• 한국방재학회:학술대회논문집
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• 한국방재학회 2008년도 정기총회 및 학술발표대회
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• pp.279-282
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• 2008

The vertical forces in rail fasteners at areas of bridge transitions near the embankment and on the pier will occur due to different deformations of adjoining bridges caused by the trainloads. The up-lifting forces is not large problem in the blast track because the elasticity of blast and rail pad buffs up-lifting effect. But, it is likely to be difficult to ensure the serviceability of the railway and the safety of the fastener in the end in that concrete slab track consist of rail, fastener, and track in a single body, delivering directly the up-lifting force to the fastener if the deck is bended because of the end rotation of the overhang due to the vertical load. When the up-lifting force exceeds the clamp force of the fastener clip, the rail pad is out of fastener, which makes decrease the serviceability of the railway, such as noise and vibration. Furthermore, it is possible to reduce the safety of the track as the longitudinal resistance. This study is focused on guideline suggestion to decrease up-lifting force in the fastener adjacent to the civil joint of slab track of bridge throughout the parametric analysis between the vertical spring stiffness of the fastener as the material approach, the space of fastener adjacent to bridge transition, the rigidity of the girder as the geometrical approach and up-lifting force under the train load.

• 지식경영연구
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• 제1권1호
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• pp.65-80
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• 2000

The main purpose of this study is to answer a question that how a company can be a learning organization producing useful knowledge by applying neuro-cybernetics approach. This approach borrows its working principles from the human body systems. The current study urges that the principles can be applied to build a learning organization. System 1 to 5, the core parts of neuro-cybernetics, are explained. And it is explored that how these systems can be designed for a company to be a learning organization. Limitations of the current study are discussed at the end of the paper.

• Smart Structures and Systems
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• 제29권1호
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• pp.221-235
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• 2022

Manual inspection of steel box girders on long span bridges is time-consuming and labor-intensive. The quality of inspection relies on the subjective judgements of the inspectors. This study proposes an automated approach to detect and segment cracks in high-resolution images. An end-to-end cascaded framework is proposed to first detect the existence of cracks using a deep convolutional neural network (CNN) and then segment the crack using a modified U-Net encoder-decoder architecture. A Naïve Bayes data fusion scheme is proposed to reduce the false positives and false negatives effectively. To generate the binary crack mask, first, the original images are divided into 448 × 448 overlapping image patches where these image patches are classified as cracks versus non-cracks using a deep CNN. Next, a modified U-Net is trained from scratch using only the crack patches for segmentation. A customized loss function that consists of binary cross entropy loss and the Dice loss is introduced to enhance the segmentation performance. Additionally, a Naïve Bayes fusion strategy is employed to integrate the crack score maps from different overlapping crack patches and to decide whether a pixel is crack or not. Comprehensive experiments have demonstrated that the proposed approach achieves an 81.71% mean intersection over union (mIoU) score across 5 different training/test splits, which is 7.29% higher than the baseline reference implemented with the original U-Net.

• 한국통신학회논문지
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• 제29권7B호
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• pp.697-710
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• 2004

네트웍 환경에서 quality of service(QoS) 에 대한 요구가 증대함에 따라 여러 가지 방안들이 제시되고 있는 가운데, Differentiated services (DiffServ) 모델은 확장성을 보장하며 QoS를 제공할 수 있는 방법으로서 제시되고 있다. 그러나 대부분의 DiffServ 관련 연구들은 통합된 트래픽에 관한 확장성 문제와, 단일 도메인에서의 per hop behavior(PHB)에 관한 문제에만 관심을 두고 있기 때문에, 시간적으로 변화하는 네트웍 조건하에서 다중 도메인의 단대단 QoS를 제공하는 데 있어서는 많은 어려움 들이 있다. 따라서 본 연구에서는 다중 DiffServ 도메인에서 네트웍 cost를 최소화하는 가운데 멀티미디어 데이터의 단대단 QoS를 제공할 수 있는 동적 클래스 재협상알고리즘을 제안하였다. 본 논문은 DiffServ의 relative 서비스 모델을 효과적으로 구현할 수 있는 방법과 QoS 레벨 전달 메카니즘, 그리고 동적 클래스 재협상 방법으로 구성되어 있으며, 실험 결과를 통해 제안된 알고리즘의 성능을 측정한다.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2012년도 제42회 동계 정기 학술대회 초록집
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• pp.436-437
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• 2012

Double patterning technology (DPT) has been suggested as a promising candidates of the next generation lithography technology in FLASH and DRAM manufacturing in sub-40nm technology node. DPT enables to overcome the physical limitation of optical lithography, and it is expected to be continued as long as e-beam lithography takes place in manufacturing. Several different processes for DPT are currently available in practice, and they are litho-litho-etch (LLE), litho-etch-litho-etch (LELE), litho-freeze-litho-etch (LFLE), and self-aligned double patterning (SADP) [1]. The self-aligned approach is regarded as more suitable for mass production, but it requires precise control of sidewall space etch profile for the exact definition of hard mask layer. In this paper, we propose etch end point detection (EPD) in spacer etching to precisely control sidewall profile in SADP. Conventional etch EPD notify the end point after or on-set of a layer being etched is removed, but the EPD in spacer etch should land-off exactly after surface removal while the spacer is still remained. Precise control of real-time in-situ EPD may help to control the size of spacer to realize desired pattern geometry. To demonstrate the capability of spacer-etch EPD, we fabricated metal line structure on silicon dioxide layer and spacer deposition layer with silicon nitride. While blanket etch of the spacer layer takes place in inductively coupled plasma-reactive ion etching (ICP-RIE), in-situ monitoring of plasma chemistry is performed using optical emission spectroscopy (OES), and the acquired data is stored in a local computer. Through offline analysis of the acquired OES data with respect to etch gas and by-product chemistry, a representative EPD time traces signal is derived. We found that the SE-EPD is useful for precise control of spacer etching in DPT, and we are continuously developing real-time SE-EPD methodology employing cumulative sum (CUSUM) control chart [2].

• International Journal of Computer Science & Network Security
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• 제21권9호
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• pp.51-62
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• 2021

Plant disease is one of the issues that can create losses in the production and economy of the agricultural sector. Early detection of this disease for finding solutions and treatments is still a challenge in the sustainable agriculture field. Currently, image processing techniques and machine learning methods have been applied to detect plant diseases successfully. However, the effectiveness of these methods still needs to be improved, especially in multiclass plant diseases classification. In this paper, a convolutional neural network with a batch normalization-based deep learning approach for classifying plant diseases is used to develop an automatic diagnostic assistance system for leaf diseases. The significance of using deep learning technology is to make the system be end-to-end, automatic, accurate, less expensive, and more convenient to detect plant diseases from their leaves. For evaluating the proposed model, an experiment is conducted on a public dataset contains 20654 images with 15 plant diseases. The experimental validation results on 20% of the dataset showed that the model is able to classify the 15 plant diseases labels with 96.4% testing accuracy and 0.168 testing loss. These results confirmed the applicability and effectiveness of the proposed model for the plant disease detection task.

• 대한의용생체공학회:의공학회지
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• 제44권5호
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• pp.346-353
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• 2023

In this paper, we propose an innovative approach that leverages deep learning to find optimal reference points for achieving precise tooth segmentation in three-dimensional tooth point cloud data. A dataset consisting of 350 aligned maxillary and mandibular cloud data was used as input, and both end coordinates of individual teeth were used as correct answers. A two-dimensional image was created by projecting the rendered point cloud data along the Z-axis, where an image of individual teeth was created using an object detection algorithm. The proposed algorithm is designed by adding various modules to the Unet model that allow effective learning of a narrow range, and detects both end points of the tooth using the generated tooth image. In the evaluation using DSC, Euclid distance, and MAE as indicators, we achieved superior performance compared to other Unet-based models. In future research, we will develop an algorithm to find the reference point of the point cloud by back-projecting the reference point detected in the image in three dimensions, and based on this, we will develop an algorithm to divide the teeth individually in the point cloud through image processing techniques.

• Structural Engineering and Mechanics
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• 제66권5호
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• pp.557-568
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• 2018

An investigation is made in the present work on the post-buckling and geometrically nonlinear behaviors of moderately thick perfect and imperfect rectangular plates made-up of functionally graded materials. Spectral collocation approach based on Legendre basis functions is developed to analyze the functionally graded plates while they are subjected to end-shortening strain. The material properties in this study are varied through the thickness according to the simple power law distribution. The fundamental equations for moderately thick rectangular plates are derived using first order shear deformation plate theory and taking into account both geometric nonlinearity and initial geometric imperfections. In the current study, the domain of interest is discretized with Legendre-Gauss-Lobatto nodes. The equilibrium equations will be obtained by discretizing the Von-Karman's equilibrium equations and also boundary conditions with finite Legendre basis functions that are substituted into the displacement fields. Due to effect of geometric nonlinearity, the final set of equilibrium equations is nonlinear and therefore the quadratic extrapolation technique is used to solve them. Since the number of equations in this approach will always be more than the number of unknown coefficients, the least squares technique will be used. Finally, the effects of boundary conditions, initial geometric imperfection and material properties are investigated and discussed to demonstrate the validity and capability of proposed method.

• Nuclear Engineering and Technology
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• 제31권6호
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• pp.541-547
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• 1999

Corrosion control, in the end-shield cooling system of Wolsung Nuclear Power Plant, is directly related to the control of dissolved oxygen (DO). The current method, being used to deoxygenate the end-shield cooling water, is a chemical treatment by addition of reducing agent, hydrazine, to react with DO. This method has several limitations including high reaction temperature of hydrazine , unwanted explosive hydrogen gas production, and its intrinsic harmful property. A new approach to remove DO using a membrane-based oxygen removal system (MORS) was tried to overcome limitations of the hydrazine treatment. The DO removal efficiency of the MORS was found to be in the range 87% to 98%: The higher vacuum, the lower water flow rate and the higher water temperature tend to increase the DO removal efficiency.

• 한국IT서비스학회지
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• 제9권3호
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• pp.83-93
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• 2010

P2P streaming technology has advantages of scalability and availability comparing to the popular IP multicast. This paper proposes an approach to apply the P2P streaming technology to the delay-sensitive multimedia multicast applications. In order for the P2P streaming to be applied to the delay-sensitive applications, prior construction of delay-guaranteed overlay network is necessarily required. Moreover, the delay-guaranteed overlay network should be able to be kept even when the hand-overs occur owing to the departures of the intermediate P2P peers. This paper proposes a delay-guaranteed overlay network construction method by using the bandwidth and end-to-end delay based admission control and the backup peer based hand-over control mechanism.