Objectives: This study aims to confirm the educational necessity and utilization of VR media. And it was conducted to prepare basic data necessary for the use of VR in various dental hygiene education in the future and the development of innovative practical training courses. Methods: Before and after using VR in oral radiology practice classes, learning interest (4 items), learning commitment (9 items), learning motivation (5 items), educational media preference (4 items), and satisfaction (10 items) were investigated and analyzed. Friedman two way ANOVA by ran a nonparametric analysis corresponding to repeated measures ANOVA was performed. The statistical significance level was 0.05. Results: It was found that there were statistically significant differences in learning interest, learning immersion, and learning motivation according to the type of oral radiology practice education medium (p<0.05). Conclusions: VR is expected that the use of learning media using VR will lead to students' interest, immersion, and learning motivation in class, and that positive learning effects on VR education media can be sufficiently obtained.
The analysis of engineering data using neural network based on supervised learning has been utilized in various engineering fields such as optimization of chemical engineering process, concentration prediction of particulate matter pollution, prediction of thermodynamic phase equilibria, and prediction of physical properties for transport phenomena system. The supervised learning requires training data, and the performance of the supervised learning is affected by the composition and the configurations of the given training data. Among the frequently observed engineering data, the data is given in log-scale such as length of DNA, concentration of analytes, etc. In this study, for widely distributed log-scaled training data of virtual 100×100 images, available loss functions were quantitatively evaluated in terms of (i) confusion matrix, (ii) maximum relative error and (iii) mean relative error. As a result, the loss functions of mean-absolute-percentage-error and mean-squared-logarithmic-error were the optimal functions for the log-scaled training data. Furthermore, we figured out that uniformly selected training data lead to the best prediction performance. The optimal loss functions and method for how to compose training data studied in this work would be applied to engineering problems such as evaluating DNA length, analyzing biomolecules, predicting concentration of colloidal suspension.
The Seoul Metropolitan Government is building and operating digital twin-based urban spatial information to solve various problems in the city and provide public services. Two essential factors to ensure the stable utilization of spatial information for the implementation of such a digital twin city are the latest and quality of the data. However, it is time-consuming and costly to maintain continuous updating of high-quality urban spatial information. To overcome this problem, we studied efficient urban spatial information construction technology and the operation, management, and update procedures of construction data. First, we demonstrated and applied automatic 3D building construction technology centered on point clouds using the latest hybrid sensors, confirmed that it is possible to automatically construct high-quality building models using high-density airborne lidar results, and established an efficient data management plan. By applying differentiated production methods by region, supporting detection of urban change areas through Seoul spatial feature identifiers, and producing international standard data by level, we strengthened the utilization of urban spatial information. We believe that this study can serve as a good precedent for local governments and related organizations that are considering activating urban spatial information based on digital twins, and we expect that discussions on the construction and management of spatial information as infrastructure information for city-level digital twin implementation will continue.
Geum Bong Yu;Chang Heon Choi;Jung-in Kim;Jin Dong Cho;Euntaek Yoon;Hyung Jin Choun;Jihye Choi;Soyeon Kim;Yongsik Kim;Do Hoon Oh;Hwajung Lee;Lee Yoo;Minsoo Chun
Progress in Medical Physics
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v.33
no.4
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pp.150-157
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2022
Purpose: Elekta synergy® was commissioned in the Seoul National University Veterinary Medical Teaching Hospital. Recently, Chung-Ang University Gwang Myeong Hospital commissioned Elekta Versa HDTM. The beam characteristics of both machines are similar because of the same AgilityTM MLC Model. We compared measured beam data calculated using the Elekta treatment planning system, Monaco®, for each institute. Methods: Beam of the commissioning Elekta linear accelerator were measured in two independent institutes. After installing the beam model based on the measured beam data into the Monaco®, Monte Carlo (MC) simulation data were generated, mimicking the beam data in a virtual water phantom. Measured beam data were compared with the calculated data, and their similarity was quantitatively evaluated by the gamma analysis. Results: We compared the percent depth dose (PDD) and off-axis profiles of 6 MV photon and 6 MeV electron beams with MC calculation. With a 3%/3 mm gamma criterion, the photon PDD and profiles showed 100% gamma passing rates except for one inplane profile at 10 cm depth from VMTH. Gamma analysis of the measured photon beam off-axis profiles between the two institutes showed 100% agreement. The electron beams also indicated 100% agreement in PDD distributions. However, the gamma passing rates of the off-axis profiles were 91%-100% with a 3%/3 mm gamma criterion. Conclusions: The beam and their comparison with MC calculation for each institute showed good performance. Although the measuring tools were orthogonal, no significant difference was found.
This study investigated the effects of utilizing 3D printed teaching aids on academic achievement and learning motivation in a non-face-to-face learning environment during the COVID-19 pandemic. The study was divided into an experimental and a comparison group that applied traditional lecture-based teaching and self-directed learning using 3D printed teaching aids and videos. The results of the study showed that the experimental group using 3D printed brain puzzles improved their academic performance compared to the comparison group using traditional lectures. This may be due to the fact that visual and experiential learning helped students to acquire knowledge on their own. The brain puzzles provided an interesting learning experience for the students, and their overall satisfaction with the class was also positive. These results indicate that teaching with teaching aids can increase students' motivation to learn and improve their academic performance. Therefore, the active introduction of 3D printed teaching aids in the non-face-to-face learning environment caused by COVID-19 is expected to improve the quality of education through innovation in learner-centered teaching methods.
Hye Jung Choo;Sun Joo Lee;Dong Wook Kim;Yoo Jin Lee;Jin Wook Baek;Ji-yeon Han;Young Jin Heo
Korean Journal of Radiology
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v.22
no.8
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pp.1341-1351
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2021
Objective: To compare the quality of various polychromatic and monochromatic images with or without using an iterative metal artifact reduction algorithm (iMAR) obtained from a dual-energy computed tomography (CT) to evaluate total knee arthroplasty. Materials and Methods: We included 58 patients (28 male and 30 female; mean age [range], 71.4 [61-83] years) who underwent 74 knee examinations after total knee arthroplasty using dual-energy CT. CT image sets consisted of polychromatic image sets that linearly blended 80 kVp and tin-filtered 140 kVp using weighting factors of 0.4, 0, and -0.3, and monochromatic images at 130, 150, 170, and 190 keV. These image sets were obtained with and without applying iMAR, creating a total of 14 image sets. Two readers qualitatively ranked the image quality (1 [lowest quality] through 14 [highest quality]). Volumes of high- and low-density artifacts and contrast-to-noise ratios (CNRs) between the bone and fat tissue were quantitatively measured in a subset of 25 knees unaffected by metal artifacts. Results: iMAR-applied, polychromatic images using weighting factors of -0.3 and 0.0 (P-0.3i and P0.0i, respectively) showed the highest image-quality rank scores (median of 14 for both by one reader and 13 and 14, respectively, by the other reader; p < 0.001). All iMAR-applied image series showed higher rank scores than the iMAR-unapplied ones. The smallest volumes of low-density artifacts were found in P-0.3i, P0.0i, and iMAR-applied monochromatic images at 130 keV. The smallest volumes of high-density artifacts were noted in P-0.3i. The CNRs were best in polychromatic images using a weighting factor of 0.4 with or without iMAR application, followed by polychromatic images using a weighting factor of 0.0 with or without iMAR application. Conclusion: Polychromatic images combined with iMAR application, P-0.3i and P0.0i, provided better image qualities and substantial metal artifact reduction compared with other image sets.
Journal of the Computational Structural Engineering Institute of Korea
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v.37
no.3
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pp.205-216
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2024
Recently, seismic Probabilistic Safety Assessment (PSA) methods have been developed for process plants, such as gas plants, oil refineries, and chemical plants. The framework originated from the PSA of nuclear power plants, which aims to assess the risk of reactor core damage. The original PSA method was modified to adopt the characteristics of a process plant whose purpose is continuous operation without shutdown. Therefore, a fault tree, whose top event is shut down, was constructed and transformed into a Bayesian Network (BN), a probabilistic graph model, for efficient risk-informed decision-making. In this research, the fault tree-based BN from the previous research is further developed to consider the multi-hazard of earthquake-induced fire and explosion (EQ-induced F&E). For this purpose, an event tree describing the occurrence of fire and explosion from a release is first constructed and transformed into a BN. And then, this BN is connected to the previous BN model developed for seismic PSA. A virtual plot plan of a gas plant is introduced as a basis for the construction of the specific EQ-induced F&E BN to test the proposed BN framework. The paper demonstrates the method through two examples of risk-informed decision-making. In particular, the second example verifies how the proposed method can establish a repair and retrofit strategy when a shutdown occurs in a process plant.
The recent advancements in Smart City and Digital Twin technologies have highlighted the critical role of integrating GIS and BIM in urban planning and construction projects. This integration ensures the consistency and accuracy of information, facilitating smooth information exchange. However, achieving interoperability requires standardization and effective project integration management strategies. This study proposes interoperability solutions for the integration of GIS and BIM for managing various projects. The research involves an in-depth analysis of the IFC schema and data structures based on the latest IFC4 version and proposes methods to ensure the consistency of reference point coordinates and coordinate systems. The study was conducted by setting the EPSG:5186 coordinate system, used by the National Geographic Information Institute's digital topographic map, and applying virtual shift origin coordinates. Through BIMvision, the results of the shape and error check coordinates' movement in the BIM model were reviewed, confirming that the error check coordinates moved consistently with the reference point coordinates. Additionally, it was verified that even when the coordinate system was changed to EPSG:5179 used by Naver Map and road name addresses, or EPSG:5181 used by Kakao Map, the BIM model's shape and coordinates remained consistently unchanged. Notably, by inputting the EPSG code information into the IFC file, the potential for coordinate system interoperability between projects was confirmed. Therefore, this study presents an integrated and systematic management approach for information sharing, automation processes, enhanced collaboration, and sustainable development of GIS and BIM. This is expected to improve compatibility across various software platforms, enhancing information consistency and efficiency across multiple projects.
Jaewoong Hwang;Heetaek Yoon;Junhyun Bae;Youngkon Park
Land and Housing Review
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v.15
no.2
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pp.125-137
/
2024
A conventional Design for Safety (DfS), introduced to eliminate potential hazards in the design phase proactively, has encountered persistent challenges, such as perfunctory risk assessments and hazard identifications based on 2D drawings and inefficient workflow processes. This study proposes a BIM-based approach to Design for Safety (DfS) to address the limitations of conventional methods, aiming to enhance efficiency and achieve practical safety management benefits. The proposed workflow process for BIM-based DfS has been refined and validated for on-site applicability through various case studies, including risk assessments during the design phase and field applications for safety management activities during the construction phase. Specifically, the critical process of risk assessment within the DfS methodology has also been transitioned to a BIM-based approach. This BIM-based risk assessment process has been evaluated through case studies, encompassing safety reviews for structural design, construction equipment operation, and construction methodology with sequence in design projects. Additionally, the proposed BIM-based DfS has demonstrated exceptional on-site applicability and efficiency, as validated by the application of a BIM deliverable embedded in DfS information for CDE-based daily activity briefing, VR-based safety training, AR-based mitigation measures inspections, and other safety management activities in the construction phase.
Background: Ginsenoside Rg1 (Rg1) is one of the main active components in Chinese medicines, Panax ginseng and Panax notoginseng. Research has shown that Rg1 has a protective effect on the cardiovascular system, including anti-myocardial ischemia-reperfusion injury, anti-apoptosis, and promotion of myocardial angiogenesis, suggesting it a potential cardiovascular agent. However, the protective mechanism involved is still not fully understood. Methods: Based on network pharmacology, ligand-based protein docking, proteomics, Western blot, protein recombination and spectroscopic analysis (UV-Vis and fluorescence spectra) techniques, potential targets and pathways for Rg1 against myocardial ischemia (MI) were screened and explored. Results: An important target set containing 19 proteins was constructed. Two target proteins with more favorable binding activity for Rg1 against MI were further identified by molecular docking, including mitogen-activated protein kinase 1 (MAPK1) and adenosine kinase (ADK). Meanwhile, Rg1 intervention on H9c2 cells injured by H2O2 showed an inhibitory oxidative phosphorylation (OXPHOS) pathway. The inhibition of Rg1 on MAPK1 and OXPHOS pathway was confirmed by Western blot assay. By protein recombination and spectroscopic analysis, the binding reaction between ADK and Rg1 was also evaluated. Conclusion: Rg1 can effectively alleviate cardiomyocytes oxidative stress injury via targeting MAPK1 and ADK, and inhibiting oxidative phosphorylation (OXPHOS) pathway. The present study provides scientific basis for the clinical application of the natural active ingredient, Rg1, and also gives rise to a methodological reference to the searching of action targets and pathways of other natural active ingredients.
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