• Restorative Dentistry and Endodontics
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• v.46 no.3
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• pp.42.1-42.15
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• 2021

Objectives: This study aimed to analyze the main features of the 25 most-cited articles in minimally invasive access cavities. Materials and Methods: An electronic search was conducted on the Clarivate Analytics' Web of Science 'All Databases' to identify the most-cited articles related to this topic. Citation counts were cross-matched with data from Elsevier's Scopus and Google Scholar. Information about authors, contributing institutions and countries, year and journal of publication, study design and topic, access cavity, and keywords were analyzed. Results: The top 25 most-cited articles received a total of 572 (Web of Science), 1,160 (Google Scholar) and 631 (Scopus) citations. It was observed a positive significant association between the number of citations and age of publication (r = 0.6907, p < 0.0001); however, there was no significant association regarding citation density and age of publication (r = -0.2631, p = 0.2038). The Journal of Endodontics made the highest contribution (n = 15, 60%). The United States had the largest number of publications (n = 7) followed by Brazil (n = 4), with the most contributions from the University of Tennessee and Grande Rio University (n = 3), respectively. The highest number of most-cited articles were ex vivo studies (n = 16), and 'fracture resistance' was the major topic studied (n = 10). Conclusions: This study revealed a growing interest for researchers in the field of minimally invasive access cavities. Future trends are focused on the expansion of collaborative networks and the conduction of laboratory studies on under-investigated parameters.

• The Journal of Bigdata
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• v.6 no.2
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• pp.109-124
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• 2021

In this paper, the structural characteristics of Industry-University cooperation networks are analyzed using network analysis. Recent studies have shown that technological cooperation and joint research has a positive effect on R&D performance. In order to boost innovation performance, various types of cooperative activities and governmental policy supports for major R&D stakeholders(i.e. universities, laboratories, etc.) are provided. However, despite these efforts, the outcome is still insufficient, so it is time to prepare for a plan to build an innovative network to strengthen university-centered Industry-University cooperation activities. Specifically, this study builds the networks according to the form of Industry-University cooperations(i.e. patent, paper, joint research, and technology transfer), and different types of Industry-University cooperation networks are analyzed from a statistical viewpoint by using QAP correlation and regression analyses. The analysis results show that joint research network is closely related to paper network, and is related to other Industry-University cooperation networks. This study is expected to shed a light on supporting innovation activities such as establishing Industry-University cooperation strategies and discovering cooperative partners necessary for creating new growth engines for universities.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.712-720
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• 2022

The use of social media to disseminate news and interact with project stakeholders is increasing over time in the construction industry. Such social media data can be analyzed to get useful insights of the industry such as demands of new housing construction and satisfaction of construction workers. However, there has been a limited attempts to analyze social media data related to the construction industry. The objective of this study is to collect and analyze construction related tweets to understand the overall sentiments of individuals and organizations about the construction industry. The study collected 87,244 tweets from April 6, 2020, to April 13, 2020, which had hashtags relevant to the construction industry. The tweets were then analyzed to evaluate its sentiments polarity (positive or negative) and sentiment intensity or scores (-1 to +1). Descriptive statistics were produced for the tweets and the sentiment scores were visualized in a scatterplot to show the trend of the sentiment scores over time. The results shows that the overall sentiment score of all the tweets was slightly positive (0.0365). Negative tweets were retweeted and marked as favorite by more users on average than the positive ones. More specifically, the tweets with negative sentiments were retweeted by 2,802 users on average compared to the tweets with positive sentiments (247 average retweet count). This study can potentially be expanded in the future to produce a real time indicator of the construction market industry such as the increased availability of construction jobs, improved wage rates, and recession.

• 한국노년학
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• v.39 no.4
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• pp.883-893
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• 2019

The purpose of this study is to analyze the characteristics of the elderly patients with depression who were admitted to the hospital with intentional self-harm. 3,280 patients were selected from KCDC database(2011-2015) using STATA 12.0. Analysis results show that gender(female), residence(micropolitan city), result of suicide(death), risk factors(financial problems, psychological problems, physical disease, conflicts with family, place(non-residence) method of suicide(poisoning) were statistically significant. The hospital should detect the elderly patient with depression when they admitted.

• Restorative Dentistry and Endodontics
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• v.45 no.4
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• pp.55.1-55.12
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• 2020

Objectives: This study investigated the effects of physically damaged and resin-contaminated tips on radiant emittance, comparing them with new undamaged, non-contaminated tips using 3 pieces of spectrophotometric laboratory equipment. Materials and Methods: Nine tips with damage and/or resin contaminants from actual clinical situations were compared with a new tip without damage or contamination (control group). The radiant emittance was recorded using 3 spectrophotometric methods: a laboratory-grade thermopile, a laboratory-grade integrating sphere, and a portable light collector (checkMARC). Results: A significant difference between the laboratory-grade thermopile and the laboratory-grade integrating sphere was found when the radiant emittance values of the control or damaged/contaminated tips were investigated (p < 0.05), but both methods were comparable to checkMARC (p > 0.05). Regardless of the method used to quantify the light output, the mean radiant emittance values of the damaged/contaminated tips were significantly lower than those of the control (p < 0.05). The beam profile of the damaged/contaminated tips was less homogeneous than that of the control. Conclusions: Damaged/contaminated tips can reduce the radiant emittance output and the homogeneity of the beam, which may affect the energy delivered to composite restorations. The checkMARC spectrophotometer device can be used in dental offices, as it provided values close to those produced by a laboratory-grade integrated sphere spectrophotometer. Dentists should assess the radiant emittance of their light-curing units to ensure optimal curing in photoactivated, resin-based materials.

• Safety and Health at Work
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• v.14 no.3
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• pp.272-278
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• 2023

Background: Some working conditions may pose a higher physical or psychological demand to pregnant women leading to increased risks of pregnancy complications. Objectives: We assessed the association of woman's employment status and the industrial classification with obstetric complications. Methods: We conducted a national population study using the National Health Information Service database of Republic of Korea. Our analysis encompassed 1,316,310 women who experienced first-order live births in 2010-2019. We collected data on the employment status and the industrial classification of women, as well as their diagnoses of preeclampsia (PE) and gestational diabetes mellitus (GDM) classified as A1 (well controlled by diet) or A2 (requiring medication). We calculated odds ratios (aORs) of complications per employment, and each industrial classification was adjusted for individual risk factors. Results: Most (64.7%) were in employment during pregnancy. Manufacturing (16.4%) and the health and social (16.2%) work represented the most prevalent industries. The health and social work exhibited a higher risk of PE (aOR = 1.11, 95% confidence interval [CI]: 1.03-1.21), while the manufacturing industry demonstrated a higher risk of class A2 GDM (1.20, 95% CI: 1.03-1.41) than financial intermediation. When analyzing both classes of GDM, women who worked in public administration and defense/social security showed higher risk of class A1 GDM (1.04, 95% CI: 1.01, 1.07). When comparing high-risk industries with nonemployment, the health and social work showed a comparable risk of PE (1.02, 95% CI: 0.97, 1.07). Conclusion: Employment was associated with overall lower risks of obstetric complications. Health and social service work can counteract the healthy worker effect in relation to PE. This highlights the importance of further elucidating specific occupational risk factors within the high-risk industries.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.99-105
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• 2023

In the 4th industrial revolution, the field of criminal justice is paying attention to Legaltech using artificial intelligence to provide efficient legal services. This paper attempted to create a crime prediction model that can apply Recurrent Neural Network(RNN) to increase the potential for using legal technology in the domestic criminal justice field. To this end, the crime process was divided into pre, during, and post stages based on the criminal facts described in the judgment, utilizing crime script analysis techniques. In addition, at each time point, the method and evidence of crime were classified into objects, actions, and environments based on the sentence composition elements and the 8 principles of investigation. The case summary analysis framework derived from this study can contribute to establishing situational crime prevention strategies because it is easy to identify typical patterns of specific crime methods. Furthermore, the results of this study can be used as a useful reference for research on generating crime situation prediction data based on RNN models in future follow-up studies.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.109-126
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• 2023

Early detection of forest fires is essential in preventing large-scale forest fires. Predicting forest fires serves as a vital early detection method, leading to various related studies. However, many previous studies focused solely on climate and geographic factors, overlooking human factors, which significantly contribute to forest fires. This study aims to develop forest fire prediction models that take into account human, weather and geographical factors. This study conducted a comparative analysis of four machine learning models alongside the logistic regression model, using forest fire data from Gangwon-do spanning 2003 to 2020. The results indicate that XG Boost models performed the best (AUC=0.925), closely followed by Random Forest (AUC=0.920), both of which are machine learning techniques. Lastly, the study analyzed the relative importance of various factors through permutation feature importance analysis to derive operational insights. While meteorological factors showed a greater impact compared to human factors, various human factors were also found to be significant.

• Restorative Dentistry and Endodontics
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• v.48 no.3
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• pp.27.1-27.11
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• 2023

Objectives: Advancements in nanotechnology have led to the widespread usage of nanoparticles in the endodontic field. This bibliometric study aimed to determine and analyze the top 100 most-cited articles about nanoparticles in endodontics from 2000 to 2022. Materials and Methods: A detailed electronic search was conducted on the "Clarivate Analytics Web of Science, All Databases" to receive the most-cited articles related to the topic. Articles were ranked in descending order based on their citation counts, and the first 100 were selected for bibliometric analysis. Parameters such as citation density, publication year, journal, country, institution, author, study design, study field, evidence level, and keywords were analyzed. Results: The top 100 most-cited articles received 4,698 citations (16-271) with 970.21 (1.91-181) citation density in total. Among decades, citations were significantly higher in 2011-2022 (p < 0.001). Journal of Endodontics had the largest number of publications. Canada and the University of Toronto made the highest contribution as country and institution, respectively. Anil Kishen was the 1 who participated in the largest number of articles. The majority of the articles were designed in vitro. The main study field was "antibacterial effect." Among keywords, "nanoparticles" followed by "Enterococcus faecalis" were used more frequently. Conclusions: Developments in nanotechnology had an impact on the increasing number of studies in recent years. This bibliometric study provides a comprehensive view of nanoparticle advances and trends using citation analysis.

• Journal of Industrial Convergence
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• v.21 no.9
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• pp.23-32
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• 2023

Interest in Serious Games for Healthcare (SGHs) that can improve health through games is increasing. Digital Therapeutics (DTx) is a treatment that must be approved for effectiveness and safety, so it should follow the traditional drug distribution method, but SGHs are wellness products that are more flexible in terms of adoption and diffusion than DTx. SGHs are effective because it can provide customized services through continuous monitoring and feedback. When SGHs are applied to cognitive impairment treatment or behavioral correction, malfunctions and side effects are minor. This study developed research model based on the Valence Framework, gathered data from 142 undergraduates, and demonstrated that only the perceived benefits have a statistically significant positive (+) effect on SGHs acceptance intentions. Based on these results, this study suggests that SGHs companies should promote benefits in accepting SGHs for general users and they need for a distribution and analytics platform strategy based on a data-driven approach.