• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.5
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• pp.95-102
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• 2008

This paper presents an appropriate approach for modeling noise in Computed Radiography(CR) images of high strength materials. The approach is specifically designed for types of noise with the statistical and nonlinear properties. CR images Ere degraded even before they are encoded by computer process. Various types of noise often contribute to contaminate radiography image, although they are detected on digitalization. Quantum noise, which is Poisson distributed, is a shot noise, but the photon distribution on Image Plate(IP) of CR system is not always Poisson process. The statistical properties are relative and case-dependant due to its material characteristics. The usual assumption of a distribution of Poisson, binomial and Gaussian statistics are considered. Nonlinear effect is also represented in the process of statistical noise model. It leads to estimate the noise variance in regions from high to low intensity, specifying analytical model. The analysis approach is tested on a database of steel tube step-wedge CR images. The results are available for the comparative parameter studies which measure noise coherence, distribution, signal/noise ratios(SNR) and nonlinear interpolation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2A
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• pp.26-33
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• 2005

Exact prediction of resource demands for future calls enhances the efficiency of the limited resource utilization in resource reservation methods for potential calls in wireless IP networks. In this paper, we propose a LMS-Wiener resource(bandwidth) prediction for future handoff calls, and then an the proposed method is compared with an existing Wiener-based method in terms of prediction error through our simulations. In our simulations, we assume that handoff call arrivals follow a non-Poisson process and each handoff call has an non-exponentially distributed channel holdingtime in the cell, considering that handoff call arrival pattern is not Poisson distribution but non-Poisson for long periods of time in wireless picocellular IP networks. Simulation results show that the prediction error in the proposed method converges to the lower value while in an existing method increase as time is passed. Therefore we may conclude that the proposed method improves the efficiency of resource utilization by more exactly predicting resource demands for future handoff calls than an existing method.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.3
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• pp.172-182
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• 2013

In this study we consider a flow line CONWIP system in which two types of product are produced. The processing times of each product type at each station follow an independent exponential distribution and the demands for the finished products of each type arrive according to a Poisson process. The demands that are not satisfied instantaneously are either backordered or lost according to the number of unsatisfied demands that exist at their arrival instants. For this system we develop an approximation method to obtain the performance measures such as steady state probabilities of the number of parts of each product type at each station, mean waiting times of backordered demands and the proportion of backordered demands. For the analysis of the proposed CONWIP system, we model the CONWIP system as a two class closed queueing network with a synchronization station and analyze the closed queueing network using a product-form approximation method for multiple classes developed by Baynat and Dallery. In the approximation method, each subsystem is analyzed using a matrix geometric method. Comparisons with simulation show that the approximation method provides fairly good results for all performance measures.

• The Transactions of the Korea Information Processing Society
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• v.3 no.3
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• pp.512-522
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• 1996

To provide broadband ISDN service for the users in scattered locations, the application of satellite communications network is seriously considered. To trans mit ATM cells efficiently in satellite communications, it is effective to use TDM A method. However, it is necessary to have a method to compensate the cell delayvari-ation caused by the difference between TDMA and ATM. This paper optimized the cell control time(Tc) when traffic inputs have poisson or markov modulated poisson process by applying cell delay variation characteristics of time stamp method, which has the most advantages among compensation methods or cell delay variation. This paper also intorduces a method of reducing the cell clumping phenomena by adapting discrete time stamp method, including the analysis and evalutation of the range of required quality of CDV distribution by ATM transmission.The result of the experiment shows that CDV distribution-range can be controlled to 1.2$\times$Tc which reduces overall cell delay variation by discrrete time stamp method.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.3
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• pp.45-52
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• 2022

Prediction of soil behavior should be interpreted based on the level of axial strain in the actual ground. Recently numerical methods have been carried out focus on the state of soil failure. However considered the deformation of soil the prior to failure, mostly the small strain occurring in the elastic range is considered. As a result of calculating the deformation modulus to 50% of the maximum unconfined compression strength, Deformation modulus (E50) showed a tendency to increase according to the degree of compaction by region. The Poisson's ratio during loading-unloading was 0.63, which was higher than the literature value of 0.5. For the unconfined compression test under cyclic loading for the measurement of permanent strain, the maximum compression strength was divided into four step and the test was performed by load step. Changes in permanent strain and deformation modulus were checked by the loading-unloading test for each stage. At 90% compaction, the permanent deformation of the SM sample was 0.21 mm, 0.37 mm, 0.6 mm, and 1.35 mm. The SC samples were 0.1 mm, 0.17 mm, 0.42 mm, and 1.66 mm, and the ML samples were 0.48 mm, 0.95 mm, 1.30 mm, and 1.68 mm.

• Journal of IKEEE
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• v.15 no.1
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• pp.43-48
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• 2011

Decision problem called an optimal release policies, after testing a software system in development phase and transfer it to the user, is studied. The infinite failure non-homogeneous Poisson process models presented and propose an optimal release policies of the life distribution applied extreme distribution which used to find the minimum (or the maximum) of a number of samples of various distributions. In this paper, discuss optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement. In a numerical example, extreme value distribution as another alternative of existing the Poisson execution time model and the log power model can be verified using inter-failure time data.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.5
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• pp.859-870
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• 2011

The purpose of this paper is to develop reliability analysis procedures for repairable systems with interval failure time data and apply the procedures for assessing the storage reliability of a subsystem of a certain type of guided missile. In the procedures, the interval failure time data are converted to pseudo failure times using the uniform random generation method, mid-point method or equispaced intervals method. Then, such analytic trend tests as Laplace, Lewis-Robinson, Pair-wise Comparison Nonparametric tests are used to determine whether the failure process follows a renewal or non-renewal process. Monte Carlo simulation experiments are conducted to compare the three conversion methods in terms of the statistical performance for each trend test when the underlying process is homogeneous Poisson, renewal, or non-homogeneous Poisson. The simulation results show that the uniform random generation method is best among the three. These results are applied to actual field data collected for a subsystem of a certain type of guided missile to identify its failure process and to estimate its mean time to failure and annual mean repair cost.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.146-151
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• 1999

The classical queuing analysis has been tremendously useful in doing capacity planning and performance prediction. However, in many real-world cases. it has found that the predicted results form a queuing analysis differ substantially from the actual observed performance. Specially, in recent years, a number of studies have demonstrated that for some environments, the traffic pattern is self-similar rather than Poisson. In this paper, we study these self-similar traffic characteristics and the definition of self-similar stochastic processes. Then, we consider the examples of self-similar data traffic, which is reported from recent measurement studies. Finally, we wish you that it makes out about the characteristics of actual data traffic more easily.

• Journal of the Korea Society for Simulation
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• v.16 no.2
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• pp.75-81
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• 2007

Previous queue inference has been studied with some limits. Larson's inference engine, which is the basis for this paper, also processed with basic assumption that arrival process is poisson process. Our inference method, which relaxes the poisson process assumption, must be a useful tool for looking into unobservable inside of queueing systems, as well as calculating accurate system performance. This paper employs these inference methods and proves the validity. Then we apply this method to system analysis for more complicated models. At first, we suggest methods to system with known number of servers, then expand to unknown number of servers. For validating our inference approach, we run some simulation models and compare true values with our results.

• The Transactions of the Korea Information Processing Society
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• v.4 no.2
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• pp.395-400
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• 1997

An important quality characteristic of a software reliability.Software reliablilty growh models prvied the tools to evluate and moniter the reliabolty growth behavior of the sofwate during the testing phase Therefore failure data collected during the testing phase should be continmuosly analyzed on the basis of some selected software reliability growth models.For the cases where nonhomogeneous Poisson proxess models are the candiate models,we suggest Poisson regression model, which expresses the relationship between the expeted and actual failures counts in disjonint time intervals,for analyzing the failure count data.The weighted lest squares method is then used to-estimate the paramethers in the parameters in the model:The resulting estimators are equivalent to the maximum likelihood estimators. The method is illustrated by analyzing the failutr count data gathered from a large- scale switchong system.