• Journal of the Korean Statistical Society
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• v.31 no.4
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• pp.491-507
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• 2002

We analyze a single server bulk input queue with optional server vacations under a single vacation policy and balking phenomenon. The service times of the customers as well as the vacation times of the server have been assumed to be arbitrary (general). We further assume that not all arriving batches join the system during server's vacation periods. The supplementary variable technique is employed to obtain time-dependent probability generating functions of the queue size as well as the system size in terms of their Laplace transforms. For the steady state, we obtain probability generating functions of the queue size as well as the system size, the expected number of customers and the expected waiting time of the customers in the queue as well as the system, all in explicit and closed forms. Some special cases are discussed and some known results have been derived.

• International Journal of Reliability and Applications
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• v.11 no.1
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• pp.41-53
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• 2010

In the present paper we develop a mathematical model that facilitates the calculation of reliability of a complex repairable system having three units namely super priority, priority and ordinary. The system is analyzed with the application of Gumbel Hougaard copula when different types of repair possible at a particular state due to deliberate failure. Various reliability measures such as reliability, MTTF and profit function have been evaluated by using supplementary variable and Laplace transform techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.1
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• pp.81-98
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• 2013

Since Probabilistic Latent Semantic Analysis (PLSA) and Latent Dirichlet Allocation (LDA) were introduced, many revised or extended topic models have appeared. Due to the intractable likelihood of these models, training any topic model requires to use some approximation algorithm such as variational approximation, Laplace approximation, or Markov chain Monte Carlo (MCMC). Although these approximation algorithms perform well, training a topic model is still computationally expensive given the large amount of data it requires. In this paper, we propose a new method, called non-simultaneous sampling deactivation, for efficient approximation of parameters in a topic model. While each random variable is normally sampled or obtained by a single predefined burn-in period in the traditional approximation algorithms, our new method is based on the observation that the random variable nodes in one topic model have all different periods of convergence. During the iterative approximation process, the proposed method allows each random variable node to be terminated or deactivated when it is converged. Therefore, compared to the traditional approximation ways in which usually every node is deactivated concurrently, the proposed method achieves the inference efficiency in terms of time and memory. We do not propose a new approximation algorithm, but a new process applicable to the existing approximation algorithms. Through experiments, we show the time and memory efficiency of the method, and discuss about the tradeoff between the efficiency of the approximation process and the parameter consistency.

• International Journal of Reliability and Applications
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• v.12 no.1
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• pp.15-39
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• 2011

This paper deals with the reliability analysis of a complex system with three possibilities at the time of repair. The considered system consists of two subsystems A and Bin series configuration (1-out-of-2: F). Subsystem A has n units which are connected in series whereas subsystem B consists of n units in parallel configuration. The configuration of subsystem A is of 1-out-of-n: F whereas subsystem B is of k-out-of-n: D and k+1-out-of-n: F nature. System has three states: Good, degraded and failed. Supplementary variable technique has been used for mathematical formulation of the model. Laplace transform is being utilized to solve the mathematical equation. Reliability, Availability, M.T.T.F., Busy Period and Cost effectiveness of the system have been computed. The repairs from state $S_7$ to $S_0$, $S_8$ to $S_0$, $S_9$ to $S_0$ and $S_{11}$ to $S_0$ have two types namely exponential and general. Joint probability distribution of repair rate from $S_7$ to $S_0$, $S_8$ to $S_0$, $S_9$ to $S_0$ and $S_{11}$ to $S_0$ is computed by Gumbel-Hougaard family of copula. Some particular cases of the system have also been derived to see the practical importance of the model.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.5
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• pp.1158-1174
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• 1988

A numerical technique is developed for the solution of fully developed turbulent recirculating flow in the passage of variable area using the non-orthogonal coordinate transformation. In the numerical analysis, primitive pressure-velocity finite difference equations were solved by SIMPLER algorithm with 2-equation turbulence model and algebraic stress model (ASM). QUICK scheme on the differencing of convective terms which is free from the inaccuracies of numerical diffusion has been applied to the variable grids and the results compared with those from HYBRID scheme. In order to test the effect of streamline curvatures on turbulent diffusion Lee and Choi streamline curvature correction model which has been obtained by modifying the Leschziner and Rodi's model is testes. The ASM was also employed and the results are compared to those from another turbulence model. The results show that difference of convective differencing schemes and turbulence models give significant differences in the prediction of velocity fields in the expansion region and outlet region of the combustor, however show little differences in the parallel flow region.

• International Journal of Reliability and Applications
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• v.11 no.2
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• pp.107-122
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• 2010

This paper deals with the reliability analysis of a complex system, which consists of two subsystems A and B connected in series. Subsystem A has only one unit and B has two units $B_1$ and $B_2$. Marked process has been applied to model the complex system. Present reliability model incorporated two repairmen: supervisor and novice to repair the failed units. Supervisor is always there and the novice remains in vacation and is called for repair as per demand. The repair rates for supervisor and novice follow general and exponential distributions respectively and the failure time for both the subsystems follows exponential distribution. The model is analyzed under "Head of line repair discipline". By employing supplementary variable technique, Laplace transformation and Gumbel-Hougaard family of copula various transition state probabilities, reliability, availability and cost analysis have been obtained along with the steady state behaviour of the system. At the end some special cases of the system have been taken.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.153-162
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• 1997

M/G/1 queueing system is one of the most widely used one to model the real system. When operating a real systems, since it often takes cost, some control policies that change the operation scheme are adopted. In particular, the N-policy is the most popular among many control policies. Almost all researches on queueing system are based on the assumption that the arrival rates of customers into the queueing system is constant, In this paper, we consider the M/G/1 queueing system whose arrival rate varies according to the servers status : idle, set-up and busy states. For this study, we construct the steady state equations of queue lengths by means of the supplementary variable method, and derive the PGF(probability generating function) of them. The L-S-T(Laplace Stieltjes transform) of waiting time and average waiting time are also presented. We also develop an algorithm to find the optimal N-value from which the server starts his set-up. An analysis on the performance measures to minimize total operation cost of queueing system is included. We finally investigate the behavior of system operation cost as the optimal N and arrival rate change by a numerical study.

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.87-92
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• 2002

A stochastic process {$A_n$, n = 1, 2, ...} is an arithmetic process (AP) if there exists some real number, d, so that {$A_n$ + (n-1)d, n =1, 2, ...} is a renewal process (RP). AP is a stochastically monotonic process and can be used for modeling a point process, i.e. point events occurring in a haphazard way in time (or space), especially with a trend. For example, the vents may be failures arising from a deteriorating machine; and such a series of failures id distributed haphazardly along a time continuum. In this paper, we discuss estimation procedures for an AP, similar to those for a geometric process (GP) proposed by Lam (1992). Two statistics are suggested for testing whether a given process is an AP. If this is so, we can estimate the parameters d, ${\mu}_{A1}$ and ${\sigma}^{2}_{A1}$ of the AP based on the techniques of simple linear regression, where ${\mu}_{A1}$ and ${\sigma}^2_{A1}$ are the mean and variance of the first random variable $A_1$ respectively. In this paper, the procedures are, for the most part, discussed in reliability terminology. Of course, the methods are valid in any area of application, in which case they should be interpreted accordingly.