• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.5
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• pp.18-24
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• 2003

The design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative sybcycles. Previous researches predifined the numbers of design processes in groups, but these group sizes should be determined optimally to balance the computing time of each groups. This paper proposes adaptive decomposition method, which determines the group sizes and the order of processes simultaneously to raise design efficiency by expanding the chromosome of the genetic algorithm. Finally, two sample cases are presented to show the effects of optimizing the sequence of processes with the adaptive decomposition method.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11a
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• pp.104-107
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• 2003

본 논문에서는 웨이브릿 영역에서 HVS 및 NVF 함수를 사용하여 영상특성에 기반한 통계적 판정법을 이용한 적응 워터마크 검출 알고리즘을 판정법을 제안한다. 워터마크는 4레벨로 분해된 웨이브릿 영역에서 JND(just noticeable difference) 특성과 NVF(noise visibility function)를 이용한 통계적 특성을 기반으로 정상상태 가우시안 모델에 따라 지각적 동조 특성을 이용하여 적응적으로 삽입하고, Bayes 이론 및 Neyman-Pearson 정리를 이용한 통계적 판정법을 이용하여 워터마크를 추출함으로써 기존의 통계적 판정법 보다 정확하게 워터마크 존재 유무를 판정 할 수 있음을 확인하였다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.12 no.4
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• pp.681-690
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• 1999

본 논문에서는 요소를 사용하지 않은 수치해석기법인 무요소법 중에서 다중해상도(multi-resolution)특성이 내재되어 있는 Reproducing Kernel Particle Method (RKPM)의 이중스케일 분해기법을 사용하여 RKPM의 형상함수를 상단성분과 하단성분으로 분리하고 이를 3차원 선형탄성해석과정에 적용하여 von Mises 응력장의 상·하단성분을 유도하였다. 유도된 응력장의 상단성분을 이용하여 후처리과정을 거치지 않고도 응력의 고변화도 부위를 손쉽게 파악할 수 있는 기법을 개발하였으며 이를 이용한 효율적인 적응적 세분화기법의 적용가능성을 연구하였다. 대표적인 2차원 및 3차원 응력집중 문제에 적용하여 응력집중부위를 파악하고 간단한 적응적 세분화과정에 따른 절점추가를 통하여 해의 정도 향상을 파악해 본 결과, 본 연구에서 개발된 기법이 응력집중부위를 정확히 판정할 수 있었으며 효율적인 적응적 세분화기법의 유용한 도구로서 활용될 수 있음을 검증하였다.

• Computational Structural Engineering
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• v.1 no.2
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• pp.121-130
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• 1988

Adaptive reinements yield a large sparse system of equations. In order to solve such a system, the core storage requirement is an important consideration. Accordingly, an iterative method which minimizes the core storage and provides a high rate of convergence is called for. In this paper the conjugate gradient algorithms with various preconditionings including the incomplete Cholesky decomposition are examined.

• The Korean Journal of Applied Statistics
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• v.19 no.2
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• pp.319-330
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• 2006

A signal in real world usually composes of multiple signals having different scales of frequencies. For example sun-spot data is fluctuated over 11 year and 85 year. Economic data is supposed to be compound of seasonal component, cyclic component and long-term trend. Decomposition of the signal is one of the main topics in time series analysis. However when the signal is subject to nonstationarity, traditional time series analysis such as spectral analysis is not suitable. Huang et. at(1998) proposed data-adaptive method called empirical mode decomposition (EMD) . Due to its robustness to nonstationarity, EMD has been applied to various fields. Huang et. at, however, have not considered denoising when data is contaminated by error. In this paper we propose efficient denoising method utilizing cross-validation.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.10
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• pp.32-43
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• 1994

This paper presents new QRD-based recursive least squares algorithms for bilinear lattice filter. Bilinear recursive least square lattice algorithms are derived by using the QR decomposition for minimization covariance matrix of predication error by applying Givens rotation to the bilinear recursive least squares lattics algorithms. The proposed algorithms are applied to the bilinear system identification to evaluate the performance of algoithms. Computer simulations show that the convergence properties of the proposed algorithms are superior to that of the algorithms proposed by Baik when signal includes the measurement noise.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.482-487
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• 2008

In case of flooding, the underwater flight vehicle (UFV) executes the blowing by blowing ballast tanks off using high pressure air (HPA), while it also uses control planes and a propulsion unit to reduce the overshoot depth caused by a flooding and blowing sequence. However, the conventional whole HPA blow-off method lets the body on the surface after blowing despite slight flooding. This results in the unnecessary mission failure or body exposure. Therefore, it is necessary to keep the body at the near surface by the blowing control while reducing the overshoot depth. To solve this problem, an adaptive blowing control algorithm, which is based on the decomposition method expanding the expert knowledge in depth control and the adaptive method using fuzzy basis function expansion (FBFE), is proposed. To verify the performance of the proposed algorithm, the blowing control of UFV is performed. Simulation results show that the proposed algorithm effectively solves the problems in the UFV blowing control system online.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.6C
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• pp.589-602
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• 2006

잡음은 음성과 관련된 시스템의 성능을 제한하는 주된 원인이기 때문에 음성향상과 관련된 연구는 꾸준히 계속되어왔다. 전통적인 음성향상 방법은 무성음과 잡음을 구분하지 알기 때문에 잡음제거 과정에서 무성음이 함께 제거되는 단점이 있으며, 웨이블릿 기반의 전통적인 잡음제거 방법은 각 대역마다 동일한 문턱값을 사용하기 때문에 시변 환경에서 성능이 떨어지는 단점이 있다. 이 단점들을 개선하기위해 다중대역 파워 차감법과 Perceptual 웨이블릿 패킷 분해를 이용한 웨이블릿 기반의 개선된 음성향상 방법을 제안한다. 전처리 과정으로 다중대역 파워 차감법을 사용하여 광대역 잡음을 제거하고 뮤지컬 잡음의 발생을 줄이며, psycho-acoustic 모델 기반 Perceptual 웨이블릿 패킷으로 신호를 분해한 후 각 웨이블릿 노드의 엔트로피 비율과 음성검출을 이용하여 무성음/유성음/잡음을 구분한다. 구분된 신호에 따라 각 웨이블릿 노드마다의 문턱값을 기준으로 웨이블릿 Shrinkage를 적용하여 잡음을 제거하고 무성음이나 파워가 작은 유성음이 제거되는 오류를 최소화한다. 또한 잡음 파워 추정 과정에 적응적으로 망각 계수를 선택하여 잡음 파워 추정 오류를 최소화한다.

• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.335-347
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• 2013

There are various types of real world signals. For example, an electrocardiogram(ECG) represents myocardium activities (contraction and relaxation) according to the beating of the heart. ECG can be expressed as the fluctuation of ampere ratings over time. A signal is a composite of various types of signals. An orchestra (which boasts a beautiful melody) consists of a variety of instruments with a unique frequency; subsequently, each sound is combined to form a perfect harmony. Various research on how to to decompose mixed stationary signals have been conducted. In the case of non-stationary signals, there is a limitation to use methodologies for stationary signals. Huang et al. (1998) proposed empirical mode decomposition(EMD) to deal with non-stationarity. EMD provides a data-driven approach to decompose a signal into intrinsic mode functions according to local oscillation through the identification of local extrema. However, due to the repeating process in the construction of envelopes, EMD algorithm is not efficient and not robust to a noise, and its computational complexity tends to increase as the size of a signal grows. In this research, we propose a new method to extract a local oscillation embedded in a signal by utilizing the second derivative.

• KSBB Journal
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• v.16 no.3
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• pp.281-285
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• 2001

Biofiltration of volatile organic compounds (VOCs) was performed for 80 days in a biofilter packed with peat. The empty bed residence time was 3.2 min. for a gas mixture of isoprene, dimethyl sulfide, chloroform. benzene, trichlorethylene, toluene, m0xylene, o-xylene and styrene. After 34 days of acclimatization the removal efficiency for a 83 g/㎥ gas input was 93% at $25^{circ}C$ and 73% at $45^{circ}C$, respectively. The maximum cell density at $25^{circ}C$ was 1.12$\times$10(sup)8 cells/g. Removal efficiencies of m-xylene and toluene (91%) were better than that of benzene (86%). The first quarter of the packed column removed 60% of the incoming VOCs.