• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.248-251
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• 1997

In this paper, We propose the concept of approximate Classification in the field of two group discriminan analysis. In our approach, an attribute space is divided into three subspaces. Two subspaces are for given two group and one subspace is for a boundary area between the two groups. We propose Approximate Pattern Classification with Rough set. We also propose learning procedures of neural networks for approximate classification. We propose two weighting methods which lead to possibility analysis and necessity analysis. We illustrate the proposed methods by numerical examples.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_2
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• pp.593-605
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• 2012

LiDAR systems provide dense and accurate topographic information. A pre-requisite to achieving the potential accuracy of LiDAR is having a proper system calibration, which aims at estimating all the systematic errors in the system measurements and the mounting parameters relating the different components. This paper presents a rigorous and two approximate methods for LiDAR system calibration. The rigorous approach makes use of the LiDAR equation and the system raw measurements. The approximate approaches utilize simplified LiDAR equations using some assumptions, which allow for less strict requirements regarding the raw measurements. The first presented approximate method, denoted as quasi-rigorous, assumes that we are dealing with a vertical platform (i.e., small pitch and roll angles). This method requires time-tagged point cloud and trajectory position data. The second approximate method, denoted as simplified, assumes that we are dealing with parallel strips, vertical platform, and minor terrain elevation variations compared to the flying height above ground. Such method can be performed using the LiDAR point cloud only. Experimental results using a real dataset, whose characteristics deviate to some extent from the utilized assumptions in the approximate methods, are presented to provide a comparative analysis of the outcome from the introduced methods.

• Journal of Biosystems Engineering
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• v.20 no.3
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• pp.205-216
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• 1995

A fast and inexpensive approximate analysis method to predict power output characteristics of the Stilting engines in a preliminary design stage was investigated. In basic equations proposed by Walker, typical temperatures of working fluids in expansion and compression spaces were treated as those of working fluids in heater and cooler respectively. While the temperature of working fluid in the expansion space was actually lower than that of working fluid in the heater, the temperature of working fluid in the compression space was higher than that of working fluids in the cooler. In this paper, the working fluid temperature of expansion space was treated as lower than the heater temperature and that of compression space was treated as higher than the cooler temperature. Also, according to them, the power output characteristics of the Stirling engine were evaluated with respect to the GPU-3 and 4-215 Stilting engines. The following conclusions were drawn from the analysis. 1. Using the available experimental data from the GPU-3 Stirling engine, it was shown that the approximate analysis predicts the brake power with a maximum error of 19 percent at 1, 000rpm and with a minimum error of 3 percent at 2, 000rpm. 2. The approximate analysis data which for the GPU-3 Stirling engine were much closer to the experimental data than those of adiabatic 2nd order and 3rd order analysis within 1, 500rpm to 2, 500rpm. 3. The approximate analysis data which for the GPU-3 and 4-215 Stilting engines were much closer to the experimental data than those of the Beal number analysis.

• Journal of the Korean Mathematical Society
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• v.54 no.4
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• pp.1063-1079
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• 2017

Two standard Bessel sequences in a Hilbert $C^*$-module are approximately duals if the distance (with respect to the norm) between the identity operator on the Hilbert $C^*$-module and the operator constructed by the composition of the synthesis and analysis operators of these Bessel sequences is strictly less than one. In this paper, we introduce (a, m)-approximate duality using the distance between the identity operator and the operator defined by multiplying the Bessel multiplier with symbol m by an element a in the center of the $C^*$-algebra. We show that approximate duals are special cases of (a, m)-approximate duals and we generalize some of the important results obtained for approximate duals to (a, m)-approximate duals. Especially we study perturbations of (a, m)-approximate duals and (a, m)-approximate duals of modular Riesz bases.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.5
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• pp.233-240
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• 2021

We propose a novel, highly accurate approximate multiplier using different types of inexact 4-2 compressors. The importance of low hardware costs leads us to develop approximate multiplication for error-resilient applications. Several rules are developed when selecting a topology for designing the proposed multiplier. Our highly accurate multiplier design considers the different error characteristics of adopted compressors, which achieves a good error distribution, including a low relative error of 0.02% in the 8-bit multiplication. Our analysis shows that the proposed multiplier significantly reduces power consumption and area by 45% and 26%, compared with the exact multiplier. Notably, a trade-off relationship between error characteristics and hardware costs can be achieved when considering those of existing highly accurate approximate multipliers. In the image blending, edge detection and image sharpening applications, the proposed 8-bit approximate multiplier shows better performance in terms of image quality metrics compared with other highly accurate approximate multipliers.

• Journal of Ocean Engineering and Technology
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• v.35 no.2
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• pp.131-140
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• 2021

The paper deals with comparative study of various surrogate models based approximate optimization in the structural design of the passive type deck support frame under design load conditions. The passive type deck support frame was devised to facilitate both transportation and installation of 20,000 ton class topside. Structural analysis was performed using the finite element method to evaluate the strength performance of the passive type deck support frame in its initial design stage. In the structural analysis, the strength performances were evaluated for various design load conditions. The optimum design problem based on surrogate model was formulated such that thickness sizing variables of main structure members were determined by minimizing the weight of the passive type deck support frame subject to the strength performance constraints. The surrogate models used in the approximate optimization were response surface method, Kriging model, and Chebyshev orthogonal polynomials. In the context of numerical performances, the solution results from approximate optimization were compared to actual non-approximate optimization. The response surface method among the surrogate models used in the approximate optimization showed the most appropriate optimum design results for the structure design of the passive type deck support frame.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1997.10a
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• pp.270-278
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• 1997

The purpose of this paper is to evaluate the effectiveness of eigen modes by modal analysis and the application of approximate eigen modes for continuum. This study proposes the appropriate selection technique of eigen modes by modal analysis and the method for the reasonable survey of post-buckling path. And the buckling characteristics of a latticed dome is studied by the application of these approximate eigen modes which have sufficient accuracy and praticallity for response analysis in symmetric and anti-symmetric state of continuous shell. To prove the effectiveness of eigen modes and application of approximate eigen modes for continuum, these results are compared with those of direct method.

• Structural Engineering and Mechanics
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• v.8 no.1
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• pp.1-18
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• 1999

Procedures are investigated by which nonlinear finite element shell analysis algorithms can be simplified to provide more cost effective approximate analyses of orthogonally-reinforced concrete flat plate structures. Two alternative effective stiffness formulations, and an unbalanced force formulation, are described. These are then implemented into a nonlinear shell analysis algorithm. Nonlinear geometry, three-dimensional layered stress analyses, and other general formulations are bypassed to reduce the computational burden. In application to standard patch test problems, these simplified approximate analysis procedures are shown to provide reasonable accuracy while significantly reducing the computational effort. Corroboration studies using various simple and complex test specimens provide an indication of the relative accuracy of the constitutive models utilized. The studies also point to the limitations of the approximate formulations, and identify situations where one should revert back to full nonlinear shell analyses.

• Communications for Statistical Applications and Methods
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• v.29 no.4
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• pp.471-486
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• 2022

Autoregressive moving average (ARMA) models involve nonlinearity in the model coefficients because of unobserved lagged errors, which complicates the likelihood function and makes the posterior density analytically intractable. In order to overcome this problem of posterior analysis, some approximation methods have been proposed in literature. In this paper we first review the main analytic approximations proposed to approximate the posterior density of ARMA models to be analytically tractable, which include Newbold, Zellner-Reynolds, and Broemeling-Shaarawy approximations. We then use the Kullback-Leibler divergence to study the relation between these three analytic approximations and to measure the distance between their derived approximate posteriors for ARMA models. In addition, we evaluate the impact of the approximate posteriors distance in Bayesian estimates of mean and precision of the model coefficients by generating a large number of Monte Carlo simulations from the approximate posteriors. Simulation study results show that the approximate posteriors of Newbold and Zellner-Reynolds are very close to each other, and their estimates have higher precision compared to those of Broemeling-Shaarawy approximation. Same results are obtained from the application to real-world time series datasets.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.1C
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• pp.78-83
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• 2002

Reachability analysis of finite state machines is very useful for many computer-aided design applications such as communication protocol or microprecessor design. We present new techniques to improve approximate reachability analysis. The key idea is to used an iterative approximate reachability analysis technique in which don't care sets derived from previous iterations are used to improve the approximation in subsequent iterations. Experimental results show that the new techniques can improve reachability analysis significantly compared to existing analysis techniques.