• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.4
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• pp.11-20
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• 1998

Fault simulatior has been used to compute exact fault coverages of test vectors for digial circuits. But it is time consuming because execution time is proportional to square of circuit size. Recently, several algorithms for testability analysis have been published to cope with these problems. COP is very fast and accurate but cannot be used for sequential circuits, while STAFAN can be used for sequential circuits but needs vast amount of execution time due to good circuit simulation. We proposed EXTASEC which gave fast and accurate fault coverage. But it shows noticeable errors for a few sequential circuits. In this paper, it is shown that the inaccuracy is due to uninitializble flipflops, and we propose ITEM to improve the EXTASEC algorithm. ITEM is an improved evaluation method of fault coverage by analysis of backward lines and uninitializable flipflops. It is expected to perform efficiently for very large circuits where execution time is critical.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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• pp.73-81
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• 1996

In this paper, based on the constrained optimizatin technique and direct recovery method, we proesent a shape form shading (SFS) algorithm to recover a 3-D shape form an image. More specifically, we first employ the membrane model for a smoothness constraint to revoer a 3-D shape coarsely. We then compute the surface height directly to reduce the shape distortion due to a regularization term. In our approach, we can obtain a stable and accurate solution by the application of these two steps. Several simulation results on various images are provided and discussed in this paper and they show that the proposed algorithm extracts the 3-D information accurately and efficiently.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.201-207
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• 2002

In this paper, Jeffrey's and reference priors are derived when the parameter of interest is the ratio of means of two in dependent Poisson distribution. To achieve the parameter orthogonality in the sense of Cox and Reid (1987), non-trivial orthogonal transformation is provided. The orthogonal transformation makes to find noninformative priors easy. Our simulation study indicates that the reference prior meet very well the target coverage probabilities in a frequentist sense. Using the real data, we compute Bayes estimator and MLE for the ratio of means based on the reference prior.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2009.05a
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• pp.196-199
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• 2009

높아지는 Graphic Processing Unit (GPU)의 연산 성능과 GPU에서의 범용 프로그래밍을 위한 개발 환경의 개발, 보급으로 인해 GPU를 일반연산에 활용하는 연구가 활발히 진행되고 있다. 이와같이 일반 연산에 활용되고 있는 GPU로 nVidia Tesla와 AMD/ATI의 FireStream 들이 있다. 특수목적 연산 장치인 GPU를 일반 연산을 위해 프로그래밍하기 위해서는 그에 맞는 프로그램 개발 환경이 필요한데 nVidia에서 개발한 CUDA (Compute Unified Device Architecture) 환경은 자사의 GPU 프로그램 개발을 위해 제공되는 개발 환경이다. CUDA 개발 환경은 nVidia GPU 프로그래밍 뿐만 아니라 차세대 이종 병렬 프로그램 개발 환경의 공개 표준으로 논의되고 있는 OpenCL (Open Computing Language) 와 유사한 특징을 보일 것으로 예상되기 때문에 그 중요성은 특정 GPU 에만 국한되지 않는다. 본 논문에서는 경로 적분 몬테 카를로 (Path Integral Monte Carlo) 방법을 CUDA 개발 환경을 사용하여 nVidia GPU 상에서 병렬화한 결과를 제시하였다.

• International Journal of Automotive Technology
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• v.7 no.7
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• pp.803-812
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• 2006

In order to reduce the negative effects of dynamic coupling among vehicle subsystems and improve the handling performance of vehicle under severe driving conditions, a vehicle chassis control integration approach based on a main-loop and servo-loop structure is proposed. In the main-loop, in order to achieve satisfactory longitudinal, lateral and yaw response, a sliding mode controller is used to calculate the desired longitudinal, lateral forces and yaw moment of the vehicle; and in the servo-loop, a nonlinear optimizing method is adopted to compute the optimal control inputs, i.e. wheel control torques and active steering angles, and thus distributes the forces and moment to four tire/road contact patches. Simulation results indicate that significant improvement in vehicle handling and stability can be expected from the proposed chassis control integration.

• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.729-742
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• 2005

In this paper, we discuss the propriety of the various noninformative priors for the Pareto distribution. The reference prior, Jeffreys prior and ad hoc noninformative prior which is used in several literatures will be introduced and showed that which prior gives the proper posterior distribution. The reference prior and Jeffreys prior give a proper posterior distribution, but ad hoc noninformative prior which is proportional to reciprocal of the parameters does not give a proper posterior. To compute survival function, we use the well-known approximation method proposed by Lindley (1980) and Tireney and Kadane (1986). And two methods are compared by simulation. A real data example is given to illustrate our methodology.

• Korean Journal of Remote Sensing
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• v.27 no.6
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• pp.717-728
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• 2011

An efficient method for the unsupervised classification of high resolution imagery is suggested in this paper. It employs pixel-linking and merging based on the adjacency graph. The proposed algorithm uses the neighbor lines of 8 directions to include information in spatial proximity. Two approaches are suggested to employ neighbor lines in the linking. One is to compute the dissimilarity measure for the pixel-linking using information from the best lines with the smallest non. The other is to select the best directions for the dissimilarity measure by comparing the non-homogeneity of each line in the same direction of two adjacent pixels. The resultant partition of pixel-linking is segmented and classified by the merging based on the regional and spectral adjacency graphs. This study performed extensive experiments using simulation data and a real high resolution data of IKONOS. The experimental results show that the new approach proposed in this study is quite effective to provide segments of high quality for object-based analysis and proper land-cover map for high resolution imagery of urban area.

• Communications for Statistical Applications and Methods
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• v.21 no.3
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• pp.213-224
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• 2014

In this paper, we study the problem of transforming to normality. We propose to estimate the transformation parameter by minimizing a weighted squared distance between the empirical characteristic function of transformed data and the characteristic function of the normal distribution. Our approach also allows for other symmetric target characteristic functions. Asymptotics are established for a random sample selected from an unknown distribution. The proofs show that the weight function $t^{-2}$ needs to be modified to have thinner tails. We also propose the method to compute the influence function for M-equation taking the form of U-statistics. The influence function calculations and a small Monte Carlo simulation show that our estimates are less sensitive to a few outliers than the maximum likelihood estimates.

• Journal of the Korean Statistical Society
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• v.33 no.2
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• pp.203-218
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• 2004

In this paper, we develop the matching priors and the reference priors for linear combination of the means under the normal populations with equal variances. We prove that the matching priors are actually the second order matching priors and reveal that the second order matching priors match alternative coverage probabilities up to the second order (Mukerjee and Reid, 1999) and also, are HPD matching priors. It turns out that among all of the reference priors, one-at-a-time reference prior satisfies a second order matching criterion. Our simulation study indicates that one-at-a-time reference prior performs better than the other reference priors in terms of matching the target coverage probabilities in a frequentist sense. We compute Bayesian credible intervals for linear combination of the means based on the reference priors.

• Communications for Statistical Applications and Methods
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• v.22 no.3
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• pp.277-283
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• 2015

Pickands constant $H_{\alpha}$ appears in the classical result about tail probabilities of the extremes of Gaussian processes and there exist several different representations of Pickands constant. However, the exact value of $H_{\alpha}$ is unknown except for two special Gaussian processes. Significant effort has been made to find numerical approximations of $H_{\alpha}$. In this paper, we attempt to compute numerically $H_{\alpha}$ based on its representation derived by $H{\ddot{u}}sler$ (1999) and Albin and Choi (2010). Our estimates are compared with the often quoted conjecture $H_{\alpha}=1/{\Gamma}(1/{\alpha})$ for 0 < ${\alpha}$ ${\leq}$ 2. This conjecture does not seem compatible with our simulation result for 1 < ${\alpha}$ < 2, which is also recently observed by Dieker and Yakir (2014) who devised a reliable algorithm to estimate these constants along with a detailed error analysis.