• Composites Research
• /
• v.37 no.2
• /
• pp.101-107
• /
• 2024

Demand for submarine cable is increasing due to advances in submarine power transmission technology and submarine cable manufacturing technology. Submarine cable use various types of protective equipment to prevent problems such as high maintenance costs in the event of cable damage and power outages during maintenance periods. Among them, flexible protection tube is a representative protective equipment to protect cables and respond to external forces such as waves and current. The flexible protection tube is made of polyurethane 85A hyperelastic material, so the calculation of mechanical behavior is carried out using mechanical properties based on experimental results. In this study, a study was conducted to determine the bending performance and tensile performance of flexible protection tube through analytical methods. The physical properties obtained through the multiaxial tensile test of polyurethane 85A were used for the analysis. Bending and tensile performance were determined for the maximum bending moment standard of 15 kN·m and the tensile load standard of 50 kN. As a result, it was confirmed that when the maximum bending moment of 15 kN·m of the flexible protection tube occurred, the bending performance of the MBR was secured at 13 m and when a tensile load of 50 kN, it was applied the maximum vertical displacement was 968 mm, confirming that the tensile performance was secured.

• Analyses & Alternatives
• /
• v.8 no.2
• /
• pp.87-115
• /
• 2024

This study examines the effect of R&D investment on firm performance and value of Chinese private firms. Through R&D investment, firms aim to acquire knowledge and technological resources to create innovation and competitive advantage, which ultimately enhances firm performance and value. However, unlike other investments, R&D investments are characterized by high adjustment costs and risks, uncertainty and asymmetric information. In addition, the effect of R&D investment on firm performance and value has been shown to be mixed results due to various internal and external contextual factors. Therefore, this study intends to consider how the ESG activities of firms, which have recently attracted attention, act as a contextual factor in the results of R&D investment. This is because interaction with stakeholders through ESG activities is considered to be an important factor in securing competitive advantages and sustainable growth. In this context, this study measures the effect of a firm's R&D investment on its business performance by dividing it into financial performance and value, respectively, and examines the moderating effect of ESG score on the relationship. Based on empirical analysis of all Chinese private firms from 2010 to 2019, the results show that a firm's R&D investment has a negative impact on performance and a positive impact on value. Furthermore, a high ESG score of private firms positively moderates each relationship, emphasizing the importance of ESG activities.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.34 no.4
• /
• pp.763-780
• /
• 2024

As the domestic and international landscape undergoes rapid changes, the importance of implementing security measures in response to the growing threats that businesses face is increasing. In this context, the need for Security by Design (SbD), integrating security from the early design stages, is becoming more pronounced, with threat modeling recognized as a fundamental tool of SbD. Particularly, to save costs and time by detecting and resolving security issues early, the application of the Shift Left strategy requires the involvement of personnel with limited security expertise, such as software developers, in threat modeling. Although various automated threat modeling tools have been released, their lack of user-friendliness for personnel lacking security expertise poses challenges in conducting threat modeling effectively. To address this, we conducted an analysis of research related to threat modeling tools and derived usability evaluation criteria based on the GQM(Goal-Question-Metric) approach. An expert survey was conducted to validate both the validity and objectivity of the derived criteria. We performed usability evaluations of three threat modeling tools (MS TMT, SPARTA, PyTM), and the evaluation results led to the conclusion that MS TMT exhibited superior usability compared to other tools. This study aims to contribute to the creation of an environment where personnel with limited security expertise can effectively conduct threat modeling by proposing usability evaluation criteria.

• Journal of the Korean Society for Heat Treatment
• /
• v.37 no.4
• /
• pp.163-171
• /
• 2024

SCR420H steel is a low-carbon chromium alloy steel designed for carburizing heat treatment. Recently, research is being conducted on high-temperature carburization heat treatment to reduce costs and CO₂ emissions by shortening the carburization time to meet the international carbon neutral policy. However, this high-temperature carburization heat treatment coarsens the steel grains and causes a decrease in mechanical properties. In this study, a large amount of Ti was added to increase the grain refinement effect in the high-temperature carburizing process. We investigated the microstructure and precipitates of SCR420H steel without Ti (Al steel) and with Ti (AlTi steel). Thermodynamic calculations showed that the AlN and (Ti,Nb)(C,N) precipitated in Al steel, while (Ti,Nb)(C,N) and Ti₄C₂S₂ precipitated in AlTi steel. Addition of Ti increases the fraction of bainite after reheating process. Transmission electron microscopy analysis shows that small amounts of AlN and (Ti,Nb)(C,N) precipitates are formed in the Al steel. The addition of Ti increases the density of (Ti,Nb)(C,N) precipitates and induces the formation of Ti₄C₂S₂ precipitates, increasing the grain coarsening temperature (GCT) under all heat treatment conditions. Higher reheating temperatures also resulted in higher GCT values due to increased precipitation.

• Korean Journal of Construction Engineering and Management
• /
• v.25 no.4
• /
• pp.34-44
• /
• 2024

In defense and military facility projects, adjustments to contract amounts due to design changes directly or indirectly affect factors such as increased construction costs and extended construction periods. Moreover, they can lead to differences of opinion and conflicts between the military and contracting parties. This case study analyzed the integrated management of defense and military facility projects by the Gyeonggi Southern Facilities Division, which oversees projects in Seoul and the southern Gyeonggi Province region for the Army, Navy, Marine Corps, and Air Force. Out of 388 completed projects, 103 cases with design changes were selected for analysis, aiming to ensure the reliability of data regarding the proportion of design changes in project completion. The study classified samples by the causes of design changes specified in the Ministry of Planning and Finance's contract regulations, assigning rankings based on the occurrence rates of each cause. Furthermore, it analyzed detailed factors for each cause of design change and derived implications to propose improvement measures. Considering the limited access to military primary data, this case study is expected to contribute to minimizing design changes in defense and military facility projects. Additionally, it is anticipated to be practically useful for subsequent research on contract amount adjustments resulting from design changes.

• The Journal of Bigdata
• /
• v.8 no.2
• /
• pp.73-82
• /
• 2023

With 78% of current fisheries workers being elderly, there's a pressing need to address labor shortages. Consequently, active research on smart aquaculture technologies, centered on object detection and tracking algorithms, is underway. These technologies allow for fish size analysis and behavior pattern forecasting, facilitating the development of real-time monitoring and automated systems. Our study utilized video data from cameras outside aquaculture facilities and implemented fish detection and tracking algorithms. We aimed to tackle high maintenance costs due to underwater conditions and camera corrosion from ammonia and pH levels. We evaluated the performance of a real-time system using YOLOv7 for fish detection and the SORT algorithm for movement tracking. YOLOv7 results demonstrated a trade-off between Recall and Precision, minimizing false detections from lighting, water currents, and shadows. Effective tracking was ascertained through re-identification. This research holds promise for enhancing smart aquaculture's operational efficiency and improving fishery facility management.

• Journal of Korea Port Economic Association
• /
• v.39 no.4
• /
• pp.127-145
• /
• 2023

As the importance of strengthening port security is increasing, it is necessary to conduct a perceptual study on port facility users who pay for port security services first. This study aims to identify improvements in the port security function of Busan Port and contribute to the future development of port security in Korea. A total of 125 questionnaires were collected from port facility security fee collectors at Busan Port. Based on the collected data, exploratory factor analysis, traditional IPA, and modified IPA were conducted. In conclusion, first, the physical function of port security is the most important and should be continuously maintained and strengthened. Second, improving the professionalism of port security personnel is most urgent, and the port security education system needs to be improved. Finally, it is necessary to gradually develop the port security information service function in consideration of future development possibilities.

• Journal of Korea Port Economic Association
• /
• v.39 no.4
• /
• pp.243-254
• /
• 2023

This study investigates the factors contributing to price fluctuations in the shipscrapping market, the final stage in a vessel's life cycle. Shipping companies make decisions on ship dismantling based on factors such as declining freight rates, increasing vessel age leading to higher costs, or compliance with new environmental regulations. Utilizing the FMOLS (Fully Modified Ordinary Least Squares) and VECM (Vector Error Correction Model) methodologies, the research explores the long-term elasticities of factors influencing shipscrapping prices and examines short-term causal relationships. Using a time series dataset spanning from December 2015 to April 2023, covering a total of 90 months, the study focuses on the shipscrapping prices of Capesize vessels in India and Bangladesh, which constitute a significant portion of the shipbreaking market. The findings indicate that, in the long term, shipscrapping prices are closely related to global scrap prices, 20-year-old secondhand Capesize vessel prices, newbuilding prices, and exchange rates. In terms of short-term causal relationships, an increase in global scrap prices induces a rise in shipscrapping prices, while the remaining variables do not contribute to such increases. Specifically, an escalation in shipscrapping prices is associated with increased prices of 20-year-old secondhand vessels, newbuilding prices, and exchange rates. However, the other variables do not show a significant influence on short-term increases in shipscrapping prices.

• Journal of Intelligence and Information Systems
• /
• v.22 no.1
• /
• pp.139-157
• /
• 2016

Bankruptcy involves considerable costs, so it can have significant effects on a country's economy. Thus, bankruptcy prediction is an important issue. Over the past several decades, many researchers have addressed topics associated with bankruptcy prediction. Early research on bankruptcy prediction employed conventional statistical methods such as univariate analysis, discriminant analysis, multiple regression, and logistic regression. Later on, many studies began utilizing artificial intelligence techniques such as inductive learning, neural networks, and case-based reasoning. Currently, ensemble models are being utilized to enhance the accuracy of bankruptcy prediction. Ensemble classification involves combining multiple classifiers to obtain more accurate predictions than those obtained using individual models. Ensemble learning techniques are known to be very useful for improving the generalization ability of the classifier. Base classifiers in the ensemble must be as accurate and diverse as possible in order to enhance the generalization ability of an ensemble model. Commonly used methods for constructing ensemble classifiers include bagging, boosting, and random subspace. The random subspace method selects a random feature subset for each classifier from the original feature space to diversify the base classifiers of an ensemble. Each ensemble member is trained by a randomly chosen feature subspace from the original feature set, and predictions from each ensemble member are combined by an aggregation method. The k-nearest neighbors (KNN) classifier is robust with respect to variations in the dataset but is very sensitive to changes in the feature space. For this reason, KNN is a good classifier for the random subspace method. The KNN random subspace ensemble model has been shown to be very effective for improving an individual KNN model. The k parameter of KNN base classifiers and selected feature subsets for base classifiers play an important role in determining the performance of the KNN ensemble model. However, few studies have focused on optimizing the k parameter and feature subsets of base classifiers in the ensemble. This study proposed a new ensemble method that improves upon the performance KNN ensemble model by optimizing both k parameters and feature subsets of base classifiers. A genetic algorithm was used to optimize the KNN ensemble model and improve the prediction accuracy of the ensemble model. The proposed model was applied to a bankruptcy prediction problem by using a real dataset from Korean companies. The research data included 1800 externally non-audited firms that filed for bankruptcy (900 cases) or non-bankruptcy (900 cases). Initially, the dataset consisted of 134 financial ratios. Prior to the experiments, 75 financial ratios were selected based on an independent sample t-test of each financial ratio as an input variable and bankruptcy or non-bankruptcy as an output variable. Of these, 24 financial ratios were selected by using a logistic regression backward feature selection method. The complete dataset was separated into two parts: training and validation. The training dataset was further divided into two portions: one for the training model and the other to avoid overfitting. The prediction accuracy against this dataset was used to determine the fitness value in order to avoid overfitting. The validation dataset was used to evaluate the effectiveness of the final model. A 10-fold cross-validation was implemented to compare the performances of the proposed model and other models. To evaluate the effectiveness of the proposed model, the classification accuracy of the proposed model was compared with that of other models. The Q-statistic values and average classification accuracies of base classifiers were investigated. The experimental results showed that the proposed model outperformed other models, such as the single model and random subspace ensemble model.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.9 no.2
• /
• pp.109-116
• /
• 2014

In this study, the factors affecting the profitability of the oriental medicine hospitals of University to be analyzed. To do this, profitability indicators and current ratio, liquidity, turnover ratio, cost factors analysis and suggested ways to improve management. The results are as follows, the operating margin(1.17%). the return on assets(3.76%), the net profit to gross revenues(2.37%), and the net profit to total assets(-1.89) were lower than the average of the entire oriental medicine hospitals in Korea(respectively 8.9%, 8.7%, 2.6%, 2.5%). Current ratio(256.76%), quick ratio(231.17%), fixed ratio(121.02%), and total assets turnover(135.69%) were similar to the average of all oriental medicine hospitals in Korea. But growth rate of total assets(-2.21%), and growth rate of patient revenue(1.89%) is low. And salaries(53.39%), materials costs(16.62%), administrative expenses(28.58%) were different to the average of all oriental medicine hospitals in Korea(respectively 35.3%, 10.7%, 45.1%). Meanwhile, the cost ratio of the oriental medicine hospitals of University was 98.59%. It was 7.49% higher than the 91.1% of the average of all oriental medicine hospitals in 2011. Correlation analysis, growth rate of patient revenue and operating margin increased at the same time, and net profit to gross revenues and net profit to total assets with a growth rate of total assets increased. And administrative expenses and profitability indicators showed a negative correlation. It means, in order to improve the profitability of the oriental medicine hospitals of University should focus on reducing administrative expenses. Multiple regression analysis, growth rate of total assets, total assets turnover, administrative expenses, and salaries has affected the profitability. Therefore, in order to improve the profitability of the oriental medicine hospitals of University to increase the total capital and the total capital turnover, and to reduce administrative expenses effort.