• Journal of Navigation and Port Research
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• v.34 no.10
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• pp.727-733
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• 2010

An estimation algorithm of collision risk among multiple ships has been developed in order to reduce human error and prevent collision accidents. The algorithm is designed to calculate the collision risk among ships based on Fuzzy theory by using AIS data as traffic information. In this paper, to validate the algorithm, the AIS data of actual collision accident, which occurred between a product carrier and a cargo carrier in Busan harbor in 2009 are collected. The replay simulation is carried out on the actual AIS data and the collision risk is calculated in real time. In this paper, the features of the estimation algorithm of collision risk and the results of replay simulation based on AIS data of actual collision accident are discussed.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.7
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• pp.9-16
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• 2016

As life in a rapidly changing Internet age at home and abroad, large amounts of information are being used medical, financial, services, etc. Accordingly, especially hospitals, is an invasion of privacy caused by leakage and intrusion of personal information in the system in medical institutions, including clinics institutions. To protect the privacy & information protection of personal health medical information in medical institutions at home and abroad presented by national policies and de-identification processing technology standards in accordance with the legislation. By comparative analysis in existing domestic and foreign institutional privacy and de-identification technique, derive a advanced one of pseudonymization and anonymization techniques for destination data items that fell short in comparison to the domestic laws and regulations, etc. De-identification processing technology for personal health information is compared to a foreign country pharmaceutical situations. We propose a new de-identification techniques by reducing the risk of re-identification processing to enable the secondary use of domestic medical privacy.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.2
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• pp.49-56
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• 2017

In this study, flood analysis was conducted to prepare for damage caused by typhoons and heavy rain due to abnormal climate and climate change. Two - dimensional flooding analysis using the FLUMEN model, which is widely used for national and international flood risk mapping, was conducted for the Nam River Basin, which is the tributary of the Nakdong River. This study divides the topography into $5m{\times}5m$ DEM by ArcView, so that the accuracy of river repair and hydrological characterization and flood area identification can be maximized. As a result of simulation of water flooding, 163.3ha in section 1, 227.7ha in section 2 and 59.9ha in section 3 were simulated.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.499-504
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• 2023

본 연구에서는 민감한 개인정보의 유출과 남용 위험이 높아지고 있는 상황에서 정확한 개인정보 탐지 및 비식별화의 효율을 높이기 위해 개인정보 항목에 특화된 개체명 체계를 개발하였다. 개인정보 태그셋이 주석된 대화 데이터 4,981세트를 구축하고, 생성 AI 모델을 활용하여 개인정보 개체명 탐지 실험을 수행하였다. 실험을 위해 최적의 프롬프트를 설계하여 퓨샷러닝(few-shot learning)을 통해 탐지 결과를 평가하였다. 구축한 데이터셋과 영어 기반의 개인정보 주석 데이터셋을 비교 분석한 결과 고유식별번호 항목에 대해 본 연구에서 구축한 데이터셋에서 더 높은 탐지 성능이 나타났으며, 이를 통해 데이터셋의 필요성과 우수성을 입증하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.174-192
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• 2021

The LIDAR sensor, which provides higher cognitive performance than cameras and radar, is difficult to apply to ADAS or autonomous driving because of its high price. On the other hand, as the price is decreasing rapidly, expectations are rising to improve existing autonomous driving functions by taking advantage of the LIDAR sensor. In level 3 autonomous vehicles, when a dangerous situation in the cognitive module occurs due to a sensor defect or sensor limit, the driver must take control of the vehicle for manual driving. If the driver does not respond to the request, the system must automatically kick in and implement a minimum risk maneuver to maintain the risk within a tolerable level. In this study, based on this background, a LIDAR-based LKS MRM algorithm was developed for the case when the normal operation of LKS was not possible due to troubles in the cognitive system. From point cloud data collected by LIDAR, the algorithm generates the trajectory of the vehicle in front through object clustering and converts it to the target waypoints of its own. Hence, if the camera-based LKS is not operating normally, LIDAR-based path tracking control is performed as MRM. The HAZOP method was used to identify the risk sources in the LKS cognitive systems. B, and based on this, test scenarios were derived and used in the validation process by simulation. The simulation results indicated that the LIDAR-based LKS MRM algorithm of this study prevents lane departure in dangerous situations caused by various problems or difficulties in the LKS cognitive systems and could prevent possible traffic accidents.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.603-608
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• 2014

In the maritime traffic environment, the near-miss between vessels is the situation approaching on collision course but collision accident is not occurred. In this study, in order to calculate the near-miss between navigating vessels, the discriminating equation using ship bumper theory and vessel position clustering methods are proposed. Applying proposed module to the vessel trajectories of the WANDO waterway, we assessment navigational risk factors of vessel type, navigational speed, meeting situation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.470-471
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• 2011

As the increase in maritime traffic and leisure, the marine accident risk has increased in the domestic coast. In this paper, we propose an anti-collision system between vessels using the shortest distance and the time to reach the distance in maritime. the shortest distance and the time to reach the distance calculated with vector analysis using AIS information, a prototype is implemented for smartphone application.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.585-586
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• 2019

Recently, the systems for managing the labs provide services that can be managed in real time by using various sensors based on IoT. The system collects sensor data and transmits it to the server, identifies the dangerous situation, and sends operation commands to the devices. These systems have a centralized structure that slows data processing when managing multiple laboratories. To solve this problem, this paper proposes a system that manages laboratories in distributed processing environment to identify and manage risk situations. The sensor module is used to control the laboratory and to automatically identify and respond to the dangerous situation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.363-365
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• 2015

우리나라 연안에서 육지와 섬 사이를 연결하는 해상교량은 계속해서 건설하고 있는 추세이며 해상교량이 선박의 안전한 운항에 새로운 위험요소로 대두되고 있다. 반면에 내항여객선 선장 및 항해사는 무중 레이더만 믿고 항해하여야 하나, 레이더가 해상교량의 주경간 항로와 해상교량 건너편 상황을 탐지하기 어렵다는 레이더의 한계를 인식하지 못하고, 경험과 관행에 의해 무리하게 선박을 운항하고 있다고 판단된다. 이 글은 목포지방해양안전심판원의 관할해역에서 발생한 여객선 비금농협카페리호가 신안1교의 교각과 접촉한 사건의 개요와 원인을 살펴보고, 레이더에 의해 해상교량의 주경간 항로를 식별할 수 있는 대책마련의 필요성, 선박의 해상교량 통항을 위한 최소 가시거리 인식 필요성, 해상교량 주변에 피항지 지정 및 관리, 내항여객선의 VHF청취능력 개선, VTS센터와 한국해운조합 운항관리실의 업무협력 강화, 연안 여객선의 안전문화 정착 필요성, GPS Plotter 과신 주의 등의 교훈 및 개선사항을 제시하고 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.927-929
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• 2021

최근 펫팸족(Pet-Family)과 같이 반려동물을 가족처럼 생각하는 가구가 증가하면서 반려동물 시장이 크게 성장하고 있다. 이러한 이유로 본 논문에서는 반려동물의 객체 식별을 통한 객체 분할과 신체 좌표추정에 기반을 둔 반려동물의 행동 분류 방법을 제안한다. 이 방법은 CCTV를 통해 반려동물 영상 데이터를 수집한다. 수집된 영상 데이터는 반려동물의 인스턴스 분할을 위해 Mask R-CNN(Region Convolutional Neural Networks) 모델을 적용하고, DeepLabCut 모델을 통해 추정된 신체 좌푯값을 도출한다. 이 결과로 도출된 영상 데이터와 추정된 신체 좌표 값은 CNN(Convolutional Neural Networks)-LSTM(Long Short-Term Memory) 모델을 적용하여 행동을 분류한다. 본 모델을 바탕으로 행동을 분석 및 분류하여, 반려동물의 위험 상황과 돌발 행동에 대한 올바른 대처를 제공할 수 있는 기반을 제공할 것이라 기대한다.