• International Journal of Reliability and Applications
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• v.4 no.1
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• pp.1-12
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• 2003

Many software reliability growth models (SRGM's) based on a nonhomogeneous Poisson process (NHPP) have been proposed by many researchers. Most of the SRGM's which have been proposed up to the present treat the event of software fault-detection in the testing and operational phases as a counting process. However, if the size of the software system is large, the number of software faults detected during the testing phase becomes large, and the change of the number of faults which are detected and removed through debugging activities becomes sufficiently small compared with the initial fault content at the beginning of the testing phase. Therefore, in such a situation, we can model the software fault-detection process as a stochastic process with a continuous state space. In this paper, we propose a new software reliability growth model describing the fault-detection process by applying a mathematical technique of stochastic differential equations of an Ito type. We also compare our model with the existing SRGM's in terms of goodness-of-fit for actual data sets.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.4B
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• pp.692-699
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• 2000

We build and analyze some types of queueing model to discuss capacity dimensioning of access links of a LAN interworking unit connected to the Internet backbone network. We assume that the IWU has a FIFO buffer to transmit IP packets to the Internet through the backbone. In order to analyze the system, we use a Poisson process and an MMPP process as input traffic models of IP packets and we use a general service time distribution as a service time model. But we use both an exponential service time and a deterministic service time in numerical examples for simple and efficient performance comparisons. As performance measures, we obtain the packet loss probability and the mean packet delay. We present some numerical results to show the effect of arrival rate, buffer size and link capacity on packet loss and mean delay.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.277-286
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• 1998

This paper investigates the problem of determining optimal replacement policies for equipment subject to failures with cyclic rates. In many situations, the system failures depend on the operating environmental conditions that vary on time, usually with periodical manners. We use nonhomogeneous Poisson processes whose rate functions exhibit cyclic behavior as well as a long-term evolutionary trend to model the stochastic process of the failures when the rate of occurrence of the failures varies periodically, for example from day to day or between seasons. In this study, we compare optimal policies under the nonhomogeneous process with/without a cyclic component in the failure rate function. The analytical results for various situations are presented along with numerical examples using simulated data.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.235-236
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• 2002

Tribological phenomena such as wear or transfer are influenced by various factors and have complicated behavior. Therefore, it is difficult to predict the behavior of the gribological phenomena because of their complexity. But, those tribological phenomena can be considered simply as to transfer micro material particles from the sliding interface. Then, we proposed the numerical simulation method for tribological phenomena such as wear of transfer using stochastic process models. This numerical simulation shows the change of the 3-D surface topography. In this numerical simulation, initial 3-D surface toughness data are generated by the method of non-causal 2-D AR (autoregressive) model. Processes of wear and transfer for some generated initial 3-D surface data are simulated. Simulation results show successfully the change of the 3-D surface topography.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.2
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• pp.67-73
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• 2003

The algorithm (or calculating the base-collector breakdown voltage of NPN BJT(Bipolar Junction Transistor) for integrated circuits is Proposed. The method for calculating the electric field using the solution of Poisson's equation is presented and the method for calculating the breakdown voltage using the integration of ionization coefficients is presented. The base-collector breakdown voltage of NPN BJT using 20V process obtained from the proposed method shows an averaged relative error of 8.0% compared with the measured data and the base-collector breakdown voltage of NPN BJT using 30V process shows an averaged relative error of 4.3% compared with the measured data

• The Journal of Engineering Geology
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• v.2 no.2
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• pp.147-154
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• 1992

A computer simulation of earthquake sequence in the time and magnitude space was done using random number generation. The theory of the simulation are based on the two statistical models of earthquake events. Those models are Stationary Poisson Process for independent earthquakes and Branching Markov Process for aftershocks. The generated earthquake sequnces resemble the actual earthquake catalogs.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.2
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• pp.73-80
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• 2005

In this paper, we consider characteristics of waiting times in s1n91e-server 3-node tandem queues with finite buffers, a Poisson arrival process and deterministic service times at all nodes. There are three buffers : one at the first node is infinite and the others are finite. We obtain the fact that sojourn time or departure process is independent of the capacities of the finite buffers and does not depend on the order of service times, which are the same results in the literature. Moreover, the explicit expressions of stationary waiting times in all areas of the systems can be derived as functions of the finite buffer capacities. We also disclose a relationship of waiting times in subareas of the systems between two blocking policies communication and manufacturing. Some numerical examples are also provided.

• Korean Journal of Mathematics
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• v.22 no.3
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• pp.529-552
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• 2014

As we know, some indices and data are strong influence to the price movement of some assets now, but not to another assets and in future. Thus we define some asset models for several time intervals; intraday, weekly, monthly, and yearly asset models. We define these asset models by using Brownian motion with volatility and Poisson process, and several deterministic functions(index function, twitter data function and big-jump simple function etc). In our asset models, these deterministic functions are the positive or negative levels of auxiliary indices, of analyzed data, and for imminent and extreme state(for example, financial shock or the highest popularity in the market). These functions determined by indices, twitter data and shocking news are a kind of one of speciality of our asset models. For reasonableness of our asset models, we introduce several real data, figurers and tables, and simulations. Perhaps from our asset models, for short-term or long-term investment, we can classify and reference many kinds of usual auxiliary indices, information and data.

• Journal of Korean Society for Quality Management
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• v.26 no.3
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• pp.71-81
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• 1998

In reliability analysis, the time difference between the expected next failure time and the current failure time or the Mean Time Between Failure(MTBF) is of significant interest. Until recently, in reliability growth studies, the reciprocal of the intensity function at current failure time has been used as being equal to MTBE($t_n$)at the n-th failure time $t_n$. That is MTBF($t_n$)=l/$\lambda (t_n)$. However, such a relationship is only true for Homogeneous Poisson Process(HPP). Tsokos(1995) obtained the upper bound and lower bound for the MTBF($t_n$) and proposed an estimator for the MTBF($t_n$) as the mean of the two bounds. In this paper, we provide the estimator for the MTBF($t_n$) which does not depend on the value of the shape parameter. The result of the Monte Carlo simulation shows that the proposed estimator has better efficiency than Tsokos's estimator.

• Management Science and Financial Engineering
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• v.5 no.2
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• pp.43-53
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• 1999

In many situations, the system failures depend on the operating environmental conditions that vary on time, usually with periodical manners. We use nonhomogeneous Poisson processes whose rate functions exhibit cyclic behavior as well as a long-term evolutionary trend to model the stochastic process of the failures when the rate of occurrence of the failures varies periodically, for example from day to day or between seasons. In this study, we compare optimal policies under the nonho-mogeneous process with/without a cyclic component in the failure rate function. The analytical re-sults for various situations are presented along with numerical examples using simulated data.