• Journal of Navigation and Port Research
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• v.46 no.5
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• pp.441-448
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• 2022

The aim of this study was to examine determinants of secondhand Bulk carrier and Oil tanker prices. This study compiled S& P transaction data taken from the Clarksons Research during J anuary 2018 to April 2022 to see how independent variables influenced secondhand ship prices. In the secondhand ship pricing model of entire segments, size, age, and LIBOR showed significant effects on prices. A vessel built in J apan and Korea was traded at a higher price than a vessel built in other countries. In the bulk segment, size, age, Clarksea index, LIBOR, and inflation were meaningful variables. In the Tanker segment, unlike Bulk carrier, only size and age were useful variables. This study performed regression analyses for various sizes of Bulk carriers and Oil tankers. It verified that impacts of variables other than ship size and age were significantly associated with ship type and size while macroeconomic variables had no influence except for bulk carriers. By applying diverse variables affecting secondhand ship price estimation according to various sizes of Bulk carriers and Oil tankers, this study will expand the scope of practical application for investors. It also reaffirms prior research findings that the secondhand ship market is primarily market-driven.

• Journal of Korea Trade
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• v.23 no.7
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• pp.113-127
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• 2019

Purpose - This paper investigates whether financial crises could be the indicators of capital outflow waves or vice versa in Korea. Korea has experienced two severe financial crises, which are the Asian Crisis and the global financial crisis. Although there were many variables associated with these two remarkable events, one notable variable was gross capital outflows, which had significantly increased around them. Motivated by existing literature which built theoretical frameworks explaining the relationship between capital flight and financial crises, we examine the empirical evidence for this relationship. Design/methodology - We use panel data from 61 countries including Korea from 1980 to 2009 to study the associations between capital flight and diverse financial crises such as banking, currency, debt, and inflation crises. To be specific, we use the complementary log-log model to see whether capital outflow waves are reliable indicators for domestic financial crises. Findings - The results show, first, that banking, currency, and inflation crises are associated with capital flight. Second, debt crises are also associated with capital flight, but the result is not robust to different specifications. And, third, the positive associations between capital flight and crises are mainly driven by banking flows rather than FDI and portfolio flows. Originality/value - This paper is one of a few studies that investigates domestic (not foreign) investors' behavior during financial turmoil. Furthermore, theoretical studies which provide contradictory explanations on the movements of gross capital outflows during financial crises emphasizes the importance of empirical evidence in this paper.

• Journal of the Korea Computer Graphics Society
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• v.28 no.3
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• pp.13-21
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• 2022

In this paper, the goal is to investigate how manipulating the camera can minimize motion sickness and maximize immersion when a user moves in a virtual environment that requires vertical movement. In general, since a user uses virtual reality in a flat space, the actual movement of the user and the virtual movement are different, resulting in sensory conflict, which has the possibility of causing virtual reality motion sickness. Therefore, we propose three powerful camera manipulation techniques, implement them, and then propose which model is most appropriate through user experiments.

• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.76-85
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• 2022

One of the most fundamental challenges when designing controllers for dynamic systems is the adjustment of controller parameters. Usually the system model is used to get the initial controller, but eventually the controller parameters must be manually adjusted in the real system to achieve the best performance. To avoid this manual tuning step, data-driven methods such as machine learning were used. Recently, reinforcement learning became one alternative of this problem to be considered as an agent learns policies in large state space with trial-and-error Markov Decision Process (MDP) which is widely used in the field of robotics. However, on initial training step, as an agent tries to explore to the new state space with random action and acts directly on the controller parameters in real systems, MDP can lead the system safety-critical system failures. Therefore, the issue of 'safe exploration' became important. In this paper we meet 'safe exploration' condition with Control Barrier Function (CBF) which converts direct constraints on the state space to the implicit constraint of the control inputs. Given an initial low-performance controller, it automatically optimizes the parameters of the control law while ensuring safety by the CBF so that the agent can learn how to predict and control unknown and often stochastic environments. Simulation results on a quadrotor UAV indicate that the proposed method can safely optimize controller parameters quickly and automatically.

• Microbiology and Biotechnology Letters
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• v.51 no.1
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• pp.69-82
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• 2023

Nitrilases are a hydrolase group of enzymes that catalyzes nitrile compounds and produce industrially important organic acids. The current objective is to optimize nitrilase production using statistical methods assisted with artificial intelligence (AI) tool from novel nitrile degrading isolate. A nitrile hydrolyzing bacteria Bacillus subtilis AGAB-2 (GenBank Ascension number- MW857547) was isolated from industrial effluent waste through an enrichment culture technique. The culture conditions were optimized by creating an orthogonal design with 7 variables to investigate the effect of the significant factors on nitrilase activity. On the basis of obtained data, an AI-driven support vector machine was used for the fitted regression, which yielded new sets of predicted responses with zero mean error and reduced root mean square error. The results of the above global optimization were regarded as the theoretical optimal function conditions. Nitrilase activity of 9832 ± 15.3 U/ml was obtained under optimized conditions, which is a 5.3-fold increase in compared to unoptimized (1822 ± 18.42 U/ml). The statistical optimization method involving Plackett Burman Design and Response surface methodology in combination with an AI tool created a better response prediction model with a significant improvement in enzyme production.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.4
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• pp.666-683
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• 2023

This research aims to develop based clothing design process tailored to the industry-university collaborative setting and apply it in a fashion design class. into three distinct phases: designing and organizing our fashion design class, conducting our class at a university, and gathering student feedback. First, we conducted a literature review on employing new technologies in traditional clothing design processes. We consulted with industry professionals from the Samsung C&T Fashion Group to develop an AI-based clothing design process. We then developed in-class learning activities that leveraged fashion brand product databases, a supervised learning AI model, and operating an AI-based Creativity Support Tool (CST). Next, we setup an industry-university fashion design class at a university in South Korea. Finally, we obtained feedback from undergraduate students who participated in the class. The survey results showed a satisfaction level of 4.7 out of 5. The evaluations confirmed that the instructional methods, communication, faculty, and student interactions within the class were both adequate and appropriate. These research findings highlighted that our AI-based clothing design process applied within the fashion design class led to valuable data-driven convergent thinking and technical experience beyond that of traditional clothing design processes.

• Journal of the Korean Society of Clothing and Textiles
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• v.48 no.1
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• pp.108-119
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• 2024

In this study, we aimed to propose enhancements to the dimensions and design of walking aids tailored for elderly women. Specifically, we focused on wheeled walking assistance devices and aligned each structural component with the appropriate human body dimensions to suggest appropriate product dimensions organized by size clusters, aiming to maximize the practicality of the results. We extracted essential factors required for product design, including human body size elements. The dimension extraction method was clustered to establish connections between key human body parameters-such as height, weight, and age groups-and product dimensions. We conducted a comparative analysis of walking aid product dimensions according to the design elements and sizes of models currently available in the market. The outcomes of this study offer objective, data-driven insights into areas where existing models on the market could benefit from improvement and we anticipate that the findings of this study will provide a solid, quantitative foundation for individuals when selecting the most suitable model for their needs.

• ETRI Journal
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• v.46 no.1
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• pp.127-136
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• 2024

The Korean language has written (formal) and spoken (phonetic) forms that differ in their application, which can lead to confusion, especially when dealing with numbers and embedded Western words and phrases. This fact makes it difficult to automate Korean speech recognition models due to the need for a complete transcription training dataset. Because such datasets are frequently constructed using broadcast audio and their accompanying transcriptions, they do not follow a discrete rule-based matching pattern. Furthermore, these mismatches are exacerbated over time due to changing tacit policies. To mitigate this problem, we introduce a data-driven Korean spoken-to-written transcription conversion technique that enhances the automatic conversion of numbers and Western phrases to improve automatic translation model performance.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.32 no.2
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• pp.82-99
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• 2024

The aim of this study is to propose strategies for in-flight OTT services by examining differences in binge-watching patterns through online video streaming services based on age. Additionally, it investigates how the moderating effects of need for cognition and critical media literacy influence the relationship between age and binge-watching. Data from the 2020 Korean Media Panel Survey conducted by the Korea Information Society Development Institute were utilized, with moderating effects analyzed using Process Macro Model 1. Results indicate that as age increases, the frequency of binge-watching content rises while the duration decreases. Moreover, moderating effects of need for cognition and critical media literacy in the age-binge-watching relationship were confirmed. This study analyzed binge-watching behaviors among online video streaming service users, confirming the influence of age, binge-watching habits, need for cognition, and critical media literacy. Theoretical and practical implications include insights for in-flight service providers, content marketers, and online video streaming service operators.

• Journal of Digital Convergence
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• v.13 no.8
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• pp.321-329
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• 2015

This study investigates effects of hardware and telecommunication and software service divided by ICT service on each 5 transportations to explore convergence of ICT and Transportation. Research models are production inducing effects, Added Value inducing effects of Demand-Driven model and Shortage cost effects of Supply-Driven model by using data for 2010~2012 of Input-Output Table. Results are that network and software service effects are more impact than hardware effects on transportations. Especially, hardware is impacted heavily on production inducing effect, telecommunications and software services has had a significant impact on the production inducing effect and Shortage cost effects. In addition, by each detail the transportation industries, packages and other transport and road transport is influenced greatly from ICT. On the other hand, rail and water transport are relatively lower impact by ICT, However, the effects of rail and water transport by ICT is grater than investment ratio of ICT. As a result, increasing investment in the ICT services could contribute to development of rail and water transport development.