• 제목/요약/키워드: random polynomials

검색결과 41건 처리시간 0.025초

Relation between the Irreducible Polynomials that Generates the Same Binary Sequence Over Odd Characteristic Field

  • Ali, Md. Arshad;Kodera, Yuta;Park, Taehwan;Kusaka, Takuya;Nogmi, Yasuyuki;Kim, Howon
    • Journal of information and communication convergence engineering
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    • 제16권3호
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    • pp.166-172
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    • 2018
  • A pseudo-random sequence generated by using a primitive polynomial, trace function, and Legendre symbol has been researched in our previous work. Our previous sequence has some interesting features such as period, autocorrelation, and linear complexity. A pseudo-random sequence widely used in cryptography. However, from the aspect of the practical use in cryptographic systems sequence needs to generate swiftly. Our previous sequence generated by utilizing a primitive polynomial, however, finding a primitive polynomial requires high calculating cost when the degree or the characteristic is large. It’s a shortcoming of our previous work. The main contribution of this work is to find some relation between the generated sequence and irreducible polynomials. The purpose of this relationship is to generate the same sequence without utilizing a primitive polynomial. From the experimental observation, it is found that there are (p - 1)/2 kinds of polynomial, which generates the same sequence. In addition, some of these polynomials are non-primitive polynomial. In this paper, these relationships between the sequence and the polynomials are shown by some examples. Furthermore, these relationships are proven theoretically also.

Genetic analysis of milk production traits of Tunisian Holsteins using random regression test-day model with Legendre polynomials

  • Zaabza, Hafedh Ben;Gara, Abderrahmen Ben;Rekik, Boulbaba
    • Asian-Australasian Journal of Animal Sciences
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    • 제31권5호
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    • pp.636-642
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    • 2018
  • Objective: The objective of this study was to estimate genetic parameters of milk, fat, and protein yields within and across lactations in Tunisian Holsteins using a random regression test-day (TD) model. Methods: A random regression multiple trait multiple lactation TD model was used to estimate genetic parameters in the Tunisian dairy cattle population. Data were TD yields of milk, fat, and protein from the first three lactations. Random regressions were modeled with third-order Legendre polynomials for the additive genetic, and permanent environment effects. Heritabilities, and genetic correlations were estimated by Bayesian techniques using the Gibbs sampler. Results: All variance components tended to be high in the beginning and the end of lactations. Additive genetic variances for milk, fat, and protein yields were the lowest and were the least variable compared to permanent variances. Heritability values tended to increase with parity. Estimates of heritabilities for 305-d yield-traits were low to moderate, 0.14 to 0.2, 0.12 to 0.17, and 0.13 to 0.18 for milk, fat, and protein yields, respectively. Within-parity, genetic correlations among traits were up to 0.74. Genetic correlations among lactations for the yield traits were relatively high and ranged from $0.78{\pm}0.01$ to $0.82{\pm}0.03$, between the first and second parities, from $0.73{\pm}0.03$ to $0.8{\pm}0.04$ between the first and third parities, and from $0.82{\pm}0.02$ to $0.84{\pm}0.04$ between the second and third parities. Conclusion: These results are comparable to previously reported estimates on the same population, indicating that the adoption of a random regression TD model as the official genetic evaluation for production traits in Tunisia, as developed by most Interbull countries, is possible in the Tunisian Holsteins.

A DEGREE REDUCTION METHOD FOR AN EFFICIENT QUBO FORMULATION FOR THE GRAPH COLORING PROBLEM

  • Hyosang Kang;Hyunwoo Jung;Chaehwan Seol;Namho Hong;Hyunjin Lim;Seokhyun Um
    • 한국수학교육학회지시리즈B:순수및응용수학
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    • 제31권1호
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    • pp.57-81
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    • 2024
  • We introduce a new degree reduction method for homogeneous symmetric polynomials on binary variables that generalizes the conventional degree reduction methods on monomials introduced by Freedman and Ishikawa. We also design an degree reduction algorithm for general polynomials on binary variables, simulated on the graph coloring problem for random graphs, and compared the results with the conventional methods. The simulated results show that our new method produces reduced quadratic polynomials that contains less variables than the reduced quadratic polynomials produced by the conventional methods.

EXCEL Tools for Geotechnical Reliability Analysis

  • Phoon, Kok-Kwang
    • 한국지반공학회:학술대회논문집
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    • 한국지반공학회 2008년도 추계 학술발표회
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    • pp.375-394
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    • 2008
  • This paper discusses two user-friendly reliability techniques that could be implemented easily using the ubiquitous EXCEL. The techniques are First-Order Reliability Method with non-Gaussian random variables expressed using Hermite polynomials and collocation-based stochastic response surface method. It is believed that ease of implementation would popularize use of reliability-based design in practice.

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A natural frequency sensitivity-based stabilization in spectral stochastic finite element method for frequency response analysis

  • Lee, Gil-Yong;Jin, Seung-Seop;Park, Yong-Hwa
    • Structural Engineering and Mechanics
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    • 제75권3호
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    • pp.311-325
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    • 2020
  • In applying the spectral stochastic finite element methods to the frequency response analysis, the conventional methods are known to give unstable and inaccurate results near the natural frequencies. To address this issue, a new sensitivity based stabilized formulation for stochastic frequency response analysis is proposed in this paper. The main difference over the conventional spectral methods is that the polynomials of random variables are applied to both numerator and denominator in approximating the harmonic response solution. In order to reflect the resonance behavior of the structure, the denominator polynomials is constructed by utilizing the natural frequency sensitivity and the random mode superposition. The numerator is approximated by applying a polynomial chaos expansion, and its coefficients are obtained through the Galerkin or the spectral projection method. Through various numerical studies, it is seen that the proposed method improves accuracy, especially in the vicinities of structural natural frequencies compared to conventional spectral methods.

Some Properties of Maximum Length Cellular Automata

  • Cho, Sung-Jin;Kim, Han-Doo;Choi, Un-Sook
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제3권2호
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    • pp.137-145
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    • 1999
  • In this paper, We consider two-dimensional Maximum Length Cellular Automata (2-D MLCA) as an extension of the 1-D MLCA. 2-D MLCA can display much better random patterns than those generated by 1-D CA and LFSR. To generate random pattern, a CA should have a maximum length cycle. So, it is necessary to find MLCA that the characteristic polynomial of the transition matrix is primitive. New boundary conditions of 3 types are proposed and some rules having primitive polynomials of 2-D MLCA are found.

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한계상태식의 3차 다항식 근사를 통한 구조물 신뢰도 평가 (Structure Reliability Analysis using 3rd Order Polynomials Approximation of a Limit State Equation)

  • 이승규;김성찬;김태욱
    • 한국전산구조공학회논문집
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    • 제26권3호
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    • pp.183-189
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    • 2013
  • 본 논문에서는 불확실성을 확률변수로 가정하고 구조물의 파손기준을 한계상태식(Limit State Equation)으로 정의하였다. 한계상태식을 Fleishman의 3차 다항식으로 근사하고 이론적인 확률 모멘트(Moments)를 계산하였다. Fleishman은 표준정규 분포 확률변수에 대해서만 3차 다항식을 제시하였으나, 본 논문에서는 이를 확장하여 베타, 감마, 균일 분포 등 다양한 확률 변수에 적용하였다. 확률 모멘트를 계산하기 위해서 누률(Cumulants)과 정규화된 한계상태식을 활용하였으며, 피어슨 시스템(Pearson System)을 통해 한계상태식의 확률분포를 근사하였다.

Random Regression Models Are Suitable to Substitute the Traditional 305-Day Lactation Model in Genetic Evaluations of Holstein Cattle in Brazil

  • Padilha, Alessandro Haiduck;Cobuci, Jaime Araujo;Costa, Claudio Napolis;Neto, Jose Braccini
    • Asian-Australasian Journal of Animal Sciences
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    • 제29권6호
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    • pp.759-767
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    • 2016
  • The aim of this study was to compare two random regression models (RRM) fitted by fourth ($RRM_4$) and fifth-order Legendre polynomials ($RRM_5$) with a lactation model (LM) for evaluating Holstein cattle in Brazil. Two datasets with the same animals were prepared for this study. To apply test-day RRM and LMs, 262,426 test day records and 30,228 lactation records covering 305 days were prepared, respectively. The lowest values of Akaike's information criterion, Bayesian information criterion, and estimates of the maximum of the likelihood function (-2LogL) were for $RRM_4$. Heritability for 305-day milk yield (305MY) was 0.23 ($RRM_4$), 0.24 ($RRM_5$), and 0.21 (LM). Heritability, additive genetic and permanent environmental variances of test days on days in milk was from 0.16 to 0.27, from 3.76 to 6.88 and from 11.12 to 20.21, respectively. Additive genetic correlations between test days ranged from 0.20 to 0.99. Permanent environmental correlations between test days were between 0.07 and 0.99. Standard deviations of average estimated breeding values (EBVs) for 305MY from $RRM_4$ and $RRM_5$ were from 11% to 30% higher for bulls and around 28% higher for cows than that in LM. Rank correlations between RRM EBVs and LM EBVs were between 0.86 to 0.96 for bulls and 0.80 to 0.87 for cows. Average percentage of gain in reliability of EBVs for 305-day yield increased from 4% to 17% for bulls and from 23% to 24% for cows when reliability of EBVs from RRM models was compared to those from LM model. Random regression model fitted by fourth order Legendre polynomials is recommended for genetic evaluations of Brazilian Holstein cattle because of the higher reliability in the estimation of breeding values.

Genetic Parameters for Litter Size in Pigs Using a Random Regression Model

  • Lukovic, Z.;Uremovic, M.;Konjacic, M.;Uremovic, Z.;Vincek, D.
    • Asian-Australasian Journal of Animal Sciences
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    • 제20권2호
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    • pp.160-165
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    • 2007
  • Dispersion parameters for the number of piglets born alive were estimated using a repeatability and random regression model. Six sow breeds/lines were included in the analysis: Swedish Landrace, Large White and both crossbred lines between them, German Landrace and their cross with Large White. Fixed part of the model included sow genotype, mating season as month-year interaction, parity and weaning to conception interval as class effects. The age at farrowing was modelled as a quadratic regression nested within parity. The previous lactation length was fitted as a linear regression. Random regressions for parity on Legendre polynomials were included for direct additive genetic, permanent environmental, and common litter environmental effects. Orthogonal Legendre polynomials from the linear to the cubic power were fitted. In the repeatability model estimate of heritability was 0.07, permanent environmental effect as ratio was 0.04, and common litter environmental effect as ratio was 0.01. Estimates of genetic parameters with the random regression model were generally higher than in the repeatability model, except for the common litter environmental effect. Estimates of heritability ranged from 0.06 to 0.10. Permanent environmental effect as a ratio increased along a trajectory from 0.03 to 0.11. Magnitudes of common litter effect were small (around 0.01). The eigenvalues of covariance functions showed that between 7 and 8 % of genetic variability was explained by individual genetic curves of sows. This proportion was mainly covered by linear and quadratic coefficients. Results suggest that the random regression model could be used for genetic analysis of litter size.