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이선영 ( Lee Seonyeong ) 한국텍스트언어학회 2016 텍스트언어학 Vol.41 No.-
Stems which are bound morphemes cannot be used without ending. We can find the examples that stems were used without endings in the `Gyerimyusa` written in the 12th century, but in the Korean materials written since then up to the modern times we can`t discover the example that stem was used independently. By the way since 2000, the examples that stems divorced from endings were used in the recent broadcastings and journal articles appeared considerably. In this paper I checked such examples and tried to establish the cause of the phenomena. As a result I made a conclusion that the phenomena such as `bureop(부럽), deoreop(더럽), eonjjanh(언짢),` that a stem of a simplex was used apart from ending happened because of clarity of stem and development of wordplay. And I thought `ppaebak(빼박), deudbo(듣보)` are the examples that stems are separate in abbreviation, `meoktwi(먹튀), kkojip(꼬집), meokyojeong(먹요정)` are the cases that stems are separate in the formation of stem-compound, `meokstagraem(먹스타그램)` is the example that stem is separate in the formation of blend. The phenomena that a stem of a simplex was used independently or the exmples that stems are separate in abbreviation didn`t exist in the Korean before 2000. I hope that many studies on the charateristics of stem will be made on the basis of the materials in this paper.
순서형 프로빗 모형을 활용한 강우 시 전국고속도로 교통사고 심각도 분석
이선영(LEE, Seonyeong),한상진(HAN, Sangjin),정연식(CHUNG, Younshik) 대한교통학회 2016 대한교통학회 학술대회지 Vol.75 No.-
본 연구는 전국고속도로의 강우 시 교통사고 심각도에 영향을 미치는 주요변수를 파악하는데 목적이 있다. 교통사고 심각도의 효용함수는 오차항(∈i)을 표준정규분포로 가정한 순서형 프로빗 통계모형을 이용하였으며 주요 설명변수로 전국고속도로의 기상상황, 도로기하구조, 교통류자료를 수집 및 융합을 통해 교통사고 심각도 예측모형을 개발하는데 있다. 이를 위해 국내 고속도로 표준노드링크 854개에서 발생한 1,505†건의 사고자료와 통계 프로그램 STATA 13.0을 이용하여 분석을 실시하였다. 주요 결과는 다음과 같다. 교통사고 심각도에 영향을 주는 요소들은 사고 등급별로 영향도가 다른 것으로 나타났다. 특히 독립변수의 상대적인 영향력 비교를 위해 제시한 한계효과는 대물사고인 경우에는 부(-)의 영향, 인명사고인 경우에는 정(+)의 영향을 미치는 것으로 나타났다. 최종적으로 개발된 강우시 심각도 모형을 분석한 결과, 교통사고 심각도에 영향을 미치는 독립변수는 우커브, 사고유형, 차량종류, 종단경사, 강우지속시간, 풍속, 사고차량 수, 제한속도로 나타났다.
카메라를 활용한 딥러닝 기반 자율주행자동차의 사각 지대 객체 검출 및 경고 시스템에 관한 연구
이선영(Seonyeong Lee),김민구(Mingu Kim),김정하(Jungha Kim) 한국자동차공학회 2018 한국자동차공학회 학술대회 및 전시회 Vol.2018 No.11
In this paper, we propose blind spot area detection and warning system for autonomous driving automobiles based on deep running using a camera to prevent accidents caused by autonomous vehicles due to angle limitation of side mirrors. Recently, algorithms capable of real-time object detection through deep learning have attracted attention in the image processing field of autonomous driving. In this paper, SSD(Single Shot Multibox Detector) algorithm is used for detection of blind spot objects. SSD has an accuracy similar to that of conventional Faster R-CNN and has the advantage of detecting objects faster than YOLO(You Only Look Once). Experimental results show that we can solve the trade-off problem of accuracy and real-time performance of existing algorithm by applying SSD in well-balanced manner, and confirm warning and real-time detection possibility of blind spot objects of autonomous vehicles.
김대환(Daehwan Kim),이선영(Seonyeong Lee),유승현(Senghyun Yu),박장진(jang Park),이성준(Seongjun Lee) 한국자동차공학회 2018 한국자동차공학회 지부 학술대회 논문집 Vol.2018 No.5
Most of the existing fire alarms work depending on levels of carbon monoxide when fires outbreak; but their reliability of safety must decrease because only the levels are detected as a sensing element. This study suggests an algorism to detect fire by considering the three information for high accuracy of sensing and reliability improvement: Temperature Sensor, Flame Detection Sensor, and Carbon Monoxide Level Sensor. In addition, a simulation was completed by using situational sensing data which are based on an open source code of Arduino. As the result, aimed results came out according to the software design.
고정 카메라 영상의 히스토그램을 이용한 주차 공간 검출
김민구(Mingu Kim),이선영(Seonyeong Lee),김정하(Jungha Kim) 한국자동차공학회 2018 한국자동차공학회 부문종합 학술대회 Vol.2018 No.6
As technology and industry continue to be developed, demand of vehicles increases together. Currently, there are vehicles that are close to half of population in Korea on the road now from statistics of Ministry of Land, Infrastructure and Transport. We spend a lot of time in the car and it means also for parking. In addition, much research is now underway on ’Auto Valet parking’ which means cars park by themselves. For these reasons we propose a detecting system using image histogram through fixed and non-movable sensor. This system is to detect empty several parking spaces with only low cost monocular cameras. This eliminates the need of thousands of sensor equipped in parking lots due to it detect several spaces at one scene. The composition of this paper is as follows. We explain a low-value, monocular camera system to extract parking spaces using ROI(Region of Interest). With this image, we adjust the threshold values and ranges of the video processing algorithm that uses histogram to detect a number of parking spaces.