews were recorded with consent while being conducted after complete approval by the Seoul National University Institution Review Board. The recorded material was evaluated using a thematic analysis after transcribing them into text. By analyzing stages of reflection, the major barriers to make the device difficult are revealed: 1) More difficulty in remembering events over the course of a full year due to diversification in the types of food that people consume 2) difficulty calculating the average for seasonal foods 3) difficulty estimating the amount of consumption from the photos presented 4) difficulty estimating amount of consumption from the quantity presented 5) difficulty processing foods that people think are healthy and foods are unhealthy simultaneously 6) difficulty having to consider foods where target food goes in as an ingredient; 7) difficulties arising from having to increase frequency when the amount consumed is higher than the quantity that is presented 8) difficulty having to combine the frequency and quantity of each food item when numerous foods are clustered into one category. These findings show that the less participants were involved in cooking, the more diverse their eating habits were, and the more they tried to adhere to rules of filling out the questionnaire, the more it was difficult for them to come up with an answer to the question being asked. It therefore seems necessary to construct a Food Frequency questionnaire that is attentive to these problems that arise from the recall stages.

• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.527-538
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• 2014

The demand prediction is a critical issue for the film industry. As the social media, such as Twitter and Facebook, gains momentum of late, considerable efforts are being dedicated to prediction and analysis of hit movies based on unstructured text data. For prediction of trends found in commercially successful films, the correlations between the amount of data and hit movies may be analyzed by estimating the data variation by period while opinion mining that assigns sentiment polarity score to data may be employed. However, it is not possible to understand why the audience chooses a certain movie or which attribute of a movie is preferred by using such a quantitative approach. This has limited the efforts to identify factors driving a movie's commercial success. In this regard, this study aims to investigate a movie's attributes that reflect the interests of the audience. This would be done by extracting topic keywords that represent the contents of Twits through frequency measurement based on the collected Twitter data while analyzing responses displayed by the audience. The objective is to propose factors driving a movie's commercial success.

• The KIPS Transactions:PartC
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• v.11C no.7 s.96
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• pp.871-878
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• 2004

Recenty, there has been great interest in MANET from various areas. In this paper we focus on performance analysis of on demand routing protocols surf as DSR, AODV, and TORA in MANET. We have conducted several simulations concerned with application service data such as sensor, text. voice, and video data. And then, we have evaluated the performance of three protocols in a pre-designed ad hoc network, which is consisted of 20 nodes. As a result, we have obtained quantitative data for packet delivery fraction, average end to-end delay, routing load, channel utilization from upper layer and supportable routing protocol for application service data. The results can be used for designing specific-purposed ad-hoc networks.

• Journal of Dental Anesthesia and Pain Medicine
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• v.22 no.2
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• pp.87-96
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• 2022

This study aimed to assess the combined use of extraoral vibratory stimulation and extraoral cooling in reducing the pain (subjective and objective) of dental local anesthesia administration in children. PubMed, Cochrane Central Register of Controlled Trials, and Ovid SP databases were searched up to July 2021. Article titles were screened and full-text evaluations of the selected articles were performed. Finally, seven studies (391 children, aged 4 - 12 years) were included in this qualitative and quantitative analysis. The pooled data determined the combined effect of extraoral vibration and extraoral cooling as a single measure. Extraoral vibration or cooling alone were not compared. The measured primary and secondary outcomes were pain perception and subjective and objective pain, respectively. When compared with the control, extraoral vibration and cooling resulted in significant differences in the mean combined data for the variables, pain perception, and pain reaction. Children's subjective pain as measured by pain scores were reduced when extraoral vibration and cooling was used during local anesthesia administration (mean difference -3.52; 95% confidence interval [-5.06 - 1.98]) and objective pain (mean difference -1.46; 95% confidence interval [-2.95 - 0.02] ; mean difference -1.93; 95% confidence interval [-3.72 - 0.14]). Within the confines of this systematic review, there is low-quality evidence to support the use of combined extraoral vibration and cooling for reducing pain (subjective and objective) during intraoral local anesthesia administration in children.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.4
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• pp.65-79
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• 2022

This study identified smart manufacturing technologies using patent and topic modeling, and compared the technology development trends in countries such as the United States, Japan, Germany, China, and South Korea. To this purpose, this study collected patents in the United States and Europe between 1991 and 2020, processed patent abstracts, and identified topics by applying latent Dirichlet allocation model to the data. As a result, technologies related to smart manufacturing are divided into seven categories. At a global level, it was found that the proportion of patents in 'data processing system' and 'thermal/fluid management' technologies is increasing. Considering the fact that South Korea has relative competitiveness in thermal/fluid management technologies related to smart manufacturing, it would be a successful strategy for South Korea to promote smart manufacturing in heavy and chemical industry. This study is significant in that it overcomes the limitations of quantitative technology level evaluation proposed a new methodology that applies text mining.

• The Research Journal of the Costume Culture
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• v.31 no.2
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• pp.141-160
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• 2023

Controlling fashion waste throughout the entire product lifecycle is critical in a circular economy. This study explored the possibility of establishing a public recycling system for fashion waste. Since consumer interests and participation are essential, theoretical research, social-text analysis, and quantitative research were conducted to identify consumers' perceptions of the public recycling of fashion waste and circular fashion. Data were collected via an online survey among women in their 20-30's living in Korea, and 304 samples were used for data analysis. The results were as follows. First, consumers' perceptions of recycling fashion waste were composed of recycling difficulty, the need for public recycling, and the need for EPR. Circular fashion perception comprised favor, environment protection, attractiveness, economics, quality and hygiene risks, and lack of diversity. Second, the reuse-recycle attitude and need for EPR affected the favor of all types of circular fashion products. Third, environmental concerns impacted attractiveness, and the favor significantly affected the purchase intention of all types of circular fashion products. In particular, quality and hygiene risk negatively affected the purchase intention of used-fashion products, while attractiveness positively impacted the purchase intention of upcycled-fashion products. The results implied that discussing the public recycling system of fashion waste and EPR policy is imperative. The results also showed the need to classify different types of circular fashion products, such as used, upcycled, and regenerated fashion items, to examine consumers' perceptions. In addition, the recycling of the fashion waste scale developed in this study could be used for further research.

• Imaging Science in Dentistry
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• v.54 no.1
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• pp.1-11
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• 2024

Purpose: This study was conducted to investigate the safety of dental imaging in pregnant women with respect to fetal health. Materials and Methods: Searches were conducted of the PubMed, Scopus, and Web of Science databases in May 2023. The inclusion criteria encompassed cross-sectional and longitudinal studies that focused on the analysis of diagnostic dental imaging in pregnant women, as well as studies utilizing phantoms to simulate imaging examinations. The exclusion criteria consisted of reviews, letters to the editor, book chapters, and abstracts from scientific conferences and seminars. Results: A total of 3,913 articles were identified. Based on a review of the titles and abstracts, 3,892 articles were excluded, leaving 21 articles remaining for full-text review. Of these, 18 were excluded, and 4 additional articles were included as cross-references. Ultimately, 7 articles underwent quantitative-qualitative analysis. Three retrospective studies were focused on pregnant women who underwent dental imaging procedures. The remaining 4 studies utilized female phantoms to simulate imaging examinations and represent the radiation doses absorbed by the uterus or thyroid. Conclusion: Few dental radiology studies have been conducted to determine the safe radiation threshold for pregnant women. Additionally, the reviewed articles did not provide numbers of dental examinations, by type, corresponding to this dose. Dental imaging examinations of pregnant women should not be restricted if clinically indicated. Ultimately, practitioners must be able to justify the examination and should adhere to the "as low as diagnostically acceptable, being indication-oriented and patient-specific" (ALADAIP) principle of radioprotection.

• Journal of Korea Entertainment Industry Association
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• v.15 no.2
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• pp.123-135
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• 2021

The data processing of this study is focused on keywords related to 'Corona 19 and professional baseball' and 'Corona 19 and professional baseball no spectators', using text mining and social network analysis of textom program to identify problems and view quality. It was used to set the variable of For quantitative analysis, a questionnaire on viewing quality was constructed, and out of 270 survey respondents, 250 questionnaires were used for the final study. As a tool for securing the validity and reliability of the questionnaire, exploratory factor analysis and reliability analysis were conducted, and IPA analysis (importance-satisfaction) was conducted based on the questionnaire that secured validity and reliability, and the results and strategies were presented. As a result of IPA analysis, factors related to the image (image composition, image coloration, image clarity, image enlargement and composition, high-quality image) were found in the first quadrant, and the second quadrant was the game situation (support team game level, support player game level, star). Player discovery, competition with rival teams), game information (match schedule information, player information check, team performance and player performance, game information), interaction (consensus with the supporting team), and some factors appeared. The factors of commentator (baseball-related knowledge, communication ability, pronunciation and voice, use of standard language, introduction of game-related information) and interaction (real-time communication with the front desk, sympathy with viewers, information exchange such as chatting) appeared.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.135-144
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• 2024

In this study, we propose an automatic classification model for quantitative multidimensional analysis based on facet theory to understand public opinions and demands on major issues through big data analysis. Civil complaints, as a form of public feedback, are generated by various individuals on multiple topics repeatedly and continuously in real-time, which can be challenging for officials to read and analyze efficiently. Specifically, our research introduces a new classification framework that utilizes facet theory and political analysis models to analyze the characteristics of citizen complaints and apply them to the policy-making process. Furthermore, to reduce administrative tasks related to complaint analysis and processing and to facilitate citizen policy participation, we employ deep learning to automatically extract and classify attributes based on the facet analysis framework. The results of this study are expected to provide important insights into understanding and analyzing the characteristics of big data related to citizen complaints, which can pave the way for future research in various fields beyond the public sector, such as education, industry, and healthcare, for quantifying unstructured data and utilizing multidimensional analysis. In practical terms, improving the processing system for large-scale electronic complaints and automation through deep learning can enhance the efficiency and responsiveness of complaint handling, and this approach can also be applied to text data processing in other fields.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.179-200
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• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.