• The Journal of Bigdata
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• v.8 no.1
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• pp.23-34
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• 2023

Nowadays, the Designated Driver Services employ dynamic pricing, which adapts in real-time based on nearby driver availability, service user volume, and current weather conditions during the user's request. The uncertain volatility is the main cause of price increases, leading to customer attrition and service refusal from driver. To make a good Designated Driver Services, development of a demand forecasting model is required. In this study, we propose developing a demand forecasting model using data from the Designated Driver Service by considering normal and peak periods, such as rush hour and rush day, as prior knowledge to enhance the model performance. We propose a new methodology called Time-Series with Conditional Probability(TSCP), which combines conditional probability and time-series models to enhance performance. Extensive experiments have been conducted with real Designated Driver Service data, and the result demonstrated that our method outperforms the existing time-series models such as SARIMA, Prophet. Therefore, our study can be considered for decision-making to facilitate proactive response in Designated Driver Services.

• Asia Marketing Journal
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• v.13 no.3
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• pp.249-264
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• 2011

Brand is the major enduring asset of a company and more valuable than the totality of specific products and facilities. Thus brands are powerful assets that must be carefully developed and managed. The company should design and implement marketing activities and marketing communication programs to build and grow the brand value. Strarbucks, Samsung Galaxy, and Nike brands get a price premium and generate strong customer loyalty. A power brand has high brand equity, which is the differential effect that brand knowledge has on consumer response to the marketing of that brand. Brand equity is created when brands have strong, favorable and unique brand associations with customers and high level of brand awareness. Therefore marketers in building a strong brand should ensure to develop the right type of customer experiences with products and effective integrated marketing communication(IMC) programs to create the brand equity. Since 2007 Sinhan card acquiring the LG card has developed the new brand identity and carefully managed the advertising campaign and other marketing communication mix tools to create the high brand awareness and differential brand image. In this case study we examine how Sinhan card with the goal of being No.1 brand in the credit card market has developed and implemented the IMC Strategy to build a high level of consumer brand awareness, unique brand image and strong customer relationship.

• Journal of Practical Engineering Education
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• v.14 no.3
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• pp.601-608
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• 2022

This study examines the current status of smart manufacturing innovation policies in Germany and Korea, compares and analyzes the supply industry strategies of both countries, and suggests the direction for Korea's smart manufacturing innovation supply industry. Germany's supply industry strategy aims to strengthen the market dominance of domestic suppliers through high technology, compatibility, and high reliability based on reference for global demanding companies. On the other hand, the Korea's supply industry strategy remains at the level improvement of the demanding companies by stage, so it is time to take a long-term and consistent response with the goal of implementing smartization at the advanced level. By referring to Germany's supply industry strategy for the advancement of smart factories, it was intended to help in establishing government support policies and supplier strategies. In addition, based on the analysis results of the supply industry strategies of both countries, improvement measures for the advancement of Korea's smart factories were presented. Ultimately, the contents of this study can be used as basic data for policy establishment to strengthen the industrial competitiveness of Korea's small and medium-sized suppliers.

• Korea Trade Review
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• v.48 no.1
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• pp.127-163
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• 2023

The objective of this study is to investigate the volatility spillover effects among BDI, CCFI and SCFI. This paper will divide the empirical analysis section into two periods to analyze and compare the differences in volatility spillover effect between shipping freight indices before and after the outbreak of COVID-19 separately. First, in order to compare the mean spillover impact and index lead-lag correlations in BDI and CCFI indices, along with BDI and SCFI indices before and after COVID-19, the co-integration analysis and the test of Granger causality built on the VAR model were utilized. Second, the impulse response and variance decomposition are employed in this work to investigate how the shipping freight index responds to shocks experienced by itself and other freight indices in a short period. Before the COVID-19 epidemic, the results demonstrated that the BDI freight index is the Granger cause of the variable CCFI freight index. But the BDI and CCFI freight indices have no apparent lead-lag relationships after COVID-19, and this empirical result echoes the cointegration test result. After the COVID-19 epidemic, the SCFI index leads the BDI index. This study employs the VAR-BEKK-GARCH joint model to explore the volatility spillover results between dry bulk and container transport markets before and after COVID-19. The empirical results demonstrate that after COVID-19, fluctuations in the BDI index still affect the CCFI index in the maritime market. However, there is no proof of a volatility spillover relationship between the BDI and SCFI after the COVID-19 epidemic. This study will provide an insight into the volatility relationship among BDI, CCFI and SCFI before and after the the COVID-19 epidemic occurred.

• Journal of Navigation and Port Research
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• v.48 no.1
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• pp.62-77
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• 2024

In the maritime shipping industry, imbalance between supply and demand has persistently increased, leading to the utilization of blank sailings by major shipping companies worldwide as a key means of flexibly adjusting vessel capacity in response to shipping market conditions. Traditionally, blank sailings have been frequently implemented around the Chinese New Year period. However, due to unique circumstances such as the global pandemic starting in 2020 and trade tensions between the United States and China, shipping companies have recently conducted larger-scale blank sailings compared to the past. As blank sailings directly impact freight transport delays, they can have negative repercussions from perspectives of both businesses and consumers. Therefore, this study employed Poisson regression models and negative binomial regression models to analyze the influence of maritime freight rate determinants on shipping companies' decisions regarding blank sailings, aiming to proactively address potential consequences. Results of the analysis indicated that, in Poisson regression analysis for 2M, significant variables included global container shipping volume, container vessel capacity, container ship scrapping volume, container ship newbuilding index, and OECD inflation. In negative binomial regression analysis, ocean alliance showed significance with global container shipping volume and container ship order volume, the alliance with container ship capacity and interest rates, non-alliance with international oil prices, global supply chain pressure index, container ship capacity, OECD inflation, and total alliance with container ship capacity and interest rates.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.1
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• pp.129-141
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• 2024

Amidst the acceleration of digital transformation across various sectors, the financial market is increasingly focusing on the development of digital and electronic payment methods, including currency. Among these, Central Bank Digital Currencies (CBDC) are emerging as future digital currencies that could replace physical cash. They are stable, not subject to value fluctuation, and can be exchanged one-to-one with existing physical currencies. Recently, both domestic and international efforts are underway in researching and developing CBDCs. However, current CBDC systems face scalability issues such as delays in processing large transactions, response times, and network congestion. To build a universal CBDC system, it is crucial to resolve these scalability issues, including the low throughput and network overload problems inherent in existing blockchain technologies. Therefore, this study proposes a solution based on reinforcement learning for handling large-scale data in a CBDC environment, aiming to improve throughput and reduce network congestion. The proposed technology can increase throughput by more than 64 times and reduce network congestion by over 20% compared to existing systems.

• Journal of Applied Biological Chemistry
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• v.66
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• pp.282-288
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• 2023

Due to the COVID-19 pandemic, the immuneenhancing health functional food market that protects our bodies from pathogens such as viruses continues to grow. In this study, we aimed to prove the Cheonggukjang, a high-nutrient food with high protein, fat, and dietary fiber content, as an immuneenhancing nutraceutical. Cheonggukjang water extract (CWE) increased the production of nitric oxide, reactive oxygen species, and cytokines such interleukin (IL)-6, IL-1β, and tumor necrosis factor-α without affecting viability in RAW 264.7 cells. Furthermore, CWE significantly upregulated the expression of inducible nitric oxide synthase and cyclooxygenase-2 in RAW 264.7 cells. CWE enhanced the phosphorylation of I kappa B kinase α/β and I kappa B (IκB)α, as well as the degradation of IκBα. CWE also induced increased phosphorylation of nuclear factor-kappa B p65 and facilitated the redistribution of p65 from the cytoplasm to the nucleus in RAW 264.7 cells. These findings suggest that CWE has potential as a health functional food material that can enhance the innate immune response.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.3
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• pp.121-129
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• 2024

The rapid advancement of digital technology and the COVID-19 pandemic have significantly accelerated the growth of online commerce, highlighting the need for support mechanisms that enable small business owners to effectively respond to these market changes. In response, this paper presents a foundational technology leveraging the Online to Offline (O2O) strategy to automatically capture products displayed on retail shelves and utilize these images to create virtual stores. The essence of this research lies in precisely identifying and recognizing the location and names of displayed products, for which a single-class-targeted, lightweight model based on YOLOv8, named ESD-YOLOv8, is proposed. The detected products are identified by their names through feature-point-based technology, equipped with the capability to swiftly update the system by simply adding photos of new products. Through experiments, product name recognition demonstrated an accuracy of 74.0%, and position detection achieved a performance with an F2-Score of 92.8% using only 0.3M parameters. These results confirm that the proposed method possesses high performance and optimized efficiency.

• Journal of Industrial Convergence
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• v.22 no.7
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• pp.1-13
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• 2024

Among e-government services, the intelligent CCTV control platform is a screening control service that utilizes artificial intelligence to display major objects such as people, cars, etc. to control personnel when they appear on CCTV. The operation of an intelligent CCTV control platform is expected to improve the quality of life of citizens by enabling rapid response in the event of an emergency and increasing the resolution of complaints. In this study, the benefits of the intelligent CCTV control platform, a non-market good, were estimated by applying the contingent valuation method (CVM), a choice experiment technique, to estimate the average willingness to pay per household and calculate the social benefits. As a result of the analysis, the average willingness to pay per household was estimated to be KRW 6,908 per year, and the economic benefits for the country as a whole were estimated to be about KRW 150.4 billion per year. This study is of academic significance as it extends the application of CVM to the field of intelligent e-Government services. The Intelligent CCTV control platforms is being actively discussed, this study has practical implications in that the benefits were estimated in monetary value.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.483-494
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• 2024

This study is a study on influencing factors to derive considerations when establishing a large drone integrated protection system targeting important national facilities. Currently, drone protection is implemented by piecemeal installation of drone protection equipment developed on the market in response to the needs of government agencies, the military, and national important facilities. For this reason, there is a waste of resources, such as duplicate installation or overlapping operation of equipment, and institutional and legal problems between operations are emerging. Accordingly, we sought to identify factors influencing the establishment of an efficient and systematic anti-drone protection system targeting national important facilities. Considering the research purpose and scope, this study derived 3 influencing factors and 12 detailed influencing factors through case analysis, protection theory research, and analysis of related laws. If the results of this study are used as considerations when building an integrated anti-drone protection system in the future, all national defense elements will be integrated and systematic integrated anti-drone protection will be possible according to their respective roles. In addition, it will provide a theoretical foundation for building an integrated anti-drone protection system. The results of this study are valuable in that they present logical and systematic influencing factors for establishing an integrated anti-drone protection system.