• Journal of the Korea Society for Simulation
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• v.33 no.1
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• pp.19-26
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• 2024

The phase-type, PH, distribution is defined as the time to absorption into a terminal state in a continuous-time Markov chain. As the PH distribution includes family of exponential distributions, it has been widely used in stochastic models. Since the PH distribution is represented and generated by an initial probability vector and a generator matrix which is called the Markovian representation, we need to find a vector and a matrix that are consistent with given set of moments if we want simulate a PH distribution. In this paper, we propose an approach to simulate a PH distribution based on distribution function which can be obtained directly from moments. For the simulation of PH distribution of order 2, closed-form formula and streamlined procedures are given based on the Jordan decomposition and the minimal Laplace transform which is computationally more efficient than the moment matching methods for the Markovian representation. Our approach can be used more effectively than the Markovian representation in generating higher order PH distribution in queueing network simulation.

• The Journal of the Acoustical Society of Korea
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• v.21 no.1
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• pp.62-68
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• 2002

It is well known that the MDVR beamforming outperforms the conventional delay-sum beamformer in the sense of noise rejection and bearing resolution. However, the MDVR method requires long observation time to achieve high frequency resolution. The STMV method uses the steered covariance matrix of sensor data, so it has an ability to form an adaptive weight vector from a single time-series snapshot. But it uses the same weight vector across all frequencies. In this paper, we propose an SSMV method. The basic idea of the SSMV method is to decompose a full frequency band into several subbands to acquire a weight vector for each subband, individually. Also the wrap may be divided into several subarrays in order to reduce a computational load and the bandwidth of each subband. Simulations using real sea trial data show that the proposed SSMV method has good performance with short observation time.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.490-496
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• 2020

We present a method to improve the performance of the multi-channel Wiener filter in noisy environment. To build subspace-based multi-channel Wiener filter, in the case of single target source, the target speech component can be effectively estimated in the principal subspace of speech correlation matrix. The speech correlation matrix can be estimated by subtracting noise correlation matrix from signal correlation matrix based on the assumption that the cross-correlation between speech and interfering noise is negligible compared with speech correlation. However, this assumption is not valid in the presence of strong interfering noise and significant error can be induced in the principal subspace accordingly. In this paper, we propose to adjust the principal subspace vector using speech presence probability and the steering vector for the desired speech source. The multi-channel speech presence probability is derived in the principal subspace and applied to adjust the principal subspace vector. Simulation results show that the proposed method improves the performance of multi-channel Wiener filter in noisy environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.53-76
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• 2020

The synchronous phasor measurement algorithm is the core content of the phasor measurement unit. This manuscript proposes a dynamic synchronous phasor measurement algorithm based on compressed sensing theory. First, a dynamic signal model based on the Taylor series was established. The dynamic power signal was preprocessed using a least mean square error adaptive filter to eliminate interference from noise and harmonic components. A Chirplet overcomplete dictionary was then designed to realize a sparse representation. A reduction of the signal dimension was next achieved using a Gaussian observation matrix. Finally, the improved orthogonal matching pursuit algorithm was used to realize the sparse decomposition of the signal to be detected, the amplitude and phase of the original power signal were estimated according to the best matching atomic parameters, and the total vector error index was used for an error evaluation. Chroma 61511 was used for the output of various signals, the simulation results of which show that the proposed algorithm cannot only effectively filter out interference signals, it also achieves a better dynamic response performance and stability compared with a traditional DFT algorithm and the improved DFT synchronous phasor measurement algorithm, and the phasor measurement accuracy of the signal is greatly improved. In practical applications, the hardware costs of the system can be further reduced.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.5
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• pp.899-909
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• 1992

An iterative solution technique is presented to analyze the dynamic systems of rigid bodies subjected to kinematic constraints. Lagrange multipliers associated with the constraints are iteratively computed by monotonically reducing an appropriately defined constraint error vector, and the resulting equation of motion is solved by a well-established ODE technique. Constraints on the velocity and acceleration as well as the position are made to be satisfied at joints at each time step. Time integration is efficiently performed because decomposition or orthonormalization of the large matrix is not required at all. An acceleration technique is suggested for the faster convergence of the iterative scheme.

• The Journal of Asian Finance, Economics and Business
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• v.4 no.4
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• pp.61-66
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• 2017

Environmental awareness and its relation to the development of economy has garnered increased attention in recent years. Researchers, over the years, have argued that sustainable development warrants for minimizing environmental degradation since one depends on the other. This study analyzes the relationship between environmental degradation (carbon emission taken as proxy for degradation), economic growth, total energy consumption and industrial production index growth in Bangladesh from year 1998 to 2013. This study uses Vector Autoregression (VAR) Model and variance decomposition of VAR to analyze the effect of these variables on carbon emission and vice-versa. The findings of VAR model suggest that industrial production and GDP per capita has significant relationship with carbon emission. Further analysis through variance decomposition shows carbon emission has consistent impact on industrial production over time, whereas, industrial production has high impact on emission in the short run which fades in the long run which is consistent with Environmental Kuznets Curve (EKC) hypothesis. Carbon emission rising along with GDP per capita and at the same time having low impact in the long run on industrial index indicates there may be other sources of pollution introduced with the rise in income of the economy over time.

• Journal of Korea Water Resources Association
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• v.30 no.1
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• pp.63-73
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• 1997

Finite element model is established for the simulation of groundwater flow due to water curtain around underground oil storage Choleski decomposition method. The symmetric global conductance matrix is solved by vector storage Choleski decomposition method. The model is verified through comparison with the results of electric analogy. For the application of this model to real site, the finite element meshes are constructed according to representative vertical cross and longitudinal sections. In cross-sectional analysis, potential and flow distributions are compared based on the cavern pressure and horizontal water curtain. For longitudinal section, effects between nearly located caverns with or without vertical water curtain are analyzed. These results prove that the established model can be used as a tool for flow analysis around underground caverns.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.3
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• pp.539-557
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• 2013

A novel multifocus image fusion algorithm based on NSCT is proposed in this paper. In order to not only attain the image focusing properties and more visual information in the fused image, but also sensitive to the human visual perception, a local multidirection variance (LEOV) fusion rule is proposed for lowpass subband coefficient. In order to introduce more visual saliency, a modified local contrast is defined. In addition, according to the feature of distribution of highpass subband coefficients, a direction vector is proposed to constrain the modified local contrast and construct the new fusion rule for highpass subband coefficients selection The NSCT is a flexible multiscale, multidirection, and shift-invariant tool for image decomposition, which can be implemented via the atrous algorithm. The proposed fusion algorithm based on NSCT not only can prevent artifacts and erroneous from introducing into the fused image, but also can eliminate 'block effect' and 'frequency aliasing' phenomenon. Experimental results show that the proposed method achieved better fusion results than wavelet-based and CT-based fusion method in contrast and clarity.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.149-156
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• 2016

We proposed a blind watermarking scheme using singular vectors based on Discrete Wavelet Transform (DWT) and Redundant Discrete Wavelet Transform (RDWT) combined with Singular Value Decomposition (SVD) for copyright protection application. We replaced the 1st left and right singular vectors decomposed from cover image with the corresponding ones from watermark image to overcome the false-positive problem in current watermark systems using SVD. The proposed scheme realized the watermarking system without a false positive problem, and shows high fidelity and robustness.

• The Journal of Industrial Distribution & Business
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• v.8 no.1
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• pp.5-13
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• 2017

Purpose - In this article, a dynamic model like a VAR is an appropriate choice for estimating the possible interrelationship between ownership structure and firm performance as a dynamic process. Research design, data, and methodology - Data of this work are collected from Chinese stock exchange including 350 Chinese-listed firms during the period of 1999-2012. We hypothesize that this interrelationship dynamically exists between ownership structure and firm performance. To examine the correlation, a panel Vector Auto-regression (PVAR) approach generated by GMM method is utilized to test the possible dynamic relation embedded in corporate governance. Another two dynamic analysis solutions such as orthogonalized impulse-response function and variance decomposition are also used simultaneously. Results - Findings of this study indicate the evidence that dynamically endogenous relationship exists between ownership structure and firm performance. Further, there is a dynamical correlation between investment and performance. Impulse response and variance decomposition illustrate that impact of a shock to variables themselves is the main source for their variability. Conclusions - The conclusion in this study is that there is a bidirectional and inter-temporal effect between proportion of ownership and corporate performance for a long run in accordance with impulse response function. Overall, our results suggest that corporate governance in China is more market oriented.