• ETRI Journal
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• v.46 no.3
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• pp.461-472
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• 2024

We propose a network traffic prediction model based on linear and nonlinear model combination. Network traffic is modeled by an autoregressive moving average model, and the error between the measured and predicted network traffic values is obtained. Then, an echo state network is used to fit the prediction error with nonlinear components. In addition, an improved slime mold algorithm is proposed for reservoir parameter optimization of the echo state network, further improving the regression performance. The predictions of the linear (autoregressive moving average) and nonlinear (echo state network) models are added to obtain the final prediction. Compared with other prediction models, test results on two network traffic datasets from mobile and fixed networks show that the proposed prediction model has a smaller error and difference measures. In addition, the coefficient of determination and index of agreement is close to 1, indicating a better data fitting performance. Although the proposed prediction model has a slight increase in time complexity for training and prediction compared with some models, it shows practical applicability.

• Bulletin of the Korean Chemical Society
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• v.31 no.7
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• pp.1920-1926
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• 2010

Yoon et $al.^1$ presented an approximate mathmatical model to describe ammonia removal from an experimental batch reactor system with gaseous headspace. The development of the model was initially based on assuming instantaneous equilibrium between ammonia in the aqueous and gas phases. In the model, a "saturation factor, $\beta$" was defined as a constant and used to check whether the equilibrium assumption was appropriate. The authors used the trends established by the estimated $\beta$ values to conclude that the equilibrium assumption was not valid. The authors presented valuable experimental results obtained using a carefully designed system and the model used to analyze the results accounted for the following effects: speciation of ammonia between $NH_3$ and $NH^+_4$ as a function of pH; temperature dependence of the reactions constants; and air flow rate. In this article, an alternative model based on the exact solution of the governing mass-balance differential equations was developed and used to describe ammonia removal without relying on the use of the saturation factor. The modified model was also extended to mathematically describe the pH dependence of the ammonia removal rate, in addition to accounting for the speciation of ammonia, temperature dependence of reactions constants, and air flow rate. The modified model was used to extend the analysis of the original experimental data presented by Yoon et $al.^1$ and the results matched the theory in an excellent manner.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3656-3671
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• 2016

Most of the research in the area of wireless communications exclusively relies on simulations. Further, it is essential that the mobility management strategies and routing protocols should be validated under realistic conditions. Most appropriate mobility models play a pivotal role to determine, whether there is any subtle error or flaw in a proposed model. Simulators are the standard tool to evaluate the performance of mobility models however sometimes they suffer from numerous documented problems. To accomplish the widely acknowledged lack of formalization in this domain, a Coloured Petri nets (CPNs) based random direction mobility model for specification, analysis and validation is presented in this paper for wireless communications. The proposed model does not suffer from any border effect or speed decay issues. It is important to mention that capturing the mobility patterns through CPN is challenging task in this type of the research. Further, an appropriate formalism of CPNs supported to analyze the future system dynamic status. Finally the formal model is evaluated with the state space analysis to show how predefined behavioral properties can be applied. In addition, proposed model is evaluated based on generated simulations to track origins of errors during debugging.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.230-236
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• 2008

In this paper, a model-based stick-slip compensation for the micro-positioning is proposed using an enhanced stick-slip model based on statistical rough surface contact model. The smart structure is comprised with PZT (lead (Pb) zirconia (Zr) Titanate (Ti)) based stack actuator incorporating with the PID (Proportional-Integral-Derivative) control algorithm, mechanical displacement amplifier and positioning devices. For the stick-slip compensation, the elastic-plastic static friction model is used considering the elastic-plastic asperity contact in the rough surfaces statistically. Mathematical model of system for the positioning apparatus was derived from the dynamic behaviors of structural parts. PID feedback control algorithms with the developed stick-slip model as well as feedforward friction compensator are formulated for achieving the accurate positioning performance. Experimental results are provided to show the performances of friction control using the developed positioning apparatus.

• Journal of the Korean Society of Safety
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• v.32 no.3
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• pp.130-135
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• 2017

This study deal with the traffic accident. The purpose of this study is to develop the accident density models reflecting the transportation and socioeconomic characteristics based on 230 zones of Korea. In this study, The models which are tested to be statistically significant are developed through multiple linear regression analysis. The main research results are as follows. First, in the transportation-based model, road length, avenue ratio, number of intersections and tunnels are analyzed to be positive to the model, however, school zone is analyzed to be negative to the model. Second, in the socioeconomic-based model, population density, transportation vulnerable ratio, children and truck ratio are analyzed to be positive to the model. Finally, in the integrated models, road ratio, population density, transportation vulnerable ratio, children ratio, truck ratio and number of companies are analyzed to be positive, however, school zone is analyzed to be negative to the model. This results could be expected to give good implications to accident-reduction policy-making.

• Geomechanics and Engineering
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• v.10 no.1
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• pp.37-48
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• 2016

The hyperbolic stress-strain model has been shown to be valid for modeling nonlinear stress-strain behavior for rockfill materials. The Duncan-Chang nonlinear constitutive model was adopted to characterize the behavior of the modeled rockfill materials in this study. Accurately estimating the model parameters of rockfill materials is a key problem for simulating dam deformations during both the dam construction period and the dam operation period. In order to estimate model parameters, triaxial compression experiments of rockfill materials were performed. Based on a genetic algorithm, the constitutive model parameters of the rockfill material were determined from the triaxial compression experimental data. The investigation results show that the predicted strains provide satisfactory precision when compared with the observed strains and the strains forecasted by a gradient-based optimization algorithm. The effectiveness of the proposed inversion procedure of model parameters was verified by experimental investigation in a laboratory.

• The Journal of the Acoustical Society of Korea
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• v.22 no.8
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• pp.680-686
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• 2003

Digital waveguide model is a general method that is used in physical modeling of musical instruments. Wave motion is analyzed by time or by space in digital waveguide model. Because sampling is made via time, it is general that musical instrument model is described by wave motion of time. In this paper, we synthesized the musical instrument sound by adding instrument body model to the spatial based string model. In this way, we could improve sound quality and process musical instrument model's tone control variables effectively. We explained about delay error that happens in string and body in space based sampling and showed method to process fractional delay using FD (Fractional Delay)filter. Finally, we explained the relation between tone quality and number of delays. And we also compared the result with time base digital waveguide model.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.8
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• pp.863-874
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• 1999

세분화란 초기 원형 모델의 삼각형 메쉬를 여러 개의 작은 메쉬로 변환하는 기법으로, 간략화 된 모델을 다시 원상태로 표현하기 위해 사용된다. 기존의 보간에 의한 세분화는 전체 모델의 에지에 일률적으로 세분화를 적용하기 때문에, 효과가 적은 부분까지도 세분화가 수행하게 되어 효율이 떨어진다. 본 논문에서는 정점 변화율을 기반으로 에지를 선택하여 세분화를 수행한다. 따라서 원형 메쉬를 변환하여 세분화된 메쉬를 생성할 때, 모델의 각 부분들은 정점 변화율의 차이에 의해 서로 다른 세분화 정도를 가지게 된다. 이 과정을 통해 원형 모델의 곡률 특성이 반영된 세분화를 수행할 수 있게 되고, 전체 모델의 세분화 정도를 조정하는 것도 가능해진다. Abstract The subdivision is a mesh transformation, which makes an original triangle mesh to subdivided meshes. This method is used for recovering original model from simplified model. The existing subdivision based on interpolation is inefficient, because it is targeted for whole edges of mesh model. Therefore, this method applies to non-effective parts. In this paper the subdivision is executed by edge selection based on curvature. When original model is transformed to subdivided model by proposed method, the parts of model has different subdivision degrees by means of the averages of vertex curvature.Proposed method makes it enable subdivision, which deploy characteristics of curvatures of original model and adjusting a degree of subdivision in whole model.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.103-109
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• 2001

Soft sensor is an effective method to deal with the estimation of variables, which are difficult to measure because of the reasons of economy or technology. Fuzzy logic system can be used to develop the soft sensor model by infinite rules, but the fuzzy dividing of variable sets is a key problem to achieve an accurate fuzzy logic model, In this paper, we proposed a new method to develop soft sensor model based on fuzzy neural network. First, using a novel method to divide the variable fuzzy sets by the process input and output data. Second, developing the fuzzy logic model based on that fuzzy set dividing. After that, expressing the fuzzy system with a fuzzy neural network and getting the initial soft sensor model based FNN. Last, adjusting the relative parameters of soft sensor model by the BP learning method. The effectiveness of the method proposed and the preferable generalization ability of soft sensor model built are demonstrated by the simulation.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.575-586
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• 2008

The main objective of this paper is to develop an improved model for the analysis of liquefaction potential and to predict excess pore pressure (EPP) using the proposed model that can simulate behavior of saturated sand under earthquake loading conditions. The damage concept is adopted for the development of the proposed model. For the development of the model, a general formulation based on experimental results and damage potential using cumulative absolute velocity (CAV) is proposed for a more realistic description of dynamic responses of saturated sand. Undrained dynamic triaxial tests are conducted using earthquake loading conditions. Based on test results, the NCER-NCW function in terms of $w_d$ and CAV is developed. Procedure for the evaluation of EPP and determination of model parameters for the proposed model is presented as well. For the determination of initial liquefaction, the minimum curvature method using the NCS-NCW curve is proposed. It is observed that predicted initial liquefaction using the proposed method agrees well with measured initial liquefaction. From results of additional undrained dynamic triaxial tests, it is seen that predicted EPP generation using the proposed model agrees well with measured results for earthquake loading cases.