• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2B
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• pp.171-178
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• 2006

The finite element model based on the 2-D advection-dispersion equation incorporating the dispersion tensor that is calculated using velocity field data was developed in order to analyze more accurately 2-D mixing of pollutants for meandering streams. The proposed model was tested using the straight channel that inclined at 45o in the Cartesian coordinate system. The simulation results showed that dispersion tensor model using velocity field data gives an accurate solution. The suitability of the proposed model in analyzing actual pollutant mixing in meandering channels was demonstrated by comparing the simulation results with experimental data obtained from the tracer tests in the laboratory flume. Comparison results showed that the proposed model with dispersion tensor can represents more accurately the mixing phenomena of the pollutants in the meandering channels in which the direction of the primary flow is varying periodically along the channel.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.792-799
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• 2022

Building Information Modeling (BIM) technology is a key component of modern construction engineering and project management workflows. As-is BIM models that represent the spatial reality of a project site can offer crucial information to stakeholders for construction progress monitoring, error checking, and building maintenance purposes. Geometric methods for automatically converting raw scan data into BIM models (Scan-to-BIM) often fail to make use of higher-level semantic information in the data. Whereas, semantic segmentation methods only output labels at the point level without creating object level models that is necessary for BIM. To address these issues, this research proposes a hybrid semantic-geometric approach for clutter-resistant floorplan generation from laser-scanned building point clouds. The input point clouds are first pre-processed by normalizing the coordinate system and removing outliers. Then, a semantic segmentation network based on PointNet++ is used to label each point as ceiling, floor, wall, door, stair, and clutter. The clutter points are removed whereas the wall, door, and stair points are used for 2D floorplan generation. A region-growing segmentation algorithm paired with geometric reasoning rules is applied to group the points together into individual building elements. Finally, a 2-fold Random Sample Consensus (RANSAC) algorithm is applied to parameterize the building elements into 2D lines which are used to create the output floorplan. The proposed method is evaluated using the metrics of precision, recall, Intersection-over-Union (IOU), Betti error, and warping error.

• Journal of Biomedical Engineering Research
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• v.44 no.5
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• pp.346-353
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• 2023

In this paper, we propose an innovative approach that leverages deep learning to find optimal reference points for achieving precise tooth segmentation in three-dimensional tooth point cloud data. A dataset consisting of 350 aligned maxillary and mandibular cloud data was used as input, and both end coordinates of individual teeth were used as correct answers. A two-dimensional image was created by projecting the rendered point cloud data along the Z-axis, where an image of individual teeth was created using an object detection algorithm. The proposed algorithm is designed by adding various modules to the Unet model that allow effective learning of a narrow range, and detects both end points of the tooth using the generated tooth image. In the evaluation using DSC, Euclid distance, and MAE as indicators, we achieved superior performance compared to other Unet-based models. In future research, we will develop an algorithm to find the reference point of the point cloud by back-projecting the reference point detected in the image in three dimensions, and based on this, we will develop an algorithm to divide the teeth individually in the point cloud through image processing techniques.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.441-449
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• 2021

With advances in autonomous vehicles, there is a growing demand for more accurate position estimation. Especially, this is a case for a moving robot for the indoor operation which necessitates the higher accuracy in position estimation when the robot is required to execute the task at a predestined location. Thus, a method for improving the position estimation which is applicable to both the fixed and the moving object is proposed. The proposed method exploits the initial position estimation from Bluetooth beacon signals as observation signals. Then, it estimates the gravitational acceleration applied to each axis in an inertial frame coordinate through computing roll and pitch angles and combining them with magnetometer measurements to compute yaw angle. Finally, it refines the control inputs for an object with motion dynamics by computing acceleration on each axis, which is used for improving the performance of Kalman filter. The experimental assessment of the proposed algorithm shows that it improves the position estimation accuracy in comparison to a conventional Kalman filter in terms of average error distance at both the fixed and moving states.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.115-121
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• 2024

As the radar mounted on a moving platform moves and rotates, the state of the radar's coordinate system also changes. At this time, in order to track target, the target's coordinates should be converted using the platform state measured from the sensor, and tracking performance may deteriorate due to causes such as sensor noise, communication delay, and sensor update cycle. In this paper, to minimize the degradation of tracking performance because of sensor error, we designed a navigation filter to estimate the state of the moving platform and analyzed the effect of improving tracking performance by applying the navigation filter through a simulation test. To design this navigation filter, three filter algorithms were applied and analyzed to confirm the effect of improving platform position and attitude performance for each filter, and the navigation filter designed by applying the highest performance filter algorithm was applied to a tracking simulation test. Finally we confirmed Improvement in tracking performance before and after applying navigation filters.

• Journal of Korean Society of Rural Planning
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• v.30 no.3
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• pp.75-84
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• 2024

This study developed the procedure and method for the accuracy assessment of unmanned boat survey data, based on the reservoir water depth data of Misan Reservoir, measured by the manned and unmanned boats in 2009 by Korea Rural Community Corporation. In the first step, this study devised the method to extract the contour map of NGIS data in AutoCAD to generate easily the reservoir boundary map used to set the survey range of reservoir water depth and to test the survey accuracy. The surveyed data coordinate systems of the manned and the unmanned boat were also unified by using ArcGIS for the standards of accuracy assessment. In the accuracy assessment, the spatial correlation coefficient of the grid maps of the two measurement results was 0.95, showing high pattern similarity, although the average error was high at 78cm. To analyze in more detail assessment, this study generated randomly the 3,250m transverse profile route (PR), and then extracted grid values of water depth on the PR. In the results of analysis to the extracted depth data on PR, the error average difference of the unmanned boat measurements was 73.18cm and the standard deviation of the error was 55cm compared to the manned boat. This study set these values as the standard for the correction value by average shift and noise removal of the unmanned boat measurement data. By correcting the unmanned boat measurements with these values, this study has high accuracy results, the reservoir water depth and surface area curve with R² = 0.97 and the water depth and storage volume curve with R² = 0.999.

• The Journal of Advanced Prosthodontics
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• v.16 no.4
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• pp.201-211
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• 2024

PURPOSE. The aim of this prospective clinical study was to compare the influence of palatal vault forms on accuracy and speed of intraoral (IO) scans in completely edentulous cases. MATERIALS AND METHODS. Based on the palatal vault form, participants were divided into three equal groups (n = 10 each); Class I: moderate; Class II: deep; Class III: flat palatal vault. A reference model was created for each patient using polyvinylsiloxane impression material. The poured models were digitized using an extraoral scanner. The resultant data were imported as a solid CAD file into 3D analysis software (GOM Inspect 2018; Gom GmbH, Braunschweig, Germany) and aligned using the software's coordinate system to determine its X, Y, and Z axes. Five digital impressions (DIs) of maxilla were captured for each patient using an intraoral scanner (TRIOS; 3Shape A/S, Copenhagen, Denmark) and the resultant Standard Tessellation Language (STL) scan files served as test models. Trueness was evaluated by calculating arithmetic mean deviation (AMD) of the vault area between reference and test files while precision was evaluated by calculating AMD between captured scans to measure repeatability of scan acquisition. The scan time taken for each participant was also recorded. RESULTS. There was no significant difference in trueness and precision among the groups (P = .806 and .950, respectively). Average scan time for Class I and III palatal vaults was 1 min 13 seconds and 1 min 37 seconds, respectively, while class II deep palatal vaults showed the highest scan time of 5 mins. CONCLUSION. Palatal vault form in edentulous cases has an influence on scan time. However, it does not have a substantial impact on the accuracy of the acquired scans.

• Computers and Concrete
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• v.34 no.4
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• pp.447-476
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• 2024

The current research proposes an innovative finite element model established within the context of higher-order beam theory to examine the bending and buckling behaviors of functionally graded carbon nanotube-reinforced composite (FG-CNTRC) beams resting on Winkler-Pasternak elastic foundations. This two-node beam element includes four degrees of freedom per node and achieves inter-element continuity with both C¹ and C⁰ continuities for kinematic variables. The isoparametric coordinate system is implemented to generate the elementary stiffness and geometric matrices as a way to enhance the existing model formulation. The weak variational equilibrium equations are derived from the principle of virtual work. The mechanical properties of FG-CNTRC beams are considered to vary gradually and smoothly over the beam thickness. The current investigation highlights the influence of porosity dispersions through the beam cross-section, which is frequently omitted in previous studies. For this reason, this analysis offers an enhanced comprehension of the mechanical behavior of FG-CNTRC beams under various boundary conditions. Through the comparison of the current results with those published previously, the proposed finite element model demonstrates a high rate of efficiency and accuracy. The estimated results not only refine the precision in the mechanical analysis of FG-CNTRC beams but also offer a comprehensive conceptual model for analyzing the performance of porous composite structures. Moreover, the current results are crucial in various sectors that depend on structural integrity in specific environments.

• Smart Structures and Systems
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• v.33 no.6
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• pp.399-414
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• 2024

This study discusses the long-term deformation monitoring and shape sensing of bridge girder surfaces with an automated extraction scheme for point clouds in the Region Of Interest (ROI), invariant to the position of a Light Detection And Ranging system (LiDAR). Advanced smart construction necessitates continuous monitoring of the deformation and shape of bridge girders during the construction phase. An automated scheme is proposed for reconstructing geometric model of ROI in the presence of noisy non-stationary background. The proposed scheme involves (i) denoising irrelevant background point clouds using dimensions from the design model, (ii) extracting the outer boundaries of the bridge girder by transforming and processing the point cloud data in a two-dimensional image space, (iii) extracting topology of pre-defined targets using the modified Otsu method, (iv) registering the point clouds to a common reference frame or design coordinate using extracted predefined targets placed outside ROI, and (v) defining the bounding box in the point clouds using corresponding dimensional information of the bridge girder and abutments from the design model. The surface-fitted reconstructed geometric model in the ROI is superposed consistently over a long period to monitor bridge shape and derive deflection during the construction phase, which is highly correlated. The proposed scheme of combining 2D-3D with the design model overcomes the sensitivity of 3D point cloud registration to initial match, which often leads to a local extremum.

• The Journal of Korean Society for Radiation Therapy
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• v.27 no.1
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• pp.73-78
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• 2015

Purpose : Under the assumption of change to the amplitude based sorting, the study will use four dimensional computed tomography imaging (4DCT) arrayed using the phase based sorting to analyze the respiratory phase difference. Materials and Methods : The study analyzed the 4DCT (4-dimensional computed tomography) images of 10 liver cancer patients that were treated with respiratory gated radiotherapy from 2015 February to March. Using RPM respiratory gating (RPM 1.7.5, Varian, USA) equipment, imaging according to respiratory cycle of phase based sorting was acquired and using a treatment planning system (Pinnacle 9.2, Philips, USA) the acquired imaging according to respiratory cycle was used to measure the abdominal movement value by respiratory cycle. The measuring point was the point where the center point of the Marker Block and the body surface met in the 50% phase image and here the coordinate values Lateral, Vertical, Longitudinal (X, Y, Z) were set as reference points, and on the X, Z plane identical to the reference point, using the identical method the Y axis coordinate value of each 0%, 30%, 40%, 50%, 60%, 80% phase images were acquired to quantitatively measure the variation of distance to the Y axis. The abdominal movement value according to respiration was applied to the theoretical model that the value decreases linearly from maximum inhalation to maximum exhalation to divide the variation of my value to predict as amplitude value by respiratory cycle and conversely the variation in amplitude was recalculated with the phase variation deviation value to analyze. Results : The deviation value between expected value and actual location was the largest in the 30% phase with 0.24 cm, and standard deviation was also the largest in 30% phase with 0.13 cm. The effective value of the deviation value derived from the average of the deviation squared value of each patient appeared as minimum 0.7 cm, maximum 0.18 cm, average 0.12 cm, and standard deviation 0.4 cm. Also by dividing the actual movement distance value with the peak expiration value then converting it into %Phase, the deviation value with actual phase 16.5% in 30% phase, 10.0% and 40% phase, 10.0% and 60% phase, 15.4% and 80% phase, and overall average about 13%, and arraying based on amplitude, phase shift occurred and further it was from peak expiration the chance of deviation occurrence was increasingly measured. Conclusion : Based on the results of the study there were differences between value acquired based on theoretical model and actual value. Therefore in respiratory gated radiotherapy using external surrogates, there needs to be establishment of respiration gated radiation system that avoids the combination of two Sorting methods considering that there will be occurrence of treatment and corresponding clinical differences due to the phase difference that occur due to the Amplitude based Phase Sorting.