• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.12
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• pp.1152-1162
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• 2008

This paper deals with the State-Dependent Riccati Equation (SDRE) technique for the design of helicopter nonlinear flight controllers. Since the SDRE controller requires a linear system-like structure for nonlinear motion equations, a state-dependent coefficient (SDC) factorization technique is developed in order to derive the conforming structure from a general nonlinear helicopter dynamic model. Also on-line numerical methods of solving the algebraic Riccati equation are investigated to improve the numerical efficiency in designing the SDRE controllers. The proposed method is applied to trajectory tracking problems of the helicopter and computational tips for a real time application are proposed using a high fidelity rotorcraft mathematical model.

• Communications for Statistical Applications and Methods
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• v.21 no.6
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• pp.521-528
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• 2014

A stochastic Gompertz diffusion model for tumor growth is a topic of active interest as cancer is a leading cause of death in Korea. The direct maximum likelihood estimation of stochastic differential equations would be possible based on the continuous path likelihood on condition that a continuous sample path of the process is recorded over the interval. This likelihood is useful in providing a basis for the so-called continuous record or infill likelihood function and infill asymptotic. In practice, we do not have fully continuous data except a few special cases. As a result, the exact ML method is not applicable. In this paper we proposed a method of parameter estimation of stochastic Gompertz differential equation via Markov chain Monte Carlo methods that is applicable for several data structures. We compared a Markov transition data structure with a data structure that have an initial point.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.130-133
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• 2000

In this paper, a new design methodology named FNNN(Fuzzy Polynomial Neural Network) algorithm is proposed to identify the structure and parameters of fuzzy model using PNN(Polynomial Neural Network) structure and a fuzzy inference method. The PNN is the extended structure of the GMDH(Group Method of Data Handling), and uses several types of polynomials such as linear, quadratic and modified quadratic besides the biquadratic polynomial used in the GMDH. The premise of fuzzy inference rules defines by triangular and gaussian type membership function. The fuzzy inference method uses simplified and regression polynomial inference method which is based on the consequence of fuzzy rule expressed with a polynomial such as linear, quadratic and modified quadratic equation are used. Each node of the FPNN is defined as fuzzy rules and its structure is a kind of neuro-fuzzy architecture Several numerical example are used to evaluate the performance of out proposed model. Also we used the training data and testing data set to obtain a balance between the approximation and generalization of proposed model.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2946-2948
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• 2000

In this paper, we proposed the Fuzzy Polynomial Neural Networks(FPNN) model with fuzzy activation node. The proposed FPNN structure is generated from the mutual combination of PNN(Polynomial Neural Networks) structure and fuzzy inference system. The premise of fuzzy inference rules defines by triangular and gaussian type membership function. The fuzzy inference method uses simplified and regression polynomial inference method which is based on the consequence of fuzzy rule expressed with a polynomial such as linear, quadratic and modified quadratic equation are used. The structure of FPNN is not fixed like in conventional Neural Networks and can be generated. The design procedure to obtain an optimal model structure utilizing FPNN algorithm is shown in each stage. Gas furnace time series data used to evaluate the performance of our proposed model.

• 한국연소학회:학술대회논문집
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• 2012.11a
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• pp.139-140
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• 2012

In laminar non-premixed flame situation, the flamelet model is not suitable for simulating slow processor like soot and radiation. Thus in this study, we overcome this limitation by using the transient flamelet model. Also, for soot formation on laminar non-premixed flame, transient flamelet coupled with two-equation soot model has been adopted due to its inherent advantages in terms of accuracy and availability. Based on numerical results, the detailed discussion has been made for the precise structure and soot formation processes in the pressurized methane air flames.

• The Journal of the Acoustical Society of Korea
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• v.25 no.1E
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• pp.1-7
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• 2006

This study examines the reflection characteristic of a thin transition layer of the ocean bottom showing variability with respect to depth. In order to model the surficial sediment simply, we reduce the Biot model to the depth dependent wave equation for the pseudo fluid using the fluid approximation (weak frame approximation). From the reduced equation, the difference between the inherent frequency dependency of the reflection and the frequency dependency resulting from a thin transition layer is investigated. Using Tang's depth porosity profile model of the surficial sediment [D. Tang et al., IEEE J. Oceanic Eng., vol.27(3), 546-560(2002)], we numerically simulated the reflection loss and investigated the contribution from both frequency dependencies. In addition, the effects of different sediment type and varying depth structure of the sediment are discussed.

• Journal of Korean Elementary Science Education
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• v.34 no.1
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• pp.1-14
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• 2015

The variety of learners include students with disabilities and general students, and an ongoing focus of inclusive education research is non-discrimination. As part of integrated education, UDL (Universal Design for Learning) for students with disabilities supports a practical approach, participation, and advancement to improve learning opportunities for all students. The purpose of this study was to examine the effects of using UDL in science classes. The dependent variables of this study were academic achievement in science, scientific attitude, and scientific motivation. In this study, the experimental groups were 9 people in the 5th grade and 11 people in 6th grade. The experimental groups were taught science class using UDL. In order to analyze the learning outcomes, the structure equation model was performed. The results of this study were as follows: First, the science achievement of learning outcomes of the science class applying UDL directly affected both scientific attitude and scientific motivation. Second, the scientific attitude of learning outcomes of the science class applying UDL directly did not affect scientific motivation. According to these results, learning outcomes for science achievement of the science class applying UDL showed that UDL affected both general students and students with disabilities. To summarize the analysis of learning outcomes, science achievement directly affected both scientific attitude and scientific motivation while scientific attitude did not affect scientific motivation. This study offered a specific implementation method for integrated education. Using the structure equation model for analyzing the effect has more significance.

• Journal of Mechanical Science and Technology
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• v.15 no.10
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• pp.1356-1368
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• 2001

In this paper, the model reference adaptive control (MRAC) of a flexible structure is investigated. Any mechanically flexible structure is inherently distributed parameter in nature, so that its dynamics are described by a partial, rather than ordinary, differential equation. The MRAC problem is formulated as an initial value problem of coupled partial and ordinary differential equations in weak form. The well-posedness of the initial value problem is proved. The control law is derived by using the Lyapunov redesign method on an infinite dimensional filbert space. Uniform asymptotic stability of the closed loop system is established, and asymptotic tracking, i. e., convergence of the state-error to zero, is obtained. With an additional persistence of excitation condition for the reference model, parameter-error convergence to zero is also shown. Numerical simulations are provided.

• International Journal of Highway Engineering
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• v.17 no.3
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• pp.117-124
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• 2015

PURPOSES : The purpose of this study is to verify traffic accident injury severity factors for elderly drivers and the relative relationship of these factors. METHODS : To verify the complicated relationship among traffic accident injury severity factors, this study employed a structural equation model (SEM). To develop the SEM structure, only the severity of human injuries was considered; moreover, the observed variables were selected through confirmatory factor analysis (CFA). The number of fatalities, serious injuries, moderate injuries, and minor injuries were selected for observed variables of severity. For latent variables, the accident situation, environment, and vehicle and driver factors were respectively defined. Seven observed variables were selected among the latent variables. RESULTS : This study showed that the vehicle and driver factor was the most influential factor for accident severity among the latent factors. For the observed variable, the type of vehicle, type of accident, and status of day or night for each latent variable were the most relative observed variables for the accident severity factor. To verify the validity of the SEM, several model fitting methods, including ${\chi}^2/df$, GFI, AGFI, CFI, and others, were applied, and the model produced meaningful results. CONCLUSIONS : Based on an analysis of results of traffic accident injury severity for elderly drivers, the vehicle and driver factor was the most influential one for injury severity. Therefore, education tailored to elderly drivers is needed to improve driving behavior of elderly driver.

• Structural Engineering and Mechanics
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• v.44 no.5
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• pp.585-600
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• 2012

This paper presents a Modified Tikhonov Regularization (MTR) method in model updating for damage identification with model errors and measurement noise influences consideration. The identification equation based on sensitivity approach from the dynamic responses is ill-conditioned and is usually solved with regularization method. When the structural system contains model errors and measurement noise, the identified results from Tikhonov Regularization (TR) method often diverge after several iterations. In the MTR method, new side conditions with limits on the identification of physical parameters allow for the presence of model errors and ensure the physical meanings of the identified parameters. Chebyshev polynomial is applied to approximate the acceleration response for moderation of measurement noise. The identified physical parameter can converge to a relative correct direction. A three-dimensional unsymmetrical frame structure with different scenarios is studied to illustrate the proposed method. Results revealed show that the proposed method has superior performance than TR Method when there are both model errors and measurement noise in the structure system.