• Journal of the Korean Statistical Society
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• v.26 no.2
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• pp.277-288
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• 1997

For the analysis of survival data including covariates whose effects vary in time, the multiprocess discount survival model is proposed. The parameter vector modeling the time-varying effects of covariates is to vary between time intervals and its evolution between time intervals depends on the perturbation of the next time interval. The recursive estimation of the parameter vector can be obtained at the end of each time interval. The retrospective estimation of the survival function and the forecasting of the survival function of individuals of the specific covariates also can be obtained based on the information gathered until the end of the time interval.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.3B
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• pp.181-188
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• 2012

In this paper, the time slot assignment algorithm, which is based on various transmission interval in TDMA DAMA communication system, has been proposed. The performance of the proposed algorithm and the random assignment algorithm is compared through computer simulations. The simulation results show that the new algorithm can enhance the efficiency of time slot usage much more than the random assignment algorithm. Especially, the lower the congestion of the network is, the higher the efficiency of time slot usage for short transmission interval is.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.3
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• pp.457-462
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• 2016

In this paper, we consider the stability of time-delayed linear systems. To derive an LMI form of result, the integral inequality is essential, and Jensen's integral inequality was the best in the last two decades until Seuret's integral inequality is appeared recently. However, these two are proportional to the inverse of integration interval, so another integral inequality is needed to make it in the form of LMI. In this paper, we derive an integral inequality which is proportional to the integration interval which can be easily converted into LMI form without any other inequality. Also, it is shown that Seuret's integral inequality is a special case of our result. Next, based on this new integral inequality, we derive a stability condition in the form of LMI. Finally, we show, by well-known two examples, that our result is less conservative than the recent results.

• ETRI Journal
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• v.41 no.5
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• pp.658-669
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• 2019

For dual-channel time-frequency (TF) overlapped signals with low sparsity in underdetermined blind source separation (UBSS), this paper proposes an effective method based on interval probability to estimate and expand the types of mixing matrices. First, the detection of TF single-source points (TF-SSP) is used to improve the TF sparsity of each source. For more distinguishability, as the ratios of the coefficients from different columns of the mixing matrix are close, a local peak-detection mechanism based on interval probability (LPIP) is proposed. LPIP utilizes uniform subintervals to optimize and classify the TF coefficient ratios of the detected TF-SSP effectively in the case of a high level of TF overlap among sources and reduces the TF interference points and redundant signal features greatly to enhance the estimation accuracy. The simulation results show that under both noiseless and noisy cases, the proposed method performs better than the selected mainstream traditional methods, has good robustness, and has low algorithm complexity.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.875-880
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• 2008

In this paper, a novel method to determine the optimal checkpoint interval for real-time control task is proposed considering its performance degradation according to tasks's execution time. The control task in this paper has a specific sampling period shorter than its deadline. Control performance is degraded as the control task execution time is prolonged across the sampling period and eventually zero when reached to the deadline. A new performance index is defined to represent the performance variation due to the extension of task execution time accompanying rollback fault recovery. The procedure to find the optimal checkpoint interval is addressed and several simulation examples are presented.

• Communications for Statistical Applications and Methods
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• v.3 no.2
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• pp.29-36
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• 1996

In regression model with nested error structure interval estimations about variability on different stages are proposed. This article derives an approximate confidence interval on the variance in the first stage and an exact confidence interval on the variance in the second stage in two stage regression model. The approximate confidence interval is vased on Ting et al. (1990) method. Computer simulation is procided to show that the approximate confidence interval maintains the stated confidence coeffient.

• Biomedical Science Letters
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• v.24 no.1
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• pp.35-42
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• 2018

Postmortem interval (PMI) is very important in the crime scene investigation. However, it is very difficult to estimate of the interval since death after a decomposition. Recently, there have been various studies on the postmortem interval since a decomposition. In particular, the total body score (TBS) and accumulated degree days (ADD) used to estimate the postmortem interval after a decomposition. This study was conducted with the aim of applying the TBS and ADD to estimate the postmortem interval in real forensic caseworks. In first murder case, TBS was 12 and ADD value was 132, respectively. An estimated time of PMI was around 23:00 on June 21, and the suspect's statement was 01:20 on June 22. Our estimated interval since death and the suspect's statement for the PMI differ by only 2 hours and 20 minutes. In second forensic case, TBS was 3 and ADD value was 55, respectively, an estimated time of PMI was around 02:26 on September 23. The suspect's statement was 10:30 on September 23. Our estimated time and the suspect's statement for the PMI differ by 8 hours. In these cases, we were able to have confirmed the feasibility of TBS and ADD on the real forensic cases. Overall, our finding suggested that the quantitative method could be used to produce PMI estimates that are accurate to within days or even hours.

• Journal of applied mathematics & informatics
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• v.8 no.2
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• pp.387-401
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• 2001

If the distance between two vertices becomes longer after the removal of a vertex u, then u is called a hinge vertex. In this paper, a linear time sequential algorithm is presented to find all hinge vertices of an interval graph. Also, a parallel algorithm is presented which takes O(n/P + log n) time using P processors on an EREW PRAM.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.105-117
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• 2003

The purpose of this research aimed at performing the easy design. and also the easy on-the-job application or the maintenance interval determination methodology by presenting the determining model or the optimizing maintenance interval in TBM for the preventive maintenance or facility TBM(time-based maintenance) as the preventive maintenance requires the adequate determination or the maintenance interval. The maintenance interval or TBM shall be applied differently for the each interval such as He patrol inspection, maintenance, overhaul inspection. exchange. And it is based on the composition level of equipment. The already informed theories or interval determination methodology for the patrol inspection. repair. and overhaul inspection are difficult for adopting because or the several restriction problems in applying the maintenance schemes as the theory So, the model for determining the optimizing exchange interval or part, maintenance interval of auxiliary machine, unit equipment etc. was presented to apply in the maintenance easily and appropriately.

• 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.