• Journal of Korea Water Resources Association
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• v.41 no.3
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• pp.265-276
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• 2008

The observed data of enough period need for design of hydrological works. But, most hydrological data aren't enough. Therefore in this paper, hourly precipitation generated by nonhomogeneous Markov chain model using variable Kernel density function. First, the Kernel estimator is used to estimate the transition probabilities. Second, wet hours are decided by transition probabilities and random numbers. Third, the amount of precipitation of each hours is calculated by the Kernel density function that estimated from observed data. At the results, observed precipitation data and generated precipitation data have similar statistic. Also, rainfall mass curve is derived by calculated transition probabilities for generation of hourly precipitation.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.6
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• pp.87-94
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• 2006

Estimating moving vehicle loads is important in modeling design loads for bridge design and construction. The paper proposes a moving force identification algorithm using moment influence lines measured at multi-axes. Density estimation function was applied to estimate more than two wheel loads when estimated load values fluctuated severely. The algorithm has been examined through simulation studies on a simple-span plate-girder bridge. Influences of measurement noise and error in velocity on the identification results were investigated in the simulation study. Also, laboratory experiments were carried out to examine the algorithm. The load identification capability was dependent on the type and speed of moving loads, but the developed algorithm could identify loads within 10% error in maximum.

• Journal of the Korean Institute of Gas
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• v.21 no.3
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• pp.61-69
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• 2017

The commercial development of unconventional gas is pursued in North America because it is more feasible owing to the technology required to improve productivity. Shale reservoir have low permeability and gas production can be carried out through cracks generated by hydraulic fracturing. The decline rate during the initial production period is high, but very low latter on, there are significant variations from the initial production behavior. Therefore, in the prediction of the production rate using deterministic decline curve analysis(DCA), it is not possible to consider the uncertainty in the production behavior. In this study, production rate of the Eagle Ford shale is predicted by Arps Hyperbolic and Modified SEPD. To minimize the uncertainty in predicting the Estimated Ultimate Recovery(EUR), Monte Carlo simulation is used to multi-wells analysis. Also, kernel density function is applied to determine probability distribution of decline curve factors without any assumption.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6A
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• pp.1001-1011
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• 2006

It is a general agreement that exact statistical solutions can be found by a Monte Carlo technique. Due to difficulties, however, in the numerical generation of random fields, which satisfy not only the probabilistic distribution but the spectral characteristics as well, it is recognized as relatively difficult to find an exact response variability of a structural response. In this study, recognizing that the random field assumes a constant over the domain under consideration when the correlation distance tends to infinity, a semi-theoretical solution of response variability is proposed for general structures. In this procedure, the probability density function is directly used. It is particularly noteworthy that the proposed methodology provides response variability for virtually any type of probability density function, and has capability of considering correlations between multiple random variables.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3
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• pp.165-173
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• 2009

The physical properties of a seafloor sediment have been used as a basic data for the ocean survey. Conventional methods such as a coring, a drilling, and a grabbing have been used to explore the physical properties but these methods have a number of shortcomings as it is time consuming, expensive and spatially limited. To overcome these limitations, seafloor sediment classification using acoustic signals has been studied actively. In this paper, we obtained the backscattered signal from the seafloor sediment using an echo sounder which is one kind of seafloor topography equipment. Nakagami probability density function of the backscattered signals from the seafloor sediment was computed and a Nakagami parameter was compared with the physical properties of the seafloor sediment. We have confirmed that Nakagami parameter, m is correlated with the physical properties of a seafloor sediment. This study will be utilized as a basic data of the seafloor sediment research.

• Journal of Korean Society for Quality Management
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• v.30 no.3
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• pp.66-78
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• 2002

Process capability indices are being used as indicators for measurements of process capability for SPC of quality assurance system in industries. In view of the enhancement of customer satisfaction, process capability indices in which loss functions are used to deal with the economic loss In the processes deviated from the target, are in an adequate representation of the customer's perception of quality In this connection, the loss function has become increasingly important in quality assurance. Taguchi uses a modified form of the quadratic loss function to demonstrate the need to consider the proximity to the target while assessing its quality. But this traditional quadratic loss function is inadequate to assessing the quality and quality improvement since different processes have different sets of economic consequences on the manufacturing, Thereby, a flexible approach to the development of the loss function needs to be desired. In this paper, we introduce an easily understood loss function, based on reflection of probability density function of the normal distribution. That is, the Reflected Normal Loss function can be adapted to an asymmetric loss as well as to a symmetric loss around the target. We propose that, instead of the process variation, a new capability index, CpI using the Reflected Normal Loss Function that can accurately reflect the losses associated with the process and a new capability index CpI Is compared with the classical indices as $C_{p}$ , $C_{pk}$, $C_{pm}$ and $C_{pm}$ $^{+}$.>.+/./.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.20-20
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• 2000

Back-propagation neural network (BPNN) is the most prevalently used paradigm in modeling semiconductor manufacturing processes, which as a neuron activation function typically employs a bipolar or unipolar sigmoid function in either hidden and output layers. In this study, applicability of another linear function as a neuron activation function is investigated. The linear function was operated in combination with other sigmoid functions. Comparison revealed that a particular combination, the bipolar sigmoid function in hidden layer and the linear function in output layer, is found to be the best combination that yields the highest prediction accuracy. For BPNN with this combination, predictive performance once again optimized by incrementally adjusting the gradients respective to each function. A total of 121 combinations of gradients were examined and out of them one optimal set was determined. Predictive performance of the corresponding model were compared to non-optimized, revealing that optimized models are more accurate over non-optimized counterparts by an improvement of more than 30%. This demonstrates that the proposed gradient-optimized teaming for BPNN with a linear function in output layer is an effective means to construct plasma models. The plasma modeled is a hemispherical inductively coupled plasma, which was characterized by a 24 full factorial design. To validate models, another eight experiments were conducted. process variables that were varied in the design include source polver, pressure, position of chuck holder and chroline flow rate. Plasma attributes measured using Langmuir probe are electron density, electron temperature, and plasma potential.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.7
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• pp.26-31
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• 2011

In this paper, torque characteristics analysis of Synchronous Reluctance Motor with the cylindrical rotor type by winding function theory(WFT) is described. The stator is same as one of the induction motor. From the d-axis, q-axis flux density distribution, to calculate self and mutual inductances needed to calculate the torque of the machine by using winding function theory the new equivalent geometry of rotor was proposed. D-axis, q-axis flux densities, self inductance and torque characteristics were obtained. From the comparison with results of finite element analysis the proposed method was verified.

• Journal of applied mathematics & informatics
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• v.18 no.1_2
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• pp.339-350
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• 2005

A space-time fractional advection-dispersion equation (ADE) is a generalization of the classical ADE in which the first-order time derivative is replaced with Caputo derivative of order $\alpha{\in}(0,1]$, and the second-order space derivative is replaced with a Riesz-Feller derivative of order $\beta{\in}0,2]$. We derive the solution of its Cauchy problem in terms of the Green functions and the representations of the Green function by applying its Fourier-Laplace transforms. The Green function also can be interpreted as a spatial probability density function (pdf) evolving in time. We do the same on another kind of space-time fractional advection-dispersion equation whose space and time derivatives both replacing with Caputo derivatives.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.8
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• pp.183-192
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• 1998

In this paper, we measure the back-EMF and the thrust of a linear brushless DC motor along the relative position between coils and magnets in various speed environments in order to obtain the back-EMF and the thrust as a function of a motor position. The measured back-EMF function and thrust function of the position differ from the analytical ones within 5%. The measured back-EMF and thrust function can, then, be employed in controlling the thrust ripple of the linear motor. Furthermore, to minimize the torque ripple of the linear motor, we suggest the design method to shape the back-EMF and thrust function of the linear motor.