• Maxillofacial Plastic and Reconstructive Surgery
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• 제23권3호
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• pp.258-262
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• 2001

Distraction osteogenesis(DO) can be performed in the bony defect associated with trauma, anomaly, and various kinds of disease. The gap generated by DO is filled with growing callus : during the period of distraction, the osteogenesis is continued. However, there have been few reports about expression pattern of growth factors in newly formed bone during the consolidation periods. We performed DO in the mandibular defect case and studied the expressed pattern of growth factors. Its pattern was compared to that of the same patient. BMP-2 and -4 were strongly expressed in the DO site. Particularly, BMP-4 was not expressed in the normal mature bone, but expressed in new bone in DO. However, there was no difference in the FGF-7 expression between the sites. Therefore, strong expression of BMP-4 are related to new bone formation in DO and they may not be related to the normal homeostasis in human bone. Though FGF-7 is related to the growth of keratinocyte, it may have minimal role in the DO and normal mature bone.

• Nuclear Engineering and Technology
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• 제54권10호
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• pp.3943-3948
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• 2022

Single-photon emission computed tomography is one of the reliable pin-by-pin verification techniques for spent-fuel assemblies. One of the challenges with this technique is to increase the total fuel assembly verification speed while maintaining high verification accuracy. The aim of the present study, therefore, was to develop an artificial intelligence (AI) algorithm-based tomographic image analysis technique for partial-defect verification of fuel assemblies. With the Monte Carlo (MC) simulation technique, a tomographic image dataset consisting of 511 fuel-rod patterns of a 3 × 3 fuel assembly was generated, and with these images, the VGG16, GoogLeNet, and ResNet models were trained. According to an evaluation of these models for different training dataset sizes, the ResNet model showed 100% pattern estimation accuracy. And, based on the different tomographic image qualities, all of the models showed almost 100% pattern estimation accuracy, even for low-quality images with unrecognizable fuel patterns. This study verified that an AI model can be effectively employed for accurate and fast partial-defect verification of fuel assemblies.

• 전기학회논문지P
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• 제58권4호
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• pp.632-632
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• 2009

The purpose of this study is to present the range of defects mentioned in the Product Liability (PL) and to establish an objective basis and grounds for the analysis of accidents expected to happen by analyzing and presenting the external flame pattern and electrical characteristics of an LED streetlight lamp, a new lighting lamp. From the analysis of the cross-section of a cable carbonized by an external flame, it was observed that the wire's strand and insulation material had solidly adhered, and that greater voids were formed at the surface than at the center. Irregular carbide lumps were formed in the globe directly exposed to the flame, and the globe carbonized by the indirect flame showed characteristics that they had melted and flowed downward. It was found that the forward and backward resistances of the normal LED were approximately 1.74 [$M{\Omega}$] and 140 [$M{\Omega}$], respectively. The lamp burnt by the strong flame exhibited infinite forward and backward resistances and the LED did not emit light. The carbonized LED lamp was gray and exhibited fine delaminations. According to the Product Liability, a product defect signifies a simple product defect. Most of the defects were caused by the lack of stability, and the defect of the product itself occurred during the design and manufacture. The defects in warnings and markings include an insufficiency of handling manuals and warnings, expressive warranty violations, defective markings, etc. In order to prevent an accident resulting from a product, it is necessary to prepare safety warnings and documentation, establish clear-cut lines of liabilities, and subscribe insurances. However, it could be seen that important factors against the Product Liability were product improvement, response to compensation requests and law suits, credit restoration, etc.

• 전기학회논문지
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• 제56권7호
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• pp.1224-1230
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• 2007

In this paper, we study the classification of defects at steam generator tube in nuclear power plant using eddy current testing (ECT). We consider 4 defect patterns of SG tube: I-In type, I-Out type, V-In type, and V-Out type. Through numerical analysis program based on finite element modeling, 400 ECT signals are generated by varying width and depth of each defect type. In order to improve the classification performance, we propose new feature extraction technique. After extracting new features from the generated ECT signals, multi-layer perceptron is used to classify the defect patterns. Through the computer simulation study, it is shown that the proposed method achieves 100% classification success rate while the previous method yields 91% success rate.

• Journal of Trauma and Injury
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• 제28권1호
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• pp.27-30
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• 2015

A child sustained a car tire friction injury and had multiple soft tissue wounds. She had a severe soft tissue defect in the medial foot and ankle aspect which requiring flap coverage. We performed an adipoafscial flap with upside-down pattern for the treatment of the medial foot and ankle soft tissue posttraumatic defect. The flap is based on the perforator artery from the posterior tibial artery. Because it gave a thin coverage for the foot, the patient could walk with normal foot wear.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.774-779
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• 2003

Arc-shaped line array slits have been used for the laser generation of focused Lamb waves. The spatially expanded Nd:YAG pulse laser was illuminated through the arc-shaped line array slit on the surface of a sample plate to generate the Lamb waves of the same pattern as the slit. Then the generated Lamb waves were focused at the point of which distance from the slit position is dependent on the curvature of slit arc. The proposed method showed better spatial resolution than the conventional linear array slit in the detection of laser machined linear defect and drill machined circular defect on aluminum plates of 1mm thickness.

• EDISON SW 활용 경진대회 논문집
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• 제5회(2016년)
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• pp.75-79
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• 2016

A helical nanosturctrue can be obtained by self-assembly method. Utilizing DPD simulation coarse-grained model, we patterned 2D layer nanosheets with repeated diagonal defects and grafts, and programed to self-roll into hollow helix structure. The defected pattern side caused anisotropy, and formed helix or helix-like structure. This opens the possibility to control the helix pitch or cavity radius. In this work, we designed several patterns about diagonal defect with a variety of defect side densities and defect widths and then simulation was carried out. Thus, our results have that parameters are affecting self-assembly of nanosheets and their conformation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권12호
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• pp.4763-4775
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• 2020

This research aims to develop a deep learning-based method that automatically detects and segments the defects on railroad surfaces to reduce the cost of visual inspection of the railroad. We developed our segmentation model by modifying a fully convolutional network model [1], a well-known segmentation model used for machine learning, to detect and segment railroad surface defects. The data used in this research are images of the railroad surface with one or more defect regions. Railroad images were cropped to a suitable size, considering the long height and relatively narrow width of the images. They were also normalized based on the variance and mean of the data images. Using these images, the suggested model was trained to segment the defect regions. The proposed method showed promising results in the segmentation of defects. We consider that the proposed method can facilitate decision-making about railroad maintenance, and potentially be applied for other analyses.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.533-534
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• 2006

Micro pyramid pattern and its array are designed to enhance the brightness and its uniformity of LGP which is one of key parts in LCD. The designed micro pyramid patterns are fabricated on a Si-wafer first through MEMS process and then a Ni-stamper is electro-plated from the Si pattern master. Adopting the fabricated Ni-stamper, LGPs are injection molded at different mold temperatures and the fidelity of the pattern replication is estimated for each molding conditions and pattern locations. The replicated patterns are found to have some defect such as local short shot or micro weld line which are believed to have negative effect on the performance of the LGP.

• 한국압력기기공학회 논문집
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• 제13권1호
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• pp.48-53
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• 2017

We diagnosed the defect using the data obtained from the nuclear power plant simulator. In this paper, we diagnosed faults in the nuclear power plant system for discovery instead of the traditional single-component or device unit. We created the six fault scenarios and used a fault simulator to obtain the fault data. It was extracted pattern from acquired failure data. Neural network model was trained and simple pattern matching algorithm was applied. We presented a simulation result and confirmed that the applied algorithm works correctly.