• 제목/요약/키워드: density map

검색결과 562건 처리시간 0.027초

오차 예측과 격자밀도 지도를 이용한 적응 Delaunay 격자생성방법 (Adaptive Delaunay Mesh Generation Technique Based on a Posteriori Error Estimation and a Node Density Map)

  • 홍진태;이석렬;박철현;양동열
    • 소성∙가공
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    • 제13권4호
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    • pp.334-341
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    • 2004
  • In this study, a remeshing algorithm adapted to the mesh density map using the Delaunay mesh generation method is developed. In the finite element simulation of forging process, the numerical error increases as the process goes on because of discrete property of the finite elements and distortion of elements. Especially, in the region where stresses and strains are concentrated, the numerical error will be highly increased. However, it is not desirable to use a uniformly fine mesh in the whole domain. Therefore, it is necessary to reduce the analysis error by constructing locally refined mesh at the region where the error is concentrated such as at the die corner. In this paper, the point insertion algorithm is used and the mesh size is controlled by using a mesh density map constructed with a posteriori error estimation. An optimized smoothing technique is adopted to have smooth distribution of the mesh and improve the mesh element quality.

LDPC 복호와 MAP 등화기를 결합한 DVB-T2 터보 등화기법의 성능분석 (Performance Analysis of DVB-T2 Turbo Equalization with LDPC and MAP Detector)

  • 태청송;한동석
    • 방송공학회논문지
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    • 제15권5호
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    • pp.665-671
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    • 2010
  • 본 논문에서는 DVB-T2 (digital video broadcasting for terrestrial - 2nd generation) 시스템을 위한 터보 등화기를 제안 하고 그 성능을 분석하였다. 터보 등화기는 MAP (maximum a posteriori) 검파기와 LDPC (low density parity check) 복호기로 구성 되었다. LS(least square) 채널 추정 기반 SISO (soft-input-soft-output) MAP 등화기는 LDPC 복호기에 외래 확률 값을 준다. 터보 등화기의 성능을 반복 횟수에 따라 컴퓨터 실험을 통하여 분석하였다.

An AFLP-based Linkage Map of Japanese Red Pine (Pinus densiflora) Using Haploid DNA Samples of Megagametophytes from a Single Maternal Tree

  • Kim, Yong-Yul;Choi, Hyung-Soon;Kang, Bum-Yong
    • Molecules and Cells
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    • 제20권2호
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    • pp.201-209
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    • 2005
  • We have constructed an AFLP-based linkage map of Japanese red pine (Pinus densiflora Siebold et Zucc.) using haploid DNA samples of 96 megagametophytes from a single maternal tree, selection clone Kyungbuk 4. Twenty-eight primer pairs generated a total of 5,780 AFLP fragments. Five hundreds and thirteen fragments were verified as genetic markers with two alleles by their Mendelian segregation. At the linkage criteria LOD 4.0 and maximum recombination fraction 0.25(${\theta}$), a total of 152 markers constituted 25 framework maps for 19 major linkage groups. The maps spanned a total length of 2,341 cM with an average framework marker spacing of 18.4 cM. The estimated genome size was 2,662 cM. With an assumption of equal marker density, 82.2% of the estimated genome would be within 10 cM of one of the 230 linked markers, and 68.1% would be within 10 cM of one of the 152 framework markers. We evaluated map completeness in terms of LOD value, marker density, genome length, and map coverage. The resulting map will provide crucial information for future genomic studies of the Japanese red pine, in particular for QTL mapping of economically important breeding target traits.

라이다 점군 밀도에 강인한 맵 오차 측정 기구 설계 및 알고리즘 (Map Error Measuring Mechanism Design and Algorithm Robust to Lidar Sparsity)

  • 정상우;정민우;김아영
    • 로봇학회논문지
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    • 제16권3호
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    • pp.189-198
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    • 2021
  • In this paper, we introduce the software/hardware system that can reliably calculate the distance from sensor to the model regardless of point cloud density. As the 3d point cloud map is widely adopted for SLAM and computer vision, the accuracy of point cloud map is of great importance. However, the 3D point cloud map obtained from Lidar may reveal different point cloud density depending on the choice of sensor, measurement distance and the object shape. Currently, when measuring map accuracy, high reflective bands are used to generate specific points in point cloud map where distances are measured manually. This manual process is time and labor consuming being highly affected by Lidar sparsity level. To overcome these problems, this paper presents a hardware design that leverage high intensity point from three planar surface. Furthermore, by calculating distance from sensor to the device, we verified that the automated method is much faster than the manual procedure and robust to sparsity by testing with RGB-D camera and Lidar. As will be shown, the system performance is not limited to indoor environment by progressing the experiment using Lidar sensor at outdoor environment.

위성영상과 음영기복도를 이용한 오대산 지역 진앙의 위치와 선구조선의 관계 분석 (The Relationship Analysis between the Epicenter and Lineaments in the Odaesan Area using Satellite Images and Shaded Relief Maps)

  • 차성은;지광훈;조현우;김은지;이우균
    • 한국지리정보학회지
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    • 제19권3호
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    • pp.61-74
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    • 2016
  • 본 연구에서는 LANDSAT 8호, KOMPSAT 2호 위성영상과 1/25,000 수치지형도를 기반으로 작성된 음영기복도를 이용하여 2007년 1월 20일 오대산 지역에서 발생한 약 4.8의 중규모 지진과 선구조선의 관계를 분석하였다. 대부분의 선행연구는 지체구조와 관련된 선구조선 분석 연구를 하였으며, 주로 2차원의 위성영상과 음영기복도를 활용하였기에 지형의 기복 등에 대한 판독이 어려워 선구조선 추출이 제한적이었다. 본 연구에서는 이를 보완하기 위해 수치표고모델(Digital Elevation Model; DEM)을 기반으로 작성한 3차원 입체 영상과 수계망 분석을 통해 지형의 기복, 수계의 연결성 등을 판독해 선구조선을 추출하여, 2차원 영상에서 나타나는 시각적인 판독에 의한 오류를 최소화한 선구조선 판독도를 작성하였다. 또한 진앙에 대한 선구조선의 통계 요소별 밀도를 추정하기 위해 spline 내삽법을 이용하여 선구조선의 빈도, 교차점, 길이에 대한 밀도를 계산하였다. 그리고 진앙에서의 선구조선 밀도가 얼마나 밀집되어 있는지 정량적으로 표현하기 위하여 각 격자 내의 선구조선 밀도에 대해 최대 선구조선 밀도로 나누는 상대밀도 값(Value of the Relative Density; VRD)을 계산하는 알고리즘을 개발하여 밀도도(density map)를 작성하였다. 각 영상의 진앙에서의 VRD는 최소 약 0.60에서 최대 약 0.90으로 나타났지만, 각 영상별 광원의 고도각과 방위각이 차이가 있어 영상별 VRD보다 통계 요소별 VRD의 평균치를 사용하였다. 그 결과, 빈도의 평균 VRD는 약 0.85로 교차점과 길이의 평균 VRD보다 약 21% 높게 나타나, 선구조선의 빈도 요소가 진앙의 위치와의 관계가 가장 밀접함을 확인하였다. 이와 같이 3차원 영상의 선구조선 추출을 통한 밀도 분석 기술은 향후 지진 발생 가능 지역 분석에 기초자료로써의 의미가 있을 것으로 기대된다.

WindSim을 이용한 싱가폴 바람지도 작성 (Wind Mapping of Singapore Using WindSim)

  • 김현구
    • 한국환경과학회지
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    • 제20권7호
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    • pp.839-843
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    • 2011
  • We have established a wind map of Singapore, a city-state characterized its land cover by urban buildings to confirm a possibility of wind farm development. As a simple but useful approximation of urban canopy, a zero-plane displacement concept was employed. The territory is divided into 15 sectors having similar urban building layouts, and zero-plane displacement, equivalent roughness height at each sector was calculated to setup a terrain boundary condition. Annual mean wind speed and mean wind power density map were drawn by a CFD micrositing model, WindSim where Changi International Airport wind data was used as an in-situ measurement. Unfortunately, predicted wind power density does not exceed 80 $W/m^2$ at 50 m above ground level which would not sufficient for wind power generation. However, the established Singapore wind map is expected to be applied for wind environment assessment and urban planning purpose.

A NONEXISTENCE THEOREM FOR STABLE EXPONENTIALLY HARMONIC MAPS

  • Koh, Sung-Eun
    • 대한수학회보
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    • 제32권2호
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    • pp.211-214
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    • 1995
  • Let M and N be compact Riemannian manifolds and $f : M \to N$ be a smooth map. Following J. Eells, f is exponentially harmonic if it represents a critical point of the exponential energy integral $$ E(f) = \int_{M} exp(\left\$\mid$ df \right\$\mid$^2) dM $$ where $(\left\ df $\mid$\right\$\mid$^2$ is the energy density defined as $\sum_{i=1}^{m} \left\$\mid$ df(e_i) \right\$\mid$^2$, m = dimM, for orthonormal frame $e_i$ of M. The Euler- Lagrange equation of the exponential energy functional E can be written $$ exp(\left\$\mid$ df \right\$\mid$^2)(\tau(f) + df(\nabla\left\$\mid$ df \right\$\mid$^2)) = 0 $$ where $\tau(f)$ is the tension field along f. Hence, if the energy density is constant, every harmonic map is exponentially harmonic and vice versa.

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볼엔드밀 경사면 가공에서 절삭력 맵을 이용한 평균절삭력 예측 (Mean Cutting Force Prediction in Ball-End Milling of Slanted Surface Using Force Map)

  • 김규만;주종남
    • 한국정밀공학회지
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    • 제15권12호
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    • pp.212-219
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    • 1998
  • During machining of dies and molds with sculptured surfaces. the cutter contact area changes continuously and results in cutting force variation. In order to implement cutting force prediction model into a CAM system, an effective and fast method is necessary. In this paper. a new method is proposed to predict mean cutting force. The cutter contact area in the spherical part of the cutter is obtained using Z-map, and expressed by the grids on the cutter plane orthogonal to the cutter axis. New empirical cutting parameters were defined to describe the cutting force in the spherical part of cutter. Before the mean cutting force calculation, the cutting force density in each grid is calculated and saved to force map on the cutter plane. The mean cutting force in an arbitrary cutter contact area can be easily calculated by summing up the cutting force density of the engaged grid of the force map. The proposed method was verifed through the slotting and slanted surface machining with various inclination angles. It was shown that the mean force can be calculated fast and effectively through the proposed method for any geometry including sculptured surfaces with cusp marks and holes.

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자율주행 인지를 위한 마코브 모델 기반의 정지 장애물 추정 연구 (Markov Model-based Static Obstacle Map Estimation for Perception of Automated Driving)

  • 윤정식;이경수
    • 자동차안전학회지
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    • 제11권2호
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    • pp.29-34
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    • 2019
  • This paper presents a new method for construction of a static obstacle map. A static obstacle is important since it is utilized to path planning and decision. Several established approaches generate static obstacle map by grid method and counting algorithm. However, these approaches are occasionally ineffective since the density of LiDAR layer is low. Our approach solved this problem by applying probability theory. First, we converted all LiDAR point to Gaussian distribution to considers an uncertainty of LiDAR point. This Gaussian distribution represents likelihood of obstacle. Second, we modeled dynamic transition of a static obstacle map by adopting the Hidden Markov Model. Due to the dynamic characteristics of the vehicle in relation to the conditions of the next stage only, a more accurate map of the obstacles can be obtained using the Hidden Markov Model. Experimental data obtained from test driving demonstrates that our approach is suitable for mapping static obstacles. In addition, this result shows that our algorithm has an advantage in estimating not only static obstacles but also dynamic characteristics of moving target such as driving vehicles.

드론 방제의 최적화를 위한 딥러닝 기반의 밀도맵 추정 (Density map estimation based on deep-learning for pest control drone optimization)

  • 성백겸;한웅철;유승화;이춘구;강영호;우현호;이헌석;이대현
    • 드라이브 ㆍ 컨트롤
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    • 제21권2호
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    • pp.53-64
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    • 2024
  • Global population growth has resulted in an increased demand for food production. Simultaneously, aging rural communities have led to a decrease in the workforce, thereby increasing the demand for automation in agriculture. Drones are particularly useful for unmanned pest control fields. However, the current method of uniform spraying leads to environmental damage due to overuse of pesticides and drift by wind. To address this issue, it is necessary to enhance spraying performance through precise performance evaluation. Therefore, as a foundational study aimed at optimizing drone-based pest control technologies, this research evaluated water-sensitive paper (WSP) via density map estimation using convolutional neural networks (CNN) with a encoder-decoder structure. To achieve more accurate estimation, this study implemented multi-task learning, incorporating an additional classifier for image segmentation alongside the density map estimation classifier. The proposed model in this study resulted in a R-squared (R2) of 0.976 for coverage area in the evaluation data set, demonstrating satisfactory performance in evaluating WSP at various density levels. Further research is needed to improve the accuracy of spray result estimations and develop a real-time assessment technology in the field.