• Journal of Chest Surgery
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• v.6 no.1
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• pp.51-56
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• 1973

This is one case report of successful resection of the aneurysm of the thoracic aorta, which det-ected by thoractomy unexpectedly, in the Department of Thoracic Surgery, Hanyang University Hospital. The patient was a 34 years old woman and subjective complaints was not related with the aneurysm. Chest film showed a small round hazy shadow in the left margin of the upper posterior mediastinum. A saccular aneurysm located on the descending thoracic aorta, 7cm distal to the left subclavian artery and arouse from the antero-lateral wall of the aorta. Excision of the saccular aneurysm was performed by cross clamping the descending aorta above and below the aneurysm, and then the defect of the aortic wall was closed by aortorrhaphy with continuous suture. Crossclamping time was required 15 minute. Histopathologically, the wall of the aneurysm consisted of all layers of the arterial wall, that is, intima, media and adventitia. Postoperative course was uneventful and aortogram showed good continuity of the blood flow of the entire aorta.

• Journal of Advanced Marine Engineering and Technology
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• v.2 no.1
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• pp.3-14
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• 1978

The authors have developed a calculating method of propeller shaft alignment by the finite element method. The propeller shaft is divided into finite elements which can be treated as uniform section bars. For each element, the nodal point equation is derived from the stiffness matrix, the external force vector and the section force vector. Then the overall nodal point equation is derived from the element nodal point equation. The deflection, offset, bending moment and shearing force of each nodal point are calculated from the overall nodal point equation by the digital computer. Reactions and deflections of supporting points of straight shaft are calculated and also the reaction influence number is derived. With the reaction influence number the optimum alignment condition that satisfies all conditions is calculated by the simplex method of linear programming. All results of calculation are compared with those of Det norske Veritas, which has developed a computor program based on the three-moment theorem of the strength of materials. The authors finite element method has shown good results and will be used effectively to design the propeller shaft alignment.

• Annual Conference of KIPS
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• 2014.04a
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• pp.749-752
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• 2014

본 논문에서는 저속으로 동작하는 구름 베어링의 다중 결함 조기 검출을 위해 결함 특징 추출, 효과적인 특징 선택, 선택된 특징을 이용한 결함 분류의 세 단계로 구성된 결함 진단 기법을 제안한다. 1단계에서 이산 웨이블릿 변환을 이용하여 미세성분으로부터 통계적 결함 특징을 추출하고, DET(distance evaluation technique)를 이용하여 추출한 결함 특징 가운데 베어링 다중 결함 검출에 효과적인 특징을 선택한다. 마지막으로 선택된 특징을 k-NN(k-Nearest Neighbors) 분류기 입력으로 사용함으로써 결함을 진단한다. 본 논문에서는 제안한 결함 진단 기법의 성능을 분류 정확도 측면에서 평가한 결과 95.14%의 높은 분류 정확도를 보였다.

• Journal of the Korean Ceramic Society
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• v.35 no.5
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• pp.443-450
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• 1998

Layered double hydroxides(LDHs) [{{{{ {Mg }_{1-x } }}{{{{ {Al }_{x } }}({{{{ {OH}_{2 } }})]ζ+({{{{ {CO }`_{3 } ^{2- } ){ }_{x/2 } }}$.${{{{ { yH}_{2 }O }} wioth variation of layer charge densitywere synthesized by co-precipitation methdo since their charge densities have a very important role to be det-ermined the physicochemical properties of layered materials. The XRD IR and thermal studies of them were discussed and the kinetic study for the decarbonation reaction was also carried out. From the results of XRD analysis we found that the lattice parameter and the unit cell volume were linearly decreased with the amount of Al substituents(x) in the vicinity of x=2∼10${\times}$1/3${\times}$10-1 but they had nearly constant values when the x are far from these vicinit. The activation energies for the decarbonation reaction of x=6.8, 10${\times}$1/3${\times}${{{{ { 10}^{-1 } }} were estimated to be 47.0, 37.6, 39.3 kcal/mol The specific surface areas(90-120 m2/g) of stable hy-drotalcite-type LDHs were dractically decreased with increasing of layer charge density.

• The Journal of Bigdata
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• v.7 no.2
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• pp.31-41
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• 2022

Steel is one of the most fundamental components to mechanical industry. However, the quality of products are greatly impacted by the surface defects in the steel. Thus, researchers pay attention to the need for surface defects detector and the deep learning methods are the current trend of object detector. There are still limitations and rooms for improvements, for example, related works focus on developing the models but don't take into account real-time application with practical implication on industrial settings. In this paper, a real-time application of steel surface defects detection based on YOLOv4 is proposed. Firstly, as the aim of this work to deploying model on real-time application, we studied related works on this field, particularly focusing on one-stage detector and YOLO algorithm, which is one of the most famous algorithm for real-time object detectors. Secondly, using pre-trained Yolov4-Darknet platform models and transfer learning, we trained and test on the hot rolled steel defects open-source dataset NEU-DET. In our study, we applied our application with 4 types of typical defects of a steel surface, namely patches, pitted surface, inclusion and scratches. Thirdly, we evaluated YOLOv4 trained model real-time performance to deploying our system with accuracy of 87.1 % mAP@0.5 and over 60 fps with GPU processing.

• Geomechanics and Engineering
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• v.38 no.1
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• pp.29-44
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• 2024

This research investigates the effectiveness of data augmentation techniques in the automated analysis of B-scan images from ground-penetrating radar (GPR) using deep learning. In spite of the growing interest in automating GPR data analysis and advancements in deep learning for image classification and object detection, many deep learning-based GPR data analysis studies have been limited by the availability of large, diverse GPR datasets. Data augmentation techniques are widely used in deep learning to improve model performance. In this study, we applied four data augmentation techniques (geometric transformation, color-space transformation, noise injection, and applying kernel filter) to the GPR datasets obtained from a testbed. A deep learning model for GPR data analysis was developed using three models (Faster R-CNN ResNet, SSD ResNet, and EfficientDet) based on transfer learning. It was found that data augmentation significantly enhances model performance across all cases, with the mAP and AR for the Faster R-CNN ResNet model increasing by approximately 4%, achieving a maximum mAP (Intersection over Union = 0.5:1.0) of 87.5% and maximum AR of 90.5%. These results highlight the importance of data augmentation in improving the robustness and accuracy of deep learning models for GPR B-scan analysis. The enhanced detection capabilities achieved through these techniques contribute to more reliable subsurface investigations in geotechnical engineering.

• Journal of the Korean Society of Safety
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• v.15 no.2
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• pp.126-135
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• 2000

Probabilistic Safety Assessment (PSA) is an engineering analysis method to identify possible contributors to the risk from a nuclear power plant and now it has become a standard tool in safety evaluation of nuclear power plants. PSA consists of three phases named as Level 1, 2 and 3. Level 2 PSA, mainly focused in this paper, uses a step-wise approach. At first, plant damage states (PDSs) are defined from the Level 1 PSA results and they are quantified. Containment event tree (CET) is then constructed considering the physico-chemical phenomena in the containment. The quantification of CET can be assisted by a decomposition event tree (DET). Finally, source terms are quantitatively characterized by the containment failure mode. As the main benefit of PSA is to provide insights into plant design, performance and environmental impacts, including the identification of the dominant risk contributors and the comparison of options for reducing risk, this technique is expected to be applied to the industrial safety area.

• Journal of Integrative Natural Science
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• v.1 no.1
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• pp.24-31
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• 2008

Brassinosteroids (BRs) are a special class of plant steroid hormones that are essential for normal growth and development. Part of confusion is whether BRs are unique to plants, because they have overlapping physiological roles with other better-studied hormones and with physiological responses caused by light. In systems designed to assay for cytokinins, the effects of BRs vary. We measured hypocotyl length for testing the ability of brassinolide (BL) to rescue double mutant between det2 and the photoreceptor null mutant phytochrome B (phyB). PHYB involved in controlling hypocotyl elongation in increased concentration of BL whereas phyBdet2 double mutant just partially rescue to phyB in white and red light indicated the involvement of BRs in PHYB regulated cell elongation. BRs regulated hypocotyl growth was delayed by BAP, a cytokinin treatment but inhibitory effects of BAPs on hypocotyl growth was slightly recovered by BL. The result indicated that the mode of action of BR and cytokinin is independent or sequential in the downstream light-regulated response control on hypocotyl elongation and also light modulated the action of BR and cytokinin in some extent.

• ETRI Journal
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• v.42 no.2
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• pp.230-238
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• 2020

Human-object interaction (HOI) detection is a popular computer vision task that detects interactions between humans and objects. This task can be useful in many applications that require a deeper understanding of semantic scenes. Current HOI detection networks typically consist of a feature extractor followed by detection layers comprising small filters (eg, 1 × 1 or 3 × 3). Although small filters can capture local spatial features with a few parameters, they fail to capture larger context information relevant for recognizing interactions between humans and distant objects owing to their small receptive regions. Hence, we herein propose a three-stream HOI detection network that employs a context convolution module (CCM) in each stream branch. The CCM can capture larger contexts from input feature maps by adopting combinations of large separable convolution layers and residual-based convolution layers without increasing the number of parameters by using fewer large separable filters. We evaluate our HOI detection method using two benchmark datasets, V-COCO and HICO-DET, and demonstrate its state-of-the-art performance.

• Journal of Convergence Society for SMB
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• v.6 no.4
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• pp.1-8
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• 2016

In this study, we must investigate what the major success factors that should be considered before introducing to successfully achieve the goal of building enterprise information systems. To evaluate the factors significantly affecting among the success factors. This study is to present by analyzing the typical success factors affecting successful introduction of the system information to companies that lack sufficient information and reviews for the introduction of enterprise information systems.