• 전자공학회논문지 IE
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• v.48 no.2
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• pp.26-31
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• 2011

In this paper we show the LCD simulator for defect inspection using image processing algorithm and neural network. The defect inspection algorithm of the LCD consists of preprocessing, feature extraction and defect classification. Preprocess removes noise from LCD image, using morphology operator and neural network is used for the defect classification. Sample images with scratch, pinhole, and spot from real LCD color filter image are used. From some experiments results, the proposed algorithms show that defect detected and classified in the ratio of 92.3% and 94.5 respectively. Accordingly, in this paper, a possibility of practical implementation of the LCD defect inspection system is finally suggested.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2846-2848
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• 2005

This paper proposes a pattern classification algorithm for the defect distribution of Hard Disk Drive (HDD). In the HDD productions, the defect pattern of defective HDD set is important information to diagnosis of defective HDD set. In this paper, 5 characteristics are determined for the classification to six standard defect pattern classes. A fuzzy inference system is proposed, the inputs of which are 5 characteristic values and the outputs are the possibilities that the input pattern is classified to the standard patterns. Classification result is the pattern with maximum possibility. The proposed algorithm is implemented with a PC system for defective HDD sets and shows its effectiveness.

• Journal of Advanced Marine Engineering and Technology
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• v.32 no.6
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• pp.834-840
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• 2008

We carried out fatigue testing with materials of aluminum alloyC7075-T6, 2024-T4) by rotary bending fatigue tester. We investigated fatigue limit, fatigue crack initiation, fatigue crack propagation behavior and possibility of fatigue life prediction to the different small circular hole defect. The summarized result are as follows; Fatigue limit of the smooth specimens were related tensile strength and yield strength. In case of more large applied stress and small circular hole crack defect, the fatigue crack was grown rapidly. The fatigue crack propagation behavior proceed at according to inclusion. Fatigue crack propagation ratio appeared instability and retardation phenomenon in the first half of fatigue life but appeared stability and replied in the latter half. On other hand, this experimental data of the materials are appeared fatigue life predictability.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.6
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• pp.383-389
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• 2005

This paper proposes a pattern classification algorithm for the defect distribution of Hard Disk Drive (HDD). In the HDD production, the defect pattern of defective HDD set is important information to diagnosis of defective HDD set. In this paper, 5 characteristics are determined for the classification to six standard defect pattern classes. A fuzzy inference system is proposed, the inputs of which are 5 characteristic values and the outputs are the possibilities that the input pattern is classified to standard patterns. Therefore, classification result is the pattern with maximum possibility. The proposed algorithm is implemented with the PC system for defective HDD sets and shows its effectiveness.

• Transactions of Materials Processing
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• v.31 no.4
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• pp.229-239
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• 2022

Convolution Neural Network(CNN) is a class of deep learning algorithms and can be used for image analysis. In particular, it has excellent performance in finding the pattern of images. Therefore, CNN is commonly applied for recognizing, learning and classifying images. In this study, the surface defect classification performance of Al 6061 extruded material using CNN-based algorithms were compared and evaluated. First, the data collection criteria were suggested and a total of 2,024 datasets were prepared. And they were randomly classified into 1,417 learning data and 607 evaluation data. After that, the size and quality of the training data set were improved using data augmentation techniques to increase the performance of deep learning. The CNN-based algorithms used in this study were VGGNet-16, VGGNet-19, ResNet-50 and DenseNet-121. The evaluation of the defect classification performance was made by comparing the accuracy, loss, and learning speed using verification data. The DenseNet-121 algorithm showed better performance than other algorithms with an accuracy of 99.13% and a loss value of 0.037. This was due to the structural characteristics of the DenseNet model, and the information loss was reduced by acquiring information from all previous layers for image identification in this algorithm. Based on the above results, the possibility of machine vision application of CNN-based model for the surface defect classification of Al extruded materials was also discussed.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.50 no.4
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• pp.222-226
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• 2024

The upper lip is a functionally and aesthetically important area of the face. Therefore, reconstruction of an upper lip defect needs sufficient consideration to ensure functional and aesthetic recovery. Several methods, such as wedge resection, rotation flaps, advancement flaps, and myomucosal advancement flaps, have been used to reconstruct vermilion defects. However, it is challenging to reconstruct a vermilion defect because of the possibility of residual asymmetry or scars and restrictions to normal lip movement after the reconstruction. We present the case of a 51-year-old female that had an upper lip vermilion defect caused by a dog bite. The lip defect was reconstructed using a mucosal V-Y advancement flap. This mucosal flap was based on the orbicularis oris muscle with a branch of the superior labial artery to ensure sufficient blood supply. Therefore, flap survival was excellent, and there was no constriction of the flaps. Moreover, the color and contour were matched to the adjacent lip tissue, and re-establishment of the white roll and adequate lip volume were achieved. This mucosal V-Y advancement flap technique represents a reliable method to repair mucosal defects without vascular compromise of the flap.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.128.1-128.1
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• 2016

Nitrided-metal gates on the high-${\kappa}$ dielectric material are widely studied because of their use for sub-20nm semiconductor devices and the academic interest for the evanescent states at the Si/insulator interface. Issues in these systems with the Si substrate are the electron mobility degradation and the reliability problems caused from N defects that permeates between the Si and the $SiO_2$ buffer layer interface from the nitrided-gate during the gate deposition process. Previous studies proposed the N defect structures with the gap states at the Si band gap region. However, recent experimental data shows the possibility of the most stable structure without any N defect state between the bulk Si valence band maximum (VBM) and conduction band minimum (CBM). In this talk, we present a new type of the N defect structure and the electronic structure of the proposed structure by using the first-principles calculation. We find that the pair structure of N atoms at the $Si/SiO_2$ interface has the lowest energy among the structures considered. In the electronic structure, the N pair changes the eigenvalue of the silicon-induced gap state (SIGS) that is spatially localized at the interface and energetically located just above the bulk VBM. With increase of the number of N defects, the SIGS gradually disappears in the bulk Si gap region, as a result, the system gap is increased by the N defect. We find that the SIGS shift with the N defect mainly originates from the change of the kinetic energy part of the eigenstate by the reduction of the SIGS modulation for the incorporated N defect.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.30A no.2
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• pp.46-52
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• 1993

The estimation of yield for semiconductor devices requires not only establishment of critical area but also a new parameter of process defect density that contains inspection mean defect density related cleanness of manufacure process line, minimum feature size and the total number of mask process. We estimate the repaired yield of memory devide, leads the semiconductor technique, repaired by redundancy scheme in relation with defect density distribution function, and we confirm the repaired yield for different devices as this model. This shows the possibility of the yield estimation as statistical analysis for the condition of device related cleanness of manufacture process line, design and manufacture process.

• Proceedings of the Korea Concrete Institute Conference
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• 2009.05a
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• pp.551-552
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• 2009

These days in execution of building works are increasing possibility of defect occurrences. On this, construction safety policy has been enforcing prevention for fault construction. But argument in relation to defects is increasing every day, because regulations for defects are abstract and uncertain. Therefore we analyzed patterns and reasons of defect, researched into question for rational solution about defect responsibility and responsibility period of a warranty in argument.

• Journal of The Korean Society of Inherited Metabolic disease
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• v.15 no.1
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• pp.25-28
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• 2015

Mitochondrial disorders are rare metabolic diseases. They often present during neonatal period but with nonspecific clinical features such as feeding difficulties, failure to thrive, and seizures. Mitochondrial defects have also known to be associated with neurological disorders, as well as cancers. We report the first case of neonatal mitochondrial respiratory chain defect with sarcoma botryoides confirmed by pathologic diagnosis, suggesting another possible link between mitochondrial dysfunction and cancer.