• Journal of Technologic Dentistry
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• v.40 no.3
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• pp.115-123
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• 2018

Purpose: The purpose of this study was establishing process of manufacturing dental prosthesis by using eZIS system(DDS Inc.,Korea). Methods: To evaluate accuracy verification, the test was practiced two ways. First, Comparison of 3D printing models and stone models was practiced by using 3D superimposing software. #36 prepared master model was scanned by eZIS system and three 'Veltz3D' 3D printing models and three 'Bio3D' 3D printing models were manufactured. three stone models were manufactured by conventional impression technique. Second, Fitness test was practiced. the 3D printing models and the stone models was compared by manufacturing same resin crown. #36 prepared master model was scanned 9 times and manufactured (milled) 9 resin crowns by eZIS system. These crowns were cemented three 'Veltz3D' 3D printing models, three 'Bio3D' 3D printing models and three stone models. These crowns were sliced mesiodistal axis and gaps were measured by digital microscope. Results: The average accuracy of Bio3D models were 65.75%. Veltz3D(Hebsiba) models were 60.11% Stone models were 41.00%. Conclusion : This study results showed 3D printing model is similar with stone model. So it was under clinical allow, didn't affect final dental prothesis. There were no significant differences in the appearance of the three types of milling crowns.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.21 no.4
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• pp.301-308
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• 2003

This study describes the methodology that improves the accuracy of the 3D object-space data extracted from IKONOS satellite images by improving the accuracy of a RPC(Rational Polynomial Coefficient) model. For this purpose, we developed the algorithm to adjust a RPC model, and could improve the accuracy of a RPC model with this algorithm and geographically well-distributed GCPs(Ground Control Points). Furthermore, when a RPC model was adjusted with this algorithm, the effects of geographic distribution and the number of GCPs on the accuracy of the adjusted RPC model was tested. The results showed that the accuracy of the adjusted RPC model is affected more by the distribution of GCPs than by the number of GCPs. On the basis of this result, the algorithm using pseudo_GCPs was developed to improve the accuracy of a RPC model in case the distribution of GCPs was poor and the number of GCPs was not enough to adjust the RPC model. So, even if poorly distributed GCPs were used, the geographically adjusted RPC model could be obtained by using pseudo_GCPs. The less the pseudo_GCPs were used -that is, GCPs were more weighted than pseudo_GCPs in the observation matrix-, the more accurate the adjusted RPC model could be obtained, Finally, to test the validity of these algorithms developed in this study, we extracted 3D object-space coordinates using RPC models adjusted with these algorithms and a stereo pair of IKONOS satellite images, and tested the accuracy of these. The results showed that 3D object-space coordinates extracted from the adjusted RPC models was more accurate than those extracted from original RPC models. This result proves the effectiveness of the algorithms developed in this study.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.208-217
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• 2021

3D-CNN is one of the deep learning techniques for learning time series data. However, these three-dimensional learning can generate many parameters, requiring high performance or having a significant impact on learning speed. We will use these 3D-CNNs to learn hand gesture and find the parameters that showed the highest accuracy, and then analyze how the accuracy of 3D-CNN varies through input data changes without any structural changes in 3D-CNN. First, choose the interval of the input data. This adjusts the ratio of the stop interval to the gesture interval. Secondly, the corresponding interframe mean value is obtained by measuring and normalizing the similarity of images through interclass 2D cross correlation analysis. This experiment demonstrates that changes in input data affect learning accuracy without structural changes in 3D-CNN. In this paper, we proposed two methods for changing input data. Experimental results show that input data can affect the accuracy of the model.

• Journal of Broadcast Engineering
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• v.25 no.7
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• pp.1095-1106
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• 2020

In this paper, we propose an algorithm that extracts a high-precision 3D skeleton using a model generated using a distributed RGB-D camera. When information about a 3D model is extracted through a distributed RGB-D camera, if the information of the 3D model is used, a skeleton with higher precision can be obtained. In this paper, in order to improve the precision of the 2D skeleton, we find the conditions to obtain the 2D skeleton well using the PCA. Through this, high-quality 2D skeletons are obtained, and high-precision 3D skeletons are extracted by combining the information of the 2D skeletons. Even though this process goes through, the generated skeleton may have errors, so we propose an algorithm that removes these errors by using the information of the 3D model. We were able to extract very high accuracy skeletons using the proposed method.

• Journal of Korean Society of Transportation
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• v.30 no.5
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• pp.43-59
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• 2012

It is generally assumed about trip distribution estimation model that growth factor model's estimation accuracy is higher than that of other models in short-term and that gravity model's estimation accuracy is higher than that of other models in long-term. For validation of such assumptions, this study compares estimation accuracies of each estimation model using 3year(1988, 1992, 2004) O-D tables from Daegu city. Each estimation model's accuracy were compared by mid-size and large-size zone as well as short-term and long-term target years. The results show that the trip distribution estimation model selection by usual assumption is not always right.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.1109-1114
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• 2022

The SMART (System-integrated Modular Advanced ReacTor) is an integral-type small modular reactor developed by KAERI (Korea Atomic Energy Research Institute). This paper discusses the feasibility and applicability of a 3D-based equivalent model using dynamic condensation method for seismic analysis of a SMART control rod drive mechanism. The equivalent model is utilized for complicated seismic analysis during the design of the SMART. While the 1D-based beam-mass equivalent model is widely used in the nuclear industry for its calculation efficiency, the 3D-based equivalent model is suggested for the seismic analysis of SMART to enhance the analysis accuracy of the 1D-based equivalent model while maintaining its analysis efficiency. To verify the suggested model, acceleration response spectra from seismic analysis based on the 3D-based equivalent model are compared to those from the 1D-based beam-mass equivalent model and experiments. The accuracy and efficiency of the dynamic condensation method are investigated by comparison to analysis results based on the conventional modeling methodology used for seismic analysis.

• International Journal of Precision Engineering and Manufacturing
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• v.9 no.4
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• pp.16-21
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• 2008

The demand for three-dimensional (3D) shape measurements is increasing in a variety of fields, including the manufacture of molds and dies. The most popular technology for 3D shape measurement is the coordinate measuring machine (CMM) with a contact trigger probe. Although a CMM provides a high degree of accuracy, it is inefficient due to its long measuring time. It also has difficulty measuring soft objects that can be deformed by the touch of the contact probe. In addition, a CMM cannot digitize areas that are difficult to reach, and cannot capture very minute details on the surface of complex parts. For these reasons, optical non-contact measurement techniques are receiving more attention since they eliminate most of the problems associated with contact methods. Laser scanning is emerging as one of the more promising non-contact measurement techniques. This paper describes various acquisition considerations for laser scanning, including the accuracy of the 3D scan data, which depends on the charge-coupled device (CCD) gain and noise. The CCD gain and noise of a 3D laser scanner are varied while keeping the other conditions constant, and the measurement results are compared to the dimensions of a standard model. The experimental results show that a considerable time savings and an optimum degree of accuracy are possible by selecting the proper CCD gain and noise.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.343-349
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• 2021

In The process from design to construction in the existing construction work was less efficient due to the contradictory approach of identifying the 3D state in the plan view and the repeated generation of surveys, floor plans, drawings. Accurate 3D design data is essential for smart construction. However, most of the existing related studies have focused on explaining the development method and main functions of equipment or improving the productivity of smart construction. Therefore, in this study, the utility of 3D design model generation for smart construction and construction survey using 3D laser scanner was evaluated. Plane and vertical road alignment were created using the specifications of the road. The generated road alignment was created as a three-dimensional corridor design using cross-sections at intervals of 20m. In addition, it was possible to create a DTM (Digital Terrain Model) using a digital map and effectively create a 3D design model for the study area through overlapping. Construction survey using a 3D laser scanner showed accuracy within 10cm as a result of the accuracy evaluation. These results proved that construction surveying using a 3D laser scanner is possible because it satisfies the acceptable accuracy of the relevant regulations modeling of target areas using 3D design and construction survey using 3D laser scanner can be a way to address shortcomings of existing GNSS (Global Navigation Satellite System) methods. And accurate 3D data will be used as essential data as basic data for smart construction.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.497-505
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• 2018

In a situation where the amount of bulky waste needs to be quantified, a three-dimensional model of the wastes can be constructed using drones. This study constructed a drone-based 3D model with a range of flight parameters and a GCPs survey, analyzed the relationship between the accuracy and time required, and derived a suitable drone application technique to estimate the amount of waste in a short time. Images of waste were photographed using the drone and auto-matching was performed to produce a model using 3D coordinates. The accuracy of the 3D model was evaluated by RMSE calculations. An analysis of the time required and the characteristics of the top 15 models with high accuracy showed that the time required for Model 1, which had the highest accuracy with an RMSE of 0.08, was 954.87 min. The RMSE of the 10th 3D model, which required the shortest time (98.27 min), was 0.15, which is not significantly different from that of the model with the highest accuracy. The most efficient flight parameters were a high overlapping ratio at a flight altitude of 150 m (60-70% overlap and 30-40% sidelap) and the minimum number of GCPs required for image matching was 10.

• Journal of Cadastre & Land InformatiX
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• v.49 no.2
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• pp.57-66
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• 2019

Recently, as a part of the production of spatial information by smart cities, three-dimensional reproduction of structures for reverse engineering has been attracting attention. In particular, terrestrial LiDAR is mainly used for 3D reproduction of structures, and 3D reproduction research by UAS has been actively conducted. However, both technologies produce blind spots due to the shooting angle. This study deals with vertical structures. 3D model implemented through SfM-based image analysis technology using UAS and reproducibility and effectiveness of 3D models by terrestrial LiDAR-based laser scanning are examined. In addition, two 3D models are merged and reviewed to complement the blind spot. For this purpose, UAS based image is acquired for artificial rock wall, VCP and check point are set through GNSS equipment and total station, and 3D model of structure is reproduced by using SfM based image analysis technology. In addition, Through 3D LiDAR scanning, the 3D point cloud of the structure was acquired, and the accuracy of reproduction and completeness of the 3D model based on the checkpoint were compared and reviewed with the UAS-based image analysis results. In particular, accuracy and realistic reproducibility were verified through a combination of point cloud constructed from UAS and terrestrial LiDAR. The results show that UAS - based image analysis is superior in accuracy and 3D model completeness and It is confirmed that accuracy improves with the combination of two methods. As a result of this study, it is expected that UAS and terrestrial LiDAR laser scanning combination can complement and reproduce precise three-dimensional model of vertical structure, so it can be effectively used for spatial information construction, safety diagnosis and maintenance management.