• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.110-116
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• 2014

Pattern matching algorithms are widely used in computer security systems such as computer networks, ubiquitous networks, sensor networks, and so on. However, the advances in information technology causes grow on the amount of data and increase on the computation complexity of pattern matching processes. Therefore, there is a strong demand for a novel high performance pattern matching algorithms. In light of this fact, this paper newly proposes a suffix tree based pattern matching algorithm. The suffix tree is constructed based on the suffix values of all patterns. Then, the shift nodes which informs how many characters can be skipped without matching operations are added to the suffix tree in order to boost matching performance. The proposed algorithm reduces memory usage on the suffix tree and the amount of matching operations by the shift nodes. From the performance evaluation, our algorithm achieved 24% performance gain compared with the traditional algorithm named as Wu-Manber.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.70-81
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• 1998

This paper proposes an accurate and cost-effective COA defuzzifier of fuzzy logic controller (FLC). The accuracy of the proposed COA defuzzifier is obtained by involving both membership values and spans of membership functions in calculating a crisp value. The cost-effectiveness of the proposed COA defuzzifier is obtained by replacing the division in the COA defuzzifier by finding an equilibrium point of both the left and right moments. The proposed COA defuzzifier has two disadvantages that it ncreases the hardware complexity due to the additional multipliers and it takes a lot of computation time to find the moment equilibrium point. The first disadvantage is overcome by replacing the multipliers with the stochastic AND operations. The second disadvantage is alleviated by using a coarse-to-fine searching algorithm that accelerates the finding of moment equilibrium point. Application of the proposed COA defuzzifier to the truck backer-upper control problem is performed in the VHDL simulation and the control accuracy of the proposed COA defuzzifier is compared with that of the conventional COA defuzzifier in terms of average tracing distance.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.275-282
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• 2004

In this paper, a transcoding method that transforms MPEG-4 video bitstream coded in 30 Hz frame rate into H.264 video bitstream of 15 Hz frame rate is proposed. The block modes and motion vectors in MPEG-4 is utilized in H.264 for block mode conversion and motion vector (MV) interpolation methods. The proposed three types of MV interpolation method can be used without performing full motion estimation in H.264. The proposed transcoder reduces computation amount for full motion estimation in H.264 and provides good quality of H.264 video at low bitrates. In experimental results, the proposed methods achieves 3.2-4 times improvement in computational complexity compared to the cascaded pixel-domain transcoding, while the PSNR (peak signal to noise ratio) is degraded with 0.2-0.9dB depending on video sizes.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.12
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• pp.36-46
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• 1999

As the requirements of embedded systems increase, the design complexity of the system becomes higher. The formal design methodology is required which supports well-balanced specification for control and dataflow to design a complex system. In this paper, control modules and function modules are separately described with FSMs and dataflow graphs respectively, and integrated into a system specification via inter-model communications. In previous approaches, the system could not be verified until control modules and dataflow modules are combined at the final design stage. However our approach enables us to design each part as the proper model of computation at early stage, and to verify the compositions and to co-synthesize the system effectively in the same framework. Especially this paper focuses on the communication protocols between control and dataflow models. Preliminary experiments show practicality of the proposed technique.

• Journal of Broadcast Engineering
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• v.12 no.5
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• pp.491-502
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• 2007

In this parer, we propose an efficient intra prediction mode decision scheme in Scalable Video Coding(SVC) which is an emerging video coding standard as an extension of H.264/MPEG-4 AVC(Advanced Video Coding). The proposed method in base on the characteristic of macroblock smoothness follows the statistical analysis of intra prediction mode in an enhancement layer and it decides a candidate intra prediction mode. We also propose an early termination scheme for Intra_BL mode decision where the RD cost value of Intra_BL is utilized. Simulation results show that the proposed method reduces 54.67% of the computation complexity of intra prediction coding, while the degradation in video quality is negligible; for low QP values, the average PSNR loss is very negligible, equivalently the bit rate increases by 0.011%. For high QP values, the average PSNR loss is less than 0.01dB, which equals to 0.249% increase in bitrate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3295-3311
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• 2020

With the wide application of hyperspectral images, it becomes more and more important to compress hyperspectral images. Conventional recursive least squares (CRLS) algorithm has great potentiality in lossless compression for hyperspectral images. The prediction accuracy of CRLS is closely related to the correlations between the reference bands and the current band, and the similarity between pixels in prediction context. According to this characteristic, we present an improved CRLS with adaptive band selection and adaptive predictor selection (CRLS-ABS-APS). Firstly, a spectral vector correlation coefficient-based k-means clustering algorithm is employed to generate clustering map. Afterwards, an adaptive band selection strategy based on inter-spectral correlation coefficient is adopted to select the reference bands for each band. Then, an adaptive predictor selection strategy based on clustering map is adopted to select the optimal CRLS predictor for each pixel. In addition, a double snake scan mode is used to further improve the similarity of prediction context, and a recursive average estimation method is used to accelerate the local average calculation. Finally, the prediction residuals are entropy encoded by arithmetic encoder. Experiments on the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) 2006 data set show that the CRLS-ABS-APS achieves average bit rates of 3.28 bpp, 5.55 bpp and 2.39 bpp on the three subsets, respectively. The results indicate that the CRLS-ABS-APS effectively improves the compression effect with lower computation complexity, and outperforms to the current state-of-the-art methods.

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.18-25
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• 1997

The feedforward control algorithm for active noise control exhibits high stability and performance robustness. But it has a slow convergence speed and requires a correlated reference signal. Broadband active control systems typically use feedback control in order to increase the convergence speed and to avoid the problems associated with obtaining and decoupling a suitable reference signal. However, it is well known that conventional feedback control systems have a gain-bandwidth limitation and stability problem. This paper presents the new system based on the combination of both feedforward and feedback system in order to increase the convergence speed. The proposed system uses a proposed control algorithm termed "optional-summed" algorithm in which the "optional summed reference signal" comprised of weighted sum of an original reference signal and a eror signal, is used as an input to an adaptive system. Thus, the proposed system can have faster convergence speed and better performance than either feedforward or feedback system using the Filtered-x LMS algorithm as almost equivalent complexity of computation as it. Several simulation results demonstrating the good properties of the proposed adaptive system as well as verifying the analytical results are also presented in the paper.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.73-82
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• 2010

Door is an important object to understand given environment and it could be used to distinguish with corridors and rooms. Doors are widely used natural landmark in mobile robotics for localization and navigation. However, almost algorithm for door recognition with camera is difficult real-time application because feature extraction and matching have heavy computation complexity. This paper proposes a method to recognize a door in corridor. First, we extract distinguished lines which have high possibility to comprise of door using Hough transformation. Then, we detect candidate of door region by applying previously extracted lines to first-stage visual fuzzy system. Finally, door regions are determined by verifying knob region in candidate of door region suing second-stage visual fuzzy system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1454-1466
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• 2016

This paper implements an estimated ranking algorithm of closeness centrality measures in large-scale workflow-supported social networks. The traditional ranking algorithms for large-scale networks have suffered from the time complexity problem. The larger the network size is, the bigger dramatically the computation time becomes. To solve the problem on calculating ranks of closeness centrality measures in a large-scale workflow-supported social network, this paper takes an estimation-driven ranking approach, in which the ranking algorithm calculates the estimated closeness centrality measures by applying the approximation method, and then pick out a candidate set of top k actors based on their ranks of the estimated closeness centrality measures. Ultimately, the exact ranking result of the candidate set is obtained by the pure closeness centrality algorithm [1] computing the exact closeness centrality measures. The ranking algorithm of the estimation-driven ranking approach especially developed for workflow-supported social networks is named as RankCCWSSN (Rank Closeness Centrality Workflow-supported Social Network) algorithm. Based upon the algorithm, we conduct the performance evaluations, and compare the outcomes with the results from the pure algorithm. Additionally we extend the algorithm so as to be applied into weighted workflow-supported social networks that are represented by weighted matrices. After all, we confirmed that the time efficiency of the estimation-driven approach with our ranking algorithm is much higher (about 50% improvement) than the traditional approach.

• Journal of Energy Engineering
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• v.14 no.1
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• pp.46-53
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• 2005

This paper presents a new approach for determining an accurate incentive levels of Direct Load Control (DLC) program using probabilistic techniques. The economic analysis of DLC resources needs to identify the hourly-by-hourly expected energy-not-served resulting from the random outage characteristics of generators as well as to reflect the availability and duration of DLC resources, which results the computational explosion. Therefore, the conventional methods are based on the scenario approaches to reduce the computation time as well as to avoid the complexity of economic studies. In this paper, we have developed a new technique based on the sequential Monte Carlo simulation to evaluate the required expected load control amount in each hour and to decide the incentive level satisfying the economic constraints. In addition, we have applied the variance reduction technique to enhance the efficiency of the simulation. To show the efficiency and effectiveness of the suggested method, the numerical studies have been performed for the modified IEEE 24-bus reliability test system.