• The Korean Journal of Applied Statistics
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• v.24 no.4
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• pp.677-693
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• 2011

In this paper, we consider Bayesian approaches to zero inflated Poisson model, one of the popular models to analyze zero inflated count data. To generate posterior samples, we deal with a Markov Chain Monte Carlo method using a Gibbs sampler and an exact sampling method using an Inverse Bayes Formula(IBF). Posterior sampling algorithms using two methods are compared, and a convergence checking for a Gibbs sampler is discussed, in particular using posterior samples from IBF sampling. Based on these sampling methods, a real data analysis is performed for Trajan data (Marin et al., 1993) and our results are compared with existing Trajan data analysis. We also discuss model selection issues for Trajan data between the Poisson model and zero inflated Poisson model using various criteria. In addition, we complement the previous work by Rodrigues (2003) via further data analysis using a hierarchical Bayesian model.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.20 no.4
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• pp.355-362
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• 2008

A reliability model of Level II AFDA is proposed to analyze the wave run-up occurring by the interaction of incident waves and sloped coastal structures. The reliability model may be satisfactorily calibrated by Level III Monte-Carlo simulation. Additionally, the partial safety factors of random variables related to wave run-up can be straightforwardly evaluated by the inverse-reliability method that use influence coefficients and uncertainties of random variables, and target probability of failure. In particular, a design equation for wave run-up is derived in the same form as that of deterministic design method so that the reliability-based design method of Level I may be applied easily. Finally, it is confirmed that results redesigned by the reliability-based design method of Level I with partial safety factors suggested in this paper are satisfactorily compared with results of CEM(2006) as well as those of Level II AFDA.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.191-196
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• 2004

This study proposed the analysis of mass position detection and modified stiffness due to the change of the mass and stiffness of structure by using the original and modified dynamic characteristics. The method is applied to examples of a cantilever and 3 degree of freedom by modifying the mass. The predicted detection of mass positions and magnitudes are in good agrement with these from the structural reanalysis using the modified mass.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1013-1016
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• 1995

This paper deals with dynamics and control of a PRP6-DOF parallel manipulator. Dynamic modeling includes the effect of inertia of all links in the mechanism to increase modeling accuracy. Kinematic analysis about forward and inverse kinematics is also explained. Using Lagrange-D' Alambert method we get equations of motions in a link space which fully represent 6DOF motions of the manipulator.

• Magazine of the Korean Society of Agricultural Engineers
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• v.40 no.1
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• pp.57-67
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• 1998

A stochastic weather generator which simulate daily precipitation, maximum and minimum daily temperature, relative humidity was developed. The model parameters were estimated using stochastic characteristics analysis of historical data of 71 weather stations. Spatial variations of the parameters for the country were also analyzed. Model parameters of ungauged Sites were determined from parameters of adjacent weather stations using inverse distance method. The model was verified on Suwon and Ulsan weather stations and showed good agreement between simulated and observed data.

• Journal of KSNVE
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• v.2 no.1
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• pp.61-66
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• 1992

In general, structures have various joints such as bonded joint, bolted joint, bearing joint and welded joint. Dynamic modelling of such joints has been the current topic of interest. In this study, the dynamic modelling of plate structures with bonded joint was investigated by using modal testing, sensitivity analysis and condensation-inverse condensation method of FEM. A proper modelling procedure was proposed and the validity was verified.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.3
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• pp.294-305
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• 2012

The objective of this study is to estimate the chemical compositions and to identify qualitative sources of fall-out particles in study area. Also, this study used a spatial analysis to estimate spatial distributions and average deposition flux. In this study, the chemical compositions of fall-out particle samples collected at Muncheon lake from May 2010 to January 2011 were analyzed by ICP and IC. The monthly trend of deposition fluxes for fall-out particles showed highest in June ($107.61kg/km^2/day$) and lowest in October ($22.22kg/km^2/day$). The average fluxes of Fe, Si, Al, Zn and Ba are 0.44, 0.24, 0.20, 0.17, $0.09kg/km^2/day$, respectively. Also, the average fluxes of $NO_3^-$, $SO_4^{2-}$, $NH_4^+$, $Ca^{2+}$, and $Na^+$ are 6.48, 5.01, 4.96, 1.75, $1.37kg/km^2/day$, respectively. A Factor analysis identified four sources such as 1) nonferrous metal, motor vehicle, and agriculture, 2) soil, 3) field burning, incineration, and 4) road dust and oil burning. The IDW (inverse distance weighting) spatial analysis method was used to estimate spatial distribution and average deposition flux for fall-out particles. A total average deposition fluxes estimated in Muncheon lake were 936.15 kg/month. The spatial distribution trend of deposition flux showed higher at site 1 and 2 than at site 3, 4 because local road is adjacent to the site 1 and 2.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2006.06a
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• pp.49-54
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• 2006

During most of manufacturing processes of auto-body panels, the trimming line should be designed in advance prior to flanging. It is an important task to find a feasible trimming line to obtain a precise final part shape after flanging. This paper proposes a new fast method to find feasible trimming line based on one-step analysis. The basic idea of the one-step analysis is to seek for the nodal positions in the initial blank from the final part, and then the distribution of strain, stress and thickness in the final configuration can be calculated by comparing the nodal position in the initial blank sheet with the one of the final part. The one-step analysis method is able to predict the trimming line before flanging since the desired product shape after flanging can be defined from the final configuration and most of strain paths are simple during the flanging process. Finally, designers can obtain a discrete trimming line from the boundary of the developed meshes after one-step analysis and import it into CAD system in the early design stage. The proposed method has been successfully applied to two basic curve flanging processes demonstrating many advantages.

• Journal of applied mathematics & informatics
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• v.32 no.1_2
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• pp.61-74
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• 2014

This paper describes an iterative method for orthogonal projections $AA^+$ and $A^+A$ of an arbitrary matrix A, where $A^+$ represents the Moore-Penrose inverse. Convergence analysis along with the first and second order error estimates of the method are investigated. Three numerical examples are worked out to show the efficacy of our work. The first example is on a full rank matrix, whereas the other two are on full rank and rank deficient randomly generated matrices. The results obtained by the method are compared with those obtained by another iterative method. The performance measures in terms of mean CPU time (MCT) and the error bounds for computing orthogonal projections are listed in tables. If $Z_k$, k = 0,1,2,... represents the k-th iterate obtained by our method then the sequence of the traces {trace($Z_k$)} is a monotonically increasing sequence converging to the rank of (A). Also, the sequence of traces {trace($I-Z_k$)} is a monotonically decreasing sequence converging to the nullity of $A^*$.

• Journal of applied mathematics & informatics
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• v.32 no.1_2
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• pp.171-184
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• 2014

A higher order iterative method to compute the Moore-Penrose inverses of arbitrary matrices using only the Penrose equation (ii) is developed by extending the iterative method described in [1]. Convergence properties as well as the error estimates of the method are studied. The efficacy of the method is demonstrated by working out four numerical examples, two involving a full rank matrix and an ill-conditioned Hilbert matrix, whereas, the other two involving randomly generated full rank and rank deficient matrices. The performance measures are the number of iterations and CPU time in seconds used by the method. It is observed that the number of iterations always decreases as expected and the CPU time first decreases gradually and then increases with the increase of the order of the method for all examples considered.