• The Journal of Korean Academy of Prosthodontics
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• v.59 no.3
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• pp.271-280
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• 2021

Purpose. The aim of this study was to evaluate the relationship between the patient's occlusion and a cracked tooth by using T-scan occlusal analysis and a quantitative light-induced fluorescence (QLF) technology. Materials and methods. This study was carried out on 51 patients having cracked teeth between January, 2019 and December, 2020. The tooth crack was determined with a Q-ray pen and QLF parameters (ΔF_max and ΔR_max) were obtained by a Q-ray software. T-scan tests were conducted to all subjects and then, the occlusal force and disclosing time were analyzed. Mann-Whitney U test was performed to compare the occlusal force and disclosing time between cracked teeth groups and contra-lateral normal teeth groups (α = .05). Mann-Whitney U test was performed to compare ΔF_max and ΔR_max according to the results of cold/bite tests (α = .05). A Spearman correlation analysis was run to determine the relationship between ΔF_max or ΔR_max and occlusal force or disclosing time (α=.05). Results. The mean occlusal force and disclosing time were significantly higher on cracked teeth than on normal teeth (P < .05). The ΔF_max or ΔR_max were not significantly different according to the results of cold/bite tests (P > .05). There was no correlation between ΔF_max or ΔR_max and occlusal force or disclosing time (P > .05). Conclusion. There was a significant relationship between occlusion and cracked tooth syndrome. QLF has the potential to be a valuable tool for the diagnosis of tooth crack in clinical practice.

• Journal of Korean Home Economics Education Association
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• v.33 no.3
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• pp.143-157
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• 2021

This study analyzed and verified the effects of a dietary education program for Korean young adults in single-person households. The dietary education program was conducted for five weeks (from November 10 to December 8, 2020) for Korean young adults in single-person households living in Seongbuk-gu, via four face-to-face education sessions and one online education session, including both theoretical lectures and practice. The effect of the dietary education program was analyzed through the Nutrition Quotient (NQ) questionnaire for adults provided by the Korean Nutrition Society, a dietary evaluation checklist questionnaire developed by the researchers, and photovoices. The average of 'Nutrition' score increased from 51.81 to 53.20, but there was no statistically significant difference. However, there was a significant change in the 'Moderation' category (p<0.05). As for the researcher-developed dietary evaluation, the average of the 'Importance' area rose from 3.77 to 3.99, but there was no statistically significant difference. The average of the 'Practice' area rose from 3.03 to 3.57, significant results were found (p<0.05). When the pre-/post-tests were compared by the sub-categories, four elements of 'Importance', i.e., balanced meals and avoided foods, and all five elements of 'Practice' were significantly improved (p<0.05). A total of 200 photovoices were analyzed according to Social Cognitive Theory. As a result of the analysis, the deterrents that help people eat healthy homemade food were 48% environmental factors, 30% behavioral factors, and 22% individual cognitive factors. The deterrents found to hinder participants from eating healthy homemade food were 72% environmental factors and 14% individual cognitive and behavioral factors. The results suggest that the dietary education program for Korean young adults in single-person households can be an effective tool that promotes self-motivation, behavioral changes, and improvements of the surrounding environment.

• Journal of the Korean Orthopaedic Association
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• v.56 no.5
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• pp.398-403
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• 2021

Purpose: A biopsy is needed to diagnose soft tissue tumors. However, it is extremely difficult to pinpoint the site of a tumor due to the heterogeneity of sarcomas. Thus, even when an open biopsy is conducted, it is difficult to diagnose a soft tissue tumor. In such cases, an ultrasound (US)-guided biopsy is used to improve the diagnostic accuracy. This study evaluated the accuracy of US-guided biopsy for a diagnosis of soft tissue tumors found initially in a magnetic resonance (MR) perfusion and assessed the availability of positron emission tomography-computed tomography (PET-CT) for a diagnosis of soft tissue tumors. Materials and Methods: From January 2014 to December 2018, the US-guided biopsy was performed on 152 patients with a suspected soft tissue tumor found in an MR perfusion and 86 cases were definitively diagnosed with a soft tissue tumor. The accuracy of the US-guided biopsy was assessed retrospectively. Among the 86 cases, only MR perfusion was used before the biopsy in 50 cases, while both MR perfusion and PET-CT was conducted on 36 cases. The accuracy was analyzed to determine if the PET-CT could improve the precision of a biopsy. Results: From 86 cases, 34 out of 50 cases, in which only MR perfusion had been conducted, matched the result of the definitive diagnosis and the US-guided biopsy. 32 out of 36 cases, in which both PET-CT and MR perfusion were conducted, matched the definitive diagnosis and the US-guided biopsy. These results show significant differences in the accuracy of US-guided biopsy. In the case of soft tissue sarcomas, 6 out of 12 cases, in which only MR perfusion had been conducted, matched the result of the definitive diagnosis and the US-guided biopsy. 17 out of 18 cases, in which both PET-CT and MR perfusion were conducted, matched the definitive diagnosis. Moreover US-guided biopsy also showed significant differences in the accuracy of US-guided biopsy. Conclusion: In diagnosing soft tissue tumors, a US-guided biopsy is a well-known tool for its high accuracy. However, the heterogeneity of sarcoma makes it difficult to locate the exact site for a biopsy using only MR perfusion. Thus, the use of PET-CT will meaningfully improve the accuracy of a diagnosis by precisely targeting the site for the US-guided biopsy.

• The Mathematical Education
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• v.62 no.3
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• pp.435-455
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• 2023

This study primarily focused on the development of an Explainable Artificial Intelligence (XAI) model to discern and analyze papers with significant impact in the field of mathematics education. To achieve this, meta-information from 29 domestic and international mathematics education journals was utilized to construct a comprehensive academic research network in mathematics education. This academic network was built by integrating five sub-networks: 'paper and its citation network', 'paper and author network', 'paper and journal network', 'co-authorship network', and 'author and affiliation network'. The Random Forest machine learning model was employed to evaluate the impact of individual papers within the mathematics education research network. The SHAP, an XAI model, was used to analyze the reasons behind the AI's assessment of impactful papers. Key features identified for determining impactful papers in the field of mathematics education through the XAI included 'paper network PageRank', 'changes in citations per paper', 'total citations', 'changes in the author's h-index', and 'citations per paper of the journal'. It became evident that papers, authors, and journals play significant roles when evaluating individual papers. When analyzing and comparing domestic and international mathematics education research, variations in these discernment patterns were observed. Notably, the significance of 'co-authorship network PageRank' was emphasized in domestic mathematics education research. The XAI model proposed in this study serves as a tool for determining the impact of papers using AI, providing researchers with strategic direction when writing papers. For instance, expanding the paper network, presenting at academic conferences, and activating the author network through co-authorship were identified as major elements enhancing the impact of a paper. Based on these findings, researchers can have a clear understanding of how their work is perceived and evaluated in academia and identify the key factors influencing these evaluations. This study offers a novel approach to evaluating the impact of mathematics education papers using an explainable AI model, traditionally a process that consumed significant time and resources. This approach not only presents a new paradigm that can be applied to evaluations in various academic fields beyond mathematics education but also is expected to substantially enhance the efficiency and effectiveness of research activities.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.57-79
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• 2016

It is a rising trend that the number of users using one of the social media channels, the Social Network Service, so called the SNS, is getting increased. As per to this social trend, more companies have interest in this networking platform and start to invest their funds in it. It has received much attention as a tool spreading and expanding the message that a company wants to deliver to its customers and has been recognized as an important channel in terms of the relationship marketing with them. The environment of media that is radically changing these days makes possible for companies to approach their customers in various ways. Particularly, the social network service, which has been developed rapidly, provides the environment that customers can freely talk about products. For companies, it also works as a channel that gives customized information to customers. To succeed in the online environment, companies need to not only build the relationship between companies and customers but focus on the relationship between customers as well. In response to the online environment with the continuous development of technology, companies have tirelessly made the novel marketing strategy. Especially, as the one-to-one marketing to customers become available, it is more important for companies to maintain the relationship marketing with their customers. Among many SNS, Facebook, which many companies use as a communication channel, provides a fan page service for each company that supports its business. Facebook fan page is the platform that the event, information and announcement can be shared with customers using texts, videos, and pictures. Companies open their own fan pages in order to inform their companies and businesses. Such page functions as the websites of companies and has a characteristic of their brand communities such as blogs as well. As Facebook has become the major communication medium with customers, companies recognize its importance as the effective marketing channel, but they still need to investigate their business performances by using Facebook. Although there are infinite potentials in Facebook fan page that even has a function as a community between users, which other platforms do not, it is incomplete to regard companies' Facebook fan pages as communities and analyze them. In this study, it explores the relationship among customers through the network of the Facebook fan page users. The previous studies on a company's Facebook fan page were focused on finding out the effective operational direction by analyzing the use state of the company. However, in this study, it draws out the structural variable of the network, which customer committment can be measured by applying the social network analysis methodology and investigates the influence of the structural characteristics of network on the business performance of companies in an empirical way. Through each company's Facebook fan page, the network of users who engaged in the communication with each company is exploited and it is the one-mode undirected binary network that respectively regards users and the relationship of them in terms of their marketing activities as the node and link. In this network, it draws out the structural variable of network that can explain the customer commitment, who pressed "like," made comments and shared the Facebook marketing message, of each company by calculating density, global clustering coefficient, mean geodesic distance, diameter. By exploiting companies' historical performance such as net income and Tobin's Q indicator as the result variables, this study investigates influence on companies' business performances. For this purpose, it collects the network data on the subjects of 54 companies among KOSPI-listed companies, which have posted more than 100 articles on their Facebook fan pages during the data collection period. Then it draws out the network indicator of each company. The indicator related to companies' performances is calculated, based on the posted value on DART website of the Financial Supervisory Service. From the academic perspective, this study suggests a new approach through the social network analysis methodology to researchers who attempt to study the business-purpose utilization of the social media channel. From the practical perspective, this study proposes the more substantive marketing performance measurements to companies performing marketing activities through the social media and it is expected that it will bring a foundation of establishing smart business strategies by using the network indicators.