• Journal of Trauma and Injury
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• v.33 no.1
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• pp.48-52
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• 2020

Composite skull defects in patients with severe head injuries are very challenging to manage. The dilemma when deciding whether to perform a definitive reconstruction is how long to wait for physiological recovery before an intervention complicates the situation. The inability of such patients to tolerate prolonged anesthetic exposure is a driving factor for performing the minimal intervention necessary to facilitate recovery. Herein, we present a case involving the successful immediate reconstructive treatment of a severely head-injured adolescent with a composite scalp defect secondary to trauma. A 14-year-old boy sustained a severe head injury from a motor vehicle accident with a composite scalp defect in the right fronto-parietal region. The frontal lobe was exposed, and the right eye was crushed and devitalized. The patient was deeply unconscious for 3 days, without any significant improvements before reconstructive surgery was proposed due to fear of possible meningitis resulting from the exposure of brain structures. We successfully managed the patient with a fronto-parieto-occipital flap, after which the patient promptly recovered consciousness.

• Journal of Applied Reliability
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• v.18 no.3
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• pp.240-249
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• 2018

Purpose: The purpose of this research is to find which technique, between the PAUT (Phased array ultrasonic test) that has been used widely in practice and RT (Radiographic test) that was used widely in the past, has the higher reliability as a non-destructive testing of welding points in water wall tubes. Methods: To evaluated the reliability of non-destructive testing, eleven test pieces that were fabricated intentionally, which have the most frequently occurred defect types in water wall tubes and then both the PAUT and RT were performed on those eleven test pieces to compare their reliability. Results: The differences of type of defect, length are occurred due to the characteristics of nondestructive testing. The RT could not detect the lack of fusion defect type in specimen #4 and #8 while PAUT could not detect the lateral crack and 1 mm size small porosity in specimen #11. Conclusion: It is concluded that applying both the RT and PAUT result the best reliability rather than applying only one test method, if it is possible, in nondestructive testing of weld water wall tube in thermal power plant boiler case.

• Pediatric Infection and Vaccine
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• v.5 no.2
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• pp.283-288
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• 1998

Recurrent meningitis in children is not only a potentially life threatening condition, but often involves the child in the trauma though repeated hospital admissions and multiple invasive investigations to find the underlying causes. Symptoms and signs of CSF rhinorrhea or otorrhea are infrequent in these patients and difficult to diagnose in young children. All young children treated for meningitis should then be administered an evoked potential audiometry as a post-treatment test. If sensorineural hearing loss is identified, the clinician should be alerted to the possibility of CSF leakage as the cause of the meningitis. Radiologic studies should be performed to rule out preexisting congenital, or acquired, abnormalities requiring surgical exploration. Two young children with recurrent meningitis due to a right cochlear aplasia and a cribriform plate defect caused by trauma are presented to illustrate the problems of diagnosis and management. A review of literatures will also be presented briefly.

• Journal of Trauma and Injury
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• v.20 no.2
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• pp.119-124
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• 2007

Purpose: Management of the soft tissue defect in the lower extremity caused by trauma has always been difficult. Coverage with local and free muscle flaps after complete surgical excision of necrotic soft tissue and bone is a major strategy for treatment. There is no doubt that muscle provides a good blood supply, thus improving bone healing and increasing resistance to bacterial inoculation. However, accompanying problems are seen in cases with shallow dead space. This research was conducted to assess the efficacy of raising anterolateral thigh flaps and transferring them to the defect after complete debridement of non-viable, infected, and scar tissue as an alternative way to use local or free muscle flaps. Methods: From March 2005 to October 2007, 18 cases of soft tissue defect on lower extremities were re-surfaced with an anterolateral thigh perforator free flap. Results: The follow-up period ranged from 1 to 31 months with a mean of 15.9 months. All flaps survived completely. Satisfactory aesthetic and functional results were achieved. Under a two-point discrimination test, 13 patients had sensory recovery from 11 mm to 20 mm after 6 months postoperatively. Conclusion: Reconstruction of the lower extremity with anterolateral thigh perforator free flaps after appropriate debridement is a good alternative way to use local or free muscle flaps.

• Journal of Distribution Science
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• v.17 no.4
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• pp.51-57
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• 2019

Purpose - This study aims to improve the distribution structure of the OLED market and develop cost-effective optimization techniques. Specifically, it is a study on the optimization of ferric chloride to improve the etch of SUS MASK for OLED. Research design, data, and methodology - Applying the optimal conditions of the experiment, the final confirmation was evaluated for improvement by the Process Capability Index (Cpk). It is possible to derive social performance such as improvement of precision of SUS MASK manufacturing, economic performance such as defect rate, reduction of waste generation and treatment cost, technological achievement such as SUS MASK production technology, improvement of profit structure of technology development and process improvement do. Results - The improvement of the Cpk before the improvement was made was confirmed to be 0.57% with a defect estimate of 25.07% with a failure estimate of 0.57% after the improvement, and 8.84% with a failure estimate of 0.57% level after the improvement. Conclusions - If the conclusions obtained from the specimen experiment are applied to the manufacturing process of SUS MASK, it will be possible to expect excellent cost-effective competitiveness due to the improvement of precision and reduction of defect rate to enhance the OLED market penetration.

• Industrial Engineering and Management Systems
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• v.9 no.3
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• pp.251-261
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• 2010

This article demonstrated the application of the Fuzzy Data Envelopment Analytical Hierarchy Process (FDEAHP) to evaluate the root causes of critical defect problems occurring in the production of liquid medicine. The methodology of the research began by collecting the defect data by using Check Sheets, and ranking the significant problems by using a Pareto Diagram. Two types of major problems were found to occur, including glass fragments in the medicine and damaged lid threads. The causes of each problem were then analyzed by using Cause and Effect Diagrams. The significant causes were ranked by FDEAHP under three criteria, Severity (S), Occurrence (O) and Detection (D), followed by the framework of the FMEA Technique. Two causes with the highest Final Weight (FW) of each problem were selected to be improved, such as installing auxiliary equipment, using the Poka-Yoke system, setting the scale of the shaft and lathing the bushes of each bottle size. The results demonstrated a reduction in defects from 3.209% to 1.669% and showed that improving a few significant root causes, identified by an experienced decision maker, was sufficient to reduce the defect rate.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.8
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• pp.596-600
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• 2009

To support an efficient management of software verification and validation activities, many defect prediction models have been proposed based on object oriented metrics. They usually adopt logistic regression analysis, And, they state that the correctness of prediction is about 60${\sim}$70%, We performed a similar experiment with Eclipse 3.3 to check their prediction effectiveness, However, the result shows that correctness is about 40% which is much lower than the original results. We also found that univariate logistic regression analysis produces better results than multivariate logistic regression analysis.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.168-173
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• 2022

As the function of a product is advanced and the process is refined, the yield in the fine manufacturing process becomes an important variable that determines the cost and quality of the product. Since a fine manufacturing process generally produces a product through many steps, it is difficult to find which process or equipment has a defect, and thus it is practically difficult to ensure a high yield. This paper presents the system architecture of how to build a smart manufacturing system to analyze the big data of the manufacturing plant, and the equipment factor analysis methodology to increase the yield of products in the smart manufacturing system. In order to improve the yield of the product, it is necessary to analyze the defect factor that causes the low yield among the numerous factors of the equipment, and find and manage the equipment factor that affects the defect factor. This study analyzed the key factors of abnormal equipment that affect the yield of products in the manufacturing process using the data mining technique. Eventually, a methodology for finding key factors of abnormal equipment that directly affect the yield of products in smart manufacturing systems is presented. The methodology presented in this study was applied to the actual manufacturing plant to confirm the effect of key factors of important facilities on yield.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.200-201
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• 2021

According to the dispute cases filed for claiming the collective defect repair fees, inter-layer concrete joints turned out to be the most frequently disputed item. For this reason, this study selects the inter-layer concrete joints to further analyze the primary causes and details of each dispute case. From the results of this study, three primary causes of the disputes are found, which are 1) the absence of standard specifications for construction quality control and management after construction; 2) the absence of established standards for repair when construction defects are found. In order to prevent construction defects in inter-layer concrete joints, this study provides three suggestions including 1) the current standard specifications for inter-layer concrete joints should be further specified by the Ministry of Land, Infrastructure and Transport; 2) a construction defect should be judged according to the compliance to the standard specifications; and 3) a clear and institutional protocol needs to be established for defect repair in cases that new public apartment houses have been judged to have defects.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.625-627
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• 2022

In the construction and development of modern industrial production technology, the traditional technology management mode is faced with many problems such as low qualification rates and high application costs. In the research, an improved workpiece defect detection method based on deep learning is proposed, which can control the application cost and improve the detection efficiency of irregular defects. Based on the research of the current situation of deep learning applications, this paper uses the improved Faster R-CNN network structure model as the core detection algorithm to automatically locate and classify the defect areas of the workpiece. Firstly, the robustness of the model was improved by appropriately changing the depth and the number of channels of the backbone network, and the hyperparameters of the improved model were adjusted. Then the deformable convolution is added to improve the detection ability of irregular defects. The final experimental results show that this method's average detection accuracy (mAP) is 4.5% higher than that of other methods. The model with anchor size and aspect ratio (65,129,257,519) and (0.2,0.5,1,1) has the highest defect recognition rate, and the detection accuracy reaches 93.88%.