• Journal of Korean Academy of Nursing
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• v.52 no.1
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• pp.4-23
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• 2022

Purpose: The aim of this study was to evaluate the effect of auriculotherapy on musculoskeletal pain in adults. Methods: A total of 885 studies were retrieved from nine databases (PubMed, Scopus, CINAHL, Web of Science, Ovid Medline, Cochrane Library, RISS, KMbase, and KISS). Sixteen studies were selected for meta-analysis, which satisfied the inclusion criteria and the evaluation of risk of bias. Demographic data, auriculotherapy types, intervention characteristics, auricular points, and outcomes related to pain (subjective pain scale, and amount of analgesic) were extracted from all included studies. The effect size of auriculotherapy was analyzed through comprehensive meta analysis 3.0, and the presence of publication bias was analyzed through a funnel plot and Egger's regression. Results: The results of the meta-analysis (n = 16) revealed that the auriculotherapy was significantly superior to the control group on present pain in adults (Hedges' g = - 0.35, 95% Confidence Interval [CI] = - 0.55~- 0.15). According to the results of subgroup analysis, the effect size of auricular acupuncture therapy (Hedges' g = 0.45, 95% CI = - 0.75~- 0.15) was higher than the auricular acupuncture (Hedges' g = 0.27, 95% CI = - 0.53~0.00): the longer the intervention period, the greater the effect size. Conclusion: In this study, auriculotherapy demonstrates a significant reduction in musculoskeletal pain in adults. Therefore, it is necessary to refine the curriculum to include auriculotherapy as a nursing intervention to relieve musculoskeletal pain in adults and encourage its use in clinical settings.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1563-1570
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• 2023

In this study, a DeCART/MIG uncertainty quantification (UQ) analysis code system with a multicorrelated cross section stochastic sampling (S.S.) module was established and verified through the UAM (Uncertainty Analysis in Modeling) and the BEAVRS (Benchmark for Evaluation And Validation of Reactor Simulations) benchmark calculations. For the S.S. calculations, a sample of 500 DeCART multigroup cross section sets for two major actinides, i.e., ²³⁵U and ²³⁸U, were generated by the MIG code and covariance data from the ENDF/B-VII.1 evaluated nuclear data library. In the three pin problems (i.e. TMI-1, PB2, and Koz-6) from the UAM benchmark, the uncertainties in k_inf by the DeCART/MIG S.S. calculations agreed very well with the sensitivity and uncertainty (S/U) perturbation results by DeCART/MUSAD and the S/U direct subtraction (S/U-DS) results by the DeCART/MIG. From these results, it was concluded that the multi-group cross section sampling module of the MIG code works correctly and accurately. In the BEAVRS whole benchmark problems, the uncertainties in the control rod bank worth, isothermal temperature coefficient, power distribution, and critical boron concentration due to cross section uncertainties were calculated by the DeCART/MIG code system. Overall, the uncertainties in these design parameters were less than the general design review criteria of a typical pressurized water reactor start-up case. This newly-developed DeCART/MIG UQ analysis code system by the S.S. method can be widely utilized as uncertainty analysis and margin estimation tools for developing and designing new advanced nuclear reactors.

• The korean journal of orthodontics
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• v.52 no.2
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• pp.112-122
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• 2022

Objective: This study aimed to present and evaluate a new deep learning model for determining cervical vertebral maturation (CVM) degree and growth spurts by analyzing lateral cephalometric radiographs. Methods: The study sample included 890 cephalograms. The images were classified into six cervical stages independently by two orthodontists. The images were also categorized into three degrees on the basis of the growth spurt: pre-pubertal, growth spurt, and post-pubertal. Subsequently, the samples were fed to a transfer learning model implemented using the Python programming language and PyTorch library. In the last step, the test set of cephalograms was randomly coded and provided to two new orthodontists in order to compare their diagnosis to the artificial intelligence (AI) model's performance using weighted kappa and Cohen's kappa statistical analyses. Results: The model's validation and test accuracy for the six-class CVM diagnosis were 62.63% and 61.62%, respectively. Moreover, the model's validation and test accuracy for the three-class classification were 75.76% and 82.83%, respectively. Furthermore, substantial agreements were observed between the two orthodontists as well as one of them and the AI model. Conclusions: The newly developed AI model had reasonable accuracy in detecting the CVM stage and high reliability in detecting the pubertal stage. However, its accuracy was still less than that of human observers. With further improvements in data quality, this model should be able to provide practical assistance to practicing dentists in the future.

• Nutrition Research and Practice
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• v.16 no.sup1
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• pp.57-69
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• 2022

BACKGROUND/OBJECTIVES: Vitamin D is produced in the skin during sun exposure and is also ingested from foods. The role of vitamin D needs to be considered in the prevention and management of various diseases. Moreover, since the majority of Koreans spend their days indoors, becoming susceptible to the risk of vitamin D deficiency. The current study aims to prepare a basis for determining dietary reference intake of vitamin D in Korea, by reviewing the evidence against various diseases and risks. MATERIALS/METHODS: Literature published in Korea and other countries between 2014 and 2018 was prioritized based on their study design and other criteria, and evaluated using the RoB 2.0 assessment form and United States Department of Agriculture Nutrition Evidence Library Conclusion Statement Evaluation Criteria. RESULTS: Of the 1,709 studies, 128 studies were included in the final systematic analysis after screening. To set the dietary reference intakes of vitamin D based on the selected articles, blood 25(OH)D levels and indicators of bone health were used collectively. Blood vitamin D levels and ultraviolet (UV) exposure time derived from the Korean National Health and Nutrition Examination Survey were analyzed to establish the dietary reference intakes of vitamin D for each stage of the life cycle. The adequate intake levels of vitamin D, according to age and gender, were determined to be in the range of 5-15 ㎍/day, and the tolerable upper intake level was established at 25-100 ㎍/day. CONCLUSIONS: The most important variable for vitamin D nutrition is lifestyle. A balanced diet comprising foods with high contents of vitamin D is important, as is vitamin D synthesis after UV exposure. The adequate intake level of vitamin D mentioned in the 2015 Dietary Reference Intakes for Korean (KDRI) remained unchanged in the 2020 KDRI for the management of vitamin D nutrition in Koreans.

• Journal of Oriental Neuropsychiatry
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• v.33 no.1
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• pp.49-78
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• 2022

Objectives: This study was conducted to evaluate the efficacy of Korean Medicine Therapy (KMT) for the treatment of Chemotherapy-induced Cognitive Impairment (CICI) through systematic review and meta-analysis of randomized controlled trials (RCTs) as proceeding research to further research the efficacy of KMT for CICI patients. Methods: We conducted a systematic review and meta-analysis according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines (PRISMA). The RCTs on the efficacy of KMT for treatment of CICI were searched by structured search strategies in MEDLINE, EMBASE, Cochrane library, CAJD, KISS, NDSL, KoreaMed, and OASIS. The searched RCTs were screened by inclusion and exclusion criteria. We evaluated the quality of the method in the included studies using the Jadad score and Cochran ROB tool. The efficacy outcomes were the Visual Analogue Scale (VAS) and the Clinical total Effective Rate (CER) of CICI. They were analyzed using mean difference for continuous variable or Relative Risk (RR) for Dichotomous variable in the random-effect model. The RevMan 5.3 program was used for meta-analysis. Results: We included 19 RCTs, including 653 participants, in the systematic review and meta-analysis. There were favorable results for the KMT group after the intervention compared with the pharmacotherapy group, physiotherapy group, and combined treatment group. KMT group showed improvement using CER and VAS compared with exercises, but their heterogeneities were slightly significant. KMT was more effective compared to the Rehabilitation program in CER and the subgroup analysis results showed that KMT had a significant difference compared to other therapies in VAS, to Medication therapy in CER. Conclusions: KMT presented reasonable evidence on improving the Clinical total Effective Rate and Visual Analogue Scale in CICI patients. However, further evaluation in future research is required.

• Smart Media Journal
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• v.12 no.6
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• pp.27-34
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• 2023

As Netflix usage has increased due to the COVID-19 pandemic, users' experiences with the service have also increased. Therefore, this study aims to conduct topic modeling analysis based on Netflix review data to explore the changes in Netflix user experience and service before and after the COVID-19 pandemic. We collected Netflix app review data from the Google Play Store using the Google Play Scraper library, and used topic modeling to examine keyword differences between app reviews before and after the pandemic. The analysis revealed four main topics: Netflix app features, Netflix content, Netflix service usage, and Netflix overall reviews. After the pandemic, when user experience increased, users tended to use more diverse and detailed keywords in their reviews. By using Netflix review data to analyze users' opinions, this study shows the changes in user experience of Netflix services before and after the pandemic, which can be used as a guide to strengthen competitiveness in the competitive OTT market.

• Restorative Dentistry and Endodontics
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• v.47 no.2
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• pp.15.1-15.18
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• 2022

This review aimed to characterize the effect of direct restorative material types and adhesive protocols on marginal adaptation and the bond strength of the interface between the material and the proximal dentin/cementum. An electronic search of 3 databases (the National Library of Medicine [MEDLINE/PubMed], Scopus, and ScienceDirect) was conducted. Studies were included if they evaluated marginal adaptation or bond strength tests for proximal restorations under the cementoenamel junction. Only 16 studies met the inclusion criteria and were included in this review. These studies presented a high degree of heterogeneity in terms of the materials used and the methodologies and evaluation criteria of each test; therefore, only a descriptive analysis could be conducted. The included studies were individually evaluated for the risk of bias following predetermined criteria. To summarize the results of the included studies, the type of restorative material affected the test results, whereas the use of different adhesive protocols had an insignificant effect on the results. It could be concluded that various categories of resin-based composites could be a suitable choice for clinicians to elevate proximal dentin/cementum margins, rather than the open sandwich technique with resin-modified glass ionomers. Despite challenges in bonding to proximal dentin/cementum margins, different adhesive protocols provided comparable outcomes.

• Restorative Dentistry and Endodontics
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• v.48 no.4
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• pp.37.1-37.17
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• 2023

This study aimed to compare the disinfectant ability of chlorhexidine (CHX) gel and sodium hypochlorite (NaOCl). Systematic searches were conducted from inception until December 8th, 2022 (MEDLINE/PubMed, Cochrane Library, Web of Science, Scopus, Embase, and Grey Literature databases). Only randomized clinical trials were included. The revised Cochrane risk of bias tools for randomized trials were used to assess the quality of studies. Meta-analyses were performed. The overall quality of evidence was assessed through the Grading of Recommendations Assessment, Development, and Evaluation tool. Six studies were included. Five had a low risk of bias and 1 had some concerns. Three studies assessed bacterial reduction. Two were included in the meta-analysis for bacterial reduction (mean difference, 75.03 [confidence interval, CI, -271.15, 421.22], p = 0.67; I² = 74%); and 3 in the meta-analysis for cultivable bacteria after chemomechanical preparation (odds ratio, 1.03 [CI, 0.20, 5.31], P = 0.98; I² = 49%). Five studies assessed endotoxin reduction. Three were included in a meta-analysis (mean difference, 20.59 [CI, -36.41, 77.59], p = 0.48; I² = 74%). There seems to be no difference in the disinfectant ability of CHX gel and NaOCl, but further research is necessary.

• The Journal of Internal Korean Medicine
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• v.44 no.4
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• pp.603-620
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• 2023

Objectives: This study reviewed randomized controlled trials (RCTs) investigating the efficacy of herbal medicine on sleep disorders associated with Parkinson's disease and suggests a better research process. Methods: We searched for RCTs for herbal medicine treatments for sleep disorders related to Parkinson's disease on July 31, 2023 using eight databases (PubMed, Embase, the Cochrane library, China National Knowledge Infrastructure [CNKI], the Research Information Service System [RISS], Science ON, the Oriental Medicine Advanced Searching Integrated System [OASIS], and the Korea Citation Index [KCI]). Cochrane's risk of bias tool was used to assess the quality of the RCTs. Results: A total of 16 RCTs met all the inclusion criteria, and in most reports, the treatment group showed a significant improvement in sleep disorders compared to the control group. Total effective rate (TER), Pittsburgh Sleep Quality Index (PSQI), Unified Parkinson's Disease Rating Scale (UPDRS), TCM Symptom Score (TSS), Parkinson's Disease Sleep Scale (PDSS), etc., were used as evaluation indicators. Conclusion: Herbal medicine is a potential treatment for sleep disorders associated with Parkinson's disease. However, the selected RCTs were of poor quality, and it is necessary to perform more systematic studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3330-3344
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• 2023

This paper proposes an antenna performance prediction model in the autonomous driving radar manufacturing process. Our research work is based upon a challenge dataset, Driving Radar Manufacturing Process Dataset, and a typical AutoML machine learning workflow engine, Pycaret open-source Python library. Note that the dataset contains the total 70 data-items, out of which 54 used as input features and 16 used as output features, and the dataset is properly built into resolving the multi-output regression problem. During the data regression analysis and preprocessing phase, we identified several input features having similar correlations and so detached some of those input features, which may become a serious cause of the multicollinearity problem that affect the overall model performance. In the training phase, we train each of output-feature regression models by using the AutoML approach. Next, we selected the top 5 models showing the higher performances in the AutoML result reports and applied the ensemble method so as for the selected models' performances to be improved. In performing the experimental performance evaluation of the regression prediction model, we particularly used two metrics, MAE and RMSE, and the results of which were 0.6928 and 1.2065, respectively. Additionally, we carried out a series of experiments to verify the proposed model's performance by comparing with other existing models' performances. In conclusion, we enhance accuracy for safer autonomous vehicles, reduces manufacturing costs through AutoML-Pycaret and machine learning ensembled model, and prevents the production of faulty radar systems, conserving resources. Ultimately, the proposed model holds significant promise not only for antenna performance but also for improving manufacturing quality and advancing radar systems in autonomous vehicles.