• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.102-108
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• 2024

In the initial stages of urban air mobility (UAM) operations, compliance with existing visual flight rules and instrument flight regulations for conventional human-crewed aircraft is crucial. Additionally, voice communication between the on board pilot and relevant UAM stakeholders, including vertiports, is essential. Consequently, very high frequency (VHF) aviation voice communication must be consistently provided throughout all phases of UAM operations. This paper presents the results of the VHF communication coverage analysis for the initial UAM demonstration areas, encompassing the Hangang River and Incheon Ara-Canal corridors, as well as potential vertiport candidate locations. By considering the influence of terrain and buildings through the utilization of a digital surface model (DSM), communication quality prediction results are obtained for the analysis areas. The three-dimensional coverage analysis results indicate that stable coverage can be achieved within altitude corridors ranging from 300 m to 600 m. However, there are shaded areas in the low-altitude vertiport regions due to the impact of high-rise buildings. Therefore, additional research to ensure stable coverage around vertiports in the lower altitude areas is required.

• Information Systems Review
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• v.25 no.1
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• pp.111-128
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• 2023

With the development of artificial intelligence technology, interest in data-based product preference estimation and personalized recommender systems is increasing. However, if the recommendation is not suitable, there is a risk that it may reduce the purchase intention of the customer and even extend to a huge financial loss due to the characteristics of the financial product. Therefore, developing a recommender system that comprehensively reflects customer characteristics and product preferences is very important for business performance creation and response to compliance issues. In the case of financial products, product preference is clearly divided according to individual investment propensity and risk aversion, so it is necessary to provide customized recommendation service by utilizing accumulated customer data. In addition to using these customer behavioral characteristics and transaction history data, we intend to solve the cold-start problem of the recommender system, including customer demographic information, asset information, and stock holding information. Therefore, this study found that the model proposed deep learning-based collaborative filtering by deriving customer latent preferences through characteristic information such as customer investment propensity, transaction history, and financial product information based on customer transaction log records was the best. Based on the customer's financial investment mechanism, this study is meaningful in developing a service that recommends a high-priority group by establishing a recommendation model that derives expected preferences for untraded financial products through financial product transaction data.

• Information Systems Review
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• v.25 no.1
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• pp.213-231
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• 2023

With the rapid development of live streaming commerce, online host as an information source plays a critical role in affecting live streaming performance. However, the impact of different product types on the relationship between online hosts and live streaming has been less studied. Based on the elaboration likelihood model (ELM) and information source theory, this study aims to empirically investigate what factors influence the sales of live streaming commerce and how product type moderates the relationship between them. The analysis of 11,422 live streaming commerce data collected for four months from October 10, 2021 to February 10, 2022 shows that, among the factors related to source credibility and attractiveness, multi-channel networks (MCN) and the number of followers positively affect the sales volume of live streaming commerce, whereas the reputation score harms the sales. Moreover, the moderating effect of the product type (i.e., ratio of involvement products) on the relationships is confirmed. The findings enrich the literature on live streaming commerce performance. The limitations and future research directions are also discussed.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.65-76
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• 2024

With the recent activation of the offshore wind power industry, there has been a development of power plants with a scale exceeding 400MW, comparable to traditional thermal power plants. Renewable energy, characterized by intermittency depending on the energy source, is a prominent feature of modern renewable power generation facilities, which are structured based on controllable inverter technology. As the integration of renewable energy sources into the grid expands, the grid codes for power system connection are progressively becoming more defined, leading to active discussions and evaluations in this area. In this paper, we propose a method for selecting optimal reactive power compensation capacity when multiple offshore wind farms are integrated and connected through a shared interconnection facility to comply with grid codes. Based on the requirements of the grid code, we analyze the reactive power compensation and excessive stability of the 400MW wind power generation site under development in the southwest sea of Jeonbuk. This analysis involves constructing a generation site database using PSS/E (Power System Simulation for Engineering), incorporating turbine layouts and cable data. The study calculates reactive power due to charging current in internal and external network cables and determines the reactive power compensation capacity at the interconnection point. Additionally, static and dynamic stability assessments are conducted by integrating with the power system database.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.267-274
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• 2024

In this paper, we investigated the number of domestic patent applications by year, the number of domestic patent disclosures by year, and the number of domestic registrations by year regarding smart factories. The number of patent applications by applicant type was investigated. Based on the patents studied, it was found that the IPC appearing in the most patents was G05B 19/418. In addition, through social network analysis of smart factory patented IPCs, it was found that G05B 19/418 was the IPC with the highest degree of centrality. From the above, if the IPC of the core technology of the patent submitted for smart factory is G05B 19/418, the technology combined with G05B 23/02, that is, the technology combining "factory control" and "monitoring" is the most patented. When the IPC of the core technology was G06Q 50/04, it was confirmed that the technology combined with G06Q 50/10, that is, the technology combining "manufacturing" and "service" was the most applied for patents. Through this, it was found that in order to apply for a patent for a smart factory, it would be necessary to file a patent application that takes into account the connectivity between IPCs.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.2
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• pp.77-84
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• 2024

In the fourth industrial-revolution era, the construction industry is transitioning from traditional methods to digital processes. This shift has been challenging owing to the industry's employment of diverse processes and extensive human resources, leading to a gradual adoption of digital technologies through trial and error. One critical area of focus is the safety management at construction sites, which is undergoing significant research and efforts towards digitization and automation. Despite these initiatives, recent statistics indicate a persistent occurrence of accidents and fatalities in construction sites. To address this issue, this study utilizes large-scale language-model artificial intelligence to analyze big data from a construction safety-management information network. The findings are integrated into on-site models, which incorporate real-time updates from detailed design models and are enriched with location information and spatial characteristics, for enhanced safety management. This research aims to develop a big-data-driven safety-management platform to bolster facility and worker safety by digitizing construction-site safety data. This platform can help prevent construction accidents and provide effective education for safety practices.

• Journal of Korea Water Resources Association
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• v.57 no.4
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• pp.277-287
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• 2024

Water distribution system (WDS) is exposed to various water quality incidents during its operation. This study utilized Quantitative Microbial Risk Assessment (QMRA) to analyze the risk associated with potential virus intrusion in WDSs. Additionally, the study determined the location and operation of rechlorination facilities to minimize potential risk. In addition, water quality resilience was calculated to confirm that the chlorine concentration maintains within the target range (0.1-1.0 mg/L) during normal operation. Hydraulic analysis was performed using EPANET, while EPANET-MSX was linked to simulate the reactions between viruses and chlorine. The proposed methodology was applied to the Bellingham network in the United States, where rechlorination facilities capable of injecting chlorine concentrations ranging from 0.5 mg/L to 1.0 mg/L were considered. Results indicated that without rechlorination facilities, the Average risk was 0.0154. However, installing rechlorination facilities and injecting chlorine at a concentration of 1.0 mg/L could reduce the Average risk to 39.1%. It was observed that excessive chlorine injection through rechlorination facilities reduced water quality resilience. Consequently, a rechlorination facility with a concentration of 0.5 mg/L was selected, resulting in a reduction of approximately 20% in average risk. This study provides insights for designing rechlorination facilities to enhance preparedness against potential virus ingress in the future.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.31-41
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• 2024

Deep learning models show excellent performance in tasks such as image classification and object detection in the field of computer vision, and are used in various ways in actual industrial sites. Recently, research on improving robustness has been actively conducted, along with pointing out that this deep learning model is vulnerable to hostile examples. A hostile example is an image in which small noise is added to induce misclassification, and can pose a significant threat when applying a deep learning model to a real environment. In this paper, we tried to confirm the robustness of the edge-learning classification model and the performance of the adversarial example detection model using it for adversarial examples of various algorithms. As a result of robustness experiments, the basic classification model showed about 17% accuracy for the FGSM algorithm, while the edge-learning models maintained accuracy in the 60-70% range, and the basic classification model showed accuracy in the 0-1% range for the PGD/DeepFool/CW algorithm, while the edge-learning models maintained accuracy in 80-90%. As a result of the adversarial example detection experiment, a high detection rate of 91-95% was confirmed for all algorithms of FGSM/PGD/DeepFool/CW. By presenting the possibility of defending against various hostile algorithms through this study, it is expected to improve the safety and reliability of deep learning models in various industries using computer vision.

• IMMUNE NETWORK
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• v.23 no.5
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• pp.39.1-39.15
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• 2023

Coronavirus disease 2019 (COVID-19) vaccination may non-specifically alter the host immune system. This study aimed to evaluate the effect of COVID-19 vaccination on hepatitis B surface Ag (HBsAg) titer and host immunity in chronic hepatitis B (CHB) patients. Consecutive 2,797 CHB patients who had serial HBsAg measurements during antiviral treatment were included in this study. Changes in the HBsAg levels after COVID-19 vaccination were analyzed. The dynamics of NK cells following COVID-19 vaccination were also examined using serial blood samples collected prospectively from 25 healthy volunteers. Vaccinated CHB patients (n=2,329) had significantly lower HBsAg levels 1-30 days post-vaccination compared to baseline (median, -21.4 IU/ml from baseline), but the levels reverted to baseline by 91-180 days (median, -3.8 IU/ml). The velocity of the HBsAg decline was transiently accelerated within 30 days after vaccination (median velocity: -0.06, -0.39, and -0.04 log₁₀ IU/ml/year in pre-vaccination period, days 1-30, and days 31-90, respectively). In contrast, unvaccinated patients (n=468) had no change in HBsAg levels. Flow cytometric analysis showed that the frequency of NK cells expressing NKG2A, an NK inhibitory receptor, significantly decreased within 7 days after the first dose of COVID-19 vaccine (median, -13.1% from baseline; p<0.001). The decrease in the frequency of NKG2A⁺ NK cells was observed in the CD56^dimCD16⁺ NK cell population regardless of type of COVID-19 vaccine. COVID-19 vaccination leads to a rapid, transient decline in HBsAg titer and a decrease in the frequency of NKG2A⁺ NK cells.

• IMMUNE NETWORK
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• v.23 no.6
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• pp.43.1-43.10
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• 2023

The continuous emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) variants has provided insights for updating current coronavirus disease 2019 (COVID-19) vaccines. We examined the neutralizing activity of Abs induced by a BA.4/5-containing bivalent mRNA vaccine against Omicron subvariants BN.1 and XBB.1.5. We recruited 40 individuals who had received a monovalent COVID-19 booster dose after a primary series of COVID-19 vaccinations and will be vaccinated with a BA.4/5-containing bivalent vaccine. Sera were collected before vaccination, one month after, and three months after a bivalent booster. Neutralizing Ab (nAb) titers were measured against ancestral SARS-CoV-2 and Omicron subvariants BA.5, BN.1, and XBB.1.5. BA.4/5-containing bivalent vaccination significantly boosted nAb levels against both ancestral SARS-CoV-2 and Omicron subvariants. Participants with a history of SARS-CoV-2 infection had higher nAb titers against all examined strains than the infection-naïve group. NAb titers against BN.1 and XBB.1.5 were lower than those against the ancestral SARS-CoV-2 and BA.5 strains. These results suggest that COVID-19 vaccinations specifically targeting emerging Omicron subvariants, such as XBB.1.5, may be required to ensure better protection against SARS-CoV-2 infection, especially in high-risk groups.