• Journal of Korea Port Economic Association
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• v.25 no.3
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• pp.67-92
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• 2009

A tugboat (tug) is a boat that maneuvers vessels by pushing or towing them. Tugs move vessels that should not move themselves alone, such as ships in a crowded harbor or a narrow canal, or those that cannot move themselves, such as barges, disabled ships, or oil platforms. Tugboats are powerful for their size and strongly built, some are ocean-going. Historically tugboats were the first seagoing vessels to receive steam propulsion, freedom from the restraint of the wind, and capability of going in any direction. As such, they were employed in harbors to assist ships in docking and departure. Towage is in essence a service by one vessel to another vessel for a fixed remuneration. The most common reason for requiring this service is the lack of its own motive power. Conventionally, towage is defined as "the employment of one vessel to expedite the voyage of another, when nothing more is required than the accelerating of her progress". Apart from accelerating vessels, acquiring towage service is a common practice for towing barges, platform of drilling oil, floating ship yards, etc.

• Journal of Navigation and Port Research
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• v.45 no.6
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• pp.276-283
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• 2021

The capital structure of the shipping business, which is characterized by its capital intensity and extreme market volatility, is closely related to long-term stability. Research in this area has been conducted mostly in the form of deriving the determinants of capital structure from company-wise financial ratios. This research, on the other hand, has a different approach to the topic. It identifies the relationship between actual cash profit and loss and other variables - i.e. actual vessel prices, interest rates and leverage ratio - by employing historical simulation. The result demonstrates that the P anamax cash profit shows 0 (break-even point) when the debt weight reaches 64.38% (debt ratio 180.74%) and the Cape, 73.04% (debt ratio 270.92%). Additionally, the ships of different types show a divided pattern for the pre- and post-'Super Boom'. It indicates that the business area and the market cycle should be considered when a leverage strategy is established. This research benefits shipping companies set a rational leverage strategy as well as delivers a reasonable guideline to government authorities for the development of a sound policy on shipping finance.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.79-92
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• 2019

This study analyzes the effects of freight transportation income, capital, asset, non-operating expenses, and debt ratio on the debts of inner port freight transportation businesses through the GLS of panel regression analysis and the estimation of fixed effects model. The factors and hypotheses were established through a theoretical background review, and the financial statement and profit and loss data of inner port freight transportation businesses for 10 years from 2006 to 2015 were analyzed. The results showed that assets had positive effects on debts, and negative effects on capital, non-operating expenses, and debt ratio, but no effect on freight transportation income. This result empirically demonstrates the tendency of inner port freight transportation businesses to secure assets by increasing debts, creation of debt reduction leverage effect using non-operating expenses such as interest expenses through bank borrowing, and the adoption of management characteristics and financial operation method to lower the debt ratio by reducing capital more than debts. In future studies, it is necessary to analyze coastal port freight transportation business by industry (oil tankers, cargo ships, and barge ships), and regions such as East, West and South sea.

• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.1-6
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• 2019

Neural networks have been used to predict the direction of stock index movement from past data. The conventional research that predicts the upward or downward movement of the stock index predicts a rise or fall even with small changes in the index. It is highly likely that losses will occur when trading ETFs by use of the prediction. In this paper, a neural network model that predicts the movement direction of the daily KOrea composite Stock Price Index (KOSPI) to reduce ETF trading losses and earn more than a certain amount per trading is presented. The proposed model has outputs that represent rising (change rate in index ${\geq}{\alpha}$), falling (change rate ${\leq}-{\alpha}$) and neutral ($-{\alpha}$ change rate < ${\alpha}$). If the forecast is rising, buy the Leveraged Exchange Traded Fund (ETF); if it is falling, buy the inverse ETF. The hit ratio (HR) of PNN1 implemented in this paper is 0.720 and 0.616 in the learning and the evaluation respectively. ETF trading yields a yield of 8.386 to 16.324 %. The proposed models show the better ETF trading success rate and yield than the neural network models predicting KOSPI.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.7-18
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• 2021

Recently, various connected industrial parks (CIPs) architectures using new technologies such as cloud computing, CPS, big data, fifth-generation mobile communication 5G, IIoT, VR-AR, and ventilation transportation AI algorithms have been proposed in Korea. Korea's small and medium-sized enterprises do not have the upper hand in technological competitiveness than overseas advanced countries such as the United States, Europe and Japan. For this reason, Korea's small and medium-sized enterprises have to invest a lot of money in technology research and development. As a latecomer, Korean SMEs need to improve their profitability in order to find sustainable growth potential. Financially, it is most efficient for small and medium-sized Korean companies to cut costs to increase their profitability. This paper made profitability improvement by reducing costs for small and medium-sized enterprises located in CIPs in Korea a major task. VJP (Vehicle Action Program) was noted as a way to reduce costs for small and medium-sized enterprises located in CIPs in Korea. The method of achieving minimum logistics costs for small businesses through the Korean CIPs payment system was analyzed. The details of the new Korean CIPs payment system were largely divided into four types: "Business", "Data", "Technique", and "Finance". Cost Benefit Analysis (CBA) was used as a performance analysis method for CIPs payment systems.

• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.9-16
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• 2021

In the past, there have been various studies on predicting the stock market by machine learning techniques using stock price data and financial big data. As stock index ETFs that can be traded through HTS and MTS are created, research on predicting stock indices has recently attracted attention. In this paper, machine learning models for KOSPI's up and down predictions are implemented separately. These models are optimized through a grid search of their control parameters. In addition, a hybrid machine learning model that combines individual models is proposed to improve the precision and increase the ETF trading return. The performance of the predictiion models is evaluated by the accuracy and the precision that determines the ETF trading return. The accuracy and precision of the hybrid up prediction model are 72.1 % and 63.8 %, and those of the down prediction model are 79.8% and 64.3%. The precision of the hybrid down prediction model is improved by at least 14.3 % and at most 20.5 %. The hybrid up and down prediction models show an ETF trading return of 10.49%, and 25.91%, respectively. Trading inverse×2 and leverage ETF can increase the return by 1.5 to 2 times. Further research on a down prediction machine learning model is expected to increase the rate of return.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.25-30
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• 2022

This study is a study on the filter bubble reinforcement phenomenon of SNS recommendation algorithm such as YouTube, which is a characteristic of the Russian-Ukraine war (2022), and the victory or defeat factors of the hybrid war. This war is identified as a hybrid war, and the use of New Media based on the SNS recommendation algorithm is emerging as a factor that determines the outcome of the war beyond political leverage. For this reason, the filter bubble phenomenon goes beyond the dictionary meaning of confirmation bias that limits information exposed to viewers. A YouTube video of Ukrainian President Zelensky encouraging protests in Kyiv garnered 7.02 million views, but Putin's speech only 800,000, which is a evidence that his speech was not exposed to the recommendation algorithm. The war of these SNS recommendation algorithms tends to develop into an algorithm war between the US (YouTube, Twitter, Facebook) and China (TikTok) big tech companies. Influenced by US companies, Ukraine is now able to receive international support, and in Russia, under the influence of Chinese companies, Putin's approval rating is over 80%, resulting in conflicting results. Since this algorithmic empowerment is based on the confirmation bias of public opinion by 'filter bubble', the justification that a new guideline setting for this distortion phenomenon should be presented shortly is drawing attention through this Russia-Ukraine war.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.105-115
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• 2022

This study aims to investigate the Effect of Money Rush on Entrepreneurial Opportunity Recognition for college students in Busan and Gyeongnam area. We also examine whether Entrepreneurship has a mediating effect between Money Rush and Entrepreneurial Opportunity Recognition. Since the outbreak of COVID-19, digital transformation of the industry have greatly changed the world of work, and job insecurity is becoming more prevalent. As income inequality expands due to the disparity in asset income, the Money Rush phenomenon, which prefers to increase asset income through investment rather than earned income, is becoming common. Money Rush secures an income pipeline and is divided into side hustles and investments that actively utilize Leverage to maximize profits. The findings of this study confirm that Money Rush has a positive effect on Entrepreneurial Opportunity Recognition and a partially positive effect on Entrepreneurship. Entrepreneurship has a partial mediating effect between Money Rush and Entrepreneurial Opportunity Recognition. The study analysis is expected to contribute to strengthening college students' competencies in Entrepreneurial Opportunity Recognition and presenting the policy and practical directions necessary to promote Start-up.

• Journal of Dental Rehabilitation and Applied Science
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• v.40 no.2
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• pp.91-99
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• 2024

In the case of skeletal class III edentulous patients, the stability of dentures can be achieved by using a crossbite by considering the residual ridge relationship when fabricating complete dentures. Forming the anterior teeth in a normal occlusal relationship in a skeletal class III ridge relationship may reduce the stability of the denture by increasing the anterior cantilever. However, when patients use complete dentures, not only functional aspects but also aesthetic aspects are important. The aesthetics of complete dentures depends on how the anterior artificial teeth are arranged, and cases of complete denture fabrication using normal occlusion or edge-to-edge bite in edentulous patients with skeletal class III ridge relationships have been reported. In this case, complete dentures were fabricated for an edentulous patient with a skeletal class III edentulous patients by forming anterior edge-to-edge bite considering neutral zone in maxillary anterior teeth, and good aesthetic and functional results were obtained.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.5 no.4
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• pp.1-34
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• 2010

Recently, failure rates of Kosdaq IPO firms are increasing and their survival rates tend to be very low, and when these firms do fail, often times backed by a number of governmental financial supports, they may inflict severe financial damage to investors, let alone economy as a whole. To ensure investors' confidence in Kosdaq and foster promising and healthy businesses, it is necessary to precisely assess their intrinsic values and survivability. This study investigates what contributed to the failure of IPO firms and analyzed how these elements are factored into corresponding firms' stock returns. Failure risks are assessed at the time of IPO. This paper considers factors reflecting IPO characteristics, a firm's underwriter prestige, auditor's quality, IPO offer price, firm's age, and IPO proceeds. The study further went on to examine how, if at all, these failure risks involved during IPO led to post-IPO stock prices. Sample firms used in this study include 98 Kosdaq firms that have failed and 569 healthy firms that are classified into the same business categories, and Logit models are used in estimate the probability of failure. Empirical results indicate that auditor's quality, IPO offer price, firm's age, and IPO proceeds shown significant relevance to failure risks at the time of IPO. Of other variables, firm's size and ROA, previously deemed significantly related to failure risks, in fact do not show significant relevance to those risks, whereas financial leverage does. This illustrates the efficacy of a model that appropriately reflects the attributes of IPO firms. Also, even though R&D expenditures were believed to be value relevant by previous studies, this study reveals that R&D is not a significant factor related to failure risks. In examing the relation between failure risks and stock prices, this study finds that failure risks are negatively related to 1 or 2 year size-adjusted abnormal returns after IPO. The results of this study may provide useful knowledge for government regulatory officials in contemplating pertinent policy and for credit analysts in their proper evaluation of a firm's credit standing.