Browsing by Subject "Monte Carlo Method"

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Open Access
Influence of phase function on modeled optical response of nanoparticle-labeled epithelial tissues
(2011) Cihan, C.; Arifler, D.
Metal nanoparticles can be functionalized with biomolecules to selectively localize in precancerous tissues and can act as optical contrast enhancers for reflectance-based diagnosis of epithelial precancer. We carry out Monte Carlo (MC) simulations to analyze photon propagation through nanoparticle-labeled tissues and to reveal the importance of using a proper form of phase function for modeling purposes. We first employ modified phase functions generated with a weighting scheme that accounts for the relative scattering strengths of unlabeled tissue and nanoparticles. To present a comparative analysis, we repeat ourMCsimulations with simplified functions that only approximate the angular scattering properties of labeled tissues. The results obtained for common optical sensor geometries and biologically relevant labeling schemes indicate that the exact form of the phase function used as model input plays an important role in determining the reflectance response and approximating functions often prove inadequate in predicting the extent of contrast enhancement due to labeling. Detected reflectance intensities computed with different phase functions can differ up to ̃60% and such a significant deviation may even alter the perceived contrast profile. These results need to be taken into account when developing photon propagation models to assess the diagnostic potential of nanoparticle-enhanced optical measurements. © 2011 Society of Photo-Optical Instrumentation Engineers (SPIE).
Open Access
On Gambler's ruin problem in some models
(2005) Sevim, Çiğdem
2-player probability games is an important subject of probability theory. In this thesis, we considered four different two-player probability games. We calculated the expected value of stopping times of the games. Since the rules of the games are complicated and it is not possible to calculate all possible shuffles, we calculated the results using the Monte Carlo method on a computer. We showed that the expected value of duration of the games are of the order square of number of cards as we expected.