In external electron beam therapy arbitrarily shaped inserts (cutouts) are used to define the contours of the irradiated field. This thesis describes the implementation and verification of a software system to calculate output factors for cutouts using Monte Carlo simulations. The design goals were: (1) A stand-alone software system running on a single workstation. (2) Task oriented graphical user interface with shape input capability. (3) Implementation on Mac OS XRTM (10A.x Tiger). (4) CPU multicore support by job splitting. (5) EGSnrc (Patch level V4-r2-2-5) for particle transport and dose scoring. (6) Validation for clinical use. / The system, called Cutout Manager, can calculate output factors with 1% statistical error in 20 minutes on Mac Pro computer (Intel XeonRTM, 4 cores). When the BEAMnrc linac model correctly reproduces percentage depth doses in the buildup region and around R100, calculated and measured output factors are in good agreement with precision measurements of circular cutouts at 100 cm source-to-surface distance (SSD) and extended SSD. Cutout Manager simulations are consistent with measurements of clinical cutouts within a 2% error margin.

No abstract available.

Dissertation submitted in partial compliance with the requirements of the Masters Degree in Technology: Chemistry, in the Faculty of Applied Sciences at the Durban University of Technology, 2008. / In this work, a holistic approach to validate analytical methods was assessed by virtue of Monte Carlo simulations. This approach involves a statement of the methodsâ s scope (i.e. analytes, matrices and concentration levels) and requisites (internal or external); selection of the methodâ s (fit-for-purpose) features; pre-validation and validation of the intermediate accuracy and its assessment by means of Monte Carlo simulations. Validation of the other methodâ s features and a validity statement in terms of a â fit-for-purposeâ decision making, harmonized validation-control-uncertainty statistics and short-term routine work with the aim of proposing virtually â ready-to-useâ methods. The protocol could be transferred to other methods. The main aim is to harmonize the work to be done by research teams and routine laboratories assuming that different aims, strategies and practical viewpoints exist. As a result, the recommended protocol should be seen as a starting point. It is necessary to propose definitive (harmonized) protocols that must be established by international normalisation/accreditation entities. The Quality Assurance (Method verification and Internal Quality Control, IQC) limits, as well as sample uncertainty were estimated consistently with the validated accuracy statistics i.e. E U (E) and RSDi + U (RSDi). Two case studies were used to assess Monte Carlo simulation as a tool for method validation in analytical laboratories, the first involves an indirect polarographic method for determining nitrate in waste water and the second involves a direct determination of heavy metals in sea water by differential pulse anodic stripping voltammetry, as an example of the application of the protocol. In this sense the uncertainty obtained could be used for decision making purposes as it is very tempting to use uncertainty as a commercial argument and in this work it has been shown that the smaller the uncertainty, the better the measurement of the instrument or the laboratoryâ s reputation.

Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2012.

To evaluate the expectation of a simple function with respect to a complicated multivariate density Monte Carlo integration has become the main technique. Gibbs sampling and importance sampling are the most popular methods for this task. In this contribution we propose a new simple general purpose importance sampling procedure. In a simulation study we compare the performance of this method with the performance of Gibbs sampling and of importance sampling using a vector of independent variates. It turns out that the new procedure is much better than independent importance sampling; up to dimension five it is also better than Gibbs sampling. The simulation results indicate that for higher dimensions Gibbs sampling is superior. (author's abstract) / Series: Preprint Series / Department of Applied Statistics and Data Processing

The importance of monitoring, and where possible reducing, the level of radiation dose from diagnostic X-ray examinations has been recognised for many years and is becoming of increasing concern. Dose reduction is of particular concern in paediatric radiology, and there are specific problems associated with the monitoring and comparison of radiation doses to children. Any optimisation study relies on a framework of good dosimetry. Two techniques have been developed to improve the collection of patient dose data: the automation of survey techniques to increase the quantity of data collected; and a method of correcting for patient size which reduces one source of variability in the data. An optimisation strategy has been developed, consisting of theoretical simulations, experimental verification and clinical implementation. Monte Carlo techniques were used for the theoretical study, which investigated the effect of beam filtration on radiation dose and image quality for a wide range of parameters, specifically for a neonatal size phantom. Simulations included both radiography of bone in soft tissue and fluoroscopy of iodine and barium based contrast media. The results were assessed in terms of the beam spectra and the absorption and transmission characteristics of the phantom and image receptor. Experimental measurements of dose and contrast were made for a simple slab phantom corresponding to that simulated, and results showed good agreement with those predicted. A further set of experimental measurements were carried out using anthropomorphic phantoms in a clinical setting, which demonstrated how the theoretical predictions translated to clinical practice. A clinical trial of the use of a 0.1mm copper filter for fluoroscopic examinations of infants was performed, and the filter shown to give substantial dose reduction with no significant loss in image quality. Some general recommendations on dose quantities and the application of optimisation strategies to paediatric radiology have been made.

No description available.

In this study, the application of a Monte Carlo method (MCM) for radiative heat transfer in three-dimensional rectangular enclosures was investigated. The study covers the development of the method from simple surface exchange problems to enclosure problems containing absorbing, emitting and isotropically/anisotropically scattering medium. The accuracy of the MCM was first evaluated by applying the method to cubical enclosure problems. The first one of the cubical enclosure problems was prediction of radiative heat flux vector in a cubical enclosure containing purely, isotropically and anisotropically scattering medium with non-symmetric boundary conditions. Then, the prediction of radiative heat flux vector in an enclosure containing absorbing, emitting, isotropically and anisotropically scattering medium with symmetric boundary conditions was evaluated. The predicted solutions were compared with the solutions of method of lines solution (MOL) of discrete ordinates method (DOM). The method was then applied to predict the incident heat fluxes on the freeboard walls of a bubbling fluidized bed combustor, and the solutions were compared with those of MOL of DOM and experimental measurements. Comparisons show that MCM provides accurate and computationally efficient solutions for modelling of radiative heat transfer in 3-D rectangular enclosures containing absorbing, emitting and scattering media with isotropic and anisotropic scattering properties.

Numerical methods form an important part of the pricing of financial derivatives and especially in cases where there is no closed form analytical formula. We begin our work with an introduction of the mathematical tools needed in the pricing of financial derivatives. Then, we discuss the assumption of the log-normal returns on stock prices and the stochastic differential equations. These lay the foundation for the derivation of the Black Scholes differential equation, and various Black Scholes formulas are thus obtained. Then, the model is modified to cater for dividend paying stock and for the pricing of options on futures. Multi-period binomial model is very flexible even for the valuation of options that do not have a closed form analytical formula. We consider the pricing of vanilla options both on non dividend and dividend paying stocks. Then show that the model converges to the Black-Scholes value as we increase the number of steps. We discuss the Finite difference methods quite extensively with a focus on the Implicit and Crank-Nicolson methods, and apply these numerical techniques to the pricing of vanilla options. Finally, we compare the convergence of the multi-period binomial model, the Implicit and Crank Nicolson methods to the analytical Black Scholes price of the option. We conclude with the pricing of exotic options with special emphasis on path dependent options. Monte Carlo simulation technique is applied as this method is very versatile in cases where there is no closed form analytical formula. The method is slow and time consuming but very flexible even for multi dimensional problems.

No abstract available.