• Journal of Venture Innovation
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• v.6 no.1
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• pp.59-73
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• 2023

In the era of the 4th Industrial Revolution, manufacturing is the implementation of smart factories through digital transformation, and refers to consumer-centered intelligent factories that combine next-generation digital new technologies and manufacturing technologies beyond the existing factory automation level. In order to successfully settle such a smart factory, it is necessary to train professionals. However, education for smart factories is difficult to have actual field mechanical facilities or overall production processes. Therefore, there is a need for a system that can visualize and control the flow and process of logistics at the actual production site. In this paper, the logistics flow of the actual site was implemented as a small FMS, a physical system, and the production process was implemented as a digital system. In real-time synchronization of the physical system and the digital system, the location of AGV and materials, and the process state can be monitored to see the flow of logistics and process processes at the actual manufacturing site. The developed digital twin system can be used as an effective educational system for training manpower in smart factories.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.4
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• pp.8-16
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• 2023

The importance of next-generation packaging technologies is being emphasized as a solution as the miniaturization of devices reaches its limits. To address the bottleneck issue, there is an increasing need for 2.5D and 3D interconnect pitches. This aims to minimize signal delays while meeting requirements such as small size, low power consumption, and a high number of I/Os. Hybrid bonding technology is gaining attention as an alternative to conventional solder bumps due to their limitations such as miniaturization constraints and reliability issues in high-temperature processes. Recently, there has been active research conducted on SiCN to address and enhance the limitations of the Cu/SiO₂ structure. This paper introduces the advantages of Cu/SiCN over the Cu/SiO₂ structure, taking into account various deposition conditions including precursor, deposition temperature, and substrate temperature. Additionally, it provides insights into the core mechanisms of SiCN, such as the role of Dangling bonds and OH groups, and the effects of plasma surface treatment, which explain the differences from SiO₂. Through this discussion, we aim to ultimately present the achievable advantages of applying the Cu/SiCN hybrid bonding structure.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.755-770
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• 2023

Due to recent severe climate change, abnormal weather phenomena, and other factors, the frequency and magnitude of natural disasters are increasing. The need for disaster management using artificial satellites is growing, especially during large-scale disasters due to time and economic constraints. In this study, we have summarized the current status of next-generation medium-sized satellites and microsatellites in operation and under development, as well as trends in satellite imagery analysis techniques using a large volume of satellite imagery driven by the advancement of the space industry. Furthermore, by utilizing satellite imagery, particularly focusing on recent major disasters such as floods, landslides, droughts, and wildfires, we have confirmed how satellite imagery can be employed for damage analysis, thereby establishing its potential for disaster management. Through this study, we have presented satellite development and operational statuses, recent trends in satellite imagery analysis technology, and proposed disaster response strategies that utilize various types of satellite imagery. It was observed that during the stages of disaster progression, the utilization of satellite imagery is more prominent in the response and recovery stages than in the prevention and preparedness stages. In the future, with the availability of diverse imagery, we plan to research the fusion of cutting-edge technologies like artificial intelligence and deep learning, and their applicability for effective disaster management.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3874-3897
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• 2023

A high-fidelity computational fluid dynamics (CFD) analysis was performed using the Large Eddy Simulation (LES) model for the lower plenum of the High-Temperature Test Facility (HTTF), a ¼ scale test facility of the modular high temperature gas-cooled reactor (MHTGR) managed by Oregon State University. In most next-generation nuclear reactors, thermal stress due to thermal striping is one of the risks to be curiously considered. This is also true for HTGRs, especially since the exhaust helium gas temperature is high. In order to evaluate these risks and performance, organizations in the United States led by the OECD NEA are conducting a thermal hydraulic code benchmark for HTGR, and the test facility used for this benchmark is HTTF. HTTF can perform experiments in both normal and accident situations and provide high-quality experimental data. However, it is difficult to provide sufficient data for benchmarking through experiments, and there is a problem with the reliability of CFD analysis results based on Reynolds-averaged Navier-Stokes to analyze thermal hydraulic behavior without verification. To solve this problem, high-fidelity 3-D CFD analysis was performed using the LES model for HTTF. It was also verified that the LES model can properly simulate this jet mixing phenomenon via a unit cell test that provides experimental information. As a result of CFD analysis, the lower the dependency of the sub-grid scale model, the closer to the actual analysis result. In the case of unit cell test CFD analysis and HTTF CFD analysis, the volume-averaged sub-grid scale model dependency was calculated to be 13.0% and 9.16%, respectively. As a result of HTTF analysis, quantitative data of the fluid inside the HTTF lower plenum was provided in this paper. As a result of qualitative analysis, the temperature was highest at the center of the lower plenum, while the temperature fluctuation was highest near the edge of the lower plenum wall. The power spectral density of temperature was analyzed via fast Fourier transform (FFT) for specific points on the center and side of the lower plenum. FFT results did not reveal specific frequency-dominant temperature fluctuations in the center part. It was confirmed that the temperature power spectral density (PSD) at the top increased from the center to the wake. The vortex was visualized using the well-known scalar Q-criterion, and as a result, the closer to the outlet duct, the greater the influence of the mainstream, so that the inflow jet vortex was dissipated and mixed at the top of the lower plenum. Additionally, FFT analysis was performed on the support structure near the corner of the lower plenum with large temperature fluctuations, and as a result, it was confirmed that the temperature fluctuation of the flow did not have a significant effect near the corner wall. In addition, the vortices generated from the lower plenum to the outlet duct were identified in this paper. It is considered that the quantitative and qualitative results presented in this paper will serve as reference data for the benchmark.

• Journal of the Korean institute of surface engineering
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• v.56 no.6
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• pp.412-419
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• 2023

Anion exchange membrane electrolysis is considered a promising next-generation hydrogen production technology that can produce low-cost, clean hydrogen. However, anion exchange membrane electrolysis technology is in its early stages of development and requires intensive research on electrodes, which are a key component of the catalyst-system interface. In this study, we optimized the pressure conditions of the hot-pressing process to manufacture cobalt oxide electrodes for the development of a high uniformity and high adhesion electrode production process for the oxygen evolution reaction. As the pressure increased, the reduction of pores within the electrode and increased densification of catalytic particles led to the formation of a uniform electrode surface. The cobalt oxide electrode optimized for pressure conditions exhibited improved catalytic activity and durability. The optimized electrode was used as the anode in an AEMWE single cell, exhibiting a current density of 1.53 A cm^-2 at a cell voltage of 1.85 V. In a durability test conducted for 100 h at a constant current density of 500 mA cm^-2, it demonstrated excellent durability with a low degradation rate of 15.9 mV kh^-1, maintaining 99% of its initial performance.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.117-132
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• 2022

Human Human species run into a blind alley due to abnormal weather and climates everywhere in global village. Human beings are helpless against the nature and might begin to learn humbleness just now. However, humans cannot attribute current abnormal weather and climates to only natural phenomenon because we have never been affectionate to global environments sufficiently up to now that results in running into this blind alley. At this point, the only thing that humans can do is to love and care for the earth more. ESG is an emerging topic to cope with this issue and practice of ESG will be the pending mission for the next generation. In this research, 'active participatory learning program for ESG practice' is designed by 'connecting ESG with Entrepreneurship' through over 20 years of experienced current teachers in elementary and junior·senior high school, professors in university and field experts in education. Analysis of learning effectiveness before and after the implementation of education program showed meaningful result in elementary and junior·senior high school. Thus, I would like to suggest a proposal based on concerns about 'What should we do to overcome the global crisis?" by paying attention to ESG from elementary school.

• Animal Bioscience
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• v.37 no.6
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• pp.1021-1030
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• 2024

Objective: R-loops are DNA:RNA triplex hybrids, and their metabolism is tightly regulated by transcriptional regulation, DNA damage response, and chromatin structure dynamics. R-loop homeostasis is dynamically regulated and closely associated with gene transcription in mouse zygotes. However, the factors responsible for regulating these dynamic changes in the R-loops of fertilized mouse eggs have not yet been investigated. This study examined the functions of candidate factors that interact with R-loops during zygotic gene activation. Methods: In this study, we used publicly available next-generation sequencing datasets, including low-input ribosome profiling analysis and polymerase II chromatin immunoprecipitation-sequencing (ChIP-seq), to identify potential regulators of R-loop dynamics in zygotes. These datasets were downloaded, reanalyzed, and compared with mass spectrometry data to identify candidate factors involved in regulating R-loop dynamics. To validate the functions of these candidate factors, we treated mouse zygotes with chemical inhibitors using in vitro fertilization. Immunofluorescence with an anti-R-loop antibody was then performed to quantify changes in R-loop metabolism. Results: We identified DEAD-box-5 (DDX5) and histone deacetylase-2 (HDAC2) as candidates that potentially regulate R-loop metabolism in oocytes, zygotes and two-cell embryos based on change of their gene translation. Our analysis revealed that the DDX5 inhibition of activity led to decreased R-loop accumulation in pronuclei, indicating its involvement in regulating R-loop dynamics. However, the inhibition of histone deacetylase-2 activity did not significantly affect R-loop levels in pronuclei. Conclusion: These findings suggest that dynamic changes in R-loops during mouse zygote development are likely regulated by RNA helicases, particularly DDX5, in conjunction with transcriptional processes. Our study provides compelling evidence for the involvement of these factors in regulating R-loop dynamics during early embryonic development.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.335-343
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• 2024

Real-time target signal processing techniques for FMCW LiDAR are described in this paper. FMCW LiDAR is gaining attention as the next-generation LiDAR for self-driving cars because of its detection robustness even in adverse environmental conditions such as rain, snow and fog etc. in addition to its long range measurement capability. The hardware architecture which is required for high-speed data acquisition, data transfer, and parallel signal processing for frequency-domain signal processing is described in this article. Fourier transformation of the acquired time-domain signal is implemented on FPGA in real time. The paper also details the C-FAR algorithm for ensuring robust target detection from the transformed target spectrum. This paper elaborates on enhancing frequency measurement resolution from the target spectrum and converting them into range and velocity data. The 3D image was generated and displayed using the 2D scanner position and target distance data. Real-time target signal processing and high-resolution image acquisition capability of FMCW LiDAR by using the proposed parallel signal processing algorithms based on FPGA architecture are verified in this paper.

• Journal of Life Science
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• v.34 no.7
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• pp.453-464
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• 2024

The fermentation of ganjang is known to be greatly influenced by the microbial communities derived from its primary ingredients, meju and sea salt. This study investigated the effects of changes in meju size on the distribution and correlation of microbial communities in ganjang fermentation, to enhance its fermentation process. Ganjang was prepared using whole meju and meju divided into thirds, and samples were collected at 7-day intervals over a period of 28 days for microbial community analysis based on 16S rRNA gene sequencing. At the genus level, during fermentation, ganjang made with whole meju exhibited a dominance of Chromohalobacter (day 7), Pediococcus (day 14), Bacillus (day 21), and Pediococcus (day 28), whereas ganjang made with meju divided into thirds consistently showed a Pediococcus predominance over the 28 days. Beta-diversity analysis of microbial communities in ganjang with different meju sizes revealed significant separation of microbial communities at fermentation days 7 and 14 but not at days 21 and 28 across all experimental groups. The linear discriminant analysis effect size (LEfSe) was determined to identify biomarkers contributing to microbial community differences at days 7 and 14, showing that on day 7, potentially halophilic microbes such as Gammaproteobacteria, Firmicutes, Oceanospirillales, Halomonadaceae, Bacilli, and Chromohalobacter were prominent, whereas on day 14, lactic acid bacteria such as Pediococcus acidilactici, Lactobacillaceae, Pediococcus, Bacilli, Leuconostocaceae, and Weissella were predominant. Furthermore, correlation analysis of microbial communities at the genus and species levels revealed differences in correlation patterns between meju sizes, suggesting that meju size may influence microbial interactions within ganjang.

• Korean Journal of Clinical Laboratory Science
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• v.55 no.4
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• pp.235-243
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• 2023

As next-generation sequencing has been developed and used widely, RNA-sequencing (RNA-seq) has rapidly emerged as the first choice of tools to validate global transcriptome profiling. With the significant advances in RNA-seq, various types of RNA-seq have evolved in conjunction with the progress in bioinformatic tools. On the other hand, it is difficult to interpret the complex data underlying the biological meaning without a general understanding of the types of RNA-seq and bioinformatic approaches. In this regard, this paper discusses the two main sections of RNA-seq. First, two major variants of RNA-seq are described and compared with the standard RNA-seq. This provides insights into which RNA-seq method is most appropriate for their research. Second, the most widely used RNA-seq data analyses are discussed: (1) exploratory data analysis and (2) pathway enrichment analysis. This paper introduces the most widely used exploratory data analysis for RNA-seq, such as principal component analysis, heatmap, and volcano plot, which can provide the overall trends in the dataset. The pathway enrichment analysis section introduces three generations of pathway enrichment analysis and how they generate enriched pathways with the RNA-seq dataset.