• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.446-449
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• 1997

We propose a control law in discrete time domain of the bilateral feedback teleoperation system using neural network and the reference model type of adaptive control. Different from traditional teleoperation systems, the transmission time delay irregularly changes. The proposed control method controls master and slave systems through identification of master and slave models using neural networks.

• Journal of the Korea Society for Simulation
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• v.5 no.2
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• pp.41-58
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• 1996

The Discrete Event Systems Specification(DEVS) formalism specifies a discrete event system in a hierarchical, modular form. This paper presents a distributed simulation environment D-DEVSim++ for models specified by the DEVS formalism. D-DEVSim++ employs a new simulation scheme which is a hybrid algorithm of the hierarchical simulation and Time Warp mechanisms. The scheme can utilize both the hierarchical scheduling parallelism and the inherent parallelism of DEVS models. This hierarchical scheduling parallelism is investigated through analysis. Performance of the proposed methodology is evaluated through benchmark simulation on a 5-dimensional hypercube parallel machine. The performance results indicate that the methodology can achieve significant speedup. Also, it is shown that the analyzed speedup for the hierarchical scheduling time corresponds the experiment.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.645-652
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• 2006

In this paper a new type of filter, called the $H_2/H_{\infty}$ FIR filter, is proposed for discrete-time state space signal models. The proposed filter requires linearity, unbiased property, FIR structure, and independence of the initial state information in addition to the performance criteria in both $H_2$ and $H_{infty}$ sense. It is shown that $H_2,\;H_{\infty}$, and $H_2/H_{\infty}$ FIR filter design problems can be converted into convex programming problems via linear matrix inequalities (LMIs) with a linear equality constraint. Simulation studies illustrate that the proposed FIR filter is more robust against temporary uncertainties and has faster convergence than the conventional IIR filters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.452-474
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• 2010

Formidable growth of Internet technologies has revealed challenging issues about its scale and performance evaluation. Modeling and simulation play a central role in the evaluation of the behavior and performance of the large-scale network systems. Large numbers of nodes affect simulation performance, simulation execution time and scalability in a weighty manner. Most of the existing simulators have numerous problems such as size, lack of system theoretic approach and complexity of modeled network. In this work, a scalable discrete-event modeling approach is described for studying networks' scalability and performance traits. Key fundamental attributes of Internet and its protocols are incorporated into a set of simulation models developed using the Discrete Event System Specification (DEVS) approach. Large-scale network models are simulated and evaluated to show the benefits of the developed network models and approaches.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.1-10
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• 2020

This study investigates the problem of outlier detection based on discrete wavelet transform in the context of time series data where the identification and treatment of outliers constitute an important component. An outlier is defined as a data point that deviates so much from the rest of observations within a data sample. In this work we focus on the application of the traditional method suggested by Tukey (1977) for detecting outliers in the closed price series of the Saudi Arabia stock market (Tadawul) between Oct. 2011 and Dec. 2019. The method is applied to the details obtained from the MODWT (Maximal-Overlap Discrete Wavelet Transform) of the original series. The result show that the suggested methodology was successful in detecting all of the outliers in the series. The findings of this study suggest that we can model and forecast the volatility of returns from the reconstructed series without outliers using GARCH models. The estimated GARCH volatility model was compared to other asymmetric GARCH models using standard forecast error metrics. It is found that the performance of the standard GARCH model were as good as that of the gjrGARCH model over the out-of-sample forecasts for returns among other GARCH specifications.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.3
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• pp.59-65
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• 2019

In many industries, particle packing is adopted quite frequently. In the particle packing process, the Discrete Element Method (DEM) can analyze the multi-collision of particles efficiently. Two types of contact models are frequently used for the DEM. One is the linear spring model, which has the fastest calculation time, and the other is the Hertz-Mindlin model, which is the most frequently used contact model employing the DEM. Meanwhile, very tiny particles in the micrometer order are used in modern industries. In the micro length order, surface force is important to decreased particle size. To consider the effect of surface force in this study, we performed a simulation with the Hertz-Mindlin model and added the Johnson-Kendall-Roberts (JKR) theory depicting surface force with surface energy. In addition, three contact models were compared with several parameters. As a result, it was found that the JKR model has larger residual stress than the general contact models because of the pull-off force. We also validated that surface force can influence particle behavior if the particles are small.

• Journal of Advanced Navigation Technology
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• v.24 no.3
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• pp.184-191
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• 2020

Avionics System Integration Laboratory is the integrated test environment for integration and verification of avionics systems. When real equipment can not be used in the laboratory for various reasons, software models should be needed. Because there hasn't been any standardized method for the models so that it is difficult to reuse the developed models, the need for a framework to develop the avionics software models was emerged. We adopted DEVS(discrete event system specification) formalism as the standardized modeling method for the avionics software models. Due to DEVS formalism is based on event-driven algorithm, it doesn't accord a legacy system which has sequential and periodic algorithms. In this paper, we propose real-time event-driven modeling and simulation method for SIL to overcome these restrictions and to maximize reusability of avionics models through the analysis of the characteristics and the limitations of avionics models.

• Tunnel and Underground Space
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• v.11 no.2
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• pp.156-166
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• 2001

A stochastic continuum(SC) modeling technique was developed to simulate the groundwater flow pathway in fractured rocks. This model was developed to overcome the disadvantageous points of discrete fracture network(DFN) modes which has the limitation of fracture numbers. Besides, SC model is able to perform probabilistic analysis and to simulate the conductive groundwater pathway as discrete fracture network model. The SC model was formulated based on the discrete fracture network(DFN) model. The spatial distribution of permeability in the stochastic continuum model was defined by the probability distribution and variogram functions defined from the permeabilities of subdivided smaller blocks of the DFN model. The analysis of groundwater travel time was performed to show the consistency between DFN and SC models by the numerical experiment. It was found that the stochastic continuum modes was an appropriate way to provide the probability density distribution of groundwater velocity which is required for the probabilistic safety assessment of a radioactive waste disposal facility.

• Korean Journal of Mathematics
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• v.29 no.2
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• pp.371-386
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• 2021

This paper investigates two discrete time queueing inventory models with positive service time and lead time. Customers arrive according to a Bernoulli process and service time and lead time follow geometric distributions. The first model under discussion based on replenishment of order upto S policy where as the second model is based on order placement by a fixed quantity Q, where Q = S - s, whenever the inventory level falls to s. We analyse this queueing systems using the matrix geometric method and derive an explicit expression for the stability condition. We obtain the steady-state behaviour of these systems and several system performance measures. The influence of various parameters on the systems performance measures and comparison on the cost analysis are also discussed through numerical example.

• Smart Structures and Systems
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• v.25 no.5
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• pp.569-580
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• 2020

The identification of delays and delay compensation are critical problems in real-time hybrid simulations (RTHS). Conventional delay compensation methods are mostly based on the assumption of a constant delay. However, the system delay may vary during tests owing to the nonlinearity of the loading system and/or the behavioral variations of the specimen. To address this issue, this study presents an adaptive delay compensation method based on a discrete model of the loading system. In particular, the parameters of this discrete model are identified and updated online with the least-squares method to represent a servo hydraulic loading system. Furthermore, based on this model, the system delays are compensated for by generating system commands using the desired displacements, achieved displacements, and previous displacement commands. This method is more general than the existing compensation methods because it can predict commands based on multiple displacement categories. Moreover, this method is straightforward and suitable for implementation on digital signal processing boards because it relies solely on the displacements rather than on velocity and/or acceleration data. The virtual and real RTHS results show that the studied method exhibits satisfactory estimation smoothness and compensation accuracy. Furthermore, considering the measurement noise, the low-order parameter models of this method are more favorable than that the high-order parameter models.