• KIPS Transactions on Software and Data Engineering
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• v.2 no.2
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• pp.119-122
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• 2013

Repetitive strings such as periods have been studied vigorously in so diverse fields as data compression, computer-assisted music analysis, bioinformatics, and etc. In bioinformatics, periods are highly related to repetitive patterns in DNA sequences so called tandem repeats. In some cases, quite similar but not the same patterns are repeated and thus we need approximate string matching algorithms to study tandem repeats in DNA sequences. In this paper, we propose a new definition of approximate periods of strings based on distance sum. Given two strings $p({\mid}p{\mid}=m)$ and $x({\mid}x{\mid}=n)$, we propose an algorithm that computes the minimum approximate period distance based on distance sum. Our algorithm runs in $O(mn^2)$ time for the weighted edit distance, and runs in O(mn) time for the edit distance, and runs in O(n) time for the Hamming distance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.177-183
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• 2022

There is no known polynomial time algorithm for QAP that is a NP-complete problem. This paper suggests O(n²) polynomial time algorithm for random type quadratic assignment problem (QAP). The proposed algorithm suggests incremental augmenting matching strategy that is to set the matching set M={(l_i,f_j)} from l_i with minimum sum of distance in location matrix L and f_j with maximum sum of quantity in facility matrix F, and incremental augmenting of matching set M from M to l_i with minimum sum of distance and to f_j with maximum sum of quantity. Finally, this algorithm performs swap strategy that is to reflect the complex correlations of distances in locations and quantities in facilities. For the experimental data, this algorithm, in spite of O(n²) polynomial time algorithm, can be improve the solution than genetic algorithm a kind of metaheuristic method.

• Journal of the Chungcheong Mathematical Society
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• v.33 no.1
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• pp.147-156
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• 2020

The functional equation related to a distance measure f(pr, qs) + f(ps, qr) = M(r, s)f(p, q) + M(p, q)f(r, s) can be generalized a sum form functional equation as follows $${\frac{1}{n}}{\sum\limits_{i=0}^{n-1}}f(P{\cdot}{\sigma}_i(Q))=M(Q)f(P)+M(P)f(Q)$$ where f, g is information measures, P and Q are the set of n-array discrete measure, and σ_i is a permutation for each i = 0, 1, ⋯, n-1. In this paper, we obtain the hyperstability of the above type functional equation.

• Journal of applied mathematics & informatics
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• v.42 no.5
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• pp.1121-1135
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• 2024

In this paper, we introduced a new distance-based index called the minimum degree Wiener index, which is the sum of distances between all unordered pairs of vertices with the minimum degree. Additionally, a matrix related to this index was introduced, and it was discovered that the sum of entries in each row was the same for some classes of graphs, contrary to many graph-related matrices. In particular, we determined the minimum degree Wiener index of the bipartite Kneser graph, bipartite Kneser type-k graphs, Johnson graph and the set inclusion graphs. The terminal Wiener index of a graph G is the sum of distances between all unordered pairs of pendant vertices of G. Also, we determined Wiener index, hyper Wiener index and corresponding polynomials of the bipartite Kneser type-k graphs for k = 2, 3.

• Journal of Environmental Impact Assessment
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• v.23 no.3
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• pp.169-176
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• 2014

The purpose of this study is to estimate the vibration reduction effect of the borehole which is controlled the vibration propagation in the ground. For this study, we measured the vibration velocity before and after the borehole installation. The results are as follows: The peak particle velocity(PPV) and peak vector sum(PVS) was reduced by the borehole. And also, the deviation of vibration velocity before and after the borehole installation showed large values in longitudinal and vertical component depending on the receive distance, and increased depending on the size of vibration energy. Finally, the vibration isolation efficiency was 25~35 percentage at 1.5m receive distance, and was 4~14 percentage at 3.0m receive distance. It was found that the vibration isolation efficiency was good in small vibration energy, but was not good at long receive distance.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.321-327
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• 2014

Feature selection is the technique to improve the classification performance by using a minimal set by removing features that are not related with each other and characterized by redundancy. This study proposed new feature selection using the distance between the center of gravity of the bounded sum of weighted fuzzy membership functions (BSWFMs) provided by the neural network with weighted fuzzy membership functions (NEWFM) in order to improve the classification performance. The distance-based feature selection selects the minimum features by removing the worst features with the shortest distance between the center of gravity of BSWFMs from the 24 initial features one by one, and then 22 minimum features are selected with the highest performance result. The proposed methodology shows that sensitivity, specificity, and accuracy are 97.7%, 99.7%, and 98.7% with 22 minimum features, respectively.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1183-1186
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• 1998

Adaptive nois canceller can extract the noiseremoved spech in noisy speech signal by adapting the filter-coefficients to the background noise environment. A kind of LMS algorithm is one of the most popular adaptive algorithm for noise cancellation due to low complexity, good numerical property and the merit of easy implementation. However there is the matter of increasing misadjustment at voiced speech signal. Therefore the demanded speech signal may be extracted. In this paper, we propose a fast and noise robust wavelet packet adaptive noise canceller with NLMS-SUM method LMS combined algorithm. That is, we decompose the frequency of noisy speech signal at the base of the proposed analysis tree structure. NLMS algorithm in low frequency band can efficiently dliminate the effect of the low frequency noise and SUM method LMS algorithm at each high frequency band can remove the high frequency nosie. The proposed wavelet packet adaptive noise canceller is enhanced the more in SNR and according to Itakura-Satio(IS) distance, it is closer to the clean speech signal than any other previous adaptive noise canceller.

• The Korean Journal of Applied Statistics
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• v.23 no.4
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• pp.759-765
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• 2010

In this paper, two new inverse regression methods are introduced. One is a distance based method, and the other is a likelihood based method. While a model is fitted by minimizing the sum of squared prediction errors of y's and x's in the classical and inverse methods, respectively. In the new distance based method, we simultaneously minimize the sum of both squared prediction errors. In the likelihood based method, we propose an inverse regression with Arnold-Beaver Skew Normal(ABSN) error distribution. Using the cross validation method with an asymmetric real data set, two new and two existing methods are studied based on the relative prediction bias(RBP) criteria.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.6
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• pp.340-345
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• 2002

In this paper, we deal with the following facility location problem. Given a set P of n points in the plane, find two (discrete) centers p and q in P that minimize the sum of there distance plus the distance of any other point to the closer center. In this paper, we propose an Ο(n$^2$1ogn)-time algorithm to compute the two centers.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.7
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• pp.138-146
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• 1996

In this paper, w epropose a new mehtod to represent the shape and to recognize the object. The shape description and the matching is implemented by using the distance transform on the morphological skeleton. The employed distance transform is the chamfer (3,4) distance transform, because the chamfer distance transform (CDT) has an approximate value to the euclidean distance. The 2-D object can be represented by means of the distribution of the distance transform on the morphological skeleton, the number of skeletons, the sum of the CDT, and the other features are employed as the mtching parameters. The matching method has the invariant features (rotation, translation, and scaling), and then the method is used effectively for recognizing the differently-posed objects and/or marks of the different shape and size.