• ETRI Journal
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• v.43 no.3
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• pp.483-510
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• 2021

In computational biology, desired patterns are searched in large text databases, and an exact match is preferable. Classical benchmark algorithms obtain competent solutions for pattern matching in O (N) time, whereas quantum algorithm design is based on Grover's method, which completes the search in $O(\sqrt{N})$ time. This paper briefly explains existing quantum algorithms and defines their processing limitations. Our initial work overcomes existing algorithmic constraints by proposing the quantum-based combined exact (QBCE) algorithm for the pattern-matching problem to process exact patterns. Next, quantum random access memory (QRAM) processing is discussed, and based on it, we propose the QRAM processing-based exact (QPBE) pattern-matching algorithm. We show that to find all t occurrences of a pattern, the best case time complexities of the QBCE and QPBE algorithms are $O(\sqrt{t})$ and $O(\sqrt{N})$, and the exceptional worst case is bounded by O (t) and O (N). Thus, the proposed quantum algorithms achieve computational speedup. Our work is proved mathematically and validated with simulation, and complexity analysis demonstrates that our quantum algorithms are better than existing pattern-matching methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.305-326
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• 2019

Discriminative correlation filter (DCF) based tracking algorithms have recently shown impressive performance on benchmark datasets. However, amount of recent researches are vulnerable to heavy occlusions, irregular deformations and so on. In this paper, we intend to solve these problems and handle the contradiction between accuracy and real-time in the framework of tracking-by-detection. Firstly, we propose an innovative strategy to combine the template and color-based models instead of a simple linear superposition and rely on the strengths of both to promote the accuracy. Secondly, to enhance the discriminative power of the learned template model, the spatial regularization is introduced in the learning stage to penalize the objective boundary information corresponding to features in the background. Thirdly, we utilize a discriminative multi-scale estimate method to solve the problem of scale variations. Finally, we research strategies to limit the computational complexity of our tracker. Abundant experiments demonstrate that our tracker performs superiorly against several advanced algorithms on both the OTB2013 and OTB2015 datasets while maintaining the high frame rates.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.283-290
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• 1999

A practical damage identification scheme for PS concrete bridges via modal testing and system identification (SID) procedures is presented. The potential damage types are classified and the possible approaches which can be implemented into each damage type are designed. Damage identification algorithms are developed on the basis of the SID and modal analysis. The feasibility of the algorithms is verified from experimental tests to detect damage in PS concrete beam structures.

• Journal of applied mathematics & informatics
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• v.23 no.1_2
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• pp.369-383
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• 2007

This paper is devoted to the foldness theory of implicative ideals in BCK-algebras. We use the fuzzy point concept to give some characterizations of fuzzy n-fold implicative ideals and establish some relationships with various n-fold ideals. We also construct some algorithms for studying the foldness of implicative ideals in BCK-algebras.

• ETRI Journal
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• v.10 no.3
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• pp.125-140
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• 1988

Computational geometry has wide applications in pattern recognition, image processing, VLSI design, and computer graphics. Voronoi diagrams in computational geometry possess many important properites which are related to other geometric structures of a set of point. In this pater the design of systolic algorithms for the static and the dynamic Voronoi diagrams is considered. The major motivation for developing the systolic architecture is for VLSI implementation. A new systematic transform technique for designing systolic arrays, in particular, for the problem in computational geometry has been proposed. Following this procedure, a type T systolic array architecture and associated systolic algorithms have been designed for constructing Voronoi diagrams. The functions of the cells in the array are also specified. The resulting systolic array achieves the maximal throughput with O(n) computational complexity.

• Computers and Concrete
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• v.23 no.5
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• pp.311-320
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• 2019

The substructuring technique is one of the efficient methods for reducing computational effort and memory usage in the finite element method, especially in large-scale structures. Proper mesh partitioning plays a key role in the efficiency of the technique. In this study, new algorithms are proposed for mesh partitioning based on an element search technique. The computational cost function is optimized by aligning each element of the structure to a proper substructure. The genetic algorithm is employed to minimize the boundary nodes of the substructures. Since the boundary nodes have a vital performance on the mesh partitioning, different strategies are proposed for the few number of substructures and higher number ones. The mesh partitioning is optimized considering both computational and memory requirements. The efficiency and robustness of the proposed algorithms is demonstrated in numerous examples for different size of substructures.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.263-277
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• 2005

In this paper, we introduce algorithms for constructing broadcasting and multicasting trees. These algorithms are general because they may be used for tree cost functions that are of arbitrary form. Thus, essentially the same algorithmic procedures are used for different tree cost functions. We evaluate the effectiveness of the general algorithms by applying them to different cost functions that are often used to model wired and wireless net­works. Besides providing a unifying framework for dealing with many present and future tree-construction applications, these algorithms typically outperform some existing algorithms that are specifically designed for energy-aware wireless networks. These general algorithms perform well at the expense of higher computational complexity. They are centralized algorithms, requiring the full network information for tree construction. Thus, we also present variations of these general algorithms to yield other algorithms that have lower complexity and distributed implementation.

• Journal of applied mathematics & informatics
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• v.8 no.2
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• pp.387-401
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• 2001

If the distance between two vertices becomes longer after the removal of a vertex u, then u is called a hinge vertex. In this paper, a linear time sequential algorithm is presented to find all hinge vertices of an interval graph. Also, a parallel algorithm is presented which takes O(n/P + log n) time using P processors on an EREW PRAM.

• Journal of applied mathematics & informatics
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• v.26 no.3_4
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• pp.481-491
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• 2008

In this paper, we introduce and analyze a new class of generalized mixed equilibrium-like problems. By using the auxiliary principle technique, we suggest three iterative algorithms for the generalized mixed equilibrium-like problem. Under certain conditions, we establish the convergence of the iterative algorithms. Our results extend, improve and unify several known results in this field.

• Journal of applied mathematics & informatics
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• v.5 no.2
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• pp.313-328
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• 1998

In this paper we establish the equivalence between the generalized nonlinear mixed variational inequalities and the gener-alized resolvent equations. This equivalence is used to suggest and analyze a number of iterative algorithms for solving generalized vari-ational inequalities. We also discuss the convergence analysis of the propose algorithms. As special cases we obtain various known re-sults from our results.