• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1451-1466
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• 2023

In the context of maritime emergencies, the utilization of drones has rapidly increased, with a particular focus on their application in search and rescue operations. Deep learning models utilizing drone images for the rapid detection of distressed vessels and other maritime drift objects are gaining attention. However, effective training of such models necessitates a substantial amount of diverse training data that considers various weather conditions and vessel states. The lack of such data can lead to a degradation in the performance of trained models. This study aims to enhance the performance of deep learning models for distress ship detection by developing a maritime environment simulator to augment the dataset. The simulator allows for the configuration of various weather conditions, vessel states such as sinking or capsizing, and specifications and characteristics of drones and sensors. Training the deep learning model with the dataset generated through simulation resulted in improved detection performance, including accuracy and recall, when compared to models trained solely on actual drone image datasets. In particular, the accuracy of distress ship detection in adverse weather conditions, such as rain or fog, increased by approximately 2-5%, with a significant reduction in the rate of undetected instances. These results demonstrate the practical and effective contribution of the developed simulator in simulating diverse scenarios for model training. Furthermore, the distress ship detection deep learning model based on this approach is expected to be efficiently applied in maritime search and rescue operations.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.99-104
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• 2022

This study was to analyze the effects of sudden rise in cortisol and human symptoms in the situation of rescue at river, The experimental results are as follows. The subjects were A, B, C, and the values of cortisol elevation before and after diving were 6.30ug/dl, 6.50ug/dl, and 6.57ug/dl, respectively. However, in the subject D, the elevation of cortisol before and after diving was significantly elevated to 11.00ug/dl. The reason for this is thought to be the depletion of physical strength through weighty due to the inferiority of the underwater view and tense during the sudden rise. The subjects E showed significantly lower cortisol elevation before and after diving, as 4.28ug/dl, because the age of E was the youngest of the subjects and the anxiety was low due to abundant experience of deep sea diving. Fatigue is 7 to 8, anxiety is 7 to 9, Both showed high values. Psychological strain increased fatigue in underwater search, and poor visual field seemed to increase anxiety. The research results will be provided as empirical data on the safe underwater search activities of rescuers.

• Journal of Navigation and Port Research
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• v.30 no.5 s.111
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• pp.357-362
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• 2006

This paper describes two kinds of personal hand-held electronic devices to enhance marine leisure safety. The one is Radar response-type safety device triggering by the pulse signal from a commercial 9GHz-band Radar to provide quick search and rescue with combined civilian-government-military fleets. The other one is M-RFID (Marine Radio Frequency IDentification) based safety electronic device using 900MHz Tx/Rx with spread spectrum frequency hopping and GPS. Through the field tests at sea using Korea Coast Guard's warship the operating performances are verified. Further plan for practical use of each device was also discussed.

• Proceedings of KOSOMES biannual meeting
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• 2017.04a
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• pp.107-107
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• 2017

• Proceedings of KOSOMES biannual meeting
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• 2017.11a
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• pp.251-251
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• 2017

• Proceedings of KOSOMES biannual meeting
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• 2017.11a
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• pp.77-77
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• 2017

• Proceedings of KOSOMES biannual meeting
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• 2007.05a
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• pp.195-201
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• 2007

In order to forecast the location of drifting objects at sea around Mokpo, Korea, the simulations were conducted with the input data of natural factors such as direction and force of wind and tidal current using SARMAP which is one of useful simulation tools for search and rescue at sea. Comparing the observed data with the calculated data of tidal currents used in SARMAP, the calculated tidal currents of SARMAP were in good agreement with the observed tidal currents. With regard to the case of marine casualties which occurred at sea around Daeheuksan-Do in July, 2006, the difference between the location of drifting body simulated by SAR model of Mokpo District Coast Guard and the location simulated by SARMAP was found to be about 20 nautical miles.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.57-64
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• 2022

If the inside of a building collapses due to a disaster such as fire, collapse, or natural disaster, the physical security inside the building is likely to become ineffective. Here, physical security is needed to minimize the human casualties and physical damages in the collapsed building. Therefore, this paper proposes an algorithm to minimize the damage in a disaster situation by fusing existing research that detects obstacles and collapsed areas in the building and a deep learning-based object detection algorithm that minimizes human casualties. The existing research uses a single camera to determine whether the corridor environment in which the robot is currently located has collapsed and detects obstacles that interfere with the search and rescue operation. Here, objects inside the collapsed building have irregular shapes due to the debris or collapse of the building, and they are classified and detected as obstacles. We also propose a method to detect rescue requesters-the most important resource in the disaster situation-and minimize human casualties. To this end, we collected open-source disaster images and image data of disaster situations and calculated the accuracy of detecting rescue requesters in disaster situations through various deep learning-based object detection algorithms. In this study, as a result of analyzing the algorithms that detect rescue requesters in disaster situations, we have found that the YOLOv4 algorithm has an accuracy of 0.94, proving that it is most suitable for use in actual disaster situations. This paper will be helpful for performing efficient search and rescue in disaster situations and achieving a high level of physical security, even in collapsed buildings.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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• pp.145-150
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• 2004

This paper suggests an evaluation of risk level for damage of marine accidents in SRRs. Qualitative analyses in words is sometimes priorior to quantative analyses in numeric symbols. This paper intoduces a concept of fuzzy theory with the plenty of related literature riview and AHP in the Korean SRRs of RCC and RSC. The methodology of this paper is maxㆍmin composition of fuzzy extensive principle, defuzzifiation is centroid of gravity methods. At the result, the evaluation of risk level is especially over Serous for smarine accident of Taean, Gunsan, Mokpo, Yosu, Tongyoung, Busan SRR. This paper recommends that many Resale Vessels and Equipments need to the reduction of risk level about those.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06a
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• pp.274-275
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• 2012

생체모방로봇은 인간을 비롯하여 새, 곤충, 물고기 등 동물들의 기본구조, 행동원리 및 메커니즘을 모방한 로봇이다. 정찰, 수색, 테러진압 등 군사작전에서부터 인명구조까지 생체모방로봇은 인간의 눈과 발을 대신하여 인간이 접근할 수 없는 오염 지역을 면밀히 탐지하는 데에도 유용하리라 예상된다. 이와 같은 생체모방로봇이나 MAV 등을 실시간으로 원격에서 모니터링하고 제어할 수 있는 DAQ 시스템의 중요성이 커지고 있다. 본 논문에서는 생체모방로봇인 가오리를 원격 관제 센터에서 RF무선통신을 이용하여 안정적인 제어 및 모니터링이 가능한 DAQ(Data AcQuisition) 시스템을 제안한다.