• 천문학회보
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• 제37권1호
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• pp.38.2-38.2
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• 2012

We use two-dimensional high-resolution MHD simulations to investigate the effects of magnetic fields on the formation and evolution of such substructures as well as on the mass inflow rates to the galaxy center. We find that there exists an outermost x1-orbit relative to which gaseous responses to an imposed stellar bar potential are completely different between inside and outside. Inside this orbit, gas is shocked into dust lanes and infalls to form a nuclear ring. Magnetic fields are compressed in dust lanes, reducing their peak density. Magnetic stress removes further angular momentum of the gas at the shocks and leads to a smaller and more centrally distributed ring, resulting in the mass inflow rates larger, by more than two orders of magnitude, than in the unmagnetized counterparts. Outside the outermost x1-orbit, on the other hand, an MHD dynamo operates near the corotation and bar-end regions, efficiently amplifying magnetic fields. The amplified fields shape into trailing magnetic arms with strong fields and low density. The base of the magnetic arms have a thin layer in which magnetic fields with opposite polarity reconnect via a tearing-mode instability. This produces numerous magnetic islands with large density which propagate along the arms to turn the outer disk into a highly chaotic state.

• 대한임베디드공학회논문지
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• 제11권3호
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• pp.163-171
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• 2016

Lane detection is a widely researched topic. Although simple road detection is easily achieved by previous methods, lane detection becomes very difficult in several complex cases involving noisy edges. To address this, we use a Convolution neural network (CNN) for image enhancement. CNN is a deep learning method that has been very successfully applied in object detection and recognition. In this paper, we introduce a robust lane detection method based on a CNN combined with random sample consensus (RANSAC) algorithm. Initially, we calculate edges in an image using a hat shaped kernel, then we detect lanes using the CNN combined with the RANSAC. In the training process of the CNN, input data consists of edge images and target data is images that have real white color lanes on an otherwise black background. The CNN structure consists of 8 layers with 3 convolutional layers, 2 subsampling layers and multi-layer perceptron (MLP) of 3 fully-connected layers. Convolutional and subsampling layers are hierarchically arranged to form a deep structure. Our proposed lane detection algorithm successfully eliminates noise lines and was found to perform better than other formal line detection algorithms such as RANSAC

• 정보통신설비학회논문지
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• 제8권4호
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• pp.170-181
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• 2009

When a slow-moving vehicle occupies one of the lanes of a multi-lane highway, it often causes queuing behind, unlike one is caused by an actual stoppage on that lane. This happens when the traffic flow rate upstream from the slow vehicle exceeds a certain critical value. This phenomena is called as the Moving Bottleneck, defined by Gazis and Herman (1992), Newell (1998) [3], and Munoz and Daganzo (2002), who conducted the flow estimates of upstream and downstream and considered slow-moving vehicle speed and the flow ratio exceeding slow vehicle and the microscopic traffic flow characteristics of moving bottleneck. But, a study of delay on moving bottleneck was not conducted until now. So this study provides a average delay time model related to upstream flow and the speed of slow vehicle. We have chosen the two-lane highway and homogeneous traffic flow. A slow-moving vehicle occupies one of the two lanes. Average delay time value is a result of AIMSUN[9], the microscopic traffic flow simulator. We developed a multiple regression model based on that value. Average delay time has a high value when the speed of slow vehicle is decreased and traffic flow is increased. Conclusively, the model is formulated by the negative exponential function.

• 한국도로학회논문집
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• 제20권1호
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• pp.117-126
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• 2018

PURPOSES : The purpose of this paper is to analyze the change in lane reflection performance through lane washing and sweeping on highway lanes. METHODS : This paper compared and analyzed the changes in lane reflection performance before and after lane washing and sweeping. The research method was as follows. First, we selected four research sites on the Gyeong-bu Highway. Second, the parameters affecting lane reflection performance are classified into luminance, brightness, and number of glass beads. Third, the change in reflection performance was measured after washing /sweeping at the same place after studying 60m of the unwashed/unswept area. Fourth, the measurement results were compared and analyzed before and after lane washing/sweeping. RESULTS : The results of this study are as follows. First, lane washing improved the luminance and brightness by 4.2~21.4% and 1.4~5.1%, respectively, and reduced the number of glass beads per wash by 0.2~1.2%. Second, lane sweeping improved the luminance and brightness by 2.3~8.5% and 0.8~2.3%, respectively, and reduced the number of glass beads per sweep by 0.8~4.9%. CONCLUSIONS : By comparing the results of lane washing and sweeping, it was found that compared to lane sweeping, lane washing improved the luminance and fewer glass beads were dropped.

• 화약ㆍ발파
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• 제22권3호
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• pp.65-70
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• 2004

최근 신설되는 도로의 경우 고속화/직선화로 인하여 터널의 연장 및 평균터널 길이, 3차선이상의 대 단면 터널이 날로 증가하고 있어 이에 따른 굴착 효율 극대화가 필요한 시점에 있다. 사패산 터널은 약 4km의 4차선 대단면 도로터널로, 환경문제로 인해 늦춰진 공기를 단축시키기 위하여 터널 굴착 시 굴진효율에 가장 큰 영향요소인 굴진장과 여굴관리, 발파효율의 개선을 위한 다양한 신 공법이 적용되고 있다. 본 논문은 당 현장에서 시도되고 있는 신 공법 중, 새로운 형태의 폭약인 Bulk 폭약에 대하여 소개하고, Bulk 폭약의 대 단면 터널 적용에 대한 효율을 검증하고자 하였다.

• 한국ITS학회 논문지
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• 제8권3호
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• pp.42-51
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• 2009

우리나라는 고속도로 차로 수에 따라 차종별로 통행차로를 지정하는 제도를 운영하고 있으며, 그 동안 제도의 유효성 논란 속에 폐지와 운영을 반복하며 시행되고 있다. 본 논문에서는 제도의 유효성을 검증하기 위해 고속도로 10개 구간을 대상으로 차로통행방법 위반율과 교통사고와의 연관성을 분석하였다. 그 결과 양(+)의 상관관계가 있는 것으로 나타나 위반차량에 대한 적극적인 단속이 요구되며, 본 논문에서는 차량번호판의 영상인식에 기반한 자동단속시스템 구축 방안을 제시하였다.

• 정보처리학회논문지B
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• 제8B권6호
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• pp.705-717
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• 2001

이 논문에서는 카메라로 연속으로 촬영한 일련의 그레이레벨 영상으로부터 전방의 차량을 포착하기 위한 빠른 차선검출방법을 제안한다. 개별 영상에서 가려지지 않는 제한된 영역을 대상으로 차선의 위치를 검출하고, 에지 영상을 이용하여 차선의 기울기를 구한다. 이를 근거로 차량이 존재할 가능성이 있는 관심영역을 구하고 그 영역 내에서 에지 성분을 이용하여 구조적 방법으로 전방 차량의 위치를 포착한다. 제안된 방식의 효과를 검증하기 위해 노트북 PC와 PC용 CCD 카메라로 도로에서의 영상을 촬영하고 차선검출알고리즘을 적용한 처리 시간, 정확도, 차량검지 등의 결과를 보인다.

• Wind and Structures
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• 제14권1호
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• pp.55-70
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• 2011

This study investigates the design criteria required for wind barriers to protect vehicles running on an expressway under a high side wind. At the first stage of this study, the lateral deviations of vehicles in crosswinds were computed from the commercial software, CarSim and TruckSim, and the critical wind speeds for a car accident were then evaluated from a predefined car accident index. The critical wind speeds for driving stability were found to be 35 m/s for a small passenger car, yet 30 m/s for a truck and a bus. From the wind tunnel tests, the minimum height of a wind barrier required to reduce the wind speed by 50% was found to be 12.5% of the road width. In the case of parallel bridges, the placement of two edge wind barriers plus one wind barrier at center was recommended for a separation distance larger than 20 m (four lanes) and 10 m (six lanes) respectively, otherwise two wind barriers were recommended.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1997년도 춘계 학술대회 발표집
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• pp.81-85
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• 1997

In a virtual environment, agents must demonstrate some degree of realism and interactivity. This paper discusses the algorithm that enables agents to navigate a virtual road network realistically and interactively. The road description files written in this language provide the information of road environments to the navigating agents and the scene visualizer. We call this navigating agent in the road an ambient car. The ambient cars must follow the traffic rules as human does. To do this, the ambient car should continuously check its circumstances, such as, the traffic lights, lanes, road signs, and other ambient cars. Because of the huge scale of road network and the large number of ambient cars, the algorithm considers only the area where the participant is currently located. By this locality, the performance of the whole system does not fluctuate much in different situations. The behavior of ambient cars according to the predefined rules may appear monotonous. We added probability distribution functions to introduce some randomness. We implemented the above idea on silicon Graphics Indigo 2 workstation. The ambient car exhibited its awareness of lanes, traffic lights, and other cars. The participants could hardly distinguish between a human-controlled car and computer-controlled ambient car generated by the algorithm.

• Design & Manufacturing
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• 제11권3호
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• pp.13-18
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• 2017

The injection molding analysis of VCM (Voice Coil Motor) housing for smart phone cameras were performed. We conducted the analysis in terms of injection molding pressure, the formation of weld lines, flow marks, and flow patterns. The goal of the analysis was targeted for the prediction of the optimal gate locations. Because the quality of VCM housing is strongly dependent on the precise control of the camera lens by its nature, we focused on the lens guiding lanes in the VCM housing. We first calculated the maximum injection molding pressure in terms of the filled volumes. The injection molding pressure were calculated within 146MPa at about 90% volume filled. We also investigated the possibility of the occurrence of design-related defects such flow marks, weld lines. Filling patterns regarding the design of the gate locations were delineated to find the weld lines. Throughout the simulations, the final deformations of the lens guiding lanes for the VCM housing were calculated. The deformations distribute ranging from $0.5{\mu}m$ to $2.50{\mu}m$, which were used to find the optimal design of the gates.