• 한국데이터정보과학회:학술대회논문집
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• 2003.10a
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• pp.155-162
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• 2003

A tandem network in which all nodes have the same load is considered. We derive bounds on the probability that the total population of the tandem network exceeds a large value by using its relation to the stationary distribution. These bounds imply a stronger asymptotic limit than that in the large deviation theory.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.715-723
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• 2003

A tandem network in which all nodes have the same load is considered. We derive bounds on the probability that the total population of the tandem network exceeds a large value by using its relation to the stationary distribution. These bounds imply a stronger asymptotic limit than that in the large deviation theory.

• MALSORI
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• no.62
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• pp.113-131
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• 2007

It is reported that the segmental feature based recognition system shows better results than conventional feature based system in the previous studies. On the other hand, the various studies of combining neural network and hidden Markov models within a single system are done with expectations that it may potentially combine the advantages of both systems. With the influence of these studies, tandem approach was presented to use neural network as the classifier and hidden Markov models as the decoder. In this paper, we applied the trend information of segmental features to tandem architecture and used posterior probabilities, which are the output of neural network, as inputs of recognition system. The experiments are performed on Auroral database to examine the potentiality of the trend feature based tandem architecture. From the results, the proposed system outperforms on very low SNR environments. Consequently, we argue that the trend information on tandem architecture can be additionally used for traditional MFCC features.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.117-139
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• 1999

This paper is concerned about the hybrid tandem configuration as the design of the automated guided vehicle system(AGVs). The hybrid tandem configuration is that the manufacturing system is divided into several non-overlapping zones, workstations of each zone are linked by network configuration including loop. That is, the manufacturing system is divided into several non-overlapping small size networks, and at most two automated guided vehicles can be available in each network. The transit point is located at proper point between adjacent networks. The parts are transported to workstations in other network through the transit points. One of the objective functions in dividing into the hybrid tandem configuration is to minimize the maximum travel time of the divided networks, and other is to minimize the total travel distance of parts moved to workstations in other networks for the next processing. The model formulation is presented, and a numerical example is shown. Also, the performances of system for the hybrid tandem, tandem and network configuration are compared through the simulation. The results of this research will contribute to the development of material handling systems in the manufacturing system. Also, it will be applied in determining the transportation area of transportation vehicles and the number and size of the transportation fleet in the transportation problem of logistics management.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.499-511
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• 2000

We consider a stable tandem network which consists of two M/M/1 nodes and study the probability that the total backlog exceeds a large level N. Since the excessive backlog is a rare event, it is difficult to estimate this probability efficiently by using the crude Monte Carlo simulation. Instead we perform the ;$h$-transform proposed by McDonald(1999) to obtain the twisted network, in which the node with the larger load is overloaded. Then we use it to run the fast simulation.

• Proceedings of the KSPS conference
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• 2007.05a
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• pp.323-326
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• 2007

The various studies of combining neural network and hidden Markov models within a single system are done with expectations that it may potentially combine the advantages of both systems. With the influence of these studies, tandem approach was presented to use neural network as the classifier and hidden Markov models as the decoder. In this paper, we applied the trend information of segmental features to tandem architecture and used posterior probabilities, which are the output of neural network, as inputs of recognition system. The experiments are performed on Aurora2 database to examine the potentiality of the trend feature based tandem architecture. The proposed method shows the better results than the baseline system on very low SNR environments.

• 한국데이터정보과학회:학술대회논문집
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• 2001.10a
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• pp.87-97
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• 2001

We consider a stable tandem network which consists of two M/M/1 queues. The optimal changes of measure to run the fast simulation for the probability of rare events such as buffer overflows are obtained.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.1
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• pp.15-26
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• 2000

We consider an open tandem queueing network with population constraint and constant service times. The total number of customers that may be present in the network can not exceed a given value k. Customers arriving at the queueing network when there are more than k customers are forced to walt in an external queue. The arrival process to the queueing network is assumed to be arbitrary. It is known that the queueing network with population constrant and constant service times can be transformed into a simple network involving only two nodes. In this paper, the departure process from the queueing network is examined using this simple network. An approximation can be calculated with accuracy. Finally, validations against simulation data establish the tightness of these.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.4
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• pp.113-121
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• 2009

In this paper, we consider the departure process from the open and nested tandem Queueing network with population constraint and constant service times. It is known that the Queueing network can be transformed into a simple Queueing network which can be easy to analyze. Using this simple Queueing network, upper and lower bounds on the interdeparture time are obtained. We prove that the variance of the interdeparture time is bounded within these two bounds. Validation against simulation data is shown that how it works the variance of the interdeparture time within two bounds. These bounds can be applied to obtain the better variance of the interdeparture time using a suitable method.

• The Journal of Engineering Research
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• v.1 no.1
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• pp.31-40
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• 1997

We first describe an approximation method for fitting a k-state MMBP to the departure process of a D-BMAP/Geo/1/K queue. The fitting model is them used in a simple decomposition algorithm to analyze a tandem configuration of finite capacity queue with cell loss.