• Transactions of Materials Processing
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• v.20 no.7
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• pp.518-523
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• 2011

The three dimensional geometries of an aluminum open cell foam before and after uniaxial compressive loading were investigated using the X-ray micro CT(computed tomography). Aluminum 6101-T6 open cell foams of 10, 20, 40 ppi (pore per inch) were considered in this work. After the serial sectioning CT images of aluminum foams were obtained from non-destructive X-ray images, the exact 3D structure were reproduced and visualized with commercial image processing program. The relative density ratio was around the 7.0 to 9.0 range, the unit cells showed anisotropic shapes having the different dimensional ratios of 1.1 to 1.3 between the rise and the transverse directions. The yield stress increased with the relative density ratio and the volumetric strain increased proportionally with compressive strain. The plateau stress in the compressive stress-strain curve was caused by the buckling of ligaments.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.10a
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• pp.295-296
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• 2010

• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.329-334
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• 2014

In this study, a new method that automatically segments trabecular bone for its morphological analysis using micro-computed tomography imaging was proposed. In the proposed method, the bone region was extracted using a threshold value, and the outer boundary of the bone was detected. The sphere of maximum size with the corresponding voxel as the center was obtained by applying the sphere-fitting method to each voxel of the bone region. If this sphere includes the outer boundary of the bone, the voxels included in the sphere are classified as cortical bone; otherwise, they are classified as trabecular bone. The proposed method was applied to images of the distal femurs of 15 mice, and comparative experiments, with results manually divided by a person, were performed. Four morphological parameters-BV/TV, Tb.Th, Tb.Sp, and Tb.N-for the segmented trabecular bone were measured. The results were compared by regression analysis and the Bland-Altman method; BV/TV, Tb.Th, Tb.Sp, and Tb.N were all in the credible range. In addition, not only can the sphere-fitting method be simply implemented, but trabecular bone can also be divided precisely by using the three-dimensional information.

• Composites Research
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• v.25 no.4
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• pp.117-125
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• 2012

Warpage of the film insert molded (FIM) part is caused by an asymmetric residual stress distribution. Asymmetric residual stress and temperature distribution is generated by the retarded heat transfer in the perpendicular direction to the attached film surface. Since warpage was not prevented by controlling injection molding conditions, glass fiber (GF) filled composites were employed as substrates for film insert molding to minimize the warpage. Distribution of short GFs was evaluated by using micro-CT equipment. Proper models for micro mechanics, anisotropic thermal expansion coefficients, and closure approximation should be selected in order to calculate fiber orientation tensor and warpage of the FIM part with the composite substrate. After six kinds of micro mechanics models, three models of the thermal expansion coefficient and five models of the closure approximation had been considered, the Mori-Tanaka model, the Rosen and Hashin model, and the third orthotropic closure approximation were selected in this study. The numerically predicted results on fiber orientation tensor and warpage were in good agreement with experimental results and effects of GF reinforcement on warpage of the FIM composite specimen were identified by the numerical results.

• Polymer(Korea)
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• v.37 no.5
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• pp.563-570
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• 2013

Poly(vinyl pivalate) (PVPi) was bulk polymerized to make poly(vinyl alcohol) (PVA) microfibrils to apply for polymeric embolization coils replacing metalic coils. Then, syndiotactic PVA (s-PVA) microfibrils having number-average degree of polymerization of 1100 and s-diad content of 60.4% were prepared via saponification of the PVPi with no separate spinning process. To make s-PVA microfibrils with radiopacity, zirconium dioxide ($ZrO_2$) and barium sulfate ($BaSO_4$) were added into s-PVA microfibrils during saponification. The computed tomography (CT) value indicating radiopacity reached up to over 1000 when the amount of $ZrO_2$ and $BaSO_4$ were 12 and 6 wt%, respectively.

• Journal of Dental Rehabilitation and Applied Science
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• v.25 no.2
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• pp.95-107
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• 2009

The purpose of this research was to examine the fitness of zirconia cores that were made by different sintering methods; generic electricity furnace and microwave furnace. Firstly, 12 cores for each group were made by using each different sintering process and attached them to a metal die with silicon. The internal and marginal gap of sintered zirconia was measured by using Skyscan 1076 micro-CT, then it was reorganized by CT-An software. To each samples, we extracted B-L image, M-D image of cutting side, and cross-sectional side of tooth long axis and calculated the mean value of marginal, axial, and occlusal gap each side. Results: 1. The mean marginal gap of sintered zirconia was $36.20{\mu}m$ for EVE, $47.67{\mu}m$ for LAV, $52.47{\mu}m$ for DEN, and $54.63{\mu}m$ for CER. 2. For the axial wall, the research showed the largest value of $63.49{\mu}m$ for EVE, but there were no statistical significance. 3. In related to the occlusal internal measurement, DEN showed the smallest value ($77.06{\mu}m$), EVE and CER showed significantly high value. From this study, it is suggested that CAD/CAM zirconia core which was made in the process of microwave sintering has clinically acceptable values in marginal and internal gap.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.5
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• pp.339-346
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• 2023

The uncertainties of microstructural features affect the properties of materials. Numerous pores that are randomly distributed in materials make it difficult to predict the properties of the materials. The distribution of pores in cementitious materials has a great influence on their mechanical properties. Existing studies focus on analyzing the statistical relationship between pore distribution and material responses, and the correlation between them is not yet fully determined. In this study, the mechanical response of cementitious materials is predicted through an image-based data approach using a convolutional neural network (CNN), and the correlation between pore distribution and material response is analyzed. The dataset for machine learning consists of high-resolution micro-CT images and the properties (tensile strength) of cementitious materials. The microstructures are characterized, and the mechanical properties are evaluated through 2D direct tension simulations using the phase-field fracture model. The attributes of input images are analyzed to identify the spot with the greatest influence on the prediction of material response through CNN. The correlation between pore distribution characteristics and material response is analyzed by comparing the active regions during the CNN process and the pore distribution.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.11
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• pp.305-310
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• 2021

Artificial intelligence technology in the medical field initially focused on analysis and algorithm development, but it is gradually changing to web application development for service as a product. This paper describes a Urinary Stone segmentation model in abdominal CT images and an artificial intelligence web application based on it. To implement this, a model was developed using U-Net, a fully-convolutional network-based model of the end-to-end method proposed for the purpose of image segmentation in the medical imaging field. And for web service development, it was developed based on AWS cloud using a Python-based micro web framework called Flask. Finally, the result predicted by the urolithiasis segmentation model by model serving is shown as the result of performing the AI web application service. We expect that our proposed AI web application service will be utilized for screening test.

• Composites Research
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• v.36 no.6
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• pp.395-401
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• 2023

In this study, finite element modeling of unidirectional composite materials of the computed tomography (CT) was conducted using a supervised learning-based segmentation technique. Firstly, Micro-CT scan was performed to obtain the raw volume of unidirectional composite materials, providing microstructure information. From the CT volume images, actual microstructure of the cross-section of unidirectional composite materials was extracted by the labeling process. Then, a U-net deep learning model was trained with a small number of raw images as inputs and their labeled images as outputs to generate a segmentation model. Subsequently, most of remaining images were input to the trained U-net deep learning model to segment all raw volume for identifying complex microstructure, which was used for the generation of finite element model. Finally, the fiber volume fraction of the finite element model was compared with that of experimentally measured volume to validate the appropriateness of the proposed method.

• Journal of Dental Rehabilitation and Applied Science
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• v.32 no.3
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• pp.184-193
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• 2016

Purpose: To evaluate marginal leakage of bulk fill flowable composite resin filling with different curing time by using microcomputed tomography technology. Materials and Methods: 30 previously extracted human molars were randomly divided into 6 groups based upon restorative system and different curing time. Class II cavities (vertical slot cavities) were prepared. An individual metallic matrix was used to build up the proximal wall. The SonicFill or SureFil SDR flow was inserted into the preparation by using 1 bulk increment, followed by light polymerization for different curing times. The different exposure times were 20, 40, and 60 seconds. All specimens were submitted to 5,000 thermal cycles for artificial aging. Micro-CT scanning was performed by using SkyScan 1272. One evaluator assessed microleakage of silver nitrated solution at the resin-dentin interface. The 3D image of each leakage around the restoration was reconstructed with CT-Analyser V.1.14.4. The leakage was analyzed with the Mann-Whitney test. Results: Significant differences were observed between the light curing times, but no significant differences were found between the bulk fill composite resins. Increasing in the photoactivation time resulted in greater microleakage in all the experimental groups. Those subjected to 60 seconds of light curing showed higher microleakage means than those exposed for 20 seconds and 40 seconds. Conclusion: Increasing the photoactivation time is factor that may increase marginal microlekage of the bulk fill composite resins. Further, micro-CT can nondestructively detect leakage around the resin composite restoration in three dimensions.