• Journal of the Korean Geotechnical Society
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• v.29 no.1
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• pp.149-159
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• 2013

This paper deals with behaviors of Poisson's ratio with water content through uniaxial compressive strength against 307 individual rock cores, which are classified into sedimentary, igneous and metamorphic rock. Poissons' ratio demonstrates independent behaviors and does not correlate with mechanical and physical parameter of rocks. The water content behavior of Poissson's ratio represents decrease, increase and random style. Rock samples with decreasing behavior demonstrate absolute preponderance above the 70% level. As Poisson' ratio shows independent behaviors, it should be considered based on experimental results of in-situ rock in the process of design, construction, and supervision.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.4
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• pp.275-282
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• 2017

In this paper, using a pattern transformation triggered by deformation, we propose a porous structure that exhibits the characteristic of negative Poisson's ratio in both tension and compression. Due to the lack of torque for rotational motion of ligaments, the existing porous structure of circular holes shows positive Poisson's ratio under tension loading. Also, the porous structure of elliptic holes has a drawback of low durability due to stress concentration. Thus, we design curved ligaments to increase the rotational torque under tension and to alleviate the stress concentration such that strain energy is uniformly distributed in the whole structure. The developed structure possesses better stiffness and durability than the existing structures. It also exhibits the negative Poisson ratio in both compression and tension of 10% nominal strain. Through nonlinear finite element analysis, the performance of developed structure is compared with the existing structure of elliptic holes. The developed structure turns out to be significantly improved in terms of stiffness and durability.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.166-175
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• 1995

When a neutral particle beam(NPB) aimed at the object and receive a small number of neutron signals at the detector without any errors, it obeys Poisson law. Under the two assumptions that neutral particle scattering distribution and aiming errors have a circular Gaussian distributions that neutral particle scattering distribution and aiming errors have a circular Gaussian distribution respectively, an exact probability distribution of neutral particles vecomes a Poisson-power function distribution. We study and prove some properties, such as limiting distribution, unimodality, stochastical ordering, computational recursion fornula, of this distribution. We also prove monotone likelihood ratio(MLR) property of this distribution. Its MLR property can be used to find a criteria for the hypothesis testing problem.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.765-774
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• 2002

Suppose one is given a vector X of a finite set of quantities $X_i$ which are independent Poisson random variables. A null hypothesis $H_0$ about E(X) is to be tested against an alternative hypothesis $H_1$. A quantity $\sum\limits_{i}w_ix_i$ is to be computed and used for the test. The optimal values of $W_i$ are calculated for three cases: (1) signal to noise ratio is used in the test, (2) normal approximations with unequal variances to the Poisson distributions are used in the test, and (3) the Poisson distribution itself is used. The above three cases are considered to the situations that are without background noise and with background noise. A comparison is made of the optimal values of $W_i$ in the three cases for both situations.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.307-315
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• 2002

Suppose one is given a vector X of a finite set of quantities $X_i$ which are independent Poisson signals. A null hypothesis $H_0$ about E(X) is to be tested against an alternative hypothesis $H_1$. A quantity $$\sum\limits_{i}\omega_ix_i$$ is to be computed and used for the test. The optimal values of $\omega_i$ are calculated for three cases : (1) signal to noise ratio is used in the test, (2) normal approximations with unequal variances to the Poisson distributions are used in the test, and (3) the Poisson distribution it self is used. A comparison is made of the optimal values of $\omega_i$ in the three cases as parameter goes to infinity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.851-858
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• 2016

This paper presents a new statistical voice activity detection (VAD) based on the probabilistic interpretation of nonnegative matrix factorization (NMF). The objective function of the NMF using Kullback-Leibler divergence coincides with the negative log likelihood function of the data if the distribution of the data given the basis and encoding matrices is modeled as Poisson distributions. Based on this probabilistic NMF, the VAD is constructed using the likelihood ratio test assuming that speech and noise follow Poisson distributions. Experimental results show that the proposed approach outperformed the conventional Gaussian model-based and NMF-based methods at 0-15 dB signal-to-noise ratio simulation conditions.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.2
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• pp.153-158
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• 2016

The elastic material constants, stiffness constants ($c_{11}$, $c_{12}$, and $c_{44}$), are three unique coefficients that establish the relation between stress and strain. Accurate knowledge of mechanical properties and the stiffness coefficients for silicon is required for design of Micro-Electro-Mechanical Systems (MEMS) devices for proper modeling of stress and strain in electronic packaging. In this work, the stiffness coefficients for silicon as a function of temperature from $-150^{\circ}C$ to $+25^{\circ}C$ have been extracted by using the experimental measurements of Poisson's ratio (${\nu}$) of silicon in several directions.

• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.503-515
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• 1998

When a neutral particle beam(NPB) aimed at the object and receive a small number of neutron signals at the detector, it follows approximately Poisson distribution. Under the four assumptions in the presence of errors and uncertainties for the Poisson parameters, an exact probability distribution of neutral particles have been derived. The probability distribution for the neutron signals received by a detector averaged over the three sources of errors is expressed as a four-dimensional integral of certain data. Two of the four integrals can be evaluated analytically and thereby the integral is reduced to a two-dimensional integral. The monotone likelihood ratio(MLR) property of the distribution is proved by using the Cauchy mean value theorem for the univariate distribution and multivariate distribution. Its MLR property can be used to find a criteria for the hypothesis testing problem related to the distribution.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.2
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• pp.407-412
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• 1990

Elastic modulus of unidirectional short fiber composite has theoretically derived with the consideration of Poisson's ratios of matrix and fiber. Unidirectional short fiber composite is modeled as an aggregate of grains developed by Kerner. Under the assumption of extra strain at fiber ends, the strain distribution along the fiber's length is determined, and the elastic modulus is derived from this distribution. For the consideration of effects of Poisson's ratio, Kerner's results for particulate composites are adapted as boundary conditions. The effect of differences in Poisson's ratio of fiber and matrix on elastic modulus is studied. Proposed equation shows a good agreement with experimental data of Halpin and Tock, et al.

• International Journal of Reliability and Applications
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• v.2 no.4
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• pp.263-268
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• 2001

Shanmugam(1991) generalized the Poisson distribution to capture a restriction on the incidence rate $\theta$ (i.e. $\theta$ ＜ $\beta$, an unknown upper limit), and named it incidence rate restricted Poisson (IRRP) distribution. Using Neyman's C($\alpha$) concept, Shanmugam then devised a hypothesis testing procedure for $\beta$ when $\theta$ remains unknown nuisance parameter. Shanmugam's C ($\alpha$) based .results involve inverse moments which are not easy tools, This article presents an alternate testing procedure based on likelihood ratio concept. It turns out that likelihood ratio test statistic offers more power than the C($\alpha$) test statistic. Numerical examples are included.