• Korean Journal of Computational Design and Engineering
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• v.5 no.4
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• pp.293-300
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• 2000

The non-manifold geometric modeling technique is to improve design process and to Integrate design, analysis, and manufacturing by handling mixture of wireframe model, surface model, and solid model in a single data structure. For the non-manifold geometric modeling, Euler operators and other high level modeling methods are necessary. Boolean operation is one of the representative modeling method for the non-manifold geometric modeling. This thesis studies Boolean operations of non-manifold model with the data structure of selective storage. The data structure of selective storage is improved non-manifold data structure in that existing non-manifold data structures using ordered topological representation method always store non-manifold information even if edges and vortices are in the manifold situation. To implement Boolean operations for non-manifold model, intersection algorithm for topological cells of three different dimensions, merging and selection algorithm for three dimensional model, and Open Inventor(tm), a 3D toolkit from SGI, are used.

• Bulletin of the Korean Chemical Society
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• v.30 no.11
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• pp.2717-2722
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• 2009

The use of the classification and regression tree (CART) methodology was studied in a quantitative structure-activity relationship (QSAR) context on a data set consisting of the binding affinities of 39 imidazobenzodiazepines for the α1 benzodiazepine receptor. The 3-D structures of these compounds were optimized using HyperChem software with semiempirical AM1 optimization method. After optimization a set of 1481 zero-to three-dimentional descriptors was calculated for each molecule in the data set. The response (dependent variable) in the tree model consisted of the binding affinities of drugs. Three descriptors (two topological and one 3D-Morse descriptors) were applied in the final tree structure to describe the binding affinities. The mean relative error percent for the data set is 3.20%, compared with a previous model with mean relative error percent of 6.63%. To evaluate the predictive power of CART cross validation method was also performed.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.6
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• pp.437-452
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• 2002

The Metropolitan Tracer Experiment (METREX) was performed over the Washington, D.C. area using two inert, non-deposition perfluorocarbon gases for over 1 year period (November 1983∼December 1984). Two perfluorocarbon gas tracers (PDCH, PMCH) were released simultaneously at intervals of every 36 hours for 6 hours, regardless of the meteorological conditions in metropolitan area. Samples were collected continuously for 8 hours at a central downtown and two adjacent suburban locations. Monthly air samples were collected at 93 sites across the whole region (at urban, suburban, and rural locations). The purpose of this study is to simulate INPUFF and ISCST model using METREX data, and to compare calculated and observed concentrations. In the case of INPUFF simulation, two meteorological input data were used. One is result data from wind field model which was calculated by diagnostic wind model (DWM), the other is meteorological data observed at single station. Here, three kinds of model calculation were performed during April and July 1984; they include (1) INPUFF model using DWM data (2) INPUFF model using single meteorological data (3) ISCST model. The monthly average concentration data were used for statistic analysis and to draw their horizontal distribution patterns. Eight-hour-averaged concentration was used to describe movement of puff during the episode period. The results showed that the concentrations calculated by puff model (INPUFF) were better than plume model (ISCST). In the case of puff model (INPUFF), a model run using wind field data produced better results than that derived by single meteorological data.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.3
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• pp.254-262
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• 2015

This paper presents 3D collision deformation modelling methodologies using photogrammetry for reconstruction of vehicle accidents. A vehicle's deformation shape in collision provides important information on how the vehicle collided. So effective measurement(scanning) and construction of a corresponding appropriate model are essential in the analysis of collision deformation shape for obtaining much information related to collision accident. Two measurement methods were used in this study: Indirect-photogrammetry which requires relatively small amount of photos or videos, and direct-photogrammetry which requires large amount of photos directly taken for the purpose of 3D modelling. When the indirect-photogrammetry method, which was mainly used in this study, lacked enough photographic information, already secured 2D numerical deformation data was used as a compensation. This made 3D collision deformation modelling for accident reconstruction analysis possible.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.210-214
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• 2008

It is actually impossible to model and store all objects which exist in real home environment into robot's database in advance. To resolve this problem, this paper proposes new object modeling method that can be available for robot self-modeling, which is capable of estimating whole model's shape from partial surface data using Generic Model. And this whole produce is conducted to cylindrical objects like cup, bottles and cans which can be easily found at indoor environment. The detailed process is firstly we obtain cylinder's initial principle axis using points coordinates and normal vectors from object's surface after we separate cylindrical object from 3D image. This 3D image is obtained from 3D sensor. And second, we compensate errors in the principle axis repeatedly. Then finally, we do modeling whole cylindrical object using cross sectional principal axis and its radius To show the feasibility of the algorithm, We implemented it and evaluated its accuracy.

• Journal of Environmental Impact Assessment
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• v.20 no.4
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• pp.575-583
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• 2011

In this study, the plausible grid size was estimated to increase for efficiency of reservoir management using 3 dimensional water quality model. To validate utilization of a real time water quality management tool, ELCOM-CAEDYM model was applied to Soyang reservoir in korea. 100m grid size can represent the real topography and take out exact analysis results. $400{\times}400m$ grid can be easily used to analysis because of data capacity. Consequently, the grid size of 200m or 300m was recommended to establish 3D model considering the required simulation time and the irrelevance between horizontal grid size and vertical distribution for temperature and turbidity analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.2
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• pp.419-424
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• 2009

This paper show about the possibility of practical application after building VR(virtual reality) data based on Airborne LiDAR data which determines complicated topography quickly for the 3D-GIS construction. In this paper, we collected Airborne LiDAR data, digital map, serial photo and a basic design. The results are expected some effective determination by 3D-GIS construction based on LiDAR data. Hereafter, because the research will be able to be given quickly topography information on ubiquitous environment the field of construction and GIS will be able to be helped.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1099-1104
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• 2007

The visual implementation of 3-dimensional national environment is focused by the requirement and importance in the fields such as, national development plan, telecommunication facility deployment plan, railway construction, construction engineering, spatial city development, safety and disaster prevention engineering. The currently used DEM system using contour lines, which embodies national geographic information based on the 2-D digital maps and facility information has limitation in implementation in reproducing the 3-D spatial city. Moreover, this method often neglects the altitude of the rail way infrastructure which has narrow width and long length. There it is needed to apply laser measurement technique in the spatial target object to obtain accuracy. Currently, the LiDAR data which combines the laser measurement skill and GPS has been introduced to obtain high resolution accuracy in the altitude measurement. In this paper, we first investigate the LiDAR based researches in advanced foreign countries, then we propose data a generation scheme and an algorithm for the optimal manage and synthesis of railway facility system in our 3-D spatial terrain information. For this object, LiDAR based height data transformed to DEM, and the realtime unification of the vector via digital image mapping and raster via exactness evaluation is transformed to make it possible to trace the model of generated 3-dimensional railway model with long distance for 3D tract model generation.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.211-212
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• 2007

Pose-variation factors present a significant problem in 2D face recognition. To solve this problem, there are various approaches for a 3D face acquisition system which was able to generate multi-view images. However, this created another pose estimation problem in terms of normalizing the 3D face data. This paper presents a 3D head pose-normalization method using 2D and 3D interaction. The proposed method uses 2D information with the AAM(Active Appearance Model) and 3D information with a 3D normal vector. In order to verify the performance of the proposed method, we designed an experiment using 2.5D face recognition. Experimental results showed that the proposed method is robust against pose variation.

• Wind and Structures
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• v.38 no.5
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• pp.381-398
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• 2024

This study presents a mode analysis of 3D turbulent velocity data around a square-section building model to identify the dynamic system for Kármán-type vortex shedding. Proper orthogonal decomposition (POD) was first performed to extract the significant 3D modes. Magnitude-squared coherence was then applied to detect the phase consistency between the modes, which were roughly divided into three groups. Group 1 (modes 1-4) depicted the main vortex shedding on the wake of the building, with mode 2 being controlled by the inflow fluctuation. Group 2 exhibited complex wake vortexes and single-sided vortex phenomena, while Group 3 exhibited more complicated phenomena, including flow separation. Subsequently, a third-order polynomial regression model was used to fit the dynamics system of modes 1, 3, and 4, which revealed average trend of the state trajectory. The two limit cycles of the regression model depicted the two rotation directions of Kármán-type vortex. Furthermore, two characteristic periods were identified from the trajectory generated by the regression model, which indicates fast and slow motions of the wake vortex. This study provides valuable insights into 3D mode morphology and dynamics of Kármán-type vortex shedding that helps to improve design and efficiency of structures in turbulent flow.