• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.3
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• pp.210-216
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• 2006

In the rule based modeling, data partitioning plays crucial role be cause partitioned sub data set implies particular information of the given data set or system. In this paper, we present an empirical study result of the data pattern estimation to find underlying data patterns of the given data. Presented method performs crisp type clustering with given n number of data samples by means of the sequential agglomerative hierarchical nested model (SAHN). In each sequence, the average value of the sum of all inter-distance between centroid and data point. In the sequel, compute the derivation of the weighted average distance to observe a pattern distribution. For the final step, after overall clustering process is completed, weighted average distance value is applied to estimate range of the number of clusters in given dataset. The proposed estimation method and its result are considered with the use of FCM demo data set in MATLAB fuzzy logic toolbox and Box and Jenkins's gas furnace data.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.79-84
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• 2003

Likelihood estimation in random-effect models is often complicated because the marginal likelihood involves an analytically intractable integral. Numerical integration such as Gauss-Hermite quadrature is an option, but is generally not recommended when the dimensionality of the integral is high. An alternative is the use of hierarchical likelihood, which avoids such burdensome numerical integration. These two approaches for fitting binary data are compared and the advantages of using the hierarchical likelihood are discussed. Random-effect models for binary outcomes and for bivariate binary-continuous outcomes are considered.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.19-30
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• 2003

Spatiotemporal statistical models are used for analyzing space-time data in many fields, such as environmental sciences, meteorology, geology, epidemiology, forestry, hydrology, fishery, and so on. It is well known that classical spatiotemporal process modeling requires the estimation of space-time variogram or covariance functions. In practice, the estimation of such variogram or covariance functions are computationally difficult and highly sensitive to data structures. We investigate a Bayesian hierarchical model which allows the specification of a more realistic series of conditional distributions instead of computationally difficult and less realistic joint covariance functions. The spatiotemporal model investigated in this study allows both spatial component and autoregressive temporal component. These two features overcome the inability of pure time series models to adequately predict changes in trends in individual sites.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.1040-1057
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• 2014

In this paper, a new bit rate estimation scheme is proposed to determine the bit rate for each subclass in an MPEG-2 TS to H.264/AVC transcoder after dividing an input MPEG-2 TS sequence into several subclasses. Video format transcoding in conventional IPTV and Smart TV services is a time-consuming process since the input sequence should be fully transcoded several times with different bit-rates to decide the bit-rate suitable for a service. The proposed scheme can automatically decide the bit-rate for the transcoded video sequence in those services which can be stored on a video streaming server as small as possible without losing any subject quality loss. In the proposed scheme, an input sequence to the transcoder is sub-classified by hierarchical clustering using a parameter value extracted from each frame. The candidate frames of each subclass are used to estimate the bit rate using a statistical analysis and a mathematical model. Experimental results show that the proposed scheme reduces the bit rate by, on an average approximately 52% in low-complexity video and 6% in high-complexity video with negligible degradation in subjective quality.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06a
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• pp.49-56
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• 1999

In this paper, the general formula of disparity estimation based on Bayesian Maximum A Posteriori (MAP) algorithm is derived. The generalized formula is implemented with the plane configuration model and applied to multiple baselined stereograms. The probabilistic plane configuration model consists of independence and similarity among the neighboring disparities in the configuration. The independence probabilistic model reduces the computation and guarantees the discontinuity at the object boundary region. The similarity model preserves the continuity or the high correlation of disparity distribution. In addition, we propose a hierarchical scheme of disparity compensation in the application to multiple-view stereo images. According to the experiments, the derived formula and the proposed estimation algorithm outperformed other ones. The proposed probabilistic models are reasonable and approximate the pure joint probability distribution very well with decreasing the computations to O(n(D)) from O(n(D)4) of the generalized formula. And, the hierarchical scheme of disparity compensation with multiple-view stereos improves the performance without any additional overhead to the decoder.

• Journal of Theoretical and Applied Mechanics
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• v.3 no.1
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• pp.16-33
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• 2002

A concept of hierarchical modeling, the newest modeling technology. has been introduced early In 1990. This nu technology has a goat 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 which are 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 errors. 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 element residuals and 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. Comparing to the classical error estimators using 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.

• 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 Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.87-95
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• 2003

This paper proposes an object detection algorithm using the Multiresolution Motion Estimation(MRME) in wavelet d야main. A existing motion estimation method has characteristics of motion estimation but it requires having computation. Motion estimation in higher resolution used the motion vector of the lower resolution with the MRME that has parent-child relationship on wavelet coefficients. This method reduces the search area of motion estimation in higher resolution and computational complexity. The computational complexity of the proposed method is about 40% of the existing method using 3-level Set Partitioning in Hierarchical Trees(SPIHT) wavelet transform. The experimental results with the proposed method showed about 11% decrease of Mean Absolute Difference(MAD) and gains able to precise tracking of object.

• Journal of Broadcast Engineering
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• v.21 no.1
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• pp.24-35
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• 2016

By estimating environment light distribution, we can generate realistic shadow images in AR(augmented reality). When we estimate light distribution without sensing equipment, environment light model, geometry of virtual object, and surface reflection property are needed. Previous study using 3D marker builds surrounding light environment with a geodesic dome model and analyzes shadow images. Because this method employs candidate shadow maps in initial scene setup, however, it is difficult to estimate precise light information. This paper presents a novel light estimation method based on hierarchical light distribution model subdivision. By using an overlapping area ratio of the segmented shadow and candidate shadow map, we can make hierarchical subdivision of light geodesic dome.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2271-2280
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• 1999

In this paper, a variable motion estimation scheme based on HBMA(Hierarchical Block Matching Algorithm) to improve the performance and to reduce heavy computational and transmission load, is presented. The proposed algorithm is composed of four steps. First, block activity for each block is defined using the edge information of differential image between two sequential images, and then average block activity of the present image is found by taking the mean of block activity. Secondly, camera pan compensation is carried out, according to the average activity of the image, in the hierarchical pyramid structure constructed by wavelet transform. Next, the LUT classifying each block into one among Moving, No Moving, Semi-Moving Block according to the block activity compensated camera pan is obtained. Finally, as varying the block size and adaptively selecting the initial search layer and the search range referring to LUT, the proposed variable HBMA can effectively carries out fast motion estimation in the hierarchical pyramid structure. The cost function needed above-mentioned each step is only the block activity defined by the edge information of the differential image in the sequential images.