• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.115-124
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• 2022

In this paper, we present an NFT auction service for the next generation, named NextAuction, which can reliably trade ownership of individual content using DID technology. Recently, as the types and sizes of tradable digital assets have expanded, the number of NFT transactions has also increased, and a significant number of marketplaces are being operated. But, the current user authentication methods of NFT marketplaces are done only through the associated blockchain wallets. It is desirable that ownership transfer through NFT transactions be transparently managed based on a more reliable identity authentication service. NextAuction increases the reliability of auction service participants by transparently and consistently providing identity authentication for users of auction services based on the DID technique using the Klaytn blockchain. In addition, in preparation for server failure that may occur during the auction of individual content, it provides users with a robust auction service using the BR2K technique that continuously provides consistent service through the replication of a target service. The NextAuction service is developed by extending BCON, a blockchain-based content management service.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1097-1104
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• 2021

Online game-bots are already known for a lot of persons by various ways. It leads to problems such as declining game player's interest, in-game financial crisis, etc. Detecting and restricting of game-bot is now essential. Because both publishers and players get disadvantages from their long term abnormal working. But it is not easy to restrict, because of false restriction risks. Game publishers need to distinguish game-bot from server-side game logs. At last, it should can make reasons for game-bot restriction. In this paper, we classified game-bot users by using daily separated game logs for testing data. For daily-driven detection, we separated total dataset into one day logs. Preliminary detects game-bots with one day logs, and determines total results by using these data. Daily driven detection advantages on detection which contains combined game playing style. Which shows like normal user and game-bot. These methodology shows better F1-score, which one of indicator which demonstrate classification accuracy. It increases from 0.898 to 0.945 by using Random Forest classifier.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1266-1271
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• 2022

Cats have strong wildness so they have a characteristic of hiding diseases well. The disease may have already worsened when the guardian finds out that the cat has a disease. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia, polyuria, and frequent urination more quickly. In this paper, 1) Efficient version of DeepLabCut for pose estimation, 2) YOLO v4 for object detection, 3) LSTM is used for behavior prediction, and 4) BoT-SORT is used for object tracking running on an artificial intelligence device. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the server system.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.1086-1091
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• 2022

The International Maritime Organization is establishing international agreements on maritime safety and security to prepare for the introduction of autonomous ships. In Korea, the industry is focusing on autonomous navigation system technology development, and to reduce accidents involving coastal ships, research on autonomous ship technology application plans for coastal ships is in progress. Interest in autonomously operated ships is increasing worldwide, and maritime demonstrations for verification of developed technologies are being pursued. In this study, a basic investigation was conducted on the design of a demonstration ship and an onshore platform (remote support center) using digital twin technology for application to coastal ships. To apply digital twin technology, an 8-m small battery-powered electric propulsion ship was selected as the target. The basic design of the twin-integrated platform was developed. The ship navigation and operation data were stored on a server system, and remote-control commands of the electric propulsion ship was achieved through communication between the ship and the onshore platform. Ship performance management, operation and operation optimization, and predictive control are possible using this digital twin technology. This safe and economical digital twin technology is applicable to ships responding to crisis scenarios.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.4
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• pp.271-282
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• 2022

In this paper, we propose a digital human content creation system. The digital human content creation system works with 3D AI modeling through whole-body scanning, and is produced with 3D modeling post-processing, texturing, rigging. By combining this with virtual reality(VR) content information, natural motion of the virtual model can be achieved in virtual reality, and digital human content can be efficiently created in one system. Therefore, there is an effect of enabling the creation of virtual reality-based digital human content that minimizes resources. In addition, it is intended to provide an automated pre-processing process that does not require a pre-processing process for 3D modeling and texturing by humans, and to provide a technology for efficiently managing various digital human contents. In particular, since the pre-processing process such as 3D modeling and texturing to construct a virtual model are automatically performed by artificial intelligence, so it has the advantage that rapid and efficient virtual model configuration can be achieved. In addition, it has the advantage of being able to easily organize and manage digital human contents through signature motion.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.713-721
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• 2022

In order to use the LED video wall in the broadcasting studio, there are a few things to be aware of. First, since the pixels are closely arranged, a moire phenomenon may occur due to a short arrangement period, and second, the distance between pixels (pixel pitch) may be recorded on the image sensor of the broadcasting camera. When moire occurs or pixel pitch is observed, viewers feel uncomfortable. Moire effect can be reduced by adjusting the shooting distance or angle of the camera, but in order to prevent the pixel pitch from being recorded on the image sensor, secure a sufficient distance between the LED video wall and camera. even when the distance secured, the zoom lens used in the broadcasting studio must be operated by appropriately changing the magnification. If the focal length is changed by changing the magnification to obtain a desired angle of view, the pixel pitch may be unintentionally recorded. In this study we propose the range that the pixel pitch is not observed while changing the magnification ratio of the zoom lens when the distance from the video wall is sufficiently secured. The content was played back on the LED video wall and the LED video wall was recorded on the server using an HD camera equipped with a B4 mount zoom lens

• Smart Media Journal
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• v.12 no.2
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• pp.66-75
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• 2023

Recently, the number of cloud web applications is increasing owing to the accelerated migration of enterprises and public sector information systems to the cloud. Traditional network attacks on cloud web applications are characterized by Denial of Service (DoS) attacks, which consume network resources with a large number of packets. However, HTTP DoS attacks, which consume application resources, are also increasing recently; as such, developing security technologies to prevent them is necessary. In particular, since low-bandwidth HTTP DoS attacks do not consume network resources, they are difficult to identify using traditional security solutions that monitor network metrics. In this paper, we propose a new detection model for detecting HTTP DoS attacks on cloud web applications by collecting the application metrics of web servers and learning them using machine learning. We collected 18 types of application metrics from an Apache web server and used five machine learning and two deep learning models to train the collected data. Further, we confirmed the superiority of the application metrics-based machine learning model by collecting and training 6 additional network metrics and comparing their performance with the proposed models. Among HTTP DoS attacks, we injected the RUDY and HULK attacks, which are low- and high-bandwidth attacks, respectively. As a result of detecting these two attacks using the proposed model, we found out that the F1 scores of the application metrics-based machine learning model were about 0.3 and 0.1 higher than that of the network metrics-based model, respectively.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.869-875
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• 2009

Safety is a big issue in the construction sites. For safe and secure management, tracking locations of construction resources such as labors, materials, machineries, vehicles and so on is important. The materials, machineries and vehicles could be controlled by computer, whereas the movement of labors does not have fixed pattern. So, the location and movement of labors need to be monitored continuously for safety. In general, Global Positioning System(GPS) is an opt solution to obtain the location information in outside environments. But it cannot be used for indoor locations as it requires a clear Line-Of-Sight(LOS) to satellites Therefore, indoor location monitoring system could be a convenient alternative for environments such as tunnel and indoor building construction sites. This paper presents a case study to investigate feasibility of Wi-Fi based indoor location monitoring system in construction site. The system is developed by using fingerprint map of gathering Received Signal Strength Indication(RSSI) from each Access Point(AP). The signal information is gathered by Radio Frequency Identification (RFID) tags, which are attached on a helmet of labors to track their locations, and is sent to server computer. Experiments were conducted in a shield tunnel construction site at Guangzhou, China. This study consists of three phases as follows: First, we have a tracking test in entrance area of tunnel construction site. This experiment was performed to find the effective geometry of APs installation. The geometry of APs installation was changed for finding effective locations, and the experiment was performed using one and more tags. Second, APs were separated into two groups, and they were connected with LAN cable in tunnel construction site. The purpose of this experiment was to check the validity of group separating strategy. One group was installed around the entrance and the other one was installed inside the tunnel. Finally, we installed the system inner area of tunnel, boring machine area, and checked the performance with varying conditions (the presence of obstacles such as train, worker, and so on). Accuracy of this study was calculated from the data, which was collected at some known points. Experimental results showed that WiFi-based indoor location system has a level of accuracy of a few meters in tunnel construction site. From the results, it is inferred that the location tracking system can track the approximate location of labors in the construction site. It is able to alert the labors when they are closer to dangerous zones like poisonous region or cave-in..

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.59 no.3
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• pp.206-214
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• 2023

Fish school monitoring technology is utilized for various purposes, such as boat fishing and resource surveys. With advancements in information and communication technology, this technology has expanded its application to remote areas. Its significance has grown in fishing sites, particularly for improving the efficiency and cost-effectiveness of set-net fishing. Set-net fishing gears are not limited to coastal areas, but are also installed in inland and remote sea regions. Consequently, fishermen require technology that allows them to quickly transmit information about approaching fish schools and enables them to perform long-term monitoring. The development of remote monitoring technology for set-net fish schools must consider crucial design factors such as communication range, transmission speed, power consumption of information modules, and operational expenses. In this study, we developed a low-power remote monitoring module for set-net fish school based on WCDMA. The module was specifically designed to minimize power consumption, allowing for communication over long distances and extended operation times in set-net fishing applications. Furthermore, we developed a web server software application that enables remote access to fish schools and provides real-time weather information. The performance of the developed module was evaluated through set-net fishing site application and experiments with moving ships on the sea. The experimental results demonstrated that the remote monitoring system, consisting of the developed low-power remote monitoring module for set-net fish school based on WCDMA and a fish finder, had an average power consumption of 4.6 W, a maximum communication range of 22.84 km, and a data transmission and reception rate of 98.79%. The maximum fish school information transmission and reception rate was 97.26%

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.697-702
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• 2023

Recently, with the introduction of drones, a core technology of the 4th industrial revolution, various convergence education using drones is being conducted in school education sites. In particular, drone theory and practice education is being conducted in connection with free semester classes and career exploration. The drone convergence education program has higher learner satisfaction than simple demonstration and practice education, and the learning effect is high due to direct practical experience. However, since practical education is being conducted for a large number of learners, it is impossible to restrict and control the flight of a large number of drones in a limited place. In this paper, we propose a monitoring system that allows the instructor to monitor multiple drones in real time and learners to recognize collisions between drones in advance when multiple drones are operated, focusing on education operated in schools. The communication module used in the experiment was equipped with GPS in Murata LoRa, and the server and client were configured to enable monitoring based on the location data received in real time. The performance of the proposed system was evaluated in an open space, and it was confirmed that the communication signal was good up to a distance of about 120m. In other words, it was confirmed that 25 educational drones can be controlled within a range of 240m and the instructor can monitor them.