• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2007.04a
• /
• pp.427-432
• /
• 2007

In general, the response of bulk material is independent of its size when it comes to considering classical elasticity theory. Because the surface to bulk ratio of the large solids is very small, the influence of surface can be negligible. But the surface effect plays important role as the surface to bulk ratio becomes larger, that is, the contribution of the surface effect must be considered in nano-size elements such as thin film or beam structure. Molecular dynamics computation has been a conventional way to analyze these ultra-thin structures but this method is limited to simulate on the order of $10^6-10^8$ atoms for a few nanoseconds, and besides, very time consuming. Analysis of structures in submicro to micro range(thin-film, wire etc.) is difficult with classical molecular dynamics due to the restriction of computing resources and time. Therefore, in this paper, the continuum-based method is considered to simulate the overall physical and mechanical properties of the structures in nano-scale, especially, for the thin-film.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.24 no.4
• /
• pp.413-419
• /
• 2011

The nano-size hoenycomb structures have the higher ratio of the surface to the volume than macro-size honeycomb structures, and they can maximize the functionality of the electrical and chemical catalyst. The mechanical behaviors of the nano-sized structures are different from ones of the macro-size structure, and it is caused by the surface effect. This surface effect can be investigated by the atomistic simulation; however, the prediction of mechanical behaviors of the nano-sized honeycombs are practically impossible due to excessive computational resources and computation time. In this paper, by combining the bridging method considering the surface stress elasticity model with homogenization method, the mechanical behaviors of the nano-sized honeycombs are predicted efficiently.

• Proceedings of the Korean Society For Composite Materials Conference
• /
• 2004.04a
• /
• pp.67-70
• /
• 2004

An investigation was performed to study the impact damage of the laminated composite plates caused by a low- velocity foreign object with multi-scale modeling based on the concepts of Direct Numerical Simulation (DNS)[4]. In the micro-scale part, we discretize the composite plates through separate modeling of fiber and matrix for the local microscopic analysis. A micro-scalemodel was developed for predicting the initiation of the damage and the extent of the final damage as a function of material properties, laminate configuration and the impactor's mass, etc. Anda macro-scale model was developed for description of global dynamic behavior. The connection betweenmicroscopic and macroscopic is implemented by the tied interface constraints of LS-DYNA contact card. A transient dynamic finite element analysis was adopted for calculating the contact force history and the stresses and strains inside the composites during impact resulting from a point-nose impactor. The low-velocity impact events such as contact force, deformation, etc. are simulated in the macroscopic sense and the impact damages, fiber-breakage, matrix cracking and delamination etc. are examined in the microscopic sense.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2004.05b
• /
• pp.64-67
• /
• 2004

Points of sharp variations in images are the most important components when we analyze singularities of images. Therefore a lot of researches for detecting those edges have been continuing even now. However, existing methods do not have excellent performance in the image which exists noise and can not detect edge selectively. In the meantime, the wavelet transform which is presented as a new technique of signal processing field is able to detect multiscale edge and is being applied widely in many fields that analyze singularities such as edge. for this reason, this paper detected image's line-edge elements with 2-D wavelet function, which is independent of line's width, in noise environment.

• Tribology and Lubricants
• /
• v.30 no.6
• /
• pp.378-383
• /
• 2014

This study predicts the of the hysteretic friction of a rubber block sliding on an SMA asphalt road. The friction of filled rubber on a rough surface is primarily determined by two elements:the viscoelasticity of the rubber and the multi-scale perspective asperities of the road. The surface asperities of the substrate exert osillating forces on the rubber surface leading to energy dissipation via the internal friction of the rubber when rubber slides on a hard and rough substrate. This study defines the power spectra at different length scales by using a high-resolution surface profilometer, and uses rubber and road surface samples to conduct friction tests. I consider in detail the case when the substrate surface has a self affine fractal structure. The theory developed by Persson is applied to describe these tests through comparison with the hysteretic friction coefficient relevant to the energy dissipation of the viscoelastic rubber attributable to cyclic deformation. The results showed differences in the absolute values of predicted and measured friction, but with high correlation between these values. Hence, the friction prediction model is an appropriate tool for separating the effects of each factor. Therefore, this model will contribute to clearer understanding of the fundamental principles of rubber friction.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.88-88
• /
• 2019

컴퓨터 성능향상과 수치해석기법의 발달로 인해 Navier-Stokes 방정식에 기초한 수치모델을 활용한 3차원 유동/파동장 해석이 증가하고 있는 추세이다. 그러나 아직까지 Navier-Stokes 방정식 모델의 계산부하를 PC에서 소화하기에는 무리가 따른다. 게다가 실험실 스케일을 벗어나, 실제 현장을 계산영역으로 설정할 경우에는 계산량이 엄청나게 증가하게 된다. 이것을 극복하기 위해서는 반듯이 병렬계산을 수행하여야 한다. 본 연구에서는 계산부하가 큰 Navier-Stokes 방정식 기반의 3차원 수치모델 LES-WASS-3D를 활용한 대용량 병렬계산체계를 구축한다. 나아가 3차원 정밀 또는 광역의 유동/파동장 해석에 있어서 병렬계산체계의 성능과 적용성을 검토한다. 현재 보급되고 있는 PC들은 모두 멀티프로세서가 장착됨으로 손쉽게 병렬계산을 수행할 수 있다. 그러나 정밀 또는 광역해석을 위해서는 대용량 병렬계산 컴퓨터가 요구된다. 따라서 본 연구에서는 보조프로세서를 장착한 공유메모리 환경의 고성능 병렬계산체계를 구축한다. 나아가 포트란 기반의 순차코드로 구축된 기존 3차원 Navier-Stokes 방정식 모델 LES-WASS- 3D를 병렬코드로 변환한다. 병렬계산 성능 및 적용성을 검토하기 위한 수치해석을 수행한다. 이상의 과정을 통해 본 연구에서 구축한 병렬계산체계의 성능 및 적용성을 확인할 수 있었다. 그리고 3차원 유동/파동장 해석에 있어서 정확도 향상뿐 아니라, 계산영역을 확장할 수 있는 계기가 마련되었다. 또한 유동/파동 해석보다 많은 계산시간이 필요한 지형변동 해석에도 충분히 적용될 수 있다고 판단된다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.14 no.3
• /
• pp.208-214
• /
• 2021

Recently, much of the intelligent security scenario and criminal investigation demands for matching photo and non-photo. Existing face recognition system can not sufficiently guarantee these needs. In this paper, we propose an algorithm to improve the performance of heterogeneous face recognition systems by reducing the different modality between sketches and photos of the same person. The proposed algorithm extracts each image's texture features through texture descriptors (gray level co-occurrence matrix, multiscale local binary pattern), and based on this, generates a transformation matrix through eigenfeature regularization and extraction techniques. The score value calculated between the vectors generated in this way finally recognizes the identity of the sketch image through the score normalization methods.

• KIPS Transactions on Software and Data Engineering
• /
• v.8 no.6
• /
• pp.251-256
• /
• 2019

A capsule endoscopy is a medical device that can capture an entire digestive organ from the esophagus to the anus at one time. It produces a vast amount of images consisted of about 8~12 hours in length and more than 50,000 frames on a single examination. However, since the analysis of endoscopic images is performed manually by a medical imaging specialist, the automation requirements of the analysis are increasing to assist diagnosis of the disease in the image. Among them, this study focused on automatic detection of polyp images. A polyp is a protruding lesion that can be found in the gastrointestinal tract. In this paper, we propose a weighted-image generation method to enhance the polyp image learning by multi-scale analysis. It is a way to extract the suspicious region of the polyp through the multi-scale analysis and combine it with the original image to generate a weighted image, that can enhance the polyp image learning. We experimented with SVM and RF which is one of the machine learning methods for 452 pieces of collected data. The F1-score of detecting the polyp with only original images was 89.3%, but when combined with the weighted images generated by the proposed method, the F1-score was improved to about 93.1%.

• Journal of the Korea Convergence Society
• /
• v.12 no.11
• /
• pp.45-51
• /
• 2021

With the development of deep learning, semantic segmentation methods are being studied in various fields. There is a problem that segmenation accuracy drops in fields that require accuracy such as medical image analysis. In this paper, we improved PSPNet, which is a deep learning based segmentation method to minimized the loss of features during semantic segmentation. Conventional deep learning based segmentation methods result in lower resolution and loss of object features during feature extraction and compression. Due to these losses, the edge and the internal information of the object are lost, and there is a problem that the accuracy at the time of object segmentation is lowered. To solve these problems, we improved PSPNet, which is a semantic segmentation model. The multi-scale attention proposed to the conventional PSPNet was added to prevent feature loss of objects. The feature purification process was performed by applying the attention method to the conventional PPM module. By suppressing unnecessary feature information, eadg and texture information was improved. The proposed method trained on the Cityscapes dataset and use the segmentation index MIoU for quantitative evaluation. As a result of the experiment, the segmentation accuracy was improved by about 1.5% compared to the conventional PSPNet.

• Journal of the Institute of Convergence Signal Processing
• /
• v.6 no.2
• /
• pp.53-58
• /
• 2005

Points of sharp variations in images are the most important components when we analyze singularities of images. And they include a variety of information about the image's location and shape etc. So a lot of researches for detecting those edges have been continuing even now and at the early stage of the research, edge detection operators used relation among neighborhood pixels. However, such methods do not have excellent performance in the image which exists noise and can not detect edge selectively. In the meantime, the wavelet transform which is presented as a new technique of signal processing field is able to detect multiscale edge and is being applied widely in many fields that analyze singularities such as edge. For this reason, in this paper we detected image's line-edge elements with 2-D wavelet function, which is independent of line's width, in mixed noise environment.