• Proceedings of the Computational Structural Engineering Institute Conference
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• 1989.04a
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• pp.50-55
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• 1989

Piping systems are composed of pipes with various thickness, diameter and length. Accurate analysis of a piping system requires a complicated three dimensional finite element model and a computer system with large memory size, while simplified models result in system response prediction with deteriorated accuracy. An efficient analysis model for piping systems is proposed in this study. The proposed model is developed by introducing a joint model which accounts for the behavior of a pipe connection. Pipes are represented by beam elements and the effect of local deformation of pipe connections are replaced by joint element deformations. The proposed model which is as simple and efficient as a beam model can be used to obtain piping system response with accuracy close to that of a finite element model.

• Structural Engineering and Mechanics
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• v.55 no.3
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• pp.473-494
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• 2015

A graded harmonic finite element formulation based on three-dimensional elasticity theory is developed for the structural analysis of 2D functionally graded axisymmetric structures. The mechanical properties of the axisymmetric solid structures composed of two different metals and ceramics are assumed to vary in radial and axial directions according to power law variations as a function of the volume fractions of the constituents. The material properties of the graded element are calculated at the integration points. Effects of material distribution profile on the static deformation, natural frequency and dynamic response analyses of particular axisymmetric solid structures are investigated by changing the power law exponents. It is observed that the displacements, stresses and natural frequencies are severely affected by the variation of axial and radial power law exponents. Good accuracy is obtained with fewer elements in the present study since Fourier series expansion eliminates the need of finite element mesh in circumferential direction and continuous material property distribution within the elements improves accuracy without refining the mesh size in axial and radial directions.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.23 no.3
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• pp.364-373
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• 1999

A combination of conjugate gradient and Levenberg-Marquardt method is used to estimate the spatially varying scattering coefficient, ${\sigma}(r)$, in the solid and hollow spheres by utilizing the measured transmitted beams from the solution of an inverse analysis. The direct radiation problem associated with the inverse problem is solved by using the $S_{12}-approximation$ of the discrete ordinates method. The accuracy of the computations increased when the results from the conjugate gradient method are used as an initial guess for the Levenberg-Marquardt method of minimization. Optical thickness up to ${\tau}_0=3$ is used for the computations. Three different values of standard deviation are considered to examine the accuracy of the solution from the inverse analysis.

• Genomics & Informatics
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• v.18 no.1
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• pp.10.1-10.9
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• 2020

Advancements in next generation sequencing (NGS) technologies have significantly increased the translational use of genomics data in the medical field as well as the demand for computational infrastructure capable processing that data. To enhance the current understanding of software and hardware used to compute large scale human genomic datasets (NGS), the performance and accuracy of optimized versions of GATK algorithms, including Parabricks and Sentieon, were compared to the results of the original application (GATK V4.1.0, Intel x86 CPUs). Parabricks was able to process a 50× whole-genome sequencing library in under 3 h and Sentieon finished in under 8 h, whereas GATK v4.1.0 needed nearly 24 h. These results were achieved while maintaining greater than 99% accuracy and precision compared to stock GATK. Sentieon's somatic pipeline achieved similar results greater than 99%. Additionally, the IBM POWER9 CPU performed well on bioinformatic workloads when tested with 10 different tools for alignment/mapping.

• Asia pacific journal of information systems
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• v.6 no.2
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• pp.77-105
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• 1996

The accuracy of knowledge is a major concern for expert system developers and users. Machine learning approaches have recently been found to be useful in knowledge acquisition for expert systems. However, the accuracy of concept acquired from machine learning could not be analyzed in most cases. In this paper we develop a comprehensive knowledge error analysis methodology for practical use of expert systems. Decision tree induction is an important type of machine learning method for business expert systems. Here we start to analyze with knowledge acquired from decision tree induction method, and extend the results to develop error analysis methodology for general machine learning methods. We give several examples and illustrations for these results. We also discuss the applicability of these results to multistrategy learning approaches.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1179-1189
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• 2017

In this study, we propose an alternative method for discriminant analysis using a multivariate empirical distribution function to express multivariate data as a simple one-dimensional statistic. This method turns to be the estimation process of the optimal threshold based on classification accuracy measures and an empirical distribution function of data composed of classes. This can also be visually represented on a two-dimensional plane and discussed with some measures in ROC curves, surfaces, and manifolds. In order to explore the usefulness of this method for discriminant analysis in the study, we conducted comparisons between the proposed method and the existing methods through simulations and illustrative examples. It is found that the proposed method may have better performances for some cases.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.6
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• pp.87-92
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• 2001

An error analysis is very important for a precision machine to estimate its performances. This study proposes a new parallel device, cubic parallel manipulator. Errors of the proposed cubic parallel manipulator include upper and down universal joint errors, due to the directional changes in the forces in the links, and actuation errors. An error analysis is presented based on an error model formed through the relation between the universal joint errors of the cubic parallel manipulator and the end effector accuracy. The analysis shows that the method can be used in predicting the accuracy of other cubic parallel devices.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.912-915
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• 2004

A vacuum environment is very important for NGL(Next Generation Lithography) apparatuses such as EUVL(Extreme Ultra Violet Lithography) or EPL(Electron Projection Lithography) and so on. The performance of these systems is dominated by vacuum level of processing and positioning accuracy of a stage. So, ultra-precision stage usable in a high vacuum level is needed for the improved performance of these devices. In contrast to atmospheric condition, a special attention must be paid to guide bearing, actuator and other elements. In this paper, air bearing is adopted because of its very high motional accuracy. So, air bearing is designed to be vacuum compatible using differential exhaust method, which prevents air from entering into vacuum chamber. For this, leakage analysis is performed theoretically and verified from experiment.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1548-1555
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• 2017

This paper attempts to employ and investigate neural based approaches as interpolation tools for modeling of Switched Reluctance Motor (SRM) drive. Precise modeling of SRM is essential to analyse the performance of control strategies for variable speed drive application. In this work the suitability of Generalized Regression Neural Network (GRNN) and Extreme Learning Machine (ELM) in addition to conventional neural network are explored for improving the modeling accuracy of SRM. The neural structures are trained with the data obtained by modeling of SRM using Finite Element Analysis (FEA) and the trained neural network is incorporated in the model of SRM drive. The results signify the modeling accuracy with GRNN model. The closed loop drive simulation is performed in MATLAB/Simulink environment and the closeness of the results in comparison with the experimental prototype validates the modeling approach.

• Journal of IKEEE
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• v.8 no.1 s.14
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• pp.63-72
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• 2004

The supply voltage has been drop rapidly and the total length of the wire increased exponentially in the nanometer SoC design environment. The ideal supply voltage was dropped sharply by the resistance and parasitic devices which stayed on the kilometers-long wire length. Even worse, it could severely affect the functional behavior of the block of the design. To analyze the effects of the long wire of the SoC while maintaining the accuracy, the modeling of the current and the RC conversion of the parasitic techniques are researched and applied. By these modeling and conversion, the multi-million gates HDTV Chipset can be analyzed within a day. The benchmark analysis of the HDTV SoC showed the superiority to the conventional methods in performance and accuracy.