• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.817-827
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• 2022

The real-name safety management system is to indicate "safety" after inspection by construction personnel before workers use it for the purpose of preventing safety accidents caused by unsafe conditions in temporary facilities and temporary constructions installed at construction sites. Purpose: By implementing the real-name system for safety management at construction sites, the objective is to respond to the "Severe Accident Punishment Act" and to improve the level of safety management at the same time. Method: In this study, a hierarchical analysis model was produced through previous studies of actual conditions such as types of safety incidents and causality at construction sites. The AHP model was used to calculate integrated weights and rankings with a pairwise comparison questionnaire for experts. Conclusion: As a result of the analysis of the upper classes, construction machinery was evaluated the highest, and real-name management system was evaluated the lowest. As a result of the lower-level analysis, it was considered that opening doors for safety facility management, tower cranes for construction equipment, management under the "Occupational Safety and Health Act" under the real-name management system, and CEO duties for safety management organizations were the most important.

• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.65-85
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• 2022

In this study, in order to derive the priority of indicators and sustainability areas of smart ports, which means ports in the digital era, previous studies and ESG, which have recently been indispensably introduced in all industries worldwide, were studied together. A hierarchical structure was established with upper evaluation items and 20 lower evaluation items in four areas (operational, environmental, social, and governance), and a relative evaluation method of weighting items among the AHP techniques was applied. The pairwise comparison questionnaire consisted of a 9-point scale proposed by Satty (1980). A survey was conducted targeting working-level workers who perform sustainability or ESG(Environmental, Social, Governance)-related work at four representative port authorities in Korea (Busan, Incheon, Ulsan, Yeosu Gwangyang). In order to increase the accuracy of the analysis results, AHP analysis was conducted on 17 questionnaires with a consistency ratio of 0.1 or less. As a result of the analysis, it was confirmed that among the four areas representing the sustainability of domestic smart ports, the operation area had the highest priority, followed by the environment area. In addition, looking at the overall priorities for the 20 detailed indicators, indicators such as operational efficiency, operational planning, energy management, and pollution measurement and management system were found to have high priority. On the other hand, it was confirmed that the social and the governance areas had relatively low importance compared to other areas.

• Journal of Korea Trade
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• v.26 no.7
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• pp.145-166
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• 2022

Purpose - The field of online videos has seen rapid changes in information and communications technology (ICT) development. Despite active academic research on the use of online platforms, few studies have analyzed the relative importance among the factors determined. In this study, the relative importance of factors found in previous studies was identified for users of online video platforms in China and Korea. Through this, factors that should be considered first in research on online video use were derived. In addition, the quality level of online video platforms currently used in China and Korea was measured and used for analysis. The analysis results can provide information for companies to enter Chinese and Korean markets and also be useful to platform providers aiming to increase usage. Design/methodology - Among the factors of Online Video Usage identified in previous studies, 13 factors to be studied were selected through focus group interviews and hierarchized into 2 layers. For the analytic hierarchy process (AHP), each factor was designed as a pairwise comparison questionnaire. The survey included questions on the quality of online video platform currently in use. Data collection was conducted on 16 platforms in China and 11 platforms in Korea, and the relative importance of factors and user perspectives was compared and analyzed using importance performance analysis (IPA). In the analytical process, platforms were divided into over-the-top (OTT) group and Creator group according to the weight of user-generated content, and data analysis focused on these groups. Findings - As a result of AHP, China and Korea showed both "Fun" and "Interests" factors at the top, while the importance of the Entertainment factor "Vicarious satisfaction" was very different for China and Korea. "Relationship with content creators" was the most important factor in China, but it ranked the lowest in Korea. The IPA showed that the factors with high importance and performance were fun, interests, and easy accessibility for both China and Korea. In contrast, the factors that showed low performance compared to high importance in China were relationship with content creators, relationship with acquaintances/friends, and trustworthiness. As for Korea, vicarious satisfaction was observed; thus, this study has raised the need for academic and industrial interest in vicarious satisfaction. The results show that fun, interests, vicarious satisfaction, and easy accessibility of the platform are factors that must be included in further studies on online videos. Originality/value - Existing studies related to the use of online platforms have derived factors or focused on the influence relationship between factors and performance. However, few studies have analyzed the relative importance among the determined factors. This paper explores factors to be considered in future studies by deriving the relative importance between these factors from the perspective of users in China and Korea.

• Animal Bioscience
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• v.35 no.10
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• pp.1499-1511
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• 2022

Objective: This study was aimed to estimate the genetic parameters, including genetic and phenotypic correlations, of milk yield, lactation curve traits and milk composition of Thai dairy cattle from three government research farms. Methods: The data of 25,789 test-day milk yield and milk composition records of 1,468 cattle from lactation 1 to 3 of Holstein Friesian (HF) and crossbred HF dairy cattle calved between 1990 and 2015 from three government research farms in Thailand were analysed. 305-day milk yield was estimated by the Wood model and a test interval method. The Wood model was used for estimating cumulative 305-day milk yield, peak milk yield, days to peak milk yield and persistency. Genetic parameters were estimated using linear mixed models with herd, breed group, year and season of calving as fixed effects, and animals linked to a pedigree as random effects, together with a residual error. Univariate models were used to estimate variance components, heritability, estimated breeding values (EBVs) and repeatability of each trait, while pairwise bivariate models were used to estimate covariance components and correlations between traits in the same lactation and in the same trait across lactations. Results: The heritability of 305-day milk yield, peak milk yield and protein percentage have moderate to high estimates ranging from 0.19 to 0.45 while days to peak milk yield, persistency and fat percentage have low heritability ranging from 0.08 to 0.14 in lactation 1 cows. Further, heritability of most traits considered was higher in lactation 1 compared with lactations 2 and 3. For cows in lactation 1, high genetic correlations were found between 305-day milk yield and peak milk yield (0.86±0.07) and days to peak milk yield and persistency (0.99±0.02) while estimates of genetic correlations between the remaining traits were imprecise due to the high standard errors. The genetic correlations within the traits across lactation were high. There was no consistent trend of EBVs for most traits in the first lactation over the study period. Conclusion: Both the Wood model and test interval method can be used for milk yield estimates in these herds. However, the Wood model has advantages over the test interval method as it can be fitted using fewer test-day records and the estimated model parameters can be used to derive estimates of other lactation curve parameters. Milk yield, peak milk yield and protein percentage can be improved by a selection and mating program while days to peak milk yield, persistency and fat percentage can be improved by including into a selection index.

• Korean Journal of Radiology
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• v.22 no.10
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• pp.1719-1729
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• 2021

Objective: Emphysema and small-airway disease are the two major components of chronic obstructive pulmonary disease (COPD). We propose a novel method of quantitative computed tomography (CT) emphysema air-trapping composite (EAtC) mapping to assess each COPD component. We analyzed the potential use of this method for assessing lung function in patients with COPD. Materials and Methods: A total of 584 patients with COPD underwent inspiration and expiration CTs. Using pairwise analysis of inspiration and expiration CTs with non-rigid registration, EAtC mapping classified lung parenchyma into three areas: Normal, functional air trapping (fAT), and emphysema (Emph). We defined fAT as the area with a density change of less than 60 Hounsfield units (HU) between inspiration and expiration CTs among areas with a density less than -856 HU on inspiration CT. The volume fraction of each area was compared with clinical parameters and pulmonary function tests (PFTs). The results were compared with those of parametric response mapping (PRM) analysis. Results: The relative volumes of the EAtC classes differed according to the Global Initiative for Chronic Obstructive Lung Disease stages (p < 0.001). Each class showed moderate correlations with forced expiratory volume in 1 second (FEV₁) and FEV₁/forced vital capacity (FVC) (r = -0.659-0.674, p < 0.001). Both fAT and Emph were significant predictors of FEV₁ and FEV₁/FVC (R² = 0.352 and 0.488, respectively; p < 0.001). fAT was a significant predictor of mean forced expiratory flow between 25% and 75% and residual volume/total vital capacity (R² = 0.264 and 0.233, respectively; p < 0.001), while Emph and age were significant predictors of carbon monoxide diffusing capacity (R² = 0.303; p < 0.001). fAT showed better correlations with PFTs than with small-airway disease on PRM. Conclusion: The proposed quantitative CT EAtC mapping provides comprehensive lung functional information on each disease component of COPD, which may serve as an imaging biomarker of lung function.

• Journal of the Korean Society of Radiology
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• v.83 no.4
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• pp.876-886
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• 2022

Purpose To evaluate the performance of MicroPure US imaging to detect and characterize microcalcifications. Materials and Methods A total of 171 lesions with suspicious microcalcifications seen on mammography and B-mode US were included and simultaneously evaluated using MicroPure US imaging. The size of microcalcifications was divided into small (punctate, amorphous, fine pleomorphic, and fine linear) and large (coarse heterogeneous), and the extent was divided into narrow (grouped) and wide (others). MicroPure US imaging visibility was divided into four types based on the number of microcalcifications on the two images: B > M (more on B-mode), B = M (similar), B < M (more on MicroPure), and negative. Triple pairwise comparison was used to evaluate the imaging features according to the MicroPure US imaging visibility. Results Among the 171 lesions examined, 157 lesions (91.8%) were detected by MicroPure US imaging. The proportion of Breast Imaging Reporting and Data System (BI-RADS) category 4A was significantly higher in the MicroPure positive group, and that of category 4B was significantly higher in the MicroPure negative group (p = 0.035). The other imaging features did not differ. Among the positive MicroPure subgroups, all features showed no significant difference. Conclusion MicroPure US imaging demonstrated 91.8% positivity in detecting microcalcifications on B-mode US. MicroPure US imaging visibility correlated with the BI-RADS category of microcalcifications.

• Korean Journal of Radiology
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• v.23 no.12
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• pp.1251-1259
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• 2022

Objective: T1 mapping provides valuable information regarding cardiomyopathies. Manual drawing is time consuming and prone to subjective errors. Therefore, this study aimed to test a DL algorithm for the automated measurement of native T1 and extracellular volume (ECV) fractions in cardiac magnetic resonance (CMR) imaging with a temporally separated dataset. Materials and Methods: CMR images obtained for 95 participants (mean age ± standard deviation, 54.5 ± 15.2 years), including 36 left ventricular hypertrophy (12 hypertrophic cardiomyopathy, 12 Fabry disease, and 12 amyloidosis), 32 dilated cardiomyopathy, and 27 healthy volunteers, were included. A commercial deep learning (DL) algorithm based on 2D U-net (Myomics-T1 software, version 1.0.0) was used for the automated analysis of T1 maps. Four radiologists, as study readers, performed manual analysis. The reference standard was the consensus result of the manual analysis by two additional expert readers. The segmentation performance of the DL algorithm and the correlation and agreement between the automated measurement and the reference standard were assessed. Interobserver agreement among the four radiologists was analyzed. Results: DL successfully segmented the myocardium in 99.3% of slices in the native T1 map and 89.8% of slices in the post-T1 map with Dice similarity coefficients of 0.86 ± 0.05 and 0.74 ± 0.17, respectively. Native T1 and ECV showed strong correlation and agreement between DL and the reference: for T1, r = 0.967 (95% confidence interval [CI], 0.951-0.978) and bias of 9.5 msec (95% limits of agreement [LOA], -23.6-42.6 msec); for ECV, r = 0.987 (95% CI, 0.980-0.991) and bias of 0.7% (95% LOA, -2.8%-4.2%) on per-subject basis. Agreements between DL and each of the four radiologists were excellent (intraclass correlation coefficient [ICC] of 0.98-0.99 for both native T1 and ECV), comparable to the pairwise agreement between the radiologists (ICC of 0.97-1.00 and 0.99-1.00 for native T1 and ECV, respectively). Conclusion: The DL algorithm allowed automated T1 and ECV measurements comparable to those of radiologists.

• Korean Journal of Radiology
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• v.23 no.12
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• pp.1281-1289
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• 2022

Objective: Radiomic modeling using multiple regions of interest in MRI of the brain to diagnose juvenile myoclonic epilepsy (JME) has not yet been investigated. This study aimed to develop and validate radiomics prediction models to distinguish patients with JME from healthy controls (HCs), and to evaluate the feasibility of a radiomics approach using MRI for diagnosing JME. Materials and Methods: A total of 97 JME patients (25.6 ± 8.5 years; female, 45.5%) and 32 HCs (28.9 ± 11.4 years; female, 50.0%) were randomly split (7:3 ratio) into a training (n = 90) and a test set (n = 39) group. Radiomic features were extracted from 22 regions of interest in the brain using the T1-weighted MRI based on clinical evidence. Predictive models were trained using seven modeling methods, including a light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree, with radiomics features in the training set. The performance of the models was validated and compared to the test set. The model with the highest area under the receiver operating curve (AUROC) was chosen, and important features in the model were identified. Results: The seven tested radiomics models, including light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree, showed AUROC values of 0.817, 0.807, 0.783, 0.779, 0.767, 0.762, and 0.672, respectively. The light gradient boosting machine with the highest AUROC, albeit without statistically significant differences from the other models in pairwise comparisons, had accuracy, precision, recall, and F1 scores of 0.795, 0.818, 0.931, and 0.871, respectively. Radiomic features, including the putamen and ventral diencephalon, were ranked as the most important for suggesting JME. Conclusion: Radiomic models using MRI were able to differentiate JME from HCs.

• Journal of Korea Port Economic Association
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• v.39 no.4
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• pp.269-283
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• 2023

Based on daily data from January 4, 2016 to September 27, 2022, the impact of extreme movements of BDI on shipping companies' network connectivity was analyzed using CoVaR network connectivity. The main results and policy implications are as follows. First, according to the copula model results, the Student-t copula was selected as the most suitable model for COSCO, HMM, HRAG, MAERSK, and WAN. EVER was selected as a time-varying Gumbel copula, and YANG was selected as a time-varying rotated-Gumbel copula. Second, as a result of analysis using the TVP-VAR model, the linkage between shipping companies tended to increase when the BDI turned into an extreme risk state. In the comparison of net connectivity, the roles of COSCO and EVER changed. In addition, in the analysis of net pairwise connectivity, it was found that the change in the extreme risk state of BDI also affected the connectivity of shipping companies. In particular, EVER, WAN, and COSCO showed large changes. Taken together, the extreme fluctuations in BDI changed the role of Asian shipping companies, intensifying competition among shipping companies and strengthening risk delivery. It was confirmed that BDI has a great influence on the network connectivity of shipping companies and has an important influence on the stability of the stock market network. Therefore, the results of this study should consider not only the connectivity of shipping companies according to market conditions, but also the connectivity in extreme situations.

• Journal of Animal Science and Technology
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• v.50 no.5
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• pp.613-620
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• 2008

The genetic parameters used in National Hanwoo Genetic Evaluation(NHGE) were needed to be monitored and updated periodically for accounting any possible changes in population parameters due to selection and environmental changes. Genetic parameters were estimated with single and two-trait models with MTDFREML package using 2,791 carcass records of steers collected from Hanwoo Progeny Test Program(HPTP). Single and two-trait models gave similar parameter estimates for all traits. The heritability estimates from single and two-trait models for carcass weight(CW), dressing percentage(DP), eye muscle area(EMA), back fat thickness(BFT) and marbling score(MS) were 0.30, 0.30, 0.37, 0.44 and 0.44, respectively. The heritability estimates for all the traits except BFT were slightly lower than those used in NHGE but seemed to be within the acceptable ranges. However, further monitoring is needed because the data might not have fully reflected the changes such as carcass grading standards in performance testing program. In order to shift statistical model of NHGE from single trait model to multiple-trait model, the genetic correlations between carcass traits were estimated with pairwise two-trait models. The genetic correlation coefficients between CW and DP, between CW and EMA, between CW and BFT and between CW and MS were 0.44, 0.63, 0.17 and 0.06, respectively. Those between DP and EMA, between DP and BFT and between DP and MS were 0.29, 0.40 and 0.20. Those between EMA and BFT and between EMA and MS were －0.24 and 0.15, respectively. The genetic correlation coefficient between BFT and MS was 0.03.