• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.171-176
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• 2023

What we have in common worldwide today is economic difficulties due to high inflation and uncertainty in the financial industry. The root cause of this is the war between Russia and Ukraine. The war between Russia and Ukraine is not simply a war between two countries. The United States and the European Union are providing military aid such as missiles to Ukraine, and Russia is attacking Ukraine by introducing UAVs (unmanned aerial vehicles) from Iran. A prominent weapon in this Russia-Ukraine war is the UAVs used in Russia. It is predicted that the form of war using UAVs will gradually expand in the future based on stealth. In addition, UAVs will continue to be used due to the fact that they can cause serious damage to the other country without harming their own lives, and because they have good cost-effectiveness. In this study, UAVs based on autonomous driving were studied. The target countries of the study include the United States, the European Union, China, and Iran, and the UAVs used in these countries have characteristics that can represent the world. In this study, the main specifications of major UAVs in use in major countries were investigated. In addition, the future technology and development direction were described through specifications and characteristics of UAVs currently in operation in major countries.

• Korean Journal of Construction Engineering and Management
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• v.23 no.4
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• pp.3-14
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• 2022

Autonomous equipment requires a large amount of data from various environments. However, it takes a lot of time and cost for an experiment in a real construction sites, which are difficulties in data collection and processing. Therefore, this study aims to develop a virtual environment for autonomous tower cranes technology development and validation. The authors defined automation functions and operation conditions of tower cranes with three performance criteria: operational design domain, object and event detection and response, and minimum functional conditions. Afterward, this study developed a virtual environment for learning and validation for autonomous functions such as recognition, decision making, and control using the Unity game engine. Validation was conducted by construction industry experts with a fidelity which is the representative matrix for virtual environment assessment. Through the virtual environment platform developed in this study, it will be possible to reduce the cost and time for data collection and technology development. Also, it is also expected to contribute to autonomous driving for not only tower cranes but also other construction equipment.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.38-46
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• 2021

In the era of the 4th Industrial Revolution, the interest in autonomous ship technology is increasing as high-tech technologies are being increasingly utilized throughout the industry. Therefore, we conducted a basic study on autonomous ships. In particular, a passenger ship model was produced and an autonomous navigation system was established by applying the ardupilot used for drones. The possibility of automatic control of the autonomous ship operations was confirmed by executing various voyage plans using the built model ship. In the performance test for maintaining the course the model ship could not follow the designated course straight and sailed up to 5.4 m away from the course while navigating in a zigzag (S-shape); however, after the parameters were modified, the deviation distance was reduced to a maximum of 1.8 m. In the turning performance test, the maximum diameter of the turning sphere was found to be approximately 9.3 m, but no significant change could be confirmed even after the parameters were modified. However, the results of our tests on slowing down the ship before arriving at the WP confirmed that the diameter of the turning sphere was reduced to a maximum of approximately 3.2 m. In order to evaluate the stopping performance, the last scheduled stopping position of all experiments was compared with the actual stopping position of the model ship and it was confirmed that the model ship stopped at a point at least 0.4 m and a maximum of 6.2 m away from the stopping position. In the future, improvement of course stability, turning performance, and stopping performance is required through modification and supplementation of various parameters. Moreover, a study on automatic berthing of the model ship through automatic control is planned.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.56 no.4
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• pp.384-394
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• 2020

This paper proposes an outlier detection model based on machine learning that can diagnose the presence or absence of major engine parts through unsupervised learning analysis of main engine big data of a ship. Engine big data of the ship was collected for more than seven months, and expert knowledge and correlation analysis were performed to select features that are closely related to the operation of the main engine. For unsupervised learning analysis, ensemble model wherein many predictive models are strategically combined to increase the model performance, is used for anomaly detection. As a result, the proposed model successfully detected the anomalous engine status from the normal status. To validate our approach, clustering analysis was conducted to find out the different patterns of anomalies the anomalous point. By examining distribution of each cluster, we could successfully find the patterns of anomalies.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1216-1221
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• 2022

Ships tend to be larger to increase the efficiency of cargo transportation. Larger ships lead to increased travel time for ship workers, increased work intensity, and reduced work efficiency. Problems such as increased work intensity are reducing the influx of young people into labor, along with the phenomenon of avoidance of high intensity labor by the younger generation. In addition, the rapid aging of the population and decrease in the young labor force aggravate the labor shortage problem in the maritime industry. To overcome this, the maritime industry has recently introduced technologies such as an intelligent production design platform and a smart production operation management system, and a smart autonomous logistics system in one of these technologies. The smart autonomous logistics system is a technology that delivers various goods using intelligent mobile robots, and enables the robot to drive itself by using sensors such as lidar and camera. Therefore, in this paper, it was checked whether the mobile robot could autonomously drive to the stop sign by detecting the passage way of the ship deck. The autonomous driving was performed by detecting the passage way of the ship deck through the camera mounted on the mobile robot based on the data learned through Nvidia's End-to-end learning. The mobile robot was stopped by checking the stop sign using SSD MobileNetV2. The experiment was repeated five times in which the mobile robot autonomously drives to the stop sign without deviation from the ship deck passage way at a distance of about 70m. As a result of the experiment, it was confirmed that the mobile robot was driven without deviation from passage way. If the smart autonomous logistics system to which this result is applied is used in the marine industry, it is thought that the stability, reduction of labor force, and work efficiency will be improved when workers work.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.349-357
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• 2021

Recently, drones are rapidly becoming common and expanding. There is a great need for diversity in whether drone flight data can be used as entertainment technology analysis data. In particular, it is necessary to check whether it is possible to analyze and utilize the flight and operation process of entertainment drones, which are developing through autonomous and intelligent methods, through data analysis and machine learning. In this paper, it was confirmed whether it can be used as a machine learning technology by using FC data in the evaluation of drones for entertainment. As a result, FC data from DJI and Parrot such as Mavic2 and Anafi were unable to analyze machine learning for entertainment. It is because data is collected at intervals of 0.1 second or more, so that it is impossible to find correlation with other data with GCS. On the other hand, it was found that machine learning technologies can be applied in the case of Fixhawk, which used an ARM processor and operates with the Nuttx OS. In the future, it is necessary to develop technologies capable of analyzing the characteristics of entertainment by dividing fixed-wing and rotary-wing flight information. For this, a model shoud be developed, and systematic big data collection and research should be conducted.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.78-84
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• 2017

Because the 'Internet of Things' and sensor network technology have become a new generation industry competitiveness with a development of Information Communication Technology, each local autonomous entity is trying to adopt a Smart City quickly. This requires an integrated platform inside of a smart city operation center. Established Smart City platform provides various services using CCTV information and ITS transportation information based on a two-dimensional map. The provision of advanced Smart City services will necessitate three-dimensional map information, building and facilities unit information, linked information with public data portal for service to the public. In this paper, the authors reviewed development trends of Smart City integrated platform and proposed mashup methods between BIM/GIS interoperability platform and external open data. BIM/GIS platform can provide spatial information services for indoor and outdoor seamlessly because it was developed based on GIS spatial data with BIM data. The linked external open data are V-World data, Seoul Open Data, and Architectural Data Open. Finally, the authors proposed the direction of development for BIM/GIS integrated platform to provide advanced Smart City services.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.115-123
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• 2021

In recent years, the automobile industry has been facing a major change with the introduction of new technologies represented by autonomous driving, electrification, and digitalization. Major domestic and overseas automakers are trying to use a systematic approach to customer satisfaction through user interfaces to provide customers with a special experience and value beyond just making products with high performance. This study proposes the Kano model as a systematic and qualitative research method for satisfaction. As a case study, 17 functions of a product were sorted (3 operation functions, 7 safety functions, and 7 convenience functions). This was done by analyzing the use case and the customers' requirements for a smart trunk system. 18 new functions were derived via creative ideation codes. In addition, a scientific analysis method is proposed for product quality attributes and the strength of customer satisfaction. Using the Kano methodology, 25 functions were classified into quality attributes: 18 attractive qualities, 3 one-dimensional qualities, and 4 complex qualities, which are combinations of one-dimension qualities and must-have qualities. The functions that have one-dimensional quality and complex qualities were found to have higher customer ratings than the functions that have attractive qualities. Based on this, enterprises could effectively reduce customer complaints and enhance customer satisfaction.