• Korean Journal of Mathematics
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• v.29 no.1
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• pp.75-80
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• 2021

For a locus with two alleles (IA and IB), the frequencies of the alleles are represented by $$p=f(I^A)={\frac{2N_{AA}+N_{AB}}{2N} },\;q=f(I^B)={\frac{2N_{BB}+N_{AB}}{2N}}$$ where NAA, NAB and NBB are the numbers of IA IA, IA IB and IB IB respectively and N is the total number of populations. The frequencies of the genotypes expected are calculated by using p2, 2pq and q2. So in this paper, we consider the method of whether some genotypes is in Hardy-Weinburg equilibrium. Also we calculate the probability generating function for the offspring number of genotype produced by a mating of the ith male and jth female under a diploid model of N population with N1 males and N2 females. Finally, we have conditional joint probability generating function of genotype frequencies.

• Journal of applied mathematics & informatics
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• v.31 no.1_2
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• pp.147-154
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• 2013

We analyze queueing model with priority scheduling by supplementary variable method. Customers are classified into two types (type-1 and type-2 ) according to their characteristics. Customers of each type arrive by independent Poisson processes, and all customers regardless of type have same general service time. The service order of each type is determined by the queue length of type-1 buffer. If the queue length of type-1 customer exceeds a threshold L, the service priority is given to the type-1 customer. Otherwise, the service priority is given to type-2 customer. Method of supplementary variable by remaining service time gives us information for queue length of two buffers. That is, we derive the differential difference equations for our queueing system. We obtain joint probability generating function for two queue lengths and the remaining service time. Also, the mean queue length of each buffer is derived.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1104-1110
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• 2006

In this paper we present a simple approach to the joint queue length distribution in the nonpreemptive priority M/G/1 queue. Without using the supplementary variable technique, we derive the joint probability generating function of the stationary queue length at arbitrary time.

• Journal of applied mathematics & informatics
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• v.28 no.1_2
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• pp.275-282
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• 2010

This paper analyzes a discrete-time bulk-service queue with probabilistic bulk size, where the service process is interrupted by a Markov chain. We study the joint probability generating function of system occupancy and the state of the Markov chain. We derive several performance measures of interest, including average system occupancy and delay distribution.

• Journal of applied mathematics & informatics
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• v.22 no.1_2
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• pp.453-460
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• 2006

A discrete-time priority queueing system with place reservation discipline is studied, in which two different types of packets arrive according to batch geometric streams. It is assumed that there is a reserved place in the queue. Whenever a high-priority packet enters the queue, it will seize the reserved place and make a new reservation at the end of the queue. Low-priority arrivals take place at the end of the queue in the usual way. Using the probability generating function method, the joint distribution of system state and the delay distribution for each type are obtained.

• Communications of the Korean Mathematical Society
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• v.25 no.4
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• pp.647-653
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• 2010

We consider an M/M/1 retrial queue with collision and impatience. It is shown that the generating functions of the joint distributions of the server state and the number of customers in the orbit at steady state can be expressed in terms of the confluent hypergeometric functions. We find the performance characteristics of the system such as the blocking probability and the mean number of customers in the orbit.

• Journal of the Korean Mathematical Society
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• v.42 no.3
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• pp.517-527
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• 2005

This paper considers a discrete-time queueing system with variable service capacity. Using the supplementary variable method and the generating function technique, we compute the joint probability distribution of queue length and remaining service time at an arbitrary slot boundary, and also compute the distribution of the queue length at a departure time.

• School Mathematics
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• v.17 no.2
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• pp.241-255
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• 2015

The purpose of this study is to analyze teachers' understanding on generating random number in Monte Carlo simulation and to provide educational implications in school practice. The results showed that the 70% of the teachers selected wrong ideas from three types for random-number as strategies for problem solving a probability problem and also they make some errors to justify their opinion. The first kind of the errors was that the probability of a point or boundary was equal to the value of the probability density function in the continuous probability distribution. The second kind of the errors was that the teachers failed to recognize that the sample space has been changed by conditional probability. The third kind of the errors was that when two random variables X, Y are independence of each other, then only, joint probability distribution is satisfied $P(X=x,\;Y=y)=p(X=x){\times}P(Y=y{\mid}X=x)$.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.91-105
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• 2019

Discrete-time Queueing models are frequently utilized to analyze the performance of computing and communication systems. The length of busy period is one of important performance measures for such systems. In this paper, we consider the busy period of the Geo/Geo/1/K queue with a single vacation. We derive the moments of the length of the busy (idle) period, the number of customers who arrive and enter the system during the busy (idle) period and the number of customers who arrive but are lost due to no vacancies in the system for both early arrival system (EAS) and late arrival system (LAS). In order to do this, recursive equations for the joint probability generating function of the busy period of the Geo/Geo/1/K queue starting with n, 1 ≤ n ≤ K, customers, the number of customers who arrive and enter the system, and arrive but are lost during that busy period are constructed. Using the result of the busy period analysis, we also numerically study differences of various performance measures between EAS and LAS. This numerical study shows that the performance gap between EAS and LAS increases as the system capacity K decrease, and the arrival rate (probability) approaches the service rate (probability). This performance gap also decreases as the vacation rate (probability) decrease, but it does not shrink to zero.

• Journal of the Korean Geotechnical Society
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• v.23 no.10
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• pp.97-107
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• 2007

Accurate evaluation of the slope stability by assuming failure block as the entire slope is considered to be apposite for the small scale slope, whereas it is not the case for the large scale slope. Hence, appropriate estimation of a failure block size is required since the safety factor and the joint strength parameters are the function of the failure block size. In this paper, the size of failure block was investigated by generating 3-dimensional rock joint system based on statistical data of joints obtained from research slope, such as joint orientation, spacing and 3-dimensional joint intensity. The result indicates that 33 potential failure blocks exist in research slope, as large as 1.4 meters at least and 38.7 meters at most, and average block height is 15.2 meters. In addition, the data obtained from 3 dimensional joint system were directly applicable to the probability analysis and 2 and 3 dimensional discontinuity analysis.