• Journal of Sensor Science and Technology
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• v.30 no.6
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• pp.388-394
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• 2021

The conventional microelectromechanical system (MEMS) process has been used to fabricate sensors with high costs and high-volume productions. Emerging 3D printing can utilize various materials and quickly fabricate a product using low-cost equipment rather than traditional manufacturing processes. 3D printing also can produce the sensor using various materials and design its sensing structure with freely optimized shapes. Hence, 3D printing is expected to be a new technology that can produce sensors on-site and respond to on-demand demand by combining it with open platform technology. Therefore, this paper reviews three standard 3D printing technologies, such as Fused Deposition Modeling (FDM), Direct Ink Writing (DIW), and Digital Light Processing (DLP), which can apply to the sensor fabrication process. The review focuses on strain/load sensors having both sensing material features and structural features as well. NCPC (Nano Carbon Piezoresistive Composite) is also introduced as a promising 3D material due to its favorable sensing characteristics.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.36-48
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• 2022

As a valid numerical method to obtain a high-resolution result of a flow field, computational fluid dynamics (CFD) have been widely used to study coolant flow and heat transfer characteristics in fuel rod bundles. However, the time-consuming, iterative calculation of Navier-Stokes equations makes CFD unsuitable for the scenarios that require efficient simulation such as sensitivity analysis and uncertainty quantification. To solve this problem, a reduced-order model (ROM) based on proper orthogonal decomposition (POD) and machine learning (ML) is proposed to simulate the flow field efficiently. Firstly, a validated CFD model to output the flow field data set of the rod bundle is established. Secondly, based on the POD method, the modes and corresponding coefficients of the flow field were extracted. Then, an deep feed-forward neural network, due to its efficiency in approximating arbitrary functions and its ability to handle high-dimensional and strong nonlinear problems, is selected to build a model that maps the non-linear relationship between the mode coefficients and the boundary conditions. A trained surrogate model for modes coefficients prediction is obtained after a certain number of training iterations. Finally, the flow field is reconstructed by combining the product of the POD basis and coefficients. Based on the test dataset, an evaluation of the ROM is carried out. The evaluation results show that the proposed POD-ROM accurately describe the flow status of the fluid field in rod bundles with high resolution in only a few milliseconds.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2077-2083
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• 2022

In the unlikely event of core disruptive accident in sodium cooled fast reactors, the reactor containment building would be bottled up with sodium and fission product aerosols. The behavior of these aerosols is crucial to estimate the in-containment source term as a part of nuclear reactor safety analysis. In this work, the evolution of sodium aerosol characteristics (mass concentration and size) is simulated using HAARM-S code. The code is based on the method of moments to solve the integro-differential equation. The code is updated to FORTRAN-77 and run in Microsoft FORTRAN PowerStation 4.0 (on Desktop). The sodium aerosol characteristics simulated by HAARM-S code are compared with the measured values at Aerosol Test Facility. The maximum deviation between measured and simulated mass concentrations is 30% at initial period (up to 60 min) and around 50% in the later period. In addition, the influence of humidity on aerosol size growth for two different aerosol mass concentrations is studied. The measured and simulated growth factors of aerosol size (ratio of saturated size to initial size) are found to be matched at reasonable extent. Since sodium is highly reactive with atmospheric constituents, the aerosol growth factor depends on the hygroscopic growth, chemical transformation and density variations besides coagulation. Further, there is a scope for the improvement of the code to estimate the aerosol dynamics in confined environment.

• Knowledge Management Research
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• v.23 no.3
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• pp.153-171
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• 2022

With the global ESG management craze, domestic and foreign companies voluntarily declare sustainable management and actively respond by establishing strategies. The Financial Services Commission mandates the disclosure of sustainability reports representing ESG management sequentially and will expand to SMEs in the future. Information disclosure of sustainability reports is mainly done through international standards such as GRI, SASB, and TCFD, and many domestic companies use GRI Standards guidelines. This study examines the composition system of sustainability reports and compares public and private companies with GRI Standards to analyze sustainable management by type. This study revealed that public enterprises focused on social and labor, while private enterprises focused on the economy and environment through TF-IDF modeling. In addition, the electronic and information communication industries focused on product responsibility. Unlike previous studies that quantified and analyzed sustainability management according to grade, the current study analyzed sustainability reports, which are unstructured data. Therefore, the results of this study are expected to provide valuable theoretical and practical implications for researchers and supervisors interested in ESG management.

• Fashion & Textile Research Journal
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• v.23 no.3
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• pp.347-357
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• 2021

This study analyzed the effects of optimism and innovativeness, the two drivers of a consumer's technological readiness to use an augmented reality(AR) fashion shopping service within the framework of the Technology Acceptance Model (TAM). The survey was conducted on 249 people (males = 58; females = 191) in their 20s who were willing to participate in the AR experience. Data were analyzed using confirmatory factor analysis (CFA) and structural equation modeling by AMOS 22.0. The results indicated that a greater level of perceived optimism had a positive influence on the ease of use and usefulness of the technology. The findings also show that consumers with a high degree of innovativeness tend to have a higher level of playfulness toward AR fashion shopping. Regarding the effects of user beliefs, ease of use had a positive effect on the perception of usefulness and playfulness with higher levels implying a higher consumer intention to adopt an AR fashion shopping service. In addition, this study reveals the moderating effect of consumers with high-fashion versus those with low-fashion innovativeness. For the latter, technological innovation had an insignificant effect on playfulness, thus indicating that consumers with low interest in fashion did not enjoy AR fashion shopping even if the technology was highly innovative. Nevertheless, the analysis confirms the possibility that experiencing a fashion product through AR technology could replace the actual experience of wearing the products.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1825-1834
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• 2022

Performing high-fidelity computational fluid dynamics (HF-CFD) to predict the flow and heat transfer state of the coolant in the reactor core is expensive, especially in scenarios that require extensive parameter search, such as uncertainty analysis and design optimization. This work investigated the performance of utilizing a multi-fidelity reduced-order model (MF-ROM) in PWR rod bundles simulation. Firstly, basis vectors and basis vector coefficients of high-fidelity and low-fidelity CFD results are extracted separately by the proper orthogonal decomposition (POD) approach. Secondly, a surrogate model is trained to map the relationship between the extracted coefficients from different fidelity results. In the prediction stage, the coefficients of the low-fidelity data under the new operating conditions are extracted by using the obtained POD basis vectors. Then, the trained surrogate model uses the low-fidelity coefficients to regress the high-fidelity coefficients. The predicted high-fidelity data is reconstructed from the product of extracted basis vectors and the regression coefficients. The effectiveness of the MF-ROM is evaluated on a flow and heat transfer problem in PWR fuel rod bundles. Two data-driven algorithms, the Kriging and artificial neural network (ANN), are trained as surrogate models for the MF-ROM to reconstruct the complex flow and heat transfer field downstream of the mixing vanes. The results show good agreements between the data reconstructed with the trained MF-ROM and the high-fidelity CFD simulation result, while the former only requires to taken the computational burden of low-fidelity simulation. The results also show that the performance of the ANN model is slightly better than the Kriging model when using a high number of POD basis vectors for regression. Moreover, the result presented in this paper demonstrates the suitability of the proposed MF-ROM for high-fidelity fixed value initialization to accelerate complex simulation.

• Journal of Powder Materials
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• v.29 no.1
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• pp.14-21
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• 2022

In the powder bed fusion (PBF) process, a 3D shape is formed by the continuous stacking of very fine powder layers using computer-aided design (CAD) modeling data, following which laser irradiation can be used to fuse the layers forming the desired product. In this method, the main process parameters for manufacturing the desired 3D products are laser power, laser speed, powder form, powder size, laminated thickness, and laser diameter. Stainless steel (STS) 316L exhibits excellent strength at high temperatures, and is also corrosion resistant. Due to this, it is widely used in various additive manufacturing processes, and in the production of corrosion-resistant components with complicated shapes. In this study, rectangular specimens have been manufactured using STS 316L powder via the PBF process. Further, the effect of heat treatment at 800 ℃ on the microstructure and hardness has been investigated.

• Knowledge Management Research
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• v.23 no.3
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• pp.89-109
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• 2022

Many companies are trying to enter into overseas markets to overcome the limited size of domestic markets. However, there are many barriers to enter the overseas markets such as difficulty to find buyers and make contract with them, payment risks, unfriendly foreign policies, and etc. Companies have used to various strategies to get opportunities of overseas markets. One of them is UN public procurement. Despite many advantages, limited number of companies are participating in the procurement. Individual governments are providing policies to support local companies to participate in the UN public procurement. However it is not easy to encourage firms, especially SMEs to participate in the procurement. This study is designed to analyze firm and product determinants of participating in UN public procurement. Based on literature reviews and empirical findings, this study shows social responsibility and global orientation can play an important role regarding the participation. In addition, the positive relationship between UN public procurement participation and sustainability in a given firm could be empirically supported. Last, we suggest combining country- and industry-level data to investigate UN public procurement participation as an interesting topic for future research. This study represents various determinants to encourage UN public procurement participation. They may contribute to enhance firm performance such as sustainability.

• Journal of the Korea Society for Simulation
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• v.18 no.2
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• pp.65-75
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• 2009

The semiconductor manufacturing process normally includes a great number of complex sequential steps those are related with various types of equipment. Such equipments are installed with the mixed patterns of serial or parallel structures while considering a number of engineering or environmental factors at the same time. It is thus extremely difficult to change the layout after installation due to expensive costs and other related factors. Because of these reasons, a new investment or layout change, which is usually caused by the production policy such as product mix or production quantity, must be carefully considered. This case study introduces a simulation conducted in a semiconductor parts production company which produces the Board on Chip (BOC)-type of packaging substrate and has plans to change the facility layout. For this study, we used $QUEST^{(R)}$ for simulation modeling and evaluated various strategies which may cause layout changes. Further, the Analytic Hierarchy Process (AHP) is applied to select the best strategy from several alternatives with multiple decision criteria.

• Journal of the Korean Society of Food Culture
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• v.38 no.1
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• pp.1-14
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• 2023

This study was conducted to explore the change in the market issues on HMR (Home Meal Replacements) using local foods after the COVID-19 outbreak. Online text data were collected from internet news, social media posts, and web documents before (from January 2016 to December 2019) and after (from January 2020 to November 2022) the COVID-19 outbreak. TF-IDF analysis showed that 'Trend', 'Market', 'Consumption', and 'Food service industry' were the major keywords before the COVID-19 outbreak, whereas 'Wanju-gun', 'Distribution', 'Development', and 'Meal-kit' were main keywords after the COVID-19 outbreak. The results of topic modeling analysis and categorization showed that after the COVID-19 outbreak, the 'Market' category included 'Non-face-to-face market' instead of 'Event,' and 'Delivery' instead of 'Distribution'. In the 'Product' category, 'Marketing' was included instead of 'Trend'. Additionally, in the 'Support' category, 'Start-up' and 'School food service' appeared as new topics after the COVID-19 outbreak. In conclusion, this study showed that meaningful change had occurred in market issues on HMR using local foods after the COVID-19 outbreak. Therefore, governments should take advantage of such market opportunity by implementing policy and programs to promote the development and marketing of HMR using local foods.