• The Korean Journal of Applied Statistics
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• v.25 no.5
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• pp.775-783
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• 2012

Several statistical models for bivariate poisson data are suggested and used to analyze 2011 K-league data. Our interest is composed of two purposes: The first purpose is to exploit potential attacking and defensive abilities of each team. Particular, a bivariate poisson model with diagonal inflation is incorporated for the estimation of draws. A joint model is applied to estimate an association between poisson distribution and probability of draw. The second one is to investigate causes on scoring time of goals and a regression technique of recurrent event data is applied. Some related future works are suggested.

• 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.

• IE interfaces
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• v.17 no.1
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• pp.1-12
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• 2004

In a modern semiconductor device manufacturing industry, statistical bin limits on wafer level test bin data are used for minimizing value added to defective product as well as protecting end customers from potential quality and reliability excursion. Most wafer level test bin data show skewed distributions. By Monte Carlo simulation, this paper evaluates methods and sample size effect regarding determination of statistical bin limits. In the simulation, it is assumed that wafer level test bin data follow the Poisson distribution. Hence, typical shapes of the data distribution can be specified in terms of the distribution's parameter. This study examines three different methods; 1) percentile based methodology; 2) data transformation; and 3) Poisson model fitting. The mean square error is adopted as a performance measure for each simulation scenario. Then, a case study is presented. Results show that the percentile and transformation based methods give more stable statistical bin limits associated with the real dataset. However, with highly skewed distributions, the transformation based method should be used with caution in determining statistical bin limits. When the data are well fitted to a certain probability distribution, the model fitting approach can be used in the determination. As for the sample size effect, the mean square error seems to reduce exponentially according to the sample size.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.603-610
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• 2003

The influence of Poisson's ratio on the tensile strength of brittle materials is neglected in many studies. When brittle materials are loaded in compression or impact, substantial tensile stresses are induced within the materials. These tensile stresses are responsible for splitting failure of the materials. In this paper, the state of stress in a spherical particle due to two diametrically opposed forces is analyzed theoretically. A simple equation for the state of stress at the center of the particle is obtained. An analysis of the distribution of stresses along the z-axis due to distributed pressures and concentrated forces, and on diametrically horizontal plane due to concentrated forces, shows that it is reasonable to propose the tensile stress at the center of the particle at the point of failure as a tensile strength of the particle. Moreover, the tensile strength is a function of the Poisson's ratio of the material. As the state of stress along the z-axis in an irregular specimen tends to be similar to that in a spherical particle compressed diametrically with the same force, this tensile strength has some validity for irregular particles as well. Therefore, it can be proposed as the tensile strength for brittle materials generally. The effect of Poisson's ratio on the tensile strength is discussed.

• Structural Engineering and Mechanics
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• v.76 no.5
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• pp.653-661
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• 2020

The paper presents a study regarding rubber compressibility behavior. The objective is to analyze the effect of compression degree of rubber on its mechanical properties and propose a new methodology based on reverse engineering to predict compressibility degree based on uniaxial stretching test and Finite Element Analysis (FEA). In general, rubbers are considered to be almost incompressible and Poisson's ratio is close to 0.5. Since this property is intimately related to the rubber packing density, little changes in Poisson's ratio can lead to significant changes regarding mechanical behavior. The deviatory hyperelastic constants were obtained through experimental data fitting by least squares method for the most relevant constitutive models implemented in commercial software Abaqus, such as: Neo-Hooke, Mooney-Rivlin, Ogden, Yeoh and Arruda-Boyce, whereas the hydrostatic part was determined through an optimization algorithm implemented in the Abaqus environment by Python scripting. The simulation results presented great influence of the Poisson's ratio in the rubber specimen mechanical behavior mainly for high strain levels. A conventional pure volumetric compression test was also carried out in order to compare the results obtained by the proposed methodology.

• Journal of the Korean Society for Advanced Composite Structures
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• v.1 no.2
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• pp.29-35
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• 2010

In addition to the Young's modulus, the Poisson's ratio is also at the center of attention in the field stochastic finite element analysis since the parameters play an important role in determining structural behavior. Accordingly, the sole effect of this parameter on the response variability is of importance from the perspective of estimation of uncertain response. To this end, a formulation to determine the response variability in laminate composite plates due to the spatial randomness of Poisson's ratio is suggested. The independent contributions of random Poisson's ratiocan be captured in terms of sub-matrices which include the effect of the random parameter in the same order, which can be attained by using the Taylor's series expansion about the mean of the parameter. In order to validate the adequacy of the proposed formulation, several example analyses are performed, and then the results are compared with Monte Carlo simulation (MCS). A good agreement between the suggested scheme and MCS is observed showing the adequacy of the scheme.

• Communications for Statistical Applications and Methods
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• v.26 no.6
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• pp.527-538
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• 2019

This paper considers the issue of obtaining the optimal design in Poisson regression model when the sample size is small. Poisson regression model is widely used for the analysis of count data. Asymptotic theory provides the basis for making inference on the parameters in this model. However, for small size experiments, asymptotic approximations, such as unbiasedness, may not be valid. Therefore, first, we employ the second order expansion of the bias of the maximum likelihood estimator (MLE) and derive the mean square error (MSE) of MLE to measure the quality of an estimator. We then define DM-optimality criterion, which is based on a function of the MSE. This criterion is applied to obtain locally optimal designs for small size experiments. The effect of sample size on the obtained designs are shown. We also obtain locally DM-optimal designs for some special cases of the model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1537-1542
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• 2011

In this paper, the subthreshold characteristics have been analyzed for various oxide thickness of double gate MOSFET(DGMOSFET) using Poisson's equation with nonuniform doping distribution. The DGMOSFET is extensively been studying since it can shrink the short channel effects(SCEs) in nano device. The degradation of subthreshold swing(SS) known as SCEs has been presented using analytical for, of Poisson's equation with nonuniform doping distribution for DGMOSFET. The SS have been analyzed for, change of gate oxide thickness to be the most important structural parameters of DGMOSFET. To verify this potential and transport models of thus analytical Poisson's equation, the results have been compared with those of the numerical Poisson's equation, and subthreshold swing has been analyzed using this models for DGMOSFET.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1481-1486
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• 2013

In this paper, a new two dimensional (2D) analytical model of a Dual Material Gate tunnel field effect transistor (DMG TFET) is presented. The parabolic approximation technique is used to solve the 2-D Poisson equation with suitable boundary conditions. The simple and accurate analytical expressions for surface potential and electric field are derived. The electric field distribution can be used to calculate the tunneling generation rate and numerically extract tunneling current. The results show a significant improvement of on-current and reduction in short channel effects. Effectiveness of the proposed method has been confirmed by comparing the analytical results with the TCAD simulation results.

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.103-110
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• 2012

PURPOSES : In Korea, over 70 percent of the land consists of mountainous and rolling area. Thus, tunnels continue its upward trend as road network are extended. In these circumstances, the importance of tunnel has been increased nowadays and then its safety investigation and research should be performed. This study is focus on confirming and improving the safety of tunnel. On tunnel hood, sunglare effect can irritate driver's behavior instantly and this can result in incident. METHODS : The study of this phenomenon is rarely conducted in domestic and foreign papers, so there is no proper measure for this. This study analyzes the driving environment of the effect of sunglare effect on tunnel hood. RESULTS : Traffic accidents stem from complex set of factors. This study build the Traffic Accident Prediction Models to find out the effect of sunglare effect on tunnel's hood. The independent variables are traffic volume, geometric design of road, length of tunnel and road side environment. Using these variables, this model estimates accident frequency on tunnel hood by Poisson regression model and Negative binomial regression model. Although Poisson regression model have more proper goodness of fit than Negative binomial regression model, Poisson regression model has overdipersion problem. So the Negative binomial regression model is used in this analysis. CONCLUSIONS : Consequently, the model shows that sunglare effect can play a role in driving safety on tunnel hood. As a result, the information of sunglare effect should be noticed ahead of tunnel hood so this can prevent drivers from being in hazard situation.