• Journal of Environmental Health Sciences
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• v.47 no.6
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• pp.521-529
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• 2021

Background: The coronavirus disease (COVID-19) has caused changes in human activity, and these changes may possibly increase or decrease exposure to fine dust (PM_2.5). Therefore, it is necessary to evaluate the exposure to PM_2.5 in relation to the outbreak of COVID-19. Objectives: The purpose of this study was to compare and evaluate the exposure to PM_2.5 concentrations by the variation of dynamic populations before and after the outbreak of COVID-19. Methods: This study evaluated exposure to PM_2.5 concentrations by changes in the dynamic population distribution in Guro-gu, Seoul, before and after the outbreak of COVID-19 between Jan and Feb, 2020. Gurogu was divided into 2,204 scale standard grids of 100 m×100 m. Hourly PM_2.5 concentrations were modeled by the inverse distance weight method using 24 sensor-based air monitoring instruments. Hourly dynamic population distribution was evaluated according to gender and age using mobile phone network data and time-activity patterns. Results: Compared to before, the population exposure to PM_2.5 decreased after the outbreak of COVID-19. The concentration of PM_2.5 after the outbreak of COVID-19 decreased by about 41% on average. The variation of dynamic population before and after the outbreak of COVID-19 decreased by about 18% on average. Conclusions: Comparing before and after the outbreak of COVID-19, the population exposures to PM_2.5 decreased by about 40%. This can be explained to suggest that changes in people's activity patterns due to the outbreak of COVID-19 resulted in a decrease in exposure to PM_2.5.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.593-609
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• 2021

We proposed a numerical method for the thermo-mechanical behavior of rock fracture using a grain-based distinct element model (GBDEM) and simulated thermally induced fracture slip. The present study is the benchmark simulation performed as part of DECOVALEX-2023 Task G, which aims to develop a numerical method to estimate the coupled thermo-hydro-mechanical processes within the crystalline rock fracture network. We represented the rock sample as an assembly of Voronoi grains and calculated the interaction of the grains (blocks) and their interfaces (contacts) using a distinct element code, 3DEC. Based on an equivalent continuum approach, the micro-parameters of grains and contacts were determined to reproduce rock as an elastic material. Then, the behavior of the fracture embedded in the rock was characterized by the contacts with Coulomb shear strength and tensile strength. In the benchmark simulation, we quantitatively examined the effects of the boundary stress and thermal stress due to heat conduction on fracture behavior, focusing on the mechanism of thermally induced fracture slip. The simulation results showed that the developed numerical model reasonably reproduced the thermal expansion and thermal stress increment, the fracture stress and displacement and the effect of boundary condition. We expect the numerical model to be enhanced by continuing collaboration and interaction with other research teams of DECOVALEX-2023 Task G and validated in further study experiments.

• Korean small business review
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• v.42 no.4
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• pp.251-283
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• 2020

The purpose of this study is to provide assistance to the establishment of related policies to improve the level of acceptance and use of smart factories for SMEs in Korea. To this end, the Unified Technology Acceptance Model (UTAUT) was extended to select additional factors that could affect the intention to accept technology, and to demonstrate this. To achieve the research objective, a questionnaire composed of 7-point Likert scales was prepared, and a survey was conducted for manufacturing-related companies. A total of 136 questionnaires were used for statistical processing. As a result of the hypothesis test, performance expectation and social influence had a positive (+) positive effect on voluntary use, but effort expectation and promotion conditions did not have a significant effect. As an extension factor, the network effect and organizational characteristics had a positive (+) effect, and the innovation resistance had a negative effect (-), but the perceived risk had no significant effect. When the size of the company is large, the perceived risk and innovation resistance are low, and the level of influencing factors for veterinary intentions, veterinary intentions, and veterinary behaviors are excluded. Through this study, factors that could have a positive and negative effect on the adoption (reduction) of smart factory-related technologies were identified and factors to be improved and factors to be reduced were suggested. As a result, this study suggests that smart factory-related technologies should be accepted.

• Economic and Environmental Geology
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• v.55 no.1
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• pp.1-17
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• 2022

The mechanical and thermal properties of the rock masses can affect the performance associated with both the isolating and retarding capacities of radioactive materials within the deep geological disposal system for High-Level Radioactive Waste (HLW). In this study, the essential parameters for the site descriptive model (SDM) related to the rock mechanics and thermal properties of the HLW disposal facilities site were reviewed, and the technical background was explored through the cases of the preceding site descriptive models developed by SKB (Swedish Nuclear and Fuel Management Company), Sweden and Posiva, Finland. SKB and Posiva studied parameters essential for the investigation and evaluation of mechanical and thermal properties, and derived a rock mechanics site descriptive model for safety evaluation and construction of the HLW disposal facilities. The rock mechanics SDM includes the results obtained from investigation and evaluation of the strength and deformability of intact rocks, fractures, and fractured rock masses, as well as the geometry of large-scaled deformation zones, the small-scaled fracture network system, thermal properties of rocks, and the in situ stress distribution of the disposal site. In addition, the site descriptive model should provide the sensitivity analysis results for the input parameters, and present the results obtained from evaluation of uncertainty.

• Journal of the Korean Electrochemical Society
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• v.25 no.4
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• pp.174-183
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• 2022

Polymer electrolyte fuel cells and water electrolysis are attracting attention in terms of high energy density and high purity hydrogen production. The catalyst layer for the polymer electrolyte fuel cell and water electrolysis is a porous electrode composed of a precious metal-based electrocatalyst and an ionomer binder. Among them, the ionomer binder plays an important role in the formation of a three-dimensional network for ion conduction in the catalyst layer and the formation of pores for the movement of materials required or generated for the electrode reaction. In terms of the use of commercial perfluorinated ionomers, the content of the ionomer, the physical properties of the ionomer, and the type of the dispersing solvent system greatly determine the performance and durability of the catalyst layer. Until now, many studies have been reported on the method of using an ionomer for the catalyst layer for polymer electrolyte fuel cells. This review summarizes the research results on the use of ionomer binders in the fuel cell aspect reported so far, and aims to provide useful information for the research on the ionomer binder for the catalyst layer, which is one of the key elements of polymer electrolyte water electrolysis to accelerate the hydrogen economy era.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.582-583
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• 2021

As the production of new and renewable energy such as solar and wind power has diversified, microgrid systems that can simultaneously produce and consume have been introduced. . In general, a decrease in electricity prices through solar power is expected in summer, so producer protection is required. In this paper, we propose a transparent and safe gift power transaction system between users using blockchain in a microgrid environment. A futures is simply a contract in which the buyer is obligated to buy electricity or the seller is obliged to sell electricity at a fixed price and a predetermined futures price. This system proposes a futures trading algorithm that searches for futures prices and concludes power transactions with automated operations without user intervention by using a smart contract, a reliable executable code within the blockchain network. If a power producer thinks that the price during the peak production period (Hajj) is likely to decrease during production planning, it sells futures first in the futures market and buys back futures during the peak production period (Haj) to make a profit in the spot market. losses can be compensated. In addition, if there is a risk that the price of electricity will rise when a sales contract is concluded, a broker can compensate for a loss in the spot market by first buying futures in the futures market and liquidating futures when the sales contract is fulfilled.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.584-585
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• 2021

As the production of new and renewable energy such as solar and wind power has diversified, microgrid systems that can simultaneously produce and consume have been introduced. In general, a decrease in electricity prices through solar power is expected in summer, so producer protection is required. In this paper, we propose a transparent and safe gift power transaction system between users using blockchain in a microgrid environment. A futures is simply a contract in which the buyer is obligated to buy electricity or the seller is obliged to sell electricity at a fixed price and a predetermined futures price. This system proposes a futures trading algorithm that searches for futures prices and concludes power transactions with automated operations without user intervention by using a smart contract, a reliable executable code within the blockchain network. If a power producer thinks that the price during the peak production period is likely to decrease during production planning, it sells futures first in the futures market and buys back futures during the peak production period to make a profit in the spot market. losses can be compensated. In addition, if there is a risk that the price of electricity will rise when a sales contract is concluded, a broker can compensate for a loss in the spot market by first buying futures in the futures market and liquidating futures when the sales contract is fulfilled.

• Journal of The Korean Astronomical Society
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• v.56 no.2
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• pp.231-252
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• 2023

We present the analysis results of the simultaneous multifrequency observations of the blazar 4C +28.07. The observations were conducted by the Interferometric Monitoring of Gamma-ray Bright Active Galactic Nuclei (iMOGABA) program, which is a key science program of the Korean Very Long Baseline Interferometry (VLBI) Network (KVN). Observations of the iMOGABA program for 4C +28.07 were conducted from 16 January 2013 (MJD 56308) to 13 March 2020 (MJD 58921). We also used γ-ray data from the Fermi Large Array Telescope (Fermi-LAT) Light Curve Repository, covering the energy range from 100 MeV to 100 GeV. We divided the iMOGABA data and the Fermi-LAT data into five periods from 0 to 4, according to the prosody of the 22 GHz data and the presence or absence of the data. In order to investigate the characteristics of each period, the light curves were plotted and compared. However, a peak that formed a hill was observed earlier than the period of a strong γ-ray flare at 43-86 GHz in period 3 (MJD 57400-58100). Therefore, we assumed that the minimum total CLEANed flux density for each frequency was quiescent flux (S_q) in which the core of 4C +28.07 emitted the minimum, with the variable flux (S_var) obtained by subtracting S_q from the values of the total CLEANed flux density. We then compared the variability of the spectral indices (α) between adjacent frequencies through a spectral analysis. Most notably, α_22-43 showed optically thick spectra in the absence of a strong γ-ray flare, and when the flare appeared, α_22-43 became optically thinner. In order to find out the characteristics of the magnetic field in the variable region, the magnetic field strength in the synchrotron self-absorption (B_SSA) and the equipartition magnetic field strength (B_eq) were obtained. We found that B_SSA is largely consistent with B_eq within the uncertainty, implying that the SSA region in the source is not significantly deviated from the equipartition condition in the γ-ray quiescent periods.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.445-471
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• 2023

Long-term safety over millennia is the top priority consideration in the construction of disposal sites. However, ensuring the mechanical stability of deep geological repositories for spent fuel, a.k.a. radwaste, disposal during construction and operation is also crucial for safe operation of the repository. Imposing restrictions or limitations on tunnel support and lining materials such as shotcrete, concrete, grouting, which might compromise the sealing performance of backfill and buffer materials which are essential elements for the long-term safety of disposal sites, presents a highly challenging task for rock engineers and tunnelling experts. In this study, as part of an extensive exploration to aid in the proper selection of disposal sites, the anticipation of constructing a deep geological repository at a depth of 500 meters in an unknown state has been carried out. Through a review of 2D and 3D numerical analyses, the study aimed to explore the range of properties that ensure stability. Preliminary findings identified the potential range of rock properties that secure the stability of central and disposal tunnels, while the stability of the vertical tunnel network was confirmed through 3D analysis, outlining fundamental rock conditions necessary for the construction of disposal sites.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.519-524
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• 2023

In hashing-based image retrieval, the hash code of a manipulated image is different from the original image, making it difficult to search for the same image. This paper proposes and evaluates a self-supervised deephashing model that generates perceptual hash codes from feature information such as texture, shape, and color of images. The comparison models are autoencoder-based variational inference models, but the encoder is designed with a fully connected layer, convolutional neural network, and transformer modules. The proposed model is a variational inference model that includes a SimAM module of extracting geometric patterns and positional relationships within images. The SimAM module can learn latent vectors highlighting objects or local regions through an energy function using the activation values of neurons and surrounding neurons. The proposed method is a representation learning model that can generate low-dimensional latent vectors from high-dimensional input images, and the latent vectors are binarized into distinguishable hash code. From the experimental results on public datasets such as CIFAR-10, ImageNet, and NUS-WIDE, the proposed model is superior to the comparative model and analyzed to have equivalent performance to the supervised learning-based deephashing model. The proposed model can be used in application systems that require low-dimensional representation of images, such as image search or copyright image determination.