• Title/Summary/Keyword: Geometric Data

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Extracting Three-Dimensional Geometric Information of Roads from Integrated Multi-sensor Data using Ground Vehicle Borne System (지상 이동체 기반의 다중 센서 통합 데이터를 활용한 도로의 3차원 기하정보 추출에 관한 연구)

  • Kim, Moon-Gie;Sung, Jung-Gon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.11 no.3
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    • pp.68-79
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    • 2008
  • Ground vehicle borne system which is named RoSSAV(Road Safety Survey and Analysis Vehicle) developed in KICT(Korea Institute of Construction Technology) can collect road geometric data. This system therefore is able to evaluate the road safety and analyze road deficient sections using data collected along the roads. The purpose of this study is to extract road geometric data for 3D road modeling in dangerous road section and The system should be able to quickly provide more accurate data. Various sensors(circular laser scanner, GPS, INS, CCD camera and DMI) are installed in moving object and collect road environment data. Finally, We extract 3d road geometry(center, boundary), road facility and slope using integrated multi-sensor data.

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3-Dimensional Concurrent Geometric Modeling on High Speed Network (초고속 통신망상에서 3차원 동시 형상 설계)

  • 정운용;한순흥
    • The Journal of Society for e-Business Studies
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    • v.1 no.1
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    • pp.141-157
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    • 1996
  • Data sharing is a major challenge to implement CALS. STEP is the international standard for the product model data exchange among heterogeneous systems and plays a key role in CALS. Advances in computer networks are rapidly changing the product development processes. The network oriented modeling system premises to integrate design activities across the enterprise. To achieve goals of CALS 3-dimensional concurrent modeling that complies international standard is required since integrity and common perception of product data can be assured. This paper presents 3-dimensional concurrent geometric modeling on high speed network using STEP and methodologies.

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Modified Delaunay Triangulation Based on Data Structure of Geometric Modeller (형상 모델러의 자료구조에 의한 수정 Delaunay 삼각화)

  • Chae E.-M.;Sah J.-Y.
    • Journal of computational fluids engineering
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    • v.2 no.2
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    • pp.97-103
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    • 1997
  • A modified Delaunay triangulation technique is tested for complicated computational domain. While a simple geometry. both in topology and geometry, has been well discretized into triangular elements, a complex geometry having difficulty in triangulation had to be divided into small sub-domains of simpler shape. The present study presents a modified Delaunay triangulation method based on the data structure of geometric modeller. This approach greatly enhances the reliability of triangulation, especially in complicated computational domain. We have shown that efficiency of Delaunay triangulation can be much improved by using both the GUI (Graphic User Interface) and OOP (Object-Oriented Programming).

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A new extended Birnbaum-Saunders model with cure fraction: classical and Bayesian approach

  • Ortega, Edwin M.M.;Cordeiro, Gauss M.;Suzuki, Adriano K.;Ramires, Thiago G.
    • Communications for Statistical Applications and Methods
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    • v.24 no.4
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    • pp.397-419
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    • 2017
  • A four-parameter extended fatigue lifetime model called the odd Birnbaum-Saunders geometric distribution is proposed. This model extends the odd Birnbaum-Saunders and Birnbaum-Saunders distributions. We derive some properties of the new distribution that include expressions for the ordinary moments and generating and quantile functions. The method of maximum likelihood and a Bayesian approach are adopted to estimate the model parameters; in addition, various simulations are performed for different parameter settings and sample sizes. We propose two new models with a cure rate called the odd Birnbaum-Saunders mixture and odd Birnbaum-Saunders geometric models by assuming that the number of competing causes for the event of interest has a geometric distribution. The applicability of the new models are illustrated by means of ethylene data and melanoma data with cure fraction.

Ship Detection by Satellite Data: Radiometric and Geometric Calibrations of RADARS AT Data (위성 데이터에 의한 선박 탐지: RADARSAT의 대기보정과 기하보정)

  • Yang, Chan-Su
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.10 no.1 s.20
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    • pp.1-7
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    • 2004
  • RADARSAT is one of many possible data sources that can play an important role in marine surveillance including ship detection because radar sensors have the two primary advantages: all-weather and day or night imaging. However, atmospheric effects on SAR imaging can not be bypassed and any remote sensing image has various geometric distortions, In this study, radiometric and geometric calibrations for RADARSAT/SAT data are tried using SGX products georeferenced as level 1. Even comparison of the near vs. far range sections of the same images requires such calibration Radiometric calibration is performed by compensating for effects of local illuminated area and incidence angle on the local backscatter, Conversion method of the pixel DNs to beta nought and sigma nought is also investigated. Finally, automatic geometric calibration based on the 4 pixels from the header file is compared to a marine chart. The errors for latitude and longitude directions are 300m and 260m, respectively. It can be concluded that the error extent is acceptable for an application to open sea and can be calibrated using a ground control point.

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A Geometric Compression Method Using Dominant Points for Transmission to LEO Satellites

  • Ko, Kwang Hee;Ahn, Hyo-Sung;Wang, Semyung;Choi, Sujin;Jung, Okchul;Chung, Daewon;Park, Hyungjun
    • International Journal of Aeronautical and Space Sciences
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    • v.17 no.4
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    • pp.622-630
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    • 2016
  • In the operation of a low earth orbit satellite, a series of antenna commands are transmitted from a ground station to the satellite within a visibility window (i.e., the time period for which an antenna of the satellite is visible from the station) and executed to control the antenna. The window is a limited resource where all data transmission is carried out. Therefore, minimizing the transmission time for the antenna commands by reducing the data size is necessary in order to provide more time for the transmission of other data. In this paper, we propose a geometric compression method based on B-spline curve fitting using dominant points in order to compactly represent the antenna commands. We transform the problem of command size reduction into a geometric problem that is relatively easier to deal with. The command data are interpreted as points in a 2D space. The geometric properties of the data distribution are considered to determine the optimal parameters for a curve approximating the data with sufficient accuracy. Experimental results demonstrate that the proposed method is superior to conventional methods currently used in practice.

Ensemble Learning for Solving Data Imbalance in Bankruptcy Prediction (기업부실 예측 데이터의 불균형 문제 해결을 위한 앙상블 학습)

  • Kim, Myoung-Jong
    • Journal of Intelligence and Information Systems
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    • v.15 no.3
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    • pp.1-15
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    • 2009
  • In a classification problem, data imbalance occurs when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. This paper proposes a Geometric Mean-based Boosting (GM-Boost) to resolve the problem of data imbalance. Since GM-Boost introduces the notion of geometric mean, it can perform learning process considering both majority and minority sides, and reinforce the learning on misclassified data. An empirical study with bankruptcy prediction on Korea companies shows that GM-Boost has the higher classification accuracy than previous methods including Under-sampling, Over-Sampling, and AdaBoost, used in imbalanced data and robust learning performance regardless of the degree of data imbalance.

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High-Capacity and Robust Watermarking Scheme for Small-Scale Vector Data

  • Tong, Deyu;Zhu, Changqing;Ren, Na;Shi, Wenzhong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.12
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    • pp.6190-6213
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    • 2019
  • For small-scale vector data, restrictions on watermark scheme capacity and robustness limit the use of copyright protection. A watermarking scheme based on robust geometric features and capacity maximization strategy that simultaneously improves capacity and robustness is presented in this paper. The distance ratio and angle of adjacent vertices are chosen as the watermark domain due to their resistance to vertex and geometric attacks. Regarding watermark embedding and extraction, a capacity-improved strategy based on quantization index modulation, which divides more intervals to carry sufficient watermark bits, is proposed. By considering the error tolerance of the vector map and the numerical accuracy, the optimization of the capacity-improved strategy is studied to maximize the embedded watermark bits for each vertex. The experimental results demonstrated that the map distortion caused by watermarks is small and much lower than the map tolerance. Additionally, the proposed scheme can embed a copyright image of 1024 bits into vector data of 150 vertices, which reaches capacity at approximately 14 bits/vertex, and shows prominent robustness against vertex and geometric attacks for small-scale vector data.

Vessel traffic geometric probability approaches with AIS data in active shipping lane for subsea pipeline quantitative risk assessment against third-party impact

  • Tanujaya, Vincent Alvin;Tawekal, Ricky Lukman;Ilman, Eko Charnius
    • Ocean Systems Engineering
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    • v.12 no.3
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    • pp.267-284
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    • 2022
  • A subsea pipeline designed across active shipping lane prones to failure against external interferences such as anchorage activities, hence risk assessment is essential. It requires quantifying the geometric probability derived from ship traffic distribution based on Automatic Identification System (AIS) data. The actual probability density function from historical vessel traffic data is ideal, as for rapid assessment, conceptual study, when the AIS data is scarce or when the local vessels traffic are not utilised with AIS. Recommended practices suggest the probability distribution is assumed as a single peak Gaussian. This study compares several fitted Gaussian distributions and Monte Carlo simulation based on actual ship traffic data in main ship direction in an active shipping lane across a subsea pipeline. The results shows that a Gaussian distribution with five peaks is required to represent the ship traffic data, providing an error of 0.23%, while a single peak Gaussian distribution and the Monte Carlo simulation with one hundred million realisation provide an error of 1.32% and 0.79% respectively. Thus, it can be concluded that the multi-peak Gaussian distribution can represent the actual ship traffic distribution in the main direction, but it is less representative for ship traffic distribution in other direction. The geometric probability is utilised in a quantitative risk assessment (QRA) for subsea pipeline against vessel anchor dropping and dragging and vessel sinking.

A Visual Effect according to Pants Style and Geometric Pattern - Using a 3D Virtual Garment System - (가상착의 시스템을 이용한 팬츠 스타일과 기하학 무늬의 특성에 따른 시각적 효과)

  • Park, Woo Mee
    • Fashion & Textile Research Journal
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    • v.15 no.4
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    • pp.504-513
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    • 2013
  • This study evaluates the difference of visual effect according to pant style and geometric pattern. The researcher made 28 stimuli-combination of four pant Stiles (classic, baggy, skinny, and bell-bottom) and seven geometric pattern (large vertical stripe, small vertical stripe, large horizontal stripe, small horizontal stripe, large check, small check, and hound's tooth check). The test involved 96 female college students. The stimuli were made with the i-Designer computer program. The panels tested the computer screen images of all manikins wearing pants. A 7-point scale was used to evaluate each image. For the data analysis, ANOVA and Duncan-test were applied along with an SPSS program. The results of this study are as follows. Three factors (lower-body compensation, abdomen highlight, and length compensation) influenced the visual effect pant styles and geometric patterns. The skinny style and large vertical stripe evaluated positively in elongated height and leg length and a slimmer overall body. It was shown that the vertical stripe pattern was evaluated as more positive than the horizontal stripe pattern in the visual effect; particularly, the results showed distinct aspects in the classic pants style. The mutual influence of the visual effect (according to pants style and geometric pattern) were indicated as two factors of lower-body compensation and length compensation. A more positive visual effects resulted in a higher mutual influence on pant style and geometric pattern.