• Journal of Institute of Control, Robotics and Systems
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• v.11 no.1
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• pp.34-40
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• 2005

In this paper, we describe the modeling for the 3D robot laser scanning system consisting of a laser stripe projector, camera, and 5-DOF robot and propose its calibration method. Nonlinear radial distortion in the camera model is considered for improving the calibration accuracy. The 3D range data is calculated using the optical triangulation principle which uses the geometrical relationship between the camera and the laser stripe plane. For optimal estimation of the system model parameters, real-coded genetic algorithm is applied in the calibration process. Experimental results show that the constructed system is able to measure the 3D position within about 1mm error. The proposed scheme could be applied to the kinematically dissimilar robot system without losing the generality and has a potential for recognition for the unknown environment.

• Smart Structures and Systems
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• v.20 no.6
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• pp.697-708
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• 2017

Maintenance plays a critical role in the bridge industry, but actual practices show many limitations because of traditional, 2D-based information systems. It is necessary to develop a new generation of maintenance information management systems for more reliable decision making in bridge maintenance. Enhancing current work processes requires a BIM-based 3D digital model that can use information from the whole lifecycle of a project (design, construction, operation, and maintenance) through continuous exchanges and updates from each stakeholder. This study describes the development of a data scheme for maintenance of cable-stayed bridges. We implemented the proposed system for a cable-stayed bridge and discussed its effectiveness.

• The Journal of the Korea Contents Association
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• v.12 no.9
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• pp.136-145
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• 2012

This research proposes a pattern making method for women's bodice by the characters of body types and develops bodice dress forms on their body shapes applying 3D body scan data. 515 women's body scan data was collected and analyzed factor and cluster analysis. Three body types were characterized in normal, obese, and slim group. In each group, 10 subjects were selected. 20 parts in 3D anthropometric data were measured using Autocad program. The amount of waist dart was calculated and three types of basic bodice pattern were developed using the calculated darts data. The amount and the position of front dart and side dart were different at obese group in comparison of normal and thin group. The three types of basic bodice model were made by the basic bodice pattern, and each model was scanned by 3D scanner to make 3D bodice dress forms. Three types of bodice dress forms were rendered using 3D max program. Bodice dress forms had the dart lines and were useful to draft patterns to fit their body shape.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2004.03a
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• pp.825-830
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• 2004

A numerical analysis based on two-dimensional and three-dimensional incompressible Navier-Stokes equations has been carried out for double-circular-arc (DCA) compressor cascades. Two types of double-circular-arc cascades were used in this analysis. The appropriate turbulence model for compressor analysis was selected among the conventional turbulence models such as Baldwin-Lomax, k-$\varepsilon$ and k-$\varepsilon$ models. The results of current study were compared with available experimental data at various incidence angles. The 2-D and 3-D computational codes based on SIMPLE/PWIM algorithm for collocated grid and hybrid scheme for the convective terms were the main features of numerical tools. As commonly known, turbulence modeling is very important for the prediction of cascade flows, which are extremely complex with separation and reattachment by adverse pressure gradient. For selection of turbulence model, 2-D analysis was performed. And then, k-$\varepsilon$ turbulence model with wall function chosen as the reasonable turbulence model for 3-D calculation was used to increase the efficiency of computation times. A reasonable result of 3-D flow pattern passing through the double-circular-arc cascade was obtained.

• The KIPS Transactions:PartB
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• v.16B no.1
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• pp.47-54
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• 2009

Automatic object recognition in 3D measuring data is of great interest in many application fields e.g. computer vision, reverse engineering and digital factory. In this paper we present a software tool for a fully automatic object detection and parameter estimation in unordered and noisy point clouds with a large number of data points. The software consists of three interactive modules each for model selection, point segmentation and model fitting, in which the orthogonal distance fitting (ODF) plays an important role. The ODF algorithms estimate model parameters by minimizing the square sum of the shortest distances between model feature and measurement points. The local quadric surface fitted through ODF to a randomly touched small initial patch of the point cloud provides the necessary initial information for the overall procedures of model selection, point segmentation and model fitting. The performance of the presented software tool will be demonstrated by applying to point clouds.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.28-35
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• 2006

Statistical models of shape variability based on active shape models (ASMs) have been successfully utilized to perform segmentation and recognition tasks in two-dimensional (2D) images. Three-dimensional (3D) model-based approaches are more promising than 2D approaches since they can bring in more realistic shape constraints for recognizing and delineating the object boundary. For 3D model-based approaches, however, building the 3D shape model from a training set of segmented instances of an object is a major challenge and currently it remains an open problem in building the 3D shape model, one essential step is to generate a point distribution model (PDM). Corresponding landmarks must be selected in all1 training shapes for generating PDM, and manual determination of landmark correspondences is very time-consuming, tedious, and error-prone. In this paper, we propose a novel automatic method for generating 3D statistical shape models. Given a set of training 3D shapes, we generate a 3D model by 1) building the mean shape fro]n the distance transform of the training shapes, 2) utilizing a tetrahedron method for automatically selecting landmarks on the mean shape, and 3) subsequently propagating these landmarks to each training shape via a distance labeling method. In this paper, we investigate the accuracy and compactness of the 3D model for the human liver built from 50 segmented individual CT data sets. The proposed method is very general without such assumptions and can be applied to other data sets.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.541-547
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• 2006

With the new paradigm of ubiquitous in the developed computing technology, it is urgently necessary to research GIS fields centering around positioning techniques. The intention of this study is to propose implementation methods for integrating topographic and cadastral data. For this purpose an integrated data model is formed to coincide the graphic data of cadastral map with that of topographic map. As a result, the integrated data model could be built by harmonizing cadastral map with topographic map. We suggest data model for connecting with other information systems in the conditions of data uniformity and implementation. This data implementation models suggested in this research can provide a good reference for the future implementation of other systems. This results will be efficiently used as basis for practical use in ubiquitous environments of spatial informations.

• 한국지역지리학회:학술대회
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• 2009.08a
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• pp.108-115
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• 2009

An increase in oil and gas plants caused by development of process industry have brought into the increase in use of flammable and toxic materials in the complex process under high temperature and pressure. There is always possibility of fire and explosion of dangerous chemicals, which exist as raw materials, intermediates, and finished goods whether used or stored in the industrial plants. Since there is the need of efforts on disaster damage reduction or mitigation process, we have been conducting a research to relate explosion model on the background of real 3D terrain model. By predicting the extent of damage caused by recent disasters, we will be able to improve efficiency of recovery and, sure, to take preventive measure and emergency counterplan in response to unprepared disaster. For disaster damage prediction, it is general to conduct quantitative risk assessment, using engineering model for environmentaldescription of the target area. There are different engineering models, according to type of disaster, to be used for industry disaster such as UVCE (Unconfined Vapor Cloud Explosion), BLEVE (Boiling Liquid Evaporation Vapor Explosion), Fireball and so on, among them.we estimate explosion damage through UVCE model which is used in the event of explosion of high frequency and severe damage. When flammable gas in a tank is released to the air, firing it brings about explosion, then we can assess the effect of explosion. As 3D terrain information data is utilized to predict and estimate the extent of damage for each human and material. 3D terrain data with synthetic environment (SEDRIS) gives us more accurate damage prediction for industrial disaster and this research will show appropriate prediction results.

• Journal of Coastal Disaster Prevention
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• v.5 no.4
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• pp.183-192
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• 2018

In recent years, coastal areas have been suffering from coastal erosion, such as destruction of coastal roads and military facilities. In this study, the Delft3D model was used to analyze the sediment transport pattern due to seasonal characteristics of summer and winter waves in Anmok beach of the East coast. Typhoon and high waves are mainly are coming from ENE direction in the summer season and the flows occur in the northward. In winter, high waves are incident from NE and the flows occur in the southward. These seasonal patterns were simulated by using Delft3D model. As for model input, reanalysis wave data of the past 38 years were used, and the seasonal patterns were analyzed by dividing the whole year into summer and winter season. The grid point of the 38 year reanalysis data is far from the Anmok beach, so the three model grid systems (wide grid -> intermediate grid -> detailed grid) are constructed. Most of the flows in the NW direction occurred in summer, but erosion and deposition was alternated along the coastline. In winter, sediment was deposited near Gangnung Port due to the southern flow and the southern port. Strong winter waves compared to summer tend to cause deposition around Gangnung Port throughout the year.

• Journal of the Korean Geotechnical Society
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• v.37 no.5
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• pp.47-63
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• 2021

Recently, the demand for three-dimensional (3D) underground maps from the perspective of digital twins and the demand for linkage utilization are increasing. However, the vastness of national geotechnical survey data and the uncertainty in applying geostatistical techniques pose challenges in modeling underground regional geotechnical characteristics. In this study, an optimal learning model based on multi-layer perceptron (MLP) was constructed for 3D subsurface lithological and geotechnical classification in Seoul, South Korea. First, the geotechnical layer and 3D spatial coordinates of each borehole dataset in the Seoul area were constructed as a geotechnical database according to a standardized format, and data pre-processing such as correction and normalization of missing values for machine learning was performed. An optimal fitting model was designed through hyperparameter optimization of the MLP model and model performance evaluation, such as precision and accuracy tests. Then, a 3D grid network locally assigning geotechnical layer classification was constructed by applying an MLP-based bet-fitting model for each unit lattice. The constructed 3D geotechnical layer map was evaluated by comparing the results of a geostatistical interpolation technique and the topsoil properties of the geological map.