• Title/Summary/Keyword: homogeneous polynomial

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Range Data Sementation and Classification Using Eigenvalues of Surface Function and Neural Network (면방정식의 고유치와 신경회로망을 이용한 거리영상의 분할과 분류)

  • 정인갑;현기호;이진재;하영호
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.29B no.7
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    • pp.70-78
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    • 1992
  • In this paper, an approach for 3-D object segmentation and classification, which is based on eigen-values of polynomial function as their surface features, using neural network is proposed. The range images of 3-D objects are classified into surface primitives which are homogeneous in their intrinsic eigenvalue properties. The misclassified regions due to noise effect are merged into correct regions satisfying homogeneous constraints of Hopfield neural network. The proposed method has advantage of processing both segmentation and classification simultaneously.

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UNIQUENESS OF HOMOGENEOUS DIFFERENTIAL POLYNOMIALS CONCERNING WEAKLY WEIGHTED-SHARING

  • Pramanik, Dilip Chandra;Roy, Jayanta
    • Communications of the Korean Mathematical Society
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    • v.34 no.2
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    • pp.439-449
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    • 2019
  • In 2006, S. Lin and W. Lin introduced the definition of weakly weighted-sharing of meromorphic functions which is between "CM" and "IM". In this paper, using the notion of weakly weighted-sharing, we study the uniqueness of nonconstant homogeneous differential polynomials P[f] and P[g] generated by meromorphic functions f and g, respectively. Our results generalize the results due to S. Lin and W. Lin, and H.-Y. Xu and Y. Hu.

GROWTH OF SOLUTIONS OF NON-HOMOGENEOUS LINEAR DIFFERENTIAL EQUATIONS AND ITS APPLICATIONS

  • Pramanik, Dilip Chandra;Biswas, Manab
    • Korean Journal of Mathematics
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    • v.29 no.1
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    • pp.65-73
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    • 2021
  • In this paper, we investigate the growth properties of solutions of the non-homogeneous linear complex differential equation L(f) = b (z) f + c (z), where L(f) is a linear differential polynomial and b (z), c (z) are entire functions and give some of its applications on sharing value problems.

Dynamic Stiffness of the Scaled Boundary Finite Element Method for Non-Homogeneous Elastic Space (비동질 탄성 무한공간에 대한 비례경계유한요소법의 동적강도행렬)

  • Lee, Gye-Hee
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.23 no.2
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    • pp.165-173
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    • 2010
  • In this paper, the dynamic stiffness of scaled boundary finite element method(SBFEM) was analytically derived to represent the non-homogeneous space. The non-homogeneous parameters were introduced as an expotential value of power function which denoted the non-homogeneous properties of analysis domain. The dynamic stiffness of analysis domain was asymptotically expanded in frequency domain, and the coefficients of polynomial series were determined to satify the radiational condition. To verify the derived dynamic stiffness of domain, the numerical analysis of the typical problems which have the analytical solution were performed as various non-homogeneous parameters. As results, the derived dynamic stiffness adequatlly represent the features of the non-homogeneous space.

Longitudinal Analysis of Body Weight and Feed Intake in Selection Lines for Residual Feed Intake in Pigs

  • Cai, W.;Wu, H.;Dekkers, J.C.M.
    • Asian-Australasian Journal of Animal Sciences
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    • v.24 no.1
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    • pp.17-27
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    • 2011
  • A selection experiment for reduced residual feed intake (RFI) in Yorkshire pigs consisted of a line selected for lower RFI (LRFI) and a random control line (CTRL). Longitudinal measurements of daily feed intake (DFI) and body weight (BW) from generation 5 of this experiment were used. The objectives of this study were to evaluate the use of random regression (RR) and nonlinear mixed models to predict DFI and BW for individual pigs, accounting for the substantial missing information that characterizes these data, and to evaluate the effect of selection for RFI on BW and DFI curves. Forty RR models with different-order polynomials of age as fixed and random effects, and with homogeneous or heterogeneous residual variance by month of age, were fitted for both DFI and BW. Based on predicted residual sum of squares (PRESS) and residual diagnostics, the quadratic polynomial RR model was identified to be best, but with heterogeneous residual variance for DFI and homogeneous residual variance for BW. Compared to the simple quadratic and linear regression models for individual pigs, these RR models decreased PRESS by 1% and 2% for DFI and by 42% and 36% for BW on boars and gilts, respectively. Given the same number of random effects as the polynomial RR models, i.e., two for BW and one for DFI, the non-linear Gompertz model predicted better than the polynomial RR models but not as good as higher order polynomial RR models. After five generations of selection for reduced RFI, the LRFI line had a lower population curve for DFI and BW than the CTRL line, especially towards the end of the growth period.

THE RING OF INVARIANTS OF 3 BY 3 MATRICES

  • Lee Woo
    • Journal of applied mathematics & informatics
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    • v.22 no.1_2
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    • pp.535-539
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    • 2006
  • The ring of invariants of two 2 by 2 matrices C(2, 2) is a polynomial ring with 5 variables [1]. In this paper we find the system of parameters of C(3, 2) by Groebner bases.

A GORENSTEIN IDEAL OF CODIMENSION 4

  • Shin, Yong-Su
    • Journal of the Korean Mathematical Society
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    • v.34 no.1
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    • pp.135-147
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    • 1997
  • Let k be an infinite field and let $X = {P_1, \cdots, P_s}$ be a set of s-distinct points in $P^n$. We denote by $I(X)$ the defining ideal of $X$ in the polynomial ring $R = k[x_0, \cdots, x_n]$ and by A the homogeneous coordinate ring of $X, A = \sum_{t = 0}^{\infty} A_t$.

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