• Journal of the Korean Society for Precision Engineering
• /
• v.13 no.11
• /
• pp.143-151
• /
• 1996

Structural reaction injection molding을 이용한 복합재료의 제품 셩형을 위한 모델링 전략을 설명하였다. 사용된 모델은 두 평행한 원판형 mold에 있는 불 균일한 온도조건의 fiber preform을 통과하는 reactive srsin의 방사형 유동을 시뮬레이션 한다. 이러한 모델은 중요한 작동인자와 공정인자(주입온도, mold의 온도, 유량, cavity의 두께와 섬유의 조밀도)등이 유동속도, 변화(monomer, radical, inhibitor) 및 온도분포 등에 미치는 영향을 예견한다. 열전달과 질량전달 및 화학반응을 고려하여 모델을 개발하였다. 중요한 공정인자를 평가하기 위한 효울적인 공정창( process window)을 제공하는데 본 연구의 목적을 두었다. 2차원적인 Lagrangian 방식에 1차원적인 유동과 제한적인 2차원 열전달을 가정하여 모델을 유도하였고, 방정식은 implicit difference scheme에 의해 전개하였다. 이 모델은 Gonzalez-Romero의 실험 결과와 비교함에 의해 확인되었고, 실험결과가 잘 일치함을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.2
• /
• pp.855-870
• /
• 2020

Windows are key components of building facades. Detecting windows, crucial to 3D semantic reconstruction and scene parsing, is a challenging task in computer vision. Early methods try to solve window detection by using hand-crafted features and traditional classifiers. However, these methods are unable to handle the diversity of window instances in real scenes and suffer from heavy computational costs. Recently, convolutional neural networks based object detection algorithms attract much attention due to their good performances. Unfortunately, directly training them for challenging window detection cannot achieve satisfying results. In this paper, we propose an approach for window detection. It involves an improved Faster R-CNN architecture for window detection, featuring in a window region proposal network, an RoI feature fusion and a context enhancement module. Besides, a post optimization process is designed by the regular distribution of windows to refine detection results obtained by the improved deep architecture. Furthermore, we present a newly collected dataset which is the largest one for window detection in real street scenes to date. Experimental results on both existing datasets and the new dataset show that the proposed method has outstanding performance.

• Journal of the Korean Society for Precision Engineering
• /
• v.22 no.7 s.172
• /
• pp.177-184
• /
• 2005

Recently, the engineering designer of injection mould has become more and more dependent on the CAE. In the design factors of injection mould, the shrinkage rate should be considered as one of the important performances to produce the reliable products. therefore the shrinkage rate can be mostly calculated by the MoldFlow and Pro-engineering. in the design process. However it is not easy to predict the shrinkage rate of a plastic injection mold in its design process because the analysis can take minutes to hours, the high computational costs of performing the analysis limit their use in design optimization. In this study, the surrogate models, DACE model, based on the Kriging in order to optimize the shrinkage rate of electric microwave oven window is used in lieu of the original models, facilitating design optimization.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.32B no.11
• /
• pp.1424-1433
• /
• 1995

The edge detection process serves to simplify the analysis of images by drastically reducing the amount of data to be processed, while preserving useful structural informations about object boundaries. At first, this paper proposes an edge detection algorithm to reduce the amount of computation. The gradients of pixels are calculated by using first order differential equations on the pixels with even rows and even columns or odd rows and odd columns, and they are compared with a threshold to decide edges. As a result, the computational complexity is reduced to one third or one forth compared with the provious ones. To enhance the accuracy of edge detection, a method with the adaptive threshold for each pixel window which is calculated by using characteristic values is proposed. In this case, the performance can be improved since the threshold is calculated properly for each window according to the local characteristics of corresponding window.

• Korean Journal of Remote Sensing
• /
• v.22 no.6
• /
• pp.601-612
• /
• 2006

This study proposes RAG (Region Adjancency Graph)-based image segmentation for large imagery in remote sensing. The proposed algorithm uses CN-chain linking for computational efficiency and multi-window operation of sliding structure for memory efficiency. Region-merging due to RAG is a process to find an edge of the best merge and update the graph according to the merge. The CN-chain linking constructs a chain of the closest neighbors and finds the edge for merging two adjacent regions. It makes the computation time increase as much as an exact multiple in the increasement of image size. An RNV (Regional Neighbor Vector) is used to update the RAG according to the change in image configuration due to merging at each step. The analysis of large images requires an enormous amount of computational memory. The proposed sliding multi-window operation with horizontal structure considerably the memory capacity required for the analysis and then make it possible to apply the RAG-based segmentation for very large images. In this study, the proposed algorithm has been extensively evaluated using simulated images and the results have shown its potentiality for the application of remotely-sensed imagery.

• Korean Journal of Computational Design and Engineering
• /
• v.2 no.3
• /
• pp.161-174
• /
• 1997

In this paper, the techniques for graphic simulation of material removal process are described. The concepts of the bounding box and base plane are proposed. With these concepts, a real-time shaded display of a Z-map model being milled by a cutting tool following an NC path can be implemented very efficiently. The base planes make it possible to detect the visible face of Z-map model effectively. And the bounding box of tool sweep volume provides minimum area of screen to be updated. The proposed techniques are suitable for implementation in raster graphic device and need a few memories and a small amount of calculation. Proposed method is written in C and executable on MS-Windows95 and Window-NT.

• Journal of the Korea Computer Industry Society
• /
• v.7 no.5
• /
• pp.513-520
• /
• 2006

In this paper, we propose a novel real-time frame-layer rate control algorithm using sliding window method for low bit rate video coding. The proposed rate control method performs bit allocation at the frame level to minimize the average distortion over an entire sequence as well as variations in distortion between frames. A new frame-layer rate-distortion model is derived, and a non-iterative optimization method is used for low computational complexity. In order to reduce the quality fluctuation, we use a sliding window scheme which does not require the pre-analysis process. Therefore, the proposed algorithm does not produce time delay from encoding, and is suitable for real-time low-complexity video encoder. Experimental results indicate that the proposed control method provides better visual and PSNR performance than the existing TMN8 rate control method.

• Proceedings of the KSME Conference
• /
• 2004.11a
• /
• pp.864-869
• /
• 2004

It is net easy to predict the shrinkage rate of a plastic injection mold in its design process. The shrinkage rate should be considered as one of the important performances to produce the reliable products. The shrinkage rate can be determined by suing the CAE tools in the design produces. However, since the analysis can take minutes to hours, the high computational costs of performing the analysis limit their use in design optimization. In this study, the surrogate models based on the DACE is used in lien of the original models, facilitating design optimization.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.3
• /
• pp.1464-1480
• /
• 2019

Robust tracking of infrared (IR) pedestrian targets with various backgrounds, e.g. appearance changes, illumination variations, and background disturbances, is a great challenge in the infrared image processing field. In the paper, we address a new tracking method for IR pedestrian targets via multi-feature local sparse representation (SR), which consists of three important modules. In the first module, a multi-feature local SR model is constructed. Considering the characterization of infrared pedestrian targets, the gray and edge features are first extracted from all target templates, and then fused into the model learning process. In the second module, an effective tracker is proposed via the learned model. To improve the computational efficiency, a sliding window mechanism with multiple scales is first used to scan the current frame to sample the target candidates. Then, the candidates are recognized via sparse reconstruction residual analysis. In the third module, an adaptive dictionary update approach is designed to further improve the tracking performance. The results demonstrate that our method outperforms several classical methods for infrared pedestrian tracking.

• Journal of Educational Research in Mathematics
• /
• v.8 no.2
• /
• pp.651-662
• /
• 1998

Mathematics is means for making sense of one's experiential world and products of human activities. A usefulness of mathematics is derived from this features of mathematics. Keeping the meaning of situations during the mathematizing of situations. However, theories about the development of mathematical concepts have turned mainly to an understanding of invariants. The purpose of this study is to show the possibility of computer in representing situation and phenomena. First, we consider situated cognition theory for looking for the relation between various representation and situation in problem. The mathematical concepts or model involves situations, invariants, representations. Thus, we should involve the meaning of situations and translations among various representations in the process of mathematization. Second, we show how the process of computational mathematization can serve as window on relating situations and representations, among various representations. When using computer software such as ALGEBRA ANIMATION in mathematics classrooms, we identified two benifits First, computer software can reduce the cognitive burden for understanding the translation among various mathematical representations. Further, computer softwares is able to connect mathematical representations and concepts to directly situations or phenomena. We propose the case study for the effect of computer software on practical mathematics classrooms.