• Journal of Korea Entertainment Industry Association
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• v.13 no.8
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• pp.243-253
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• 2019

Geyonggi-geommu have developed based on the long history of Korean sword dance. Han Sung-joon, the great master of modern music and dance of Korea during the Japanese colonial period, collected and reconstructed folk dances that had disappeared or were cut off due to the policy to obliterate Korean culture through Chosun Music Dance Research Society. Since then, it has been passed down to Kang Sun-young and Kim Geun-hee that has designated as the Intangible Cultural Property No. 53. of Geyonggi-do in 2011. This study focuses on highlighting the uniqueness of Geyonggi-geommu for proper modeling and transmission of Geyonggi-geommu with historical significance so as to understand and preserve the Intangible Cultural Heritage. This study examines the transmission system of Geyonggi-geommu, followed by Kang Sun-young and Kim Geun-hee, originated by the master Han Sung-Joon of Geyonggi-geommu. Geyonggi-geommu has its uniqueness of using the pure Korean dance terminology established by the holder Kim Geun-hee at the time of designation of intangible cultural properties in Gyeonggi-do. The unique features of Geyonggi-geommu are performed and transmitted in two forms, Daemu(Group dance) and Holchum(Solo dance) which are not currently found in other regions. This is meaningful to passed down according to the original form of Geommu(Sword dance). In particular, the Holchum(Solo dance) is a form of artistic dance, showing the beauty of the sword dance during the Chosun Dynasty. In short, Gyeonggi-geommu can be described as an artistic dance with a soft and strong temperament considering its unique features.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4102-4110
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• 2022

Aiming at high-power and long-pulse operation up to 1000 s, some improvements have been made for both 2.45 GHz and 4.6 GHz lower hybrid (LH) systems during the recent 5 years. At first, the guard limiters of the LH antennas with graphite tiles were upgraded to tungsten, the most promising material for plasma facing components in nuclear fusion devices. These new guard limiters can operate at a peak power density of 12.9 MW/m². Strong hot spots were usually observed on the old graphite limiters when 4.6 GHz system operated with power >2.0 MW [B. N. Wan et al., Nucl. Fusion 57 (2017) 102019], leading to a reduction of the maximum power capability. With the new limiters, 4.6 GHz LH system, the main current drive (CD) and electron heating tool for EAST, can be operated with power >2.5 MW routinely. Long-pulse operation up to 100 s with 4.6 GHz LH power of 2.4 MW was achieved in 2021 and the maximal temperature on the guard limiters measured by an infrared (IR) camera was about 540 ℃, much below the permissible value of tungsten material (~1200 ℃). A discharge with a duration of 1056 s was achieved and the 4.6 GHz LH energy injected into the plasma was up to 1.05 GJ. Secondly, the fully-active-multijunction (FAM) launcher of 2.45 GHz system was upgraded to a passive-active-multijunction (PAM), for which the density of optimum coupling was relatively low (below the cut-off value). Good coupling with reflection coefficient ~3% has been achieved with plasma-antenna distance up to 11 cm for the new PAM. Finally, in order to eliminate the effect of ion cyclotron range of frequencies (ICRF) wave on 4.6 GHz LH wave coupling, the location of the ICRF launcher was changed to a port that is located 157.5° toroidally from the 4.6 GHz LH system and is not magnetically connected.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.249-256
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• 2022

Various studies are being actively conducted to show that the real-time visualization technology that combines BIM (Building Information Modeling) and AR (Augmented Reality) helps to increase construction management decision-making and processing efficiency. However, when large-capacity BIM data is projected into AR, there are various limitations such as data transmission and connection problems and the image cut-off issue. To improve the high efficiency of visualizing, a mesh optimization algorithm based on the k-nearest neighbors (KNN) classification framework to reconstruct BIM data is proposed in place of existing mesh optimization methods that are complicated and cannot adequately handle meshes with numerous boundaries of the 3D models. In the proposed algorithm, our target BIM model is optimized with the Unity C# code based on triangle centroid concepts and classified using the KNN. As a result, the algorithm can check the number of mesh vertices and triangles before and after optimization of the entire model and each structure. In addition, it is able to optimize the mesh vertices of the original model by approximately 56 % and the triangles by about 42 %. Moreover, compared to the original model, the optimized model shows no visual differences in the model elements and information, meaning that high-performance visualization can be expected when using AR devices.

• Journal of Chest Surgery
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• v.56 no.4
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• pp.244-251
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• 2023

Background: Extracorporeal membrane oxygenation (ECMO) has been widely used in patients with cardiorespiratory failure. The serum albumin level is an important prognostic marker in critically ill patients. We evaluated the efficacy of using pre-ECMO serum albumin levels to predict 30-day mortality in patients with cardiogenic shock (CS) who underwent venoarterial (VA) ECMO. Methods: We reviewed the medical records of 114 adult patients who underwent VA-ECMO between March 2021 and September 2022. The patients were divided into survivors and non-survivors. Clinical data before and during ECMO were compared. Results: Patients' mean age was 67.8±13.6 years, and 36 (31.6%) were female. The proportion of survival to discharge was 48.6% (n=56). Cox regression analysis showed that the pre-ECMO albumin level independently predicted 30-day mortality (hazard ratio, 0.25; 95% confidence interval [CI], 0.11-0.59; p=0.002). The area under the receiver operating characteristic curve of albumin levels (pre-ECMO) was 0.73 (standard error [SE], 0.05; 95% CI, 0.63-0.81; p<0.001; cut-off value=3.4 g/dL). Kaplan-Meier survival analysis showed that the cumulative 30-day mortality was significantly higher in patients with a pre-ECMO albumin level ≤3.4 g/dL than in those with a level >3.4 g/dL (68.9% vs. 23.8%, p<0.001). As the adjusted amount of albumin infused increased, the possibility of 30-day mortality also increased (coefficient=0.140; SE, 0.037; p<0.001). Conclusion: Hypoalbuminemia during ECMO was associated with higher mortality, even with higher amounts of albumin replacement, in patients with CS who underwent VA-ECMO. Further studies are needed to predict the timing of albumin replacement during ECMO.

• 한국노년학
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• v.39 no.4
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• pp.895-902
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• 2019

This study reviewed the diagnosis accuracy and evaluation criteria of the fall risk assessment questionnaire that proved validity through factor analysis in previous studies. The purpose of this study was to diagnose high-risk groups and propose personal fall risk profiles for the Korean community-dwelling elderly. The participants of this study were 439 elderly people living in S, U, B, and Y cities Korea (mean age 75.0 ± 5.7 years). Receiver operating characteristic analysis was conducted to review the accuracy of the fall risk assessment and evaluation criteria of the FRA. The results showed that the four sub-factors of the FRA: 'Potential for fall', 'Disease and physical symptoms', 'Environment' and 'Physical function', can effectively diagnose the fall risk of the community-dwelling elderly. The evaluation criteria was presented based on the sensitivity and specificity results. In addition, as a result of analyzing the patterns by the sub factors of the fall risk, the high-risk group accounted for 80% of the elderly who had problems with two or more factors. Therefore, the four sub-factors of FRA can effectively diagnose the fall risk level, and could be present individual fall risk profiles based on the evaluation criteria.

• Journal of radiological science and technology
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• v.46 no.5
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• pp.367-377
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• 2023

This study investigates the utility of the Triglyceride-glucose(TyG) index and Cardiometabolic Index(CMI) as predictors for diagnosing metabolic syndrome. The study involved 1970 males, 1459 females, totaling 3429 participants who underwent health checkups at P Hospital in Busan between January 2023 and June 2023. Metabolic syndrome diagnosis was based on the presence of 3 or more risk factors out of the 5 criteria outlined by the American Heart Association/National Heart, Lung, and Blood Institute(AHA/NHLBI), and participants with 2 or fewer risk factors were categorized as normal. Statistical analyses included independent sample t-tests, chi-square tests, Pearson's correlation analysis, Receiver Operating Characteristic(ROC) curve analysis, and logistic regression analysis, using the Statistical Package for the Social Sciences(SPSS) program. Significance was established at p<0.05. The comparison revealed that the metabolic syndrome group exhibited attributes such as advanced age, male gender, elevated systolic and diastolic blood pressures, high blood sugar, elevated triglycerides, reduced LDL-C, elevated HDL-C, higher Cardiometabolic Index, Triglyceride-glucose index, and components linked to abdominal obesity. Pearson correlation analysis showed strong positive correlations between waist circumference/height ratio, waist circumference, Cardiometabolic Index, and triglycerides. Weak positive correlations were observed between LDL-C, body mass index, and Cardiometabolic index, while a strong negative correlation was found between Cardiometabolic Index and HDL-C. ROC analysis indicated that the Cardiometabolic Index(CMI), Triglyceride-glucose(TyG) index, and waist circumference demonstrated the highest Area Under the Curve(AUC) values, indicating their efficacy in diagnosing metabolic syndrome. Optimal cut-off values were determined as >1.34, >8.86, and >84.5 for the Cardiometabolic Index, Triglyceride-glucose index, and waist circumference, respectively. Logistic regression analysis revealed significant differences for age(p=0.037), waist circumference(p<0.001), systolic blood pressure(p<0.001), triglycerides(p<0.001), LDL-C(p=0.028), fasting blood sugar(p<0.001), Cardiometabolic Index(p<0.001), and Triglyceride-glucose index (p<0.001). The odds ratios for these variables were 1.015, 1.179, 1.090, 3.03, and 69.16, respectively. In conclusion, the Cardiometabolic Index and Triglyceride-glucose index are robust predictive indicators closely associated with metabolic syndrome diagnosis, and waist circumference is identified as an excellent predictor. Integrating these variables into clinical practice holds the potential for enhancing early diagnosis and prevention of metabolic syndrome.

• Clinical and Experimental Vaccine Research
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• v.12 no.1
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• pp.25-31
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• 2023

Purpose: Since late 2019, the novel coronavirus disease has been a global concern, and alongside preventive strategies, including social distancing and personal hygiene, vaccination is now the primary hope for controlling the pandemic. Sputnik V is an adenovirus vector vaccine used against coronavirus disease 2019 (COVID-19) among Iranian health care providers, and there is a lack of information regarding the Adverse Events Following Immunisation (AEFI) by Sputnik V among the Iranian population. The present study aimed to evaluate AEFI by Sputnik V vaccine among Iranian population. Materials and Methods: Every member of the Islamic Republic of Iran Medical Council received their first dose of the Sputnik V vaccine in Mashhad (Iran) and was referred to receive their second dose enrolled in the present study and asked to fill an English language checklist asking about development of any AEFI following immunization with the first dose of Sputnik V vaccine. Results: A total number of 1,347 with a mean±standard deviation age of 56.2±9.6 years filled the checklist. Most of the participants were male (838 [62.2%]). The present study demonstrated that immunization with the first dose of Sputnik V results in at least one AEFI in 32.8% of the Iranian medical council members. Most of the AEFI was related to musculoskeletal symptoms, including myalgia. By considering the age of 55 years as a cut-off point, individuals younger than 55 had a higher rate of AEFI (41.3% vs. 22.5%, p=0.0001). Male gender, use of analgesics, beta-blockers, and previous COVID-19 infection have a lower chance of developing AEFI (p<0.05). Conclusion: The present study demonstrated that most of the AEFI was related to musculoskeletal symptoms, including myalgia, and older individuals, male gender and those receiving analgesics and beta-blockers were less likely to develop AEFI following immunization with the first dose of Sputnik V.

• Journal of Veterinary Clinics
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• v.40 no.6
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• pp.399-407
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• 2023

Chronic kidney disease (CKD) occurs in more than 15% of the dogs over 10 years of age and causes irreversible renal function deterioration. Therefore, it is important to diagnose CKD early and treat the disease properly. The purpose of this study aimed to to evaluate the clinical utility of urine albumin/creatinine ratio (ACR) using POC (point-of-care) device as an early detection urinary biomarker in CKD dogs and to confirm the correlation between ACR and other known CKD biomarkers. Urine and serum samples were obtained from 50 healthy dogs and 50 dogs with CKD. Serum blood urea nitrogen (BUN), creatinine, and symmetric dimethylarginine (SDMA) concentrations, and urine protein creatinine ratio (UPC) were measured. Urine specific gravity (USG) was evaluated using refractometer, and ACR was measured using an i-SENS A1Care analyzer. The ACR values of dogs with CKD were significantly different from those of healthy dogs (p < 0.001), as with other renal biomarkers. ACR showed significant differences between healthy dogs and dogs with CKD at every IRIS stage (p < 0.005), whereas no significant differences were observed between dogs with CKD IRIS stage I and healthy dogs with UPC. There are significant positive correlation between ACR and BUN (r = 0.611, p < 0.001), creatinine (r = 0.788, p < 0.001), SDMA (r = 0.747, p < 0.001), and UPC (r = 0.784, p < 0.001), and significant negative correlation between ACR and USG (r = -0.700, p < 0.001). In receiver operator characteristic curve analysis, the area under the curve (AUC) was 0.982 (95% CI 0.963-1.000, p < 0.001), with an optimal cut-off value of 64.20 mg/g (94% sensitivity and 94% specificity). Thus, ACR is a useful urinary biomarker for the early diagnosis of proteinuria in CKD and combined use of ACR and other renal biomarkers may be helpful for early diagnosis and prevention of CKD in dogs.

• Korean Journal of Radiology
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• v.21 no.7
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• pp.859-868
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• 2020

Objective: To investigate the value of initial CT quantitative analysis of ground-glass opacity (GGO), consolidation, and total lesion volume and its relationship with clinical features for assessing the severity of coronavirus disease 2019 (COVID-19). Materials and Methods: A total of 84 patients with COVID-19 were retrospectively reviewed from January 23, 2020 to February 19, 2020. Patients were divided into two groups: severe group (n = 23) and non-severe group (n = 61). Clinical symptoms, laboratory data, and CT findings on admission were analyzed. CT quantitative parameters, including GGO, consolidation, total lesion score, percentage GGO, and percentage consolidation (both relative to total lesion volume) were calculated. Relationships between the CT findings and laboratory data were estimated. Finally, a discrimination model was established to assess the severity of COVID-19. Results: Patients in the severe group had higher baseline neutrophil percentage, increased high-sensitivity C-reactive protein (hs-CRP) and procalcitonin levels, and lower baseline lymphocyte count and lymphocyte percentage (p < 0.001). The severe group also had higher GGO score (p < 0.001), consolidation score (p < 0.001), total lesion score (p < 0.001), and percentage consolidation (p = 0.002), but had a lower percentage GGO (p = 0.008). These CT quantitative parameters were significantly correlated with laboratory inflammatory marker levels, including neutrophil percentage, lymphocyte count, lymphocyte percentage, hs-CRP level, and procalcitonin level (p < 0.05). The total lesion score demonstrated the best performance when the data cut-off was 8.2%. Furthermore, the area under the curve, sensitivity, and specificity were 93.8% (confidence interval [CI]: 86.8-100%), 91.3% (CI: 69.6-100%), and 91.8% (CI: 23.0-98.4%), respectively. Conclusion: CT quantitative parameters showed strong correlations with laboratory inflammatory markers, suggesting that CT quantitative analysis might be an effective and important method for assessing the severity of COVID-19, and may provide additional guidance for planning clinical treatment strategies.

• Korean Journal of Radiology
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• v.21 no.12
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• pp.1345-1354
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• 2020

Objective: To evaluate radiomics analysis in studies on mild cognitive impairment (MCI) and Alzheimer's disease (AD) using a radiomics quality score (RQS) system to establish a roadmap for further improvement in clinical use. Materials and Methods: PubMed MEDLINE and EMBASE were searched using the terms 'cognitive impairment' or 'Alzheimer' or 'dementia' and 'radiomic' or 'texture' or 'radiogenomic' for articles published until March 2020. From 258 articles, 26 relevant original research articles were selected. Two neuroradiologists assessed the quality of the methodology according to the RQS. Adherence rates for the following six key domains were evaluated: image protocol and reproducibility, feature reduction and validation, biologic/clinical utility, performance index, high level of evidence, and open science. Results: The hippocampus was the most frequently analyzed (46.2%) anatomical structure. Of the 26 studies, 16 (61.5%) used an open source database (14 from Alzheimer's Disease Neuroimaging Initiative and 2 from Open Access Series of Imaging Studies). The mean RQS was 3.6 out of 36 (9.9%), and the basic adherence rate was 27.6%. Only one study (3.8%) performed external validation. The adherence rate was relatively high for reporting the imaging protocol (96.2%), multiple segmentation (76.9%), discrimination statistics (69.2%), and open science and data (65.4%) but low for conducting test-retest analysis (7.7%) and biologic correlation (3.8%). None of the studies stated potential clinical utility, conducted a phantom study, performed cut-off analysis or calibration statistics, was a prospective study, or conducted cost-effectiveness analysis, resulting in a low level of evidence. Conclusion: The quality of radiomics reporting in MCI and AD studies is suboptimal. Validation is necessary using external dataset, and improvements need to be made to feature reproducibility, feature selection, clinical utility, model performance index, and pursuits of a higher level of evidence.