• Journal of the Earthquake Engineering Society of Korea
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• v.19 no.1
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• pp.1-11
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• 2015

In order to perform a soil-isolation-structure interaction analysis of seismically isolated nuclear power plant (NPP) structures, the nonlinear behavior of a seismic isolation system may be converted to an equivalent linear model used in frequency domain analysis. Seismic responses for seismically isolated NPP containment structures subjected to a simple artificial acceleration history and different site class earthquakes are evaluated for the equivalent-linear and nonlinear models that have been applied to lead-rubber bearing (LRB) modeling. It can be observed that the maximum displacements of the equivalent linear model are larger than that of the nonlinear model. From the floor response spectrum analysis for the top of NPP containment structures, it can be observed that the spectral acceleration of an equivalent linear model at about 0.5 Hz frequency is about 2~3 times larger than that of a nonlinear model.

• Journal of Aerospace System Engineering
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• v.14 no.6
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• pp.18-25
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• 2020

This study investigated the structural behaviors and safety of an electro-mechanical linear actuator and a load simulator with a plate spring. The material and dimensions of the plate spring were determined by theoretically calculating the stress and torsional angle for the rating load of the actuator. Thereafter, a flexible multibody dynamics (FMBD) analysis was conducted on the linear actuator and load simulator to confirm the performance of the load simulator and acquire the reaction forces acting on the actuator and simulator. The structural safety of the linear actuator and load simulator was evaluated via finite element analysis using the aforementioned reaction forces. Consequently, the proposed linear actuator and load simulator were determined to be structurally safe; however, the safety factors for the actuation rod and the housing on the actuator were excessively high. Therefore, the weight and cost must be reduced to improve their design parameters in the future.

• Earthquakes and Structures
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• v.20 no.3
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• pp.279-293
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• 2021

Most of the existing seismic codes for RC buildings consider only a scenario earthquake for analysis, often characterized by the response spectrum at the specified location. However, any real earthquake event often involves occurrences of multiple earthquakes within a few hours or days, possessing similar or even higher energy than the first earthquake. This critically impairs the rehabilitation measures thereby resulting in the accumulation of structural damages for subsequent earthquakes after the first earthquake. Also, the existing seismic provisions account for the non-linear response of an RC building frame implicitly by specifying a constant response modification factor (R) in a linear elastic design. However, the 'R' specified does not address the changes in structural configurations of RC moment-resisting frames (RC MRFs) viz., building height, number of bays present, bay width, irregularities arising out of mass and stiffness changes, etc. resulting in changed dynamic characteristics of the structural system. Hence, there is an imperative need to assess the seismic performance under sequential earthquake ground motions, considering the adequacy of code-specified 'R' in the representation of dynamic characteristics of RC buildings. Therefore, the present research is focused on the evaluation of the non-linear response of medium-rise 3D RC MRFs with and without vertical irregularities under bi-directional sequential earthquake ground motions using non-linear dynamic analysis. It is evident from the results that collapse probability increases, and 'R' reduces significantly for various RC MRFs subjected to sequential earthquakes, pronouncing the vulnerability and inadequacy of estimation of design base shear by code-specified 'R' under sequential earthquakes.

• Communications for Statistical Applications and Methods
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• v.28 no.2
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• pp.189-204
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• 2021

In a regression analysis, a single best model is usually selected among several candidate models. However, it is often useful to combine several candidate models to achieve better performance, especially, in the prediction viewpoint. Model combining methods such as stacking and Bayesian model averaging (BMA) have been suggested from the perspective of averaging candidate models. When the candidate models include a true model, it is expected that BMA generally gives better performance than stacking. On the other hand, when candidate models do not include the true model, it is known that stacking outperforms BMA. Since stacking and BMA approaches have different properties, it is difficult to determine which method is more appropriate under other situations. In particular, it is not easy to find research papers that compare stacking and BMA when regression model assumptions are violated. Therefore, in the paper, we compare the performance among model averaging methods as well as a single best model in the linear regression analysis when standard linear regression assumptions are violated. Simulations were conducted to compare model averaging methods with the linear regression when data include outliers and data do not include them. We also compared them when data include errors from a non-normal distribution. The model averaging methods were applied to the water pollution data, which have a strong multicollinearity among variables. Simulation studies showed that the stacking method tends to give better performance than BMA or standard linear regression analysis (including the stepwise selection method) in the sense of risks (see (3.1)) or prediction error (see (3.2)) when typical linear regression assumptions are violated.

• Progress in Superconductivity and Cryogenics
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• v.14 no.3
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• pp.43-47
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• 2012

A linear compressor generates pulsating pressure and oscillating flow in a cryocooler such as Stirling cryocooler and pulse tube refrigerator. It is driven by AC power source and designed to operate at resonance of piston motion. The driving voltage level is determined by electric parameters of resistance, inductance and thrust constant of linear motor. From voltage equation on linear motor, the power factor of driving power is inherently less than 1. The phase difference between voltage and current of supplied power can be zero using capacitor and this can minimize a supply voltage level. Especially, the linear compressor of kW class requires high voltage and thus can cause a difficulty in selecting power supply unit due to limitation of voltage level. The capacitor in driving electric circuit is useful to settle this problem. In this study, the electric circuit of linear compressor is analytically investigated with assumption of mechanical resonance. The electric parameters of commercial linear motor are used in the analysis. The effects of capacitor on driving voltage level and power factor are investigated. From analytic results, it is shown that the voltage level can be mimized with using capacitor in driving electric circuit.

• Proceedings of the KIEE Conference
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• 1998.07a
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• pp.224-227
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• 1998

Linear motors are increasingly employed as direct actuators replacing the more conventional systems composed by a rotating motor and a mechanical device. Linear DC motor is useful in a high speed and high accuracy positioning system with a feedback controller. Because of these advantages, linear DC motors have already been used as motors of pen recorders and magnetic disk storage devices, these are moving coil type linear DC motors as these movers are light. Moving magnet type linear DC motor has advantages at long stroke motors because its mover's feeding wires for driving is not necessary. This paper is concerned with the analysis of linear DC motor that is moving magnet type with unipolar. In order to analyze the dynamic behaviour a mathematical model based on a simplified field analysis developed. A two dimensional finite element field solution is employed in order to illustrate the effect of yoke saturation and motor performance. It is deduced the relation between the limit value of the thrust of the linear DC motor and the dimension of the yokes.

• Communications for Statistical Applications and Methods
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• v.30 no.1
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• pp.95-107
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• 2023

Purpose: The statistical analysis of point processes on linear networks is a recent area of research that studies processes of events happening randomly in space (or space-time) but with locations limited to reside on a linear network. For example, traffic accidents happen at random places that are limited to lying on a network of streets. This paper applies techniques developed for point processes on linear networks and the tools available in the R-package spatstat to estimate the intensity of traffic accidents in Leon County, Florida. Methods: The intensity of accidents on the linear network of streets is estimated using log-linear Poisson models which incorporate cubic basis spline (B-spline) terms which are functions of the x and y coordinates. The splines used equally-spaced knots. Ten different models are fit to the data using a variety of covariates. The models are compared with each other using an analysis of deviance for nested models. Results: We found all covariates contributed significantly to the model. AIC and BIC were used to select 9 as the number of knots. Additionally, covariates have different effects such as increasing the speed limit would decrease traffic accident intensity by 0.9794 but increasing the number of lanes would result in an increase in the intensity of traffic accidents by 1.086. Conclusion: Our analysis shows that if other conditions are held fixed, the number of accidents actually decreases on roads with higher speed limits. The software we currently use allows our models to contain only spatial covariates and does not permit the use of temporal or space-time covariates. We would like to extend our models to include such covariates which would allow us to include weather conditions or the presence of special events (football games or concerts) as covariates.

• Journal of Educational Research in Mathematics
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• v.19 no.3
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• pp.461-477
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• 2009

In this study, an operational analysis in the context of linear equations is presented. For the analysis, several second-order models concerning students' whole number knowledge and fraction knowledge based on teaching experiment methodology were employed, in addition to our first-order analysis. This ontogenetic analysis begins with students' Explicitly Nested number Sequence (ENS) and proceeds on through various forms of linear equations. This study shows that even in the same representational forms of linear equations, the mathematical knowledge necessary for solving those equations might be different based on the type of coefficients and constants the equation consists of. Therefore, the pedagogical implications are that teachers should be able to differentiate between different types of linear equation problems and propose them appropriately to students by matching the required mathematical knowledge to the students' potential constructs.

• Science of Emotion and Sensibility
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• v.16 no.3
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• pp.409-416
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• 2013

Attention is one of important cognitive functions in human affecting on the selectional concentration of relevant events and ignorance of irrelevant events. The discrimination of attentional and inattentional status is the first step to manage human's attentional capability using computer assisted device. In this paper, we newly combine the non-linear recurrence pattern analysis and spectrum analysis to effectively extract features(total number of 13) from the electroencephalographic signal used in the input to classifiers. The performance of diverse types of attention-inattention classifiers, including supporting vector machine, back-propagation algorithm, linear discrimination, gradient decent, and logistic regression classifiers were evaluated. Among them, the support vector machine classifier shows the best performance with the classification accuracy of 81 %. The use of spectral band feature set alone(accuracy of 76 %) shows better performance than that of non-linear recurrence pattern feature set alone(accuracy of 67 %). The support vector machine classifier with hybrid combination of non-linear and spectral analysis can be used in later designing attention-related devices.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.4
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• pp.467-474
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• 2004

A numerical method and algorithms is proposed to perform optimization of non-linear response structures. An analytical and numerical method based finite element method is also proposed for the transformation of non-linear response into linear response. Loads transformed from this method are defined as the equivalent linear loads. With the loads and the transformed response, linear static optimization is performed for nonlinear response structure with geometric and/or material non-linearity. The results of the optimization are compared with them of typical non-linear response optimization using finite difference method. The proposed method is very efficient and derives good solution.