• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권6호
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• pp.3166-3187
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• 2017

For "generic" multivariate public key cryptography (MPKC) systems, experts believe that the Unbalanced Oil-Vinegar (UOV) scheme is a feasible signature scheme with good efficiency and acceptable security. In this paper, we address two problems that are to find inversion solution of quadratic multivariate equations and find another structure with some random Oil-Oil terms for UOV, then propose a novel signature scheme based on hyper-sphere (HS-Sign for short) which directly answers these two problems. HS-Sign is characterized by its adding Oil-Oil terms and more advantages compared to UOV. On the one side, HS-Sign is based on a new inversion algorithm from hyper-sphere over finite field, and is shown to be a more secure UOV-like scheme. More precisely, according to the security analysis, HS-Sign achieves higher security level, so that it has larger security parameters choice ranges. On the other side, HS-Sign is beneficial from both the key side and computing complexity under the same security level compared to many baseline schemes. To further support our view, we have implemented 5 different attack experiments for the security analysis and we make comparison of our new scheme and the baseline schemes with simulation programs so as to show the efficiencies. The results show that HS-Sign has exponential attack complexity and HS-Sign is competitive with other signature schemes in terms of the length of the message, length of the signature, size of the public key, size of the secret key, signing time and verification time.

• Wind and Structures
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• 제9권3호
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• pp.231-243
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• 2006

An improvement to the spectral representation algorithm for the simulation of wind velocity fields on large scale structures is proposed in this paper. The method proposed by Deodatis (1996) serves as the basis of the improved algorithm. Firstly, an interpolation approximation is introduced to simplify the computation of the lower triangular matrix with the Cholesky decomposition of the cross-spectral density (CSD) matrix, since each element of the triangular matrix varies continuously with the wind spectra frequency. Fast Fourier Transform (FFT) technique is used to further enhance the efficiency of computation. Secondly, as an alternative spectral representation, the vectors of the triangular matrix in the Deodatis formula are replaced using an appropriate number of eigenvectors with the spectral decomposition of the CSD matrix. Lastly, a turbulent wind velocity field through a vertical plane on a long-span bridge (span-wise) is simulated to illustrate the proposed schemes. It is noted that the proposed schemes require less computer memory and are more efficiently simulated than that obtained using the existing traditional method. Furthermore, the reliability of the interpolation approximation in the simulation of wind velocity field is confirmed.

• Genomics & Informatics
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• 제20권1호
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• pp.8.1-8.14
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• 2022

Despite the success of recent genome-wide association studies investigating longitudinal traits, a large fraction of overall heritability remains unexplained. This suggests that some of the missing heritability may be accounted for by gene-gene and gene-time/environment interactions. In this paper, we develop a Bayesian variable selection method for longitudinal genetic data based on mixed models. The method jointly models the main effects and interactions of all candidate genetic variants and non-genetic factors and has higher statistical power than previous approaches. To account for the within-subject dependence structure, we propose a grid-based approach that models only one fixed-dimensional covariance matrix, which is thus applicable to data where subjects have different numbers of time points. We provide the theoretical basis of our Bayesian method and then illustrate its performance using data from the 1000 Genome Project with various simulation settings. Several simulation studies show that our multivariate method increases the statistical power compared to the corresponding univariate method and can detect gene-time/ environment interactions well. We further evaluate our method with different numbers of individuals, variants, and causal variants, as well as different trait-heritability, and conclude that our method performs reasonably well with various simulation settings.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2017년도 학술발표회
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• pp.421-421
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• 2017

현재 우리나라에서 끊임없이 발생하고 있는 폭풍해일로부터 연안지역의 안전을 확보하기 위해서는 태풍 시 파랑의 거동 및 특성을 정확히 예측하는 것이 중요하다. 폭풍해일 모의실험의 정확성을 향상시키고 폭풍해일의 위험성을 정량화하기 위해서는 해일파고, 파주기, 그리고 폭풍 지속시간 간의 상관성이 분석되어야한다. 이를 위해 본 연구에서는 Copulas(Archimedean) 이론을 이용하여 폭풍해일에 대한 다변량 통계분석이 이루어졌다. 동해안 연안에서 나타나는 파고, 파주기, 태풍 지속시간, 해면수위, 태풍 도착간격시간 간의 의존성을 켄달의 타우 상관계수를 이용하여 조사하였다. Copulas 다변량 통계분석의 결과, 오직 파고와 파주기, 그리고 태풍지속시간만이 명확한 상관성을 나타냈다.

• Geomechanics and Engineering
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• 제16권6호
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• pp.655-667
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• 2018

To evaluate the stability of a rock slope with one pre-exiting vertical crack, this paper performs corresponding probabilistic stability analysis. The existence of cracks is generally ignored in traditional deterministic stability analysis. However, they are widely found in either cohesive soil or rock slopes. The influence of one pre-exiting vertical crack on a rock slope is considered in this study. The safety factor, which is usually adopted to quantity the stability of slopes, is derived through the deterministic computation based on the strength reduction technique. The generalized Hoek-Brown (HB) failure criterion is adopted to characterize the failure of rock masses. Considering high nonlinearity of the limit state function as using nonlinear HB criterion, the multivariate adaptive regression splines (MARS) is used to accurately approximate the implicit limit state function of a rock slope. Then the MARS is integrated with Monte Carlo simulation to implement reliability analysis, and the influences of distribution types, level of uncertainty, and constants on the probability density functions and failure probability are discussed. It is found that distribution types of random variables have little influence on reliability results. The reliability results are affected by a combination of the uncertainty level and the constants. Finally, a reliability-based design figure is provided to evaluate the safety factor of a slope required for a target failure probability.

• Communications for Statistical Applications and Methods
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• 제28권1호
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• pp.59-79
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• 2021

Value at Risk (VaR) is one of the most common risk management tools in finance. Since a portfolio of several assets, rather than one asset portfolio, is advantageous in the risk diversification for investment, VaR for a portfolio of two or more assets is often used. In such cases, multivariate distributions of asset returns are considered to calculate VaR of the corresponding portfolio. Copulas are one way of generating a multivariate distribution by identifying the dependence structure of asset returns while allowing many different marginal distributions. However, they are used mainly for bivariate distributions and are not widely used in modeling joint distributions for many variables in finance. In this study, we would like to examine the performance of various copulas for high dimensional data and several different dependence structures. This paper compares copulas such as elliptical, vine, and hierarchical copulas in computing the VaR of portfolios to find appropriate copula functions in various dependence structures among asset return distributions. In the simulation studies under various dependence structures and real data analysis, the hierarchical Clayton copula shows the best performance in the VaR calculation using four assets. For marginal distributions of single asset returns, normal inverse Gaussian distribution was used to model asset return distributions, which are generally high-peaked and heavy-tailed.

• 한국산학기술학회논문지
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• 제19권3호
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• pp.40-45
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• 2018

생산 공정의 다변량 데이터에 기반한 지능적 공정 감시 및 진단 시스템은 조업의 안정성과 고품질의 제품을 달성하고 경쟁력을 유지하기 위해서는 필수적인 업무 중 하나로 간주되고 있는데, 이와 같은 추세는 공정 이상이 발생하는 경우 안정적이고 경제적인 조업에 큰 영향을 미치는 것에 기인한다. 본 연구에서는 다변량 공정 데이터에 기반한 진단기법을 제시하고 이를 시뮬레이션 공정 데이터를 활용하여 그 성능을 평가하고자 한다. 또한 원 데이터의 전처리 과정의 유무와 비선형 방법론의 활용이 진단 성능에 마치는 영향을 시뮬레이션 공정에서 제시된 15개의 공정 이상에 대해 평가하였다. 그 결과 제안된 방법론이 신뢰할 만한 결과를 주었으며 다른 비교 방법론인 전처리 과정이 없거나 선형 방법론을 사용한 타 방법론 대비 우월한 성능을 보여주었다. 제시된 방법론은 공정 데이터에 기반한 방법론으로서 공정에 대한 수학적 모델이나 지식 모델에 비하여 상대적으로 모델링이 간편하며 공정 데이터의 잡음에 강건하다는 장점을 가진다.

• 응용통계연구
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• 제28권5호
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• pp.1013-1024
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• 2015

본 논문에서는 다변량 DCC(dynamic conditional correlation) GARCH 모형에서 동태적 상관계수를 추정하기 위한 대표적 방법인 쌍별 추정법과 다차원 추정법의 효율성을 비교한다. 이를 위하여 금융 시장의 변동성을 반영하는 다변량 시계열을 생성하고 이에 대한 DCC GARCH 모형을 수립 및 추정하는 시뮬레이션을 실시하였다. 또한 KOSPI 200 섹터지수를 이용하여 포트폴리오를 구성하고 이의 변동성 추정 및 VaR 계산을 통하여 동태적 상관계수 추정에 대한 정확성을 평가하였다. 그 결과로서, 전반적으로 다차원 추정법이 쌍별 추정법보다 우수함을 발견하였다. 특히, 다차원 추정법에서 상대적으로 상관관계가 낮은 시계열을 추가할수록 쌍별 시계열에 대한 동태적 상관계수 추정의 정확성을 높여줌을 발견하였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.540-544
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• 2009

Hydrologic pattern under climate change has been paid attention to as one of the most important issues in hydrologic science group. Rainfall and runoff is a key element in the Earth's hydrological cycle, and associated with many different aspects such as water supply, flood prevention and river restoration. In this regard, a main objective of this study is to evaluate design flood using simulation techniques which can consider a full spectrum of uncertainty. Here we utilize a weather state based stochastic multivariate model as conditional probability model for simulating the rainfall field. A major premise of this study is that large scale climatic patterns are a major driver of such persistent year to year changes in rainfall probabilities. Uncertainty analysis in estimating design flood is inevitably needed to examine reliability for the estimated results. With regard to this point, this study applies a Bayesian Markov Chain Monte Carlo scheme to the NWS-PC rainfall-runoff model that has been widely used, and a case study is performed in Soyang Dam watershed in Korea. A comprehensive discussion on design flood under climate change is provided.

• 응용통계연구
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• 제18권1호
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• pp.99-113
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• 2005

이 논문에서는 카이제곱 구형 대칭성 검정을 제안한다. 이 검정은 검정통계량과 점근적 유의확률을 쉽게 계산할 수 있는 장점이 있다. 이 통계량의 구형 대칭성 가정하의 극한 분포를 도출하고 유한표본에서 잘 부합되는지 모의실험을 통해 살펴본다. 또한 다양한 대립분포에서 기존의 구형 대칭성 검정과 검정력을 비교하는 모의실험을 수행하며 마지막으로 실제 자료 분석 예제를 제공한다.