• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.329-338
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• 2022

As the non-face-to-face economic situation developed due to the COVID-19 pandemic, untact stock groups appeared in the stock market. This study proposed the Korea COVID-19 fear index following the spread of infectious diseases in the COVID-19 pandemic situation and analyzed the influence on the untact stock and contact stock returns. The results of the empirical analysis are as follows. First, as a result of the Granger causality analysis using the Korea COVID-19 fear index, significant causality was found in the return of contact stocks such as Korean Air, Hana Tour, CJ CGV, and Paradise. Second, as a result of stock price prediction based on the LSTM model, Kakao, Korean Air, and Naver's prediction performance was high. Third, the investment performances of the Alexander filter entry rule using the predicted stock price were high in Naver futures and Kakao futures. This study can find a difference from previous studies in that it analyzed the influence of the spread of the COVID-19 pandemic on untact and contact stocks in the COVID-19 situation where the non-face-to-face economy is in full swing.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.152-159
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• 2023

This study endeavors to enrich investment prospects in cryptocurrency by establishing a rationale for investment decisions. The primary objective involves evaluating the predictability of four prominent cryptocurrencies - Bitcoin, Ethereum, Litecoin, and EOS - and scrutinizing the efficacy of trading strategies developed based on the prediction model. To identify the most effective prediction model for each cryptocurrency annually, we employed three methodologies - AutoRegressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), and Prophet - representing traditional statistics and artificial intelligence. These methods were applied across diverse periods and time intervals. The result suggested that Prophet trained on the previous 28 days' price history at 15-minute intervals generally yielded the highest performance. The results were validated through a random selection of 100 days (20 target dates per year) spanning from January 1st, 2018, to December 31st, 2022. The trading strategies were formulated based on the optimal-performing prediction model, grounded in the simple principle of assigning greater weight to more predictable assets. When the forecasting model indicates an upward trend, it is recommended to acquire the cryptocurrency with the investment amount determined by its performance. Experimental results consistently demonstrated that the proposed trading strategy yields higher returns compared to an equal portfolio employing a buy-and-hold strategy. The cryptocurrency trading model introduced in this paper carries two significant implications. Firstly, it facilitates the evolution of cryptocurrencies from speculative assets to investment instruments. Secondly, it plays a crucial role in advancing deep learning-based investment strategies by providing sound evidence for portfolio allocation. This addresses the black box issue, a notable weakness in deep learning, offering increased transparency to the model.

• Korea Trade Review
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• v.47 no.6
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• pp.335-353
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• 2022

There are two aspects of digital trade: the digitalisation of goods/services being traded and the digitalisation of the transactional act. Digital data (i.e. machine-readable industrial data and transactional data) is the major driving force for both aspects of digital trade. Digital data is a non-rivalrous input, whether for production or marketing activities, and is thus able to be used by many firms or government agencies without limiting the use of others. Digital platforms provide online infrastructure for the interactions between groups, for instance, consumers and producers. The externality effect refers to the situation in which prosperity in one group on a given platform will improve the returns of other groups on the same platform. In the era of the data-driven economy, strategic trade policy can involve data-related policies. The major objective of these policies is to improve the competitiveness of domestic firms. For instance, firms may be subsidised if they use cloud services provided by specific platforms. This strand of strategic trade policies might be useful for increasing the competitiveness of small-and medium-sized enterprises (SMEs) via the digitalisation of production/marketing processes. Alternatively, strategic trade policy may also exploit the externality effect via platform economy-related policies. Further, some countries may form data coalitions to facilitate cross-border data flow. This paper uses cases in Asian countries to illustrate which role these strategic trade policies can play in the digital economy.

• Korea Trade Review
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• v.48 no.4
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• pp.121-148
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• 2023

The rapid melting of Arctic sea ice has increased interest in the Northern Sea Route (NSR) as a viable alternative trade route between Europe and Asia. While extensive research has examined its competitiveness in terms of technical feasibility, safety, profitability, and environmental impact, the topic of the NSR ports remains relatively underrepresented in the literature. Hence, this study aims to contribute to the existing research by assessing the efficiency of 17 NSR ports to gain insights into their operations and identify areas for improvement using models of Data Envelopment Analysis(DEA). The obtained results show that efficient ports mainly belong to the western NSR region, with ports like Murmansk and Varandei consistently demonstrating high efficiency and constant returns to scale. Several ports, such as Onega, Arkhangelsk, Naryan-Mar, and Khatanga, showed inefficiencies in the utilization of berths and quay lengths. The findings not only contribute to academic knowledge but also offer practical implications for NSR port authorities, assisting them in making well-informed decisions regarding infrastructure development plans.

• Convergence Security Journal
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• v.23 no.3
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• pp.29-36
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• 2023

With the recent surge in exposure to fake advertising phishing sites in search engines, the damage caused by poor search quality and personal information leakage is increasing. In particular, the seriousness of the problem is worsening faster as the possibility of automating the creation of advertising phishing sites through tools such as ChatGPT increases. In this paper, the source code of fake advertising phishing sites was statically analyzed to derive structural commonalities, and among them, a detection crawler that filters sites step by step based on foreign domains and redirection was developed to confirm that fake advertising posts were finally detected. In addition, we demonstrate the need for new guide lines by verifying that the redirection page of fake advertising sites is divided into three types and returns different sites according to each situation. Furthermore, we propose new detection guidelines for fake advertising phishing sites that cannot be detected by existing detection methods.

• Advances in aircraft and spacecraft science
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• v.10 no.6
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• pp.495-519
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• 2023

The drone serves the customers not served by vans. At the same time, considering the safety, policy and terrain as well as the need to replace the battery, the drone needs to be transported by truck to the identified station along with the parcel. From each such station, the drone serves a subset of customers according to a direct assignment pattern, i.e., every time the drone is launched, it serves one demand node and returns to the station to collect another parcel. Similarly, the truck is used to transport the drone and cargo between stations. This is somewhat different from the research of other scholars. In terms of the joint distribution of the drone and road vehicle, most scholars will choose the combination of two transportation tools, while we use three. The drone and vans are responsible for distribution services, and the trucks are responsible for transporting the goods and drone to the station. The goal is to optimize the total delivery cost which includes the transportation costs for the vans and the delivery cost for the drone. A fixed cost is also considered for each drone parking site corresponding to the cost of positioning the drone and using the drone station. A discrete optimization model is presented for the problem in addition to a two-phase heuristic algorithm. The results of a series of computational tests performed to assess the applicability of the model and the efficiency of the heuristic are reported. The results obtained show that nearly 10% of the cost can be saved by combining the traditional delivery mode with the use of a drone and drone stations.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.2
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• pp.69-80
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• 2024

In this paper, we studied a discrete-time queuing system that operates under a mixed situation of D-policy and T-policy, one of the representative server control policies in queuing theory. A single server serves customers arriving by Bernoulli arrival process on a first-in, first-out basis(FIFO). If there are no customers to serve in the system, the server goes on vacation and returns, until the total service time (i.e., total amount of workload) of waiting customers exceeds predetermined workload threshold D. The operation of the system covered in this study can be used to model the efficient resource utilization of mobile devices using secondary batteries. In addition, it is significant in that the steady state waiting time and system sojourn time of the queuing system under a flexible mixed control policy were derived within a unified framework.

• Informatization Policy
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• v.31 no.2
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• pp.65-81
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• 2024

The scale of e-procurement through online shopping malls of public institutions including government comprehensive shopping malls is increasing day by day. This study aims to examine how public officials evaluate products, delivery, and post service of online shopping malls for public institutions and to explore ways of improving their satisfaction. The results from a survey conducted among public officials of public institutions who have experience using online shopping malls of public institutions showed generally high satisfaction levels, although there was dissatisfaction with product diversity. Perception of delivery quality was generally positive, but there was room for improvement in delivery service. Furthermore, employing structural equation modeling, the study examined the influences on satisfaction and intention to reuse. Perceived product quality, delivery quality, and delivery service quality were confirmed to influence satisfaction considerably. Therefore, more efforts should be directed towards managing the information and quality of products to prevent returns, exchanges, and repairs and, in case of issues, handling them promptly and transparently.

• The Korean Journal of Applied Statistics
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• v.37 no.3
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• pp.265-282
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• 2024

Research in the area of financial portfolio optimization, with the dual goals of increasing expected returns and reducing financial risk, has actively explored various risk measurement indicators. At the same time, the incorporation of various penalty terms to construct efficient portfolios with limited assets has been investigated. In this study, we present a novel portfolio optimization formula that combines the mean-shortfall portfolio and the SLOPE penalty term. Specifically, we formulate this optimization expression, which differs from linear programming, by introducing new variables and using the alternating direction method of multipliers (ADMM) algorithms. Through simulations, we validate the automatic grouping property of the SLOPE penalty term within the proposed mean-shortfall portfolio. Furthermore, using the model introduced in this paper, we propose and evaluate four different types of portfolio compositions relevant to real-world investment scenarios through empirical data analysis.

• Hip & pelvis
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• v.34 no.3
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• pp.161-171
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• 2022

Purpose: The number of obese patients seeking total hip arthroplasty (THA) continues to expand despite body mass index (BMI) cutoffs. We sought to determine the outcomes of THA in the morbidly obese patient, and hypothesized they would have comparable outcomes to two cohorts of obese, and normal weight patients. Materials and Methods: THA performed on morbidly obese patients (BMI >40 kg/m²) at a single academic center from 2010 until 2020 were retrospectively reviewed. Eighty morbidly obese patients were identified, and matched in a 1:3:3 ratio to control cohorts with BMI 30-40 kg/m² and BMI <30 kg/m². Acute postoperative outcomes and BMI change after surgery were evaluated for clinical significance with univariate and regression analyses. Cox proportional hazard ratio was calculated to evaluate prosthetic joint infection (PJI) and revision surgery through follow-up. Mean follow-up was 3.9 years. Results: In the acute postoperative period, morbidly obese patients trended towards increased hospital length of stay, facility discharge and 90-day hospital returns. At final follow-up, a higher percentage of morbidly obese patients had clinically significant (>5%) BMI loss; however, this was not significant. Cox hazard ratio with BMI <30 kg/m² as a reference demonstrated no significant difference in survival to PJI and all-cause revision in the morbidly obese cohort. Conclusion: Morbidly obese patients (BMI >40 kg/m²) require increased resource expenditure in the acute postoperative period. However, they are not inferior to the control cohorts (BMI <30 kg/m², BMI 30-40 kg/m²) in terms of PJI or all-cause revisions at mid-term follow-up.