• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.483-503
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• 2015

This paper analyzes the optimal user density and power allocation for Device-to-Device (D2D) communication underlaying cellular networks on multiple bands with the target of maximizing the D2D transmission capacity. The entire network is modeled by Poisson point process (PPP) which based on stochastic geometry. Then in order to ensure the outage probabilities of both cellular and D2D communication, a sum capacity optimization problem for D2D system on multiple bands is proposed. Using convex optimization, the optimal D2D density is obtained in closed-form when the D2D transmission power is determined. Next the optimal D2D transmission power is obtained in closed-form when the D2D density is fixed. Based on the former two conclusions, an iterative algorithm for the optimal D2D density and power allocation on multiple bands is proposed. Finally, the simulation results not only demonstrate the D2D performance, density and power on each band are constrained by cellular communication as well as the interference of the entire system, but also verifies the superiority of the proposed algorithm over sorting-based and removal algorithms.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.1
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• pp.52-59
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• 2004

Recently, many researches for fine particles plasma have been focused on the fabrication of the new devices and materials in micro-electronic industry, although reduction or elimination of fine particles was interested in plasma processing until now on. In order to enhance their utilization, it is necessary to control and analyze fine particle behavior. Therefore, we developed simulation model of fine particles in RF Ar plasmas. This model consists of the calculation parts of plasma structure using a two-dimensional fluid model and of fine particle behavior. The motion of fine particles was derived from the charge amount on the fine particles and forces applied to them. In this paper, Ar plasma properties using two-dimensional fluid model without fine particles were calculated at power source voltage 15[V] and pressure 0.5[Torr]. Time-averaged spatial distributions of Ar plasma were shown. The process on the formation of Coulomb crystal of fine particles was investigated and it was explained by combination of ion drag and electrostatic forces. And also analysis on the forces of fine particles was presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.10
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• pp.1815-1821
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• 2006

In this paper, the subthreshold swing has been analyzed for FinFET under channel length of 20nm. The analytical current model has been developed , including thermionic current and tunneling current models. The potential distribution by Poisson equation and carrier distribution by Maxwell-Boltzman statistics are used to calculate thermionic emission current and WKB(Wentzel-Kramers-Brillouin) approximation to tunneling current. The cutoff current is obtained by simple adding two currents since two current is independent. The subthreshold swings by this model are compared with those by two dimensional simulation and two values agree well. Since the tunneling current increases especially under channel length of 10nm, the characteristics of subthreshold swing is degraded. The channel and gate oxide thickness have to be fabricated as am as possible to decrease this short channel effects, and this process has to be developed. The subthreshold swings as a function of channel doping concentrations are obtained. Note that subthreshold swings are resultly constant at low doping concentration.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.6
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• pp.566-572
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• 2016

Software Reliability implemented in software development is one of the most important issues. In finite failure NHPP software reliability models for software failure analysis, the hazard function that means a failure rate may have constant independently for failure time, non-increasing or non-decreasing pattern. In this study, software development cost analysis considering the variable shape parameter of Erlang distribution as the failure life distribution in the software product testing process was studied. The software failure model was applied finite failure Non-Homogeneous Poisson Procedure and the parameters approximation using maximum likelihood estimation was accompanied. Thus, this paper was presented comparative analysis by applying a software failure time data to the software, considering the shape parameter of Erlang distribution for development cost model analysis. When compared to the cost curve in accordance with the shape parameter, the model of smaller shape can be seen that the optimal software release time delay and more cost. Through this study, it is thought that it can serve as a preliminary information which can basically help the software developers to search for development cost according to software shape parameters.

• Journal of Internet Computing and Services
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• v.5 no.4
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• pp.63-76
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• 2004

For efficient design and operation of a communication network, precise simulation of network characteristics is essential. This issue has been the focus of research by several groups. In this study, we first modeled the HTTP traffic which would be employed on simulation on the level of application using the real collected traffic data. There are two different viewpoints on the characteristics of web traffic pattern, Poisson distribution and self-similar characteristics. In our study, the results show that web traffic characteristics do not depend on only one type of distribution, but the traffic can be modeled as composition of these depending on the size of response of Web server. This implicates that the web traffic can be modeled as the combination of two characteristics. We also found that the characteristics of Web traffic rely on the properties of web servers. This result was deployed as a traffic generator in implementing the network simulator (NetDAS).

• Journal of the Korea Computer Industry Society
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• v.6 no.5
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• pp.689-696
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• 2005

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the Kappa(2) reliability model, which can capture the nomotonic decreasing nature of the failure occurrence rate per fault. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on sum of the squared errors and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using real data set, SYS2(Allen P.Nikora and Michael R.Lyu), for the sake of proposing two parameter of the Kappa distribution, was employed. This analysis of failure data compared with the Kappa model and the existing model using arithmetic and Laplace trend tests, bias tests is presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.8
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• pp.1190-1200
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• 1993

In this work, the performance of both delay sensitive traffics and loss sensitive traffics of the output buffered ATM switch with priority control mechanisms has been evaluated. We choose the partial buffer sharing mechanism as the loss priority control mechanism and the HOL(Head Of Line) priority control mechanism as the time priority control mechanism. We model loss sensitive traffics with Poisson process and delay sensitive traffics with MMPP. With loss priority control, it is confirmed that loss probability of loss sensitive traffice decreases when the loss priority control mechanism is chosen. With time priority control, it has also been confirmed that mean cell delay of delay sensitive traffics decreases when the HOL priority control mechanism is used. From this analysis, It has been confirmed that the requirements of QOS for both loss sensitive and delay sensitive traffics can be satisfied in the ATM switch by combining both the loss priority control mechanism and the HOL priority control mechanism.

• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.813-823
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• 2008

The non-homogeneous Poisson process(NHPP) based software reliability growth models are proved quite successful in practical software reliability engineering. The fault detection rate is usually assumed to be the continuous and monotonic function. However, the fault detection rate can be affected by many factors such as the testing strategy, running environment and resource allocation. This paper describes a parameter estimation of software reliability growth model with change-point problem. We obtain the maximum likelihood estimate(MLE) and least square estimate(LSE), and compare goodness-of-fit.

• Journal of the Korea Safety Management & Science
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• v.10 no.3
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• pp.89-98
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• 2008

A preventive maintenance model, caller FNBM($\alpha$, $\delta$, $\gamma$)model, is proposed to decide an optimal repair number under achieved availability requirements(r) along with taking two types of failures (repairable or irrepairable) into account. In this model, the current system is replaced by a new one in case when it doesn't meet the achieved availability requirement, even though it is repairable failure; Otherwise it is replaced in time of the first irrepairable failure. Assumed that the j-th failure is repairable with probability ${\alpha}_j$ minimal repairs are allowed for repairable failure between replacements. Expected cost rate for preventive maintenance model is developed using NHPP(Non-Homogeneous Poisson Process) in order to determine the optimal number $n^*$, also numerical examples are shown in order to explain the proposed model. Since the proposed FNBM($\alpha$, $\delta$, $\gamma$)model includes Park FNBM model(1979) and Nakagawa FNBM(p)model(1983) this proposed model is thought to be better than previous model, especially for weapon system which requires availability as primary parameter.

• Convergence Security Journal
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• v.6 no.3
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• pp.117-126
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• 2006

Bayesian inference and model selection method for software reliability growth models are studied. Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. In this paper, could avoid multiple integration using Gibbs sampling, which is a kind of Markov Chain Monte Carlo method to compute the posterior distribution. Bayesian inference for general order statistics models in software reliability with diffuse prior information and model selection method are studied. For model determination and selection, explored goodness of fit (the error sum of squares), trend tests. The methodology developed in this paper is exemplified with a software reliability random data set introduced by of Weibull distribution(shape 2 & scale 5) of Minitab (version 14) statistical package.