• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.109-114
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• 2021

When we inspect scaffold defect using sight, inspecting performance is decrease and inspecting time is increase. We need for automatically scaffold defect detection method to increase detection accuracy and reduce detection times. In this paper. We produced scaffold defect classification models using densenet, alexnet, vggnet algorithms based on CNN. We photographed scaffold using multi dimension camera. We learned scaffold defect classification model using photographed scaffold images. We evaluated the scaffold defect classification accuracy of each models. As result of evaluation, the defect classification performance using densenet algorithm was at 99.1%. The defect classification performance using VGGnet algorithm was at 98.3%. The defect classification performance using Alexnet algorithm was at 96.8%. We were able to quantitatively compare defect classification performance of three type algorithms based on CNN.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.679-680
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• 2009

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.115-116
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• 2009

• Journal of Periodontal and Implant Science
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• v.38 no.3
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• pp.437-444
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• 2008

Purpose: A number of techniques and materials have been used for periodontal regeneration and bone graft procedures with guided tissue regeneration(GTR) have been suggested as alternatives to osseous surgery in the management of local infra-bony defects. However, the long-term stability and treatment outcome following bone graft procedure of infra-bony defects is poorly documented. The purpose of this study was to assess radiographic change in infra-bony defects over 2 years after bone graft procedures with various graft materials. Material and Methods: Patients attending the department of periodontics of Kyungpook National University Hospital were studied. Patients showed clinical and radiographic evidence of infra-bony defect(s). 44 sites of 34 patients aged 31 to 69 (mean age 48.3) were treated by bone graft procedure with a bone graft material. Baseline and 2-year follow-up radiographs were collected and evaluated for this study. Radiographic assessment includes a bone fill, bone crest change, defect resolution, and % of defect resolution. Pre- and post-treatment differences between variables (maxilla and mandible, defect depth, defect angle, bone graft materials) using the paired t-test were examined. Result: We observed $1.15{\pm}1.95\;mm$ of bone fill, $0.40{\pm}1.19\;mm$ of crestal resorption, $1.55{\pm}1.77\;mm$ of defect resolution, and $40{\pm}44%$ of percentage of defect resolution. Deeper initial defect depth, narrower initial defect angle showed significantly greater bone fill, defect resolution, and % of defect resolution. But no significant difference was observed in graft sites and graft materials. Conclusion: If good oral hygiene maintenance and periodic recall check of patients is assured, bone graft procedure using various graft materials is one of the appropriate treatment modality for regenerative therapy of infra-bony defects.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.125-130
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• 2021

Scaffold is used to produce bio sensor. Scaffold is required high dimensional accuracy. 3D printer is used to manufacture scaffold. 3D printer can't detect defect during printing. Defect detection is very important in scaffold printing. Real-time defect detection is very necessary on industry. In this paper, we proposed the method for real-time scaffold defect detection. Real-time defect detection model is produced using CNN(Convolution Neural Network) algorithm. Performance of the proposed model has been verified through evaluation. Real-time defect detection system are manufactured on hardware. Experiments were conducted to detect scaffold defects in real-time. As result of verification, the defect detection system detected scaffold defect well in real-time.

• Journal of the Korean housing association
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• v.27 no.5
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• pp.65-72
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• 2016

The purpose of the study was to investigate defect cases in residential interior design, to identify the state of defects, and to categorize types of defect and disputes. In addition, consumer appraisal to residential interior design service were analyzed. The results of this study could provide fundamental information regarding the defects and claims in residential interior design. First, we did literature review for defect disputes in architectural design and interior design. We identify the definition of defects by building life cycle, by state of construction, by activity, and by design performance. Second, we analysed interior design defects cases reported in Korea Consumer Agency & Ministry of Land, Infrastructure and Transport. A total of 49 cases of defect disputes in residential interior design from 2000 to 2015 were investigated. As a result, many defects appeared during the construction stage. A majority of defects cases fall into insulation, water-proofing/leakage work. In terms of design aspects claim, functional and aesthetic defects were claimed. Third, from Consumer Market Evaluation Indicators, raw data from 500 respondents were investigated for the housing repair and interior design. It is found that information comparability, responsiveness to consumer claim, price, and safety are important factors for consumer satisfaction in interior design.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.5
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• pp.1202-1210
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• 1995

Aiming at nondestructive evaluation of defect with high accuracy and resolution, ICFPD(Induced Current Focusing Potential Drop) technique was newly developed. This technique can be applied for locating and sizing of defects in components with not only simple shape such as plain surface but also more complex shape and geometry such as curved surface and dissimilar joing. This paper describes the principle of ICFPD technique and also the results of 2-dimensional surface crack in ferromagnetic metal(A508 Cl. III steel) and paramagnetic metal (pure aluminum and stainless 304 steel) measured by this technique. Results are that surface defects in each specimen are detected with the difference of potential drop, and potential drops are distributed a similar shape for each metal and each depth. The normalized potential drop ( $V_{\delta}$2/$^{t}$ / $V_{{\delta} 2}$$^{-1}$) max. in the vicinity of defect is varied with the depth of defect. Therefore, ICFPD technique can be used for the evaluation of defect not only in ferromagnetic metal but also in paramagnetic steel..

• Archives of Craniofacial Surgery
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• v.20 no.1
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• pp.17-23
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• 2019

Background: The resection of head and neck cancer can result in postoperative defect. Many patients have difficulty swallowing and masticating, and some have difficulty speaking. Various types of flaps are used for palatal reconstruction, but flap selection remains controversial. Therefore, our study will suggest which flap to choose during palatal reconstruction. Methods: Thirteen patients who underwent palatal reconstruction from 30 January, 1989 to 4 October, 2016 at our institution. Size was classified as small when the width was < $4cm^2$, medium when it was $4-6cm^2$, and large when it was ${\geq}6cm^2$. Based on speech evaluation, the subjects were divided into a normal group and an easily understood group. After surgery, we assessed whether flap selection was appropriate through the evaluation of flap success, complications, and speech evaluation. Results: Defect size ranged from $1.5{\times}2.0cm$ to $5.0{\times}6.0cm$. In four cases, the defect was in the anterior third of the palate, in eight cases it was in the middle, and there was one case of whole palatal defect. There were three small defects, two medium-sized defects, and eight large defects. Latissimus dorsi free flaps were used in six of the eight large defects in the study. Conclusion: The key to successful reconstructive surgery is appropriate selection of the flap with reference to the characteristics of the defect. Depending on the size and location of the defect, the profiles of different flaps should be matched with the recipient from the outset.

• Journal of IKEEE
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• v.25 no.4
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• pp.689-696
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• 2021

In this paper, in order to apply Prognostics and Health Management(PHM) to an electronic system or circuit, a circuit capable of detecting and predicting defect characteristics inside the system or circuit is implemented, and the results are described. In the previous study, we demonstrated that the frequency of the amplitude of S-parameter changed as the circuit defect progressed. These characteristics were measured by network analyser. but in this study, even if the same defect detection method is used, a circuit is proposed to check the progress of the defect, the remaining time, and the occurrence of the defect without large measurement devices. The circuit is designed to detect the change in impedance that generates changes of S-parameter, and it is verified through simulation using the measurement results of Bond-wires.

• Journal of Welding and Joining
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• v.16 no.3
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• pp.64-73
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• 1998

This paper is concerned with defects detection and evaluation of heat affected zone (HAZ) in austenitic stainless steel type 304 by ultrasonic wave and neural network. In experiment, the reflected ultrasonic defect signals from artificial defects (side hole, vertical hole, notch) of HAZ appears as beam distance of prove-defect, distance of probe-surface, depth of defect-surface on CRT. For defect classification simulation, neural network system was organized using total results of ultrasonic experiment. The organized neural network system was learned with the accuracy of 99%. Also it could be classified with the accuracy of 80% in side hole, and 100% in vertical hole, 90% in notch about ultrasonic pattern recognition. Simulation results of neural network agree fairly well with results of ultrasonic experiment. Thus were think that the constructed system (ultrasonic wave - neural network) in this work is useful for defects dection and classification such as holes and notches in HAZ of austenitic stainless steel 304.