• Phonetics and Speech Sciences
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• v.1 no.4
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• pp.127-132
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• 2009

The feature vectors which are used in conventional speaker recognition (SR) systems may have many correlations between their neighbors. To improve the performance of the SR, many researchers adopted linear transformation method like principal component analysis (PCA). In general, the linear transformation of the feature vectors is based on concatenated form of the static features and their dynamic features. However, the linear transformation which based on both the static features and their dynamic features is more complex than that based on the static features alone due to the high order of the features. To overcome these problems, we propose an efficient method that applies linear transformation and temporal information of the features to reduce complexity and improve the performance in speaker verification (SV). The proposed method first performs a linear transformation by PCA coefficients. The delta parameters for temporal information are then obtained from the transformed features. The proposed method only requires 1/4 in the size of the covariance matrix compared with adding the static and their dynamic features for PCA coefficients. Also, the delta parameters are extracted from the linearly transformed features after the reduction of dimension in the static features. Compared with the PCA and conventional methods in terms of equal error rate (EER) in SV, the proposed method shows better performance while requiring less storage space and complexity.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.97-114
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• 2022

Interest is increasing in electrocardiogram (ECG) signal analysis for embedded devices, creating the need to develop an algorithm suitable for a low-power, low-memory embedded device. Linear approximation of the ECG signal facilitates the detection of fiducial points by expressing the signal as a small number of vertices. However, dynamic programming, a global optimization method used for linear approximation, has the disadvantage of high complexity using memoization. In this paper, the calculation area and memory usage are improved using a linear approximated template. The proposed algorithm reduces the calculation area required for dynamic programming through local optimization around the vertices of the template. In addition, it minimizes the storage space required by expressing the time information using the error from the vertices of the template, which is more compact than the time difference between vertices. When the length of the signal is L, the number of vertices is N, and the margin tolerance is M, the spatial complexity improves from O(NL) to O(NM). In our experiment, the linear approximation processing time was 12.45 times faster, from 18.18 ms to 1.46 ms on average, for each beat. The quality distribution of the percentage root mean square difference confirms that the proposed algorithm is a stable approximation.

• Journal of Korea Multimedia Society
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• v.9 no.1
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• pp.59-72
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• 2006

The rapid growth of technology for network and terminal devices is able to service multimedia contents in mobile environments. But as the environment of networks and the performance of devices is varied, the same quality service is very difficult to be provided for user in internet and mobile environment. Therefore, multimedia streaming system must provide an adaptive service in considering network and device environment. Video transcoding techniques are the good solution that can provide video streaming service in various network environments adaptively. This paper proposes a dynamic frame-skipping transcoding scheme to provide adaptive streaming service in various network environments. This scheme uses the prediction period for transcoding. A proposed transcoding scheme can reduce time complexity through combination of prediction period and skipping period to control frame-skipping rate in encoder. In simulation results, the performance of proposed scheme is similar to the performance of a traditional dynamic frame-skipping scheme in PSNR value. But the performance of proposed scheme outperforms the performance of traditional scheme in time complexity.

• Journal of Korea Multimedia Society
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• v.13 no.1
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• pp.30-37
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• 2010

Many embedded real - lime systems have adopted processors supported with dynamic voltage scal-ing(DVS) recently. Power is one of the important metrics for Optimization in the design and operation of embedded real-time systems. We can save considerable energy by using slowdown of processor sup-ported with DVS. In this paper, we improved the previous algorithm at a point of view of time complexity to calculate task slowdown factors for an efficient energy consumption in embedded real-time systems with task synchronization. We grasped the properties of the previous algorithm having $O(n^{2})$ time complexity through mathematical analysis and s simulation. Using its properties we proposed the improved algorithms with O(nlogn) and O(n) time complexity which have the same performance as the previous algorithm has.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.1
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• pp.46-53
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• 2013

Recently, intensive research has been performed for reducing video decoder energy consumption, especially based on DVFS (Dynamic Voltage and Frequency Scaling) technique. Our previous work [1] has proposed the optimal DVFS algorithm for energy reduction in video decoders. In spite of the mathematical optimality of the algorithm, the precondition of known frame decoding cycle/complexity limits its application to some realistic scenarios. This paper overcomes this limitation by frame data size-based estimation of frame decoding complexity. The proposed decoding complexity estimation method shows over 90% accuracy. And with this estimation method and buffer underflow margin of around 20% of frame size, almost same power consumption reduction performance as the optimal algorithm can be achieved.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.6
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• pp.56-62
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• 2009

Inexpensive high performance computer systems combined with high speed networks and machine independent communication libraries have made cluster computing a viable option for parallel applications. In a heterogeneous cluster environment, efficient resource management is critically important since the computing power of the individual computer system is a significant performance factor when executing applications in parallel. This paper presents a dynamic task manager, called DWM (dynamic work manager). It makes a heterogeneous cluster system fully utilize the different computing power of its individual computer system. We measure the performance of DWM in a heterogeneous cluster environment with several kernel-level benchmark programs and their programming complexity quantitatively. From the experiments, we found that DWM provides competitive performance with a notable reduction in programming effort.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10C
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• pp.787-797
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• 2008

In this paper, we propose a fast disparity estimation method considering temporal and spatial redundancy based on a dynamic programming for stereo matching. For the first step, the dynamic programming is performed to estimate disparity vectors with correlation between neighboring pixels in an image. Next, we efficiently compensate regions, which disparity vectors are not allocated, with neighboring disparity vectors assuming that disparity vectors in same object are quite similar. Moreover, in case of video sequence, we can decrease a complexity with temporal redundancy between neighboring frames. For performance comparison, we generate an intermediate-view image using the estimated disparity vector. Test results show that the proposed algorithm gives $0.8{\sim}2.4dB$-increased PSNR(peak signal to noise ratio) compared to a conventional block matching algorithm, and the proposed algorithm also gives approximately 0.1dB-increased PSNR and $48{\sim}68%$-lower complexity compared to the disparity estimation method based on general dynamic programming.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9A
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• pp.814-821
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• 2005

When there are many tags using the same frequency around the reader in RFID system, they disturb each other and in the end their response cannot be received by the reader. To solve this disturbance and fast identify the tags, the anti-collision algorithm, which is the core technology in RFID system, is needed. We propose two ALOHA-type Dynamic Framed Slotted ALOHA(DFS-ALOHA) algorithms using Dynamic Slot Allocation(DSA), which dynamically allocates the frame size in accordance with the number of tags and Tag Estimation Method(TEM), which estimates the number of tags around the reader. We also compare the performance of the proposed DFS-ALOHA algorithms with that of the conventional Framed Slotted ALOHA (FS-ALOHA) algorithms and the algorithms proposed by Vogt using OPNET simulation. According to the analysis, the two proposed DFS-ALOHA algorithms(DFS-ALOHA I and DFS-ALOHA II) show better performance than the conventional ALOHA-based algorithms regardless of the number of tags. Although the two proposed DFS-ALOHA algorithms show the similar performance, BFS-ALOHA ll is better because it is easier to be implemented in the system and the complexity is lower.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1645-1654
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• 2007

In this paper, we study the problem of load balancing routing in clustered-based wireless mesh network in order to enhance the overall network throughput. We first address the problems of cluster allocation in wireless mesh network to achieve load-balancing state. Due to the complexity of the problem, we proposed a simplified algorithm using gradient load-balancing model. This method searches for a localized optimal solution of cluster allocation instead of solving the optimal solution for overall network. To support for load-balancing algorithm and reduce complexity of topology control, we also introduce limited broadcasting between two clusters. This mechanism maintain shortest path between two nodes in adjacent clusters while minimizing the topology broadcasting complexity. The simulation experiments demonstrate that our proposed model achieve performance improvement in terms of network throughput in comparison with other clustering methods.

• The KIPS Transactions:PartC
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• v.11C no.3
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• pp.345-352
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• 2004

Recently, contents distribution technologies have been used to cope with the explosive demand for Web services. In this paper, we addressed the issue of the optimal placement of replicas in the environment where Web contents are replicated. We placed replicas so that clients can have access to replicas with the proper delay and bandwidth. We attempted to solve the problem via dynamic programming considering cost of delay and traffic We have come up with time complexity that is less than $O(n^2)$. We defined the threshold and proved that our algorithm guarantees the reliable services.