• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.94-107
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• 2022

Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.

• Journal of the Korean Society of Safety
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• v.38 no.2
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• pp.104-111
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• 2023

Rolling stock maintenance, which focuses on preventive maintenance, is typically implemented considering the potential harm that may be inflicted to passengers in the event of failure. The cost of preventive maintenance throughout the life cycle of a rolling stock is 60%-75% of the initial purchase cost. Therefore, ensuring stability and reducing maintenance costs are essential in terms of economy. In particular, private railroad operators must reduce government support budget by effectively utilizing railroad resources and reducing maintenance costs. Accordingly, this study analyzes the reliability characteristics of components using field data. Moreover, it resolves the problem of determining an economical replacement interval considering the timing of scrapping railroad vehicles. The procedure for determining the optimal replacement interval involves five steps. According to the decision model, the optimal replacement interval for the onboard signal device components of the "A" line train is calculated using field data, such as failure data, preventive maintenance cost, and failure maintenance cost. The field data analysis indicates that the mileage meter is 9 years, which is less than the designed durability of 15 years. Furthermore, a life cycle in which the phase signal has few failures is found to be the same as the actual durability of 15 years.

• Steel and Composite Structures
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• v.45 no.2
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• pp.205-218
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• 2022

Proper calculation of splitting tensile strength (STS) of concrete has been a crucial task, due to the wide use of concrete in the construction sector. Following many recent studies that have proposed various predictive models for this aim, this study suggests and tests the functionality of three hybrid models in predicting the STS from the characteristics of the mixture components including cement compressive strength, cement tensile strength, curing age, the maximum size of the crushed stone, stone powder content, sand fine modulus, water to binder ratio, and the ratio of sand. A multi-layer perceptron (MLP) neural network incorporates invasive weed optimization (IWO), cuttlefish optimization algorithm (CFOA), and electrostatic discharge algorithm (ESDA) which are among the newest optimization techniques. A dataset from the earlier literature is used for exploring and extrapolating the STS behavior. The results acquired from several accuracy criteria demonstrated a nice learning capability for all three hybrid models viz. IWO-MLP, CFOA-MLP, and ESDA-MLP. Also in the prediction phase, the prediction products were in a promising agreement (above 88%) with experimental results. However, a comparative look revealed the ESDA-MLP as the most accurate predictor. Considering mean absolute percentage error (MAPE) index, the error of ESDA-MLP was 9.05%, while the corresponding value for IWO-MLP and CFOA-MLP was 9.17 and 13.97%, respectively. Since the combination of MLP and ESDA can be an effective tool for optimizing the concrete mixture toward a desirable STS, the last part of this study is dedicated to extracting a predictive formula from this model.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.5
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• pp.25-35
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• 2023

The estuary reservoir is a major source of agricultural water in Korea; for effective and sustainable water resource management of the estuary reservoir, it is crucial to comprehensively consider various water resource factors, including water supply, flood, and pollutant management, and analyze future runoff changes in consideration of environmental changes such as climate change. The objective of this study is to estimate the impact of future climate change on the runoff characteristics of an estuary reservoir watershed. Climate data on future Shared Socioeconomic Pathway (SSP) scenarios were derived from two Global Climate Models (GCMs) of the Coupled Model Intercomparison Project phase 6 (CMIP6). The Hydrological Simulation Program-Fortran (HSPF) was used to simulate past and future long-term runoff of the Ganwol estuary reservoir watershed. The findings showed that as the impact of climate change intensified, the average annual runoff in the future period was higher in the order of SSP5, SSP3, SSP1, and SSP2, and the ratio of runoff in July decreased while the ratio of runoff in October increased. Moreover, in terms of river flow regime, the SSP2 scenario was found to be the most advantageous and the SSP3 scenario was the most disadvantageous. The findings of this study can be used as basic data for developing sustainable water resource management plans and can be applied to estuary reservoir models to predict future environmental changes in estuary reservoirs.

• Journal of Korean Dental Science
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• v.16 no.2
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• pp.172-181
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• 2023

Purpose: To investigate the effect of epidermal growth factor (EGF) with collagen matrix (CM) for increasing gingival thickness. Materials and Methods: In five mongrel dogs, bilateral gingival defects were surgically made on the maxillary canines. After two months, either a subepithelial connective tissue graft (group SCTG) or CM with EGF (0.1 ug/ml, group EGF) was grafted, and the flap was coronally positioned to cover the graft materials. The animals were sacrificed after three months. Intraoral scanning was performed for soft tissue analysis. Histologic and histomorphometric analyses were performed. Result: Two animals exhibited wound dehiscence during the healing phase, leaving three for analysis. No statistically significant difference was found in soft tissue changes (P>0.05). The level of gingival margin (GM) increased in both groups (1.02±0.74 mm in group SCTG vs. 1.24±0.83 mm in group EGF). Linear increases at the GM pre-augmentation in the soft tissue profile were 1.08±0.58 mm in group SCTG and 0.96±0.73 mm in group EGF. Histomorphometric parameters (keratinized tissue height, tissue thickness, and rete peg density) were not significantly different between the groups (P>0.05). Conclusion: EGF loaded onto CM led to comparable gingival phenotype enhancement to SCTG.

• The Transactions of the Korea Information Processing Society
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• v.13 no.2
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• pp.76-90
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• 2024

Although artificial intelligence (AI) can be utilized in various domains such as smart city, healthcare, it is limited due to concerns about the exposure of personal and sensitive information. In response, the concept of distributed machine learning has emerged, wherein learning occurs locally before training a global model, mitigating the concentration of data on a central server. However, overall learning phase in a collaborative way among multiple participants poses threats to data privacy. In this paper, we systematically analyzes recent trends in privacy protection within the realm of distributed machine learning, considering factors such as the presence of a central server, distribution environment of the training datasets, and performance variations among participants. In particular, we focus on key distributed machine learning techniques, including horizontal federated learning, vertical federated learning, and swarm learning. We examine privacy protection mechanisms within these techniques and explores potential directions for future research.

• Journal of Korean Association for Spatial Structures
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• v.24 no.2
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• pp.31-41
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• 2024

This study aims to investigate the seismic response of a large span thin shell structures and assess their displacement under seismic loads. The study employs finite element analysis to model a thin shell structure subjected to seismic excitation. The analysis includes eigenvalue analysis and time history analysis to evaluate the natural frequencies and displacement response of the structure under seismic loads. The findings show that the seismic response of the large span thin shell structure is highly dependent on the frequency content of the seismic excitation. The eigenvalue analysis reveals that the tenth mode of vibration of the structure corresponds to a large-span mode. The time history analysis further demonstrates, with 5% damping, that the displacement response of the structure at the critical node number 4920 increases with increasing seismic intensity, reaching a maximum displacement of 49.87mm at 3.615 seconds. Nevertheless, the maximum displacement is well below the allowable limit of the thin shell. The results of this study provide insight into the behaviour of complex large span thin shell structures as elevated foundations for buildings under seismic excitation, based on the displacement contours on different modes of eigenvalues. The findings suggest that the displacement response of the structure is significant for this new application of thin shell, and it is recommended to enhance the critical displacement area in the next design phase to align with the findings of this study to resist the seismic impact.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.2
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• pp.17-40
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• 2007

Most research on web site design has focused on technological factors, while visual aesthetic factors have been considered less important. In contrast, this study focuses on visual aesthetic factors in web site design. Findings of this study can be summarized as follows : (1) The result of SPSS-factor analysis shows that there are 3 distinct factors, 'classical aesthetics', 'expressive aesthetics', and 'usability' 'Classical aesthetics' and 'expressive aesthetics' can be described by visual aesthetic design, 'Visual aesthetic design' can be distinguished from 'usability'. This conceptual confusion relating to 'usability' and 'visual aesthetic design' can be clarified by these findings. (2) As a result of multiple regression analyses, 'classical aesthetics', 'expressive aesthetics', and 'usability' have a positive influence on 'interactivity' and 'web site evaluation'. This research clarifies the concepts of 'expectations' of Grier [18] and 'engagement' of Rosen and Purinton [33] as the 'interactivity' between users and web sites. Furthermore, this research suggests a valid model with high $R^2$(interactivity, 48% : web site evaluation, 68%). (3) Empirical tests show that the differences among users in 'entry point' are related to the characteristics of web sites and the personal characteristics of users. The differences among users in terms of 'scanning time' are closely related to the attitudes and evaluation tendencies of users with respect to web sites. These findings could contribute to the 'search phase' of the Faraday model [16], enabling it to be more precise and extensible. The managerial implication of this study is that customers' preferences regarding web site designs are differences, as their preferences are based on their individual characteristics. Therefore, marketing managers should consider promotional tools on web sites that are relevant to the target market. An optimal strategy for web design could be a carefully-selected combination of factors that are relevant to the 'interactivity' and 'evaluation' of web sites. Additionally, if marketing managers want to attract more favorable attitudes and more affirmative evaluations from users, web sites should be designed so that they are understood more quickly by users. finally, this study suggests that 'good design' for web sites depends on understanding how to attain the appropriate balance between 'classical aesthetics' and 'expressive aesthetics', based on the target customer.

• Journal of the Korean earth science society
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• v.26 no.6
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• pp.489-500
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• 2005

The objective of this study is to examine the cognitive process that undergoes a middle student’s conceptual change about the universe by the cognitive conflict, using science history materials as a teaching strategy. Four eighth graders were selected and classified by three cognitive level. Students were interviewed and conducted to an inquiry activities regarding their viewpoint about the universe after each class, and their conceptual change patterns were analysed from pre-test and post-test. This study showed that each student held dissimilar astronomical preconceptions and various misconceptions about celestial motion. Students at the formal operational stage and transitional stage experienced the conceptual change from geocentricism to heliocentricism by instructional model upon the science history materials. Student at the concrete operational stage had either unscientific conception, no conception, or could not have a conceptual change even when being presented with an environment that arouses cognitive conflict ($R^2$: Phase change of Venus and its Rise and set time). They ended up having a cognitive change from geocentricism to heliocentricism by solving another problem ($R^2$: Relation between visible diameter and position of Mars). After the instruction, a conceptual achievement progress was reported with a $10\%$ improvement. Therefore, the instruction model based upon science history was effective on student’s scientific conceptual change.

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.105-113
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• 2009

The interpretation of observed waveform characteristics identified in refraction and wide-angle reflection data increases confidence in the crustal structure model obtained. When calculating traveltimes and raypaths, wavefront methods on a regular grid based on graph theory are robust even with complicated structures, but basically compute only first arrivals. In this paper, we develop new algorithms to compute traveltimes and raypaths not only for first arrivals, but also for fast and later reflection arrivals, later refraction arrivals, and converted waves between P and S, using the modified wavefront method based on slowness network nodes mapped on a multi-layer model. Using the new algorithm, we can interpret reflected arrivals, Pg-later arrivals, strong arrivals appearing behind Pn, triplicated Moho reflected arrivals (PmP) to obtain the shape of the Moho, and phases involving conversion between P and S. Using two models of an ocean-continent transition zone and an oceanic ridge or seamount, we show the usefulness of this algorithm, which is confirmed by synthetic seismograms using the 2D Finite Difference Method (2D-FDM). Characteristics of arrivals and raypaths of the two models differ from each other in that using only first-arrival traveltime data for crustal structure analysis involves risk of erroneous interpretation in the ocean-continent transition zone, or the region around a ridge or seamount.