• Journal of the Korean Society of Safety
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• v.30 no.2
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• pp.70-76
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• 2015

This study deals with the traffic accident of circular intersections. The purpose of the study is to develop the accident models by traffic violation type. In pursuing the above, this study gives particular attention to analyzing various factors that influence traffic accident and developing such the optimal models as Poisson and Negative binomial regression models. The main results are the followings. First, 4 negative binomial models which were statistically significant were developed. This was because the over-dispersion coefficients had a value greater than 1.96. Second, the common variables in these models were not adopted. The specific variables by model were analyzed to be traffic volume, conflicting ratio, number of circulatory lane, width of circulatory lane, number of traffic island by access road, number of reduction facility, feature of central island and crosswalk.

• The Journal of Fisheries Business Administration
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• v.36 no.2 s.68
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• pp.121-134
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• 2005

In order to evaluate the effectiveness of management measures and to provide policy suggestions for the allocation of total allowable catch between recreational and commercial sectors, the economic value of red grouper recreational fishery in the United States Gulf of Mexico was estimated using a Travel Cost Method(TCM), Due to the characteristic of count data, a Poisson model(PM) and a Negative binomial model(NBM) were used in the TCM. Results of models showed that the NBM was statistically more suitable than the PM since the overdispersion problem occurred in the PM. Results also indicated all signs of the estimated parameters were as expected and were significant, except for a Boat parameter in both models. Based on the results of NBM, the total economic value of the recreational red grouper fishery was estimated to be $\$698.6$ and the value per trip was $\$179.5$. In addition, the total changes in expected consumer surplus due to changes in catch rates was $ \$42.3$.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.11
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• pp.1290-1298
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• 1992

In this paper, the Poisson's equation is solved two-dimensionally without employing any fitting parameters, and the model formulation of a short-channel MOSFET is accomplished fully analytically. It automatically derives a very accurate drain current expression that can be used simultaneously for strong inversion, subthreshold, and saturation regions. Furthermore, this model gives a unified explanation for the short-channel effect, the body effect, the DIBL effect, and even the variation of the effective carrier mobility. The obtained expression of the threshold voltage also includes the dependence on the oxide thickness, the n+ junction depth, and temperature.

• Journal of Communications and Networks
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• v.17 no.5
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• pp.534-540
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• 2015

In this paper we propose an analytical model for jitter, wherein we implement the interrupted Poisson process (IPP) for incoming traffic. First, we obtain an analytical model for the jitter on one node with respect to the phase probabilities, traffic load, and tagged traffic share in the aggregate traffic flow. Then, we analyze N-node cases, and propose a model for end-to-end jitter. Our analysis leads to some fast-to-compute approximations that can be used for future network design or admission control. Finally, we validate our analytical results by comparing them with previous results for limit cases, as well as with event-driven simulations. We propose the use of our results as guidelines for jitter evaluation of real IP traffic.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.845-852
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• 2010

The outcomes of counts commonly occur in the area of disease mapping for mortality rates or disease rates. A Poisson distribution is usually assumed as a model of disease rates in conjunction with a gamma prior. The small area typically refers to a small geographical area or demographic group for which very little information is available from the sample surveys. Under this situation the model-based estimation is very popular, in which the auxiliary variables from various administrative sources are used. The empirical Bayes estimator under Poissongamma model has been considered with its accuracy measures. An accuracy measure using a bootstrap samples adjust the underestimation incurred by the posterior variance as an estimator of true mean squared error. We explain the suggested method through a practical dataset of hitters in baseball games. We also perform a Monte Carlo study to compare the accuracy measures of mean squared error.

• East Asian Economic Review
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• v.26 no.2
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• pp.143-169
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• 2022

This study investigates the effect of economic factors on immigration using the gravity model of immigration. Cross-sectional regression and panel data analyses are conducted from 2000 to 2019 using the OECD International Migration Database, which consists of 36 destination countries and 201 countries of origin. The Poisson pseudo-maximum-likelihood method, which can effectively correct potential biased estimates caused by zeros in the immigration data, is used for estimation. The results indicate that the economic factors strengthened after the global financial crisis. Additionally, this effect varies depending on the type of immigration (the income level of origin country). The gravity model applied to immigration performs reasonably well, but it is necessary to consider the country-specific and time-varying characteristics.

• Geophysics and Geophysical Exploration
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• v.10 no.1
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• pp.1-18
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• 2007

Non-linear elastic wavefield inversion is a powerful method for estimating elastic parameters for physical constraints that determine subsurface rock and properties. Here, I introduce six elastic-wave velocity models by reconstructing elastic-wave velocity variations from real data and a 2D elastic-wave velocity model. Reflection seismic data information is often decoupled into short and long wavelength components. The local search method has difficulty in estimating the longer wavelength velocity if the starting model is far from the true model, and source frequencies are then changed from lower to higher bands (as in the 'frequency-cascade scheme') to estimate model elastic parameters. Elastic parameters are inverted at each inversion step ('simultaneous mode') with a starting model of linear P- and S-wave velocity trends with depth. Elastic parameters are also derived by inversion in three other modes - using a P- and S-wave velocity basis $('V_P\;V_S\;mode')$; P-impedance and Poisson's ratio basis $('I_P\;Poisson\;mode')$; and P- and S-impedance $('I_P\;I_S\;mode')$. Density values are updated at each elastic inversion step under three assumptions in each mode. By evaluating the accuracy of the inversion for each parameter set for elastic models, it can be concluded that there is no specific difference between the inversion results for the $V_P\;V_S$ mode and the $I_P$ Poisson mode. The same conclusion is expected for the $I_P\;I_S$ mode, too. This gives us a sound basis for full wavelength elastic wavefield inversion.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.5
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• pp.21-28
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• 2007

In this paper, in order to derive the two-dimensional field effect of n-InAlAs/InGaAs HEMTs, we suggested analytical model by solving the two-dimensional Poisson's equation in both InAlAs and InGaAs regions by taking into account the longitudinal field variation, field-dependent mobility, and the continuity condition of the channel current flowing within the quantum well shaped channel. Derived expressions for long and short channel devices would be applicable to the entire operating regions in a unified manner. Simulation results show that the drain saturation current increases and the threshold voltage decreases as drain voltage increases. Compared with the conventional model, the present model may offer more reasonable explanation for the drain-induced threshold voltage roll-off, the Early effect, and the channel length modulation effect. Furthermore, it is expected that the proposed model would provide more reasonable theoretical basis for analyzing various long and short channel InAlAs/InGaAs HEMT devices.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.6
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• pp.1338-1342
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• 2011

In this paper, threshold voltage characteristics have been analyzed as one of short channel effects occurred in double gate(DG)MOSFET to be next-generation devices. The Gaussian function to be nearly experimental distribution has been used as carrier distribution to solve Poisson's equation, and threshold voltage has been investigated according to projected range and standard projected deviation, variables of Gaussian function. The analytical potential distribution model has been derived from Poisson's equation, and threshold voltage has been obtained from this model. Since threshold voltage has been defined as gate voltage when surface potential is twice of Fermi potential, threshold voltage has been derived from analytical model of surface potential. Those results of this potential model are compared with those of numerical simulation to verify this model. As a result, since potential model presented in this paper is good agreement with numerical model, the threshold voltage characteristics have been considered according to the doping profile of DGMOSFET.

• The Korean Journal of Applied Statistics
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• v.19 no.1
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• pp.1-12
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• 2006

The aim of this study is to analyse a survey data on the number of charitable donations using a mixture of two Poisson regression models. The survey was conducted in 2002 by Volunteer 21, an nonprofit organization, based on Koreans, who were older than 20. The mixture of two Poisson distributions is used to model the number of donations based on the empirical distribution of the data. The mixture of two Poisson distributions implies the whole population is subdivided into two groups, one with lesser number of donations and the other with larger number of donations. We fit the mixture of Poisson regression models on the number of donations to identify significant covariates. The expectation-maximization algorithm is employed to estimate the parameters. We computed 95% bootstrap confidence interval based on bias-corrected and accelerated method and used then for selecting significant explanatory variables. As a result, the income variable with four categories and the volunteering variable (1: experience of volunteering, 0: otherwise) turned out to be significant with the positive regression coefficients both in the lesser and the larger donation groups. However, the regression coefficients in the lesser donation group were larger than those in larger donation group.