• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.395-402
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• 2005

This paper deals with modeling and computer simulation of a full multibody vehicle model for a driving simulator. The multibody vehicle model is based on the recursive formulation and a corresponding simulation code is generated automatically from AUTOCODE, which is a symbolic computation package developed by the authors using MAPLE. The paper describes a procedure for automatically generating a highly efficient simulation code for the full vehicle model, while incorporating realistically modeled components. The following issues have been accounted for in the procedure, including software design for representing a mechanical system in symbolic form as a set of computer data objects, a multibody formulation for systems with various types of connections between bodies, automatic manipulation of symbolic expressions in the multibody formulation, interface design for allowing users to describe unconventional force-and torque-producing components, and a method for accommodating external computer subroutines that may have already been developed. The effectiveness and efficiency of the proposed method have been demonstrated by the simulation code developed and implemented for driving simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.7 s.178
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• pp.1878-1884
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• 2000

In multibody dynamic analysis, one of the most important problems is to reduce computation times for real time simulation. In this paper, a symbolic computation method is implemented and tested for each dynamic analysis step. Applying symbolic formulations to the vehicle dynamics program AutoDyn7, the effectiveness of the symbolic computation method is verified.

• Journal of the Korea Society for Simulation
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• v.3 no.2
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• pp.1-13
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• 1994

Deep reasoning procedures are model-based, inferring single or multiple causes and/or timing relations from the knowledge of behavior of component models and their causal structure. The overall goal of this paper is to develop an automated deep reasoning methodology that exploits deep knowledge of structure and behavior of a system. We have proceeded by building a software environment that uses such knowledge to reason from advanced symbolic simulation techniques introduced by Chi and Zeigler. Such reasoning system has been implemented and tested on several examples in the domain of performance evaluation, and event-based control.

• Journal of Korean Society of Transportation
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• v.14 no.1
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• pp.101-116
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• 1996

Increased attention has been paid in recent years to the need of traffic management for alleviating urban traffic congestion. This paper presents a discrete event modeling and simulation framework for analyzing the traffic flow. Traffic simulation models can be classified as being either microscopic and macroscopic models. The discrete event modeling and simulation technique can be basically employed to describe the macroscopic traffic simulation model. To do this, we have employed the System Entity Structure/Model Base (SES/MB) framework which integrates the dynamic-based formalism of simulation with the symbolic formalism of AI. The SES/MB framework supports to hierarchical, modular discrete event modeling and simulation environment. We also adopt the Symbolic DEVS (Discrete Event System Specification) to developed the automated analysis methodology for generating optimal signal light policy. Several simulation tests will demonstrates the techniques.

• Communications for Statistical Applications and Methods
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• v.21 no.3
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• pp.225-234
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• 2014

We propose a novel hierarchical clustering for distribution valued dissimilarities. Analysis of large and complex data has attracted significant interest. Symbolic Data Analysis (SDA) was proposed by Diday in 1980's, which provides a new framework for statistical analysis. In SDA, we analyze an object with internal variation, including an interval, a histogram and a distribution, called a symbolic object. In the study, we focus on a cluster analysis for distribution valued dissimilarities, one of the symbolic objects. A hierarchical clustering has two steps in general: find out step and update step. In the find out step, we find the nearest pair of clusters. We extend it for distribution valued dissimilarities, introducing a measure on their order relations. In the update step, dissimilarities between clusters are redefined by mixture of distributions with a mixing ratio. We show an actual example of the proposed method and a simulation study.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.8 no.11
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• pp.69-77
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• 1985

The queue theory is based on the assumption that most system are normally assigned to stay under steady state. Therefore, the initial problem can be represented by a symbolic model but such a representation does not permit analysis of all the interesting alternatives. When the solution to the problem is thus restricted to a particular subclass of available alternatives, the symbolic model can be solved by mathematics to deduce which alternative is optimal. However, when be consider slightly more complicated alternatives, the analytic procedures become interactable. The purpose of this study is to show how a simulation model enable us to handle the more complicated system after examining the characteristics of the complications that negate more complicated system. Then construct a simulation model and compare the solution of simulation models with analytic methods.

• Proceedings of the Korea Society for Simulation Conference
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• 1992.10a
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• pp.7-7
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• 1992

Extending discrete event modelling formalisms to facilitate greater symbol manipulation capabilities is important to further their use in intelligent control and design of high autonomy systems. This paper defines an extension to the DEVS formalism that facilitates symbolic expression of discrete event times by extending the time base from the real numbers to the field of linear polynomials over the reals. A simulation algorithm is developed to generate the branching trajectories resulting from the underlying non-determinism. To efficiently manage linear polynomial constraints based on feasibility checking algorithm borrowed from linear programming. The extended formalism offers a convenient means to conduct multiple, simultaneous explorations of model behaviors. Examples of application are given with consideration on fault model analysis.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.3
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• pp.109-119
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• 1996

We propsoed a multiplexed optical correlation filter method for an optical parallel addition based on symbolic substitution. In the proposed mthod, we used redundant binary number which was easy to minimize the number of the symbolic substitution rules. We chose MACE filter which had very low sidelobes and good correlation peak compared with SDF filter as the optical correlation recognition filter and encoded input numbers properly to increase the discrimination capability. In order to minimize the number of symbolic substitution rules, sixteen input patterns were divided into six groups of the same addition results and six filters for recognizing the input patterns were used. these filters were multiplexed in two MMACE filter planes and the corresponding substitution method was proposed. Through the computer simulation, we confirmed the proposed method was suitable to implement the optical parallel adder.

• JSTS:Journal of Semiconductor Technology and Science
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• v.7 no.4
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• pp.221-228
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• 2007

In this paper, we propose a new symbolic simulation for scan chain diagnosis to solve the diagnosis resolution problem. The proposed scan chain fault simulation, called the SF-simulation, is able to analyze the effects caused by faulty scan cells in good scan chains. A new scan chain fault simulation is performed with a modified logic ATPG pattern. In this simulation, we consider the effect of errors caused by scan shifting in the faulty scan chain. Therefore, for scan chain diagnosis, we use the faulty information in good scan chains which are not contaminated by the faults while unloading scan out responses. The SF-simulation can tighten the size of the candidate list and achieve a high diagnosis resolution by analyzing fault effects of good scan chains, which are ignored by most previous works. Experimental results demonstrate the effectiveness of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.1
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• pp.269-280
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• 1996

We proposed a symbolic substitution method based on an optical correlator for an optical parallel addition. In the proposed symbolic substitution method, we used redundant binary number of the symbolic substitution rules as a number system and chose MAC3E filter which had very low sidelobes and good correlation peak compared with SDF filter as the optical correlation filter. We encoeded input numbers property to increase the discrimination capability and divided inpt patterns into 5 groups of the same addition results to minimize the number of symbolic substitution rules. Through the computer simulation, we confirmed the proposed method was suitable to implement the optical parallel adder.