• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.634-639
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• 2014

This paper specifies a collision alarm using an infrared distance sensor that can identify the dangerousness of collision of active mobile robotic systems to various objects, such as unknown objects or another robots. And we analyse the major operating signals and features of the collision alarm for effective industrial applications. For the purpose, we consider a typical parking situation of a mobile robotic system with the collision alarm designed. As a result, it is shown that the proposed collision alarm is applicable for effective collision avoidance and safe driving of various mobile robots or vehicles.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.1085-1092
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• 2018

Recently, Internet (IoT) and big data have been utilized in various fields such as medical, military and sports. Korea Nazarene University is a rehabilitation-welfare university with about 300 students with disabilities. This paper proposes a smart campus that provides the optimal path for the calculation of the route and risk avoidance using the BLE beacon and the 3-axis acceleration sensor when the students with disabilities move in the campus both indoors and outdoors. So we can manage the big data and sensor-based IoT technology for students with disabilities.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.2
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• pp.712-717
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• 2011

Option issuers generally utilize Dynamic Delta Hedging(DDH) technique to avoid the risk resulting from continuously changing option value. DDH duplicates payoff of option position by adjusting hedge position according to the delta value from Black-Scholes(BS) model in order to maintain risk neutral state. DDH, however, is not able to guarantee optimal hedging performance because of the weaknesses caused by impractical assumptions inherent in BS model. Therefore, this study presents a methodology for dynamic option hedge using artificial neural network(ANN) to enhance hedging performance and show the superiority of the proposed method using various computational experiments.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.486-490
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• 2018

Radar Beacons are marine aids that helps the navigators avoid dangers such as dangerous rocks, heavy fog, nighttime, etc. when sailing. The existing antenna was researching on the development of the advanced radar Beacon (Enhanced Radar Beacon) for the improvement of the next generation racon with the AIS (Automatic Identification System) function.

• Journal of Korea Game Society
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• v.19 no.1
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• pp.135-146
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• 2019

World Health Organization reveals its plan for listing 'Gaming Disorder' on the 11th International Disease Codes (ICD-11) in 2018 and it opens hot debate among scholars on its validity and timeliness. Korea, however, seems to have avoided the issue without appropriate academic refutation. In this paper, we review past academic studies related to game addiction or disorder focused on their validity of disorder measurement tools, research designs and the effect of neuroimaging studies. This analysis reveals that excessive use of gaming is not sufficient to register it as a disease and there is a risk of stigmatizing healthy gamers.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.4
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• pp.37-44
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• 2021

In case of South Korea, the airspace which airlines can operate is extremely limited due to the military operational area located within the Incheon flight information region. As a result, safety problems such as mid-air collision between aircraft or Traffic alert and Collision Avoidance System Resolution Advisory (TCAS RA) may occur with higher probability than in wider airspace. In order to prevent such safety problems, an mid-air collision risk detection model based on Detect-And-Avoid (DAA) well clear metrics is investigated. The model calculates the risk of mid-air collision between aircraft using aircraft trajectory data. In this paper, the practical use of DAA well clear metrics based model has been validated. Aviation safety data such as aviation safety mandatory report and Automatic Dependent Surveillance Broadcast is used to measure the performance of the model. The attributes of individual aircraft track data is analyzed to correct the threshold of each parameter of the model.

• Journal of Hydrogen and New Energy
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• v.33 no.4
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• pp.383-390
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• 2022

Appropriate explosion proof electrical equipment should be installed in hazardous areas. In areas where hydrogen is handled, explosion proof electrical equipment adjacent to the hydrogen handing facility must be reviewed for selection of gas group IIC (or IIB+H₂) equipment. When selecting explosion proof electrical equipment for the flammable substance handling facility in areas where hydrogen and flammable substance are handled, the method to avoid gas group IIC (or IIB+H₂) equipment has been suggested by using the operating pressure of the hydrogen handling facility. When the operating pressure of the outdoor hydrogen handling facility is 1.065 MPa or less, it has been confirmed that there is no need to install gas group IIC (or IIB+H₂) equipment for the flammable substance handling facility adjacent to the hydrogen handling facility. And the method of selecting explosion proof electrical equipment for the flammable substance handling facility has been suggested as a flowchart, so it will be able to be utilized when selecting appropriate explosion proof electrical equipment.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.299-300
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• 2024

첨단 기술의 발전과 함께 지능형 운전자 보조 시스템의 성능 및 교통 시스템 체계가 고도화됨에 따라 전반적인 교통사고 발생 건수는 줄어드는 추세지만 대한민국의 교통사고 발생 빈도는 아직 OECD 평균 대비 높은 실정이다. 특히, 2020년 경제 협력 개발 기구(OECD) 통계에 따르면 대한민국의 인구 10만 명당 교통사고 사망자 수는 회원국 36개 중 29위로 매우 높은 축에 속한다. 따라서, 본 논문에서는 교통사고 발생률을 낮추는 데 도움을 줄 수 있는 주행 이상 패턴 감지 시스템을 제안한다. 제안한 방법에서는 실시간 영상 분석을 통해 신호등 및 차선을 인식함과 동시 차량 내부 진단 데이터에 대한 시계열 분석을 기반으로 운전자의 운전 패턴을 분석한 후 평소와 다른 이상 징후를 발견하면 운전자에게 경고 알림을 제공하여 위험한 상황을 회피할 수 있도록 지원한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.392-397
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• 2014

Recently, there are many researches on active safety system of intelligent vehicle. To reduce the probability of collision caused by driver's inattention and mistakes, the active safety system gives warning or controls the vehicle toward avoiding collision. For the purpose, it is necessary to recognize and analyze circumstances around. In this paper, we will treat the problem about collision risk assessment. In general, it is difficult to calculate the collision risk before it happens. To consider the uncertainty of the situation, Monte Carlo simulation can be employed. However it takes long computation time and is not suitable for practice. In this paper, we apply neural networks to solve this problem. It efficiently computes the unseen data by training the results of Monte Carlo simulation. Furthermore, we propose the features affects the performance of the assessment. The proposed algorithm is verified by applications in various crash scenarios.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.5
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• pp.497-503
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• 2018

Passenger ships and training ships have a common feature in that they serve many passengers. Thus, safe navigation is very important. During normal sailing, a ship may turn using various types of steering, including maneuvers to avoid collisions with dangerous target. When a ship turns, a heeling angle occurs. If trouble arises during sailing, a dangerous heeling angle may result or a capsizing accident. In this study, the heeling angle during turning was measured through experimentation with two training ships similar to passenger ships. These findings were compared with theoretical formulas for heeling angle when turning. We confirmed that the limit of the maximum heeling angle estimation using heeling angle formula when turning presented in IMO stability criteria. In addition, it was confirmed that the maximum estimated heeling angle can be reached by applying the result calculated in the theoretical formula 1.4 times when turning right and 1.1 times when turning left to reflect sailing speed when of rudder hard over. It is expected that this study will provide basis data for establishing safe operation standards for the prevention of dangerous heeling angles when turning.