• Journal of applied mathematics & informatics
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• v.28 no.3_4
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• pp.569-582
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• 2010

The following "Periodic Jacobi Procrustes" problem is studied: find the Periodic Jacobi matrix X which minimizes the Frobenius (or Euclidean) norm of AX - B, with A and B as given rectangular matrices. The class of Procrustes problems has many application in the biological, physical and social sciences just as in the investigation of elastic structures. The different problems are obtained varying the structure of the matrices belonging to the feasible set. Higham has solved the orthogonal, the symmetric and the positive definite cases. Andersson and Elfving have studied the symmetric positive semidefinite case and the (symmetric) elementwise nonnegative case. In this contribution, we extend and develop these research, however, in a relatively simple way. Numerical difficulties are discussed and illustrated by examples.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.11 no.9
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• pp.431-438
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• 2001

This paper present experimental results of source identification for non-minimum phase system. Generally, a causal linear system may be described by matrix form. The inverse problem is considered as a matrix inversion. Direct inverse method can\`t be applied for a non-minimum phase system, the reason is that the system has ill-conditioning. Therefore, in this study to execute an effective inversion, SVD inverse technique is introduced. In a Non-minimum phase system, its system matrix may be singular or near-singular and has one more very small singular values. These very small singular values have information about a phase of the system and ill-conditioning. Using this property we could solve the ill-conditioned problem of the system and then verified it for the practical system(cantilever beam). The experimental results show that SVD inverse technique works well for non-minimum phase system.

• Structural Engineering and Mechanics
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• v.21 no.3
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• pp.237-254
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• 2005

This article deals with the reconstruction of an impact force. This requires to take measurements from the impacted structures and then to deconvolve those signals from the impulse response function. More precisely, the purpose of the work described here is to analyse the method of deconvolution and the problems that it implies. Thus, it is highlighted that the associated deconvolution problem depends on the location of the measurement points: it is possible or not to reconstruct the force of impact in function of the location of this point. Then, the role of the antiresonances is linked up with this problem. The singular value decomposition is used to understand these difficulties. Numerical predictions are compared and validated with experiments.

• Journal of the Chungcheong Mathematical Society
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• v.31 no.4
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• pp.487-509
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• 2018

The Truncated Moment Problem (TMP) entails finding a positive Borel measure to represent all moments in a finite sequence as an integral; once the sequence admits one or more such measures, it is known that at least one of the measures must be finitely atomic with positive densities (equivalently, a linear combination of Dirac point masses with positive coefficients). On the contrary, there are more general moment problems for which we aim to find a "signed" measure to represent a sequence; that is, the measure may have some negative densities. This type of problem is referred to as the General Truncated Moment Problem (GTMP). The Jordan Decomposition Theorem states that any (signed) measure can be written as a difference of two positive measures, and hence, in the view of this theorem, we are able to apply results for TMP to study GTMP. In this note we observe differences between TMP and GTMP; for example, we cannot have an analogous to the Flat Extension Theorem for GTMP. We then present concrete solutions to lower-degree problems.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.697-699
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• 2004

Despite many successful spectral clustering algorithm (based on the spectral decomposition of Laplacian(1) or stochastic matrix(2) ) there are several unsolved problems. Most spectral clustering Problems are based on the normalized of algorithm(3) . are close to the classical graph paritioning problem which is NP-hard problem. To get good solution in polynomial time. it needs to establish its convex form by using relaxation. In this paper, we apply a novel optimization technique. semidefinite programming(SDP). to the unsupervised clustering Problem. and present a new multiple Partitioning method. Experimental results confirm that the Proposed method improves the clustering performance. especially in the Problem of being mixed with non-compact clusters compared to the previous multiple spectral clustering methods.

• Journal of KIISE:Software and Applications
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• v.27 no.6
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• pp.583-594
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• 2000

The thinning process which is commonly used in extracting skeletons from handwritten Hangul characters has a problem of distorting the original pattern shapes. This paper proposes a method of skeleton extraction using a shape decomposition algorithm. We decompose the character pattern into a set of near convex parts using a shape decomposition algorithm. From the shape-decomposed pattern, we detect the joint parts and extract the skeletons from the parts incident to the joint parts. Then the skeletons not incident to the joint parts are extracted. Finally, the process of skeleton extension is performed to ensure the connectivity. We setup five criteria for the comparison of quality of skeletons extracted by our method and the thinning based method. The comparison shows the superiority of our method in terms of several criteria.

• Korean Journal of Computational Design and Engineering
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• v.18 no.1
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• pp.71-82
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• 2013

To modify product design easily, modern CAD systems adopt the feature-based model as their primary representation. On the other hand, the boundary representation (B-rep) model is used as their secondary representation. IGES and STEP AP203 edition 1 are the representative standard formats for the exchange of CAD files. Unfortunately, both of them only support the B-rep model. As a result, feature data are lost during the CAD file exchange based on these standards. Loss of feature data causes the difficulty of CAD model modification and prevents the transfer of design intent. To resolve this problem, a tool for recognizing design features from a B-rep model and then reconstructing a feature-based model with the recognized features should be developed. As the first part of this research, this paper presents a method for decomposing a B-rep model into simple volumes suitable for design feature recognition. The results of experiments with a prototype system are analyzed. From the analysis, future research issues are suggested.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.6
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• pp.345-351
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• 2014

This paper presents pedestrian recognition to improve performance for vehicle safety system or surveillance system. Pedestrian detection method using HOG (Histograms of Oriented Gradients) has showed 90% recognition rate. But if someone takes a picture in the rain, the image may be distorted by rain streaks and recognition rate goes down by 62%. To solve this problem, we applied image decomposition method using MCA (Morphological Component Analysis). In this case, rain removal method improves recognition rate from 62% to 70%. However, it is difficult to apply conventional image decomposition method using MCA on vehicle safety system or surveillance system as conventional method is too slow for real-time system. To alleviate this issue, we propose a rain removal method by using low-pass filter and DCT (Discrete Cosine Transform). The DCT helps separate the image into rain components. The image is removed rain components by Butterworth filtering. Experimental results show that our method achieved 90% of recognition rate. In addition, the proposed method had accelerated processing time to 17.8ms which is acceptable for real-time system.

• Transactions of the Korean hydrogen and new energy society
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• v.28 no.1
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• pp.70-76
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• 2017

To synthesize copper nanoparticle a thermal decomposition was adopted. And to solve the problem of surface oxidation of the synthesized copper powder an electroless Ag plating method was used. The size and shape of synthesized Cu nanoparticle were affected by the size of copper oxalate used as a precursor, reaction solvent, reaction temperature and amount of reducing agent. Especially reaction solvent is dominant factor to control shape of Cu nano-particle which can have the shapes of sphere, polygon and rod. In case of glycerol, it produced spherical shape of about 500 nm in size. Poly ethylene produced uniform polygonal shape in about 700 nm and ethylene glycol produced both of polygon and rod having size range between 500 and 1500 nm. The silver coated copper powder showed a high electrical conductivity.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.9
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• pp.1822-1830
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• 2002

The paper describes the development of a decomposition based multidisciplinary design optimization (MDO) method that coordinates each of disciplinary subspace optimization (DSO). A multidisciplinary design system considered in the present study is decomposed into a number of subspaces based on their own design objective and constraints associated with engineering discipline. The coupled relations among subspaces are identified by interdisciplinary design variables. Each of subsystem level optimization, that is DSO would be performed in parallel, and the system level coordination is determined by the first order optimal sensitivities of subspace objective functions with respect to interdisciplinary design variables. The central of the present work resides on the formulation of system level coordination strategy and its capability in decomposition based MDO. A fluid-structure coupled design problem is explored as a test-bed to support the proposed MDO method.