• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.729-732
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• 2014

본 논문에서는 부분 노이즈 제거를 지원하는 윤곽선 이미지 매칭의 성능 최적화 문제를 다룬다. 윤곽선 이미지 매칭에서 이미지의 노이즈를 제거하는 것은 직관적이고 정확한 매칭을 위해 매우 중요한 요소이다. 그러나, 윤곽선 이미지 매칭에서 부분 노이즈 제거를 지원하기 위해서는 매우 많은 계산이 빈번하게 발생한다. 본 논문에서는 기존 부분 노이즈 제거 윤곽선 이미지 매칭 연구를 좀 더 구체화하여 성능 향상을 위해 유사 거리의 하한을 제안한다. 실험 결과, 부분 노이즈 제거 윤곽선 이미지 매칭 성능을 수 배에서 수십 배까지 향상시킨 것으로 나타났다.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.117-120
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• 2004

본 논문에서는 시계열 데이터베이스에서 타임 워핑 하의 서브시퀀스 매칭을 효과적으로 처리하는 방안에 관하여 논의한다. 타임 워핑은 데이터베이스내 시퀀스들의 길이가 서로 다른 경우에도 유사한 패턴을 갖는 시퀀스들을 찾을 수 있도록 해 준다. 본 논문에서는 타임 워핑 하의 서브시퀀스 매칭을 위한 기존의 기본 처리 방식인 Naive-Scan의 CPU 처리 과정을 최적화하는 새로운 기법을 제안한다. 제안된 기법은 질의 시퀀스와 서브시퀀스들 간의 타임 워핑 거리들을 계산하는 과정에서 발생하는 중복 작업들을 사전에 제거함으로써 CPU 처리 성능을 극대화한다. 제안된 기법이 착오 기각을 발생시키지 않음과 Naive-Scan을 처리하기 위한 최적의 기법임을 이론적으로 규명한다. 또한, 다양한 실험을 통한 성능 평가에 의하여 제안된 최적화 기법이 가져오는 성능 개선 효과를 정량적으로 검증한다. 아울러, 제안된 기법이 기존의 여과 단계를 포함하는 방식인 LB-Scan과 ST-Filter의 후처리 단계에도 성공적으로 적용될 수 있음을 보인다.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.8
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• pp.156-167
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• 1995

In this paper, we propose a 3-D range finding method for situation that stereo camera has small translational motion. Binocular stereo generally tends to produce stereo correspondence errors and needs huge amount of computation. The former drawback is because the additional constraints to regularize the correspondence problem are not always true for every scene. The latter drawback is because they use either correlation or optimization to find correct disparity. We present a method which overcomes these drawbacks by moving the stereo camera actively. The method utilized a motion parallax acquired by monocular motion stereo to restrict the search range of binocular disparity. Using only the uniqueness of disparity makes it possible to find reliable binocular disparity. Experimental results with real scene are presented to demonstrate the effectiveness of this method.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.389-398
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• 2007

Case-based reasoning (CBR) is one of the most popular prediction techniques for medical diagnosis because it is easy to apply, has no possibility of overfitting, and provides a good explanation for the output. However, it has a critical limitation - its prediction performance is generally lower than other artificial intelligence techniques like artificial neural networks (ANNs). In order to obtain accurate results from CBR, effective retrieval and matching of useful prior cases for the problem is essential, but it is still a controversial issue to design a good matching and retrieval mechanism for CBR systems. In this study, we propose a novel approach to enhance the prediction performance of CBR. Our suggestion is the simultaneous optimization of feature weights, instance selection, and the number of neighbors that combine using genetic algorithms (GAs). Our model improves the prediction performance in three ways - (1) measuring similarity between cases more accurately by considering relative importance of each feature, (2) eliminating redundant or erroneous reference cases, and (3) combining several similar cases represent significant patterns. To validate the usefulness of our model, this study applied it to a real-world case for evaluating cytological features derived directly from a digital scan of breast fine needle aspirate (FNA) slides. Experimental results showed that the prediction accuracy of conventional CBR may be improved significantly by using our model. We also found that our proposed model outperformed all the other optimized models for CBR using GA.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.9
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• pp.47-53
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• 2011

The signal transmission properties of the connector such as insertion loss and return loss are investigated using analysis procedure of S-parameter simulation, equivalent model extraction, and characteristic impedance calculation. S-parameter simulation is performed by connector's modeling and solving based on 3-dimensional finite element method. The connector's equivalent model of ${\pi}$ type is are proposed and extracted with an optimization process of circuit analysis simulator. The characteristic impedance of the connector is calculated with results of circuit analysis simulation and S-parameter data. According to the connector's characteristic impedance, it's revised design is carried out. In this work, the connector's effective contact area is increased and its body is applied as a high dielectric material in order to increase its capacitance and then obtain impedance matching. Therefore, return loss of the connector is improved by approximately 10 dB due to its design revision.

• Journal of Korea Game Society
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• v.18 no.1
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• pp.125-134
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• 2018

This paper presents a practical method to efficiently extract the rotational part of a $3{\times}3$ matrix that changes continuously in time. This is the key technique in the corotational FEM and the shape matching deformation popular in physics-based dynamic deformation. Recently, in contrast to the traditional polar decomposition methods independent of time, an iterative method was proposed that formulates the rotation extraction in a physics-based way and exploits an incremental representation of rotation. We develop an optimization method that reduces the number of iterations under the assumption that the maximum magnitude of the incremental rotation vector is limited within ${\pi}/2$. Realistic simulation of dynamic deformation employs a sufficiently small time step, and thus this assumption is not problematic in practice. We demonstrate the efficiency and practicality of our method in various experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.285-290
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• 2007

In this paper, we presents robust digital redesign (DR) method for observer-based linear time-invariant (LTI) system. The term of DR involves converting an analog controller into an equivalent digital one by considering two condition: state-matching and stability. The design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between interpolated linear operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed the uncertain parts of given observer-based system more precisely, When a sampling period is sufficiently small, the conversion of a analog structured uncertain system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs).

• The KIPS Transactions:PartD
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• v.14D no.5
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• pp.459-470
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• 2007

A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Query processing for such a data stream should also be continuous and rapid, which requires strict time and space constraints. In most DSMS(Data Stream Management System), the selection predicates of continuous queries are grouped or indexed to guarantee these constraints. This paper proposes a new scheme tailed an ASC(Attribute Selection Construct) that collectively evaluates selection predicates containing the same attribute in multiple continuous queries. An ASC contains valuable information, such as attribute usage status, partially pre calculated matching results and selectivity statistics for its multiple selection predicates. The processing order of those ASC's that are corresponding to the attributes of a base data stream can significantly influence the overall performance of multiple query evaluation. Consequently, a method of establishing an efficient evaluation order of multiple ASC's is also proposed. Finally, the performance of the proposed method is analyzed by a series of experiments to identify its various characteristics.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1243-1258
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• 2017

A new medical materials scheduling system and its modeling method for the complex rescue are presented. Different from other similar system, first both the BeiDou Satellite Communication System (BSCS) and the Special Fiber-optic Communication Network (SFCN) are used to collect the rescue requirements and the location information of disaster areas. Then all these messages will be displayed in a special medical software terminal. After that the bipartite graph models are utilized to compute the optimal scheduling of medical materials. Finally, all these results will be transmitted back by the BSCS and the SFCN again to implement a fast guidance of medical rescue. The sole drug scheduling issue, the multiple drugs scheduling issue, and the backup-scheme selection issue are all utilized: the Kuhn-Munkres algorithm is used to realize the optimal matching of sole drug scheduling issue, the spectral clustering-based method is employed to calculate the optimal distribution of multiple drugs scheduling issue, and the similarity metric of neighboring matrix is utilized to realize the estimation of backup-scheme selection issue of medical materials. Many simulation analysis experiments and applications have proved the correctness of proposed technique and system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.311-326
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• 2024

The rapid development of neural network technology promotes the neural network model driven by big data to overcome the texture effect of complex objects. Due to the limitations in complex scenes, it is necessary to establish custom template matching and apply it to the research of many fields of computational vision technology. The dependence on high-quality small label sample database data is not very strong, and the machine learning system of deep feature connection to complete the task of texture effect inference and speculation is relatively poor. The style transfer algorithm based on neural network collects and preserves the data of patterns, extracts and modernizes their features. Through the algorithm model, it is easier to present the texture color of patterns and display them digitally. In this paper, according to the texture effect reasoning of custom template matching, the 3D visualization of the target is transformed into a 3D model. The high similarity between the scene to be inferred and the user-defined template is calculated by the user-defined template of the multi-dimensional external feature label. The convolutional neural network is adopted to optimize the external area of the object to improve the sampling quality and computational performance of the sample pyramid structure. The results indicate that the proposed algorithm can accurately capture the significant target, achieve more ablation noise, and improve the visualization results. The proposed deep convolutional neural network optimization algorithm has good rapidity, data accuracy and robustness. The proposed algorithm can adapt to the calculation of more task scenes, display the redundant vision-related information of image conversion, enhance the powerful computing power, and further improve the computational efficiency and accuracy of convolutional networks, which has a high research significance for the study of image information conversion.