• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.2
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• pp.103-110
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• 2011

It is necessary to accurate and efficient management for measured digital data from sensors in u-health system. It is not efficient that sensor network process input stream data of mass storage stored in database the same time. We propose to improve the processing performance of multidimensional stream data continuous incoming from multiple sensor. We propose process query based on sliding window for efficient input stream and found multiple query plan to Mjoin method and we reduce stored data using backpropagation algorithm. As a result, we obtained to efficient result about 18.3% reduction rate of database using 14,324 data sets.

• Journal of Communications and Networks
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• v.9 no.3
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• pp.330-341
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• 2007

This work analyzes the performance of the parallel packet switch (PPS) with a sliding window (SW) method. The PPS involves numerous packet switches that operate independently and in parallel. The conventional PPS dispatch algorithm adopts a round robin (RR) method. The class of PPS is characterized by deployment of parallel low-speed switches whose all memory buffers run more slowly than the external line rate. In this work, a novel SW packet switching method for PPS, called SW-PPS, is proposed. The SW-PPS employs memory space more effectively than the existing PPS using RR algorithm. Under identical Bernoulli and bursty data traffic, the SW-PPS provided significantly improved performance when compared to PPS with RR method. Moreover, this investigation presents a novel mathematical analytical model to evaluate the performance of the PPS using RR and SW method. Under various operating conditions, our proposed model and analysis successfully exhibit these performance characteristics including throughput, cell delay, and cell drop rate.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.285-294
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• 2007

In this paper, we investigate a novel online estimation algorithm for dynamic Bayesian network(DBN) parameters, given as conditional probabilities. We sequentially update the parameter adjustment rule based on observation data. We apply our algorithm to two well known representations of DBNs: to a first-order Markov Chain(MC) model and to a Hidden Markov Model(HMM). A sliding window allows efficient adaptive computation in real time. We also examine the stochastic convergence and stability of the learning algorithm.

• Journal of the Korea Computer Industry Society
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• v.7 no.5
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• pp.513-520
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• 2006

In this paper, we propose a novel real-time frame-layer rate control algorithm using sliding window method for low bit rate video coding. The proposed rate control method performs bit allocation at the frame level to minimize the average distortion over an entire sequence as well as variations in distortion between frames. A new frame-layer rate-distortion model is derived, and a non-iterative optimization method is used for low computational complexity. In order to reduce the quality fluctuation, we use a sliding window scheme which does not require the pre-analysis process. Therefore, the proposed algorithm does not produce time delay from encoding, and is suitable for real-time low-complexity video encoder. Experimental results indicate that the proposed control method provides better visual and PSNR performance than the existing TMN8 rate control method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.147-151
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• 2002

One of the main issues in Diffserv AS architecture is guaranteeing fairness among the flows which have their own QoS requirements. Because the methodology of resource allocation and traffic conditioning would affect the end-to-end QoS and backbone link utilization. In this paper, we propose a variant of TSW algorithm for enhancing fair bandwidth allocation and link utilization and presents performance evaluation between TSW & TS2W3C through NS-2 Simulations.

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.1
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• pp.116-126
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• 2000

Turbo codes are the most exciting and potentially important development in coding theory in recent years. They were introduced in 1993 by Berrou, Glavieux and $Thitimajshima,({(1)}$ and claimed to achieve near Shannon-limit error correction performance with relatively simple component codes and large interleavers. A required Eb/N0 of 0.7㏈ was reported for BER of $10^{-5}$ and code rate of $l/2.^{(1)}$ However, to implement the turbo code system, there are various important details that are necessary to reproduce these results such as AGC gain control, optimal wordlength determination, and metric rescaling. Further, the memory required to implement MAP-based turbo decoder is relatively considerable. In this paper, we confirmed the accuracy of these claims by computer simulation considering these points, and presented a optimal wordlength for Turbo code design. First, based on the analysis and simulation of the turbo decoder, we determined an optimal wordlength of Turbo decoder. Second, we suggested the MAP decoding algorithm based on sliding-window method which reduces the system memory significantly. By computer simulation, we could demonstrate that the suggested fixed-point Turbo decoder operates well with negligible performance loss.

• Journal of Korea Multimedia Society
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• v.22 no.1
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• pp.35-43
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• 2019

Template tracking refers to the procedure of finding the most similar image patch corresponding to the given template through an image sequence. In order to obtain more accurate trajectory of the template, the template requires to be updated to reflect various appearance changes as it traverses through an image sequence. To do that, appearance images are used to model appearance variations and these are obtained by the computation of the principal components of the augmented image matrix at every iteration. Unfortunately, it is prohibitively expensive to compute the principal components at every iteration. Thus in this paper, we suggest a new Sliding Window based truncated URV Decomposition (TURVD) algorithm which enables updating their structure by recycling their previous decomposition instead of decomposing the image matrix from the beginning. Specifically, we show an efficient algorithm for updating and downdating the TURVD simultaneously, followed by the rank-one update to the TURVD while tracking the decomposition error accurately and adjusting the truncation level adaptively. Experiments show that the proposed algorithm produces no-meaningful differences but much faster execution speed compared to the typical algorithms in template tracking applications, thereby maintaining a good approximation for the principal components.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.649-652
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• 2015

Previous marking policy for the AF service of TCP traffic in the Diffserv network have no sufficient consideration on the effect of RTT and target rate. In this paper, in order to improve fairness Index by the effect RTT difference of TCP traffic, we propose the modified TSW3CDM(Time Sliding Window Three Color Dynamic Marker) based on average transfer rate estimation and the flow state. The proposed algorithm is dynamic marking policy that do allocate band width in proportion to transmission rate. To evaluate the performance of the proposed algorithm, We accomplished a computer simulation using NS-2. From simulation results, the proposed TSW3CDM algorithm improves fairness index by comparison with TSW3CM.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.790-792
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• 2004

문서 범주화에서 이진분류를 다중 분류에 적용할 때, 일반적으로 One-Against-All 방법을 사용한다. 하지만, 이 One-Against-All 방법은 한가지 문제점을 가진다. 즉, positive 집합의 문서들은 사람이 직접 범주를 할당한 것이지만, negative 집합의 문서들은 사람이 직접 범주를 할당한 것이 아니기 때문에 오류 문서들이 포함될 수 있다는 것이다. 본 논문에서는 이러한 문제점을 해결하기 위해 Sliding Window기법과 EM 알고리즘을 이진 분류 기반의 문서 범주화에 적용할 것을 제안한다. 먼저 Sliding Window 기법을 이용하여 학습 데이터로부터 오류 문서들을 추출하고 이 문서들을 EM 알고리즘을 사용해서 다시 범주를 할당함으로써 이진 분류 기반의 문서 범주화 기법의 성능을 향상시킨다.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.4
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• pp.129-135
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• 2016

In this paper, we propose a novel tracking algorithm called slide window tracker (SWT) suitable for maneuvering target. To efficiently estimate trajectory of moving target, we adopt a sliding piecewise linear window which includes past trace information. By adjusting the window parameters, the proposed algorithm is to reduce measurement noise and to track fast maneuvering target with little computational increment as compared to ${\alpha}-{\beta}$ tracker. Throughout the computer simulations, we verify outstanding tracking performance of the SWT algorithm in noisy linear and nonlinear trajectories. Also, we show that the SWT algorithm is not sensitive to initial model parameter selection, which gives large degree of freedom in applying the SWT algorithm to unknown time-varying measurement environments.