• 한국산업정보학회논문지
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• 제11권5호
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• pp.163-169
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• 2006

In order to use parallel computers in specific applications, algorithms need to be developed and mapped onto parallel computer architectures. Main memory access for shared memory system or global communication in message passing system deteriorate the computation speed. In this paper, it is found that the m-step generalization of the block Lanczos method enhances parallel properties by forming in simultaneous search direction vector blocks. QR factorization, which lowers the speed on parallel computers, is not necessary in the m-step block Lanczos method. The m-step method has the minimized synchronization points, which resulted in the minimized global communications and main memory access compared to the standard methods.

• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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• pp.13-16
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• 2005

It would be desirable to have methods for specific problems, which have low communication costs compared to the computation costs, and in specific applications, algorithms need to be developed and mapped onto parallel computer architectures. Main memory access for shared memory system or global communication in message passing system deteriorate the computation speed. In this paper, it is found that the m-step generalization of the block Lanczos method enhances parallel properties by forming m simultaneous search direction vector blocks. QR factorization, which lowers the speed on parallel computers, is not necessary in the m-step block Lanczos method. The m-step method has the minimized synchronization points, which resulted in the minimized global communications compared to the standard methods.

• 한국지리정보학회지
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• 제20권1호
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• pp.137-151
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• 2017

도시표면의 건물정보는 빗물의 유출경로이며 또한 격자기반의 수치해석을 위한 빗물흐름과 건물 외곽을 구분하는 경계조건에 해당한다. 경계조건인 건물자료의 왜곡 최소화는 수치해석 결과의 사실성 확보를 위한 필수적 과정이다. 격자기반의 래스터 전환은 건물자료의 왜곡을 유발하기 때문에 왜곡의 정도를 완화시키기 위한 전처리로 건물 일반화가 필요하다. 본 연구의 목적은 건물 일반화가 일반주거지역의 빗물 유출경로 연속성에 미치는 영향을 분석하고 적정한 일반화 임계값과 수치해석 격자크기를 제시하고자 한다. 빗물 유출경로 연결성 평가를 위한 설명변수로는 일반화 임계값과 수치계산 격자크기를 사용하는 한편 종속변수로는 격자망의 단절 개수와 단절면적을 사용했다. 적정한 격자크기와 일반화 임계값 선정은 임의 격자크기와 임계값을 적용한 일반화 결과로부터 산출된 건물 면적 변화율과 단절 면적 변화율 각각을 비교하고 크기가 가장 낮은 것으로 하였다. 적정 임계값과 격자크기 범위는 각각 3m와 $5{\times}5m{\sim}10{\times}10m$ 이었다. 이를 적용한 결과 건물면적 증가율은 5%이하 그리고 단절면적 감소율은 94.4%이상이었다. 대상지 토지용도를 구분한 건물 일반화 모의 결과, 아파트 단지인 3종의 건물면적과 빗물 유출경로 연결성은 임계값 10m이하에서 크게 변하지 않았다. 한편 개별 주택인 2종 지역에서는 임계값 3m와 격자크기 $5{\times}5m$을 적용한 모의결과는 단절면적의 감소와 양호한 유출경로 연결성을 보였다.

• 호남수학학술지
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• 제32권3호
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• pp.481-491
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• 2010

In this paper, we investigate a generalization of the Adams-Bashforth method by using the Taylor's series. In case of m-step method, the local truncation error can be expressed in terms of m - 1 coefficients. With an appropriate choice of coefficients, the proposed method has produced much smaller error than the original Adams-Bashforth method. As an application of the generalized Adams-Bashforth method, the accuracy performance is demonstrated in the satellite orbit prediction problem. This implies that the generalized Adams-Bashforth method is applied to the orbit prediction of a low-altitude satellite. This numerical example shows that the prediction of the satellite trajectories is improved one order of magnitude.

• Smart Structures and Systems
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• 제29권1호
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• pp.153-166
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• 2022

Identifying fine cracks in steel bridge facilities is a challenging task of structural health monitoring (SHM). This study proposed an end-to-end crack image segmentation framework based on a one-step Convolutional Neural Network (CNN) for pixel-level object recognition with high accuracy. To particularly address the challenges arising from small object detection in complex background, efforts were made in loss function selection aiming at sample imbalance and module modification in order to improve the generalization ability on complicated images. Specifically, loss functions were compared among alternatives including the Binary Cross Entropy (BCE), Focal, Tversky and Dice loss, with the last three specialized for biased sample distribution. Structural modifications with dilated convolution, Spatial Pyramid Pooling (SPP) and Feature Pyramid Network (FPN) were also performed to form a new backbone termed CrackDet. Models of various loss functions and feature extraction modules were trained on crack images and tested on full-scale images collected on steel box girders. The CNN model incorporated the classic U-Net as its backbone, and Dice loss as its loss function achieved the highest mean Intersection-over-Union (mIoU) of 0.7571 on full-scale pictures. In contrast, the best performance on cropped crack images was achieved by integrating CrackDet with Dice loss at a mIoU of 0.7670.

• 대한수학회논문집
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• 제31권1호
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• pp.147-161
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• 2016

In this paper, we study the strong convergence and stability of a new two step random iterative scheme with errors for accretive Lipschitzian mapping in real Banach spaces. The new iterative scheme is more acceptable because of much better convergence rate and less restrictions on parameters as compared to random Ishikawa iterative scheme with errors. We support our analytic proofs by providing numerical examples. Applications of random iterative schemes with errors to variational inequality are also given. Our results improve and establish random generalization of results obtained by Chang [4], Zhang [31] and many others.