• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.9-18
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• 2006

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 exponentiated exponential distribution reliability model, which maked out efficiency substituted for gamma and Weibull model(2 parameter shape illustrated by Gupta and Kundu(2001) Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using NTDS data set for the sake of proposing shape parameter of the exponentiated exponential distribution was employed. This analysis of failure data compared with the exponentiated exponential distribution model and the existing model (using arithmetic and Laplace trend tests, bias tests) is presented.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.45-53
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• 2006

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 $x^2$ reliability model, which can capture the increasing 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 SSE, AIC statistics 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 shape parameter of the $x^2$ distribution using the degree of freedom, was employed. This analysis of failure data compared with the $x^2$ model and the existing model using arithmetic and Laplace trend tests, Kolmogorov test is presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.12
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• pp.2311-2318
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• 2007

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. Accurate predictions of software release times, and estimation of the reliability and availability of a software product require Release times of a critical element of the software testing process : test coverage. This model called Enhanced non-homogeneous Poission process(ENHPP). In this paper, exponential coverage and S-shaped model was reviewed, proposes the Kappa coverage model, which make out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics and Kolmogorov distance, for the sake of efficient model, was employed. Numerical examples using real data set for the sake of proposing Kappa coverage model was employed. This analysis of failure data compared with the Kappaa coverage model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.3
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• pp.514-522
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• 2007

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this parer, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the Burr distribution reliability model, which making out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using real data set for the sake of proposing shape parameter of the Burr distribution was employed. This analysis of failure data compared with the Burr distribution model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.5
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• pp.218-225
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• 2001

This paper analyses the performance of network system using the CAN(Controller Area Network) protocol. Given messages are assumed to be scheduled by the DMS(Deadline Monotonic Scheduling) algorithm. The mathematical models for time-delay that can be occurred between CAN nodes are defined. The effectiveness of modeling is shown by comparing the difference of time-delay between simulations and practical experiments. We analyse the results according to the variation of factors, such as the number of nodes, the transmission speed, the message size and the number of aperiodic messages through simulation and confirm the real-time performance of lower priority messages. We also investigate the real-time performance of periodic messages when aperiodic message generates.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.6
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• pp.1122-1129
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• 2007

For a system with multiple real-time tasks of different deadlines, it is very difficult to find the optimal checkpoint interval because of the complexity in considering the scheduling of tasks. In this paper, we determine the optimal checkpoint interval for multiple real-time tasks that are scheduled by RM(Rate Monotonic) algorithm. Faults are assumed to occur with Poisson distribution. Checkpoints are inserted in the execution of task with equal distance in the same task, but different distances in other tasks. When faults occur, rollback to the latest checkpoint and re-execute task after the checkpoint. We derive the equation of maximum slack time for each task, and determine the number of re-executable checkpoint intervals for fault recovery. The equation to check the schedulibility of tasks is also derived. Based on these equations, we find the probability of all tasks executed within their deadlines successfully. Checkpoint intervals which make the probability maximum is the optimal.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.110-114
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• 2012

We studied on the nondestructive evaluation of the elastic wave signal of SiC ceramics and SiC/SiC composite ceramics under monotonic tensile loading. The elastic wave signal of cross and unidirectional SiC/SiC composite ceramics were obtained by pencil lead method and bending test. It was applied for the time-frequency method which used by the discrete wavelet analysis algorithm. The time-frequency analysis provides time variation of each frequency component involved in a waveform, which makes it possible to evaluate the contribution of SiC fiber frequency. The results were compared with the characteristic of frequency group from SiC slurry and fiber. Based on the results, if it is possible to shift up and design as a higher frequency group, we will can make the superior material better than those of exiting SiC/SiC composites.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04a
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• pp.104-106
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• 2000

단일프로세서 환경에서 주기 태스크의 시간 제약 조건을 만족시키면서 비주기 태스크의 평균 서비스 시간을 최소화하는 연구가 계속 진행되어 왔으나, 최근의 시스템은 여러 개의 프로세서를 병렬처리하여 프로그램의 처리속도 향상을 꾀하는 멀티프로세서 환경으로 전환되어 가는 추세다. 따라서, 멀티프로세서 환경에서의 태스크 스케쥴링에 관한 다양한 여구가 필요하게 되었다. 일반적으로 멀티프로세서 환경에서는 주기 태스크를 스케쥴링하기 위해서 RMFF(Rate-monotonic First-Fit) 스케쥴링 알고리즘을 사용하는데, 이 알고리즘에서는 비주기 태스크의 스케쥴링을 위한 알고리즘을 추가로 요구한다. 따라서, 본 논문에서는 멀티프로세서 환경에서 주기 태스크와 비주기 태스크가 혼합되어 있을 때, 기존의 RMFF 방식에 슬랙 체크테이블(Slack Check Table;SCT)을 이용하여 비주가 태스크를 효율적으로 스케쥴링하기 위한 방법을 제안한다.

• Journal of the Korea Safety Management & Science
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• v.10 no.4
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• pp.127-134
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• 2008

The objective of this study is to evaluate the mechanical behaviors and structural integrity of the weldment of high strength steel by using an acoustic emission (AE) techniques. Monotonic simple tension and AE tests were conducted against the 3 kinds of welded specimen. In order to analysis the effectiveness of weldability, joinability and structural integrity, we used K-means clustering method as a unsupervised learning pattern recognition algorithm for obtained multi-variate AE main data sets, such as AE counts, energy, amplitude, hits, risetime, duration, counts to peak and rms signals. Through the experimental results, the effectiveness of the proposed method is discussed.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.119-133
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• 1999

A Markov Chain Monte Carlo method is developed to compute the software reliability model. We consider computation problem for determining of posterior distibution in Bayseian inference. Metropolis algorithms along with Gibbs sampling are proposed to preform the Bayesian inference of the Mixed model with record value statistics. For model determiniation, we explored the prequential conditional predictive ordinate criterion that selects the best model with the largest posterior likelihood among models using all possible subsets of the component intensity functions. To relax the monotonic intensity function assumptions. A numerical example with simulated data set is given.