• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.4
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• pp.121-130
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• 2012

In this paper, the structure of the Aladdin system was modeled by Petri nets for performance evaluation of 40G bps class Aladdin system which was developed in ETRI as the high-speed DDoS defensive tool. The efficiency analysis of the system architecture according to the input traffic of the Aladdin system was performed based on the modeling.

• Computers and Concrete
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• v.16 no.4
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• pp.569-585
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• 2015

Various computational tools are available for modeling highly nonlinear structural engineering problems that lack a precise analytical theory or understanding of the phenomena involved. This paper adopts a fairly simple nonparametric adaptive regression algorithm known as multivariate adaptive regression splines (MARS) to model the nonlinear interactions between variables. The MARS method makes no specific assumptions about the underlying functional relationship between the input variables and the response. Details of MARS methodology and its associated procedures are introduced first, followed by a number of examples including three practical structural engineering problems. These examples indicate that accuracy of the MARS prediction approach. Additionally, MARS is able to assess the relative importance of the designed variables. As MARS explicitly defines the intervals for the input variables, the model enables engineers to have an insight and understanding of where significant changes in the data may occur. An example is also presented to demonstrate how the MARS developed model can be used to carry out structural reliability analysis.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.664-667
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• 1997

For higher component density per chip, it is necessary to identify and control the semiconductor manufacturing process more stringently. Recently, neural networks have been identified as one of the most promising techniques for modeling and control of complicated processes such as plasma etching process. Since wafer states after each run using identical recipe may differ from each other, conventional neural network models utilizing input factors only cannot represent the actual state of process and equipment. In this paper, in addition to the input factors of the recipe, real-time tool data are utilized for modeling of 64M DRAM s-poly plasma etching process to reflect the actual state of process and equipment. For real-time tool data, we collect optical emission spectroscopy (OES) data. Through principal component analysis (PCA), we extract principal components from entire OES data. And then these principal components are included to input parameters of neural network model. Finally neural network model is trained using feed forward error back propagation (FFEBP) algorithm. As a results, simulation results exhibit good wafer state prediction capability after plasma etching process.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.773-780
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• 1999

A digital tracking controller is proposed for micro electrostatic actuator with input nonlinearity, where disturbance observer is utilized in cooperation with inverse function. Generally the disturbance observer is announced to be robust to modeling uncertainty, and external disturbance. But, when the nonlinearity exists in the systems, the disturbance observer may not directly be applied to that system, because the nonlinearity may destabilize the overall system. Therefore, first, we linearize the nonlinear input characteristics of micro electrostatic actuator by the use of inverse function. Secondly, we apply disturbance observer to approximately linearized system for eliminating the residuals of nonlinearity and the modeling uncertainty. Then, we get the good properties of the disturbance rejection as well as the robustness due to the own nature of disturbance observer. In this case, we propose a sufficient condition for the robust stability of overall systems. Furthermore, we discuss the problem that may be exposed when disturbance observer is applied to the internally stable system with saturation, and analyze two methods to overcome input saturation problem in the sense of internal stability. Simulations have been carried out to show the effectiveness of the proposed controller.

• Journal of the Korean Society for Railway
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• v.18 no.3
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• pp.194-202
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• 2015

In this paper, dynamic modeling with viscoelastic properties of a human body resting on a seat is presented to quantitatively analyze ride quality of passengers exposed to vertical vibrations. In describing the motions of a seated body, a 5 degree-of-freedom multibody model from the literature is investigated. The viscoelastic characteristics of seats used in railway vehicles are mathematically formulated with nonlinear stiffness characteristics and convolution integrals representing time delay terms. Transfer functions for the floor input are investigated and it is found that these are different in accordance with the input magnitude due to nonlinear characteristics of the seat. Measured floor input at the railway vehicle is used to analyze realistic human vibration characteristics. Frequency weighted RMS acceleration values are calculated and the effects of the seat design parameters on the frequency weighted RMS acceleration values are presented.

• Journal of Integrative Natural Science
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• v.14 no.4
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• pp.183-188
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• 2021

Collaborative filtering is one of the commonly used methods in the web recommendation system. Numerous researches on the collaborative filtering proposed the numbers of measures for enhancing the accuracy. This study suggests the movie recommendation system applied with Word2Vec and ensemble convolutional neural networks. First, user sentences and movie sentences are made from the user, movie, and rating information. Then, the user sentences and movie sentences are input into Word2Vec to figure out the user vector and movie vector. The user vector is input on the user convolutional model while the movie vector is input on the movie convolutional model. These user and movie convolutional models are connected to the fully-connected neural network model. Ultimately, the output layer of the fully-connected neural network model outputs the forecasts for user, movie, and rating. The test result showed that the system proposed in this study showed higher accuracy than the conventional cooperative filtering system and Word2Vec and deep neural network-based system suggested in the similar researches. The Word2Vec and deep neural network-based recommendation system is expected to help in enhancing the satisfaction while considering about the characteristics of users.

• Journal of Drive and Control
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• v.19 no.2
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• pp.1-10
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• 2022

Field robots operate in various areas, including construction, agriculture, forestry and manufacturing. Typical tasks of field robots used in various areas include excavation, flattening, and demolition. Such tasks are often accomplished in narrow alleys or indoors. In the case of field robots, there is a limit to working in a small space. Thus, to compensate for these shortcomings, many field robots equipped with Tiltrotators have recently been observed. The advantages of Tiltrotator are improved task efficiency and reduced operating time by reducing unnecessary behavior. We need simulation models that can improve the ability of new people to work and simulate tasks in advance. Thus, in this paper, we developed a simscape-based simulation model and modeling of 6DOF systems for field robots equipped with Tiltrotator. Dynamic modeling of field robot 3D models using Simcape multibody and hydraulic systems of field robots using Simcape Hydraulics were modeled. We applied a PID controller to create a control system that operates along the input angle. Simulation results show that errors occur when comparing input and output angles, but overall, they move along input angles.

• Journal of the Korean Home Economics Association
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• v.44 no.2 s.216
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• pp.127-135
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• 2006

This paper suggests guidelines for virtual clothes modeling and draping software suitable for clothes designers. We first analyze Maya Cloth, which is widely used in game and animation fields, and which has been adopted by Pad System as a 3D cloth draping system. We then discuss what functions and procedures would improve Maya Cloth to assist designers in being able to create the clothes they have conceptualized. While Maya Cloth has many good functions and features forvirtual cloth modeling and draping, it treats input 2D patterns as approximat and it creates 3D clothes by considering other factors such as the 3D body model. As a result, it is hard for clothes designers to control the shape of the 3D clothes by changing 2D patterns. Furthermore, Maya Cloth does not handle seamlines satisfactorily. We suggest that the following new features should be added to Maya Cloth : respecting the input 2D patterns, handling seamlines, and controlling the shape of the clothes in 3D space.

• Journal of KIBIM
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• v.4 no.3
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• pp.1-9
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• 2014

As BIM application continues to increase in civil engineering, in this study, 3D information model for RC(Reinforced Concrete) bridge pylon was developed and verified its effectiveness at the structural-design stage. To define 3D information model of RC A-Type pylon, characteristics of pylon were analyzed and 3D model structure was constructed. The 3D information model, one of the core product of BIM, manages all information generated during all life-cycle of a structure and consequently maximizes the efficiency of utilizing information. Also, this study proposes interface module between input data in structural analysis and 3D model of RC pylon. The module can create the input data for non-linear structural analysis. It is essential to study on method of developing 3D information model and propose a structural analysis model by utilizing 3D model for the effective use of BIM techniques in construction industry. The results of this study can be used as the base data for developing the 3D information model of RC pylon in the structural analysis field.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2008.10a
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• pp.404-405
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• 2008