• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.500-506
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• 2012

A method to model left ventricular assist device (LVAD) and detect suction occurrence for safe LVAD operation is presented. An axial flow blood pump as a LVAD has been used to assist patient with heart problems. While an axial flow blood pump, a kind of a non-pulsatile pump, has relative advantages of small size and efficiency compared to pulsatile devices, it has a difficulty in determining a safe pump operating condition. It can show different pump operating statuses such as a normal status and a suction status whether suction occurs in left ventricle or not. A fuzzy subtractive clustering method is used to determine a model of the axial flow blood pump with this pump operating characteristic and the developed pump model can provide blood flow estimates before and after suction occurrence in left ventricle. Also, a fuzzy subtractive clustering method is utilized to develop a suction detection model which can identify whether suction occurs in left ventricle or not.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.18-34
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• 2021

Pedestrian deaths in Korea due to traffic accidents are 40 percent of the fatalities in traffic accidents, which is about twice the average of OECD member countries. To reduce severe pedestrian accidents, it is necessary to apply the accident reduction measures to high-risk drivers (novice, elderly, and commercial vehicle drivers) who are more likely to cause traffic accidents than general drivers. Therefore, this study analyzed the effect of safe driving education on high-risk drivers' behavior. Here, the safe driving education is chosen as the measure to reduce traffic accidents. As part of the study, sudden pedestrian crossing situations were implemented in the driving simulator, and the vehicle trajectory data were collected to compare the driving behavior before and after the education. Most surrogate safety measures showed no improvement in the driving behavior of novice and elderly drivers, and the effect of safe driving education was found to be significant only in the group of commercial vehicle drivers. The results implied that additional measures such as pedestrian safety infrastructure and driver assistance systems, apart from the safe driving education, may be needed for novice and elderly drivers to reduce pedestrian accidents caused by them. With the findings mentioned above, this study is expected to provide a foundation to establish a plan to reduce pedestrian accidents caused by high-risk drivers.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.616-618
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• 2012

본 논문에서는 터널 내 환경에서 2차 사고의 위험성이 되는 정지차량, 보행자와 같은 유고상황 검출 시스템의 안전성을 확보하고 효율성을 증대시킬 수 있도록 하기위해 차선검출알고리즘에 기반하여 카메라 이동을 조기에 감지하는 방법을 제시한다. 제안하는 알고리즘은 다른 컬러변환 및 복잡한 계산량 증가 없이 입력되는 RGB 컬러 정보의 실험적 분석을 통하여 효과적으로 차선을 검출함으로써 카메라 이동을 감지한다. 제안하는 알고리즘은 직선을 찾는 알고리즘에 비해 수행시간을 단축시킬 수 있으며 실시간 처리에 용이함을 알 수 있으며 운전보조안전시스템에서 활용 가능함을 알 수 있다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.149-155
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• 2020

The Korea Highway Traffic Authority provides statistics that analyze the causes of traffic accidents that occurred since 2015 using the Traffic Accident Analysis System (TAAS). it was reported Through TAAS that the driver's forward carelessness was the main cause of traffic accidents in 2018. As statistics on the cause of traffic accidents, 51.2 percent used mobile phones and watched DMB while driving, 14 percent did not secure safe distance, and 3.6 percent violated their duty to protect pedestrians, representing a total of 68.8 percent. In this paper, we propose a system that has improved the advanced driver assistance system ADAS (Advanced Driver Assistance Systems) by utilizing CNN (Convolutional Neural Network) among the algorithms of Deep Learning. The proposed system learns a model that classifies the movement of the driver's face and eyes using Conv2D techniques which are mainly used for Image processing, while recognizing and detecting objects around the vehicle with cameras attached to the front of the vehicle to recognize the driving environment. Then, using the learned visual steering model and driving environment data, the hazard is classified and detected in three stages, depending on the driver's view and driving environment to assist the driver with the forward and blind spots.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.318-321
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• 2011

도로 주행 시 운전을 보조하고 안전 운전을 지원하기 위한 기술인 도로상황인지 시스템에 있어 효율적인 차선 차간 검출 기법은 위의 핵심적인 기술이다. 실시간으로 수집되는 도로 상황 영상 데이터 분석에 대한 처리 시간을 단축하기 위하여 각각의 영상 프레임에 대해 관심 영역을 설정한 후 허프 변환을 적용하였다. 본 논문은 카메라로 수집되는 도로 상황 영상에 관심 영역 설정을 통한 실시간 차선 차간 인식에 관한 연구로서, 차선과 차간 인식을 위한 효율적인 알고리즘을 제안한다.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.5
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• pp.54-58
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• 2013

In recent days, vehicles have become equipped with electric systems that assist and help drivers driving safe by reducing possible accidents. LDWS(Lane Departure Warning System) and LKAS(Lane Keeping Assistant System) are involved in assist systems, especially for lateral motion of vehicles. Sudden and inattentive lateral motion of vehicles due to drivers' fatigue, illness, inattention, and drowsiness are major causes of accidents in highway. LDWS and LKAS provide drivers with warnings or assisting power to reduce any possibilities of accidents. In order to prevent or minimize the possibilities of accidents, lateral motion control of vehicles has been introduced in this research. DGPS/RTK(Differential Global Positioning System/Real Time Kinematics) and GIS(Geographic Information System) have been used to obtain the current position of vehicles and decide when activate controlling lateral motion of vehicles. The presented lateral motion control has been validated with actual vehicle tests.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.6
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• pp.788-793
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• 2014

In this study, the electrical power consumption saving effect is studied through installing an inverter which is able to control the R.P.M. of marine sea water pump by effective flow control. The study looks at how sea water pump's flow control influences on the system without the Marine Growths Protection System(MGPS). Auxiliary sea water pump and refrigerator sea water pump in training ships, which are always operated not only in harbor but also in navigation, was used in the experiment and the experiment was conducted by dividing into harbor and navigation. As a result of research, in the case the sea water temperature is under $18^{\circ}C$, the operation was possible with a 58.3 % decrease in pump R.P.M. and electric power consumption was saved by 50 %. In spite of the sea water temperature increasing upto $34^{\circ}C$, pump R.P.M. at 91.6 % was sufficient to operate with a 20 % electric power consumption saving effect. In the pipelines without MGPS, lowering R.P.M. along with lowering pressure results in the attachment of various marine growths.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.12
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• pp.123-129
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• 2014

In accordance with the development of various convergence devices, cameras are being used in many types of the systems such as security system, driver assistance device and so on, and a lot of people are exposed to these system. Therefore the system should be able to recognize the human behavior and support some useful functions with the information that is obtained from detected human behavior. In this paper we use a machine learning approach based on 2D image and propose the human behavior pattern recognition methods. The proposed methods can provide valuable information to support some useful function to user based on the recognized human behavior. First proposed one is "phone call behavior" recognition. If a camera of the black box, which is focused on driver in a car, recognize phone call pose, it can give a warning to driver for safe driving. The second one is "looking ahead" recognition for driving safety where we propose the decision rule and method to decide whether the driver is looking ahead or not. This paper also shows usefulness of proposed recognition methods with some experiment results in real time.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.621-626
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• 2015

This paper presents a camera calibration method in order to estimate the lane detection and inter-vehicle distance estimation system for an automotive safety driving system. In order to implement the lane detection and vision-based inter-vehicle distance estimation to the embedded navigations or black box systems, it is necessary to consider the computation time and algorithm complexity. The process of camera calibration estimates the horizon, the position of the car's hood and the lane width for extraction of region of interest (ROI) from input image sequences. The precision of the calibration method is very important to the lane detection and inter-vehicle distance estimation. The proposed calibration method consists of three main steps: 1) horizon area determination; 2) estimation of the car's hood area; and 3) estimation of initial lane width. Various experimental results show the effectiveness of the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.427-430
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• 2012

최근 차량용 블랙박스, 자동 운전 시스템, 어라운드 뷰 시스템 등과 같은 운전자의 편의와 안전을 위한 장치 및 시스템들이 개발되고 있다. 현재 운전자를 위한 보조 시스템으로 구글(google)의 자동 운전 시스템(Auto Car Driving System)과 현대 모비스(hyundai mobis)의 AVM 시스템(Around View Monitoring System) 등의 다양한 차량용 편의장치 시스템들이 등장했다. 위와 같은 다양한 ECU들을 관리하기 위한 서버 및 저장 장치 역할을 할 수 있는 고사양의 Car PC의 장착이 필수적이다. 기존의 AVM 시스템은 차량 주변을 실시간으로 제공하기 위해 임베디드 또는 별도의 차량용 네트워크를 통해 임베디드 시스템 또는 SoC(System On Chip)형태의 하드웨어 기반으로 개발되고 있다. 하지만 고사양의 Car PC 기반에서는 별도의 비용없이 소프트웨어로 구현이 가능하다. 본 논문에서는 차량의 전 후 좌 우에 장착된 4대의 카메라로부터 입력된 차량 주변 상황을 한눈에 보여주는 AVM 시스템(Around-View Monitoring System)을 위한 카메라 보정 및 정합 처리 모듈 및 AVM 시스템을 Windows를 O/S로 하는 PC 내부에서 기존의 AVM 시스템을 이용하여 화면에 전 후 좌 우 버튼을 각각 만들어 버튼을 터치했을 때, 각 버튼에 해당되는 영상이 AVM 시스템과 함께 출력되도록 하거나 디스플레이에 Full 버전으로 출력되도록 S-UI(Smart User Interface)를 설계 및 구현한다. 제안하는 AVM 시스템과 기존의 AVM 시스템의 성능과 기능을 비교 분석함으로써 제안하는 영상 처리 모듈을 이용하여 추가 비용이 발생하지 않는 AVM 시스템의 구현 가능성을 검증한다.