• Journal of the Korea Society of Computer and Information
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• v.4 no.4
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• pp.101-112
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• 1999

In this paper variable bit rate VBR Moving Picture Experts Group (MPEG) coded full-motion video traffic is modeled by a nonlinear time-series process. The threshold autoregressive (TAR) process is of particular interest. The TAR model is comprised of a set of autoregressive (AR) processes that are switched between amplitude sub-regions. To model the dynamics of the switching between the sub-regions a selection of amplitude dependent thresholds and a delay value is required. To this end, an efficient and accurate TAR model construction algorithm is developed to model VBR MPEG-coded video traffic. The TAR model is shown to accurately represent statistical characteristics of the actual full-motion video trace. Furthermore. in simulations for the bit-loss rate actual and TAR traces show good agreement.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.5C
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• pp.398-405
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• 2005

The multiuser detection (MUD) based wireless receiver requires more accurate channel estimation than the single user detection (SUD) schemes such as Rake receiver, and hence the post processing is required for MUD to clean up the estimated channel coefficients by eliminating the noise only coefficients. The adaptive post processing method is proposed in order to provide more accurate channel responses and the power level of the background noise and interferences at the cost of the negligible processing delay compared to the conventional method based on the threshold test with the threshold value relative to the noise variance. The simulations are performed in 3GPP-TDD mode environment. The results show that the noise estimation error of the proposed method is maximum $10\%$, which is much smaller than $50\%$ maximum error of the conventional method.

• The Transactions of the Korea Information Processing Society
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• v.6 no.2
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• pp.282-291
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• 1999

In order to construct the News Video Database System, cut detection technique is very important. In general, the color histogram, $\chi$2 histogram or Bin-to-Bin difference(B2B) techniques are mainly using for the scene partitioning. In this paper, we propose the efficient algorithm that is applied the weight in terms of NTSC standard to cut detection. This algorithm is able to reduce the time of acquiring and comparing histogram using by separate calculation of R, G, and B for the color histogram technique. And it also provide the efficient selection method fo threshold value by and use the news videos of KBS, MBC, SBS, CNN and NHK as experimental domains. By the result of experiment, we present the proposed algorithm is more efficient for cut detection than the previous methods, and that the basis for the automatic selection of threshold values.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3A
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• pp.272-280
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• 2009

Measurement of the background radio noise is very important process being used in survey of radio noise environment, calculating the threshold level for the frequency occupancy measurement and so forth. First step of background radio noise measurement is to select the sample sub-band which is mostly dominated by the background white Gaussian noise (WGN) within the target band. The second step is to carry out the main measurement of radio noise on this selected sample sub-band for the representative value of the noise power. In this paper, a method for selection of sample sub-band for the effective background radio noise measurement using SVD is proposed under the assumption that background radio noise is WGN. The performance of the proposed method is compared with that of the APD method which is widely used for the same purpose. Simulation results are shown to demonstrate the high performance of the proposed method in comparison with the existing APD method.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.430-432
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• 2008

Visible channel calibration method using deep convective clouds (DCCs) is developed. The method has advantages that visible radiance is not sensitive to cloud optical thickness (COT) for deep convective clouds because visible radiance no longer increases when COT exceeds 100. Therefore, once DCCs are chosen appropriately, and then cloud optical properties can be assumed without operational ancillary data for the specification of cloud conditions in radiative transfer model. In this study, it is investigated whether IR measurements can be used for the selection of DCC targets. To construct appropriate threshold value for the selection of DCCs, the statistics of cloud optical properties are collected with MODIS measurements. When MODIS brightness temperature (TB) at 11 ${\mu}$ m is restricted to be less than 190 K, it is shown that more than 85% of selected pixels show COT ${\geq}$ 100. Moreover, effective radius ($r_e$) distribution shows a sharp peak around 20 ${\mu}m$. Based on those MODIS observations, cloud optical properties are assumed as COT = 200 and $r_e$ = 20 ${\mu}m$ for the simulation of MODIS visible (0.646 ${\mu}m$) band radiances over DCC targets.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.157-160
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• 1999

A prediction method of conditional event matching pre-diction (EMP) for a purpose of predicting nonlinear phenomena of insulator pollution was proposed in this paper. The EMP was used if the conditional probability for increase of insulator pollution exceeded a threshold value. A performance of the EMP was strongly related to selection of database of events and a closeness function. By use of the prediction of the insulator pollution based on the conditional EMP, reliable decision making for the washing timing of the polluted insulators was e-valuated based on actual data in Kasatsu substation, Japan.

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.65-85
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• 2024

The tail probability of a function of a multivariate random variable is not easy to estimate by the crude Monte Carlo simulation. When the occurrence of the function value over a threshold is rare, the accurate estimation of the corresponding probability requires a huge number of samples. When the explicit form of the cumulative distribution function of each component of the variable is known, the inverse transform likelihood ratio method is directly applicable scheme to estimate the tail probability efficiently. The method is a type of the importance sampling and its efficiency depends on the selection of the importance sampling distribution. When the cumulative distribution of the multivariate random variable is represented by a copula and its marginal distributions, we develop an iterative algorithm to find the optimal importance sampling distribution, and show the convergence of the algorithm. The performance of the proposed scheme is compared with the crude Monte Carlo simulation numerically.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.10
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• pp.591-597
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• 2003

In this paper, a best-basis selection algorithm that improves the performance of the coding gains and the computational complexity is proposed. The proposed algorithm limits the computational complexity according to the resolved threshold value and decomposes the parent subbands by using the top-down tree search and the relative energy between the parent subbands and the child subbands. For the experiments of the proposed algorithm, the bit-rates, the peak signal-to-noise ratio (PSNR), and the reconstructed images are presented by using the Quad-tree coder. The result of the proposed algorithm is compared to that of DWT algorithm using the Quad-tree coder for a set of standard test images. In addition, the result of the proposed algorithm is compared to that of JPEG-2000 algorithm and that of S+P algorithm.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.4
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• pp.571-579
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• 1990

A dynamic relocation algorithm for non-deterministic process graph in distributed computer systems is proposed. A method is represented for determining the optimal policy for processing a process tree. A general database query request is modelled by a process tree which represent a set of subprocesses together with their precedence relationship. The process allocation model is based on operating cost which is a function fo selection of site for processing operation, data reduction function and file size. By using expected values of parameters for non-deterministic process tree, the process graph and optimal policy that yield minimum operating cost are determined. As process is relocated according to threshold value and new information of parameters after the execution of low level process for non-deterministic process graph, the assigned state that approximate to optiaml solution is obtained. The proposed algorihtm is heuristic By performing algorithm for sample problems, it is shown that the proposed algorithm is good in obtaining optimal solution.

• The Korean Journal of Financial Management
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• v.22 no.1
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• pp.119-146
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• 2005

This study applies extreme value theory to get extreme value-VAR for Korean Stock market and showed the usefulness of the approach. Block maxima model and POT model were used as extreme value models and tested which model was more appropriate through back testing. It was shown that the block maxima model was unstable as the variation of the estimate was very large depending on the confidence level and the magnitude of the estimates depended largely on the block size. This shows that block maxima model was not appropriate for Korean Stock market. On the other hand POT model was relatively stable even though extreme value VAR depended on the selection of the critical value. Back test also showed VAR showed a better result than delta VAR above 97.5% confidence level. POT model performs better the higher the confidence level, which suggests that POT model is useful as a risk management tool especially for VAR estimates with a confidence level higher than 99%. This study picks up the right tail and left tail of the return distribution and estimates the EVT-VAR for each, which reflects the asymmetry of the return distribution of the Korean Stock market.