• Journal of the Korean Solar Energy Society
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• v.32 no.2
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• pp.74-86
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• 2012

For the improvement of environmental comfort in the buildings with the blind control, the objective of this study is to prevent the direct glare caused by the daylight inlet. During the process of solar profile prediction, time are significant factors that may cause error and glare during the blind control. This research proposes and evaluates the correction and control method to minimize prediction error. For the local areas with different longitude and local standard meridian, error occurred in the process of the time conversion from local standard time to apparent solar time. In order to correct error in time conversion, apparent solar time should be recalculated after adjusting the day of year and the equation of time. To solve the problems by the potential time errors, control method is suggested to divide the control sections using the calibrated fitting-curve and this method is verified through simulations. The proposed correction and control method, which considered potential time errors by loop lop leap years, could solve the problems about direct glare caused by daylight inlet on the work-plane according to the prediction errors of solar profile. And also these methods could maximize daylight inlet and solar heat gain, because the blocked area on windows could be minimized.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2565-2574
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• 2000

The error diffusion method is good for reproducing continuous image to binary image. However the reproduction of edge characteristic is weak in power spectrum analysis of display error. In this paper. we present an edge-enhanced error-diffusion method which include pre-processing algorithm for edge characteristic enhancement. Pre-processing algorithm consists of the difference value between current pixel and local average of original image and weighting function of pre-filter. First. it is obtained the difference value between current pixel and the local average of peripheral pixels(5x5) in original image. Second, weighting function of pre-filter is composed by function including absolute value and sign of difference value. The improved Error diffusion algorithm using pre-processing algorithm, present a good result visually which edge characteristic is enhanced. The performance of the proposed algorithm is compared with that of the conventional edge-enhanced error diffusion by measuring the RAPSD of display error, the egde correlation and the local average accordance.

• Structural Engineering and Mechanics
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• v.14 no.4
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• pp.381-400
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• 2002

This paper presents several applications of an improved estimator of the constitutive relation error (CRE) for plasticity problems. The cumulative aspect of the CRE estimator with respect to time is analyzed and we propose a first analysis of the local effectivity indexes of the CRE estimator in plasticity.

• Communications for Statistical Applications and Methods
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• v.4 no.1
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• pp.177-183
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• 1997

A data-adaptive order selection procedure is proposed for local polynomial nonparametric regression. For each given polynomial order, bias and variance are estimated and the adaptive polynomial order that has the smallest estimated mean squared error is selected locally at each location point. To estimate mean squared error, empirical bias estimate of Ruppert (1995) and local polynomial variance estimate of Ruppert, Wand, Wand, Holst and Hossjer (1995) are used. Since the proposed method does not require fitting polynomial model of order higher than the model order, it is simpler than the order selection method proposed by Fan and Gijbels (1995b).

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.4
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• pp.190-200
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• 1996

Step-by-step time integration methods are widely used for solving structural dynamics problem. One difficult yet critical choice an analyst must make is to decide an appropriate time step size. The choice of time step size has a significant effect on solution accuracy and computational expense. The objective of this research is to derive error estimate for newly developed time integration method and develop automatic time step size control algorithm for structural dynamics. A formula for computing error tolerance is derived based on desired period resolution. An automatic time step size control strategy is proposed based on a normalized local error estimate for the generalized-α method. Numerical examples demonstrate the developed strategy satisfies general design criteria for time step size control algorithm for dynamic problem.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.612-615
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• 2003

The error diffusion is a good method to reconstruct the continuous tones of an image to the bilevel tones However the reconstruction of edge characteristic by the nor diffusion is represented work when power spectrum is analyzed fer display error. In this paper, we present an edge enhanced error diffusion method to preprocess original image to achieve the enhancement for the edge characteristic. The preprocessing algorithm consist of two processes. First the difference value between the current pixel and the local average of the surrounding pixel in original image is obtained. Second, the weighting function is composed by the magnitude and the sign of the local average. To confirm the effect of the proposed method, it is compared with the conventional edge enhanced error diffusion methods by measuring the radially averaged power spectrum densities (RAPSDs) for their display errors. The comparison result demonstrate the superiority of the proposed method over the conventional ones.

• Journal of Korea Multimedia Society
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• v.6 no.4
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• pp.698-706
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• 2003

The primary goal of surface approximation is to reduce the degree of deviation of the simplified surface from the original surface. However it is difficult to define the metric that can measure the amount of deviation quantitatively. Many of the existing studies analogize it by using the change of the scalar quantity before and after simplification. This approach makes a lot of sense in the point that the local surfaces with small scalar are relatively less important since they make a low impact on the adjacent areas and thus can be removed from the current surface. However using scalar value alone there can exist many cases that cannot compute the degree of geometric importance of local surface. Especially the perceptual geometric features providing important clues to understand an object, in our observation, are generally constructed with small scalar value. This means that the distinguishing features can be removed in the earlier stage of the simplification process. In this paper, to resolve this problem, we present various factors and their combination as the metric for calculating the deviation error by introducing the orientation of local surfaces. Experimental results indicate that the surface orientation has an important influence on measuring deviation error and the proposed combined error metric works well retaining the relatively high curvature regions on the object's surface constructed with various and complex curvatures.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.3
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• pp.79-89
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• 1998

The Error Back-Propagation(EBP) algorithm is widely applied to train a multi-layer perceptron, which is a neural network model frequently used to solve complex problems such as pattern recognition, adaptive control, and global optimization. However, the EBP is basically a gradient descent method, which may get stuck in a local minimum, leading to failure in finding the globally optimal solution. Moreover, a multi-layer perceptron suffers from locking a systematic determination of the network structure appropriate for a given problem. It is usually the case to determine the number of hidden nodes by trial and error. In this paper, we propose a new algorithm to efficiently train a multi-layer perceptron. OUr algorithm uses stochastic perturbation in the weight space to effectively escape from local minima in multi-layer perceptron learning. Stochastic perturbation probabilistically re-initializes weights associated with hidden nodes to escape a local minimum if the probabilistically re-initializes weights associated with hidden nodes to escape a local minimum if the EGP learning gets stuck to it. Addition of new hidden nodes also can be viewed asa special case of stochastic perturbation. Using stochastic perturbation we can solve the local minima problem and the network structure design in a unified way. The results of our experiments with several benchmark test problems including theparity problem, the two-spirals problem, andthe credit-screening data show that our algorithm is very efficient.

• Structural Engineering and Mechanics
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• v.8 no.5
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• pp.513-529
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• 1999

A concept of hierarchical modeling, the newest modeling technology, has been introduced in early 1990's. This new technology has a great potential to advance the capabilities of current computational mechanics. A first step to implement this concept is to construct hierarchical models, a family of mathematical models sequentially connected by a key parameter of the problem under consideration and have different levels in modeling accuracy, and to investigate characteristics in their numerical simulation aspects. Among representative model problems to explore this concept are elastic structures such as beam-, arch-, plate- and shell-like structures because the mechanical behavior through the thickness can be approximated with sequential accuracy by varying the order of thickness polynomials in the displacement or stress fields. But, in the numerical, analysis of hierarchical models, two kinds of errors prevail, the modeling error and the numerical approximation error. To ensure numerical simulation quality, an accurate estimation of these two errors is definitely essential. Here, a local a posteriori error estimator for elastic structures with thin domain such as plate- and shell-like structures is derived using the element residuals and the flux balancing technique. This method guarantees upper bounds for the global error, and also provides accurate local error indicators for two types of errors, in the energy norm. Compared to the classical error estimators using the flux averaging technique, this shows considerably reliable and accurate effectivity indices. To illustrate the theoretical results and to verify the validity of the proposed error estimator, representative numerical examples are provided.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.5
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• pp.120-127
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• 1998

Differential inequalities occurring in problems of obstacle contact problems are recast into variational inequalities and analyzed by finite element methods. A new a posteriori error estimator, which is essential in adaptive finite element method, is introduced to capture the errors in finite element approximations of these variational inequalities. In order to construct a posteriori error estimates, saddle point problems are introduced using Lagrange parameters and upper bounds are provided. The global upper bound is localized by a special mixed formulation, which leads to upper bounds of the element errors. A numerical experiment is performed on an obstacle contact problem to check the effectivity index both in a local and a global sense.