• Journal of Ubiquitous Convergence Technology
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• v.2 no.1
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• pp.18-26
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• 2008

The invariance relation existing in the non-negative matrix factorization (NMF) is used for constructing robust image hashes in this work. The image is first re-scaled to a fixed size. Low-pass filtering is performed on the luminance component of the re-sized image to produce a normalized matrix. Entries in the normalized matrix are pseudo-randomly re-arranged under the control of a secret key to generate a secondary image. Non-negative matrix factorization is then performed on the secondary image. As the relation between most pairs of adjacent entries in the NMF's coefficient matrix is basically invariant to ordinary image processing, a coarse quantization scheme is devised to compress the extracted features contained in the coefficient matrix. The obtained binary elements are used to form the image hash after being scrambled based on another key. Similarity between hashes is measured by the Hamming distance. Experimental results show that the proposed scheme is robust against perceptually acceptable modifications to the image such as Gaussian filtering, moderate noise contamination, JPEG compression, re-scaling, and watermark embedding. Hashes of different images have very low collision probability. Tampering to local image areas can be detected by comparing the Hamming distance with a predetermined threshold, indicating the usefulness of the technique in digital forensics.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.387-397
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• 2003

Generally, most of researches that need a variable-clustering process use an exploratory factor analysis technique or a divisive hierarchical variable-clustering method based on a correlation matrix. And some researchers apply a object-clustering method to a distance matrix transformed from a correlation matrix, though this approach is known to be improper. On this paper an agglomerative hierarchical variable-clustering method based on a correlation matrix itself is suggested. It is derived from a geometric concept by using variate-spaces and a characterizing variate.

• Structural Engineering and Mechanics
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• v.67 no.5
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• pp.457-464
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• 2018

This paper presents a method for detecting damage in irregular 2D and 3D continuum structures based on combination of wavelet transform (WT) with fuzzy inference system (FIS) and particle swarm optimization (PSO). Many damage detection methods study regular structures. This method studies irregular structures and doesn't need response of healthy structures. First the damaged structure is analyzed with finite element methods, and damage response is obtained at the finite element points that have irregular distance, secondly the FIS, which is optimized by PSO is used to obtain responses at points, having equal distance by response at those points that previously obtained by the finite element methods. Then a 2D (for 2D continuum structures) or a 3D (for 3D continuum structures) matrix is performed by equal distance point response. Thirdly, by applying 2D or 3D wavelet transform on 2D or 3D matrix that previously obtained by FIS detail matrix coefficient of WT is obtained. It is shown that detail matrix coefficient can determine the damage zone of the structure by perturbation in the damaged area. In order to illustrate the capability of proposed method some examples are considered.

• Nonlinear Functional Analysis and Applications
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• v.27 no.4
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• pp.709-730
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• 2022

We consider the nonlinear matrix equation (NMEs) of the form 𝓤 = 𝓠 + Σ^k_i=1 𝓐^*_iℏ(𝓤)𝓐_i, where 𝓠 is n × n Hermitian positive definite matrices (HPDS), 𝓐₁, 𝓐₂, . . . , 𝓐_m are n × n matrices, and ~ is a nonlinear self-mappings of the set of all Hermitian matrices which are continuous in the trace norm. We discuss a sufficient condition ensuring the existence of a unique positive definite solution of a given NME and demonstrate this sufficient condition for a NME 𝓤 = 𝓠 + 𝓐^*₁(𝓤²/900)𝓐₁ + 𝓐^*₂(𝓤²/900)𝓐₂ + 𝓐^*₃(𝓤²/900)𝓐₃. In order to do this, we define 𝓕𝓖_w-contractive conditions and derive fixed points results based on aforesaid contractive condition for a mapping in extended Branciari b-metric distance followed by two suitable examples. In addition, we introduce weak well-posed property, weak limit shadowing property and generalized Ulam-Hyers stability in the underlying space and related results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10C
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• pp.1363-1369
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• 2004

LDPC(Low Density Parity Check) codes are described by bipartite graphs with bit nodes and parity-check nodes. Tanner derived minimum distance bounds of the regular LDPC code in terms of the eigenvalues of the associated adjacency matrix. In this paper we generalize the Tanner's results. We derive minimum distance bounds applicable to both regular and blockwise-irregular LDPC codes. The first bound considers the relation between bit nodes in a minimum-weight codeword, and the second one considers the connectivity between parity nodes adjacent to a minimum-weight codeword. The derived bounds make it possible to describe the distance property of the code in terms of the eigenvalues of the associated matrix.

• Journal of the military operations research society of Korea
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• v.26 no.1
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• pp.89-99
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• 2000

This paper deals with a heuristic algorithm for the vehicle routing-scheduling problem to minimize the total travel distance and the total cost. Because the aim of the Clarke-Wright method, one of famous heuristic methods, is to minimize the total travel distance of vehicles, it cannot consider the cost if the cost and the travel distance is not proportional. In the Clarke-Wright method, the route of each vehicle is found by using the saving matrix which is made by an assumption that the vehicle comes back to the starting point. The problem dealt with in the paper, however, does not need the vehicle to come back because each vehicle has its hoping-start-points and hoping-destination-points. Therefore we need a different saving matrix appropriate to this occasion. We propose a method to find an initial solution by applying network simplex method after transforming the vehicle routing-scheduling problem into the minimum cost problem. Moreover, we propose a method to minimize the total travel distance by using the modified saving matrix which is appropriate to no-return occasion and the method for the case of plural types of vehicles and freights.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.2
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• pp.227-230
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• 2009

In this paper, we performed the optimum design of reactors for matrix-type superconducting-fault current limiters (SFCLs), using electromagnetic analysis tools. We decided a optimun position within a reactor for superconducting elements of current-limiting parts and trigger parts from the calculation of magnetic flux internsity for reactor structures. Also we decided effective distance length between two reactors through the analysis of the distribution of magnetic field, according to distance lengths between them. We designed and characterized matrix-type SFCLs, based on our optimum design of a reactor. We confirmed uniform distribution of a fault current, resulted from the improvement of simultaneous quench characteristics within our matrix-type SFCL.

• Bulletin of the Korean Mathematical Society
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• v.56 no.5
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• pp.1273-1283
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• 2019

In matrix analysis, the Wielandt-Mirsky conjecture states that $$dist({\sigma}(A),{\sigma}(B)){\leq}{\parallel}A-B{\parallel}$$ for any normal matrices $A,B{\in}{\mathbb{C}}^{n{\times}n}$ and any operator norm ${\parallel}{\cdot}{\parallel}$ on $C^{n{\times}n}$. Here dist(${\sigma}(A),{\sigma}(B)$) denotes the optimal matching distance between the spectra of the matrices A and B. It was proved by A. J. Holbrook (1992) that this conjecture is false in general. However it is true for the Frobenius distance and the Frobenius norm (the Hoffman-Wielandt inequality). The main aim of this paper is to study the Hoffman-Wielandt inequality and some weaker versions of the Wielandt-Mirsky conjecture for matrix polynomials.

• The Journal of the Acoustical Society of Korea
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• v.30 no.2
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• pp.80-85
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• 2011

Speaker change detection involves the identification of time indices of an audio stream, where the identity of the speaker changes. In this paper, we propose novel measures for the speaker change detection based on a graph-partitioning criterion over the pairwise distance matrix of feature-vector stream. Experiments on both synthetic and real-world data were performed and showed that the proposed approach yield promising results compared with the conventional statistical measures.

• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.2061-2074
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• 1998

In pattern recognition and image analysis upplications, a graph is a useful tool for complex obect representation and recognition. However it takes much time to pair proper nodes between the prototype graph and an input data graph. Futhermore it is difficult to decide whether the two graphs in a class are the same hecause real images are degradd in general by noise and other distortions. In this paper we propose a matching algorithm using a matrix. The matrix is suiable for simple and easily understood representation and enables the ordering and matching process to be convenient due to its predefined matrix manipulation. The nodes which constitute a gaph are ordered in the matrix by their geometrical positions and this makes it possible to save much comparison time for finding proper node pairs. for the classification, we defined a distance measure thatreflects the symbo's structural aspect that is the sum of the mode distance and the relation distance; the fornet is from the parameters describing the node shapes, the latter from the relations with othes node in the matrix. We also introduced a subdivision operation to compensate node merging which is mainly due t the prepreocessing error. The proposed method is applied to the recognition of musteal symbols and the result is given. The result shows that almost all, except heavily degraded symbols are recognized, and the recognition rate is approximately 95 percent.