• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.4
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• pp.108-113
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• 2013

Industrialization and modernization of the beginning of the IT industry is growing very fast. Since telecommunications industry was developed rapidly, technologies about miniaturization and high-precision of parts have been actively developed to lead information revolution. generally, the entire shear surface of the product applying fine blanking technology must be very precise. Fine blanking is used to save cost by avoiding post-processing of the product. When using press blanking, it spends a lot of money on the production by using many post-processing. Fine blanking typically used in 0.5~18 mm thick steel plate. Because a lot of post-processing cost can be used to process, except for fine blanking. In order to develop components "CHANCE CONTENTS" in the fine blanking process, the purpose of this study is to minimize the edge of the bridge, secured 95% of the material thickness of the shear surface using the 1.6 mm thickness of the material SPCC. Blanking process by introducing after changing thickness through forging process, due to change in vee-rring force and counter force, the experimental amount of depressions and flatness and the shear surface were analyzed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.25-32
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• 2004

We propose a hierarchical disparity estimation algorithm with edge-preserving energy-based regularization. Initial disparity vectors are obtained from downsampled stereo images using a feature-based region-dividing disparity estimation technique. Dense disparities are estimated from these initial vectors with shape-adaptive windows in full resolution images. Finally, the vector fields are regularized with the minimization of the energy functional which considers both fidelity and smoothness of the fields. The first two steps provide highly reliable disparity vectors, so that local minimum problem can be avoided in regularization step. The proposed algorithm generates accurate disparity map which is smooth inside objects while preserving its discontinuities in boundaries. Experimental results are presented to illustrate the capabilities of the proposed disparity estimation technique.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.5C
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• pp.422-434
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• 2002

We propose 3-layered hierarchical fiber-optic backbone transmission network composed of B-DCS, Backbone ring, Edge ring for efficient transmission of high capacity traffic and consider design method to ensure network survivability of each layer at affordable cost. Mathematical ring-construction cost minimization using MIP(Mixed Integer Programming) models results in NP-complete problem. So, it is hard to solve it within reasonable computing time. on a large-scale network. Therefore we develop heuristic algorithms solving WSCAP(Working and Spared Channel Assignment Problem) for B-DCS, MRLB(Multi-Ring Load Balancing) problem for Backbone ring, and ORLB(Overlayed Ring Load Balancing) problem for Edge ring and show their usefulness through case study.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2558-2562
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• 1999

This paper proposes on the methods of noise removal and edge extraction which is done by eliminating the ambiguities of the image using normalization and minimizing the entropy. Pre-existing methods have their own peculiarities and limitations, such as gray level distributions change very slowly or two regions which having similar gray level distribution are touched. This affects on the post processing such as feature extraction, as a result, this leads to false-recognition or no-recognition. Therefore, this paper proposes on the methods which overcome these problems. Finally, the effectiveness of this paper is demonstrated by several experiments.

• Transactions of Materials Processing
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• v.15 no.6 s.87
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• pp.445-452
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• 2006

In most of automobile body panel manufacturing, trimming process is generally performed before flanging. To find feasible trimming line is crucial in obtaining accurate edge profile after flanging. Section-based method develops blank along manually chosen section planes and find trimming line by generating loop of end points. This method suffers from inaccurate results of edge profile. On the other hand, simulation-based method can produce more accurate trimming line by iterative strategy. In this study, new fast simulation-based method to find feasible trimming line is proposed. Finite element inverse method is used to analyze the flanging process because final shape after flanging can be explicitly defined and most of strain paths are simple in flanging. In utilizing finite element inverse method, the main obstacle is the initial guess generation for general mesh. Robust initial guess generation method is developed to handle genera] mesh with very different size and undercut. The new method develops final triangular mesh incrementally onto the drawing tool surface. Also in order to remedy mesh distortion during development, energy minimization technique is utilized. Trimming line is extracted from the outer boundary after finite element inverse method simulation. This method has many advantages since trimming line can be obtained in the early design stage. The developed method is verified by shrink/stretch flange forming and successfully applied to the complex industrial applications such as door outer flanging process.

• Journal of Biomedical Engineering Research
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• v.31 no.6
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• pp.464-471
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• 2010

Compressed sensing can be used to reduce scan time or to enhance spatial resolution in MRI. It is now recognized that compressed sensing works well in reconstructing magnitude images if the sampling mask and the sparsifying transform are well chosen. Phase images also play important roles in MRI particularly in chemical shift imaging and magnetic resonance electrical impedance tomography (MREIT). We reconstruct MRI phase images using the compressed sensing technique. Through computer simulation and real MRI experiments, we reconstructed phase images using the compressed sensing technique and we compared them with the ones reconstructed by conventional Fourier reconstruction technique. As compared to conventional Fourier reconstruction with the same number of phase encoding steps, compressed sensing shows better performance in terms of mean squared phase error and edge preservation. We expect compressed sensing can be used to reduce the scan time or to enhance spatial resolution of MREIT.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.5
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• pp.203-211
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• 2002

In this paper, the implementation of a new AF(Automatic Focusing) system for a digital still camera is introduced. The proposed system operates in real-time while adjusting focus after the measurement of distance to an object using a passive sensor, which is different from a typical method. In audition, measurement errors were minimized by using the data acquired empirically, and the optimal measuring time was obtained using EV(Exposure Value) which is calculated from CCD luminance signal. Moreover, this system adopted an auxiliary light source for focusing in absolute dark conditions, which is very hard for CCD image Processing. Since this is an open-loop system adjusting focus immediately after the distance measurement, it guarantees real-time operation. The performance of this new AF system was verified by comparing the focusing value curve obtained from AF experiment with the one from the measurement by MF(Manual-Focusing). In both case, edge detector was used for various objects and backgrounds.

• IE interfaces
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• v.18 no.3
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• pp.247-252
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• 2005

In the automated production environment in the present days, the minimization of manual operation becomes a very important factor in increasing the efficiency of the production system. The exit burr produced through the milling operation on the edge of workpiece usually requires manual deburring process to enhance the level of precision of the resulting product. So far, researchers have developed various methods to understand the formation of exit burr in cutting process. One method to analytically identify the formation of exit burr was to use the geometrical information of CAD and CAM data used in automated machining. This method, in turn, generated the information resulting from the analysis such as burr type, cutting region, and exit angle. Up to now, the geometrical data were restricted to the single feature and single path. In this paper, a method to deal with the complicated geometric features such as line segment, arc, hole, and spline will be presented and validated using the field data. This method also deals with the complex workpiece shape which is a combination of multiple features. As for the cutting path, multiple tool path is analyzed in order to simulate the real cutting process. All this analysis is combined into a Windows based software and real data are used to validate the program in the conclusion.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.521-526
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• 2003

In this paper, we propose a geometric active contour model based on intensity information and curve evolution for detecting region boundaries. We put boundary extraction problem as the minimization of the difference between the average intensity of the region and the intensity of the expanding closed curves. We used level set theory to implement the curve evolution for optimal solution. It offered much more freedom in the initial curve position than a general active contour model. Our methods could detect regions whose boundaries are not necessarily defiened by gradient compared to general edge based methods and detect multiple boundaries at the same time. We could improve the result by using anisotropic diffusion filter in image preprocessing. The performance of our model was demonstrated on several data sets like CT and MRI medical images.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.721-736
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• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.