• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.2
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• pp.235-247
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• 2014

Based on two dimensional model partition method proposed in Part 1, Part 2 provides detailed model specification and implementation. To mathematically delineate a model's behaviors and interactions among them, we extend the DEVS (Discrete Event Systems Specification) formalism and newly propose CE-DEVS (Combat Entity-DEVS) for an upper abstraction sub-model of a combat entity model. The proposed CE-DEVS additionally define two sets and one function to reflect essential semantics for the model's behaviors explicitly. These definitions enable us to understand and represent the model's behaviors easily since they eliminate differences of meaning between real-world expressions and model specifications. For model implementation, upper abstraction sub-models are implemented with DEVSim++, while the lower sub-models are realized using the C++ language. With the use of overall modeling techniques proposed in Part 1 and 2, we can conduct constructive simulation and assess factors about combat logics as well as battle field functions of the next-generation combat entity, minimizing additional modeling efforts. From the anti-torpedo warfare experiment, we can gain interesting experimental results regarding engagement situations employing developing weapons and their tactics. Finally, we expect that this work will serve an immediate application for various engagement warfare.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.760-772
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• 1999

The CAN is a serial communication protocol for distributed real-time control and automation systems. Data generated from field devices in the distributed control of power plant are classified into three categories: real-time event data, real-time control data, non-real-time data. These data share a CAN medium. If the traffic of the CAN protocol is not efficiently controlled, performance requirements of the power plant system could not be satisfied. This paper proposes a bandwidth allocation algorithm that can be applicable to the CAN protocol. The bandwidth allocation algorithm not only satisfies the performance requirements of the real-time systems in the power plant but also fully utilizes the bandwidth of CAN. The bandwidth allocation algorithm introduced in this paper is validated using the integrated discrete-event/continuous-time simulation model which comprises the CAN network and distributed control system of power plant.

• Journal of KIISE
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• v.42 no.7
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• pp.823-833
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• 2015

Hybrid system is a dynamic system that is composed of both a continuous and discrete system, suitable for automobile, avionic and defense systems. Various modeling languages and their supporting tools have been proposed and used in the hybrid system. The languages and tools have specific characteristics for their purpose. Electronics and Telecommunications Research Institute (ETRI) proposed a hybrid system modeling language, ECML (ETRI CPS Modeling Language). ECML extends DEV&DESS (Differential Event and Differential Equation Specified System) formalism with consideration of CPS (Cyber-Physical System), which supports modeling and simulation. In this paper, we introduce ECML and suggest a formal definition. The case study specifies a simple vehicle model using the suggested formal definition.

• Journal of Korean Institute of Industrial Engineers
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• v.12 no.1
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• pp.119-131
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• 1986

Described in this paper is a modelling methodology for mass production system simulation. The mass production system under consideration consists of various types of flow lines, special purpose production facilities, conveyor lines, palletized carts, and storage facilities. This type of production system is typical in home appliance industry, automobile industry, footwear industry, etc. where a variety of product mix are mass-produced. The modelling methodology is based on the "discrete-event formalism", and an "activity-oriented world view" is adopted to formalize the system description. A distinctive feature of the modelling methodology is that only the static structure (ie, system components) is included in the fixed model. The dynamic structure of the system is specified through a "data-driven" mechanism, which is an extension of the "experimental frame" concept. Each type of system components (ie, flow line, conveyors, carts, etc.) is formally modeled by using Activity Cycle Diagrams. The issue of "model structuring" is also addressed. The modeling methodology has been successfully applied in a real simulation study of a mass production system.

• The KIPS Transactions:PartA
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• v.13A no.5 s.102
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• pp.445-454
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• 2006

We introduce a family of simulators for I/O-intensive distributed or parallel applications, and a methodology that permits selecting the most efficient simulator meeting a given user-defined accuracy requirement. This methodology consists of a series of tests to choose an appropriate simulation based on the attributes of the application. In addition, each simulator provides two estimates of application execution time: the minimum expected time and the maximum. We present the results of applying our methodology to existing applications, and show that we can accurately simulate applications tens to hundreds of tunes faster than the application execution times.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.1
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• pp.1218-1225
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• 2001

This paper presents a design procedure for the supervisory controller(SC) of the high-speed train car. The proposed SC manages control logic and scenario of the overall train system, and monitors input/output signals among the sub-controllers in the system, The roles and functions of each sub-control system are defined, and the interfaces among the control systems are developed. Train control system is modeled with automata, and the model is implemented into a program using a computer-aided software engineering(CASE) tool, Object GEODE, The designed SC is verified and evaluated by using simulation. The SC is shown to successfully perform the designed functions without any errors.

• 한국디지털정책학회:학술대회논문집
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• 2006.12a
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• pp.327-336
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• 2006

The odds ratio is used for assessing the disease-exposure association, because epidemiological data for case-control of cohort studies are often summarized into 2 ${\times}$ 2 tables. In this paper we define the odds ratio function(ORF) that extends odds ratio used on discrete survival event data to continuous survival time data and propose estimation procedures with censored data. The first one is a nonparametric estimator based on the Nelson-Aalen estimator of comulative hazard function, and the others are obtained using the concept of empirical odds ratio. Asymptotic properties such as consistency and weak convergence results are also provided. The ORF provides a simple interpretation and is comparable to survival function or comulative hazard function in comparing two groups. The mean square errors are investigated via Monte Carlo simulation. The result are finally illustrated using the Melanoma data.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.4
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• pp.46-55
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• 1997

This paper presents the development of intelligent performance management of computer communication networks for larger-scale integrated systems and the demonstration of its efficacy using computer simula- tion. The innermost core of the performance management is based on fuzzy set theory. This fuzzy perfor- mance manager has learning ability by using principles of neuro-fuzzy model, neuralnetwork, genetic algo- rithm(GA). Two types of performance managers are described in this paper. One is the Neuro-Fuzzy Per- formance Manager(NFPM) of which learning ability is based on the conventional gradient method, and the other is GA-based Neuro-Fuzzy Performance Manager(GNFPM)with its learning ability based on a genetic algorithm. These performance managers have been evaluated via discrete event simulation of a computer network.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.6
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• pp.433-440
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• 2000

To flexibly evaluate performance and reliability of a real-time system which is intrinsically characterized by stringent timing constraints to generate correct responses, we propose fuzzyrandom variables and build a discrete event model embedded with fuzzy-random variables. Also, we adapt fuzzy-variables to a path-space approach, which derives the upper and lower bounds of reliability by using a semi-Markov model that explicitly contains the deadline information. Consequently, we propose certain formulas of state automata properly transformed by fuzzy-random variables, and present numerical examples applying the formulas to RTP(Rapid Thermal Process) to show that a complex system can be properly evaluated based on this model by computer simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7B
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• pp.1279-1288
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• 1999

DEVSim++ is a C++ based, object-oriented modeling/simulation environment which realizes the hierarchical, modular DEVS formalism for discrete event systems specification. The paper describes a methodology for performance modeling and analysis of an ATM-based network system within the DEVSim++ environment. The methodology develops performance models for the system using the DEVS framework and implement the models in C++. Performance indices measured are the length of queues located at connection of the system and cell waiting times with respect to QoS grades for a network bandwidth of 155 Mbps.