• Journal of Information Processing Systems
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• v.15 no.4
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• pp.986-1016
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• 2019

Mobile user interface pattern (MUIP) is a kind of structured representation of interaction design knowledge. Several studies have suggested that MUIPs are a proven solution for recurring mobile interface design problems. To facilitate MUIP selection, an effective clustering method is required to discover hidden knowledge of pattern data set. In this paper, we employ the semi-supervised kernel fuzzy c-means clustering (SSKFCM) method to cluster MUIP data. In order to improve the performance of clustering, clustering parameters are optimized by utilizing the global optimization capability of particle swarm optimization (PSO) algorithm. Since the PSO algorithm is easily trapped in local optima, a novel PSO algorithm is presented in this paper. It combines an improved intuitionistic fuzzy entropy measure and a new population search strategy to enhance the population search capability and accelerate the convergence speed. Experimental results show the effectiveness and superiority of the proposed clustering method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1232-1239
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• 2006

In video standards such as MPEG-1/2/4 and H.264/AVC, motion estimation / compensation(ME/MC) process causes the most encoding complexity of video encoder. The full search method, which is used in general video codecs, exhausts much encoding time because it compares current macroblock with those at all positions within search window for searching a matched block. For the alleviation of this problem, the fast search methods such as TSS, NTSS, DS and HEXBS are exploited at first. Thereafter, DS based MVFAST, PMVFAST, MAS and FAME, which utilize temporal or spacial correlation characteristics of motion vectors, are developed. But there remain the problems of image quality degradation and algorithm complexity increase. In this thesis, the proposed algorithm maximizes search speed and minimizes the degradation of image quality by determining initial search point correctly and using simple one-dimension search patterns considering motion characteristics of each frame.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.55-65
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• 2006

Most of fast block motion estimation algorithms reported so far in literatures aim to reduce the computation in terms of the number of search points, thus do not fit well with multimedia processors due to their irregular data flow. For multimedia processors, proper reuse of data is more important than reducing number of absolute difference operations because the execution cycle performance strongly depends on the number of off-chip memory access. Therefore, in this paper, we propose a Hexagon-shape line search (HEXSLS) algorithm using line search pattern which can increase data reuse from on-chip local buffer, and check sub-sampling points in line search pattern to reduce unnecessary SAD operation. Our experimental results show that the prediction error (MAE) performance of the proposed HEXSLS is similar to that of the full search block matching algorithm (FSBMA), while compared with the hexagon-based search (HEXBS), the HEXSLS outperforms. Also the proposed HEXSLS requires much lesser off-chip memory access than the conventional fast motion estimation algorithm such as the hexagon-based search (HEXBS) and the predictive line search (PLS). As a result, the proposed HEXSLS algorithm requires smaller number of execution cycles on media processor.

• Journal of applied mathematics & informatics
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• v.16 no.1_2
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• pp.195-205
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• 2004

To the unconstrained programme of non-convex function, this article give a modified BFGS algorithm. The idea of the algorithm is to modify the approximate Hessian matrix for obtaining the descent direction and guaranteeing the efficacious of the quasi-Newton iteration pattern. We prove the global convergence properties of the algorithm associating with the general form of line search, and prove the quadratic convergence rate of the algorithm under some conditions.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.903-904
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• 2008

This paper suggests a simple scheme of block motion estimation in which the search pattern selection is based on the classification of motion content available in the spatio temporal neighboring blocks. The search area is divided into eight sectors and the search pattern selection is also based on the direction of predicted motion vector. Experimental results show that the proposed algorithm has achieved good predicted image quality measured in terms of PSNR and has very less computational complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.711-725
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• 2013

A heuristic with multi-byte suffix matching plays an important role in real pattern matching algorithms. By skipping many characters at a time in the process of comparing a given pattern with the text, the pattern matching algorithm based on a heuristic with multi-byte suffix matching shows a faster average search time than algorithms based on deterministic finite automata. Based on various experimental results and simulations, the previous works show that the pattern matching algorithms with multi-byte suffix matching performs well. However, there have been limited studies on the mathematical model for analyzing the performance in a standard manner. In this paper, we propose a new probabilistic model, which evaluates the performance of a heuristic with multi-byte suffix matching in an average-case search. When the theoretical analysis results and experimental results were compared, the proposed probabilistic model was found to be sufficient for evaluating the performance of a heuristic with suffix matching in the real pattern matching algorithms.

• Journal of Korea Multimedia Society
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• v.3 no.4
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• pp.372-379
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• 2000

In this paper, we propose a fast variable-size block matching algorithm for motion estimation based on bit-pattern. Motion estimation in the proposed algorithm is performed after the representation of image sequence is transformed 8bit pixel values into 1bit ones depending on the mean value of search block, which brings a short searching time by reducing the computational complexity. Moreover, adaptive searching methods according to the motion information of the block make the procedure of motion estimation efficient by eliminating an unnecessary searching of low motion block and deepening a searching procedure in high motion block. Experimental results show that the proposed algorithm provides better performance-0.5dB PSNR improvement-than full search block matching algorithm with a fixed block size.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.12
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• pp.1219-1223
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• 2010

This paper proposes a fast motion estimation algorithm based on motion speed and multiple initial center points. The proposed method predicts initial search points by means of the spatio-temporal neighboring motion vectors. A dynamic search pattern based on the motion speed and the predicted initial center points is proposed to quickly obtain the motion vector. Due to the usage of the spatio-temporal information and the dynamic search pattern, the proposed method greatly accelerates the search speed while keeping a good predicted image quality. Experimental results show that the proposed method has a good predicted image quality in terms of PSNR with less searching time comparing with the Full Search, New Three-Step Search, and Four-Step Search.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4D
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• pp.555-561
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• 2009

In lieu of section profile data, a fitting of the bored tunnel shape is more significant confirmation for maintenance of a tunnel. Before the permit on the completion of a tunnel, deformation of the completed tunnel with respect to the design model are considered. And deformation can be produced at continuously along the entire of the tunnel section. This study firstly includes an analysis of algebraic approach and test it with an observed field data. And then a number of methods, line search method, genetic algorithm, and pattern search methods, are compared with the 3D tunnel shape fitting. Algebraic methods can solve a simple circular cylinder type as like a railway tunnel. However, a more complex model (compound circular curve and non circular) as like a highway tunnel has to be solved with soft computing tools in the cause of conditional constraints. The genetic algorithm and pattern search methods are computationally more intensive, but they are more flexible at a complex condition. The line search method is fastest, but it needs a narrow bounds of the initial values.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.247-256
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• 2004

In this paper, we propose the prediction search algorithm for block matching using the temporal/spatial correlation of the video sequence and the renter-biased property of motion vectors The proposed algorithm determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(Sum of Absolute Difference) value by the predicted motion vector from the same block of the previous frame and the predictor candidate pint in each search region and the predicted motion vector from the neighbour blocks of the current frame. And the searching process after moving the starting point is processed a adaptive search pattern according to the magnitude of motion vector Simulation results show that PSNR(Peak-to-Signal Noise Ratio) values are improved up to the 0.75dB as depend on the video sequences and improved about 0.05∼0.34dB on an average except the FS (Full Search) algorithm.