• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.535-541
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• 2007

The Non-homogeneous Poisson process is probably the most popular model since it can model systems that are deteriorating or improving. The renewal process is a model that is often used to describe the random occurrence of events in time. But both these models are based on too restrictive assumptions on the effect of the repair action. The Modulated Power Law Process is a suitable model for describing the failure pattern of repairable systems when both renewal-type behavior and time trend are present. In this paper we propose maximum likelihood estimation of the next failure time after the system has experienced some failures, that is, Mean Time Between Failure for the MPLP model.

• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.3
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• pp.237-244
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• 2013

A continuous, explicit drain-current equation for short-channel double-gate (DG) MOSFETs has been derived based on the explicit surface potential equation. The model is physically derived from Poisson's equation in each region of operation and adopted in the unified regional approach. The proposed model has been verified with numerical solutions, physically scalable with channel length and gate/oxide materials as well as oxide/channel thicknesses.

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.393-400
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• 2001

This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process (NHPP). The failure process is analyzed to develop a suitable mean value function for the NHPP ; expressions are given for several performance measure. Actual software failure data are compared with generalized model by Goel dependent on the constant reflecting the quality of testing. The performance measures and parametric inferences of the new models, Rayleigh and Gumbel distributions, are discussed. The results of the new models are applied to real software failure data and compared with Goel-Okumoto and Yamada, Ohba and Osaki models. Tools of parameter inference was used method of the maximun likelihood estimate and the bisection algorithm for the computing nonlinear root. In this paper, using the sum of the squared errors, model selection was employed. The numerical example by NTDS data was illustrated.

• The KIPS Transactions:PartD
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• v.9D no.3
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• pp.389-398
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• 2002

Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process(NHPP) and performs Bayesian inference using prior information. The failure process is analyzed to develop a suitable mean value function for the NHPP ; expressions are given for several performance measure. Actual software failure data are compared with several model on the constant reflecting the quality of testing. The performance measures and parametric inferences of the suggested models using Rayleigh distribution and Laplace distribution are discussed. The results of the suggested models are applied to real software failure data and compared with Goel model. Tools of parameter point inference and 95% credible intereval was used method of Gibbs sampling. In this paper, model selection using the sum of the squared errors was employed. The numerical example by NTDS data was illustrated.

• Journal of the Semiconductor & Display Technology
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• v.17 no.4
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• pp.42-45
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• 2018

As The semiconductor decrease from 10 nanometer to 7 nanometer, It is suggested that "More than Moore" is needed to follow Moore's Law, which has been a guide for the semiconductor industry. Fan-Out Wafer Level Package(FOWLP) is considered as the key to "More than Moore" to lead the next generation in semiconductors, and the reasons are as follows. the fan-out WLP does not require a substrate, unlike conventional wire bonding and flip-chip bonding packages. As a result, the thickness of the package reduces, and the interconnection becomes shorter. It is easy to increase the number of I / Os and apply it to the multi-layered 3D package. However, FOWLP has many issues that need to be resolved in order for mass production to become feasible. One of the most critical problem is the warpage problem in a process. Due to the nature of the FOWLP structure, the RDL is wired to multiple layers. The warpage problem arises when a new RDL layer is created. It occurs because the solder ball reflow process is exposed to high temperatures for long periods of time, which may cause cracks inside the package. For this reason, we have studied warpage in the FOWLP structure using commercial simulation software through the implementation of the reflow process. Simulation was performed to reproduce the experiment of products of molding compound company. Young's modulus and poisson's ratio were found to be influenced by the order of influence of the factors affecting the distortion. We confirmed that the lower young's modulus and poisson's ratio, the lower warpage.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.935-944
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• 2023

In this study, the Inverse-type (: Inverse-Exponential, Inverse-Rayleigh) life distribution, which is known to be suitable for reliability research, was applied to a software development cost model based on finite failure NHPP(: Nonhomogeneous Poisson Process), and then the attributes that determine the model's performance were analyzed. Additionally, to evaluate the efficiency of the model, it was compared with the Goel-Okumoto basic model. The performance of the model was analyzed using failure time data, and MLE (: Maximum Likelihood Estimation) was applied to calculate the parameters. In conclusion, first, as a result of analyzing m(t), which determines the development cost, the Inverse-Exponential model was efficient due to its small error in the true value. Second, as a result of analyzing the release time along with the development cost, the Inverse-Rayleigh model was confirmed to be the best. Third, as a result of comprehensive evaluation of the attributes (m(t), cost, and release time) of the proposed model, the Inverse-Rayleigh model had the best performance. Therefore, if software developers can effectively utilize this research data in the early process, they will be able to proactively explore and analyze attributes that affect cost.

• IE interfaces
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• v.12 no.2
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• pp.312-318
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• 1999

This paper considers the cell loss probability(CLP) in a multiplexer with the superposition of heterogeneous ON/OFF sources. The input traffic is composed of k classes. Traffic of class i is the superposition of M_(i) ON/OFF sources. Recently, the method based on the Markov modulated deterministic process(MMDP) is presented. Basically, it is the discretized model of stochastic fluid flow process(SFFP) and gives the CLP very fast, but under-estimates the CLP especially when the value of estimated CLP is very low. This paper develops the discretized model of Markov modulated Poisson process(MMPP). It is a special type of switched batch Bernoulli process(SBBP). Combining the transition probability matrix of MMDP and SBBP according to the state which is characterized by the arrival rate, this paper presents hybrid algorithm. The hybrid algorithm gives better estimate of CLP than that of MMDP and faster than SBBP.

• Journal of Information Processing Systems
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• v.7 no.4
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• pp.653-678
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• 2011

WiMAX is intended for fourth generation wireless mobile communications where a group of users are provided with a connection and a fixed length queue. In present literature traffic of such network is analyzed based on the generator matrix of the Markov Arrival Process (MAP). In this paper a simple analytical technique of the two dimensional Markov chain is used to obtain the trajectory of the congestion of the network as a function of a traffic parameter. Finally, a two state phase dependent arrival process is considered to evaluate probability states. The entire analysis is kept independent of modulation and coding schemes.

• International Journal of Reliability and Applications
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• v.14 no.2
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• pp.55-70
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• 2013

This paper deals with the Bayesian analysis of the failure data of a repairable mechanical system subject to minimal repairs and periodic overhauls. The effect of overhauls on the reliability of the system is modeled by a proportional age reduction model and the failure process between two successive overhauls is assumed to be 2-parameter Engelhardt-Bain process (2-EBP). Power Law Process (PLP) model has a disadvantage which 2-EBP can overcome. On the basis of the observed data and of a number of suitable prior densities, point and interval estimation of model parameters, as well as quantities of relevant interest are found. Also hypothesis tests on the effectiveness of performed overhauls have been developed using Bayes factor. Sensitivity analysis of improvement parameter is carried out. Finally, a numerical application is used to illustrate the proposed method.

• Journal of Korea Water Resources Association
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• v.39 no.4 s.165
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• pp.373-382
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• 2006

In this study a theoretical drought severity-duration-frequency analysis is performed based on a simple Rectangular Pulses Poisson Process Model(RPPM). Data set with various durations are prepared for a given truncation level, whose statistics are then derived to be used for parameter estimation. These parameters are then used for the theoretical drought severity-duration-frequency analysis. The analysis is considered for two cases; one is to consider the overlap probability and the other is not. The drought severity of considering the overlap probability increases more as the return period increases. However, the overlap probability itself decreases as the duration increases, which is because the occurrence probability of events decreases as the duration increases. Also, if the duration increases, the events rarely or even not occur, since parameters of the model cannot be estimated in those cases, so the drought severity may not be computed. This is an obvious limitation of the simple RPPM. In this study the return periods of the important drought events occurred in Seoul are estimated using the results of the study. If the return period of an event is assumed to be the longest one among those with various durations, the return periods of some important event in Seoul are estimated to be between 14 and 35 years. These return periods are not so long to indicate that these droughts can occur frequently.