• Genomics & Informatics
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• v.20 no.1
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• pp.9.1-9.6
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• 2022

Mendelian randomization (MR) uses genetic variation as a natural experiment to investigate the causal effects of modifiable risk factors (exposures) on outcomes. Two-sample Mendelian randomization (2SMR) is widely used to measure causal effects between exposures and outcomes via genome-wide association studies. 2SMR can increase statistical power by utilizing summary statistics from large consortia such as the UK Biobank. However, the first-order term approximation of standard error is commonly used when applying 2SMR. This approximation can underestimate the variance of causal effects in MR, which can lead to an increased false-positive rate. An alternative is to use the second-order approximation of the standard error, which can considerably correct for the deviation of the first-order approximation. In this study, we simulated MR to show the degree to which the first-order approximation underestimates the variance. We show that depending on the specific situation, the first-order approximation can underestimate the variance almost by half when compared to the true variance, whereas the second-order approximation is robust and accurate.

• Management Science and Financial Engineering
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• v.21 no.2
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• pp.25-30
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• 2015

This short article compares different solution methods for a basic RBC model (Hansen, 1985). We solve and simulate the model using two main algorithms: the methods of perturbation and projection, respectively. One novelty is that we offer a type of the hybrid method: we compute easily a second-order approximation to decision rules and use that approximation as an initial guess for finding Chebyshev polynomials. We also find that the second-order perturbation method is most competitive in terms of accuracy for standard RBC model.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.5
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• pp.647-652
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• 1986

The controller tuning methods proposed by Yuwana-Seborg and Suh utilizes Pade first order approximation for the delay terms in the closed loop transfer function. In this paper, the use of a Pade second-order approximation method is investigated. The simulation results show that the new method is superior to pervious approaches such as Ziegler-Nichols and Cohen-Coon methods.

• Ocean Systems Engineering
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• v.7 no.1
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• pp.53-74
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• 2017

Ship shaped FPSO (Floating Production, Storage and Offloading) units are the most commonly used floating production units to extract hydrocarbons from reservoirs under the seabed. These structures are usually much larger than general cargo ships and have their natural frequency outside the wave frequency range. This results in the response to first order wave forces acting on the hull to be negligible. However, second order difference frequency forces start to significantly impact the motions of the structure. When the difference frequency between wave components matches the roll natural frequency, the structure experiences a significant roll motion which is also termed as second order roll. This paper describes the theory and numerical implementation behind the calculation of second order forces and motions of any general floating structure subjected to waves. The numerical implementation is validated in zero speed case against the commercial code OrcaFlex. The paper also describes in detail the popular approximations used to simplify the computation of second order forces and provides a discussion on the limitations of each approximation.

• ETRI Journal
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• v.37 no.4
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• pp.727-735
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• 2015

This paper deals with the problem of blind source separation (BSS), where observed signals are a mixture of delayed sources. In reference to a previous work, when the delay time is small such that the first-order Taylor approximation holds, delayed observations are transformed into an instantaneous mixture of original sources and their derivatives, for which an extended second-order blind identification (SOBI) approach is used to recover sources. Inspired by the results of this previous work, we propose to generalize its first-order Taylor approximation to suit higher-order approximations in the case of a large delay time based on a similar version of its extended SOBI. Compared to SOBI and its extended version for a first-order Taylor approximation, our method is more efficient in terms of separation quality when the delay time is large. Simulation results verify the performance of our approach under different time delays and signal-to-noise ratio conditions, respectively.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.2
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• pp.236-247
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• 1992

Optimization has been developed to minimize the cost function while satisfying constraints. Nonlinear Programming method is used as a tool for the optimization. Usually, cost and constraint function calculations are required in the engineering applications, but those calculations are extremely expensive. Especially, the function and sensitivity analyses cause a bottleneck in structural optimization which utilizes the Finite Element Method. Also, when the functions are quite noisy, the informations do not carry out proper role in the optimization process. An algorithm called "Second-order Approximation Method" has been proposed to overcome the difficulties recently. The cost and constraint functions are approximated by the second-order Taylor series expansion on a nominal points in the algorithm. An optimal design problem is defined with the approximated functions and the approximated problem is solved by a nonlinear programming numerical algorithm. The solution is included in a candidate point set which is evaluated for a new nominal point. Since the functions are approximated only by the function values, sensitivity informations are not needed. One-dimensional line search is unnecessary due to the fact that the nonlinear algorithm handles the approximated functions. In this research, the method is analyzed and the performance is evaluated. Several mathematical problems are created and some standard engineering problems are selected for the evaluation. Through numerical results, applicabilities of the algorithm to large scale and complex problems are presented.presented.

• Journal of the Korean Data and Information Science Society
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• v.11 no.1
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• pp.103-110
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• 2000

Suppose that there is a population of hidden objects of which the total number N is unknown. From such data, we derive second-order approximations to the stopping time with fixed proportional accuracy.

• Journal of applied mathematics & informatics
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• v.26 no.5_6
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• pp.1057-1069
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• 2008

We consider singularly perturbed Boundary Value Problems (BVPs) for third and fourth order Ordinary Differential Equations(ODEs) of convection-diffusion type with discontinuous source term and a small positive parameter multiplying the highest derivative. Because of the type of Boundary Conditions(BCs) imposed on these equations these problems can be transformed into weakly coupled systems. In this system, the first equation does not have the small parameter but the second contains it. In this paper a computational method named as 'An asymptotic finite element method' for solving these systems is presented. In this method we first find an zero order asymptotic approximation to the solution and then the system is decoupled by replacing the first component of the solution by this approximation in the second equation. Then the second equation is independently solved by a fitted mesh Finite Element Method (FEM). Numerical experiments support our theoritical results.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.376-386
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• 1995

Designs for polynomial approximation to the unknown response function are considered. Optimality criteria are monotone functions of the mean squared error matrix of the least squares estimator. They correspond to the classical A-, D-, G- and Q-optimalities. Optimal first order designs are chosen from the invariant designs and then compared with optimal second order designs.

• Journal of Ocean Engineering and Technology
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• v.15 no.1
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• pp.12-18
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• 2001

This study concentrates on the second-order diffraction problem around circular cylinders in multi-frequency waves. The method of solution is a time-domain Rankine panel method which adopts a higher-order approximation for the velocity potential and wave elevation. In the present study, the multiple second-order quadratic transfer functions are extracted from the second-order time signal generated in random waves, and the comparison with other bench-mark test results shows a good agreement. This approach is directly applicable to prediction of nonlinear forces on offshore structures in random ocean.