• Title/Summary/Keyword: Common Random Number

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An Efficient ID-Based Multisignature Scheme Based on the High Residuosity Problem (고차잉여류 문제에 기반을 둔 다중서명 방식)

  • Lee, Bo-Yeong;Park, Taek-Jin;Won, Dong-Ho
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.3
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    • pp.664-671
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    • 1999
  • Itakura and Nakamura proposed the first multisignature scheme based on RSA signature scheme. But if many users sign on one paper, then their scheme has a reblocking problem. In 1991, Ohta and Okamoto proposed a multisignature scheme by using Fiat-Shamir signature scheme. But in this scheme, the group of signers must generate common random number in the first round, and in the second round, they sign the message with common random number. Also L.Harn proposed a multsignature scheme which is based on the ElGamal's. In korea, S.D.Kim et al. at ICEIC'95 conference, proposed an efficient sequential multisignature scheme by using the modified Park-Won scheme. This scheme is not require an additional round to generate common random number, and has fixed signature length. In this paper, we analyze problem of Kim's multisignature scheme, and propose a new multisignature scheme based on ${\gamma}$\ulcorner residuosity problem.

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Genetic Similarity and Difference between Common Carp and Israeli Carp (Cyprinus carpio) Based on Random Amplified Polymorphic DNAs Analyses

  • Yoon, Jong-Man
    • Animal cells and systems
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    • v.5 no.4
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    • pp.333-339
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    • 2001
  • Common carp (Cyprinus carpio) and its aquaculture breed Israeli carp samples were obtained from two separate aquaculture facilities under the similar raising conditions during two years in the Kunsan National University, Korea. Genomic DNA was isolated from the common carp and Israeli carp for identification of genetic characteristics and genomic polymorphisms by polymerase chain reaction amplification of DNA using arbitrary primers. The arbitrary primer No.21 (ACTTCGCCAC) yielded the highest number of fragments with the average of 15.0 among the primers used in Israeli carp. A tota1 of 294 polymorphic products in common carp and 336 in Israeli carp were observed by random primers. The average number of polymorphic products generated by random RAPD primer No. 2 (GTAGAC-CCGT) showed 8.0 in Israeli carp. On average, each random RAPD primer produced 5.4 amplified polymorphic products in common carp and 6.2 in Israeli carp. An average genetic similarity (BS value) was 0.44$\pm$0.05 within the common carp and 0.32$\pm$0.04 within the Israeli carp. The degree of similarity frequency (BS) between two carps was 0.67 as generated by the primer No. 19 (GACGGATCAG). The average level of bandsharing was 0.57$\pm$0.03 between the two carps. Accordingly, the two carp populations were genetically a little distant. The electrophoretic analysis of PCR-RAPD products showed middle levels of variation between the two carp populations. This result implies that the genetic diversity among intra-population may be higher when compared with that between the two carps. The RAPD polymorphism generated by these random primers might be used as a genetic marker for populations or lines identification in important aquacultural carp.

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Application of Central Composite Design in Simulation Experiment (시뮬레이션 실험에서 중심합성계획의 응용)

  • 권치명
    • Proceedings of the Korea Society for Simulation Conference
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    • 2004.05a
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    • pp.41-47
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    • 2004
  • 중심합성계획(central composite design: ccd)은 반응 표면이 곡면적인 특성을 나타낼때 반응 공간을 추정하기 위해 사용되는 실험계획이다. 반응공간이 2차 회귀모형으로 나타나는 경우에 반응곡면의 변화량을 알기 위해서는 변수의 수준이 3이상이 되어야하는데 ccd는 적은 횟수의 실험으로 곡면을 효과적으로 추정하기 위해 2$^{k}$ 요인실험에 추가적으로 중심점(central point)과 축점(axial point)을 표본점에 포함시키는 계획이다. 본 연구에서는 시뮬레이션 실험에서 반응변수가 2차 회귀모형으로 근사되는 경우에 cod를 이용하여 관심 성과치의 반응표면을 추정하고자 한다. 일반적인 실험에서와는 달리 시뮬레이션 실험에서는 두개의 표본점(인자 수준의 조합)에서 분석자가 공통 난수계열(common random number series)을 부여하여 시뮬레이션 시스템 요소의 변화과정을 유사하게 통제할 수 있다. 일반적으로 공통난수법(common random number method)에 의해 얻어지는 두 표본점에서의 반응변수는 서로 양의 상관관계를 가지며 대조 난수(antithetic random number)에 의한 두 반응변수는 음의 상관성을 가지는 것으로 알려졌다. 본 연구는 ccd의 표본점에 공통난수와 대조난수 법을 이용하여 회귀모형의 파라미터를 효과적으로 추정하는 방법을 조사하고 이를 (s, S) 재고관리 모형에 적용하여 그 효율성을 평가하고자 한다.

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POISSON APPROXIMATION OF INDUCED SUBGRAPH COUNTS IN AN INHOMOGENEOUS RANDOM INTERSECTION GRAPH MODEL

  • Shang, Yilun
    • Bulletin of the Korean Mathematical Society
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    • v.56 no.5
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    • pp.1199-1210
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    • 2019
  • In this paper, we consider a class of inhomogeneous random intersection graphs by assigning random weight to each vertex and two vertices are adjacent if they choose some common elements. In the inhomogeneous random intersection graph model, vertices with larger weights are more likely to acquire many elements. We show the Poisson convergence of the number of induced copies of a fixed subgraph as the number of vertices n and the number of elements m, scaling as $m={\lfloor}{\beta}n^{\alpha}{\rfloor}$ (${\alpha},{\beta}>0$), tend to infinity.

Application of Common Random Numbers in Simulation Experiments Using Central Composite Design (중심합성계획 시뮬레이션 실험에서 공통난수의 활용)

  • Kwon, Chi-Myung
    • Journal of the Korea Society for Simulation
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    • v.23 no.3
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    • pp.11-17
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    • 2014
  • The central composite design (CCD) is often used to estimate the second-order linear model. This paper uses a correlation induction strategy of common random numbers (CRN) in simulation experiment and utilizes the induced correlations to obtain better estimates for the second-order linear model. This strategy assigns the CRN to all design points in the CCD. An appropriate selection of the axial points in CCD makes the weighted least squares (WLS) estimator be equivalent to ordinary least squares (OLS) estimator in estimating the linear model parameters of CCD. We analytically investigate the efficiency of this strategy in estimation of model parameters. Under certain conditions, this correlation induction strategy yields better results than independent random number strategy in estimating model parameters except intercept. The simulation experiment on a selected model supports such results. We expect a suggested random number assignment is useful in application of CCD in simulation experiments.

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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    • v.20 no.2
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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.

Estimation Using Monte Carlo Methods in Nonlinear Random Coefficient Models (몬테카를로법을 이용한 비선형 확률계수모형의 추정)

  • 김성연
    • Journal of the Korea Society for Simulation
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    • v.10 no.3
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    • pp.31-46
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    • 2001
  • Repeated measurements on units under different conditions are common in biological and biomedical studies. In a number of growth and pharmacokinetic studies, the relationship between the response and the covariates is assumed to be nonlinear in some unknown parameters and the form remains the same for all units. Nonlinear random coefficient models are used to analyze such repeated measurement data. Extended least squares methods are proposed in the literature for estimating the parameters of the model. However, neither objective function has closed form expression in practice. This paper proposes Monte Carlo methods to estimate the objective functions and the corresponding estimators. A simulation study that compare various methods is included.

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Optical Implementation of Improved IPA Model Using Hierarchical Recognition Algorithm (계층적 인식 알고리즘을 이용한 개선된 패턴상호연상모델의 광학적 구현)

  • 하재홍;김성용;김수중
    • Journal of the Korean Institute of Telematics and Electronics A
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    • v.31A no.7
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    • pp.55-62
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    • 1994
  • Interpattern association (IPA) model which the interconnection weight matrix(IWM) is constructed by the association between patterns is effective in similar pattern recognitions. But, if the number of reference patterns is increased, the ability of recognition is decreased. Using a hierarchical recognition algorithm which adopts the tree search strategy, we classified reference patterns into sub-groups by similarity. In IPA model, if input includes random noise we make it converge to reference pattern by means of input includes random noise we make it converge to reference pattern by means of increasing the number of pixels of prohibited state in IWM. In relation to reference patterns the pixel of prohibited state made partially prohibited state of no connected state using which is not included common and feature regions by each reference patterns.

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A research on the key factors for classification of diabetes based on random forest

  • Shin, Yong sub;Lee, Namju;Hwang, Chigon
    • International Journal of Internet, Broadcasting and Communication
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    • v.12 no.3
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    • pp.102-107
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    • 2020
  • Recently, the number of people visiting the hospital is increasing due to diabetes. According to the Korean Diabetes Association, statistically, 1 in 7 adults over the age of 30 are suffering from diabetes. As such, diabetes is one of the most common diseases among modern people. In this paper, in addition to blood sugar, which is widely used for diabetes awareness, BMI, which is known to be related to diabetes, triglycerides and cholesterol that cause various complications in diabetics it was studied using random forest techniques and decision trees known to be effective for classification. The importance of each element was confirmed using the results and characteristic importance derived using two techniques. Through this, we studied the diabetes-related relationship between BMI, triglyceride, and cholesterol as well as blood sugar, a factor that diabetic patients should pay much attention to.