• ETRI Journal
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• 제24권6호
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• pp.465-468
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• 2002

Ethernet passive optical networks (PONs) are an emerging access network technology that provides a low-cost method of deploying optical access lines between a carrier's central office and a customer site. In this paper, we propose a new algorithm of dynamic bandwidth allocation for multimedia services over Ethernet PONs. To implement the suggested dynamic bandwidth allocation algorithm, we present control message formats that handle classified bandwidths in a multi-point control protocol of Ethernet PONs.

• 제어로봇시스템학회논문지
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• 제5권4호
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• pp.403-410
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• 1999

In this study, a parallel algorithm has been developed that can quickly solve the optiaml control problem of large-scale dynamic systems. The algorithm adopts the sequential quadratic programming methods and achieves domain decomposition-type parallelism in computing sensitivities for search direction computation. A silicon wafer thermal process problem has been solved using the algorithm, and a parallel efficiency of 45% has been achieved with 16 processors. Practical methods have also been investigated in this study as a way to further speed up the computation time.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2008년도 추계학술대회 및 정기총회
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• pp.290-296
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• 2008

This paper considers a two-stage dynamic lot-sizing problem constrained by a supplier's production capacity. We derive an improved O($T^6$) algorithm over the O($T^7$) algorithm in van Hoesel et al. (2005).

• 한국음향학회지
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• 제3권1호
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• pp.25-35
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• 1984

This paper analysis the Dynamic Time Warping algorithms for time normalization of speech pattern and discusses the Dynamic Programming algorithm for spoken Korean isolated digits recognition. In the DP matching, feature vectors of the reference and test pattern are consisted of first three formant frequencies extracted by power spectrum density estimation algorithm of the ARMA model. The major differences in the various DTW algorithms include the global path constrains, the local continuity constraints on the path, and the distance weighting/normalization used to give the overall minimum distance. The performance criterias to evaluate these DP algorithms are memory requirement, speed of implementation, and recognition accuracy.

• 한국정보처리학회논문지
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• 제6권9호
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• pp.2384-2392
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• 1999

프로그램에서 요류가 발생되었을 때 프로그래머는 어떤 시험 사례(test case)를 통해 프로그램을 분석한다. 이처럼 현재 입력 값에 영향을 끼치는 모든 명령문들에 관련된 동적 슬라이싱(dynamic slicing)과 이를 구현하는 기술은 실제 테스팅 및 디버깅 분야에서 매우 중요하다고 할 것이다. 지금까지의 동적 슬라이싱은 슬라이싱 기준 변수가 1개 일 때의 경우에 대해서만 연구해 왔다. 그러나, 실제적인 테스팅 및 디버깅 분야에서는 슬라이싱 기준이 되는 변수가 2개 이상인 경우가 아주 많이 발생한다. 따라서 슬라이싱 기준 변수가 n 개 일 때 동적 프로그램 슬라이스(dynamic program slices)를 만드는 알고리즘을 제시하였고 프로그래밍 언어를 사용하여 동적 프로그램 슬라이싱 알고리즘을 프로그래밍한 뒤 예제 프로그램을 적용시켜 구현하였다. 구현 결과는 실행 이력에 대한 마킹 테이블(marking table)과 동적 종속 그래프로 나타내었다. 그리고, 본 논문에서 제시한 다중기준변수 동적 슬라이스 생성을 위한 마킹 알고리즘이 기존의 단일기준변수 기법보다 실제적인 테스팅 환경에서 더 우수함을 보였다.

• 전기전자학회논문지
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• 제11권4호
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• pp.219-226
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• 2007

본 논문은 HDR(High Dynamic Range) 영상을 기존의 JPEG 압축 방법을 이용하여 효율적으로 압축할 수 있는 방안을 제안한다. 입력 HDR 영상을 동적 영역 압축(Dynamic range compression)하여 통해 얻어지는 LDR(Low Dynamic Rage) 영상 및 HDR 영상과 LDR영상의 비율을 나타내는 비율 (Ratio) 영상으로 분리한다. LDR 영상은 하위 호환성을 유지하기 위해 기존의 JPEG 알고리듬을 이용하여 압축하며, 비율 영상은 각 블록별로 HVS(Human Visual System)이 인지하는 차이를 모델링 한 비용함수를 최소화 하도록 압축한다. 따라서 제안하는 알고리듬을 적용하면 동일한 조건에서 압축된 결과 영상에 왜곡이 적게 발생하게 되며, 컴퓨터 모의실험을 통해 그 유효성을 확인한다.

• 한국자기공명학회논문지
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• 제9권2호
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• pp.93-102
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• 2005

Purpose: To develop an advanced non-linear curve fitting (NLCF) algorithm for dynamic susceptibility contrast study of brain. Materials and Methods: The first pass effects give rise to spuriously high estimates of $K^{trans}$ in voxels with large vascular components. An explicit threshold value has been used to reject voxels. Results: By using this non-linear curve fitting algorithm, the blood perfusion and the volume estimation were accurately evaluated in T2*-weighted dynamic contrast enhanced (DCE)-MR images. From the recalculated each parameters, perfusion weighted image were outlined by using modified non-linear curve fitting algorithm. This results were improved estimation of T2*-weighted dynamic series. Conclusion: The present study demonstrated an improvement of an estimation of kinetic parameters from dynamic contrast-enhanced (DCE) T2*-weighted magnetic resonance imaging data, using contrast agents. The advanced kinetic models include the relation of volume transfer constant $K^{trans}\;(min^{-1})$ and the volume of extravascular extracellular space (EES) per unit volume of tissue $\nu_e$.

• Journal of the Korean Data and Information Science Society
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• 제19권2호
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• pp.645-655
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• 2008

As wireless connectivity is integrated into many handheld devices, streaming multimedia content among mobile ad-hoc peers is becoming a popular application. In this paper, we propose a dynamic service replication algorithm for providing guaranteed continuous streaming services to all nodes in mobile ad-hoc networks (MANETs). First, a MANET is comprised of logical grid hierarchy, and a streaming service is replicated to a lower server region of the logical grid hierarchy by considering the link availability between a mobile node and the streaming server within a server region or the popularity of the streaming service. We evaluate analytically the performance of the proposed algorithm, and compared with that of existing Qin's algorithm. Evaluation results show that our algorithm can achieve better streaming performance than Qin's algorithm. Therefore, the proposed algorithm not only improves the sharing availability of replicated streaming services but also controls efficiently the number of streaming service replications.

• 제어로봇시스템학회논문지
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• 제17권7호
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• pp.651-658
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• 2011

An efficient modified $D^*$ lite algorithm is suggested, which can perform online path planning for mobile robots in dynamic indoor environment. Online path planning should plan and execute alternately in a short time, and hence it enables the robot avoid unknown dynamic obstacles which suddenly appear on robot's path. Based on $D^*$ Lite algorithm, we improved representation of edge cost, heuristic function, and priority queue management, to build a modified $D^*$ Lite algorithm. Performance of the proposed algorithm is revealed via extensive simulation study.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.349-351
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• 2004

The classical dynamic backpropagation learning algorithm has the problems of learning speed and the determine of learning parameter. The Extend Kalman Filter(EKF) is used effectively for a state estimation method for a non linear dynamic system. This paper presents a learning algorithm using Dual Extended Kalman Filter(DEKF) for Fully Recurrent Neural Network(FRNN). This DEKF learning algorithm gives the minimum variance estimate of the weights and the hidden outputs. The proposed DEKF learning algorithm is applied to the system identification of a nonlinear SISO system and compared with dynamic backpropagation learning algorithm.