• Journal of dental hygiene science
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• v.20 no.4
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• pp.187-199
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• 2020

Background: Korean dental hygienists perform various tasks under the supervision of dentists in addition to the tasks listed in the law. Many meaningful studies have been conducted to determine the actual tasks of dental hygienists, but these studies did not show common results due to the differences in research methods or designs. Hence, this study aimed to review the reported data on the tasks of dental hygienists in Korea and to clarify them based on a systematic literature review. Methods: For the literature search, the COre, Standard, and Ideal model presented by the National Library of Medicine was referenced. Seven databases were searched for literatures published in Korea, including PubMed, and Google Scholar. Of the 352 studies found using key words, titles, and abstracts, 46 were finally extracted based on the first and second exclusion criteria. After confirming the tasks of Korean dental hygienists in 46 literatures, 136 tasks were listed and calculated as appearance rate in the literature. Results: The most common tasks in 46 studies were fluoride application (67.2%), radiography (65.4%), scaling (65.4%), sealant (60.7%), patient management and counseling (56.7%), tooth-brushing education (52.2%), impression taking with alginate (50.1%), and making temporary crowns (47.9%). The most mentioned tasks of dental hygienists in public health centers were fluoride application (100%), sealant (100%), oral health education (71.4%), public oral health program evaluation (71.4%), school fluoride mouth-rinsing program (71.4%), water fluoridation (57.1%), tooth-brushing education (57.1%), school oral health programs (57.1%), and public elderly oral health programs (57.1%). Conclusion: This study showed that Korean dental hygienists had 136 tasks by reviewing 46 related studies and that the main job of Korean dental hygienists was oral disease prevention including scaling, sealant, and fluoride application.

• Smart Media Journal
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• v.10 no.1
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• pp.32-38
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• 2021

Image classification through deep learning on the image from photographs has been a very active research field for the past several years. In this paper, we propose a method of automatically discriminating stone images from domestic source through deep learning, which is to use Python's hash library to scan 300×300 pixel photo images of granites such as Hwangdeungseok, Goheungseok, and Pocheonseok, performing data preprocessing to create learning images by examining duplicate images for each stone, removing duplicate images with the same hash value as a result of the inspection, and deep learning by stone. In addition, to utilize VGGNet, the size of the images for each stone is resized to 224×224 pixels, learned in VGG16 where the ratio of training and verification data for learning is 80% versus 20%. After training of deep learning, the loss function graph and the accuracy graph were generated, and the prediction results of the deep learning model were output for the three kinds of stone images.

• Journal of the Korean Society for information Management
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• v.38 no.2
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• pp.113-127
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• 2021

The purpose of this study is to propose a personalized book recommendation system to promote the use of university libraries. In particular, unlike many recommended services that are based on existing users' preferences, this study proposes a method that derive evaluation metrics using individual users' book rental history and tendencies, which can be an effective alternative when users' preferences are not available. This study suggests models using two matrix decomposition methods: Singular Value Decomposition(SVD) and Stochastic Gradient Descent(SGD) that recommend books to users in a way that yields an expected preference score for books that have not yet been read by them. In addition, the model was implemented using a user-based collaborative filtering algorithm by referring to book rental history of other users that have high similarities with the target user. Finally, user evaluation was conducted for the three models using the derived evaluation metrics. Each of the three models recommended five books to users who can either accept or reject the recommendations as the way to evaluate the models.

• Imaging Science in Dentistry
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• v.52 no.2
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• pp.133-140
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• 2022

Purpose: The aim of this review was to systematically analyze the available literature on the correlation between the gray values (GVs) of cone-beam computed tomography (CBCT) and the Hounsfield units (HUs) of computed tomography (CT) for assessing bone mineral density. Materials and Methods: A literature search was carried out in PubMed, Cochrane Library, Google Scholar, Scopus, and LILACS for studies published through September 2021. In vitro, in vivo, and animal studies that analyzed the correlations GVs of CBCT and HUs of CT were included in this review. The review was prepared according to the PRISMA checklist for systematic reviews, and the risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. A quantitative analysis was performed using a fixed-effects model. Results: The literature search identified a total of 5,955 studies, of which 14 studies were included for the qualitative analysis and 2 studies for the quantitative analysis. A positive correlation was observed between the GVs of CBCT and HUs of CT. Out of the 14 studies, 100% had low risks of bias for the domains of patient selection, index test, and reference standards, while 95% of studies had a low risk of bias for the domain of flow and timing. The fixed-effects meta-analysis performed for Pearson correlation coefficients between CBCT and CT showed a moderate positive correlation (r=0.669; 95% CI, 0.388 to 0.836; P<0.05). Conclusion: The available evidence showed a positive correlation between the GVs of CBCT and HUs of CT.

• The korean journal of orthodontics
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• v.52 no.3
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• pp.182-200
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• 2022

Objective: This study aims to examine the effectiveness of miniscrew assisted rapid palatal expansion (MARPE) treatment in late adolescents and adult patients using cone-beam computed tomography (CBCT). Methods: Literature search was conducted in five electronic databases (PubMed, Embase, Scopus, Web of Science, and Cochrane Library) based on the PICOS keyword design focusing on MARPE. Out of the 18 CBCT screened outcomes, only nine parameters were sufficient for the quantitative meta-analysis. The parameters were classified into three main groups: 1) skeletal changes, 2) alveolar change, and 3) dental changes. Heterogeneity test, estimation of pooled means, publication bias, sensitivity analysis and risk of bias assessment were also performed. Results: Upon database searching, only 14 full-text articles were qualified from the 364 obtained results. Heterogeneity test indicated the use of the random-effects model. The pooled mean estimate were as follows: 1) Skeletal expansion: zygomatic width, 2.39 mm; nasal width, 2.68 mm; jugular width, 3.12 mm; and midpalatal suture at the posterior nasal spine and anterior nasal spine, 3.34 mm and 4.56 mm, respectively; 2) Alveolar molar width expansion, 4.80 mm; and 3) Dental expansion: inter-canine width, 3.96 mm; inter-premolar width, 4.99 mm and inter-molar width, 5.99 mm. The percentage of expansion demonstrated a skeletal expansion (PNS) of 55.76%, alveolar molar width expansion of 24.37% and dental expansion of 19.87%. Conclusions: In the coronal view, the skeletal and dental expansion created by MARPE was of the pyramidal pattern. MARPE could successfully expand the constricted maxilla in late adolescents and adult patients.

• Animal Bioscience
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• v.35 no.7
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• pp.975-988
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• 2022

Objective: In this study, we aimed to identify long non-coding RNAs (lncRNAs) that play important roles in starvation stress, analyze their functions, and discover potential molecular targets to alleviate starvation stress to provide a theoretical reference for subsequent in-depth research. Methods: We generated a piglet starvation stress animal model. Nine Yorkshire weaned piglets were randomly divided into a long-term starvation stress group (starved for 72 h), short-term starvation stress group (starved for 48 h), and the control group. LncRNA libraries were constructed using high-throughput sequencing of piglet ileums. Results: We obtained 11,792 lncRNAs, among which, 2,500 lncRNAs were novel. In total, 509 differentially expressed (DE)lncRNAs were identified in this study. Target genes of DElncRNAs were predicted via cis and trans interactions, and functional and pathway analyses were performed. Gene ontology functions and Kyoto encyclopedia of genes and genomes analysis revealed that lncRNA-targeted genes mainly participated in metabolic pathways, cellular processes, immune system processes, digestive systems, and transport activities. To reveal the mechanism underlying starvation stress, the interaction network between lncRNAs and their targets was constructed based on 26 DElncRNAs and 72 DEmRNAs. We performed an interaction network analysis of 121 DElncRNA-DEmRNA pairs with a Pearson correlation coefficient greater than 0.99. Conclusion: We found that MSTRG.19894.13, MSTRG.16726.3, and MSTRG.12176.1 might play important roles in starvation stress. This study not only generated a library of enriched lncRNAs in piglets, but its outcomes also provide a strong foundation to screen key lncRNAs involved in starvation stress and a reference for subsequent in-depth research.

• Journal of Korean Medicine Rehabilitation
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• v.32 no.3
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• pp.29-35
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• 2022

Objectives The purpose of this systematic review is to analyse randomized controlled trials about acupuncture for patellofemoral pain syndrome (PFPS) and evaluate it's pain improvement effect. Methods Studies will be searched from ten databases (Medline/PubMed, Cochrane Library, EMBASE, China National Knowledge Infrastructure [CNKI], WanFang Data, Citation Information by NII [CiNII], ScienceON, Koreanstudies Information Service System [KISS], KMBASE, and KoreaMed). Participants will be patients diagnosed with PFPS, regardless of cause, gender, age or race, and interventions will be acupuncture, electroacupuncture, dry needling, fire needle, and acupotomy. Other treatments than interventions will be the control group and the main outcome will be reviewed by visual analogue scale (VAS). Results Data will be extracted and assessed according to the Preferred Reporting Items for Systematic Review and Meta-Analysis flow chart and Cochrane risk of bias tools. Meta-analysis will be conducted using random effect model within 95% confidence interval. Conclusions We expect this systematic review to provide useful data about the pain improvements of patellofemoral pain using acupuncture and expect to stimulate and systematize acupuncture treatment on PFPS in the future.

• The Journal of Korean Obstetrics and Gynecology
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• v.35 no.3
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• pp.122-136
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• 2022

Objectives: The aim of this study is to investigate Heart Rate Variability (HRV) characteristics of patients with primary dysmenorrhea at the menstrual phase. Methods: 7 databases (Pubmed, Cochrane library, CNKI, RISS, KISS, OASIS, ScienceON) were searched for eligible studies published before 2021 December. The studies comparing HRV between patients with primary dysmenorrhea and controls were included. A random-effects model was used to evaluate differences of HRV parameters between patients with primary dysmenorrhea and controls. Results: 4 articles were included in this review based on inclusion and exclusion criteria. SDNN (Standard deviation of NN intervals), RMSSD (Square root of the mean squared difference of successive NN intervals), mean PR (Mean of pulse rate), LF (Low frequency), HF (High frequency), was the most frequently used as HRV parameters. RMSSD was significantly lower in patients with primary dysmenorrhea than controls. There was no statistically significant difference of other HRV parameters between patients with primary dysmenorrhea and controls. Conclusions: This study suggests that parasympathetic activity and overall functions of autonomic nervous system might be decreased in patients with primary dysmenorrhea at the menstrual phase. In the future, well-designed clinical studies using HRV and additional meta-analysis should be conducted to obtain a wealth of information about HRV characteristics of patients with primary dysmenorrhea.

• Research in Community and Public Health Nursing
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• v.33 no.3
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• pp.340-355
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• 2022

Purpose: This study aimed to examine the effects of non-pharmacological sleep intervention programs in improving sleep quality among older adults in long-term care facilities. Methods: A literature search and selection was performed on nine different databases using the guidelines of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Overall, 14 studies met the inclusion criteria and were systematically reviewed. For the meta-analysis, the effect size was estimated using the random-effects model in Review Manager (RevMan) desktop version 5.4 of the Cochrane Library. Results: The meta-analysis of overall non-pharmacological interventions obtained a total effect size of 1.0 (standardized mean difference [SMD]=1.0, 95% confidence interval [CI]: 0.64~1.35), which was statistically significant (Z=5.55, p<.001). The most frequently studied non-pharmacological intervention was aroma therapy, with an effect size of 0.61 (SMD=0.61, 95% CI: 0.14~1.08), which was statistically significant (Z=2.55, p=.010). In the subgroup analysis, group-based interventions, interventions for >4 weeks, and untreated control studies were more effective. Conclusion: This study confirms that non-pharmacological interventions are effective in improving sleep quality among older adults in long-term care facilities. However, the sample size was small and the risk of bias in assessing the interventions of individual studies was unclear or high, thereby limiting the generalizability of the results. Further reviews that evaluate randomized control trials, evidence-based interventions that consider older adult participants' physical activity levels, different intervention methods and durations, and different control group intervention types are needed to obtain more conclusive evidence.

• Journal of Internet of Things and Convergence
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• v.8 no.1
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• pp.37-43
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• 2022

The fundamental basis of AI technology is learningable data. Recently, the types and amounts of data collected and produced by the government or private companies are increasing exponentially, however, verified data that can be used for actual machine learning has not yet led to it. This study discusses the conditions that data actually can be used for machine learning should meet, and identifies factors that degrade data quality through case studies. To this end, two representative cases of developing a prediction model using public big data was selected, and data for actual problem solving was collected from the public data portal. Through this, there is a difference from the results of applying valid data screening criteria and post-processing. The ultimate purpose of this study is to argue the importance of data quality management that must be most fundamentally preceded before the development of machine learning technology, which is the core of artificial intelligence, and accumulating valid data.