• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.495-500
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• 2012

We consider a Bayesian test of independence in a two-way contingency table that has some zero cells. To do this, we take a three-stage hierarchical Bayesian model under each hypothesis. For prior, we use Dirichlet density to model the marginal cell and each cell probabilities. Our method does not require complicated computation such as a Metropolis-Hastings algorithm to draw samples from each posterior density of parameters. We draw samples using a Gibbs sampler with a grid method. For complicated posterior formulas, we apply the Monte-Carlo integration and the sampling important resampling algorithm. We compare the values of the Bayes factor with the results of a chi-square test and the likelihood ratio test.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.159-162
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• 2000

In this paper, we propose an efficient method to detect shot changes in compressed MPEG video data by using reference features among video frames. The reference features among video frames imply the similarities among adjacent frames by prediction coded type of each frame. A shot change is detected if the similarity degrees of a frame and its adjacent frames are low. And the shot change detection algorithm is improved by using Fuzzy c-means (FCM) clustering algorithm. The FCM clustering algorithm uses the shot change probabilities evaluated in the mask matching of reference ratios and difference measure values based on frame reference ratios.

• Journal of Communications and Networks
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• v.16 no.1
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• pp.56-66
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• 2014

We propose a novel opportunistic access scheme for cognitive radios in an interweave cognitive system, that considers the channel gain as well as the predicted idle channel probability (primary user occupancy: Busy/idle). In contrast to previous work where a cognitive user vacates a channel only when that channel becomes busy, the proposed scheme requires the cognitive user to switch to the channel with the next highest idle probability if the current channel's gain is below a certain threshold. We derive the threshold values that maximize the long term throughput for various primary user transition probabilities and cognitive user's relative movement.

• International Journal of Contents
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• v.4 no.3
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• pp.20-28
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• 2008

To obtain realistic performance measures for wireless networks, one should consider changes in performance due to failure related behavior. In performability analysis, simultaneous consideration is given to both pure performance and performance with failure measures. SRN is an extension of stochastic Petri nets and provides compact modeling facilities for system analysis. In this paper, a new methodology to model and analyze performability based on stochastic reward nets (SRN) is presented. Composite performance and availability SRN models for wireless handoff schemes are developed and then these models are decomposed hierarchically. The SRN models can yield measures of interest such as blocking and dropping probabilities. These measures are expressed in terms of the expected values of reward rate functions for SRNs. Numerical results show the accuracy of the hierarchical model. The key contribution of this paper constitutes the Petri nets modeling techniques instead of complicate numerical analysis of Markov chains and easy way of performance analysis for channel allocation under SRN reward concepts.

• ETRI Journal
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• v.30 no.3
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• pp.492-494
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• 2008

While the retrial phenomenon plays an important role in communication networks and should not be ignored, retrial systems do not present an exact analytic solution, so approximate techniques are required. To the best of our knowledge, all the existing techniques are based on computing the steady states probabilities. We propose another approach based on the relative state values which appear in the Howard equations. The results of the numerical evaluation carried out show that this solution outperforms previous approaches in terms of both accuracy and computation time.

• MALSORI
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• no.64
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• pp.121-135
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• 2007

Speech signal is distorted by channel characteristics or additive noise and then the performances of speaker or speech recognition are severely degraded. To cope with the noise problem, we propose a modified HMM decoder algorithm using SNR-based observation confidence, which was successfully applied for GMM in speaker identification task. The modification is done by weighting observation probabilities with reliability values obtained from SNR. Also, we apply PSO (particle swarm optimization) method to the confidence function for maximizing the speaker identification performance. To evaluate our proposed method, we used the ETRI database for speaker recognition. The experimental results showed that the performance was definitely enhanced with the modified HMM decoder algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.12 s.177
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• pp.61-69
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• 2005

This paper presents an efficient method of extracting line segments from the occupancy grids in a grid map. The grid map is composed of 2-D grids that have both the occupancy and orientation probabilities using sonar sensors. We evaluate the orientation information of every grid when the occupancy probability of the grid is updated from sonar range data. To find the shape of an object in the map from orientation information, the orientations are clustered into several groups according to their values. The line segments are, then, extracted from the clusters based on Hough transform. Finally, a feature-based map is built with these line segments. The proposed method is illustrated with the results produced by sets of experiments in an indoor environment.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.552-557
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• 1998

Sampling schemes are intended for use in situations where stream-flow data are collected regularly, but concentration data are collected during only a limited number of time periods. Estimating water pollutant loading considering sampling intervals is presented, and for illustrative purposes the criterion is applied to the sampling station HS#3 of the Balan-reservoir watershed which is located at the southwest of Suwon. The stratification is employed uniformly for all sampling strategies in that the strata boundaries are defined using the actual distribution of flow values and the selected nonexceedence probabilities to minimize inaccuracy. Ratio estimator for SS, T-N, and T-P were used in order to calculate the water pollutant loading. A sampling scheme incorporating stratified sampling with real-time of the sampling characteristics is found to give the appropriate estimate of the mass load.

• The Transactions of the Korea Information Processing Society
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• v.4 no.1
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• pp.177-183
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• 1997

The cumulative function of the noncentral t distribution calculate power in testing equality of means of two normal populations and confidence intervals for the ratio of population mean to standard deviation. In this paper, the evaluation of the cumulative function of noncentral t distribution is applied to the neural network consists of the multi-layer perception structure and learning process has the algorithm of the backpropagation. Numerical comparisons are made between the Fisher's values and the results obtained by neural network theory.

• Journal of Korean Society for Quality Management
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• v.16 no.2
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• pp.82-91
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• 1988

This study is concerned with the development of the economic sampling inspection plan when it is possible to carry out a nondestructive screening inspection for the rejected lots by substitutive characteristics closely related to the original quality characteristic. It is assumed that the probabilities of those errors depend linearly on the fraction defective of the process. The inspection policies considered are as follows: take a random sample of size n from the lot of size N and perform a destructive test on the sample. If the number of the defective items is not greater than a critical number C, accept the lot. Expected cost functions are obtained when the process average can be considered to follow a beta distribution and the way of finding the optimal values of (n, c) is to be explored.