• Journal of the Korea Society for Simulation
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• v.21 no.3
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• pp.11-16
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• 2012

Simulation is the imitation of the operation of a real-world process or system over time. It concerns the study of the operating characteristics of real systems. Typically, a simulation project consists of several steps such as data collection, coding, model verification, model validation, experimental design, output data analysis, and implementation. Among these steps of a simulation study this paper focus on statistical analysis methods of simulation output data. Specially, we explain how to develop confidence interval estimators for mean ${\mu}$ in terminating and non-terminating simulation cases. We, then, explore the estimation techniques for $f({\mu})$, where the function $f({\bullet})$ is a nonlinear that is continuously differentiable in a neighborhood of ${\mu}$ with $f'({\mu}){\neq}0$.

• East Asian mathematical journal
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• v.25 no.2
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• pp.179-196
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• 2009

Let E be a uniformly convex Banach space and K a nonempty closed convex subset which is also a nonexpansive retract of E. For i = 1, 2, 3, let $T_i:K{\rightarrow}E$ be an asymptotically nonexpansive mappings with sequence ${\{k_n^{(i)}\}\subset[1,{\infty})$ such that $\sum_{n-1}^{\infty}(k_n^{(i)}-1)$ < ${\infty},\;k_{n}^{(i)}{\rightarrow}1$, as $n{\rightarrow}\infty$ and F(T)=$\bigcap_{i=3}^3F(T_i){\neq}{\phi}$ (the set of all common xed points of $T_i$, i = 1, 2, 3). Let {$a_n$},{$b_n$} and {$c_n$} are three real sequences in [0, 1] such that $\in{\leq}\;a_n,\;b_n,\;c_n\;{\leq}\;1-\in$ for $n{\in}N$ and some ${\in}{\geq}0$. Starting with arbitrary $x_1{\in}K$, define sequence {$x_n$} by setting {$$x_{n+1}=P((1-a_n)x_n+a_nT_1(PT_1)^{n-1}y_n)$$ $$y_n=P((1-b_n)x_n+a_nT_2(PT_2)^{n-1}z_n)$$ $$z_n=P((1-c_n)x_n+c_nT_3(PT_3)^{n-1}x_n)$$. Assume that one of the following conditions holds: (1) E satises the Opial property, (2) E has Frechet dierentiable norm, (3) $E^*$ has Kedec -Klee property, where $E^*$ is dual of E. Then sequence {$x_n$} converges weakly to some p${\in}$F(T).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4D
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• pp.387-393
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• 2010

This paper studies static crack growth of asphalt pavement using the extended finite element method (XFEM). To consider nonlinear characteristics of asphalt concrete, a viscoelastic constitutive equation using the Maxwell chain is used. And a linear cohesive crack model is used to regularize the crack. Instead of constructing the viscoelastic constitutive law from the Prony approximation of compliance and retardation time measured experimentally, we use a smooth log-power function which optimally fits experimental data and is infinitely differentiable. The partial moduli of the Maxwell chain from the log-power function make analysis easy because they change more smoothly in a more stable way than the ordinary method such as the least square method. Using the developed method, we can simulates the static crack growth test results satisfactorily.

• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.129-140
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• 2007

The planning procedure of a transit operation consists of design, operation, and evaluation according to the research characteristics. There are some review studies on the operation and evaluation procedure, but the research on the design procedure has not yet been organized systematically. In this study, the research on transit system design was reviewed and the model structure and its solution method were arranged. The decision variables of the design procedure are network structure, line spacing or position, stop spacing, dispatching headway, and fleet size. In the analytical research on design procedure, system total cost is generally used as the objective function. System total cost is comprised of user cost, which is the sum of user access, waiting, and travel cost, and operating cost. Total cost of the transit system, used as the objective function, has the unique minimum because it is differentiable. There is a certain decision variable that makes the derivative of the objective function equal to zero and the second derivative of the objective function is positive. Therefore the decision variable that makes the first derivative of the objective function zero is the optimum that minimizes the objective function, and each of the cost components of the objective function become the same. This study is expected to help understanding about the research on the design procedure of transit operation planning and to help be a catalyst for relevant research.

• Journal of Food Hygiene and Safety
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• v.29 no.2
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• pp.158-163
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• 2014

In this study, two commercial PCR and ELISA test kits were examined for identification of eight animal species (beef, pork, chicken, duck, turkey, goat, lamb, and horse) from raw meat and meat products in Korea. The detection limit in RAW meat ELISA kit$^{(R)}$ on three types of meat samples blended with beef, pork and chicken, demonstrated that all meat species were differentiable down to 0.2%. RAW meat ELISA kit$^{(R)}$ on animal species resulted in differentiation rate of 94.5% for beef, 93.3% for pork, 90% for lamb, and 100% for chicken, duck, turkey, goat, and horse. In contrast, Powercheck Animal Species ID PCR kit$^{TM}$ resulted in 100% specificity at 0.05% limit of detection for all meat species. The detection limit of Cooked Meat ELISA kit$^{(R)}$ on mixed meat samples heat-treated with different temperatures and times, resulted in 0.1% for all heat-treated mixed meat except for chicken at 1.0%. Additionally, ELISA kit on sixty meat products resulted in specificity of 31.8% for ham, 13.6% for sausages, and 12.5% for ground processed products, and relatively low rate for more than 2 types of mixed meats. On the contrary, meat species differentiation using PCR kit showed higher percentage than that using ELISA kit$^{(R)}$: 50.0% for ham, 41.7% for sausages, and 28.6% for ground processed meat. Futhermore, PCR kit on 54 dried beef meats detected pork genes in 13 products whereas ELISA kit showed negative results for all products. Hence, the possibility of cross-contamination during manufacturing process was investigated, and it was found that identical tumblers, straining trays, cutters and dryers were used in both beef and pork jerky production line, suggesting the inclusion of pork genes in beef products due to cross-contamination. In this study, PCR and ELISA test kits were found to be excellent methods for meat species differentiation in raw meat and heat-processed mixed meat. However, lower differentiation rate demonstrated in case of meat processed products raised the possibility of inclusion of other species due to cross-contamination during manufacturing process.