• Journal of the Korean Data and Information Science Society
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• 제7권1호
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• pp.69-78
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• 1996

Consider a natural model for stochastic flow systems is Brownian motion, which is Brownian motion on the positive real line with constant drift and constant diffusion coefficient, modified by an impenetrable reflecting barrier at $x_{0}$. In this paper, we investigate the joint distribution functions and study on the distribution of the first-passage time. Also we find out the distribution of ${\mu}-RBMPx_{0}$.

• 대한기계학회논문집A
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• 제25권4호
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• pp.582-591
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• 2001

It is known that the reduced integration, modified shape function, anisoparametric and non-conforming element can reduce the error induced by stiffness locking phenomenon in the finite element analysis. In this study, we propose new anisoparametric curved beam element. The new element based on reduced minimization theory is composed of different shape functions in each displacement field. By the substitution of this modified shape function, the unmatched coefficient that cause stiffness locking in the constraint energy is eliminated. To confirm the availability of this new model, we performed numerical tests for a simple model. As a result of numerical test, the undulate stress patterns are disappeared in static analysis, and displacements and stresses are close to exact solution. Not only in the static analysis but also in the eigen analysis of free vibrated curved beam model, this element shows successful convergent results.

• 전기학회논문지
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• 제58권5호
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• pp.1050-1056
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• 2009

Heart Rate Variability(HRV) is a parameter that represents monitoring variability of time intervals between R-peak in electrocardiography. HRV serves to various applications, such as indices of autonomic functions, prediction of cardiac sudden death, assessment of stress and emotional, etc. However, as measuring R-peak in ECG needs at least 3-electrodes, and it is inconvenient for end users. In this paper, we suggested the modified laplacian electrodes for measuring HRV at one-point, which are producted by MEMS fabrication and have the two circular electrodes on the pad. For optimal position and direction, we performed an experiment that compared with pearson correlation coefficient and the amplitude of signals, between standard lead II and proposed electrodes. We analyzed the HRV parameters, such as standard deviation of the NN interval(SDNN), high frequency(HF), low frequency(LF), LF/HF ratio. The result showed that the average correlation coefficient and amplitude are 0.967 and 0.685 mVpp at the position 2. The coeffiecient correlation between the standard HRV and proposed electrode-HRV is 0.999

• 한국해안·해양공학회논문집
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• 제21권3호
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• pp.224-229
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• 2009

케이슨식 안벽의 Level I 신뢰성설계를 위한 부분안전계수를 산정하였다. 일계신뢰도법에 의한 부분안전계수는 한계상태함수의 확률변수에 대한 민감도, 목표신뢰도지수, 확률특성치 및 설계특성치 등의 함수로써 표현하였으며 전면조위와 잔류수위에 대해서는 현행설계법과의 연계성을 유지하기 위하여 수정부분안전계수를 새롭게 정의하였다. 수치해석을 통하여 목표신뢰도지수에 대한 부분안전계수를 산정하였으며 지진계수의 확률분포는 극치분포를 사용하였다. 지진계수의 설계치를 적용함에 있어서 재현주기가 길수록 부분안전계수가 작게 산정됨을 확인하였다.

• 한국농공학회논문집
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• 제63권1호
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• pp.103-116
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• 2021

Analysis of runoff is substantial for effective water management in the watershed. Runoff occurs by reaction of a watershed to the rainfall and has non-linearity and uncertainty due to the complex relation of weather and watershed factors. ANN (Artificial Neural Network), which learns from the data, is one of the machine learning technique known as a proper model to interpret non-linear data. The performance of ANN is affected by the ANN's structure, the number of hidden layer nodes, learning rate, and activation function. Especially, the activation function has a role to deliver the information entered and decides the way of making output. Therefore, It is important to apply appropriate activation functions according to the problem to solve. In this paper, ANN models were constructed to estimate runoff with different activation functions and each model was compared and evaluated. Sigmoid, Hyperbolic tangent, ReLU (Rectified Linear Unit), ELU (Exponential Linear Unit) functions were applied to the hidden layer, and Identity, ReLU, Softplus functions applied to the output layer. The statistical parameters including coefficient of determination, NSE (Nash and Sutcliffe Efficiency), NSEln (modified NSE), and PBIAS (Percent BIAS) were utilized to evaluate the ANN models. From the result, applications of Hyperbolic tangent function and ELU function to the hidden layer and Identity function to the output layer show competent performance rather than other functions which demonstrated the function selection in the ANN structure can affect the performance of ANN.

• 전기학회논문지
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• 제58권4호
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• pp.832-839
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• 2009

In this paper, we introduce an design of fuzzy relation-based fuzzy neural networks with multi-output. Fuzzy relation-based fuzzy neural networks comprise the network structure generated by dividing the entire input space. The premise part of the fuzzy rules of the network reflects the relation of the division space for the entire input space and the consequent part of the fuzzy rules expresses three types of polynomial functions such as constant, linear, and modified quadratic. For the multi-output structure the neurons in the output layer were connected with connection weights. The learning of fuzzy neural networks is realized by adjusting connections of the neurons both in the consequent part of the fuzzy rules and in the output layer, and it follows a back-propagation algorithm. In addition, in order to optimize the network, the parameters of the network such as apexes of membership functions, learning rate and momentum coefficient are automatically optimized by using real-coded genetic algorithm. Two examples are included to evaluate the performance of the proposed network.

• 전기학회논문지
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• 제62권5호
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• pp.705-711
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• 2013

In this paper, we introduce an design of multi-output fuzzy neural networks based on Interval Type-2 fuzzy set. The proposed Interval Type-2 fuzzy set-based fuzzy neural networks with multi-output (IT2FS-based FNNm) comprise the network structure generated by dividing the input space individually. The premise part of the fuzzy rules of the network reflects the individuality of the division space for the entire input space and the consequent part of the fuzzy rules expresses three types of polynomial functions with interval sets such as constant, linear, and modified quadratic inference for pattern recognition. The learning of fuzzy neural networks is realized by adjusting connections of the neurons in the consequent part of the fuzzy rules, and it follows a back-propagation algorithm. In addition, in order to optimize the network, the parameters of the network such as apexes of membership functions, uncertainty factor, learning rate and momentum coefficient were automatically optimized by using real-coded genetic algorithm. The proposed model is evaluated with the use of numerical experimentation.

• 대한물리의학회지
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• 제5권2호
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• pp.281-288
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• 2010

Purpose : The purpose of this study was to examine the correlation between Pediatric Balance Scale(PBS) and Gross Motor Function Measurement(GMFM) with cerebral palsy(CP) children. Methods : 31 ambulatory children with CP were recruited for this study. PBS is a modified version of the Berg’s Balance Scale to access the children with motor impairments. To access the motor functions that directly influence to the functional independence of the ambulatory CP children, total scores of standing category and walking/running/jumping category of GMFM were selectively compared with PBS score by Spearman correlation coefficient analysis. Results : The results revealed high correlation between PBS and GMFM scores both in standing and walking/running/jumping categories(r=.9). Conclusions : Therefore, this study indicates that PBS can be applied not only as a tool to access balance, but also as a measurement to predict and access the level of standing and ambulatory related functions of children with CP.

• Wind and Structures
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• 제23권6호
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• pp.577-594
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• 2016

In this paper a practical modelling methodology is presented for a series of aero- servo- elastic- coupled numerical analyses of small wind turbine operation, with particular emphasis on variable speed generator modelling in various wind speed conditions. The following characteristics are determined using the available computer tools: the tip speed ratio as a function of the generator constant (under the assumption of constant wind speed), the turbine coefficient of power as a function of the tip speed ratio (the torque curve is modified accordingly and generator speed and power curves are plotted), turbine power curves and coefficient of power curve as functions of the incoming wind speed. The last stage is to determine forces and torques acting on rotor blades and turbine tower for specific incoming wind speeds in order to examine the impact of the stall phenomena on these values (beyond the rated power of the turbine). It is shown that the obtained results demonstrate a valuable guideline for small wind turbines design process.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2004년도 춘계학술대회 논문집
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• pp.967-973
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• 2004

Rock socketed drilled shafts transfer significant portion of structural loads at the socketed part. Therefore, a proper design of side and base resistances of a shaft at the socket is a major concern for the geotechnical engineers. In this study, we modified the Hoek-Brown criterion to estimate side resistance of rock socketed drilled shafts. Earlier method to compute side resistance of a shaft is linear or power functions of intact rock masses. However, side resistance is mobilized like shearing which influenced by the mechanical properties of concrete and rock masses, adhesion of rock/concrete interface, roughness of rock socket. Therefore, a single coefficient or power of uniaxial compressive strength of intact rock cannot provide accurate values of side resistance in a wide range of the uniaxial compressive strength. A new approach proposed in this study can consider in situ rock mass condition (frequency or discontinuities, weathering condition), and rock types thus, it has a wider applicability than the earlier models.