• Journal of applied mathematics & informatics
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• v.31 no.3_4
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• pp.479-490
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• 2013

In this paper, we investigate a priori error estimates and superconvergence of varitional discretization for nonlinear parabolic optimal control problems with control constraints. The time discretization is based on the backward Euler method. The state and the adjoint state are approximated by piecewise linear functions and the control is not directly discretized. We derive a priori error estimates for the control and superconvergence between the numerical solution and elliptic projection for the state and the adjoint state and present a numerical example for illustrating our theoretical results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.2
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• pp.135-144
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• 2009

In this present work, spline FEA for the trimmed NURBS surface of the 2D linear elasticity problem is presented. The main benefit of the proposed method is that no additional efforts for modeling of trimmed NURBS surfaces are needed and the information of the trimming curves and trimmed surfaces exported from the CAD system can be directly used for analysis. For this, trimmed elements are searched by using NURBS projection scheme. The integration of the trimmed elements is performed by using the NURBS-enhanced integration scheme. The formulation of constructing stiffness matrix of trimmed elements is presented. In this formulation, the information of the trimming curve is used for calculating the Jacobian as well as for obtaining integration points. The robustness and effectiveness of the proposed method are investigated through various numerical examples.

• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.113-123
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• 1996

Data-dependent (adaptive) choice of asymptotically efficient score functions for rank estimators and M-estimators of regression parameters in a linear regression model with left-truncated and right-censored data are developed herein. The locally adaptive smoothing techniques of Muller and Wang (1990) and Uzunogullari and Wang (1992) provide good estimates of the hazard function h and its derivative h' from left-truncated and right-censored data. However, since we need to estimate h'/h for the asymptotically optimal choice of score functions, the naive estimator, which is just a ratio of estimated h' and h, turns out to have a few drawbacks. An altermative method to overcome these shortcomings and also to speed up the algorithms is developed. In particular, we use a subroutine of the PPR (Projection Pursuit Regression) method coded by Friedman and Stuetzle (1981) to find the nonparametric derivative of log(h) for the problem of estimating h'/h.

• The Korean Journal of Applied Statistics
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• v.22 no.1
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• pp.205-220
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• 2009

For modeling skewed semicircular data, we derive new family of the exponential distributions. We extend it to the l-axial exponential distribution by a transformation for modeling any arc of arbitrary length. It is straightforward to generate samples from the f-axial exponential distribution. Asymptotic result reveals two things. The first is that linear exponential distribution can be used to approximate the l-axial exponential distribution. The second is that the l-axial exponential distribution has the asymptotic memoryless property though it doesn't have strict memoryless property. Some trigonometric moments are also derived in closed forms. Maximum likelihood estimation is adopted to estimate model parameters. Some hypotheses tests and confidence intervals are also developed. The Kolmogorov-Smirnov test is adopted for goodness of fit test of the l-axial exponential distribution. We finally obtain a bivariate version of two kinds of the l-axial exponential distributions.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1125-1145
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• 2010

For modeling(skewed) semicircular data, we derive a new exponential family of distributions. We extend it to the l-axial exponential family of distributions by a projection for modeling any arc of arbitrary length. It is straightforward to generate samples from the l-axial exponential family of distributions. Asymptotic result reveals that the linear exponential family of distributions can be used to approximate the l-axial exponential family of distributions. Some trigonometric moments are also derived in closed forms. The maximum likelihood estimation is adopted to estimate model parameters. Some hypotheses tests and confidence intervals are also developed. The Kolmogorov-Smirnov test is adopted for a goodness of t test of the l-axial exponential family of distributions. Samples of orientations are used to demonstrate the proposed model.

• Journal of Magnetics
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• v.17 no.4
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• pp.255-260
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• 2012

In this study, we determine that the electron paramagnetic resonance line-width (EPRLW) is axially symmetric about the c-axis and analyze the spin Hamiltonian with an isotopic g-factor of 1.9920 at a frequency of 9.5 GHz. It should be noted that the electron paramagnetic resonance signals are Lorentzian. Our findings show that the EPRLW decreases exponentially with an increase in the temperature; i.e., its temperature dependence in the range 300-400 K obeys Arrhenius behavior, this kind of temperature dependence indicates an off-center a motional narrowing of the spectrum when $Mn^{2+}$ impurity ions substitute for $Nb^{5+}$ ions. The specific heats follow a linear dependence suggesting a simple Debye $T^3$ behavior.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.959-960
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• 2008

Recently, biometric authentication mechanism has been used to provide high level of security in cryptographic systems. In this paper, we propose an efficient method of generating invariant iris key to be applied in cryptographic systems. In order to generate iris key and improve the performance at the stolen token scenario, multiple random projection technique was combined with multiple linear transformation methods. From the experimental results, we proved that invariant iris keys were generated and the proposed method was robust to stolen token scenario.

• Bulletin of the Korean Chemical Society
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• v.32 no.2
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• pp.439-443
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• 2011

Using the projection operator technique, a reduced density matrix theory for linear absorption spectrum of energy transfer systems is developed for the theoretical absorption line shape of the systems with non-Condon transitions. As an application, we considered a model system of OH vibrations of water. In the present model calculation, the OH vibration modes are coupled to each other via intra-molecular coupling mechanism while their intermolecular couplings are turned off. The time-correlation functions appearing in the formulation are calculated from a mixed quantum/classical mechanics method. The present theory is successful in reproducing the exact absorption line shape. Also the present theory was improved from an existing approximate theory, time-averaged approximation approach.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.2
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• pp.420-423
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• 2007

In this paper, an efficient nonlinear echo cancellation method is proposed, whereby the fast block exact Gauss-Seidel pseudo affine projection (FBEGS-PAP) is further utilized for adaptive Volterra filtering. In particular, the proposed nonlinear echo cancellation approach requires lower computational complexity as in the conventional linear adaptive echo cancellation methods based on NLMS and GS-PAP, and still provides nonlinear echo cancellation performance similar to the GS-PAP method. Finally, echo cancellation performance of the proposed approach is demonstrated by providing some simulation results.

• Journal of Multimedia Information System
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• v.4 no.2
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• pp.79-82
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• 2017

Smoke and fire have different shapes and colours. This article suggests a fully connected system which is used two features using Adaboost algorithm for constructing a strong classifier as linear combination. We calculate the local histogram feature by gradient and bin, local binary pattern value, and projection vectors for each cell. According to the histogram magnitude, this paper applied adapted weighting value to improve the recognition rate. To preserve the local region and shape feature which has edge intensity, this paper processed the normalization sequence. For the extracted features, this paper Adaboost algorithm which makes strong classification to classify the objects. Our smoke detection system based on the proposed approach leads to higher detection accuracy than other system.