• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.975-989
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• 2014

Lasso (Tibshirani, 1996) and Elastic Net (Zou and Hastie, 2005) have been widely used in various fields for simultaneous variable selection and coefficient estimation. Bayesian methods using a conditional Laplace and a double Pareto prior specification have been discussed in the form of hierarchical specification. Full conditional posterior distributions with each priors have been derived. We compare the performance of Bayesian lassos with Laplace prior and the performance with double Pareto prior using simulations. We also apply the proposed Bayesian hierarchical models to real data sets to predict the collapse of governments in Asia.

• Journal of Biomedical Engineering Research
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• v.42 no.6
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• pp.268-276
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• 2021

Functional near-infrared spectroscopy-based brain-computer interface (fNIRS-based BCI) has been receiving much attention. However, we are practically constrained to obtain a lot of fNIRS data by inherent hemodynamic delay. For this reason, when employing machine learning techniques, a problem due to the high-dimensional feature vector may be encountered, such as deteriorated classification accuracy. In this study, we employ an elastic net-based feature selection which is one of the embedded methods and demonstrate the utility of which by analyzing the results. Using the fNIRS dataset obtained from 18 participants for classifying brain activation induced by mental arithmetic and idle state, we calculated classification accuracies after performing feature selection while changing the parameter α (weight of lasso vs. ridge regularization). Grand averages of classification accuracy are 80.0 ± 9.4%, 79.3 ± 9.6%, 79.0 ± 9.2%, 79.7 ± 10.1%, 77.6 ± 10.3%, 79.2 ± 8.9%, and 80.0 ± 7.8% for the various values of α = 0.001, 0.005, 0.01, 0.05, 0.1, 0.2, and 0.5, respectively, and are not statistically different from the grand average of classification accuracy estimated with all features (80.1 ± 9.5%). As a result, no difference in classification accuracy is revealed for all considered parameter α values. Especially for α = 0.5, we are able to achieve the statistically same level of classification accuracy with even 16.4% features of the total features. Since elastic net-based feature selection can be easily applied to other cases without complicated initialization and parameter fine-tuning, we can be looking forward to seeing that the elastic-based feature selection can be actively applied to fNIRS data.

• Bulletin of the Korean Mathematical Society
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• v.49 no.5
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• pp.961-987
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• 2012

A compartment model of the flow driven by pumping without valves (valveless pumping) in an open tank system is proposed. By the open tank system, we mean that two rigid cylindrical tanks are connected with an elastic tube. An incompressible fluid fills this system up to a certain level in tanks under the gravity. The compartment model for analyzing such open system is derived from the energy principle which will be called the energy conserving compartment model or shortly the ECCM. Based on this ECCM of valveless pumping, we explore the occurrence of directional net flow or directional net power by a specific excitation at an asymmetric part of the elastic tube. The interaction between deformable elastic tube and the fluid inside is considered in the ECCM. The reliability of the ECCMis investigated through some physical examples. The ECCM shows the existence of directional net power of the valveless pump system with open tanks and confirms that the direction and magnitude of the net power depend on the pumping frequency as well. Furthermore, the phase synchronization in time between the fluid pressure difference and the external pinching force over the pumping region is highly related to the direction of energy storing or net power.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.207-218
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• 2010

Generalized additive model(GAM) is the statistical model that resolves most of the problems existing in the traditional linear regression model. However, overfitting phenomenon can be aroused without applying any method to reduce the number of independent variables. Therefore, variable selection methods in generalized additive model are needed. Recently, Lasso related methods are popular for variable selection in regression analysis. In this research, we consider Group Lasso and Elastic net models for variable selection in GAM and propose an algorithm for finding solutions. We compare the proposed methods via Monte Carlo simulation and applying auto insurance data in the fiscal year 2005. lt is shown that the proposed methods result in the better performance.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.364-369
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• 2023

Time-delay estimation between two receivers is a technique that has been applied in a variety of fields, from underwater acoustics to room acoustics and robotics. There are two types of time delay estimation techniques: one that estimates the amount of time delay from the correlation between receivers, and the other that parametrically models the time delay between receivers and estimates the parameters by system recognition. The latter has the characteristic that only a small fraction of the system's parameters are directly related to the delay. This characteristic can be exploited to improve the accuracy of the estimation by methods such as Lasso regularization. However, in the case of Lasso regularization, the necessary information is lost. In this paper, we propose a method using Elastic Net that adds Ridge regularization to Lasso regularization to compensate for this. Comparing the proposed method with the conventional Generalized Cross Correlation (GCC) method and the method using Lasso regularization, we show that the estimation variance is very small even for white Gaussian signal sources and colored signal sources.

• Computers and Concrete
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• v.19 no.1
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• pp.1-6
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• 2017

Prestressed concrete I-girders are subject to different load types at their construction stages. At the time of strand release, i.e., detensioning, prestressed concrete girders are under the effect of dead and prestressing loads. At this stage, the camber, total net upward deflection, of prestressed girder is summation of the upward deflection due to the prestressing force and the downward deflection due to dead loads. For the calculation of the upward deflection, it is generally considered that prestressed concrete I-girder behaves linear-elastic. However, the field measurements on total net upward deflection of prestressed I-girder after detensioning show contradictory results. In this paper, camber calculations with the linear-elastic beam and elastic-stability theories are presented. One of a typical precast I-girder with 120 cm height and 31.5 m effective span length is selected as a case study. 3D finite element model (FEM) of the girder is developed by SAP2000 software, and the deflections of girder are obtained from linear and nonlinear-static analyses. Only geometric nonlinearity is taken into account. The material test and field measurement of this study are performed at prestressing girder plant. The results of the linear-elastic beam and elastic-stability theories are compared with FEM results and field measurements. It is seen that the camber predicted by elastic-stability theory gives acceptable results than the linear-elastic beam theory while strand releasing.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.2
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• pp.111-117
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• 2013

A valveless pump consisting of a pumping chamber with an elastic tube was simulated using an immersed boundary method. The interaction between the motion of the elastic tube and the pumping chamber generated a net flow toward the outlet through a full cycle of the pump. The net flow rate of the valveless pump was examined by varying the stretching coefficient, bending coefficient, and aspect ratio of the elastic tube. Photographs of the fluid velocity vectors and the wave motions of the elastic tube were examined over one cycle of the pump to gain a better understanding of the mechanism underlying the valveless pump. The relationship between the gap in the elastic tube and the average flow rate of the pump was analyzed.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.10a
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• pp.331-338
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• 2000

In this paper, a non-linear finite element formulation for the spatial cable-net structures is simulated and using this formulation, the characteristics of structural behaviors for the elastic catenary cable are examined In the simulating procedure for the elastic catenary cable, nodal forces and tangential stiffness matrices are derived using catenary parameters of the exact solutions by a governing differential equation of catenary cable, cable self-weights and unstressed cable length. Dynamic Relaxation Method that considers kinetic damping is used for the structure analysis and Newton Raphson Method is used to verify the accuracy of solutions. In the analysis of two dimensional cable, the results obtain from the elastic catenary elements are shown more accurate than does of truss elements and in the case of spatial cable-net structures, Dynamic Relaxation Method is more stable to be converged than Newton Raphson Method.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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• v.27 no.2
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• pp.27-36
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• 2021

Background : Prone hip extension (PHE) is commonly used for exercises and tests in patients with low back pain. Previous studies have shown that pelvic compression belts (PCB) and non-elastic taping (NET) contribute greatly to improvements in lumbopelvic stability. This study aimed to compare the effect of two lumbopelvic stability methods such as PCB and NET on the trunk and hip extensor muscle activities during PHE tests. Methods: Subjects who experienced low back pain (low back pain group, LBPG; n=20) and those who did not experience low back pain (non-LBPG; n=20) participated in this study. The subjects were instructed to perform PHE with and without a PCB and NET. PHE tests were performed in the condition wherein the two stabilization methods were applied, and the actions of the muscles at that time were measured using surface electromyography (EMG). EMG data were collected from the hamstring, gluteus maximus, erector spine (ES), and multifidus (MF) muscles. The data were collected three times for 5 s with a 1-min rest between each of the three sets. Results: In the LBPG, EMG of the ES muscle was significantly reduced when NET or a PCB was applied (p<.05). There was no difference in the change in the ES muscle activity when NET and a PCB were applied. The ratio of MF/ES muscleactivity showed a significant increase in the LBPG with NET (p<.05). Conclusion: Both NET and PCB applied to subjects who experienced low back pain significantly reduced the ES muscle activity during PHE exercises and helped control the balance of the superficial and deep trunk extensor muscles.

• Communications for Statistical Applications and Methods
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• v.21 no.4
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• pp.349-361
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• 2014

This paper compares of lasso type estimators in various high-dimensional data situations with sparse parameters. Lasso, adaptive lasso, fused lasso and elastic net as lasso type estimators and ridge estimator are compared via simulation in linear models with correlated and uncorrelated covariates and binary regression models with correlated covariates and discrete covariates. Each method is shown to have advantages with different penalty conditions according to sparsity patterns of regression parameters. We applied the lasso type methods to Arabidopsis microarray gene expression data to find the strongly significant genes to distinguish two groups.