• Korean Journal of Radiology
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• v.24 no.11
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• pp.1093-1101
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• 2023

Objective: Cine magnetic resonance imaging (MRI) has emerged as a noninvasive method to quantitatively assess bowel motility. However, its accuracy in measuring various degrees of small bowel motility has not been extensively evaluated. We aimed to draw a quantitative small bowel motility score from cine MRI and evaluate its performance in a population with varying degrees of small bowel motility. Materials and Methods: A total of 174 participants (28.5 ± 7.6 years; 135 males) underwent a 22-second-long cine MRI sequence (2-dimensional balanced turbo-field echo; 0.5 seconds per image) approximately 5 minutes after being intravenously administered 10 mg of scopolamine-N-butyl bromide to deliberately create diverse degrees of small bowel motility. In a manually segmented area of the small bowel, motility was automatically quantified using a nonrigid registration and calculated as a quantitative motility score. The mean value (MV) of motility grades visually assessed by two radiologists was used as a reference standard. The quantitative motility score's correlation (Spearman's ρ) with the reference standard and performance (area under the receiver operating characteristics curve [AUROC], sensitivity, and specificity) for diagnosing adynamic small bowel (MV of 1) were evaluated. Results: For the MV of the quantitative motility scores at grades 1, 1.5, 2, 2.5, and 3, the mean ± standard deviation values were 0.019 ± 0.003, 0.027 ± 0.010, 0.033 ± 0.008, 0.032 ± 0.009, and 0.043 ± 0.013, respectively. There was a significant positive correlation between the quantitative motility score and the MV (ρ = 0.531, P < 0.001). The AUROC value for diagnosing a MV of 1 (i.e., adynamic small bowel) was 0.953 (95% confidence interval, 0.923-0.984). Moreover, the optimal cutoff for the quantitative motility score was 0.024, with a sensitivity of 100% (15/15) and specificity of 89.9% (143/159). Conclusion: The quantitative motility score calculated from a cine MRI enables diagnosis of an adynamic small bowel, and potentially discerns various degrees of bowel motility.

• Information Systems Review
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• v.21 no.4
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• pp.197-220
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• 2019

This study aims to identify consumer motivations of open innovation project participation from digital transformation perspective. By extending a traditional intrinsic/extrinsic motivation framework, we propose a three-dimensional perspective of the self-driven, firm-driven, and sociality-driven motivations. This reveals the significance of the social effects of open innovation projects as an example of digital transformation by categorizing the motivations based on the 'influencer' of the motivation building and by highlighting the importance of sociality as an influencer. As a result, self-efficacy is identified as a key motivation when the influencer exists internally. Economic incentive and firm reputation are identified when the influencer exists externally. Finally, competition, peer evaluation and social contributions are identified when the influencer exists socially. The role of knowledge type sought through innovation projects is further introduced to explain its moderating effects on motivations. The study is validated in two steps. First, we investigate four cases of open innovation projects and examine what motivations are highlighted in each context. Second, we collect survey data from 203 online game users and ask them on their motivations. The results confirm most of our hypotheses and highlight the significance of sociality in the knowledge-seeking process in open innovation projects. This study largely contributes to digital transformation literature by extending the view of motivation and examining the moderating role of knowledge involved in the projects.

• Korean Journal of Radiology
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• v.21 no.8
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• pp.998-1006
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• 2020

Objective: To compare the accuracies of quantitative computed tomography (CT) parameters and semiquantitative visual score in evaluating clinical classification of severity of coronavirus disease (COVID-19). Materials and Methods: We retrospectively enrolled 187 patients with COVID-19 treated at Tongji Hospital of Tongji Medical College from February 15, 2020, to February 29, 2020. Demographic data, imaging characteristics, and clinical data were collected, and based on the clinical classification of severity, patients were divided into groups 1 (mild) and 2 (severe/critical). A semiquantitative visual score was used to estimate the lesion extent. A three-dimensional slicer was used to precisely quantify the volume and CT value of the lung and lesions. Correlation coefficients of the quantitative CT parameters, semiquantitative visual score, and clinical classification were calculated using Spearman's correlation. A receiver operating characteristic curve was used to compare the accuracies of quantitative and semi-quantitative methods. Results: There were 59 patients in group 1 and 128 patients in group 2. The mean age and sex distribution of the two groups were not significantly different. The lesions were primarily located in the subpleural area. Compared to group 1, group 2 had larger values for all volume-dependent parameters (p < 0.001). The percentage of lesions had the strongest correlation with disease severity with a correlation coefficient of 0.495. In comparison, the correlation coefficient of semiquantitative score was 0.349. To classify the severity of COVID-19, area under the curve of the percentage of lesions was the highest (0.807; 95% confidence interval, 0.744-0.861: p < 0.001) and that of the quantitative CT parameters was significantly higher than that of the semiquantitative visual score (p = 0.001). Conclusion: The classification accuracy of quantitative CT parameters was significantly superior to that of semiquantitative visual score in terms of evaluating the severity of COVID-19.

• Journal of Cardiovascular Imaging
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• v.31 no.1
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• pp.18-23
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• 2023

BACKGROUND: Three-dimensional (3D) transesophageal echocardiogram (TEE) is the gold standard for the diagnosis of degenerative mitral regurgitation (dMR) and preoperative planning for transcatheter mitral valve repair (TMVr). TEE is an invasive modality requiring anesthesia and esophageal intubation. The severe acute respiratory syndrome coronavirus 2 pandemic has limited the number of elective invasive procedures. Multi-detector computed tomographic angiography (MDCT) provides high-resolution images and 3D reconstructions to assess complex mitral anatomy. We hypothesized that MDCT would reveal similar information to TEE relevant to TMVr, thus deferring the need for a preoperative TEE in certain situations like during a pandemic. METHODS: We retrospectively analyzed data on patients who underwent or were evaluated for TMVr for dMR with preoperative MDCT and TEE between 2017 and 2019. Two TEE and 2 MDCT readers, blinded to patient outcome, analyzed: leaflet pathology (flail, degenerative, mixed), leaflet location, mitral valve area (MVA), flail width/gap, anterior-posterior (AP) and commissural diameters, posterior leaflet length, leaflet thickness, presence of mitral valve cleft and degree of mitral annular calcification (MAC). RESULTS: A total of 22 (out of 87) patients had preoperative MDCT. MDCT correctly identified the leaflet pathology in 77% (17/22), flail leaflet in 91% (10/11), MAC degree in 91% (10/11) and the dysfunctional leaflet location in 95% (21/22) of patients. There were no differences in the measurements for MVA, flail width, commissural or AP diameter, posterior leaflet length, and leaflet thickness. MDCT overestimated the measurements of flail gap. CONCLUSIONS: For preoperative TMVr planning, MDCT provided similar measurements to TEE in our study.

• Korean Journal of Radiology
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• v.21 no.6
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• pp.670-683
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• 2020

Objective: The presence of coagulative necrosis (CN) in clear cell renal cell carcinoma (ccRCC) indicates a poor prognosis, while the absence of CN indicates a good prognosis. The purpose of this study was to build and validate a radiomics signature based on preoperative CT imaging data to estimate CN status in ccRCC. Materials and Methods: Altogether, 105 patients with pathologically confirmed ccRCC were retrospectively enrolled in this study and then divided into training (n = 72) and validation (n = 33) sets. Thereafter, 385 radiomics features were extracted from the three-dimensional volumes of interest of each tumor, and 10 traditional features were assessed by two experienced radiologists using triple-phase CT-enhanced images. A multivariate logistic regression algorithm was used to build the radiomics score and traditional predictors in the training set, and their performance was assessed and then tested in the validation set. The radiomics signature to distinguish CN status was then developed by incorporating the radiomics score and the selected traditional predictors. The receiver operating characteristic (ROC) curve was plotted to evaluate the predictive performance. Results: The area under the ROC curve (AUC) of the radiomics score, which consisted of 7 radiomics features, was 0.855 in the training set and 0.885 in the validation set. The AUC of the traditional predictor, which consisted of 2 traditional features, was 0.843 in the training set and 0.858 in the validation set. The radiomics signature showed the best performance with an AUC of 0.942 in the training set, which was then confirmed with an AUC of 0.969 in the validation set. Conclusion: The CT-based radiomics signature that incorporated radiomics and traditional features has the potential to be used as a non-invasive tool for preoperative prediction of CN in ccRCC.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.3
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• pp.191-208
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• 2024

In this study, a hydro-mechanical-damage coupled analysis model was developed to evaluate the structural safety of radioactive waste disposal structures. The Mazars damage model, widely used to model the fracture behavior of brittle materials such as rocks or concrete, was coupled with conventional hydro-mechanical analysis and the developed model was verified via theoretical solutions from literature. To derive the numerical input values for damage-coupled analysis, uniaxial compressive strength and Brazilian tensile strength tests were performed on concrete samples made using the mix ratio of the disposal concrete silo cured under dry and saturated conditions. The input factors derived from the laboratory-scale experiments were applied to a two-dimensional finite element model of the concrete silos at the Wolseong Nuclear Environmental Management Center in Gyeongju and numerical analysis was conducted to analyze the effects of damage consideration, analysis technique, and waste loading conditions. The hydro-mechanical-damage coupled model developed in this study will be applied to the long-term behavior and stability analysis of deep geological repositories for high-level radioactive waste disposal.

• Atmosphere
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• v.34 no.3
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• pp.305-317
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• 2024

The study examines the effects of parameters that define the characteristics of raindrops on the simulated precipitation during the summer season over Korea using the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) cloud microphysics scheme. Prescribed parameters, defining the characteristics of hydrometeors in the WDM6 scheme such as a_R, b_R, and f_R in the fall velocity (V_R) - diameter (D_R) relationship and shape parameter (𝜇_R) in the number concentration (N_R) - D_R relationship, presents different values compared to the observed data from Two-Dimensional Video Disdrometer (2DVD) at Boseong standard meteorological observatory during 2018~2019. Three experiments were designed for the heavy rainfall event on August 8, 2022 using WRF version 4.3. These include the control (CNTL) experiment with original parameters in the WDM6 scheme; the MUR experiment, adopting the 50th percentile observation value for 𝜇_R; and the MEDI experiment, which uses the same 𝜇_R as MUR, but also includes fitted values for a_R, b_R, and f_R from the 50th percentile of the observed V_R - D_R relationship. Both sensitivity experiments show improved precipitation simulation compared to the CNTL by reducing the bias and increasing the probability of detection and equitable threat scores. In these experiments, the raindrop mixing ratio increases and its number concentration decreases in the lower atmosphere. The microphysics budget analysis shows that the increase in the rain mixing ratio is due to enhanced source processes such as graupel melting, vapor condensation, and accretion between cloud water and rain. Our study also emphasizes that applying the solely observed 𝜇_R produces more positive impact in the precipitation simulation.

• Journal of the Society of Disaster Information
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• v.20 no.3
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• pp.484-499
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• 2024

Purpose: Recently, due to the aging of safety facilities in national industrial complexes, there has been an increase in the frequency and scale of safety accidents, highlighting the need for a shift toward a prevention-centered disaster management paradigm and the establishment of a digital safety network. In response, this study aims to provide an information system that supports more rapid and precise decision-making during disasters by utilizing digital twin-based integrated control technology to predict the spread of hazardous substances, trace the origin of accidents, and offer safe evacuation routes. Method: We considered various simulation results, such as surface diffusion, upper-level diffusion, and combined diffusion, based on the actual characteristics of hazardous substances and weather conditions, addressing the limitations of previous studies. Additionally, we designed an integrated management system to minimize the limitations of spatiotemporal monitoring by utilizing an IoT sensor-based backtracking model to predict leakage points of hazardous substances in spatiotemporal blind spots. Results: We selected two pilot companies in the Gumi Industrial Complex and installed IoT sensors. Then, we operated a living lab by establishing an integrated management system that provides services such as prediction of hazardous substance dispersion, traceback, AI-based leakage prediction, and evacuation information guidance, all based on digital twin technology within the industrial complex. Conclusion: Taking into account the limitations of previous research, we used digital twin-based AI analysis to predict hazardous chemical leaks, detect leakage accidents, and forecast three-dimensional compound dispersion and traceback diffusion.

• Journal of the Korean Wood Science and Technology
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• v.52 no.5
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• pp.423-437
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• 2024

Wood biomass, such as sawdust, particles, and chips from the wood industry, can be potentially used as a composite product. Chip block pallets (CBP) are composite products that can be produced from industrial wood waste and are in high demand in the logistics sector. Therefore, this study aimed to investigate the production of CBP from teak wood biomass with varying polyurethane contents. In addition, this study analyzed the optimum particle-size composition was determined. The CBP production of CBP be divided into two stages. The first stage evaluated the use of polyurethane adhesive content, whereas the second stage considered the effect of particle size composition. The 9 × 9 × 9 cm³ of CBP with 0.6 g/cm³ target density was fabricated using a cold press. The National Wooden Pallet and Container Association (NWPCA) standards were used to evaluate the density, moisture content, dimensional stability, water absorption, compressive strength (CS), and screw-holding strength (SHS) of our CBP products. The mechanical and physical properties of CBP products were investigated. As a result, the CBP sample prepared using 4-14 mesh particle size and 4.5% adhesive content showed the optimal strength values, such as CS of 14.67 MPa and SHS of 371.50 N. These findings demonstrate that the CBPs derived from teak wood waste closely resemble commercial chip blocks and have the potential to replace wood bearings as pallet pads.

• Journal of the Korean Society of Earth Science Education
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• v.17 no.2
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• pp.181-193
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• 2024

Summative assessment provides information on how well students have achieved learning objectives, making the development of high-quality assessment items essential for accurate evaluation. This is one of the competencies that teachers must possess. This study aims to analyze summative assessment items created by pre-service elementary teachers, examining their intentions and the difficulties encountered in the item development process. The study involved 45 second-year students enrolled in an elementary teacher training university. They were grouped into teams of three and tasked with developing ten items, documenting the purpose of each item, the answer key, and the challenges faced during item creation. The collected summative assessment items were analyzed using a two-dimensional purpose classification table that includes Klopfer's taxonomy of educational objectives. The intentions behind the summative assessments and the difficulties faced during item development were inductively organized and analyzed through qualitative data analysis. The results revealed that pre-service elementary teachers adequately reflected scientific content elements but did not evenly cover assessment domains. The most challenging aspect for them was adjusting the difficulty level. Although they considered most factors that should be taken into account during item development, these considerations were not reflected in the actual items. These findings suggest that knowledge and experience are crucial in developing summative assessment items, and systematic lectures are necessary for pre-service elementary teachers.