The purpose of this study was to explore the regulations and operational problems of on-board training, and to investigate and analyze the satisfaction level of consignment on-board training among students who completed their training at Korea Maritime & Ocean University. In terms of satisfaction differences by gender, female students generally had a higher relative satisfaction level than male students. The different types of satisfaction in the navigation and engineering categories, the overall practical effect and satisfaction level of the training records shows that the satisfaction level of the trainee is much lower than that of the trainee, so relevant educational institutions and shipping companies need to take measures to improve the satisfaction level of this part. The most important part of the comprehensive company evaluation completed by trainees asked whether they thought the training was equivalent in labor to the employees. Results suggest shipping companies must make a clear distinction between employees and trainees, while establishing relevant internal procedures so that the on-board training process can be carried out in accordance with the purpose of the on-board training consignment.
Journal of the Korea Society of Computer and Information
/
v.27
no.7
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pp.165-175
/
2022
The objective of this study is to identify the relationships among app attribution(perceived usefulness, design, information quality, and mobility), user satisfaction, trust, and continuous use intention of bus information apps; The structural equation of AMOS 21.0 was used to test the hypothesis of this study. The results of the analysis are as follows. First, perceived usefulness, design, information quality, and mobility positively impact user satisfaction. Second, only mobility has a positive effect on trust, but the remaining perceived usefulness, design, and information quality have no effect at the significance level of 5%. Third, user satisfaction has a positive impact on trust and continuous use intention. Fourth, trust has a positive impact on continuous use intention. Therefore, it was confirmed that the characteristics of the bus information mobile app are important influencing factors for the improvement of user satisfaction, trust, and continuous use intention. Local governments and bus companies will be able to establish strategic directions for the activation of bus information mobile apps. The limitation of this study is that it is somewhat lacking in generalizing the study results, so future research needs to focus on improving this part.
Purpose This paper aims to prepare a full operational readiness by establishing an optimal flight plan considering the weather conditions in order to effectively perform the mission and operation of military aircraft. This paper suggests a flight prediction model and rules by analyzing the correlation between flight implementation and cancellation according to weather conditions by using big data collected from historical flight information of military aircraft supplied by Korean manufacturers and meteorological information from the Korea Meteorological Administration. In addition, by deriving flight rules according to weather information, it was possible to discover an efficient flight schedule establishment method in consideration of weather information. Design/methodology/approach This study is an analytic study using data mining techniques based on flight historical data of 44,558 flights of military aircraft accumulated by the Republic of Korea Air Force for a total of 36 months from January 2013 to December 2015 and meteorological information provided by the Korea Meteorological Administration. Four steps were taken to develop optimal flight prediction models and to derive rules for flight implementation and cancellation. First, a total of 10 independent variables and one dependent variable were used to develop the optimal model for flight implementation according to weather condition. Second, optimal flight prediction models were derived using algorithms such as logistics regression, Adaboost, KNN, Random forest and LightGBM, which are data mining techniques. Third, we collected the opinions of military aircraft pilots who have more than 25 years experience and evaluated importance level about independent variables using Python heatmap to develop flight implementation and cancellation rules according to weather conditions. Finally, the decision tree model was constructed, and the flight rules were derived to see how the weather conditions at each airport affect the implementation and cancellation of the flight. Findings Based on historical flight information of military aircraft and weather information of flight zone. We developed flight prediction model using data mining techniques. As a result of optimal flight prediction model development for each airbase, it was confirmed that the LightGBM algorithm had the best prediction rate in terms of recall rate. Each flight rules were checked according to the weather condition, and it was confirmed that precipitation, humidity, and the total cloud had a significant effect on flight cancellation. Whereas, the effect of visibility was found to be relatively insignificant. When a flight schedule was established, the rules will provide some insight to decide flight training more systematically and effectively.
This study is to investigate, using AHP, what technologies should be applied first to Korean SMEs in order to respond to the 4th industrial revolution and change to a smart enterprise. To this end, technologies related to the 4th industrial revolution and smart factory are synthesized, and the classification criteria of Dae-Hoon Kim et al. (2019) are applied, but additional opinions of experts are collected and related technologies are converted to artificial intelligence (AI), Big Data, and Cloud Computing. As a base technology, mobile, Internet of Things (IoT), block chain as hyper-connected technology, unmanned transportation (autonomous driving), robot, 3D printing, drone as a convergence technology, smart manufacturing and logistics, smart healthcare, smart transportation and smart finance were classified as smart industrial technologies. As a result of confirming the priorities for technical use by AHP analysis and calculating the total weight, manufacturing companies have a high ranking in mobile, artificial intelligence (AI), big data, and robots, while service companies are in big data and robots, artificial intelligence (AI), and smart healthcare are ranked high, and in all companies, it is in the order of big data, artificial intelligence (AI), robot, and mobile. Through this study, it was clearly identified which technologies should be applied first in order to respond to the 4th industrial revolution and change to a smart company.
This study analyzed changes in the market concentration of Korean ocean-going shipping companies using shipping revenue based CR (Concentration Ratio), and HHI (Herfindahl - Hirschman Index) to examine the effects of the government's selection and concentration based the shipping reconstruction scheme. The results of this study showed that the market structure of the Korean shipping industry has changed from a competitive market to a rather concentrated market, as CR as well as HHI values have increased from 2019 to 2021. In particular, the market share of the deep-sea shipping lines has risen significantly compared to the intra-Asian short-sea shipping lines and the tramp carriers, implying that the Korean liner shipping market has become a monopoly, or highly concentrated oligopoly market. Compared to other shipping markets, the high rise in ocean freight rates (i.e. Asia-Europe America) was the leading cause of the increase in the revenues of the ocean-going shipping lines, and the increased fleet through preemptive government support has enabled them to achieve more revenues. As a result, it can be interpreted that the government's fleet expansion strategy has been more effective than expected, but it is too early to conclude if the market structure of the Korean ocean-going shipping companies has been strengthened.
Journal of the Korea Society of Computer and Information
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v.27
no.11
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pp.147-155
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2022
In this study, we developed a system to dynamically balance a daily stock portfolio and performed trading simulations using gradient boosting and genetic algorithms. We collected various stock market data from stocks listed on the KOSPI and KOSDAQ markets, including investor-specific transaction data. Subsequently, we indexed the data as a preprocessing step, and used feature engineering to modify and generate variables for training. First, we experimentally compared the performance of three popular gradient boosting algorithms in terms of accuracy, precision, recall, and F1-score, including XGBoost, LightGBM, and CatBoost. Based on the results, in a second experiment, we used a LightGBM model trained on the collected data along with genetic algorithms to predict and select stocks with a high daily probability of profit. We also conducted simulations of trading during the period of the testing data to analyze the performance of the proposed approach compared with the KOSPI and KOSDAQ indices in terms of the CAGR (Compound Annual Growth Rate), MDD (Maximum Draw Down), Sharpe ratio, and volatility. The results showed that the proposed strategies outperformed those employed by the Korean stock market in terms of all performance metrics. Moreover, our proposed LightGBM model with a genetic algorithm exhibited competitive performance in predicting stock price movements.
Journal of Korea Society of Industrial Information Systems
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v.14
no.5
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pp.289-296
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2009
All over the world more and more attention is being paid to green management which enables environment-friendly sustainable development. To keep up with these global trends and in response to the government's "low carbon green growth" policy, many efforts are being made in the port and logistics in order to drastically reduce carbon emissions and save operating expenses. To this end, the engine power source of the cranes in the container terminal is being replaced with electricity from fossil fuel. Among those cranes, especially e-RTGC has been proved to be practical and excellent in its performance through many previous studies. However, no empirical study has yet been made on its introduction effects when e-RTGC has been introduced to the container terminal. In the meantime, however, many domestic container terminals have introduced e-RTGC, and so some data have been accumulated for further research. Under these circumstances, this study has tried to make an empirical study through the case study of D container terminal, checking the restriction factors to be considered at the time of eURTGC introduction, and analyzing its introduction effects and problems. We have high expectations that this study will provide key consideration factors and empirical analysis data to the decision makers who plan to introduce an e-RTGC system, and also will be used as a reference to the development direction of e-RTGC.
The role of drones has been expanded to various fields such as agriculture, construction, and logistics. In particular, agriculture drones are emerging as an effective alternative to solve the problem of labor shortage and reduce the input cost. In this study therefore, we proposed the fruit recognition algorithm and harvesting mechanism for fruit harvesting drone system that can safely harvest fruits at high positions. In the fruit recognition algorithm, we employ "You-Only-Look-Once" which is a deep learning-based object detection algorithm and verify its feasibility by establishing a virtual simulation environment. In addition, we propose the fruit harvesting mechanism which can be operated by a single driving motor. The rotational motion of the motor is converted into a linear motion by the scotch yoke, and the opened gripper moves forward, grips a fruit and rotates it for harvesting. The feasibility of the proposed mechanism is verified by performing Multi-body dynamics analysis.
Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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v.8
no.6
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pp.121-130
/
2018
The purpose of this study is to analyze the effect of partnership type (pre-competitive, competitive, pro - competitive, non - competitive partnership) and national cultural characteristics on partnership performance. In order to analyze this, we conducted questionnaires on companies that have conducted international management and affiliated companies. A total of 223 questionnaires were sent. A total of 121 inquiries were collected from 224 survey requests. Based on this, a structured questionnaire was sent back to the staff members listed in the survey request, and a total of 98 samples were collected. The results of the empirical analysis through the questionnaire showed that the difference between the affiliation type and the national culture had a significant effect on the partnership performance. The results showed that the difference between the affiliation type and the national culture had a significant effect on the partnership performance. This could be a very meaningful implication for companies that are able to achieve successful alliances in a way that enables them to achieve successful alliances.
Franchise system in Korea has been developed in different way compared with American way of franchising based on mutual contract and intellectual property context. Korean franchising is mostly based on product distribution franchise concept rather than business format franchise in which franchisor makes revenue sources from providing their products as much as possible thru group purchasing and logistics rather than receiving royalty. Many franchise enterprises from Korea drive to enter into global franchise market based on the successful performance of Korean way of franchising. Korean enterprises are required to prepare completely for research and survey regarding local culture, custom, way of life and legal matters etc. when entering into global franchise market to gain a substantial performance. CaffeBene recently entered into American franchise business with success, and many other Korean franchise enterprises have a deep interest in proceeding with global franchise business modeling CaffeBene case. There is no Korean franchise enterprise in United Kingdom in which service franchise area in particular with personal service is considered to become a promising and potential franchise business and many people show a great interest in Oriental foods and beverages with well-being trend. Korean franchise enterprises have now access to United Kingdom easier because IT industry including internet of the country have been developed by leaps and bounds since London Olympic in 2012. The purpose of this study is to suggest key success factors and basic strategy such as situation analysis, selecting business format, and marketing strategy for successful launching of franchise business in United Kingdom.
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