• Journal of Navigation and Port Research
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• v.45 no.3
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• pp.173-180
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• 2021

Although accounting is one of the core fields of corporate management, few studies have reported accounting phenomena involving shipping companies. In addition, although financial reporting is very important to shipping companies that use several financial tools such as ship finance and financial lease, it is difficult to identify studies investigating shipping companies' financial reporting, especially their earnings management. The purpose of this study is to analyze accrual earnings management behavior of shipping companies. Companies with high debt ratios and net losses are known to have incentives for earnings management. Due to the nature of the industry, shipping companies have a high debt ratio and often report net losses. Accordingly, shipping companies are expected to engage in substantial earnings management. Based on the analysis of KOSP I companies listed on the Korea Exchange from 2001 to 2020, it was found that shipping companies are engaged in higher levels of earnings management than non-shipping companies. Discretionary accrual was used as a proxy variable for earnings management. Discretionary accrual was measured using the modified Jones model of Dechow et al. (1995) and the performance matched model of Kothari et al.(2005). In this study, significant results were derived by comparatively analyzing the earnings management practices, which is one of the major accounting behaviors of shipping and non-shipping companies. Stakeholders such as external auditors, investors, financial institutions, analysts, and government authorities need to be aware of the earnings management behavior of listed shipping companies during their external audit, financial analysis, and supervision. Finally, listed shipping companies must conduct stricter accounting based on accounting principles.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.539-545
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• 2018

In recent years, research on shipping market forecasting with the employment of non-linear AI models has attracted significant interest. In previous studies, input variables were selected with reference to past papers or by relying on the intuitions of the researchers. This paper attempts to address this issue by applying the stepwise regression model and the random forest model to the Cape-size bulk carrier market. The Cape market was selected due to the simplicity of its supply and demand structure. The preliminary selection of the determinants resulted in 16 variables. In the next stage, 8 features from the stepwise regression model and 10 features from the random forest model were screened as important determinants. The chosen variables were used to test both models. Based on the analysis of the models, it was observed that the random forest model outperforms the stepwise regression model. This research is significant because it provides a scientific basis which can be used to find the determinants in shipping market forecasting, and utilize a machine-learning model in the process. The results of this research can be used to enhance the decisions of chartering desks by offering a guideline for market analysis.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.546-554
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• 2018

The Bulk market, unlike the line market, is characterized by stiff competition where certain ship or freight owners have no influence on freight rates. However, freights are subject to macroeconomic variables and economic external shock which should be considered in determining management or chartering decisions. According to the results analyzed by use of ARIMA Inventiom model, the impact of the financial crisis was found to have a very strong bearing on the BDI index. First, according to the results of the VEC model, the libor rate affects the BDI index negatively (-) while exchange rate affects the BDI index by positively (+). Secondly, according to the results of the VEC model's J ohanson test, the order ship volume affects the BDI index by negatively (-) while China's economic growth rate affects the BDI index by positively (+). This shows that the shipping company has moved away from the simple carrier and responded appropriately to changes in macroeconomic variables (economic fluctuations, interest rates and exchange rates). It is believed that the shipping companies should be more aggressive in its "trading" management strategy in order to prevent any unfortunate situation such as the Hanjin Shipping incident.

• The Journal of Korean Institute of Information Technology
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• v.16 no.11
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• pp.51-59
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• 2018

The Multi-Mission Unmanned Surface Vehicle(MMUSV), which is manufactured using glass Fiber Reinforced Plastic(FRP) material, is designed to perform a surveillance and reconnaissance on the sea. Various navigation sensors, such as RADAR, RIDAR, camera, are mounted on a mast to perform an autonomous navigation. And a dummy gun is mounted on the deck of the MMUSV for a target tracking and disposal. It is necessary to analyze a strength for structures mounted on the deck because the MMUSV performs missions under a severe sea state. In this paper, a strength analysis of the mast structure is performed on static loads and lateral external loads to verify an adequacy of the designed mast through a series of simulations. Based on the results of captive model tests, a strength analysis for a heave motion of the mast structure is conducted using a simulation tool. Also a simulation and fatigue test for a mounting part between the MMUSV and the dummy gun are performed using a specimen. The simulation and test results are represented that a structure of the mast and mounting part of the dummy gun are appropriately designed.he impact amount are performed through simulation and experiments.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.64-71
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• 2019

It is very important to understand the mechanism of estuary topographic changes for the study of estuary management and treatment methods. In this study, the effects from the land-side, such as rainfall, river discharge, sediment discharge, and sea side, such as tide, tidal current, wave and surface sediments related to the topographic changes of the Nakdong river estuary were investigated and analyzed. Based on the analyzed data, topographic modeling was performed to analyze the topographic change and contribution of external force conditions. As a result of numerical modeling, the topographic change showed that erosion that predominates in the water directly affected by the discharge of the estuary barrage. The deposition predominates in the indirectly affected tideland. As sediments moved along the water way being sorted and distributed by the wave, the deposition predominated in the front of the barrier island. Compared with the deposition dominance, which is the result of the topographic change prediction, the impact of each external force condition gives larger erosion. However, the combined impact of each external force condition showed deposition dominant. Therefore, the topographic changes of the Nakdong river estuary are considered to be the result of various complex external factors. The impacts of each external force condition show the different contribution to each comparison area. These results should be considered when establishing the estuary management method. It must be understood that this is the result of complex interactions.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.280-288
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• 2022

This study examined the diagnostics of abnormalities and faults of equipment, whose rotational speed changes even during regular operation. The purpose of this study was to suggest a procedure that can properly apply machine learning to the time series data, comprising non-stationary characteristics as the rotational speed changes. Anomaly and fault diagnosis was performed using machine learning: k-Nearest Neighbor (k-NN), Support Vector Machine (SVM), and Random Forest. To compare the diagnostic accuracy, an autoencoder was used for anomaly detection and a convolution based Conv1D was additionally used for fault diagnosis. Feature vectors comprising statistical and frequency attributes were extracted, and normalization & dimensional reduction were applied to the extracted feature vectors. Changes in the diagnostic accuracy of machine learning according to feature selection, normalization, and dimensional reduction are explained. The hyperparameter optimization process and the layered structure are also described for each algorithm. Finally, results show that machine learning can accurately diagnose the failure of a variable-rotation machine under the appropriate feature treatment, although the convolution algorithms have been widely applied to the considered problem.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.567-576
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• 2022

Seafarers are exposed to various unpredictable maritime risks due to the spatial specificity of the working environment of the sea; thus, sufficient compensation for injured crewmembers is needed. However, Korea does not provide such compensation. Therefore, this study attempted to examine the Maritime Labor Act and the Industrial Accident Insurance Act of Germany, an advanced European social insurance country, and derive implications compared to Korea. First, we investigated how compensations are managed by a public institution in Germany and by shipowners in Korea. Second, regarding the contents of accident compensation, Germany does not only provide continuous treatment and care through various support systems, but also operates various programs to enable a return to ship work. In contrast, Korea has a temporary compensation system that allows shipowners to avoid liability for accident compensation, which is disadvantageous to shipwrecked seafarers. Finally, in Germany, workers' compensation insurance is public, judged considering the origin of work, whereas in Korea, it is determined by shipowners or insurance companies. Therefore, it is necessary to establish a public institution in charge of crew accident compensation to ensure proper compensation for crewmembers in Korea and to improve the Seafarers Act or system to provide compensation for additional medical care, disability pension, and rehabilitation benefits.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.209-215
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• 2022

On the Jeju coast, international cruise ships, passenger ships, and other ships pass frequently, as well as many fishing boats. Thus, there is a high risk of marine accidents and frequent ship collisions. Accordingly, it is urgent to establish a coastal VTS for systematic safety management of ships passing through the coastal waters of Jeju. The purpose of this study was to set the area of the VTS to be newly established. In this study, to calculate the workload of the VTS operators, a formula was proposed that reflects the monitoring workload considering the monitoring frequency and required time for target as well as non-target ships and the workload for ship collision situations. The proposed formula was applied to the newly established VTS area in Jeju. Three control sectors were set up in each VTS center. The average number of workstations per hour was approximately 1, so the division between sectors was appropriate. Thus, it was deduced that there would be no workload for the VTS operators. It is expected that the method proposed in this study can be used as primary data for calculating the appropriate number of workstations for the current VTS, and setting the VTS area for a new coastal VTS in the future.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.266-274
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• 2021

Ship officers are subject to excessive job stress, which has negative physical and psychological impacts and may adversely affect the smooth supply and demand of human resources. In this study, a mobile web application was developed as a tool for systematic job stress measurement and management of officers and verified through quality evaluation. Requirement analysis was performed by ship officers and staff in charge of human resources of shipping companies, and the results were reflected in the application configuration step. The application was designed according to the waterfall model, which is a traditional software development method, and functions were implemented using JSP and Spring Framework. Performance evaluation on the user interface, confirmed that proper input and output results were implemented, and the respondent results and the database were configured in the administrator interface. The results of evaluation questionnaires for quality evaluation of the interface based on ISO/IEC 9126-2 metric were significant 4.60 for the user interface and 4.65 for the administrator interface in a 5-point scale. In the future, it is necessary to conduct follow-up research on the development of data analysis system through utilization of the collected big-data sets.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.367-374
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• 2022

The purpose of this study was to propose a deep learning algorithm that applies to the fault diagnosis of fuel pumps and purifiers of autonomous ships. A deep learning algorithm reflecting the time dependence of the measured signal was configured, and the failure pattern was trained using the vibration signal, measured in the equipment's regular operation and failure state. Considering the sequential time-dependence of deterioration implied in the vibration signal, this study adopts Conv1D with sliding window computation for fault detection. The time dependence was also reflected, by transferring the measured signal from two-dimensional to three-dimensional. Additionally, the optimal values of the hyper-parameters of the Conv1D model were determined, using the grid search technique. Finally, the results show that the proposed data preprocessing method as well as the Conv1D model, can reflect the sequential dependency between the fault and its effect on the measured signal, and appropriately perform anomaly as well as failure detection, of the equipment chosen for application.